diff --git a/HelperFunction.R b/HelperFunction.R
index 73d4448..c59dd2e 100644
--- a/HelperFunction.R
+++ b/HelperFunction.R
@@ -1,6 +1,6 @@
 gam.variables <- function(data){
   sapply(1:ncol(data), function(i){
-    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste("s", "(",names(data)[i], ")", sep="")}
+    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste("s", "(",names(data)[i], ", k=5)", sep="")}
     else{names(data[i]) }
   })
 }
@@ -221,6 +221,8 @@ pboot <- function(data, X_sim, sim.size, seed){
   
   X_R0 <- X_sim[which(data$R==0), ]
   t_R0 <- data$t[which(data$R==0)]
+  X_R1 <- X_sim[which(data$R==1), ]
+  t_R1 <- data$t[which(data$R==1)]
   
   X_with_t_R0 <- X_with_t[which(data$R==0), ]
   X_with_t_R1 <- X_with_t[which(data$R==1), ]
@@ -229,6 +231,7 @@ pboot <- function(data, X_sim, sim.size, seed){
   
   g.fit <- mgcv::gam(as.formula(paste("data$R ~", gam.var)), data=X_sim, family=binomial) 
   t_R0.fit <- mgcv::gam(as.formula(paste("t_R0 ~", gam.var)), data=X_R0, family=binomial) ## treatment model
+  t_R1.fit <- mgcv::gam(as.formula(paste("t_R1 ~", gam.var)), data=X_R1, family=binomial) ## treatment model
   M_R0.fit <- mgcv::gam(as.formula(paste("M_R0 ~", gam.var.M)), data=X_with_t_R0, family=binomial) ## missing data model
   M_R1.fit <- mgcv::gam(as.formula(paste("M_R1 ~", gam.var.M)), data=X_with_t_R1, family=binomial) ## missing data model
   
@@ -379,29 +382,259 @@ pboot <- function(data, X_sim, sim.size, seed){
   data.new <- data.frame(cbind(Y.new, M.new, R.new, T.new, X.new))
   colnames(data.new) <- c("Y", "M", "R", "t", colnames(X.new))  
   
+  coef_g.fit <- coef(g.fit)
+  coef_t_R0.fit <- coef(t_R0.fit)
+  coef_t_R1.fit <- coef(t_R1.fit)
+  coef_M_R0.fit <- coef(M_R0.fit)
+  coef_M_R1.fit <- coef(M_R1.fit)
+  
+  return(list(data.new=data.new, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, 
+              coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit))
+  
+}
+
+## 1st step of parametric bootstrap: model fitting using original data
+pboot_model <- function(data, X_sim){
+  
+  ## fit models
+  X_with_t <- cbind(as.factor(data$t), X_sim)
+  colnames(X_with_t)[1] <- "treatment"
+  gam.var <- paste(gam.variables(X_sim), collapse = "+") ## gam variables for treatment assignment model
+  gam.var.M <- paste(gam.variables(X_with_t), collapse = "+") ## gam variables for missing data model
+  index.var.Y <- paste(single.index.variables(X_sim), collapse = "+")
+  X_adjust <- model.matrix(as.formula(paste("~", index.var.Y)), data = X_sim)[,-1]
+  X_adjust_scale <- scale(X_adjust)
+  
+  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]
+  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]
+  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]
+  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]
+  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]
+  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]
+  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]
+  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]
+  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]
+  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]
+  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]
+  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]
+  
+  X_R0 <- X_sim[which(data$R==0), ]
+  t_R0 <- data$t[which(data$R==0)]
+  X_R1 <- X_sim[which(data$R==1), ]
+  t_R1 <- data$t[which(data$R==1)]
+  
+  X_with_t_R0 <- X_with_t[which(data$R==0), ]
+  X_with_t_R1 <- X_with_t[which(data$R==1), ]
+  M_R0 <- data$M[which(data$R==0)]
+  M_R1 <- data$M[which(data$R==1)]
+  
+  g.fit <- mgcv::gam(as.formula(paste("data$R ~", gam.var)), data=X_sim, family=binomial) 
+  t_R0.fit <- mgcv::gam(as.formula(paste("t_R0 ~", gam.var)), data=X_R0, family=binomial) ## treatment model
+  t_R1.fit <- mgcv::gam(as.formula(paste("t_R1 ~", gam.var)), data=X_R1, family=binomial) ## treatment model
+  M_R0.fit <- mgcv::gam(as.formula(paste("M_R0 ~", gam.var.M)), data=X_with_t_R0, family=binomial) ## missing data model
+  M_R1.fit <- mgcv::gam(as.formula(paste("M_R1 ~", gam.var.M)), data=X_with_t_R1, family=binomial) ## missing data model
+  
+  fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],
+                                                              Y = Y_t_R1[which(M_t_R1==1)],
+                                                              ids=1:length(Y_t_R1[which(M_t_R1==1)]), 
+                                                              kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                              use_mave=TRUE), silent = TRUE)
+  if (inherits(fit_t_R1_h, "try-error")) {
+    fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],
+                                                                Y = Y_t_R1[which(M_t_R1==1)],
+                                                                ids=1:length(Y_t_R1[which(M_t_R1==1)]), 
+                                                                kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                                use_mave=FALSE), silent = TRUE)
+  }
+  
+  fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],
+                                                              Y = Y_t_R0[which(M_t_R0==1)],
+                                                              ids=1:length(Y_t_R0[which(M_t_R0==1)]), 
+                                                              kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                              use_mave=TRUE), silent = TRUE)
+  if (inherits(fit_t_R0_h, "try-error")) {
+    fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],
+                                                                Y = Y_t_R0[which(M_t_R0==1)],
+                                                                ids=1:length(Y_t_R0[which(M_t_R0==1)]), 
+                                                                kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                                use_mave=FALSE), silent = TRUE)
+  }
+  
+  fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],
+                                                               Y = Y_t0_R1[which(M_t0_R1==1)],
+                                                               ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), 
+                                                               kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                               use_mave=TRUE), silent = TRUE)
+  if (inherits(fit_t0_R1_h, "try-error")) {
+    fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],
+                                                                 Y = Y_t0_R1[which(M_t0_R1==1)],
+                                                                 ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), 
+                                                                 kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                                 use_mave=FALSE), silent = TRUE)
+  }
+  
+  fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],
+                                                               Y = Y_t0_R0[which(M_t0_R0==1)],
+                                                               ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), 
+                                                               kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                               use_mave=TRUE), silent = TRUE)
+  if (inherits(fit_t0_R0_h, "try-error")) {
+    fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],
+                                                                 Y = Y_t0_R0[which(M_t0_R0==1)],
+                                                                 ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), 
+                                                                 kernel="dnorm", bw.selection="ise", bw.method="optim", 
+                                                                 use_mave=FALSE), silent = TRUE)
+  }
+  
+  return(list(fit_t_R0_h=fit_t_R0_h, fit_t_R1_h=fit_t_R1_h, fit_t0_R0_h=fit_t0_R0_h, 
+              fit_t0_R1_h=fit_t0_R1_h, g.fit=g.fit, t_R0.fit=t_R0.fit, t_R1.fit=t_R1.fit, 
+              M_R0.fit=M_R0.fit, M_R1.fit=M_R1.fit))
+  
+}
+
+## 2nd step of parametric bootstrap: simulate new data
+pboot_sim <- function(data, X_sim, sim.size, seed, 
+                      fit_t_R0_h, fit_t_R1_h, fit_t0_R0_h, 
+                      fit_t0_R1_h, g.fit, t_R0.fit, M_R0.fit, M_R1.fit){
+  
+  ## fit models
+  index.var.Y <- paste(single.index.variables(X_sim), collapse = "+")
+  X_adjust <- model.matrix(as.formula(paste("~", index.var.Y)), data = X_sim)[,-1]
+  X_adjust_scale <- scale(X_adjust)
+  
+  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]
+  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]
+  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]
+  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]
+  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]
+  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]
+  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]
+  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]
+  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]
+  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]
+  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]
+  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]
+
+  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)
+  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)
+  X_t0_R0_beta_t0_R0 <- as.vector(X_adjust_scale_t0_R0[which(M_t0_R0==1), ] %*% fit_t0_R0_h$coef)
+  X_t0_R1_beta_t0_R1 <- as.vector(X_adjust_scale_t0_R1[which(M_t0_R1==1), ] %*% fit_t0_R1_h$coef)
+  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    
+  ny_t_R0 = length(y_t_R0) 
+  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    
+  ny_t_R1 = length(y_t_R1) 
+  y_t0_R0 = sort(unique(Y_t0_R0[which(M_t0_R0==1)]))    
+  ny_t0_R0 = length(y_t0_R0) 
+  y_t0_R1 = sort(unique(Y_t0_R1[which(M_t0_R1==1)]))    
+  ny_t0_R1 = length(y_t0_R1) 
+  
+  ## simulate data
+  if(!is.null(seed)){set.seed(seed)}
+  boot.indices <- sample(1:sim.size, size=sim.size, replace = T)
+  X.new <- X_sim[boot.indices,]
+  X_adjust_scale.new <- X_adjust_scale[boot.indices, ]
+  ## new R
+  prob.R <- predict(g.fit, newdata=X.new, type="response") 
+  R.new <- rbinom(n=sim.size, size=1, prob=prob.R)
+  ## new T
+  T.new_R1 <- rbinom(n=sim.size,size=1,prob=0.5)
+  prob.T_R0 <- predict(t_R0.fit, newdata=X.new, type="response")
+  T.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.T_R0)
+  T.new <- T.new_R1*R.new+T.new_R0*(1-R.new)
+  
+  ## new Y
+  X.new_beta_t_R0 <- as.vector(X_adjust_scale.new %*% fit_t_R0_h$coef)
+  X.new_beta_t_R1 <- as.vector(X_adjust_scale.new %*% fit_t_R1_h$coef)
+  X.new_beta_t0_R0 <- as.vector(X_adjust_scale.new %*% fit_t0_R0_h$coef)
+  X.new_beta_t0_R1 <- as.vector(X_adjust_scale.new %*% fit_t0_R1_h$coef)
+  
+  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], 
+                     xb=X.new_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, 
+                     kernel = "dnorm")
+  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], 
+                     xb=X.new_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, 
+                     kernel = "dnorm")
+  F_X_t0_R0 <- NW_new(Xb=X_t0_R0_beta_t0_R0, Y=Y_t0_R0[which(M_t0_R0==1)], 
+                      xb=X.new_beta_t0_R0, y=y_t0_R0, h=fit_t0_R0_h$bandwidth, 
+                      kernel = "dnorm")
+  F_X_t0_R1 <- NW_new(Xb=X_t0_R1_beta_t0_R1, Y=Y_t0_R1[which(M_t0_R1==1)], 
+                      xb=X.new_beta_t0_R1, y=y_t0_R1, h=fit_t0_R1_h$bandwidth, 
+                      kernel = "dnorm")
+  
+  i1 = which(apply(F_X_t_R0==0,1,prod)==1)
+  i1.closest <- apply(abs(outer(X.new_beta_t_R0[i1], X.new_beta_t_R0[-i1], FUN = "-")), 1, which.min)
+  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]
+  
+  i1 = which(apply(F_X_t_R1==0,1,prod)==1)
+  i1.closest <- apply(abs(outer(X.new_beta_t_R1[i1], X.new_beta_t_R1[-i1], FUN = "-")), 1, which.min)
+  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]
+  
+  i1 = which(apply(F_X_t0_R0==0,1,prod)==1)
+  i1.closest <- apply(abs(outer(X.new_beta_t0_R0[i1], X.new_beta_t0_R0[-i1], FUN = "-")), 1, which.min)
+  F_X_t0_R0[i1, ] <- F_X_t0_R0[-i1, ][i1.closest, ]
+  
+  i1 = which(apply(F_X_t0_R1==0,1,prod)==1)
+  i1.closest <- apply(abs(outer(X.new_beta_t0_R1[i1], X.new_beta_t0_R1[-i1], FUN = "-")), 1, which.min)
+  F_X_t0_R1[i1, ] <- F_X_t0_R1[-i1, ][i1.closest, ]
+  
+  Y.new_t_R0 <- apply(F_X_t_R0, 1, function(x){
+    ecdf <- runif(1,0,1)
+    y_t_R0[min(which(ecdf<=x))]
+  })
+  Y.new_t_R1 <- apply(F_X_t_R1, 1, function(x){
+    ecdf <- runif(1,0,1)
+    y_t_R1[min(which(ecdf<=x))]
+  })
+  Y.new_t0_R0 <- apply(F_X_t0_R0, 1, function(x){
+    ecdf <- runif(1,0,1)
+    y_t0_R0[min(which(ecdf<=x))]
+  })
+  Y.new_t0_R1 <- apply(F_X_t0_R1, 1, function(x){
+    ecdf <- runif(1,0,1)
+    y_t0_R1[min(which(ecdf<=x))]
+  })
+  Y.new <- Y.new_t_R0*T.new*(1-R.new)+Y.new_t_R1*T.new*R.new+
+    Y.new_t0_R0*(1-T.new)*(1-R.new)+Y.new_t0_R1*(1-T.new)*R.new
+  
+  ## new M
+  X_with_t.new <- cbind(T.new, X.new)
+  colnames(X_with_t.new)[1] <- "treatment"
+  prob.M_R0 <- predict(M_R0.fit, newdata=X_with_t.new, type="response")
+  prob.M_R1 <- predict(M_R1.fit, newdata=X_with_t.new, type="response")
+  M.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.M_R0)
+  M.new_R1 <- rbinom(n=sim.size,size=1,prob=prob.M_R1)
+  M.new <- M.new_R0*(1-R.new)+M.new_R1*R.new
+  
+  Y.new[M.new==0] <- NA
+  
+  data.new <- data.frame(cbind(Y.new, M.new, R.new, T.new, X.new))
+  colnames(data.new) <- c("Y", "M", "R", "t", colnames(X.new))  
+  
   return(data.new)
   
 }
 
+
 ## run algorithm
-fit_one <- function(data, X, trt_val) {
+fit_one <- function(data, X, trt_val, coef_g.fit=NULL, coef_t_R0.fit=NULL, 
+                    coef_t_R1.fit=NULL, coef_M_R0.fit=NULL, coef_M_R1.fit=NULL) {
   # try mave first
-  out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, 
-                     X=X,
+  out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, X=X,
                      t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,
                      IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel="dnorm",
                      method="optim", single_index_method="norm1coef",
-                     use_mave=TRUE, seed=NULL),
+                     use_mave=TRUE, seed=NULL, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, 
+                     coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit),
              silent = TRUE)
   
   if (inherits(out, "try-error")) {
     # fallback cumSIR
-    out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, 
-                       X=X,
+    out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, X=X,
                        t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,
                        IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel="dnorm",
                        method="optim", single_index_method="norm1coef",
-                       use_mave=FALSE, seed=NULL),
+                       use_mave=FALSE, seed=NULL, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, 
+                       coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit),
                silent = TRUE)
   }
   
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..4ca5063
--- /dev/null
+++ b/README.md
@@ -0,0 +1,3 @@
+## Comprehensive Cohort Project
+
+This is an example of a commit
diff --git a/SIDR_Ravinew.R b/SIDR_Ravinew.R
new file mode 100644
index 0000000..b71b5b2
--- /dev/null
+++ b/SIDR_Ravinew.R
@@ -0,0 +1,303 @@
+SIDR_Ravinew <- function(X, Y,
+                         Y.CP = NULL,
+                         initial = NULL,
+                         kernel = "dnorm",
+                         method = "optim",
+                         optim_method = "BFGS",
+                         abs.tol = 1e-4,
+                         bandwidth = NULL,
+                         wi.boot = NULL,
+                         index_ID)
+{
+    X <- as.matrix(X)
+    Y <- as.matrix(Y)
+
+    number_n <- dim(X)[1]
+    number_p <- dim(X)[2]
+
+    if (is.null(initial))
+    {
+        initial <- c(1, rep(0, number_p-1))
+    }else
+    {
+        initial <- as.vector(initial)
+        if(initial[1] != 0)
+            initial <- initial/initial[1]
+    }
+
+    if (is.null(bandwidth))
+    {
+        if (kernel=="K2_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- exp(parameter[number_p])
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)  # Ravi
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+
+                        # remove all obs of ith obs's patient
+                        index_remove <- which(index_ID == index_ID[i])
+                        Kih[index_remove] <- 0
+
+                        #Kih[i] <- 0                       # the fix
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+            }else
+            {
+                stop("There's no weighted version of the K2_Biweight kernel.")
+            }
+        }else if (kernel == "dnorm")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) dnorm(x/h, 0, 1)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- exp(parameter[number_p])
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+
+                        # remove all obs of ith obs's patient
+                        index_remove <- which(index_ID == index_ID[i])
+                        Kih[index_remove] <- 0
+
+                        # Kih[i] <- 0       # the fix
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+            }else
+            {
+                stop("There's no weighted version of the dnorm kernel.")
+            }
+        # }else if (kernel=="K4_Biweight")
+        # {
+        #     if (is.null(wi.boot))
+        #     {
+        #         Eij3 <- function(parameter){
+        #             K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h)
+        #
+        #             b <- c(1, parameter[1:(number_p-1)])
+        #             h <- exp(parameter[number_p])
+        #
+        #             x <- c(X%*%b)
+        #             y <- Y
+        #
+        #             n <- length(y)
+        #             yo <- order(y)
+        #             ys <- y[yo]
+        #             uy <- rle(ys)[[1]]
+        #             cols <- cumsum(uy)
+        #             ei <- rep(0, n)
+        #             for (i in 1:n){
+        #                 Kih <- K(x-x[i],h=h)
+        #
+        #                 # remove all obs of ith obs's patient
+        #                 index_remove <- which(index_ID == index_ID[i])
+        #                 Kih[index_remove] <- 0
+        #
+        #                 # Kih[i] <- 0                       # the fix
+        #                 denom <- sum(Kih)
+        #                 ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+        #             }
+        #             return(sum(ei)/n^2)
+        #         }
+        #     }else
+        #     {
+        #         stop("There's no weighted version of the K4_Biweight kernel.")
+        #     }
+        } else
+            rlang::abort("The kernel is not supported.")
+
+        if(method == "nlminb")
+        {
+            esti <- nlminb(start = c(initial[-1], 0),
+                           objective = Eij3,
+                           control = list(abs.tol = abs.tol))
+        }else if (method == "optim")
+        {
+            # the new optimize function using optim, you can change the lower and upper
+            esti <- optim(par = c(initial[-1], 0),
+                          fn = Eij3,
+                          method = optim_method,
+                          control = list(abstol = abs.tol))
+        }else if (method == "nmk")
+        {
+            assertthat::assert_that(requireNamespace("dfoptim", quietly = TRUE))
+            esti <- dfoptim::nmk(par = c(initial[-1], 0),
+                        fn = Eij3,
+                        control = list(tol = abs.tol))
+        }
+
+        results <- list(coef = c(1, esti$par[1:(number_p-1)]),
+                        bandwidth = exp(esti$par[number_p]),
+                        details = esti)
+    }else
+    {
+        if (kernel=="K2_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- bandwidth
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)  # Ravi
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+
+                        # remove all obs of ith obs's patient
+                        index_remove <- which(index_ID == index_ID[i])
+                        Kih[index_remove] <- 0
+
+                        # Kih[i] <- 0                       # the fix
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+
+            }else
+            {
+                stop("There's no weighted version of the K2_Biweight kernel.")
+            }
+        }else if (kernel=="dnorm")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) dnorm(x/h,0,1)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- bandwidth
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)  # Ravi
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+
+                        # remove all obs of ith obs's patient
+                        index_remove <- which(index_ID == index_ID[i])
+                        Kih[index_remove] <- 0
+
+                        # Kih[i] <- 0                       # the fix
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+            }else
+            {
+                stop("There's no weighted version of the dnorm kernel.")
+            }
+        # }else if (kernel=="K4_Biweight")
+        # {
+        #     if (is.null(wi.boot))
+        #     {
+        #         Eij3 <- function(parameter){
+        #             K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h)
+        #
+        #             b <- c(1, parameter[1:(number_p-1)])
+        #             h <- bandwidth
+        #
+        #             x <- c(X%*%b)
+        #             y <- Y
+        #
+        #             n <- length(y)
+        #             yo <- order(y)
+        #             ys <- y[yo]
+        #             uy <- rle(ys)[[1]]
+        #             cols <- cumsum(uy)  # Ravi
+        #             ei <- rep(0, n)
+        #             for (i in 1:n){
+        #                 Kih <- K(x-x[i],h=h)
+        #
+        #                 # remove all obs of ith obs's patient
+        #                 index_remove <- which(index_ID == index_ID[i])
+        #                 Kih[index_remove] <- 0
+        #
+        #                 # Kih[i] <- 0                       # the fix
+        #                 denom <- sum(Kih)
+        #                 ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+        #             }
+        #             return(sum(ei)/n^2)
+        #         }
+        #     }else
+        #     {
+        #         stop("There's no weighted version of the K4_Biweight kernel.")
+        #     }
+        } else
+            rlang::abort("The kernel is not supported.")
+
+        if(method == "nlminb")
+        {
+            esti <- nlminb(start = initial[-1],
+                           objective = Eij3,
+                           control = list(abs.tol = abs.tol))
+        }else if (method == "optim")
+        {
+            # the new optimize function using optim, you can change the lower and upper
+            esti <- optim(par = initial[-1],
+                          fn = Eij3,
+                          method = optim_method,
+                          control = list(abstol = abs.tol))
+        }else if (method == "nmk")
+        {
+            assertthat::assert_that(requireNamespace("dfoptim", quietly = TRUE))
+            esti <- dfoptim::nmk(par = initial[-1],
+                        fn = Eij3,
+                        control = list(tol = abs.tol))
+        }
+        results <- list(coef = c(1, esti$par[1:(number_p-1)]),
+                        bandwidth = bandwidth,
+                        details = esti)
+    }
+
+    return(results)
+}
diff --git a/SIDRnew.R b/SIDRnew.R
new file mode 100644
index 0000000..b01d143
--- /dev/null
+++ b/SIDRnew.R
@@ -0,0 +1,405 @@
+##### This function defined by MingYueh
+SIDRnew <- function(X, Y,
+                    Y.CP = NULL,
+                    initial = NULL,
+                    kernel = "K2_Biweight",
+                    method = c("optim", "nlminb", "nmk"),
+                    optim_method = "BFGS",
+                    abs.tol = 1e-4,
+                    bandwidth = NULL,
+                    wi.boot = NULL)
+{
+    X <- as.matrix(X)
+    Y <- as.matrix(Y)
+
+    method <- match.arg(method)
+
+    number_n <- dim(X)[1]
+    number_p <- dim(X)[2]
+
+    if (is.null(initial))
+    {
+        initial <- c(1, rep(0, number_p-1))
+    }else
+    {
+        initial <- as.vector(initial)
+        initial <- initial/initial[1]
+    }
+
+    if (is.null(bandwidth))
+    {
+        if (kernel=="K2_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h) * (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- exp(parameter[number_p])
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+                # cv.bh <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   h <- exp(parameter[number_p])
+                #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,
+                #                                  h = h))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                stop("There's no weighted version of the K2_Biweight kernel.")
+            }
+        }else if (kernel == "dnorm")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) dnorm(x/h, 0, 1)* (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- exp(parameter[number_p])
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+                # cv.bh <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   h <- exp(parameter[number_p])
+                #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,
+                #                                    h = h))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                # wi.boot <- as.vector(wi.boot)
+                # cv.bh <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   h <- exp(parameter[number_p])
+                #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,
+                #                                    h = h, w = wi.boot))^2)
+                #   return(cv)
+                # }
+                stop("There's no weighted version of the dnorm kernel.")
+            }
+        }else if (kernel=="K4_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) * (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- exp(parameter[number_p])
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+                # cv.bh <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   h <- exp(parameter[number_p])
+                #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,
+                #                                            h = h), 0), 1))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                stop("There's no weighted version of the K4_Biweight kernel.")
+            }
+        }
+
+        if(method == "nlminb")
+        {
+            esti <- nlminb(start = c(initial[-1], 0),
+                           objective = Eij3,
+                           control = list(abs.tol = abs.tol))
+        }else if (method == "optim")
+        {
+            # the new optimize function using optim, you can change the lower and upper
+            esti <- optim(par = c(initial[-1], 0),
+                          fn = Eij3,
+                          method = optim_method,
+                          control = list(abstol = abs.tol))
+        }else if (method == "nmk")
+        {
+            assertthat::assert_that(requireNamespace("dfoptim", quietly = TRUE))
+            esti <- dfoptim::nmk(par = c(initial[-1], 0),
+                                 fn = Eij3,
+                                 control = list(tol = abs.tol))
+        }
+
+        results <- list(coef = c(1, esti$par[1:(number_p-1)]),
+                        bandwidth = exp(esti$par[number_p]),
+                        details = esti)
+    }else
+    {
+        if (kernel=="K2_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h) * (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- bandwidth
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+
+                # cv.b <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,
+                #                                  h = bandwidth))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                stop("There's no weighted version of the K2_Biweight kernel.")
+            }
+        }else if (kernel=="dnorm")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) dnorm(x/h,0,1) * (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- bandwidth
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+
+                # cv.b <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,
+                #                                    h = bandwidth))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                # wi.boot <- as.vector(wi.boot)
+                # cv.b <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,
+                #                                    h = bandwidth, w = wi.boot))^2)
+                #   return(cv)
+                # }
+                stop("There's no weighted version of the dnorm kernel.")
+            }
+        }else if (kernel=="K4_Biweight")
+        {
+            if (is.null(wi.boot))
+            {
+                Eij3 <- function(parameter){
+                    K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) * (x!=0)
+
+                    b <- c(1, parameter[1:(number_p-1)])
+                    h <- bandwidth
+
+                    x <- c(X%*%b)
+                    y <- Y
+
+                    n <- length(y)
+                    yo <- order(y)
+                    ys <- y[yo]
+                    uy <- rle(ys)[[1]]
+                    cols <- cumsum(uy)
+                    ei <- rep(0, n)
+                    for (i in 1:n){
+                        Kih <- K(x-x[i],h=h)
+                        denom <- sum(Kih)
+                        ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+                    }
+                    return(sum(ei)/n^2)
+                }
+                # cv.b <- function(parameter)
+                # {
+                #   b <- c(1, parameter[1:(number_p-1)])
+                #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,
+                #                                            h = bandwidth), 0), 1))^2)
+                #   return(cv)
+                # }
+            }else
+            {
+                stop("There's no weighted version of the K4_Biweight kernel.")
+            }
+        }
+
+        if(method == "nlminb")
+        {
+            esti <- nlminb(start = initial[-1],
+                           objective = Eij3,
+                           control = list(abs.tol = abs.tol))
+        }else if (method == "optim")
+        {
+            # the new optimize function using optim, you can change the lower and upper
+            esti <- optim(par = initial[-1],
+                          fn = Eij3,
+                          method = optim_method,
+                          control = list(abstol = abs.tol))
+        }else if (method == "nmk")
+        {
+            assertthat::assert_that(requireNamespace("dfoptim", quietly = TRUE))
+            esti <- dfoptim::nmk(par = initial[-1],
+                                 fn = Eij3,
+                                 control = list(tol = abs.tol))
+        }else rlang::abort("Invalid optimization method")
+        results <- list(coef = c(1, esti$par[1:(number_p-1)]),
+                        bandwidth = bandwidth,
+                        details = esti)
+    }
+
+    return(results)
+}
+
+SIDRnew_fixed_bandwidth <-
+function(X, Y, ids,
+         Y.CP = NULL,
+         initial = NULL,
+         kernel = "K2_Biweight",
+         method = c("optim", "nlminb", "nmk"),
+         optim_method = "BFGS",
+         abs.tol = 1e-4
+    ){
+    X <- as.matrix(X)
+    Y <- as.matrix(Y)
+
+    method <- match.arg(method)
+
+    number_n <- dim(X)[1]
+    number_p <- dim(X)[2]
+
+    if (is.null(initial))
+    {
+        initial <- rep(0, number_p)
+    }else
+    {
+        initial <- as.vector(initial)
+    }
+
+    if (kernel=="K2_Biweight")
+        K <- function(x) 15/16*(1-(x)^2)^2 * (abs(x) <= 1)
+    else if (kernel=="dnorm")
+        K <- function(x) dnorm(x,0,1)
+    else if (kernel=="K4_Biweight")
+        K <- function(x) 105/64*(1-3*((x)^2))*(1-(x)^2)^2 * (abs(x) <= 1)
+    else rlang::abort("Bad Kernel")
+
+    Eij3 <- function(parameter){
+        x <- c(X %*% parameter)
+        y <- Y
+
+        n <- length(y)
+        yo <- order(y)
+        ys <- y[yo]
+        uy <- rle(ys)[[1]]
+        cols <- cumsum(uy)
+        ei <- rep(0, n)
+        for (i in 1:n){
+            Kih <- ifelse(ids==ids[i], 0, K(x-x[i]))
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+        }
+        return(sum(ei)/n^2)
+    }
+
+
+    if(method == "nlminb")
+    {
+        esti <- nlminb(start = initial,
+                       objective = Eij3,
+                       control = list(abs.tol = abs.tol))
+    }else if (method == "optim")
+    {
+        # the new optimize function using optim, you can change the lower and upper
+        esti <- optim(par = initial,
+                      fn = Eij3,
+                      method = optim_method,
+                      control = list(abstol = abs.tol))
+    }else if (method == "nmk")
+    {
+        assertthat::assert_that(requireNamespace("dfoptim", quietly = TRUE))
+        esti <- dfoptim::nmk(par = initial,
+                             fn = Eij3,
+                             control = list(tol = abs.tol))
+    }else rlang::abort("Invalid optimization method")
+    results <- list(coef = esti$par,
+                    bandwidth = 1,
+                    details = esti)
+}
diff --git a/SensIAT_sim_outcome_modeler_mave.R b/SensIAT_sim_outcome_modeler_mave.R
new file mode 100644
index 0000000..187e028
--- /dev/null
+++ b/SensIAT_sim_outcome_modeler_mave.R
@@ -0,0 +1,178 @@
+# Single Index Model using MAVE and Optimizing Bandwidth.
+#
+# Single index model estimation using minimum average variance estimation (MAVE).
+# A direction is estimated using MAVE, and then the bandwidth is selected by
+# minimization of the cross-validated pseudo-integrated squared error.
+# Optionally, the initial coefficients of the outcome model can be re-estimated
+# by optimization on a spherical manifold.  This option requires the
+# [ManifoldOptim][ManifoldOptim::manifold.optim] package.
+
+fit_SensIAT_single_index_norm1coef_model <-
+function(X, Y, ids, 
+         kernel = "K2_Biweight",
+         mave.method = "meanMAVE",
+         use_mave,
+         id = ..id..,
+         bw.selection = c('ise', 'mse'),
+         bw.method = c('optim', 'grid', 'optimize'),
+         bw.range = c(0.01, 1.5),
+         reestimate.coef = 0,
+         ...
+){
+    unique_y <- sort(unique(Y))
+
+    if (kernel=="K2_Biweight"){
+        K <- function(x) 15/16*(1-(x)^2)^2 * (abs(x) <= 1)
+        K1<- function(x) 3/4*(1-(x)^2) * (abs(x) <= 1)
+    } else if (kernel=="dnorm") {
+        K <- function(x) dnorm(x,0,1)
+        K1 <- function(x) -x*dnorm(x, 0, 1)
+    } else if (kernel=="K4_Biweight"){
+        K <- function(x) 105/64*(1-3*((x)^2)) * (1-(x)^2)^2 * (abs(x) <= 1)
+    } else{
+        stop("Unknown kernel type. Please use either 'K2_Biweight', 'dnorm', or 'K4_Biweight'.")
+    }
+
+    if(use_mave){
+      assertthat::assert_that(requireNamespace("MAVE", quietly = TRUE))
+      mave_fit <- MAVE::mave.compute(X, Y, max.dim = 1, method = mave.method)
+      beta_hat <- mave_fit$dir[[1]][,1,drop=TRUE]
+    }else{
+      beta_hat <- cumuSIR(X = X, Y = Y)
+    }
+
+    bw_old <- 1
+    delta_beta = NA_real_
+    res <- NULL
+
+    Id_neq <- outer(ids, ids, \(x,y)as.numeric(x!=y))
+    Imat <- outer(Y, unique_y, `<=`)
+    repeat{
+        Xbeta <- (X %*% beta_hat)[,]
+        sigma <- sd(Xbeta)
+        D <- outer(Xbeta, Xbeta, FUN = `-`)
+
+        bw.selection <- match.arg(bw.selection)
+        if(bw.selection == 'ise'){
+            # Use Integrated Squared Error (ISE) for bandwidth selection
+            err <- function(log_bandwidth){
+                W <- K(D/exp(log_bandwidth)) * Id_neq
+                denom <- rowSums(W)
+                Fhat <- sweep(W %*% Imat, 1, denom, "/")
+                Fhat[is.nan(Fhat)] <- 0
+                return (sum((Imat - Fhat)^2)/length(Fhat)^2)
+            }
+        } else if(bw.selection == 'mse'){
+            # Use Mean Squared Error (MSE) for bandwidth selection
+            err <- function(log_bandwidth){
+                W <- K(D/exp(log_bandwidth)) * Id_neq
+                denom <- rowSums(W)
+                mean_Y <- c(W %*% Y) / denom
+                return (mean((Y - mean_Y)^2, na.rm = TRUE))
+            }
+        } else {
+            stop("Unknown bw.selection type. Please use either 'ise' or 'mse'.")
+        }
+
+        bw.method <- match.arg(bw.method)
+        if(bw.method == 'grid'){
+            # Use grid search for bandwidth selection
+            log_bw_seq <- log(seq(min(bw.range), max(bw.range), length.out = 100) * sigma)
+            err_values <- purrr::map_dbl(log_bw_seq, err)
+            bw_opt <- log_bw_seq[which.min(err_values)]
+            bw.details <- list(par = bw_opt,
+                           value = min(err_values),
+                           convergence = 0,
+                           message = "Grid search completed successfully.",
+                           bw.method = bw.method,
+                           log_bw_seq = log_bw_seq,
+                           err_values = err_values
+                           )
+        } else if(bw.method == 'optim'){
+            # Use optimization for bandwidth selection
+            initial <- log(sigma * 0.30)
+            bw.details <- optim(initial, err, method = "L-BFGS-B", lower = log(sigma * min(bw.range)), upper = log(sigma * max(bw.range)), ...)
+            bw.details$initial = initial
+            bw.details$bw.method = bw.method
+            bw_opt <- bw.details$par
+        } else if(bw.method == 'optimize'){
+            # Use optimize for bandwidth selection
+            result <- stats::optimize(err,
+                               interval = c(log(sigma * min(bw.range)), log(sigma * max(bw.range))),
+                               ...)
+            bw_opt <- result$minimum
+            bw.details <- list(minimum = result$minimum,
+                               value = result$objective,
+                               bw.method  = bw.method,
+                               interval = c(log(sigma * 0.05), log(sigma * 1.5)))
+        } else{
+            stop("Unknown bw.method type. Please use either 'optim' or 'grid'.")
+        }
+
+
+        delta_bw = abs(bw_opt - bw_old)
+
+        if(!is.null(res) && res$fval <= bw.details$value) break
+        last.optimized = 'bandwidth'
+
+        if(reestimate.coef <= 0) break
+        reestimate.coef <- reestimate.coef - 1
+
+
+        bw_old <- bw_opt
+        rlang::check_installed("ManifoldOptim")
+        requireNamespace("ManifoldOptim", quietly = TRUE)
+
+        beta_hat_old <- beta_hat
+        if(bw.selection == "ise") {
+            objFun <- function(beta){
+                Xbeta <- (X %*% beta)[,]
+                D <- outer(Xbeta, Xbeta, FUN = `-`)
+                W <- K(D/exp(bw_opt)) * Id_neq
+                denom <- rowSums(W)
+                Fhat <- sweep(W %*% Imat, 1, denom, "/")
+                Fhat[is.nan(Fhat)] <- 0
+                return (sum((Imat - Fhat)^2)/length(Fhat)^2)
+            }
+        } else if(bw.selection == "mse") {
+            objFun <- function(beta){
+                Xbeta <- (X %*% beta)[,]
+                D <- outer(Xbeta, Xbeta, FUN = `-`)
+                W <- K1(D/exp(bw_opt)) * Id_neq
+                denom <- rowSums(W)
+                mean_Y <- c(W %*% Y) / denom
+                return (mean((Y - mean_Y)^2, na.rm = TRUE))
+            }
+        } else {
+            stop("Unknown bw.selection type. Please use either 'ise' or 'mse'.")
+        }
+        mod <- Rcpp::Module("ManifoldOptim_module", PACKAGE = "ManifoldOptim")
+        prob <- new(mod$RProblem, objFun)
+        mani.params <- ManifoldOptim::get.manifold.params(IsCheckParams = FALSE)
+        solver.params <- ManifoldOptim::get.solver.params(IsCheckParams = FALSE)
+        maniDef <- ManifoldOptim::get.sphere.defn(length(beta_hat))
+
+        res <- ManifoldOptim::manifold.optim(prob, maniDef,
+                              mani.params = mani.params,
+                              solver.params = solver.params, x0 = beta_hat)
+        if(res$fval >= bw.details$value) break
+        last.optimized = 'beta'
+
+        beta_hat <- as.vector(res$xopt)
+        delta_beta = abs(beta_hat - beta_hat_old)
+    }
+    return(
+            list(
+                coef = beta_hat,
+                bandwidth = exp(bw_opt),
+                details = list(bw.last = bw.details,
+                               bw.delta = delta_bw,
+                               bw.unscaled = bw_opt/sigma,
+                               beta.delta = delta_beta,
+                               beta.last  = res,
+                               last.optimized = last.optimized
+                               )
+            )
+    )
+}
+
diff --git a/est_s_t_y.R b/est_s_t_y.R
index b6bd976..a71baff 100644
--- a/est_s_t_y.R
+++ b/est_s_t_y.R
@@ -1,7 +1,8 @@
 
 est_psi <- function(Y, M, R, X, t, trt, gamma, fold, seed, IF_output, 
                     simple_trunc, quant, kernel, method, single_index_method, 
-                    use_mave=TRUE){
+                    use_mave=TRUE, coef_g.fit=NULL, coef_t_R0.fit=NULL, coef_t_R1.fit=NULL, 
+                    coef_M_R0.fit=NULL, coef_M_R1.fit=NULL){
   
   n <- length(t)
   Y[is.na(Y)] <- 0
@@ -97,9 +98,9 @@ est_psi <- function(Y, M, R, X, t, trt, gamma, fold, seed, IF_output,
     X_out_fold <- X[out_fold_id_list, ]
     X_with_T_out_fold <- X_with_T[out_fold_id_list, ]
     
-    trt.ind_out_fold_R0 <- trt.ind_out_fold[which(R_out_fold==0)]
+    t_out_fold_R0 <- t_out_fold[which(R_out_fold==0)]
     X_out_fold_R0 <- X_out_fold[which(R_out_fold==0), ]
-    trt.ind_out_fold_R1 <- trt.ind_out_fold[which(R_out_fold==1)]
+    t_out_fold_R1 <- t_out_fold[which(R_out_fold==1)]
     X_out_fold_R1 <- X_out_fold[which(R_out_fold==1), ]
     
     M_out_fold_R0 <- M_out_fold[which(R_out_fold==0)]
@@ -124,17 +125,25 @@ est_psi <- function(Y, M, R, X, t, trt, gamma, fold, seed, IF_output,
     X_with_T_in_fold_R1 <- X_with_T_in_fold[which(R_in_fold==1), ]
     
     ## fit models
-    t_R0.fit <- mgcv::gam(as.formula(paste("trt.ind_out_fold_R0 ~", gam.var)), data=X_out_fold_R0, family=binomial) ## treatment model
-    t_R1.fit <- mgcv::gam(as.formula(paste("trt.ind_out_fold_R1 ~", gam.var)), data=X_out_fold_R1, family=binomial) ## treatment model
-    
-    M_R0.fit <- mgcv::gam(as.formula(paste("M_out_fold_R0 ~", gam.var.M)), data=X_with_T_out_fold_R0, family=binomial) ## missing data model
-    M_R1.fit <- mgcv::gam(as.formula(paste("M_out_fold_R1 ~", gam.var.M)), data=X_with_T_out_fold_R1, family=binomial) ## missing data model
+    t_R0.fit <- mgcv::gam(as.formula(paste("t_out_fold_R0 ~", gam.var)), data=X_out_fold_R0, 
+                          family=binomial, start=coef_t_R0.fit) ## treatment model
+    t_R1.fit <- mgcv::gam(as.formula(paste("t_out_fold_R1 ~", gam.var)), data=X_out_fold_R1, 
+                          family=binomial, start=coef_t_R1.fit) ## treatment model
+    M_R0.fit <- mgcv::gam(as.formula(paste("M_out_fold_R0 ~", gam.var.M)), data=X_with_T_out_fold_R0, 
+                          family=binomial, start=coef_M_R0.fit) ## missing data model
+    M_R1.fit <- mgcv::gam(as.formula(paste("M_out_fold_R1 ~", gam.var.M)), data=X_with_T_out_fold_R1, 
+                          family=binomial, start=coef_M_R1.fit) ## missing data model
     
     prop.R1 <- mean(R_in_fold)
     
     ## get predictions for pi
-    pi_R0 <- predict(t_R0.fit, newdata=X_in_fold_t_R0, type="response") 
-    pi_R1 <- predict(t_R1.fit, newdata=X_in_fold_R1, type="response")
+    if(trt==1){
+      pi_R0 <- predict(t_R0.fit, newdata=X_in_fold_t_R0, type="response") 
+      pi_R1 <- predict(t_R1.fit, newdata=X_in_fold_R1, type="response")  
+    }else{
+      pi_R0 <- 1-predict(t_R0.fit, newdata=X_in_fold_t_R0, type="response") 
+      pi_R1 <- 1-predict(t_R1.fit, newdata=X_in_fold_R1, type="response")  
+    }
     pi_R0_l <- c(pi_R0_l, pi_R0)
     pi_R1_l <- c(pi_R1_l, pi_R1)
     fold_index_pi_R0_l <- c(fold_index_pi_R0_l, rep(k, length(pi_R0)))
diff --git a/profvis.html b/profvis.html
new file mode 100644
index 0000000..cf77c96
--- /dev/null
+++ b/profvis.html
@@ -0,0 +1,4637 @@
+<!DOCTYPE html>
+<html>
+<head>
+<meta charset="utf-8" />
+<title>profvis</title>
+<style type="text/css">@layer htmltools {
+.html-fill-container {
+display: flex;
+flex-direction: column;
+
+min-height: 0;
+min-width: 0;
+}
+.html-fill-container > .html-fill-item {
+
+flex: 1 1 auto;
+min-height: 0;
+min-width: 0;
+}
+.html-fill-container > :not(.html-fill-item) {
+
+flex: 0 0 auto;
+}
+}
+</style>
+<script>(function() {
+  // If window.HTMLWidgets is already defined, then use it; otherwise create a
+  // new object. This allows preceding code to set options that affect the
+  // initialization process (though none currently exist).
+  window.HTMLWidgets = window.HTMLWidgets || {};
+
+  // See if we're running in a viewer pane. If not, we're in a web browser.
+  var viewerMode = window.HTMLWidgets.viewerMode =
+      /\bviewer_pane=1\b/.test(window.location);
+
+  // See if we're running in Shiny mode. If not, it's a static document.
+  // Note that static widgets can appear in both Shiny and static modes, but
+  // obviously, Shiny widgets can only appear in Shiny apps/documents.
+  var shinyMode = window.HTMLWidgets.shinyMode =
+      typeof(window.Shiny) !== "undefined" && !!window.Shiny.outputBindings;
+
+  // We can't count on jQuery being available, so we implement our own
+  // version if necessary.
+  function querySelectorAll(scope, selector) {
+    if (typeof(jQuery) !== "undefined" && scope instanceof jQuery) {
+      return scope.find(selector);
+    }
+    if (scope.querySelectorAll) {
+      return scope.querySelectorAll(selector);
+    }
+  }
+
+  function asArray(value) {
+    if (value === null)
+      return [];
+    if ($.isArray(value))
+      return value;
+    return [value];
+  }
+
+  // Implement jQuery's extend
+  function extend(target /*, ... */) {
+    if (arguments.length == 1) {
+      return target;
+    }
+    for (var i = 1; i < arguments.length; i++) {
+      var source = arguments[i];
+      for (var prop in source) {
+        if (source.hasOwnProperty(prop)) {
+          target[prop] = source[prop];
+        }
+      }
+    }
+    return target;
+  }
+
+  // IE8 doesn't support Array.forEach.
+  function forEach(values, callback, thisArg) {
+    if (values.forEach) {
+      values.forEach(callback, thisArg);
+    } else {
+      for (var i = 0; i < values.length; i++) {
+        callback.call(thisArg, values[i], i, values);
+      }
+    }
+  }
+
+  // Replaces the specified method with the return value of funcSource.
+  //
+  // Note that funcSource should not BE the new method, it should be a function
+  // that RETURNS the new method. funcSource receives a single argument that is
+  // the overridden method, it can be called from the new method. The overridden
+  // method can be called like a regular function, it has the target permanently
+  // bound to it so "this" will work correctly.
+  function overrideMethod(target, methodName, funcSource) {
+    var superFunc = target[methodName] || function() {};
+    var superFuncBound = function() {
+      return superFunc.apply(target, arguments);
+    };
+    target[methodName] = funcSource(superFuncBound);
+  }
+
+  // Add a method to delegator that, when invoked, calls
+  // delegatee.methodName. If there is no such method on
+  // the delegatee, but there was one on delegator before
+  // delegateMethod was called, then the original version
+  // is invoked instead.
+  // For example:
+  //
+  // var a = {
+  //   method1: function() { console.log('a1'); }
+  //   method2: function() { console.log('a2'); }
+  // };
+  // var b = {
+  //   method1: function() { console.log('b1'); }
+  // };
+  // delegateMethod(a, b, "method1");
+  // delegateMethod(a, b, "method2");
+  // a.method1();
+  // a.method2();
+  //
+  // The output would be "b1", "a2".
+  function delegateMethod(delegator, delegatee, methodName) {
+    var inherited = delegator[methodName];
+    delegator[methodName] = function() {
+      var target = delegatee;
+      var method = delegatee[methodName];
+
+      // The method doesn't exist on the delegatee. Instead,
+      // call the method on the delegator, if it exists.
+      if (!method) {
+        target = delegator;
+        method = inherited;
+      }
+
+      if (method) {
+        return method.apply(target, arguments);
+      }
+    };
+  }
+
+  // Implement a vague facsimilie of jQuery's data method
+  function elementData(el, name, value) {
+    if (arguments.length == 2) {
+      return el["htmlwidget_data_" + name];
+    } else if (arguments.length == 3) {
+      el["htmlwidget_data_" + name] = value;
+      return el;
+    } else {
+      throw new Error("Wrong number of arguments for elementData: " +
+        arguments.length);
+    }
+  }
+
+  // http://stackoverflow.com/questions/3446170/escape-string-for-use-in-javascript-regex
+  function escapeRegExp(str) {
+    return str.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g, "\\$&");
+  }
+
+  function hasClass(el, className) {
+    var re = new RegExp("\\b" + escapeRegExp(className) + "\\b");
+    return re.test(el.className);
+  }
+
+  // elements - array (or array-like object) of HTML elements
+  // className - class name to test for
+  // include - if true, only return elements with given className;
+  //   if false, only return elements *without* given className
+  function filterByClass(elements, className, include) {
+    var results = [];
+    for (var i = 0; i < elements.length; i++) {
+      if (hasClass(elements[i], className) == include)
+        results.push(elements[i]);
+    }
+    return results;
+  }
+
+  function on(obj, eventName, func) {
+    if (obj.addEventListener) {
+      obj.addEventListener(eventName, func, false);
+    } else if (obj.attachEvent) {
+      obj.attachEvent(eventName, func);
+    }
+  }
+
+  function off(obj, eventName, func) {
+    if (obj.removeEventListener)
+      obj.removeEventListener(eventName, func, false);
+    else if (obj.detachEvent) {
+      obj.detachEvent(eventName, func);
+    }
+  }
+
+  // Translate array of values to top/right/bottom/left, as usual with
+  // the "padding" CSS property
+  // https://developer.mozilla.org/en-US/docs/Web/CSS/padding
+  function unpackPadding(value) {
+    if (typeof(value) === "number")
+      value = [value];
+    if (value.length === 1) {
+      return {top: value[0], right: value[0], bottom: value[0], left: value[0]};
+    }
+    if (value.length === 2) {
+      return {top: value[0], right: value[1], bottom: value[0], left: value[1]};
+    }
+    if (value.length === 3) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[1]};
+    }
+    if (value.length === 4) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[3]};
+    }
+  }
+
+  // Convert an unpacked padding object to a CSS value
+  function paddingToCss(paddingObj) {
+    return paddingObj.top + "px " + paddingObj.right + "px " + paddingObj.bottom + "px " + paddingObj.left + "px";
+  }
+
+  // Makes a number suitable for CSS
+  function px(x) {
+    if (typeof(x) === "number")
+      return x + "px";
+    else
+      return x;
+  }
+
+  // Retrieves runtime widget sizing information for an element.
+  // The return value is either null, or an object with fill, padding,
+  // defaultWidth, defaultHeight fields.
+  function sizingPolicy(el) {
+    var sizingEl = document.querySelector("script[data-for='" + el.id + "'][type='application/htmlwidget-sizing']");
+    if (!sizingEl)
+      return null;
+    var sp = JSON.parse(sizingEl.textContent || sizingEl.text || "{}");
+    if (viewerMode) {
+      return sp.viewer;
+    } else {
+      return sp.browser;
+    }
+  }
+
+  // @param tasks Array of strings (or falsy value, in which case no-op).
+  //   Each element must be a valid JavaScript expression that yields a
+  //   function. Or, can be an array of objects with "code" and "data"
+  //   properties; in this case, the "code" property should be a string
+  //   of JS that's an expr that yields a function, and "data" should be
+  //   an object that will be added as an additional argument when that
+  //   function is called.
+  // @param target The object that will be "this" for each function
+  //   execution.
+  // @param args Array of arguments to be passed to the functions. (The
+  //   same arguments will be passed to all functions.)
+  function evalAndRun(tasks, target, args) {
+    if (tasks) {
+      forEach(tasks, function(task) {
+        var theseArgs = args;
+        if (typeof(task) === "object") {
+          theseArgs = theseArgs.concat([task.data]);
+          task = task.code;
+        }
+        var taskFunc = tryEval(task);
+        if (typeof(taskFunc) !== "function") {
+          throw new Error("Task must be a function! Source:\n" + task);
+        }
+        taskFunc.apply(target, theseArgs);
+      });
+    }
+  }
+
+  // Attempt eval() both with and without enclosing in parentheses.
+  // Note that enclosing coerces a function declaration into
+  // an expression that eval() can parse
+  // (otherwise, a SyntaxError is thrown)
+  function tryEval(code) {
+    var result = null;
+    try {
+      result = eval("(" + code + ")");
+    } catch(error) {
+      if (!(error instanceof SyntaxError)) {
+        throw error;
+      }
+      try {
+        result = eval(code);
+      } catch(e) {
+        if (e instanceof SyntaxError) {
+          throw error;
+        } else {
+          throw e;
+        }
+      }
+    }
+    return result;
+  }
+
+  function initSizing(el) {
+    var sizing = sizingPolicy(el);
+    if (!sizing)
+      return;
+
+    var cel = document.getElementById("htmlwidget_container");
+    if (!cel)
+      return;
+
+    if (typeof(sizing.padding) !== "undefined") {
+      document.body.style.margin = "0";
+      document.body.style.padding = paddingToCss(unpackPadding(sizing.padding));
+    }
+
+    if (sizing.fill) {
+      document.body.style.overflow = "hidden";
+      document.body.style.width = "100%";
+      document.body.style.height = "100%";
+      document.documentElement.style.width = "100%";
+      document.documentElement.style.height = "100%";
+      cel.style.position = "absolute";
+      var pad = unpackPadding(sizing.padding);
+      cel.style.top = pad.top + "px";
+      cel.style.right = pad.right + "px";
+      cel.style.bottom = pad.bottom + "px";
+      cel.style.left = pad.left + "px";
+      el.style.width = "100%";
+      el.style.height = "100%";
+
+      return {
+        getWidth: function() { return cel.getBoundingClientRect().width; },
+        getHeight: function() { return cel.getBoundingClientRect().height; }
+      };
+
+    } else {
+      el.style.width = px(sizing.width);
+      el.style.height = px(sizing.height);
+
+      return {
+        getWidth: function() { return cel.getBoundingClientRect().width; },
+        getHeight: function() { return cel.getBoundingClientRect().height; }
+      };
+    }
+  }
+
+  // Default implementations for methods
+  var defaults = {
+    find: function(scope) {
+      return querySelectorAll(scope, "." + this.name);
+    },
+    renderError: function(el, err) {
+      var $el = $(el);
+
+      this.clearError(el);
+
+      // Add all these error classes, as Shiny does
+      var errClass = "shiny-output-error";
+      if (err.type !== null) {
+        // use the classes of the error condition as CSS class names
+        errClass = errClass + " " + $.map(asArray(err.type), function(type) {
+          return errClass + "-" + type;
+        }).join(" ");
+      }
+      errClass = errClass + " htmlwidgets-error";
+
+      // Is el inline or block? If inline or inline-block, just display:none it
+      // and add an inline error.
+      var display = $el.css("display");
+      $el.data("restore-display-mode", display);
+
+      if (display === "inline" || display === "inline-block") {
+        $el.hide();
+        if (err.message !== "") {
+          var errorSpan = $("<span>").addClass(errClass);
+          errorSpan.text(err.message);
+          $el.after(errorSpan);
+        }
+      } else if (display === "block") {
+        // If block, add an error just after the el, set visibility:none on the
+        // el, and position the error to be on top of the el.
+        // Mark it with a unique ID and CSS class so we can remove it later.
+        $el.css("visibility", "hidden");
+        if (err.message !== "") {
+          var errorDiv = $("<div>").addClass(errClass).css("position", "absolute")
+            .css("top", el.offsetTop)
+            .css("left", el.offsetLeft)
+            // setting width can push out the page size, forcing otherwise
+            // unnecessary scrollbars to appear and making it impossible for
+            // the element to shrink; so use max-width instead
+            .css("maxWidth", el.offsetWidth)
+            .css("height", el.offsetHeight);
+          errorDiv.text(err.message);
+          $el.after(errorDiv);
+
+          // Really dumb way to keep the size/position of the error in sync with
+          // the parent element as the window is resized or whatever.
+          var intId = setInterval(function() {
+            if (!errorDiv[0].parentElement) {
+              clearInterval(intId);
+              return;
+            }
+            errorDiv
+              .css("top", el.offsetTop)
+              .css("left", el.offsetLeft)
+              .css("maxWidth", el.offsetWidth)
+              .css("height", el.offsetHeight);
+          }, 500);
+        }
+      }
+    },
+    clearError: function(el) {
+      var $el = $(el);
+      var display = $el.data("restore-display-mode");
+      $el.data("restore-display-mode", null);
+
+      if (display === "inline" || display === "inline-block") {
+        if (display)
+          $el.css("display", display);
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      } else if (display === "block"){
+        $el.css("visibility", "inherit");
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      }
+    },
+    sizing: {}
+  };
+
+  // Called by widget bindings to register a new type of widget. The definition
+  // object can contain the following properties:
+  // - name (required) - A string indicating the binding name, which will be
+  //   used by default as the CSS classname to look for.
+  // - initialize (optional) - A function(el) that will be called once per
+  //   widget element; if a value is returned, it will be passed as the third
+  //   value to renderValue.
+  // - renderValue (required) - A function(el, data, initValue) that will be
+  //   called with data. Static contexts will cause this to be called once per
+  //   element; Shiny apps will cause this to be called multiple times per
+  //   element, as the data changes.
+  window.HTMLWidgets.widget = function(definition) {
+    if (!definition.name) {
+      throw new Error("Widget must have a name");
+    }
+    if (!definition.type) {
+      throw new Error("Widget must have a type");
+    }
+    // Currently we only support output widgets
+    if (definition.type !== "output") {
+      throw new Error("Unrecognized widget type '" + definition.type + "'");
+    }
+    // TODO: Verify that .name is a valid CSS classname
+
+    // Support new-style instance-bound definitions. Old-style class-bound
+    // definitions have one widget "object" per widget per type/class of
+    // widget; the renderValue and resize methods on such widget objects
+    // take el and instance arguments, because the widget object can't
+    // store them. New-style instance-bound definitions have one widget
+    // object per widget instance; the definition that's passed in doesn't
+    // provide renderValue or resize methods at all, just the single method
+    //   factory(el, width, height)
+    // which returns an object that has renderValue(x) and resize(w, h).
+    // This enables a far more natural programming style for the widget
+    // author, who can store per-instance state using either OO-style
+    // instance fields or functional-style closure variables (I guess this
+    // is in contrast to what can only be called C-style pseudo-OO which is
+    // what we required before).
+    if (definition.factory) {
+      definition = createLegacyDefinitionAdapter(definition);
+    }
+
+    if (!definition.renderValue) {
+      throw new Error("Widget must have a renderValue function");
+    }
+
+    // For static rendering (non-Shiny), use a simple widget registration
+    // scheme. We also use this scheme for Shiny apps/documents that also
+    // contain static widgets.
+    window.HTMLWidgets.widgets = window.HTMLWidgets.widgets || [];
+    // Merge defaults into the definition; don't mutate the original definition.
+    var staticBinding = extend({}, defaults, definition);
+    overrideMethod(staticBinding, "find", function(superfunc) {
+      return function(scope) {
+        var results = superfunc(scope);
+        // Filter out Shiny outputs, we only want the static kind
+        return filterByClass(results, "html-widget-output", false);
+      };
+    });
+    window.HTMLWidgets.widgets.push(staticBinding);
+
+    if (shinyMode) {
+      // Shiny is running. Register the definition with an output binding.
+      // The definition itself will not be the output binding, instead
+      // we will make an output binding object that delegates to the
+      // definition. This is because we foolishly used the same method
+      // name (renderValue) for htmlwidgets definition and Shiny bindings
+      // but they actually have quite different semantics (the Shiny
+      // bindings receive data that includes lots of metadata that it
+      // strips off before calling htmlwidgets renderValue). We can't
+      // just ignore the difference because in some widgets it's helpful
+      // to call this.renderValue() from inside of resize(), and if
+      // we're not delegating, then that call will go to the Shiny
+      // version instead of the htmlwidgets version.
+
+      // Merge defaults with definition, without mutating either.
+      var bindingDef = extend({}, defaults, definition);
+
+      // This object will be our actual Shiny binding.
+      var shinyBinding = new Shiny.OutputBinding();
+
+      // With a few exceptions, we'll want to simply use the bindingDef's
+      // version of methods if they are available, otherwise fall back to
+      // Shiny's defaults. NOTE: If Shiny's output bindings gain additional
+      // methods in the future, and we want them to be overrideable by
+      // HTMLWidget binding definitions, then we'll need to add them to this
+      // list.
+      delegateMethod(shinyBinding, bindingDef, "getId");
+      delegateMethod(shinyBinding, bindingDef, "onValueChange");
+      delegateMethod(shinyBinding, bindingDef, "onValueError");
+      delegateMethod(shinyBinding, bindingDef, "renderError");
+      delegateMethod(shinyBinding, bindingDef, "clearError");
+      delegateMethod(shinyBinding, bindingDef, "showProgress");
+
+      // The find, renderValue, and resize are handled differently, because we
+      // want to actually decorate the behavior of the bindingDef methods.
+
+      shinyBinding.find = function(scope) {
+        var results = bindingDef.find(scope);
+
+        // Only return elements that are Shiny outputs, not static ones
+        var dynamicResults = results.filter(".html-widget-output");
+
+        // It's possible that whatever caused Shiny to think there might be
+        // new dynamic outputs, also caused there to be new static outputs.
+        // Since there might be lots of different htmlwidgets bindings, we
+        // schedule execution for later--no need to staticRender multiple
+        // times.
+        if (results.length !== dynamicResults.length)
+          scheduleStaticRender();
+
+        return dynamicResults;
+      };
+
+      // Wrap renderValue to handle initialization, which unfortunately isn't
+      // supported natively by Shiny at the time of this writing.
+
+      shinyBinding.renderValue = function(el, data) {
+        Shiny.renderDependencies(data.deps);
+        // Resolve strings marked as javascript literals to objects
+        if (!(data.evals instanceof Array)) data.evals = [data.evals];
+        for (var i = 0; data.evals && i < data.evals.length; i++) {
+          window.HTMLWidgets.evaluateStringMember(data.x, data.evals[i]);
+        }
+        if (!bindingDef.renderOnNullValue) {
+          if (data.x === null) {
+            el.style.visibility = "hidden";
+            return;
+          } else {
+            el.style.visibility = "inherit";
+          }
+        }
+        if (!elementData(el, "initialized")) {
+          initSizing(el);
+
+          elementData(el, "initialized", true);
+          if (bindingDef.initialize) {
+            var rect = el.getBoundingClientRect();
+            var result = bindingDef.initialize(el, rect.width, rect.height);
+            elementData(el, "init_result", result);
+          }
+        }
+        bindingDef.renderValue(el, data.x, elementData(el, "init_result"));
+        evalAndRun(data.jsHooks.render, elementData(el, "init_result"), [el, data.x]);
+      };
+
+      // Only override resize if bindingDef implements it
+      if (bindingDef.resize) {
+        shinyBinding.resize = function(el, width, height) {
+          // Shiny can call resize before initialize/renderValue have been
+          // called, which doesn't make sense for widgets.
+          if (elementData(el, "initialized")) {
+            bindingDef.resize(el, width, height, elementData(el, "init_result"));
+          }
+        };
+      }
+
+      Shiny.outputBindings.register(shinyBinding, bindingDef.name);
+    }
+  };
+
+  var scheduleStaticRenderTimerId = null;
+  function scheduleStaticRender() {
+    if (!scheduleStaticRenderTimerId) {
+      scheduleStaticRenderTimerId = setTimeout(function() {
+        scheduleStaticRenderTimerId = null;
+        window.HTMLWidgets.staticRender();
+      }, 1);
+    }
+  }
+
+  // Render static widgets after the document finishes loading
+  // Statically render all elements that are of this widget's class
+  window.HTMLWidgets.staticRender = function() {
+    var bindings = window.HTMLWidgets.widgets || [];
+    forEach(bindings, function(binding) {
+      var matches = binding.find(document.documentElement);
+      forEach(matches, function(el) {
+        var sizeObj = initSizing(el, binding);
+
+        var getSize = function(el) {
+          if (sizeObj) {
+            return {w: sizeObj.getWidth(), h: sizeObj.getHeight()}
+          } else {
+            var rect = el.getBoundingClientRect();
+            return {w: rect.width, h: rect.height}
+          }
+        };
+
+        if (hasClass(el, "html-widget-static-bound"))
+          return;
+        el.className = el.className + " html-widget-static-bound";
+
+        var initResult;
+        if (binding.initialize) {
+          var size = getSize(el);
+          initResult = binding.initialize(el, size.w, size.h);
+          elementData(el, "init_result", initResult);
+        }
+
+        if (binding.resize) {
+          var lastSize = getSize(el);
+          var resizeHandler = function(e) {
+            var size = getSize(el);
+            if (size.w === 0 && size.h === 0)
+              return;
+            if (size.w === lastSize.w && size.h === lastSize.h)
+              return;
+            lastSize = size;
+            binding.resize(el, size.w, size.h, initResult);
+          };
+
+          on(window, "resize", resizeHandler);
+
+          // This is needed for cases where we're running in a Shiny
+          // app, but the widget itself is not a Shiny output, but
+          // rather a simple static widget. One example of this is
+          // an rmarkdown document that has runtime:shiny and widget
+          // that isn't in a render function. Shiny only knows to
+          // call resize handlers for Shiny outputs, not for static
+          // widgets, so we do it ourselves.
+          if (window.jQuery) {
+            window.jQuery(document).on(
+              "shown.htmlwidgets shown.bs.tab.htmlwidgets shown.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+            window.jQuery(document).on(
+              "hidden.htmlwidgets hidden.bs.tab.htmlwidgets hidden.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+          }
+
+          // This is needed for the specific case of ioslides, which
+          // flips slides between display:none and display:block.
+          // Ideally we would not have to have ioslide-specific code
+          // here, but rather have ioslides raise a generic event,
+          // but the rmarkdown package just went to CRAN so the
+          // window to getting that fixed may be long.
+          if (window.addEventListener) {
+            // It's OK to limit this to window.addEventListener
+            // browsers because ioslides itself only supports
+            // such browsers.
+            on(document, "slideenter", resizeHandler);
+            on(document, "slideleave", resizeHandler);
+          }
+        }
+
+        var scriptData = document.querySelector("script[data-for='" + el.id + "'][type='application/json']");
+        if (scriptData) {
+          var data = JSON.parse(scriptData.textContent || scriptData.text);
+          // Resolve strings marked as javascript literals to objects
+          if (!(data.evals instanceof Array)) data.evals = [data.evals];
+          for (var k = 0; data.evals && k < data.evals.length; k++) {
+            window.HTMLWidgets.evaluateStringMember(data.x, data.evals[k]);
+          }
+          binding.renderValue(el, data.x, initResult);
+          evalAndRun(data.jsHooks.render, initResult, [el, data.x]);
+        }
+      });
+    });
+
+    invokePostRenderHandlers();
+  }
+
+
+  function has_jQuery3() {
+    if (!window.jQuery) {
+      return false;
+    }
+    var $version = window.jQuery.fn.jquery;
+    var $major_version = parseInt($version.split(".")[0]);
+    return $major_version >= 3;
+  }
+
+  /*
+  / Shiny 1.4 bumped jQuery from 1.x to 3.x which means jQuery's
+  / on-ready handler (i.e., $(fn)) is now asyncronous (i.e., it now
+  / really means $(setTimeout(fn)).
+  / https://jquery.com/upgrade-guide/3.0/#breaking-change-document-ready-handlers-are-now-asynchronous
+  /
+  / Since Shiny uses $() to schedule initShiny, shiny>=1.4 calls initShiny
+  / one tick later than it did before, which means staticRender() is
+  / called renderValue() earlier than (advanced) widget authors might be expecting.
+  / https://github.com/rstudio/shiny/issues/2630
+  /
+  / For a concrete example, leaflet has some methods (e.g., updateBounds)
+  / which reference Shiny methods registered in initShiny (e.g., setInputValue).
+  / Since leaflet is privy to this life-cycle, it knows to use setTimeout() to
+  / delay execution of those methods (until Shiny methods are ready)
+  / https://github.com/rstudio/leaflet/blob/18ec981/javascript/src/index.js#L266-L268
+  /
+  / Ideally widget authors wouldn't need to use this setTimeout() hack that
+  / leaflet uses to call Shiny methods on a staticRender(). In the long run,
+  / the logic initShiny should be broken up so that method registration happens
+  / right away, but binding happens later.
+  */
+  function maybeStaticRenderLater() {
+    if (shinyMode && has_jQuery3()) {
+      window.jQuery(window.HTMLWidgets.staticRender);
+    } else {
+      window.HTMLWidgets.staticRender();
+    }
+  }
+
+  if (document.addEventListener) {
+    document.addEventListener("DOMContentLoaded", function() {
+      document.removeEventListener("DOMContentLoaded", arguments.callee, false);
+      maybeStaticRenderLater();
+    }, false);
+  } else if (document.attachEvent) {
+    document.attachEvent("onreadystatechange", function() {
+      if (document.readyState === "complete") {
+        document.detachEvent("onreadystatechange", arguments.callee);
+        maybeStaticRenderLater();
+      }
+    });
+  }
+
+
+  window.HTMLWidgets.getAttachmentUrl = function(depname, key) {
+    // If no key, default to the first item
+    if (typeof(key) === "undefined")
+      key = 1;
+
+    var link = document.getElementById(depname + "-" + key + "-attachment");
+    if (!link) {
+      throw new Error("Attachment " + depname + "/" + key + " not found in document");
+    }
+    return link.getAttribute("href");
+  };
+
+  window.HTMLWidgets.dataframeToD3 = function(df) {
+    var names = [];
+    var length;
+    for (var name in df) {
+        if (df.hasOwnProperty(name))
+            names.push(name);
+        if (typeof(df[name]) !== "object" || typeof(df[name].length) === "undefined") {
+            throw new Error("All fields must be arrays");
+        } else if (typeof(length) !== "undefined" && length !== df[name].length) {
+            throw new Error("All fields must be arrays of the same length");
+        }
+        length = df[name].length;
+    }
+    var results = [];
+    var item;
+    for (var row = 0; row < length; row++) {
+        item = {};
+        for (var col = 0; col < names.length; col++) {
+            item[names[col]] = df[names[col]][row];
+        }
+        results.push(item);
+    }
+    return results;
+  };
+
+  window.HTMLWidgets.transposeArray2D = function(array) {
+      if (array.length === 0) return array;
+      var newArray = array[0].map(function(col, i) {
+          return array.map(function(row) {
+              return row[i]
+          })
+      });
+      return newArray;
+  };
+  // Split value at splitChar, but allow splitChar to be escaped
+  // using escapeChar. Any other characters escaped by escapeChar
+  // will be included as usual (including escapeChar itself).
+  function splitWithEscape(value, splitChar, escapeChar) {
+    var results = [];
+    var escapeMode = false;
+    var currentResult = "";
+    for (var pos = 0; pos < value.length; pos++) {
+      if (!escapeMode) {
+        if (value[pos] === splitChar) {
+          results.push(currentResult);
+          currentResult = "";
+        } else if (value[pos] === escapeChar) {
+          escapeMode = true;
+        } else {
+          currentResult += value[pos];
+        }
+      } else {
+        currentResult += value[pos];
+        escapeMode = false;
+      }
+    }
+    if (currentResult !== "") {
+      results.push(currentResult);
+    }
+    return results;
+  }
+  // Function authored by Yihui/JJ Allaire
+  window.HTMLWidgets.evaluateStringMember = function(o, member) {
+    var parts = splitWithEscape(member, '.', '\\');
+    for (var i = 0, l = parts.length; i < l; i++) {
+      var part = parts[i];
+      // part may be a character or 'numeric' member name
+      if (o !== null && typeof o === "object" && part in o) {
+        if (i == (l - 1)) { // if we are at the end of the line then evalulate
+          if (typeof o[part] === "string")
+            o[part] = tryEval(o[part]);
+        } else { // otherwise continue to next embedded object
+          o = o[part];
+        }
+      }
+    }
+  };
+
+  // Retrieve the HTMLWidget instance (i.e. the return value of an
+  // HTMLWidget binding's initialize() or factory() function)
+  // associated with an element, or null if none.
+  window.HTMLWidgets.getInstance = function(el) {
+    return elementData(el, "init_result");
+  };
+
+  // Finds the first element in the scope that matches the selector,
+  // and returns the HTMLWidget instance (i.e. the return value of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with that element, if any. If no element matches the
+  // selector, or the first matching element has no HTMLWidget
+  // instance associated with it, then null is returned.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.find = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var el = scope.querySelector(selector);
+    if (el === null) {
+      return null;
+    } else {
+      return window.HTMLWidgets.getInstance(el);
+    }
+  };
+
+  // Finds all elements in the scope that match the selector, and
+  // returns the HTMLWidget instances (i.e. the return values of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with the elements, in an array. If elements that
+  // match the selector don't have an associated HTMLWidget
+  // instance, the returned array will contain nulls.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.findAll = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var nodes = scope.querySelectorAll(selector);
+    var results = [];
+    for (var i = 0; i < nodes.length; i++) {
+      results.push(window.HTMLWidgets.getInstance(nodes[i]));
+    }
+    return results;
+  };
+
+  var postRenderHandlers = [];
+  function invokePostRenderHandlers() {
+    while (postRenderHandlers.length) {
+      var handler = postRenderHandlers.shift();
+      if (handler) {
+        handler();
+      }
+    }
+  }
+
+  // Register the given callback function to be invoked after the
+  // next time static widgets are rendered.
+  window.HTMLWidgets.addPostRenderHandler = function(callback) {
+    postRenderHandlers.push(callback);
+  };
+
+  // Takes a new-style instance-bound definition, and returns an
+  // old-style class-bound definition. This saves us from having
+  // to rewrite all the logic in this file to accomodate both
+  // types of definitions.
+  function createLegacyDefinitionAdapter(defn) {
+    var result = {
+      name: defn.name,
+      type: defn.type,
+      initialize: function(el, width, height) {
+        return defn.factory(el, width, height);
+      },
+      renderValue: function(el, x, instance) {
+        return instance.renderValue(x);
+      },
+      resize: function(el, width, height, instance) {
+        return instance.resize(width, height);
+      }
+    };
+
+    if (defn.find)
+      result.find = defn.find;
+    if (defn.renderError)
+      result.renderError = defn.renderError;
+    if (defn.clearError)
+      result.clearError = defn.clearError;
+
+    return result;
+  }
+})();
+</script>
+<script>/*! jQuery v3.7.1 | (c) OpenJS Foundation and other contributors | jquery.org/license */
+!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(ie,e){"use strict";var oe=[],r=Object.getPrototypeOf,ae=oe.slice,g=oe.flat?function(e){return oe.flat.call(e)}:function(e){return oe.concat.apply([],e)},s=oe.push,se=oe.indexOf,n={},i=n.toString,ue=n.hasOwnProperty,o=ue.toString,a=o.call(Object),le={},v=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},y=function(e){return null!=e&&e===e.window},C=ie.document,u={type:!0,src:!0,nonce:!0,noModule:!0};function m(e,t,n){var r,i,o=(n=n||C).createElement("script");if(o.text=e,t)for(r in u)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function x(e){return null==e?e+"":"object"==typeof e||"function"==typeof e?n[i.call(e)]||"object":typeof e}var t="3.7.1",l=/HTML$/i,ce=function(e,t){return new ce.fn.init(e,t)};function c(e){var t=!!e&&"length"in e&&e.length,n=x(e);return!v(e)&&!y(e)&&("array"===n||0===t||"number"==typeof t&&0<t&&t-1 in e)}function fe(e,t){return e.nodeName&&e.nodeName.toLowerCase()===t.toLowerCase()}ce.fn=ce.prototype={jquery:t,constructor:ce,length:0,toArray:function(){return ae.call(this)},get:function(e){return null==e?ae.call(this):e<0?this[e+this.length]:this[e]},pushStack:function(e){var t=ce.merge(this.constructor(),e);return t.prevObject=this,t},each:function(e){return ce.each(this,e)},map:function(n){return this.pushStack(ce.map(this,function(e,t){return n.call(e,t,e)}))},slice:function(){return this.pushStack(ae.apply(this,arguments))},first:function(){return this.eq(0)},last:function(){return this.eq(-1)},even:function(){return this.pushStack(ce.grep(this,function(e,t){return(t+1)%2}))},odd:function(){return this.pushStack(ce.grep(this,function(e,t){return t%2}))},eq:function(e){var t=this.length,n=+e+(e<0?t:0);return this.pushStack(0<=n&&n<t?[this[n]]:[])},end:function(){return this.prevObject||this.constructor()},push:s,sort:oe.sort,splice:oe.splice},ce.extend=ce.fn.extend=function(){var e,t,n,r,i,o,a=arguments[0]||{},s=1,u=arguments.length,l=!1;for("boolean"==typeof a&&(l=a,a=arguments[s]||{},s++),"object"==typeof a||v(a)||(a={}),s===u&&(a=this,s--);s<u;s++)if(null!=(e=arguments[s]))for(t in e)r=e[t],"__proto__"!==t&&a!==r&&(l&&r&&(ce.isPlainObject(r)||(i=Array.isArray(r)))?(n=a[t],o=i&&!Array.isArray(n)?[]:i||ce.isPlainObject(n)?n:{},i=!1,a[t]=ce.extend(l,o,r)):void 0!==r&&(a[t]=r));return a},ce.extend({expando:"jQuery"+(t+Math.random()).replace(/\D/g,""),isReady:!0,error:function(e){throw new Error(e)},noop:function(){},isPlainObject:function(e){var t,n;return!(!e||"[object Object]"!==i.call(e))&&(!(t=r(e))||"function"==typeof(n=ue.call(t,"constructor")&&t.constructor)&&o.call(n)===a)},isEmptyObject:function(e){var t;for(t in e)return!1;return!0},globalEval:function(e,t,n){m(e,{nonce:t&&t.nonce},n)},each:function(e,t){var n,r=0;if(c(e)){for(n=e.length;r<n;r++)if(!1===t.call(e[r],r,e[r]))break}else for(r in e)if(!1===t.call(e[r],r,e[r]))break;return e},text:function(e){var t,n="",r=0,i=e.nodeType;if(!i)while(t=e[r++])n+=ce.text(t);return 1===i||11===i?e.textContent:9===i?e.documentElement.textContent:3===i||4===i?e.nodeValue:n},makeArray:function(e,t){var n=t||[];return null!=e&&(c(Object(e))?ce.merge(n,"string"==typeof e?[e]:e):s.call(n,e)),n},inArray:function(e,t,n){return null==t?-1:se.call(t,e,n)},isXMLDoc:function(e){var t=e&&e.namespaceURI,n=e&&(e.ownerDocument||e).documentElement;return!l.test(t||n&&n.nodeName||"HTML")},merge:function(e,t){for(var n=+t.length,r=0,i=e.length;r<n;r++)e[i++]=t[r];return e.length=i,e},grep:function(e,t,n){for(var r=[],i=0,o=e.length,a=!n;i<o;i++)!t(e[i],i)!==a&&r.push(e[i]);return r},map:function(e,t,n){var r,i,o=0,a=[];if(c(e))for(r=e.length;o<r;o++)null!=(i=t(e[o],o,n))&&a.push(i);else for(o in e)null!=(i=t(e[o],o,n))&&a.push(i);return g(a)},guid:1,support:le}),"function"==typeof Symbol&&(ce.fn[Symbol.iterator]=oe[Symbol.iterator]),ce.each("Boolean Number String Function Array Date RegExp Object Error Symbol".split(" "),function(e,t){n["[object "+t+"]"]=t.toLowerCase()});var pe=oe.pop,de=oe.sort,he=oe.splice,ge="[\\x20\\t\\r\\n\\f]",ve=new RegExp("^"+ge+"+|((?:^|[^\\\\])(?:\\\\.)*)"+ge+"+$","g");ce.contains=function(e,t){var n=t&&t.parentNode;return e===n||!(!n||1!==n.nodeType||!(e.contains?e.contains(n):e.compareDocumentPosition&&16&e.compareDocumentPosition(n)))};var f=/([\0-\x1f\x7f]|^-?\d)|^-$|[^\x80-\uFFFF\w-]/g;function p(e,t){return t?"\0"===e?"\ufffd":e.slice(0,-1)+"\\"+e.charCodeAt(e.length-1).toString(16)+" ":"\\"+e}ce.escapeSelector=function(e){return(e+"").replace(f,p)};var ye=C,me=s;!function(){var e,b,w,o,a,T,r,C,d,i,k=me,S=ce.expando,E=0,n=0,s=W(),c=W(),u=W(),h=W(),l=function(e,t){return e===t&&(a=!0),0},f="checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|ismap|loop|multiple|open|readonly|required|scoped",t="(?:\\\\[\\da-fA-F]{1,6}"+ge+"?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+",p="\\["+ge+"*("+t+")(?:"+ge+"*([*^$|!~]?=)"+ge+"*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|("+t+"))|)"+ge+"*\\]",g=":("+t+")(?:\\((('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|((?:\\\\.|[^\\\\()[\\]]|"+p+")*)|.*)\\)|)",v=new RegExp(ge+"+","g"),y=new RegExp("^"+ge+"*,"+ge+"*"),m=new RegExp("^"+ge+"*([>+~]|"+ge+")"+ge+"*"),x=new RegExp(ge+"|>"),j=new RegExp(g),A=new RegExp("^"+t+"$"),D={ID:new RegExp("^#("+t+")"),CLASS:new RegExp("^\\.("+t+")"),TAG:new RegExp("^("+t+"|[*])"),ATTR:new RegExp("^"+p),PSEUDO:new RegExp("^"+g),CHILD:new RegExp("^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\("+ge+"*(even|odd|(([+-]|)(\\d*)n|)"+ge+"*(?:([+-]|)"+ge+"*(\\d+)|))"+ge+"*\\)|)","i"),bool:new RegExp("^(?:"+f+")$","i"),needsContext:new RegExp("^"+ge+"*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\("+ge+"*((?:-\\d)?\\d*)"+ge+"*\\)|)(?=[^-]|$)","i")},N=/^(?:input|select|textarea|button)$/i,q=/^h\d$/i,L=/^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/,H=/[+~]/,O=new RegExp("\\\\[\\da-fA-F]{1,6}"+ge+"?|\\\\([^\\r\\n\\f])","g"),P=function(e,t){var n="0x"+e.slice(1)-65536;return t||(n<0?String.fromCharCode(n+65536):String.fromCharCode(n>>10|55296,1023&n|56320))},M=function(){V()},R=J(function(e){return!0===e.disabled&&fe(e,"fieldset")},{dir:"parentNode",next:"legend"});try{k.apply(oe=ae.call(ye.childNodes),ye.childNodes),oe[ye.childNodes.length].nodeType}catch(e){k={apply:function(e,t){me.apply(e,ae.call(t))},call:function(e){me.apply(e,ae.call(arguments,1))}}}function I(t,e,n,r){var i,o,a,s,u,l,c,f=e&&e.ownerDocument,p=e?e.nodeType:9;if(n=n||[],"string"!=typeof t||!t||1!==p&&9!==p&&11!==p)return n;if(!r&&(V(e),e=e||T,C)){if(11!==p&&(u=L.exec(t)))if(i=u[1]){if(9===p){if(!(a=e.getElementById(i)))return n;if(a.id===i)return k.call(n,a),n}else if(f&&(a=f.getElementById(i))&&I.contains(e,a)&&a.id===i)return k.call(n,a),n}else{if(u[2])return k.apply(n,e.getElementsByTagName(t)),n;if((i=u[3])&&e.getElementsByClassName)return k.apply(n,e.getElementsByClassName(i)),n}if(!(h[t+" "]||d&&d.test(t))){if(c=t,f=e,1===p&&(x.test(t)||m.test(t))){(f=H.test(t)&&U(e.parentNode)||e)==e&&le.scope||((s=e.getAttribute("id"))?s=ce.escapeSelector(s):e.setAttribute("id",s=S)),o=(l=Y(t)).length;while(o--)l[o]=(s?"#"+s:":scope")+" "+Q(l[o]);c=l.join(",")}try{return k.apply(n,f.querySelectorAll(c)),n}catch(e){h(t,!0)}finally{s===S&&e.removeAttribute("id")}}}return re(t.replace(ve,"$1"),e,n,r)}function W(){var r=[];return function e(t,n){return r.push(t+" ")>b.cacheLength&&delete e[r.shift()],e[t+" "]=n}}function F(e){return e[S]=!0,e}function $(e){var t=T.createElement("fieldset");try{return!!e(t)}catch(e){return!1}finally{t.parentNode&&t.parentNode.removeChild(t),t=null}}function B(t){return function(e){return fe(e,"input")&&e.type===t}}function _(t){return function(e){return(fe(e,"input")||fe(e,"button"))&&e.type===t}}function z(t){return function(e){return"form"in e?e.parentNode&&!1===e.disabled?"label"in e?"label"in e.parentNode?e.parentNode.disabled===t:e.disabled===t:e.isDisabled===t||e.isDisabled!==!t&&R(e)===t:e.disabled===t:"label"in e&&e.disabled===t}}function X(a){return F(function(o){return o=+o,F(function(e,t){var n,r=a([],e.length,o),i=r.length;while(i--)e[n=r[i]]&&(e[n]=!(t[n]=e[n]))})})}function U(e){return e&&"undefined"!=typeof e.getElementsByTagName&&e}function V(e){var t,n=e?e.ownerDocument||e:ye;return n!=T&&9===n.nodeType&&n.documentElement&&(r=(T=n).documentElement,C=!ce.isXMLDoc(T),i=r.matches||r.webkitMatchesSelector||r.msMatchesSelector,r.msMatchesSelector&&ye!=T&&(t=T.defaultView)&&t.top!==t&&t.addEventListener("unload",M),le.getById=$(function(e){return r.appendChild(e).id=ce.expando,!T.getElementsByName||!T.getElementsByName(ce.expando).length}),le.disconnectedMatch=$(function(e){return i.call(e,"*")}),le.scope=$(function(){return T.querySelectorAll(":scope")}),le.cssHas=$(function(){try{return T.querySelector(":has(*,:jqfake)"),!1}catch(e){return!0}}),le.getById?(b.filter.ID=function(e){var t=e.replace(O,P);return function(e){return e.getAttribute("id")===t}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&C){var n=t.getElementById(e);return n?[n]:[]}}):(b.filter.ID=function(e){var n=e.replace(O,P);return function(e){var t="undefined"!=typeof e.getAttributeNode&&e.getAttributeNode("id");return t&&t.value===n}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&C){var n,r,i,o=t.getElementById(e);if(o){if((n=o.getAttributeNode("id"))&&n.value===e)return[o];i=t.getElementsByName(e),r=0;while(o=i[r++])if((n=o.getAttributeNode("id"))&&n.value===e)return[o]}return[]}}),b.find.TAG=function(e,t){return"undefined"!=typeof t.getElementsByTagName?t.getElementsByTagName(e):t.querySelectorAll(e)},b.find.CLASS=function(e,t){if("undefined"!=typeof t.getElementsByClassName&&C)return t.getElementsByClassName(e)},d=[],$(function(e){var t;r.appendChild(e).innerHTML="<a id='"+S+"' href='' disabled='disabled'></a><select id='"+S+"-\r\\' disabled='disabled'><option selected=''></option></select>",e.querySelectorAll("[selected]").length||d.push("\\["+ge+"*(?:value|"+f+")"),e.querySelectorAll("[id~="+S+"-]").length||d.push("~="),e.querySelectorAll("a#"+S+"+*").length||d.push(".#.+[+~]"),e.querySelectorAll(":checked").length||d.push(":checked"),(t=T.createElement("input")).setAttribute("type","hidden"),e.appendChild(t).setAttribute("name","D"),r.appendChild(e).disabled=!0,2!==e.querySelectorAll(":disabled").length&&d.push(":enabled",":disabled"),(t=T.createElement("input")).setAttribute("name",""),e.appendChild(t),e.querySelectorAll("[name='']").length||d.push("\\["+ge+"*name"+ge+"*="+ge+"*(?:''|\"\")")}),le.cssHas||d.push(":has"),d=d.length&&new RegExp(d.join("|")),l=function(e,t){if(e===t)return a=!0,0;var n=!e.compareDocumentPosition-!t.compareDocumentPosition;return n||(1&(n=(e.ownerDocument||e)==(t.ownerDocument||t)?e.compareDocumentPosition(t):1)||!le.sortDetached&&t.compareDocumentPosition(e)===n?e===T||e.ownerDocument==ye&&I.contains(ye,e)?-1:t===T||t.ownerDocument==ye&&I.contains(ye,t)?1:o?se.call(o,e)-se.call(o,t):0:4&n?-1:1)}),T}for(e in I.matches=function(e,t){return I(e,null,null,t)},I.matchesSelector=function(e,t){if(V(e),C&&!h[t+" "]&&(!d||!d.test(t)))try{var n=i.call(e,t);if(n||le.disconnectedMatch||e.document&&11!==e.document.nodeType)return n}catch(e){h(t,!0)}return 0<I(t,T,null,[e]).length},I.contains=function(e,t){return(e.ownerDocument||e)!=T&&V(e),ce.contains(e,t)},I.attr=function(e,t){(e.ownerDocument||e)!=T&&V(e);var n=b.attrHandle[t.toLowerCase()],r=n&&ue.call(b.attrHandle,t.toLowerCase())?n(e,t,!C):void 0;return void 0!==r?r:e.getAttribute(t)},I.error=function(e){throw new Error("Syntax error, unrecognized expression: "+e)},ce.uniqueSort=function(e){var t,n=[],r=0,i=0;if(a=!le.sortStable,o=!le.sortStable&&ae.call(e,0),de.call(e,l),a){while(t=e[i++])t===e[i]&&(r=n.push(i));while(r--)he.call(e,n[r],1)}return o=null,e},ce.fn.uniqueSort=function(){return this.pushStack(ce.uniqueSort(ae.apply(this)))},(b=ce.expr={cacheLength:50,createPseudo:F,match:D,attrHandle:{},find:{},relative:{">":{dir:"parentNode",first:!0}," ":{dir:"parentNode"},"+":{dir:"previousSibling",first:!0},"~":{dir:"previousSibling"}},preFilter:{ATTR:function(e){return e[1]=e[1].replace(O,P),e[3]=(e[3]||e[4]||e[5]||"").replace(O,P),"~="===e[2]&&(e[3]=" "+e[3]+" "),e.slice(0,4)},CHILD:function(e){return e[1]=e[1].toLowerCase(),"nth"===e[1].slice(0,3)?(e[3]||I.error(e[0]),e[4]=+(e[4]?e[5]+(e[6]||1):2*("even"===e[3]||"odd"===e[3])),e[5]=+(e[7]+e[8]||"odd"===e[3])):e[3]&&I.error(e[0]),e},PSEUDO:function(e){var t,n=!e[6]&&e[2];return D.CHILD.test(e[0])?null:(e[3]?e[2]=e[4]||e[5]||"":n&&j.test(n)&&(t=Y(n,!0))&&(t=n.indexOf(")",n.length-t)-n.length)&&(e[0]=e[0].slice(0,t),e[2]=n.slice(0,t)),e.slice(0,3))}},filter:{TAG:function(e){var t=e.replace(O,P).toLowerCase();return"*"===e?function(){return!0}:function(e){return fe(e,t)}},CLASS:function(e){var t=s[e+" "];return t||(t=new RegExp("(^|"+ge+")"+e+"("+ge+"|$)"))&&s(e,function(e){return t.test("string"==typeof e.className&&e.className||"undefined"!=typeof e.getAttribute&&e.getAttribute("class")||"")})},ATTR:function(n,r,i){return function(e){var t=I.attr(e,n);return null==t?"!="===r:!r||(t+="","="===r?t===i:"!="===r?t!==i:"^="===r?i&&0===t.indexOf(i):"*="===r?i&&-1<t.indexOf(i):"$="===r?i&&t.slice(-i.length)===i:"~="===r?-1<(" "+t.replace(v," ")+" ").indexOf(i):"|="===r&&(t===i||t.slice(0,i.length+1)===i+"-"))}},CHILD:function(d,e,t,h,g){var v="nth"!==d.slice(0,3),y="last"!==d.slice(-4),m="of-type"===e;return 1===h&&0===g?function(e){return!!e.parentNode}:function(e,t,n){var r,i,o,a,s,u=v!==y?"nextSibling":"previousSibling",l=e.parentNode,c=m&&e.nodeName.toLowerCase(),f=!n&&!m,p=!1;if(l){if(v){while(u){o=e;while(o=o[u])if(m?fe(o,c):1===o.nodeType)return!1;s=u="only"===d&&!s&&"nextSibling"}return!0}if(s=[y?l.firstChild:l.lastChild],y&&f){p=(a=(r=(i=l[S]||(l[S]={}))[d]||[])[0]===E&&r[1])&&r[2],o=a&&l.childNodes[a];while(o=++a&&o&&o[u]||(p=a=0)||s.pop())if(1===o.nodeType&&++p&&o===e){i[d]=[E,a,p];break}}else if(f&&(p=a=(r=(i=e[S]||(e[S]={}))[d]||[])[0]===E&&r[1]),!1===p)while(o=++a&&o&&o[u]||(p=a=0)||s.pop())if((m?fe(o,c):1===o.nodeType)&&++p&&(f&&((i=o[S]||(o[S]={}))[d]=[E,p]),o===e))break;return(p-=g)===h||p%h==0&&0<=p/h}}},PSEUDO:function(e,o){var t,a=b.pseudos[e]||b.setFilters[e.toLowerCase()]||I.error("unsupported pseudo: "+e);return a[S]?a(o):1<a.length?(t=[e,e,"",o],b.setFilters.hasOwnProperty(e.toLowerCase())?F(function(e,t){var n,r=a(e,o),i=r.length;while(i--)e[n=se.call(e,r[i])]=!(t[n]=r[i])}):function(e){return a(e,0,t)}):a}},pseudos:{not:F(function(e){var r=[],i=[],s=ne(e.replace(ve,"$1"));return s[S]?F(function(e,t,n,r){var i,o=s(e,null,r,[]),a=e.length;while(a--)(i=o[a])&&(e[a]=!(t[a]=i))}):function(e,t,n){return r[0]=e,s(r,null,n,i),r[0]=null,!i.pop()}}),has:F(function(t){return function(e){return 0<I(t,e).length}}),contains:F(function(t){return t=t.replace(O,P),function(e){return-1<(e.textContent||ce.text(e)).indexOf(t)}}),lang:F(function(n){return A.test(n||"")||I.error("unsupported lang: "+n),n=n.replace(O,P).toLowerCase(),function(e){var t;do{if(t=C?e.lang:e.getAttribute("xml:lang")||e.getAttribute("lang"))return(t=t.toLowerCase())===n||0===t.indexOf(n+"-")}while((e=e.parentNode)&&1===e.nodeType);return!1}}),target:function(e){var t=ie.location&&ie.location.hash;return t&&t.slice(1)===e.id},root:function(e){return e===r},focus:function(e){return e===function(){try{return T.activeElement}catch(e){}}()&&T.hasFocus()&&!!(e.type||e.href||~e.tabIndex)},enabled:z(!1),disabled:z(!0),checked:function(e){return fe(e,"input")&&!!e.checked||fe(e,"option")&&!!e.selected},selected:function(e){return e.parentNode&&e.parentNode.selectedIndex,!0===e.selected},empty:function(e){for(e=e.firstChild;e;e=e.nextSibling)if(e.nodeType<6)return!1;return!0},parent:function(e){return!b.pseudos.empty(e)},header:function(e){return q.test(e.nodeName)},input:function(e){return N.test(e.nodeName)},button:function(e){return fe(e,"input")&&"button"===e.type||fe(e,"button")},text:function(e){var t;return fe(e,"input")&&"text"===e.type&&(null==(t=e.getAttribute("type"))||"text"===t.toLowerCase())},first:X(function(){return[0]}),last:X(function(e,t){return[t-1]}),eq:X(function(e,t,n){return[n<0?n+t:n]}),even:X(function(e,t){for(var n=0;n<t;n+=2)e.push(n);return e}),odd:X(function(e,t){for(var n=1;n<t;n+=2)e.push(n);return e}),lt:X(function(e,t,n){var r;for(r=n<0?n+t:t<n?t:n;0<=--r;)e.push(r);return e}),gt:X(function(e,t,n){for(var r=n<0?n+t:n;++r<t;)e.push(r);return e})}}).pseudos.nth=b.pseudos.eq,{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})b.pseudos[e]=B(e);for(e in{submit:!0,reset:!0})b.pseudos[e]=_(e);function G(){}function Y(e,t){var n,r,i,o,a,s,u,l=c[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=y.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=m.exec(a))&&(n=r.shift(),i.push({value:n,type:r[0].replace(ve," ")}),a=a.slice(n.length)),b.filter)!(r=D[o].exec(a))||u[o]&&!(r=u[o](r))||(n=r.shift(),i.push({value:n,type:o,matches:r}),a=a.slice(n.length));if(!n)break}return t?a.length:a?I.error(e):c(e,s).slice(0)}function Q(e){for(var t=0,n=e.length,r="";t<n;t++)r+=e[t].value;return r}function J(a,e,t){var s=e.dir,u=e.next,l=u||s,c=t&&"parentNode"===l,f=n++;return e.first?function(e,t,n){while(e=e[s])if(1===e.nodeType||c)return a(e,t,n);return!1}:function(e,t,n){var r,i,o=[E,f];if(n){while(e=e[s])if((1===e.nodeType||c)&&a(e,t,n))return!0}else while(e=e[s])if(1===e.nodeType||c)if(i=e[S]||(e[S]={}),u&&fe(e,u))e=e[s]||e;else{if((r=i[l])&&r[0]===E&&r[1]===f)return o[2]=r[2];if((i[l]=o)[2]=a(e,t,n))return!0}return!1}}function K(i){return 1<i.length?function(e,t,n){var r=i.length;while(r--)if(!i[r](e,t,n))return!1;return!0}:i[0]}function Z(e,t,n,r,i){for(var o,a=[],s=0,u=e.length,l=null!=t;s<u;s++)(o=e[s])&&(n&&!n(o,r,i)||(a.push(o),l&&t.push(s)));return a}function ee(d,h,g,v,y,e){return v&&!v[S]&&(v=ee(v)),y&&!y[S]&&(y=ee(y,e)),F(function(e,t,n,r){var i,o,a,s,u=[],l=[],c=t.length,f=e||function(e,t,n){for(var r=0,i=t.length;r<i;r++)I(e,t[r],n);return n}(h||"*",n.nodeType?[n]:n,[]),p=!d||!e&&h?f:Z(f,u,d,n,r);if(g?g(p,s=y||(e?d:c||v)?[]:t,n,r):s=p,v){i=Z(s,l),v(i,[],n,r),o=i.length;while(o--)(a=i[o])&&(s[l[o]]=!(p[l[o]]=a))}if(e){if(y||d){if(y){i=[],o=s.length;while(o--)(a=s[o])&&i.push(p[o]=a);y(null,s=[],i,r)}o=s.length;while(o--)(a=s[o])&&-1<(i=y?se.call(e,a):u[o])&&(e[i]=!(t[i]=a))}}else s=Z(s===t?s.splice(c,s.length):s),y?y(null,t,s,r):k.apply(t,s)})}function te(e){for(var i,t,n,r=e.length,o=b.relative[e[0].type],a=o||b.relative[" "],s=o?1:0,u=J(function(e){return e===i},a,!0),l=J(function(e){return-1<se.call(i,e)},a,!0),c=[function(e,t,n){var r=!o&&(n||t!=w)||((i=t).nodeType?u(e,t,n):l(e,t,n));return i=null,r}];s<r;s++)if(t=b.relative[e[s].type])c=[J(K(c),t)];else{if((t=b.filter[e[s].type].apply(null,e[s].matches))[S]){for(n=++s;n<r;n++)if(b.relative[e[n].type])break;return ee(1<s&&K(c),1<s&&Q(e.slice(0,s-1).concat({value:" "===e[s-2].type?"*":""})).replace(ve,"$1"),t,s<n&&te(e.slice(s,n)),n<r&&te(e=e.slice(n)),n<r&&Q(e))}c.push(t)}return K(c)}function ne(e,t){var n,v,y,m,x,r,i=[],o=[],a=u[e+" "];if(!a){t||(t=Y(e)),n=t.length;while(n--)(a=te(t[n]))[S]?i.push(a):o.push(a);(a=u(e,(v=o,m=0<(y=i).length,x=0<v.length,r=function(e,t,n,r,i){var o,a,s,u=0,l="0",c=e&&[],f=[],p=w,d=e||x&&b.find.TAG("*",i),h=E+=null==p?1:Math.random()||.1,g=d.length;for(i&&(w=t==T||t||i);l!==g&&null!=(o=d[l]);l++){if(x&&o){a=0,t||o.ownerDocument==T||(V(o),n=!C);while(s=v[a++])if(s(o,t||T,n)){k.call(r,o);break}i&&(E=h)}m&&((o=!s&&o)&&u--,e&&c.push(o))}if(u+=l,m&&l!==u){a=0;while(s=y[a++])s(c,f,t,n);if(e){if(0<u)while(l--)c[l]||f[l]||(f[l]=pe.call(r));f=Z(f)}k.apply(r,f),i&&!e&&0<f.length&&1<u+y.length&&ce.uniqueSort(r)}return i&&(E=h,w=p),c},m?F(r):r))).selector=e}return a}function re(e,t,n,r){var i,o,a,s,u,l="function"==typeof e&&e,c=!r&&Y(e=l.selector||e);if(n=n||[],1===c.length){if(2<(o=c[0]=c[0].slice(0)).length&&"ID"===(a=o[0]).type&&9===t.nodeType&&C&&b.relative[o[1].type]){if(!(t=(b.find.ID(a.matches[0].replace(O,P),t)||[])[0]))return n;l&&(t=t.parentNode),e=e.slice(o.shift().value.length)}i=D.needsContext.test(e)?0:o.length;while(i--){if(a=o[i],b.relative[s=a.type])break;if((u=b.find[s])&&(r=u(a.matches[0].replace(O,P),H.test(o[0].type)&&U(t.parentNode)||t))){if(o.splice(i,1),!(e=r.length&&Q(o)))return k.apply(n,r),n;break}}}return(l||ne(e,c))(r,t,!C,n,!t||H.test(e)&&U(t.parentNode)||t),n}G.prototype=b.filters=b.pseudos,b.setFilters=new G,le.sortStable=S.split("").sort(l).join("")===S,V(),le.sortDetached=$(function(e){return 1&e.compareDocumentPosition(T.createElement("fieldset"))}),ce.find=I,ce.expr[":"]=ce.expr.pseudos,ce.unique=ce.uniqueSort,I.compile=ne,I.select=re,I.setDocument=V,I.tokenize=Y,I.escape=ce.escapeSelector,I.getText=ce.text,I.isXML=ce.isXMLDoc,I.selectors=ce.expr,I.support=ce.support,I.uniqueSort=ce.uniqueSort}();var d=function(e,t,n){var r=[],i=void 0!==n;while((e=e[t])&&9!==e.nodeType)if(1===e.nodeType){if(i&&ce(e).is(n))break;r.push(e)}return r},h=function(e,t){for(var n=[];e;e=e.nextSibling)1===e.nodeType&&e!==t&&n.push(e);return n},b=ce.expr.match.needsContext,w=/^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i;function T(e,n,r){return v(n)?ce.grep(e,function(e,t){return!!n.call(e,t,e)!==r}):n.nodeType?ce.grep(e,function(e){return e===n!==r}):"string"!=typeof n?ce.grep(e,function(e){return-1<se.call(n,e)!==r}):ce.filter(n,e,r)}ce.filter=function(e,t,n){var r=t[0];return n&&(e=":not("+e+")"),1===t.length&&1===r.nodeType?ce.find.matchesSelector(r,e)?[r]:[]:ce.find.matches(e,ce.grep(t,function(e){return 1===e.nodeType}))},ce.fn.extend({find:function(e){var t,n,r=this.length,i=this;if("string"!=typeof e)return this.pushStack(ce(e).filter(function(){for(t=0;t<r;t++)if(ce.contains(i[t],this))return!0}));for(n=this.pushStack([]),t=0;t<r;t++)ce.find(e,i[t],n);return 1<r?ce.uniqueSort(n):n},filter:function(e){return this.pushStack(T(this,e||[],!1))},not:function(e){return this.pushStack(T(this,e||[],!0))},is:function(e){return!!T(this,"string"==typeof e&&b.test(e)?ce(e):e||[],!1).length}});var k,S=/^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/;(ce.fn.init=function(e,t,n){var r,i;if(!e)return this;if(n=n||k,"string"==typeof e){if(!(r="<"===e[0]&&">"===e[e.length-1]&&3<=e.length?[null,e,null]:S.exec(e))||!r[1]&&t)return!t||t.jquery?(t||n).find(e):this.constructor(t).find(e);if(r[1]){if(t=t instanceof ce?t[0]:t,ce.merge(this,ce.parseHTML(r[1],t&&t.nodeType?t.ownerDocument||t:C,!0)),w.test(r[1])&&ce.isPlainObject(t))for(r in t)v(this[r])?this[r](t[r]):this.attr(r,t[r]);return this}return(i=C.getElementById(r[2]))&&(this[0]=i,this.length=1),this}return e.nodeType?(this[0]=e,this.length=1,this):v(e)?void 0!==n.ready?n.ready(e):e(ce):ce.makeArray(e,this)}).prototype=ce.fn,k=ce(C);var E=/^(?:parents|prev(?:Until|All))/,j={children:!0,contents:!0,next:!0,prev:!0};function A(e,t){while((e=e[t])&&1!==e.nodeType);return e}ce.fn.extend({has:function(e){var t=ce(e,this),n=t.length;return this.filter(function(){for(var e=0;e<n;e++)if(ce.contains(this,t[e]))return!0})},closest:function(e,t){var n,r=0,i=this.length,o=[],a="string"!=typeof e&&ce(e);if(!b.test(e))for(;r<i;r++)for(n=this[r];n&&n!==t;n=n.parentNode)if(n.nodeType<11&&(a?-1<a.index(n):1===n.nodeType&&ce.find.matchesSelector(n,e))){o.push(n);break}return this.pushStack(1<o.length?ce.uniqueSort(o):o)},index:function(e){return e?"string"==typeof e?se.call(ce(e),this[0]):se.call(this,e.jquery?e[0]:e):this[0]&&this[0].parentNode?this.first().prevAll().length:-1},add:function(e,t){return this.pushStack(ce.uniqueSort(ce.merge(this.get(),ce(e,t))))},addBack:function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}}),ce.each({parent:function(e){var t=e.parentNode;return t&&11!==t.nodeType?t:null},parents:function(e){return d(e,"parentNode")},parentsUntil:function(e,t,n){return d(e,"parentNode",n)},next:function(e){return A(e,"nextSibling")},prev:function(e){return A(e,"previousSibling")},nextAll:function(e){return d(e,"nextSibling")},prevAll:function(e){return d(e,"previousSibling")},nextUntil:function(e,t,n){return d(e,"nextSibling",n)},prevUntil:function(e,t,n){return d(e,"previousSibling",n)},siblings:function(e){return h((e.parentNode||{}).firstChild,e)},children:function(e){return h(e.firstChild)},contents:function(e){return null!=e.contentDocument&&r(e.contentDocument)?e.contentDocument:(fe(e,"template")&&(e=e.content||e),ce.merge([],e.childNodes))}},function(r,i){ce.fn[r]=function(e,t){var n=ce.map(this,i,e);return"Until"!==r.slice(-5)&&(t=e),t&&"string"==typeof t&&(n=ce.filter(t,n)),1<this.length&&(j[r]||ce.uniqueSort(n),E.test(r)&&n.reverse()),this.pushStack(n)}});var D=/[^\x20\t\r\n\f]+/g;function N(e){return e}function q(e){throw e}function L(e,t,n,r){var i;try{e&&v(i=e.promise)?i.call(e).done(t).fail(n):e&&v(i=e.then)?i.call(e,t,n):t.apply(void 0,[e].slice(r))}catch(e){n.apply(void 0,[e])}}ce.Callbacks=function(r){var e,n;r="string"==typeof r?(e=r,n={},ce.each(e.match(D)||[],function(e,t){n[t]=!0}),n):ce.extend({},r);var i,t,o,a,s=[],u=[],l=-1,c=function(){for(a=a||r.once,o=i=!0;u.length;l=-1){t=u.shift();while(++l<s.length)!1===s[l].apply(t[0],t[1])&&r.stopOnFalse&&(l=s.length,t=!1)}r.memory||(t=!1),i=!1,a&&(s=t?[]:"")},f={add:function(){return s&&(t&&!i&&(l=s.length-1,u.push(t)),function n(e){ce.each(e,function(e,t){v(t)?r.unique&&f.has(t)||s.push(t):t&&t.length&&"string"!==x(t)&&n(t)})}(arguments),t&&!i&&c()),this},remove:function(){return ce.each(arguments,function(e,t){var n;while(-1<(n=ce.inArray(t,s,n)))s.splice(n,1),n<=l&&l--}),this},has:function(e){return e?-1<ce.inArray(e,s):0<s.length},empty:function(){return s&&(s=[]),this},disable:function(){return a=u=[],s=t="",this},disabled:function(){return!s},lock:function(){return a=u=[],t||i||(s=t=""),this},locked:function(){return!!a},fireWith:function(e,t){return a||(t=[e,(t=t||[]).slice?t.slice():t],u.push(t),i||c()),this},fire:function(){return f.fireWith(this,arguments),this},fired:function(){return!!o}};return f},ce.extend({Deferred:function(e){var o=[["notify","progress",ce.Callbacks("memory"),ce.Callbacks("memory"),2],["resolve","done",ce.Callbacks("once memory"),ce.Callbacks("once memory"),0,"resolved"],["reject","fail",ce.Callbacks("once memory"),ce.Callbacks("once memory"),1,"rejected"]],i="pending",a={state:function(){return i},always:function(){return s.done(arguments).fail(arguments),this},"catch":function(e){return a.then(null,e)},pipe:function(){var i=arguments;return ce.Deferred(function(r){ce.each(o,function(e,t){var n=v(i[t[4]])&&i[t[4]];s[t[1]](function(){var e=n&&n.apply(this,arguments);e&&v(e.promise)?e.promise().progress(r.notify).done(r.resolve).fail(r.reject):r[t[0]+"With"](this,n?[e]:arguments)})}),i=null}).promise()},then:function(t,n,r){var u=0;function l(i,o,a,s){return function(){var n=this,r=arguments,e=function(){var e,t;if(!(i<u)){if((e=a.apply(n,r))===o.promise())throw new TypeError("Thenable self-resolution");t=e&&("object"==typeof e||"function"==typeof e)&&e.then,v(t)?s?t.call(e,l(u,o,N,s),l(u,o,q,s)):(u++,t.call(e,l(u,o,N,s),l(u,o,q,s),l(u,o,N,o.notifyWith))):(a!==N&&(n=void 0,r=[e]),(s||o.resolveWith)(n,r))}},t=s?e:function(){try{e()}catch(e){ce.Deferred.exceptionHook&&ce.Deferred.exceptionHook(e,t.error),u<=i+1&&(a!==q&&(n=void 0,r=[e]),o.rejectWith(n,r))}};i?t():(ce.Deferred.getErrorHook?t.error=ce.Deferred.getErrorHook():ce.Deferred.getStackHook&&(t.error=ce.Deferred.getStackHook()),ie.setTimeout(t))}}return ce.Deferred(function(e){o[0][3].add(l(0,e,v(r)?r:N,e.notifyWith)),o[1][3].add(l(0,e,v(t)?t:N)),o[2][3].add(l(0,e,v(n)?n:q))}).promise()},promise:function(e){return null!=e?ce.extend(e,a):a}},s={};return ce.each(o,function(e,t){var n=t[2],r=t[5];a[t[1]]=n.add,r&&n.add(function(){i=r},o[3-e][2].disable,o[3-e][3].disable,o[0][2].lock,o[0][3].lock),n.add(t[3].fire),s[t[0]]=function(){return s[t[0]+"With"](this===s?void 0:this,arguments),this},s[t[0]+"With"]=n.fireWith}),a.promise(s),e&&e.call(s,s),s},when:function(e){var n=arguments.length,t=n,r=Array(t),i=ae.call(arguments),o=ce.Deferred(),a=function(t){return function(e){r[t]=this,i[t]=1<arguments.length?ae.call(arguments):e,--n||o.resolveWith(r,i)}};if(n<=1&&(L(e,o.done(a(t)).resolve,o.reject,!n),"pending"===o.state()||v(i[t]&&i[t].then)))return o.then();while(t--)L(i[t],a(t),o.reject);return o.promise()}});var H=/^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/;ce.Deferred.exceptionHook=function(e,t){ie.console&&ie.console.warn&&e&&H.test(e.name)&&ie.console.warn("jQuery.Deferred exception: "+e.message,e.stack,t)},ce.readyException=function(e){ie.setTimeout(function(){throw e})};var O=ce.Deferred();function P(){C.removeEventListener("DOMContentLoaded",P),ie.removeEventListener("load",P),ce.ready()}ce.fn.ready=function(e){return O.then(e)["catch"](function(e){ce.readyException(e)}),this},ce.extend({isReady:!1,readyWait:1,ready:function(e){(!0===e?--ce.readyWait:ce.isReady)||(ce.isReady=!0)!==e&&0<--ce.readyWait||O.resolveWith(C,[ce])}}),ce.ready.then=O.then,"complete"===C.readyState||"loading"!==C.readyState&&!C.documentElement.doScroll?ie.setTimeout(ce.ready):(C.addEventListener("DOMContentLoaded",P),ie.addEventListener("load",P));var M=function(e,t,n,r,i,o,a){var s=0,u=e.length,l=null==n;if("object"===x(n))for(s in i=!0,n)M(e,t,s,n[s],!0,o,a);else if(void 0!==r&&(i=!0,v(r)||(a=!0),l&&(a?(t.call(e,r),t=null):(l=t,t=function(e,t,n){return l.call(ce(e),n)})),t))for(;s<u;s++)t(e[s],n,a?r:r.call(e[s],s,t(e[s],n)));return i?e:l?t.call(e):u?t(e[0],n):o},R=/^-ms-/,I=/-([a-z])/g;function W(e,t){return t.toUpperCase()}function F(e){return e.replace(R,"ms-").replace(I,W)}var $=function(e){return 1===e.nodeType||9===e.nodeType||!+e.nodeType};function B(){this.expando=ce.expando+B.uid++}B.uid=1,B.prototype={cache:function(e){var t=e[this.expando];return t||(t={},$(e)&&(e.nodeType?e[this.expando]=t:Object.defineProperty(e,this.expando,{value:t,configurable:!0}))),t},set:function(e,t,n){var r,i=this.cache(e);if("string"==typeof t)i[F(t)]=n;else for(r in t)i[F(r)]=t[r];return i},get:function(e,t){return void 0===t?this.cache(e):e[this.expando]&&e[this.expando][F(t)]},access:function(e,t,n){return void 0===t||t&&"string"==typeof t&&void 0===n?this.get(e,t):(this.set(e,t,n),void 0!==n?n:t)},remove:function(e,t){var n,r=e[this.expando];if(void 0!==r){if(void 0!==t){n=(t=Array.isArray(t)?t.map(F):(t=F(t))in r?[t]:t.match(D)||[]).length;while(n--)delete r[t[n]]}(void 0===t||ce.isEmptyObject(r))&&(e.nodeType?e[this.expando]=void 0:delete e[this.expando])}},hasData:function(e){var t=e[this.expando];return void 0!==t&&!ce.isEmptyObject(t)}};var _=new B,z=new B,X=/^(?:\{[\w\W]*\}|\[[\w\W]*\])$/,U=/[A-Z]/g;function V(e,t,n){var r,i;if(void 0===n&&1===e.nodeType)if(r="data-"+t.replace(U,"-$&").toLowerCase(),"string"==typeof(n=e.getAttribute(r))){try{n="true"===(i=n)||"false"!==i&&("null"===i?null:i===+i+""?+i:X.test(i)?JSON.parse(i):i)}catch(e){}z.set(e,t,n)}else n=void 0;return n}ce.extend({hasData:function(e){return z.hasData(e)||_.hasData(e)},data:function(e,t,n){return z.access(e,t,n)},removeData:function(e,t){z.remove(e,t)},_data:function(e,t,n){return _.access(e,t,n)},_removeData:function(e,t){_.remove(e,t)}}),ce.fn.extend({data:function(n,e){var t,r,i,o=this[0],a=o&&o.attributes;if(void 0===n){if(this.length&&(i=z.get(o),1===o.nodeType&&!_.get(o,"hasDataAttrs"))){t=a.length;while(t--)a[t]&&0===(r=a[t].name).indexOf("data-")&&(r=F(r.slice(5)),V(o,r,i[r]));_.set(o,"hasDataAttrs",!0)}return i}return"object"==typeof n?this.each(function(){z.set(this,n)}):M(this,function(e){var t;if(o&&void 0===e)return void 0!==(t=z.get(o,n))?t:void 0!==(t=V(o,n))?t:void 0;this.each(function(){z.set(this,n,e)})},null,e,1<arguments.length,null,!0)},removeData:function(e){return this.each(function(){z.remove(this,e)})}}),ce.extend({queue:function(e,t,n){var r;if(e)return t=(t||"fx")+"queue",r=_.get(e,t),n&&(!r||Array.isArray(n)?r=_.access(e,t,ce.makeArray(n)):r.push(n)),r||[]},dequeue:function(e,t){t=t||"fx";var n=ce.queue(e,t),r=n.length,i=n.shift(),o=ce._queueHooks(e,t);"inprogress"===i&&(i=n.shift(),r--),i&&("fx"===t&&n.unshift("inprogress"),delete o.stop,i.call(e,function(){ce.dequeue(e,t)},o)),!r&&o&&o.empty.fire()},_queueHooks:function(e,t){var n=t+"queueHooks";return _.get(e,n)||_.access(e,n,{empty:ce.Callbacks("once memory").add(function(){_.remove(e,[t+"queue",n])})})}}),ce.fn.extend({queue:function(t,n){var e=2;return"string"!=typeof t&&(n=t,t="fx",e--),arguments.length<e?ce.queue(this[0],t):void 0===n?this:this.each(function(){var e=ce.queue(this,t,n);ce._queueHooks(this,t),"fx"===t&&"inprogress"!==e[0]&&ce.dequeue(this,t)})},dequeue:function(e){return this.each(function(){ce.dequeue(this,e)})},clearQueue:function(e){return this.queue(e||"fx",[])},promise:function(e,t){var n,r=1,i=ce.Deferred(),o=this,a=this.length,s=function(){--r||i.resolveWith(o,[o])};"string"!=typeof e&&(t=e,e=void 0),e=e||"fx";while(a--)(n=_.get(o[a],e+"queueHooks"))&&n.empty&&(r++,n.empty.add(s));return s(),i.promise(t)}});var G=/[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/.source,Y=new RegExp("^(?:([+-])=|)("+G+")([a-z%]*)$","i"),Q=["Top","Right","Bottom","Left"],J=C.documentElement,K=function(e){return ce.contains(e.ownerDocument,e)},Z={composed:!0};J.getRootNode&&(K=function(e){return ce.contains(e.ownerDocument,e)||e.getRootNode(Z)===e.ownerDocument});var ee=function(e,t){return"none"===(e=t||e).style.display||""===e.style.display&&K(e)&&"none"===ce.css(e,"display")};function te(e,t,n,r){var i,o,a=20,s=r?function(){return r.cur()}:function(){return ce.css(e,t,"")},u=s(),l=n&&n[3]||(ce.cssNumber[t]?"":"px"),c=e.nodeType&&(ce.cssNumber[t]||"px"!==l&&+u)&&Y.exec(ce.css(e,t));if(c&&c[3]!==l){u/=2,l=l||c[3],c=+u||1;while(a--)ce.style(e,t,c+l),(1-o)*(1-(o=s()/u||.5))<=0&&(a=0),c/=o;c*=2,ce.style(e,t,c+l),n=n||[]}return n&&(c=+c||+u||0,i=n[1]?c+(n[1]+1)*n[2]:+n[2],r&&(r.unit=l,r.start=c,r.end=i)),i}var ne={};function re(e,t){for(var n,r,i,o,a,s,u,l=[],c=0,f=e.length;c<f;c++)(r=e[c]).style&&(n=r.style.display,t?("none"===n&&(l[c]=_.get(r,"display")||null,l[c]||(r.style.display="")),""===r.style.display&&ee(r)&&(l[c]=(u=a=o=void 0,a=(i=r).ownerDocument,s=i.nodeName,(u=ne[s])||(o=a.body.appendChild(a.createElement(s)),u=ce.css(o,"display"),o.parentNode.removeChild(o),"none"===u&&(u="block"),ne[s]=u)))):"none"!==n&&(l[c]="none",_.set(r,"display",n)));for(c=0;c<f;c++)null!=l[c]&&(e[c].style.display=l[c]);return e}ce.fn.extend({show:function(){return re(this,!0)},hide:function(){return re(this)},toggle:function(e){return"boolean"==typeof e?e?this.show():this.hide():this.each(function(){ee(this)?ce(this).show():ce(this).hide()})}});var xe,be,we=/^(?:checkbox|radio)$/i,Te=/<([a-z][^\/\0>\x20\t\r\n\f]*)/i,Ce=/^$|^module$|\/(?:java|ecma)script/i;xe=C.createDocumentFragment().appendChild(C.createElement("div")),(be=C.createElement("input")).setAttribute("type","radio"),be.setAttribute("checked","checked"),be.setAttribute("name","t"),xe.appendChild(be),le.checkClone=xe.cloneNode(!0).cloneNode(!0).lastChild.checked,xe.innerHTML="<textarea>x</textarea>",le.noCloneChecked=!!xe.cloneNode(!0).lastChild.defaultValue,xe.innerHTML="<option></option>",le.option=!!xe.lastChild;var ke={thead:[1,"<table>","</table>"],col:[2,"<table><colgroup>","</colgroup></table>"],tr:[2,"<table><tbody>","</tbody></table>"],td:[3,"<table><tbody><tr>","</tr></tbody></table>"],_default:[0,"",""]};function Se(e,t){var n;return n="undefined"!=typeof e.getElementsByTagName?e.getElementsByTagName(t||"*"):"undefined"!=typeof e.querySelectorAll?e.querySelectorAll(t||"*"):[],void 0===t||t&&fe(e,t)?ce.merge([e],n):n}function Ee(e,t){for(var n=0,r=e.length;n<r;n++)_.set(e[n],"globalEval",!t||_.get(t[n],"globalEval"))}ke.tbody=ke.tfoot=ke.colgroup=ke.caption=ke.thead,ke.th=ke.td,le.option||(ke.optgroup=ke.option=[1,"<select multiple='multiple'>","</select>"]);var je=/<|&#?\w+;/;function Ae(e,t,n,r,i){for(var o,a,s,u,l,c,f=t.createDocumentFragment(),p=[],d=0,h=e.length;d<h;d++)if((o=e[d])||0===o)if("object"===x(o))ce.merge(p,o.nodeType?[o]:o);else if(je.test(o)){a=a||f.appendChild(t.createElement("div")),s=(Te.exec(o)||["",""])[1].toLowerCase(),u=ke[s]||ke._default,a.innerHTML=u[1]+ce.htmlPrefilter(o)+u[2],c=u[0];while(c--)a=a.lastChild;ce.merge(p,a.childNodes),(a=f.firstChild).textContent=""}else p.push(t.createTextNode(o));f.textContent="",d=0;while(o=p[d++])if(r&&-1<ce.inArray(o,r))i&&i.push(o);else if(l=K(o),a=Se(f.appendChild(o),"script"),l&&Ee(a),n){c=0;while(o=a[c++])Ce.test(o.type||"")&&n.push(o)}return f}var De=/^([^.]*)(?:\.(.+)|)/;function Ne(){return!0}function qe(){return!1}function Le(e,t,n,r,i,o){var a,s;if("object"==typeof t){for(s in"string"!=typeof n&&(r=r||n,n=void 0),t)Le(e,s,n,r,t[s],o);return e}if(null==r&&null==i?(i=n,r=n=void 0):null==i&&("string"==typeof n?(i=r,r=void 0):(i=r,r=n,n=void 0)),!1===i)i=qe;else if(!i)return e;return 1===o&&(a=i,(i=function(e){return ce().off(e),a.apply(this,arguments)}).guid=a.guid||(a.guid=ce.guid++)),e.each(function(){ce.event.add(this,t,i,r,n)})}function He(e,r,t){t?(_.set(e,r,!1),ce.event.add(e,r,{namespace:!1,handler:function(e){var t,n=_.get(this,r);if(1&e.isTrigger&&this[r]){if(n)(ce.event.special[r]||{}).delegateType&&e.stopPropagation();else if(n=ae.call(arguments),_.set(this,r,n),this[r](),t=_.get(this,r),_.set(this,r,!1),n!==t)return e.stopImmediatePropagation(),e.preventDefault(),t}else n&&(_.set(this,r,ce.event.trigger(n[0],n.slice(1),this)),e.stopPropagation(),e.isImmediatePropagationStopped=Ne)}})):void 0===_.get(e,r)&&ce.event.add(e,r,Ne)}ce.event={global:{},add:function(t,e,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=_.get(t);if($(t)){n.handler&&(n=(o=n).handler,i=o.selector),i&&ce.find.matchesSelector(J,i),n.guid||(n.guid=ce.guid++),(u=v.events)||(u=v.events=Object.create(null)),(a=v.handle)||(a=v.handle=function(e){return"undefined"!=typeof ce&&ce.event.triggered!==e.type?ce.event.dispatch.apply(t,arguments):void 0}),l=(e=(e||"").match(D)||[""]).length;while(l--)d=g=(s=De.exec(e[l])||[])[1],h=(s[2]||"").split(".").sort(),d&&(f=ce.event.special[d]||{},d=(i?f.delegateType:f.bindType)||d,f=ce.event.special[d]||{},c=ce.extend({type:d,origType:g,data:r,handler:n,guid:n.guid,selector:i,needsContext:i&&ce.expr.match.needsContext.test(i),namespace:h.join(".")},o),(p=u[d])||((p=u[d]=[]).delegateCount=0,f.setup&&!1!==f.setup.call(t,r,h,a)||t.addEventListener&&t.addEventListener(d,a)),f.add&&(f.add.call(t,c),c.handler.guid||(c.handler.guid=n.guid)),i?p.splice(p.delegateCount++,0,c):p.push(c),ce.event.global[d]=!0)}},remove:function(e,t,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=_.hasData(e)&&_.get(e);if(v&&(u=v.events)){l=(t=(t||"").match(D)||[""]).length;while(l--)if(d=g=(s=De.exec(t[l])||[])[1],h=(s[2]||"").split(".").sort(),d){f=ce.event.special[d]||{},p=u[d=(r?f.delegateType:f.bindType)||d]||[],s=s[2]&&new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"),a=o=p.length;while(o--)c=p[o],!i&&g!==c.origType||n&&n.guid!==c.guid||s&&!s.test(c.namespace)||r&&r!==c.selector&&("**"!==r||!c.selector)||(p.splice(o,1),c.selector&&p.delegateCount--,f.remove&&f.remove.call(e,c));a&&!p.length&&(f.teardown&&!1!==f.teardown.call(e,h,v.handle)||ce.removeEvent(e,d,v.handle),delete u[d])}else for(d in u)ce.event.remove(e,d+t[l],n,r,!0);ce.isEmptyObject(u)&&_.remove(e,"handle events")}},dispatch:function(e){var t,n,r,i,o,a,s=new Array(arguments.length),u=ce.event.fix(e),l=(_.get(this,"events")||Object.create(null))[u.type]||[],c=ce.event.special[u.type]||{};for(s[0]=u,t=1;t<arguments.length;t++)s[t]=arguments[t];if(u.delegateTarget=this,!c.preDispatch||!1!==c.preDispatch.call(this,u)){a=ce.event.handlers.call(this,u,l),t=0;while((i=a[t++])&&!u.isPropagationStopped()){u.currentTarget=i.elem,n=0;while((o=i.handlers[n++])&&!u.isImmediatePropagationStopped())u.rnamespace&&!1!==o.namespace&&!u.rnamespace.test(o.namespace)||(u.handleObj=o,u.data=o.data,void 0!==(r=((ce.event.special[o.origType]||{}).handle||o.handler).apply(i.elem,s))&&!1===(u.result=r)&&(u.preventDefault(),u.stopPropagation()))}return c.postDispatch&&c.postDispatch.call(this,u),u.result}},handlers:function(e,t){var n,r,i,o,a,s=[],u=t.delegateCount,l=e.target;if(u&&l.nodeType&&!("click"===e.type&&1<=e.button))for(;l!==this;l=l.parentNode||this)if(1===l.nodeType&&("click"!==e.type||!0!==l.disabled)){for(o=[],a={},n=0;n<u;n++)void 0===a[i=(r=t[n]).selector+" "]&&(a[i]=r.needsContext?-1<ce(i,this).index(l):ce.find(i,this,null,[l]).length),a[i]&&o.push(r);o.length&&s.push({elem:l,handlers:o})}return l=this,u<t.length&&s.push({elem:l,handlers:t.slice(u)}),s},addProp:function(t,e){Object.defineProperty(ce.Event.prototype,t,{enumerable:!0,configurable:!0,get:v(e)?function(){if(this.originalEvent)return e(this.originalEvent)}:function(){if(this.originalEvent)return this.originalEvent[t]},set:function(e){Object.defineProperty(this,t,{enumerable:!0,configurable:!0,writable:!0,value:e})}})},fix:function(e){return e[ce.expando]?e:new ce.Event(e)},special:{load:{noBubble:!0},click:{setup:function(e){var t=this||e;return we.test(t.type)&&t.click&&fe(t,"input")&&He(t,"click",!0),!1},trigger:function(e){var t=this||e;return we.test(t.type)&&t.click&&fe(t,"input")&&He(t,"click"),!0},_default:function(e){var t=e.target;return we.test(t.type)&&t.click&&fe(t,"input")&&_.get(t,"click")||fe(t,"a")}},beforeunload:{postDispatch:function(e){void 0!==e.result&&e.originalEvent&&(e.originalEvent.returnValue=e.result)}}}},ce.removeEvent=function(e,t,n){e.removeEventListener&&e.removeEventListener(t,n)},ce.Event=function(e,t){if(!(this instanceof ce.Event))return new ce.Event(e,t);e&&e.type?(this.originalEvent=e,this.type=e.type,this.isDefaultPrevented=e.defaultPrevented||void 0===e.defaultPrevented&&!1===e.returnValue?Ne:qe,this.target=e.target&&3===e.target.nodeType?e.target.parentNode:e.target,this.currentTarget=e.currentTarget,this.relatedTarget=e.relatedTarget):this.type=e,t&&ce.extend(this,t),this.timeStamp=e&&e.timeStamp||Date.now(),this[ce.expando]=!0},ce.Event.prototype={constructor:ce.Event,isDefaultPrevented:qe,isPropagationStopped:qe,isImmediatePropagationStopped:qe,isSimulated:!1,preventDefault:function(){var e=this.originalEvent;this.isDefaultPrevented=Ne,e&&!this.isSimulated&&e.preventDefault()},stopPropagation:function(){var e=this.originalEvent;this.isPropagationStopped=Ne,e&&!this.isSimulated&&e.stopPropagation()},stopImmediatePropagation:function(){var e=this.originalEvent;this.isImmediatePropagationStopped=Ne,e&&!this.isSimulated&&e.stopImmediatePropagation(),this.stopPropagation()}},ce.each({altKey:!0,bubbles:!0,cancelable:!0,changedTouches:!0,ctrlKey:!0,detail:!0,eventPhase:!0,metaKey:!0,pageX:!0,pageY:!0,shiftKey:!0,view:!0,"char":!0,code:!0,charCode:!0,key:!0,keyCode:!0,button:!0,buttons:!0,clientX:!0,clientY:!0,offsetX:!0,offsetY:!0,pointerId:!0,pointerType:!0,screenX:!0,screenY:!0,targetTouches:!0,toElement:!0,touches:!0,which:!0},ce.event.addProp),ce.each({focus:"focusin",blur:"focusout"},function(r,i){function o(e){if(C.documentMode){var t=_.get(this,"handle"),n=ce.event.fix(e);n.type="focusin"===e.type?"focus":"blur",n.isSimulated=!0,t(e),n.target===n.currentTarget&&t(n)}else ce.event.simulate(i,e.target,ce.event.fix(e))}ce.event.special[r]={setup:function(){var e;if(He(this,r,!0),!C.documentMode)return!1;(e=_.get(this,i))||this.addEventListener(i,o),_.set(this,i,(e||0)+1)},trigger:function(){return He(this,r),!0},teardown:function(){var e;if(!C.documentMode)return!1;(e=_.get(this,i)-1)?_.set(this,i,e):(this.removeEventListener(i,o),_.remove(this,i))},_default:function(e){return _.get(e.target,r)},delegateType:i},ce.event.special[i]={setup:function(){var e=this.ownerDocument||this.document||this,t=C.documentMode?this:e,n=_.get(t,i);n||(C.documentMode?this.addEventListener(i,o):e.addEventListener(r,o,!0)),_.set(t,i,(n||0)+1)},teardown:function(){var e=this.ownerDocument||this.document||this,t=C.documentMode?this:e,n=_.get(t,i)-1;n?_.set(t,i,n):(C.documentMode?this.removeEventListener(i,o):e.removeEventListener(r,o,!0),_.remove(t,i))}}}),ce.each({mouseenter:"mouseover",mouseleave:"mouseout",pointerenter:"pointerover",pointerleave:"pointerout"},function(e,i){ce.event.special[e]={delegateType:i,bindType:i,handle:function(e){var t,n=e.relatedTarget,r=e.handleObj;return n&&(n===this||ce.contains(this,n))||(e.type=r.origType,t=r.handler.apply(this,arguments),e.type=i),t}}}),ce.fn.extend({on:function(e,t,n,r){return Le(this,e,t,n,r)},one:function(e,t,n,r){return Le(this,e,t,n,r,1)},off:function(e,t,n){var r,i;if(e&&e.preventDefault&&e.handleObj)return r=e.handleObj,ce(e.delegateTarget).off(r.namespace?r.origType+"."+r.namespace:r.origType,r.selector,r.handler),this;if("object"==typeof e){for(i in e)this.off(i,t,e[i]);return this}return!1!==t&&"function"!=typeof t||(n=t,t=void 0),!1===n&&(n=qe),this.each(function(){ce.event.remove(this,e,n,t)})}});var Oe=/<script|<style|<link/i,Pe=/checked\s*(?:[^=]|=\s*.checked.)/i,Me=/^\s*<!\[CDATA\[|\]\]>\s*$/g;function Re(e,t){return fe(e,"table")&&fe(11!==t.nodeType?t:t.firstChild,"tr")&&ce(e).children("tbody")[0]||e}function Ie(e){return e.type=(null!==e.getAttribute("type"))+"/"+e.type,e}function We(e){return"true/"===(e.type||"").slice(0,5)?e.type=e.type.slice(5):e.removeAttribute("type"),e}function Fe(e,t){var n,r,i,o,a,s;if(1===t.nodeType){if(_.hasData(e)&&(s=_.get(e).events))for(i in _.remove(t,"handle events"),s)for(n=0,r=s[i].length;n<r;n++)ce.event.add(t,i,s[i][n]);z.hasData(e)&&(o=z.access(e),a=ce.extend({},o),z.set(t,a))}}function $e(n,r,i,o){r=g(r);var e,t,a,s,u,l,c=0,f=n.length,p=f-1,d=r[0],h=v(d);if(h||1<f&&"string"==typeof d&&!le.checkClone&&Pe.test(d))return n.each(function(e){var t=n.eq(e);h&&(r[0]=d.call(this,e,t.html())),$e(t,r,i,o)});if(f&&(t=(e=Ae(r,n[0].ownerDocument,!1,n,o)).firstChild,1===e.childNodes.length&&(e=t),t||o)){for(s=(a=ce.map(Se(e,"script"),Ie)).length;c<f;c++)u=e,c!==p&&(u=ce.clone(u,!0,!0),s&&ce.merge(a,Se(u,"script"))),i.call(n[c],u,c);if(s)for(l=a[a.length-1].ownerDocument,ce.map(a,We),c=0;c<s;c++)u=a[c],Ce.test(u.type||"")&&!_.access(u,"globalEval")&&ce.contains(l,u)&&(u.src&&"module"!==(u.type||"").toLowerCase()?ce._evalUrl&&!u.noModule&&ce._evalUrl(u.src,{nonce:u.nonce||u.getAttribute("nonce")},l):m(u.textContent.replace(Me,""),u,l))}return n}function Be(e,t,n){for(var r,i=t?ce.filter(t,e):e,o=0;null!=(r=i[o]);o++)n||1!==r.nodeType||ce.cleanData(Se(r)),r.parentNode&&(n&&K(r)&&Ee(Se(r,"script")),r.parentNode.removeChild(r));return e}ce.extend({htmlPrefilter:function(e){return e},clone:function(e,t,n){var r,i,o,a,s,u,l,c=e.cloneNode(!0),f=K(e);if(!(le.noCloneChecked||1!==e.nodeType&&11!==e.nodeType||ce.isXMLDoc(e)))for(a=Se(c),r=0,i=(o=Se(e)).length;r<i;r++)s=o[r],u=a[r],void 0,"input"===(l=u.nodeName.toLowerCase())&&we.test(s.type)?u.checked=s.checked:"input"!==l&&"textarea"!==l||(u.defaultValue=s.defaultValue);if(t)if(n)for(o=o||Se(e),a=a||Se(c),r=0,i=o.length;r<i;r++)Fe(o[r],a[r]);else Fe(e,c);return 0<(a=Se(c,"script")).length&&Ee(a,!f&&Se(e,"script")),c},cleanData:function(e){for(var t,n,r,i=ce.event.special,o=0;void 0!==(n=e[o]);o++)if($(n)){if(t=n[_.expando]){if(t.events)for(r in t.events)i[r]?ce.event.remove(n,r):ce.removeEvent(n,r,t.handle);n[_.expando]=void 0}n[z.expando]&&(n[z.expando]=void 0)}}}),ce.fn.extend({detach:function(e){return Be(this,e,!0)},remove:function(e){return Be(this,e)},text:function(e){return M(this,function(e){return void 0===e?ce.text(this):this.empty().each(function(){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||(this.textContent=e)})},null,e,arguments.length)},append:function(){return $e(this,arguments,function(e){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||Re(this,e).appendChild(e)})},prepend:function(){return $e(this,arguments,function(e){if(1===this.nodeType||11===this.nodeType||9===this.nodeType){var t=Re(this,e);t.insertBefore(e,t.firstChild)}})},before:function(){return $e(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this)})},after:function(){return $e(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this.nextSibling)})},empty:function(){for(var e,t=0;null!=(e=this[t]);t++)1===e.nodeType&&(ce.cleanData(Se(e,!1)),e.textContent="");return this},clone:function(e,t){return e=null!=e&&e,t=null==t?e:t,this.map(function(){return ce.clone(this,e,t)})},html:function(e){return M(this,function(e){var t=this[0]||{},n=0,r=this.length;if(void 0===e&&1===t.nodeType)return t.innerHTML;if("string"==typeof e&&!Oe.test(e)&&!ke[(Te.exec(e)||["",""])[1].toLowerCase()]){e=ce.htmlPrefilter(e);try{for(;n<r;n++)1===(t=this[n]||{}).nodeType&&(ce.cleanData(Se(t,!1)),t.innerHTML=e);t=0}catch(e){}}t&&this.empty().append(e)},null,e,arguments.length)},replaceWith:function(){var n=[];return $e(this,arguments,function(e){var t=this.parentNode;ce.inArray(this,n)<0&&(ce.cleanData(Se(this)),t&&t.replaceChild(e,this))},n)}}),ce.each({appendTo:"append",prependTo:"prepend",insertBefore:"before",insertAfter:"after",replaceAll:"replaceWith"},function(e,a){ce.fn[e]=function(e){for(var t,n=[],r=ce(e),i=r.length-1,o=0;o<=i;o++)t=o===i?this:this.clone(!0),ce(r[o])[a](t),s.apply(n,t.get());return this.pushStack(n)}});var _e=new RegExp("^("+G+")(?!px)[a-z%]+$","i"),ze=/^--/,Xe=function(e){var t=e.ownerDocument.defaultView;return t&&t.opener||(t=ie),t.getComputedStyle(e)},Ue=function(e,t,n){var r,i,o={};for(i in t)o[i]=e.style[i],e.style[i]=t[i];for(i in r=n.call(e),t)e.style[i]=o[i];return r},Ve=new RegExp(Q.join("|"),"i");function Ge(e,t,n){var r,i,o,a,s=ze.test(t),u=e.style;return(n=n||Xe(e))&&(a=n.getPropertyValue(t)||n[t],s&&a&&(a=a.replace(ve,"$1")||void 0),""!==a||K(e)||(a=ce.style(e,t)),!le.pixelBoxStyles()&&_e.test(a)&&Ve.test(t)&&(r=u.width,i=u.minWidth,o=u.maxWidth,u.minWidth=u.maxWidth=u.width=a,a=n.width,u.width=r,u.minWidth=i,u.maxWidth=o)),void 0!==a?a+"":a}function Ye(e,t){return{get:function(){if(!e())return(this.get=t).apply(this,arguments);delete this.get}}}!function(){function e(){if(l){u.style.cssText="position:absolute;left:-11111px;width:60px;margin-top:1px;padding:0;border:0",l.style.cssText="position:relative;display:block;box-sizing:border-box;overflow:scroll;margin:auto;border:1px;padding:1px;width:60%;top:1%",J.appendChild(u).appendChild(l);var e=ie.getComputedStyle(l);n="1%"!==e.top,s=12===t(e.marginLeft),l.style.right="60%",o=36===t(e.right),r=36===t(e.width),l.style.position="absolute",i=12===t(l.offsetWidth/3),J.removeChild(u),l=null}}function t(e){return Math.round(parseFloat(e))}var n,r,i,o,a,s,u=C.createElement("div"),l=C.createElement("div");l.style&&(l.style.backgroundClip="content-box",l.cloneNode(!0).style.backgroundClip="",le.clearCloneStyle="content-box"===l.style.backgroundClip,ce.extend(le,{boxSizingReliable:function(){return e(),r},pixelBoxStyles:function(){return e(),o},pixelPosition:function(){return e(),n},reliableMarginLeft:function(){return e(),s},scrollboxSize:function(){return e(),i},reliableTrDimensions:function(){var e,t,n,r;return null==a&&(e=C.createElement("table"),t=C.createElement("tr"),n=C.createElement("div"),e.style.cssText="position:absolute;left:-11111px;border-collapse:separate",t.style.cssText="box-sizing:content-box;border:1px solid",t.style.height="1px",n.style.height="9px",n.style.display="block",J.appendChild(e).appendChild(t).appendChild(n),r=ie.getComputedStyle(t),a=parseInt(r.height,10)+parseInt(r.borderTopWidth,10)+parseInt(r.borderBottomWidth,10)===t.offsetHeight,J.removeChild(e)),a}}))}();var Qe=["Webkit","Moz","ms"],Je=C.createElement("div").style,Ke={};function Ze(e){var t=ce.cssProps[e]||Ke[e];return t||(e in Je?e:Ke[e]=function(e){var t=e[0].toUpperCase()+e.slice(1),n=Qe.length;while(n--)if((e=Qe[n]+t)in Je)return e}(e)||e)}var et=/^(none|table(?!-c[ea]).+)/,tt={position:"absolute",visibility:"hidden",display:"block"},nt={letterSpacing:"0",fontWeight:"400"};function rt(e,t,n){var r=Y.exec(t);return r?Math.max(0,r[2]-(n||0))+(r[3]||"px"):t}function it(e,t,n,r,i,o){var a="width"===t?1:0,s=0,u=0,l=0;if(n===(r?"border":"content"))return 0;for(;a<4;a+=2)"margin"===n&&(l+=ce.css(e,n+Q[a],!0,i)),r?("content"===n&&(u-=ce.css(e,"padding"+Q[a],!0,i)),"margin"!==n&&(u-=ce.css(e,"border"+Q[a]+"Width",!0,i))):(u+=ce.css(e,"padding"+Q[a],!0,i),"padding"!==n?u+=ce.css(e,"border"+Q[a]+"Width",!0,i):s+=ce.css(e,"border"+Q[a]+"Width",!0,i));return!r&&0<=o&&(u+=Math.max(0,Math.ceil(e["offset"+t[0].toUpperCase()+t.slice(1)]-o-u-s-.5))||0),u+l}function ot(e,t,n){var r=Xe(e),i=(!le.boxSizingReliable()||n)&&"border-box"===ce.css(e,"boxSizing",!1,r),o=i,a=Ge(e,t,r),s="offset"+t[0].toUpperCase()+t.slice(1);if(_e.test(a)){if(!n)return a;a="auto"}return(!le.boxSizingReliable()&&i||!le.reliableTrDimensions()&&fe(e,"tr")||"auto"===a||!parseFloat(a)&&"inline"===ce.css(e,"display",!1,r))&&e.getClientRects().length&&(i="border-box"===ce.css(e,"boxSizing",!1,r),(o=s in e)&&(a=e[s])),(a=parseFloat(a)||0)+it(e,t,n||(i?"border":"content"),o,r,a)+"px"}function at(e,t,n,r,i){return new at.prototype.init(e,t,n,r,i)}ce.extend({cssHooks:{opacity:{get:function(e,t){if(t){var n=Ge(e,"opacity");return""===n?"1":n}}}},cssNumber:{animationIterationCount:!0,aspectRatio:!0,borderImageSlice:!0,columnCount:!0,flexGrow:!0,flexShrink:!0,fontWeight:!0,gridArea:!0,gridColumn:!0,gridColumnEnd:!0,gridColumnStart:!0,gridRow:!0,gridRowEnd:!0,gridRowStart:!0,lineHeight:!0,opacity:!0,order:!0,orphans:!0,scale:!0,widows:!0,zIndex:!0,zoom:!0,fillOpacity:!0,floodOpacity:!0,stopOpacity:!0,strokeMiterlimit:!0,strokeOpacity:!0},cssProps:{},style:function(e,t,n,r){if(e&&3!==e.nodeType&&8!==e.nodeType&&e.style){var i,o,a,s=F(t),u=ze.test(t),l=e.style;if(u||(t=Ze(s)),a=ce.cssHooks[t]||ce.cssHooks[s],void 0===n)return a&&"get"in a&&void 0!==(i=a.get(e,!1,r))?i:l[t];"string"===(o=typeof n)&&(i=Y.exec(n))&&i[1]&&(n=te(e,t,i),o="number"),null!=n&&n==n&&("number"!==o||u||(n+=i&&i[3]||(ce.cssNumber[s]?"":"px")),le.clearCloneStyle||""!==n||0!==t.indexOf("background")||(l[t]="inherit"),a&&"set"in a&&void 0===(n=a.set(e,n,r))||(u?l.setProperty(t,n):l[t]=n))}},css:function(e,t,n,r){var i,o,a,s=F(t);return ze.test(t)||(t=Ze(s)),(a=ce.cssHooks[t]||ce.cssHooks[s])&&"get"in a&&(i=a.get(e,!0,n)),void 0===i&&(i=Ge(e,t,r)),"normal"===i&&t in nt&&(i=nt[t]),""===n||n?(o=parseFloat(i),!0===n||isFinite(o)?o||0:i):i}}),ce.each(["height","width"],function(e,u){ce.cssHooks[u]={get:function(e,t,n){if(t)return!et.test(ce.css(e,"display"))||e.getClientRects().length&&e.getBoundingClientRect().width?ot(e,u,n):Ue(e,tt,function(){return ot(e,u,n)})},set:function(e,t,n){var r,i=Xe(e),o=!le.scrollboxSize()&&"absolute"===i.position,a=(o||n)&&"border-box"===ce.css(e,"boxSizing",!1,i),s=n?it(e,u,n,a,i):0;return a&&o&&(s-=Math.ceil(e["offset"+u[0].toUpperCase()+u.slice(1)]-parseFloat(i[u])-it(e,u,"border",!1,i)-.5)),s&&(r=Y.exec(t))&&"px"!==(r[3]||"px")&&(e.style[u]=t,t=ce.css(e,u)),rt(0,t,s)}}}),ce.cssHooks.marginLeft=Ye(le.reliableMarginLeft,function(e,t){if(t)return(parseFloat(Ge(e,"marginLeft"))||e.getBoundingClientRect().left-Ue(e,{marginLeft:0},function(){return e.getBoundingClientRect().left}))+"px"}),ce.each({margin:"",padding:"",border:"Width"},function(i,o){ce.cssHooks[i+o]={expand:function(e){for(var t=0,n={},r="string"==typeof e?e.split(" "):[e];t<4;t++)n[i+Q[t]+o]=r[t]||r[t-2]||r[0];return n}},"margin"!==i&&(ce.cssHooks[i+o].set=rt)}),ce.fn.extend({css:function(e,t){return M(this,function(e,t,n){var r,i,o={},a=0;if(Array.isArray(t)){for(r=Xe(e),i=t.length;a<i;a++)o[t[a]]=ce.css(e,t[a],!1,r);return o}return void 0!==n?ce.style(e,t,n):ce.css(e,t)},e,t,1<arguments.length)}}),((ce.Tween=at).prototype={constructor:at,init:function(e,t,n,r,i,o){this.elem=e,this.prop=n,this.easing=i||ce.easing._default,this.options=t,this.start=this.now=this.cur(),this.end=r,this.unit=o||(ce.cssNumber[n]?"":"px")},cur:function(){var e=at.propHooks[this.prop];return e&&e.get?e.get(this):at.propHooks._default.get(this)},run:function(e){var t,n=at.propHooks[this.prop];return this.options.duration?this.pos=t=ce.easing[this.easing](e,this.options.duration*e,0,1,this.options.duration):this.pos=t=e,this.now=(this.end-this.start)*t+this.start,this.options.step&&this.options.step.call(this.elem,this.now,this),n&&n.set?n.set(this):at.propHooks._default.set(this),this}}).init.prototype=at.prototype,(at.propHooks={_default:{get:function(e){var t;return 1!==e.elem.nodeType||null!=e.elem[e.prop]&&null==e.elem.style[e.prop]?e.elem[e.prop]:(t=ce.css(e.elem,e.prop,""))&&"auto"!==t?t:0},set:function(e){ce.fx.step[e.prop]?ce.fx.step[e.prop](e):1!==e.elem.nodeType||!ce.cssHooks[e.prop]&&null==e.elem.style[Ze(e.prop)]?e.elem[e.prop]=e.now:ce.style(e.elem,e.prop,e.now+e.unit)}}}).scrollTop=at.propHooks.scrollLeft={set:function(e){e.elem.nodeType&&e.elem.parentNode&&(e.elem[e.prop]=e.now)}},ce.easing={linear:function(e){return e},swing:function(e){return.5-Math.cos(e*Math.PI)/2},_default:"swing"},ce.fx=at.prototype.init,ce.fx.step={};var st,ut,lt,ct,ft=/^(?:toggle|show|hide)$/,pt=/queueHooks$/;function dt(){ut&&(!1===C.hidden&&ie.requestAnimationFrame?ie.requestAnimationFrame(dt):ie.setTimeout(dt,ce.fx.interval),ce.fx.tick())}function ht(){return ie.setTimeout(function(){st=void 0}),st=Date.now()}function gt(e,t){var n,r=0,i={height:e};for(t=t?1:0;r<4;r+=2-t)i["margin"+(n=Q[r])]=i["padding"+n]=e;return t&&(i.opacity=i.width=e),i}function vt(e,t,n){for(var r,i=(yt.tweeners[t]||[]).concat(yt.tweeners["*"]),o=0,a=i.length;o<a;o++)if(r=i[o].call(n,t,e))return r}function yt(o,e,t){var n,a,r=0,i=yt.prefilters.length,s=ce.Deferred().always(function(){delete u.elem}),u=function(){if(a)return!1;for(var e=st||ht(),t=Math.max(0,l.startTime+l.duration-e),n=1-(t/l.duration||0),r=0,i=l.tweens.length;r<i;r++)l.tweens[r].run(n);return s.notifyWith(o,[l,n,t]),n<1&&i?t:(i||s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l]),!1)},l=s.promise({elem:o,props:ce.extend({},e),opts:ce.extend(!0,{specialEasing:{},easing:ce.easing._default},t),originalProperties:e,originalOptions:t,startTime:st||ht(),duration:t.duration,tweens:[],createTween:function(e,t){var n=ce.Tween(o,l.opts,e,t,l.opts.specialEasing[e]||l.opts.easing);return l.tweens.push(n),n},stop:function(e){var t=0,n=e?l.tweens.length:0;if(a)return this;for(a=!0;t<n;t++)l.tweens[t].run(1);return e?(s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l,e])):s.rejectWith(o,[l,e]),this}}),c=l.props;for(!function(e,t){var n,r,i,o,a;for(n in e)if(i=t[r=F(n)],o=e[n],Array.isArray(o)&&(i=o[1],o=e[n]=o[0]),n!==r&&(e[r]=o,delete e[n]),(a=ce.cssHooks[r])&&"expand"in a)for(n in o=a.expand(o),delete e[r],o)n in e||(e[n]=o[n],t[n]=i);else t[r]=i}(c,l.opts.specialEasing);r<i;r++)if(n=yt.prefilters[r].call(l,o,c,l.opts))return v(n.stop)&&(ce._queueHooks(l.elem,l.opts.queue).stop=n.stop.bind(n)),n;return ce.map(c,vt,l),v(l.opts.start)&&l.opts.start.call(o,l),l.progress(l.opts.progress).done(l.opts.done,l.opts.complete).fail(l.opts.fail).always(l.opts.always),ce.fx.timer(ce.extend(u,{elem:o,anim:l,queue:l.opts.queue})),l}ce.Animation=ce.extend(yt,{tweeners:{"*":[function(e,t){var n=this.createTween(e,t);return te(n.elem,e,Y.exec(t),n),n}]},tweener:function(e,t){v(e)?(t=e,e=["*"]):e=e.match(D);for(var n,r=0,i=e.length;r<i;r++)n=e[r],yt.tweeners[n]=yt.tweeners[n]||[],yt.tweeners[n].unshift(t)},prefilters:[function(e,t,n){var r,i,o,a,s,u,l,c,f="width"in t||"height"in t,p=this,d={},h=e.style,g=e.nodeType&&ee(e),v=_.get(e,"fxshow");for(r in n.queue||(null==(a=ce._queueHooks(e,"fx")).unqueued&&(a.unqueued=0,s=a.empty.fire,a.empty.fire=function(){a.unqueued||s()}),a.unqueued++,p.always(function(){p.always(function(){a.unqueued--,ce.queue(e,"fx").length||a.empty.fire()})})),t)if(i=t[r],ft.test(i)){if(delete t[r],o=o||"toggle"===i,i===(g?"hide":"show")){if("show"!==i||!v||void 0===v[r])continue;g=!0}d[r]=v&&v[r]||ce.style(e,r)}if((u=!ce.isEmptyObject(t))||!ce.isEmptyObject(d))for(r in f&&1===e.nodeType&&(n.overflow=[h.overflow,h.overflowX,h.overflowY],null==(l=v&&v.display)&&(l=_.get(e,"display")),"none"===(c=ce.css(e,"display"))&&(l?c=l:(re([e],!0),l=e.style.display||l,c=ce.css(e,"display"),re([e]))),("inline"===c||"inline-block"===c&&null!=l)&&"none"===ce.css(e,"float")&&(u||(p.done(function(){h.display=l}),null==l&&(c=h.display,l="none"===c?"":c)),h.display="inline-block")),n.overflow&&(h.overflow="hidden",p.always(function(){h.overflow=n.overflow[0],h.overflowX=n.overflow[1],h.overflowY=n.overflow[2]})),u=!1,d)u||(v?"hidden"in v&&(g=v.hidden):v=_.access(e,"fxshow",{display:l}),o&&(v.hidden=!g),g&&re([e],!0),p.done(function(){for(r in g||re([e]),_.remove(e,"fxshow"),d)ce.style(e,r,d[r])})),u=vt(g?v[r]:0,r,p),r in v||(v[r]=u.start,g&&(u.end=u.start,u.start=0))}],prefilter:function(e,t){t?yt.prefilters.unshift(e):yt.prefilters.push(e)}}),ce.speed=function(e,t,n){var r=e&&"object"==typeof e?ce.extend({},e):{complete:n||!n&&t||v(e)&&e,duration:e,easing:n&&t||t&&!v(t)&&t};return ce.fx.off?r.duration=0:"number"!=typeof r.duration&&(r.duration in ce.fx.speeds?r.duration=ce.fx.speeds[r.duration]:r.duration=ce.fx.speeds._default),null!=r.queue&&!0!==r.queue||(r.queue="fx"),r.old=r.complete,r.complete=function(){v(r.old)&&r.old.call(this),r.queue&&ce.dequeue(this,r.queue)},r},ce.fn.extend({fadeTo:function(e,t,n,r){return this.filter(ee).css("opacity",0).show().end().animate({opacity:t},e,n,r)},animate:function(t,e,n,r){var i=ce.isEmptyObject(t),o=ce.speed(e,n,r),a=function(){var e=yt(this,ce.extend({},t),o);(i||_.get(this,"finish"))&&e.stop(!0)};return a.finish=a,i||!1===o.queue?this.each(a):this.queue(o.queue,a)},stop:function(i,e,o){var a=function(e){var t=e.stop;delete e.stop,t(o)};return"string"!=typeof i&&(o=e,e=i,i=void 0),e&&this.queue(i||"fx",[]),this.each(function(){var e=!0,t=null!=i&&i+"queueHooks",n=ce.timers,r=_.get(this);if(t)r[t]&&r[t].stop&&a(r[t]);else for(t in r)r[t]&&r[t].stop&&pt.test(t)&&a(r[t]);for(t=n.length;t--;)n[t].elem!==this||null!=i&&n[t].queue!==i||(n[t].anim.stop(o),e=!1,n.splice(t,1));!e&&o||ce.dequeue(this,i)})},finish:function(a){return!1!==a&&(a=a||"fx"),this.each(function(){var e,t=_.get(this),n=t[a+"queue"],r=t[a+"queueHooks"],i=ce.timers,o=n?n.length:0;for(t.finish=!0,ce.queue(this,a,[]),r&&r.stop&&r.stop.call(this,!0),e=i.length;e--;)i[e].elem===this&&i[e].queue===a&&(i[e].anim.stop(!0),i.splice(e,1));for(e=0;e<o;e++)n[e]&&n[e].finish&&n[e].finish.call(this);delete t.finish})}}),ce.each(["toggle","show","hide"],function(e,r){var i=ce.fn[r];ce.fn[r]=function(e,t,n){return null==e||"boolean"==typeof e?i.apply(this,arguments):this.animate(gt(r,!0),e,t,n)}}),ce.each({slideDown:gt("show"),slideUp:gt("hide"),slideToggle:gt("toggle"),fadeIn:{opacity:"show"},fadeOut:{opacity:"hide"},fadeToggle:{opacity:"toggle"}},function(e,r){ce.fn[e]=function(e,t,n){return this.animate(r,e,t,n)}}),ce.timers=[],ce.fx.tick=function(){var e,t=0,n=ce.timers;for(st=Date.now();t<n.length;t++)(e=n[t])()||n[t]!==e||n.splice(t--,1);n.length||ce.fx.stop(),st=void 0},ce.fx.timer=function(e){ce.timers.push(e),ce.fx.start()},ce.fx.interval=13,ce.fx.start=function(){ut||(ut=!0,dt())},ce.fx.stop=function(){ut=null},ce.fx.speeds={slow:600,fast:200,_default:400},ce.fn.delay=function(r,e){return r=ce.fx&&ce.fx.speeds[r]||r,e=e||"fx",this.queue(e,function(e,t){var n=ie.setTimeout(e,r);t.stop=function(){ie.clearTimeout(n)}})},lt=C.createElement("input"),ct=C.createElement("select").appendChild(C.createElement("option")),lt.type="checkbox",le.checkOn=""!==lt.value,le.optSelected=ct.selected,(lt=C.createElement("input")).value="t",lt.type="radio",le.radioValue="t"===lt.value;var mt,xt=ce.expr.attrHandle;ce.fn.extend({attr:function(e,t){return M(this,ce.attr,e,t,1<arguments.length)},removeAttr:function(e){return this.each(function(){ce.removeAttr(this,e)})}}),ce.extend({attr:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return"undefined"==typeof e.getAttribute?ce.prop(e,t,n):(1===o&&ce.isXMLDoc(e)||(i=ce.attrHooks[t.toLowerCase()]||(ce.expr.match.bool.test(t)?mt:void 0)),void 0!==n?null===n?void ce.removeAttr(e,t):i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:(e.setAttribute(t,n+""),n):i&&"get"in i&&null!==(r=i.get(e,t))?r:null==(r=ce.find.attr(e,t))?void 0:r)},attrHooks:{type:{set:function(e,t){if(!le.radioValue&&"radio"===t&&fe(e,"input")){var n=e.value;return e.setAttribute("type",t),n&&(e.value=n),t}}}},removeAttr:function(e,t){var n,r=0,i=t&&t.match(D);if(i&&1===e.nodeType)while(n=i[r++])e.removeAttribute(n)}}),mt={set:function(e,t,n){return!1===t?ce.removeAttr(e,n):e.setAttribute(n,n),n}},ce.each(ce.expr.match.bool.source.match(/\w+/g),function(e,t){var a=xt[t]||ce.find.attr;xt[t]=function(e,t,n){var r,i,o=t.toLowerCase();return n||(i=xt[o],xt[o]=r,r=null!=a(e,t,n)?o:null,xt[o]=i),r}});var bt=/^(?:input|select|textarea|button)$/i,wt=/^(?:a|area)$/i;function Tt(e){return(e.match(D)||[]).join(" ")}function Ct(e){return e.getAttribute&&e.getAttribute("class")||""}function kt(e){return Array.isArray(e)?e:"string"==typeof e&&e.match(D)||[]}ce.fn.extend({prop:function(e,t){return M(this,ce.prop,e,t,1<arguments.length)},removeProp:function(e){return this.each(function(){delete this[ce.propFix[e]||e]})}}),ce.extend({prop:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return 1===o&&ce.isXMLDoc(e)||(t=ce.propFix[t]||t,i=ce.propHooks[t]),void 0!==n?i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:e[t]=n:i&&"get"in i&&null!==(r=i.get(e,t))?r:e[t]},propHooks:{tabIndex:{get:function(e){var t=ce.find.attr(e,"tabindex");return t?parseInt(t,10):bt.test(e.nodeName)||wt.test(e.nodeName)&&e.href?0:-1}}},propFix:{"for":"htmlFor","class":"className"}}),le.optSelected||(ce.propHooks.selected={get:function(e){var t=e.parentNode;return t&&t.parentNode&&t.parentNode.selectedIndex,null},set:function(e){var t=e.parentNode;t&&(t.selectedIndex,t.parentNode&&t.parentNode.selectedIndex)}}),ce.each(["tabIndex","readOnly","maxLength","cellSpacing","cellPadding","rowSpan","colSpan","useMap","frameBorder","contentEditable"],function(){ce.propFix[this.toLowerCase()]=this}),ce.fn.extend({addClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).addClass(t.call(this,e,Ct(this)))}):(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++)i=e[o],n.indexOf(" "+i+" ")<0&&(n+=i+" ");a=Tt(n),r!==a&&this.setAttribute("class",a)}}):this},removeClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).removeClass(t.call(this,e,Ct(this)))}):arguments.length?(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++){i=e[o];while(-1<n.indexOf(" "+i+" "))n=n.replace(" "+i+" "," ")}a=Tt(n),r!==a&&this.setAttribute("class",a)}}):this:this.attr("class","")},toggleClass:function(t,n){var e,r,i,o,a=typeof t,s="string"===a||Array.isArray(t);return v(t)?this.each(function(e){ce(this).toggleClass(t.call(this,e,Ct(this),n),n)}):"boolean"==typeof n&&s?n?this.addClass(t):this.removeClass(t):(e=kt(t),this.each(function(){if(s)for(o=ce(this),i=0;i<e.length;i++)r=e[i],o.hasClass(r)?o.removeClass(r):o.addClass(r);else void 0!==t&&"boolean"!==a||((r=Ct(this))&&_.set(this,"__className__",r),this.setAttribute&&this.setAttribute("class",r||!1===t?"":_.get(this,"__className__")||""))}))},hasClass:function(e){var t,n,r=0;t=" "+e+" ";while(n=this[r++])if(1===n.nodeType&&-1<(" "+Tt(Ct(n))+" ").indexOf(t))return!0;return!1}});var St=/\r/g;ce.fn.extend({val:function(n){var r,e,i,t=this[0];return arguments.length?(i=v(n),this.each(function(e){var t;1===this.nodeType&&(null==(t=i?n.call(this,e,ce(this).val()):n)?t="":"number"==typeof t?t+="":Array.isArray(t)&&(t=ce.map(t,function(e){return null==e?"":e+""})),(r=ce.valHooks[this.type]||ce.valHooks[this.nodeName.toLowerCase()])&&"set"in r&&void 0!==r.set(this,t,"value")||(this.value=t))})):t?(r=ce.valHooks[t.type]||ce.valHooks[t.nodeName.toLowerCase()])&&"get"in r&&void 0!==(e=r.get(t,"value"))?e:"string"==typeof(e=t.value)?e.replace(St,""):null==e?"":e:void 0}}),ce.extend({valHooks:{option:{get:function(e){var t=ce.find.attr(e,"value");return null!=t?t:Tt(ce.text(e))}},select:{get:function(e){var t,n,r,i=e.options,o=e.selectedIndex,a="select-one"===e.type,s=a?null:[],u=a?o+1:i.length;for(r=o<0?u:a?o:0;r<u;r++)if(((n=i[r]).selected||r===o)&&!n.disabled&&(!n.parentNode.disabled||!fe(n.parentNode,"optgroup"))){if(t=ce(n).val(),a)return t;s.push(t)}return s},set:function(e,t){var n,r,i=e.options,o=ce.makeArray(t),a=i.length;while(a--)((r=i[a]).selected=-1<ce.inArray(ce.valHooks.option.get(r),o))&&(n=!0);return n||(e.selectedIndex=-1),o}}}}),ce.each(["radio","checkbox"],function(){ce.valHooks[this]={set:function(e,t){if(Array.isArray(t))return e.checked=-1<ce.inArray(ce(e).val(),t)}},le.checkOn||(ce.valHooks[this].get=function(e){return null===e.getAttribute("value")?"on":e.value})});var Et=ie.location,jt={guid:Date.now()},At=/\?/;ce.parseXML=function(e){var t,n;if(!e||"string"!=typeof e)return null;try{t=(new ie.DOMParser).parseFromString(e,"text/xml")}catch(e){}return n=t&&t.getElementsByTagName("parsererror")[0],t&&!n||ce.error("Invalid XML: "+(n?ce.map(n.childNodes,function(e){return e.textContent}).join("\n"):e)),t};var Dt=/^(?:focusinfocus|focusoutblur)$/,Nt=function(e){e.stopPropagation()};ce.extend(ce.event,{trigger:function(e,t,n,r){var i,o,a,s,u,l,c,f,p=[n||C],d=ue.call(e,"type")?e.type:e,h=ue.call(e,"namespace")?e.namespace.split("."):[];if(o=f=a=n=n||C,3!==n.nodeType&&8!==n.nodeType&&!Dt.test(d+ce.event.triggered)&&(-1<d.indexOf(".")&&(d=(h=d.split(".")).shift(),h.sort()),u=d.indexOf(":")<0&&"on"+d,(e=e[ce.expando]?e:new ce.Event(d,"object"==typeof e&&e)).isTrigger=r?2:3,e.namespace=h.join("."),e.rnamespace=e.namespace?new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"):null,e.result=void 0,e.target||(e.target=n),t=null==t?[e]:ce.makeArray(t,[e]),c=ce.event.special[d]||{},r||!c.trigger||!1!==c.trigger.apply(n,t))){if(!r&&!c.noBubble&&!y(n)){for(s=c.delegateType||d,Dt.test(s+d)||(o=o.parentNode);o;o=o.parentNode)p.push(o),a=o;a===(n.ownerDocument||C)&&p.push(a.defaultView||a.parentWindow||ie)}i=0;while((o=p[i++])&&!e.isPropagationStopped())f=o,e.type=1<i?s:c.bindType||d,(l=(_.get(o,"events")||Object.create(null))[e.type]&&_.get(o,"handle"))&&l.apply(o,t),(l=u&&o[u])&&l.apply&&$(o)&&(e.result=l.apply(o,t),!1===e.result&&e.preventDefault());return e.type=d,r||e.isDefaultPrevented()||c._default&&!1!==c._default.apply(p.pop(),t)||!$(n)||u&&v(n[d])&&!y(n)&&((a=n[u])&&(n[u]=null),ce.event.triggered=d,e.isPropagationStopped()&&f.addEventListener(d,Nt),n[d](),e.isPropagationStopped()&&f.removeEventListener(d,Nt),ce.event.triggered=void 0,a&&(n[u]=a)),e.result}},simulate:function(e,t,n){var r=ce.extend(new ce.Event,n,{type:e,isSimulated:!0});ce.event.trigger(r,null,t)}}),ce.fn.extend({trigger:function(e,t){return this.each(function(){ce.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return ce.event.trigger(e,t,n,!0)}});var qt=/\[\]$/,Lt=/\r?\n/g,Ht=/^(?:submit|button|image|reset|file)$/i,Ot=/^(?:input|select|textarea|keygen)/i;function Pt(n,e,r,i){var t;if(Array.isArray(e))ce.each(e,function(e,t){r||qt.test(n)?i(n,t):Pt(n+"["+("object"==typeof t&&null!=t?e:"")+"]",t,r,i)});else if(r||"object"!==x(e))i(n,e);else for(t in e)Pt(n+"["+t+"]",e[t],r,i)}ce.param=function(e,t){var n,r=[],i=function(e,t){var n=v(t)?t():t;r[r.length]=encodeURIComponent(e)+"="+encodeURIComponent(null==n?"":n)};if(null==e)return"";if(Array.isArray(e)||e.jquery&&!ce.isPlainObject(e))ce.each(e,function(){i(this.name,this.value)});else for(n in e)Pt(n,e[n],t,i);return r.join("&")},ce.fn.extend({serialize:function(){return ce.param(this.serializeArray())},serializeArray:function(){return this.map(function(){var e=ce.prop(this,"elements");return e?ce.makeArray(e):this}).filter(function(){var e=this.type;return this.name&&!ce(this).is(":disabled")&&Ot.test(this.nodeName)&&!Ht.test(e)&&(this.checked||!we.test(e))}).map(function(e,t){var n=ce(this).val();return null==n?null:Array.isArray(n)?ce.map(n,function(e){return{name:t.name,value:e.replace(Lt,"\r\n")}}):{name:t.name,value:n.replace(Lt,"\r\n")}}).get()}});var Mt=/%20/g,Rt=/#.*$/,It=/([?&])_=[^&]*/,Wt=/^(.*?):[ \t]*([^\r\n]*)$/gm,Ft=/^(?:GET|HEAD)$/,$t=/^\/\//,Bt={},_t={},zt="*/".concat("*"),Xt=C.createElement("a");function Ut(o){return function(e,t){"string"!=typeof e&&(t=e,e="*");var n,r=0,i=e.toLowerCase().match(D)||[];if(v(t))while(n=i[r++])"+"===n[0]?(n=n.slice(1)||"*",(o[n]=o[n]||[]).unshift(t)):(o[n]=o[n]||[]).push(t)}}function Vt(t,i,o,a){var s={},u=t===_t;function l(e){var r;return s[e]=!0,ce.each(t[e]||[],function(e,t){var n=t(i,o,a);return"string"!=typeof n||u||s[n]?u?!(r=n):void 0:(i.dataTypes.unshift(n),l(n),!1)}),r}return l(i.dataTypes[0])||!s["*"]&&l("*")}function Gt(e,t){var n,r,i=ce.ajaxSettings.flatOptions||{};for(n in t)void 0!==t[n]&&((i[n]?e:r||(r={}))[n]=t[n]);return r&&ce.extend(!0,e,r),e}Xt.href=Et.href,ce.extend({active:0,lastModified:{},etag:{},ajaxSettings:{url:Et.href,type:"GET",isLocal:/^(?:about|app|app-storage|.+-extension|file|res|widget):$/.test(Et.protocol),global:!0,processData:!0,async:!0,contentType:"application/x-www-form-urlencoded; charset=UTF-8",accepts:{"*":zt,text:"text/plain",html:"text/html",xml:"application/xml, text/xml",json:"application/json, text/javascript"},contents:{xml:/\bxml\b/,html:/\bhtml/,json:/\bjson\b/},responseFields:{xml:"responseXML",text:"responseText",json:"responseJSON"},converters:{"* text":String,"text html":!0,"text json":JSON.parse,"text xml":ce.parseXML},flatOptions:{url:!0,context:!0}},ajaxSetup:function(e,t){return t?Gt(Gt(e,ce.ajaxSettings),t):Gt(ce.ajaxSettings,e)},ajaxPrefilter:Ut(Bt),ajaxTransport:Ut(_t),ajax:function(e,t){"object"==typeof e&&(t=e,e=void 0),t=t||{};var c,f,p,n,d,r,h,g,i,o,v=ce.ajaxSetup({},t),y=v.context||v,m=v.context&&(y.nodeType||y.jquery)?ce(y):ce.event,x=ce.Deferred(),b=ce.Callbacks("once memory"),w=v.statusCode||{},a={},s={},u="canceled",T={readyState:0,getResponseHeader:function(e){var t;if(h){if(!n){n={};while(t=Wt.exec(p))n[t[1].toLowerCase()+" "]=(n[t[1].toLowerCase()+" "]||[]).concat(t[2])}t=n[e.toLowerCase()+" "]}return null==t?null:t.join(", ")},getAllResponseHeaders:function(){return h?p:null},setRequestHeader:function(e,t){return null==h&&(e=s[e.toLowerCase()]=s[e.toLowerCase()]||e,a[e]=t),this},overrideMimeType:function(e){return null==h&&(v.mimeType=e),this},statusCode:function(e){var t;if(e)if(h)T.always(e[T.status]);else for(t in e)w[t]=[w[t],e[t]];return this},abort:function(e){var t=e||u;return c&&c.abort(t),l(0,t),this}};if(x.promise(T),v.url=((e||v.url||Et.href)+"").replace($t,Et.protocol+"//"),v.type=t.method||t.type||v.method||v.type,v.dataTypes=(v.dataType||"*").toLowerCase().match(D)||[""],null==v.crossDomain){r=C.createElement("a");try{r.href=v.url,r.href=r.href,v.crossDomain=Xt.protocol+"//"+Xt.host!=r.protocol+"//"+r.host}catch(e){v.crossDomain=!0}}if(v.data&&v.processData&&"string"!=typeof v.data&&(v.data=ce.param(v.data,v.traditional)),Vt(Bt,v,t,T),h)return T;for(i in(g=ce.event&&v.global)&&0==ce.active++&&ce.event.trigger("ajaxStart"),v.type=v.type.toUpperCase(),v.hasContent=!Ft.test(v.type),f=v.url.replace(Rt,""),v.hasContent?v.data&&v.processData&&0===(v.contentType||"").indexOf("application/x-www-form-urlencoded")&&(v.data=v.data.replace(Mt,"+")):(o=v.url.slice(f.length),v.data&&(v.processData||"string"==typeof v.data)&&(f+=(At.test(f)?"&":"?")+v.data,delete v.data),!1===v.cache&&(f=f.replace(It,"$1"),o=(At.test(f)?"&":"?")+"_="+jt.guid+++o),v.url=f+o),v.ifModified&&(ce.lastModified[f]&&T.setRequestHeader("If-Modified-Since",ce.lastModified[f]),ce.etag[f]&&T.setRequestHeader("If-None-Match",ce.etag[f])),(v.data&&v.hasContent&&!1!==v.contentType||t.contentType)&&T.setRequestHeader("Content-Type",v.contentType),T.setRequestHeader("Accept",v.dataTypes[0]&&v.accepts[v.dataTypes[0]]?v.accepts[v.dataTypes[0]]+("*"!==v.dataTypes[0]?", "+zt+"; q=0.01":""):v.accepts["*"]),v.headers)T.setRequestHeader(i,v.headers[i]);if(v.beforeSend&&(!1===v.beforeSend.call(y,T,v)||h))return T.abort();if(u="abort",b.add(v.complete),T.done(v.success),T.fail(v.error),c=Vt(_t,v,t,T)){if(T.readyState=1,g&&m.trigger("ajaxSend",[T,v]),h)return T;v.async&&0<v.timeout&&(d=ie.setTimeout(function(){T.abort("timeout")},v.timeout));try{h=!1,c.send(a,l)}catch(e){if(h)throw e;l(-1,e)}}else l(-1,"No Transport");function l(e,t,n,r){var i,o,a,s,u,l=t;h||(h=!0,d&&ie.clearTimeout(d),c=void 0,p=r||"",T.readyState=0<e?4:0,i=200<=e&&e<300||304===e,n&&(s=function(e,t,n){var r,i,o,a,s=e.contents,u=e.dataTypes;while("*"===u[0])u.shift(),void 0===r&&(r=e.mimeType||t.getResponseHeader("Content-Type"));if(r)for(i in s)if(s[i]&&s[i].test(r)){u.unshift(i);break}if(u[0]in n)o=u[0];else{for(i in n){if(!u[0]||e.converters[i+" "+u[0]]){o=i;break}a||(a=i)}o=o||a}if(o)return o!==u[0]&&u.unshift(o),n[o]}(v,T,n)),!i&&-1<ce.inArray("script",v.dataTypes)&&ce.inArray("json",v.dataTypes)<0&&(v.converters["text script"]=function(){}),s=function(e,t,n,r){var i,o,a,s,u,l={},c=e.dataTypes.slice();if(c[1])for(a in e.converters)l[a.toLowerCase()]=e.converters[a];o=c.shift();while(o)if(e.responseFields[o]&&(n[e.responseFields[o]]=t),!u&&r&&e.dataFilter&&(t=e.dataFilter(t,e.dataType)),u=o,o=c.shift())if("*"===o)o=u;else if("*"!==u&&u!==o){if(!(a=l[u+" "+o]||l["* "+o]))for(i in l)if((s=i.split(" "))[1]===o&&(a=l[u+" "+s[0]]||l["* "+s[0]])){!0===a?a=l[i]:!0!==l[i]&&(o=s[0],c.unshift(s[1]));break}if(!0!==a)if(a&&e["throws"])t=a(t);else try{t=a(t)}catch(e){return{state:"parsererror",error:a?e:"No conversion from "+u+" to "+o}}}return{state:"success",data:t}}(v,s,T,i),i?(v.ifModified&&((u=T.getResponseHeader("Last-Modified"))&&(ce.lastModified[f]=u),(u=T.getResponseHeader("etag"))&&(ce.etag[f]=u)),204===e||"HEAD"===v.type?l="nocontent":304===e?l="notmodified":(l=s.state,o=s.data,i=!(a=s.error))):(a=l,!e&&l||(l="error",e<0&&(e=0))),T.status=e,T.statusText=(t||l)+"",i?x.resolveWith(y,[o,l,T]):x.rejectWith(y,[T,l,a]),T.statusCode(w),w=void 0,g&&m.trigger(i?"ajaxSuccess":"ajaxError",[T,v,i?o:a]),b.fireWith(y,[T,l]),g&&(m.trigger("ajaxComplete",[T,v]),--ce.active||ce.event.trigger("ajaxStop")))}return T},getJSON:function(e,t,n){return ce.get(e,t,n,"json")},getScript:function(e,t){return ce.get(e,void 0,t,"script")}}),ce.each(["get","post"],function(e,i){ce[i]=function(e,t,n,r){return v(t)&&(r=r||n,n=t,t=void 0),ce.ajax(ce.extend({url:e,type:i,dataType:r,data:t,success:n},ce.isPlainObject(e)&&e))}}),ce.ajaxPrefilter(function(e){var t;for(t in e.headers)"content-type"===t.toLowerCase()&&(e.contentType=e.headers[t]||"")}),ce._evalUrl=function(e,t,n){return ce.ajax({url:e,type:"GET",dataType:"script",cache:!0,async:!1,global:!1,converters:{"text script":function(){}},dataFilter:function(e){ce.globalEval(e,t,n)}})},ce.fn.extend({wrapAll:function(e){var t;return this[0]&&(v(e)&&(e=e.call(this[0])),t=ce(e,this[0].ownerDocument).eq(0).clone(!0),this[0].parentNode&&t.insertBefore(this[0]),t.map(function(){var e=this;while(e.firstElementChild)e=e.firstElementChild;return e}).append(this)),this},wrapInner:function(n){return v(n)?this.each(function(e){ce(this).wrapInner(n.call(this,e))}):this.each(function(){var e=ce(this),t=e.contents();t.length?t.wrapAll(n):e.append(n)})},wrap:function(t){var n=v(t);return this.each(function(e){ce(this).wrapAll(n?t.call(this,e):t)})},unwrap:function(e){return this.parent(e).not("body").each(function(){ce(this).replaceWith(this.childNodes)}),this}}),ce.expr.pseudos.hidden=function(e){return!ce.expr.pseudos.visible(e)},ce.expr.pseudos.visible=function(e){return!!(e.offsetWidth||e.offsetHeight||e.getClientRects().length)},ce.ajaxSettings.xhr=function(){try{return new ie.XMLHttpRequest}catch(e){}};var Yt={0:200,1223:204},Qt=ce.ajaxSettings.xhr();le.cors=!!Qt&&"withCredentials"in Qt,le.ajax=Qt=!!Qt,ce.ajaxTransport(function(i){var o,a;if(le.cors||Qt&&!i.crossDomain)return{send:function(e,t){var n,r=i.xhr();if(r.open(i.type,i.url,i.async,i.username,i.password),i.xhrFields)for(n in i.xhrFields)r[n]=i.xhrFields[n];for(n in i.mimeType&&r.overrideMimeType&&r.overrideMimeType(i.mimeType),i.crossDomain||e["X-Requested-With"]||(e["X-Requested-With"]="XMLHttpRequest"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(Yt[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onreadystatechange=function(){4===r.readyState&&ie.setTimeout(function(){o&&a()})},o=o("abort");try{r.send(i.hasContent&&i.data||null)}catch(e){if(o)throw e}},abort:function(){o&&o()}}}),ce.ajaxPrefilter(function(e){e.crossDomain&&(e.contents.script=!1)}),ce.ajaxSetup({accepts:{script:"text/javascript, application/javascript, application/ecmascript, application/x-ecmascript"},contents:{script:/\b(?:java|ecma)script\b/},converters:{"text script":function(e){return ce.globalEval(e),e}}}),ce.ajaxPrefilter("script",function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type="GET")}),ce.ajaxTransport("script",function(n){var r,i;if(n.crossDomain||n.scriptAttrs)return{send:function(e,t){r=ce("<script>").attr(n.scriptAttrs||{}).prop({charset:n.scriptCharset,src:n.url}).on("load error",i=function(e){r.remove(),i=null,e&&t("error"===e.type?404:200,e.type)}),C.head.appendChild(r[0])},abort:function(){i&&i()}}});var Jt,Kt=[],Zt=/(=)\?(?=&|$)|\?\?/;ce.ajaxSetup({jsonp:"callback",jsonpCallback:function(){var e=Kt.pop()||ce.expando+"_"+jt.guid++;return this[e]=!0,e}}),ce.ajaxPrefilter("json jsonp",function(e,t,n){var r,i,o,a=!1!==e.jsonp&&(Zt.test(e.url)?"url":"string"==typeof e.data&&0===(e.contentType||"").indexOf("application/x-www-form-urlencoded")&&Zt.test(e.data)&&"data");if(a||"jsonp"===e.dataTypes[0])return r=e.jsonpCallback=v(e.jsonpCallback)?e.jsonpCallback():e.jsonpCallback,a?e[a]=e[a].replace(Zt,"$1"+r):!1!==e.jsonp&&(e.url+=(At.test(e.url)?"&":"?")+e.jsonp+"="+r),e.converters["script json"]=function(){return o||ce.error(r+" was not called"),o[0]},e.dataTypes[0]="json",i=ie[r],ie[r]=function(){o=arguments},n.always(function(){void 0===i?ce(ie).removeProp(r):ie[r]=i,e[r]&&(e.jsonpCallback=t.jsonpCallback,Kt.push(r)),o&&v(i)&&i(o[0]),o=i=void 0}),"script"}),le.createHTMLDocument=((Jt=C.implementation.createHTMLDocument("").body).innerHTML="<form></form><form></form>",2===Jt.childNodes.length),ce.parseHTML=function(e,t,n){return"string"!=typeof e?[]:("boolean"==typeof t&&(n=t,t=!1),t||(le.createHTMLDocument?((r=(t=C.implementation.createHTMLDocument("")).createElement("base")).href=C.location.href,t.head.appendChild(r)):t=C),o=!n&&[],(i=w.exec(e))?[t.createElement(i[1])]:(i=Ae([e],t,o),o&&o.length&&ce(o).remove(),ce.merge([],i.childNodes)));var r,i,o},ce.fn.load=function(e,t,n){var r,i,o,a=this,s=e.indexOf(" ");return-1<s&&(r=Tt(e.slice(s)),e=e.slice(0,s)),v(t)?(n=t,t=void 0):t&&"object"==typeof t&&(i="POST"),0<a.length&&ce.ajax({url:e,type:i||"GET",dataType:"html",data:t}).done(function(e){o=arguments,a.html(r?ce("<div>").append(ce.parseHTML(e)).find(r):e)}).always(n&&function(e,t){a.each(function(){n.apply(this,o||[e.responseText,t,e])})}),this},ce.expr.pseudos.animated=function(t){return ce.grep(ce.timers,function(e){return t===e.elem}).length},ce.offset={setOffset:function(e,t,n){var r,i,o,a,s,u,l=ce.css(e,"position"),c=ce(e),f={};"static"===l&&(e.style.position="relative"),s=c.offset(),o=ce.css(e,"top"),u=ce.css(e,"left"),("absolute"===l||"fixed"===l)&&-1<(o+u).indexOf("auto")?(a=(r=c.position()).top,i=r.left):(a=parseFloat(o)||0,i=parseFloat(u)||0),v(t)&&(t=t.call(e,n,ce.extend({},s))),null!=t.top&&(f.top=t.top-s.top+a),null!=t.left&&(f.left=t.left-s.left+i),"using"in t?t.using.call(e,f):c.css(f)}},ce.fn.extend({offset:function(t){if(arguments.length)return void 0===t?this:this.each(function(e){ce.offset.setOffset(this,t,e)});var e,n,r=this[0];return r?r.getClientRects().length?(e=r.getBoundingClientRect(),n=r.ownerDocument.defaultView,{top:e.top+n.pageYOffset,left:e.left+n.pageXOffset}):{top:0,left:0}:void 0},position:function(){if(this[0]){var e,t,n,r=this[0],i={top:0,left:0};if("fixed"===ce.css(r,"position"))t=r.getBoundingClientRect();else{t=this.offset(),n=r.ownerDocument,e=r.offsetParent||n.documentElement;while(e&&(e===n.body||e===n.documentElement)&&"static"===ce.css(e,"position"))e=e.parentNode;e&&e!==r&&1===e.nodeType&&((i=ce(e).offset()).top+=ce.css(e,"borderTopWidth",!0),i.left+=ce.css(e,"borderLeftWidth",!0))}return{top:t.top-i.top-ce.css(r,"marginTop",!0),left:t.left-i.left-ce.css(r,"marginLeft",!0)}}},offsetParent:function(){return this.map(function(){var e=this.offsetParent;while(e&&"static"===ce.css(e,"position"))e=e.offsetParent;return e||J})}}),ce.each({scrollLeft:"pageXOffset",scrollTop:"pageYOffset"},function(t,i){var o="pageYOffset"===i;ce.fn[t]=function(e){return M(this,function(e,t,n){var r;if(y(e)?r=e:9===e.nodeType&&(r=e.defaultView),void 0===n)return r?r[i]:e[t];r?r.scrollTo(o?r.pageXOffset:n,o?n:r.pageYOffset):e[t]=n},t,e,arguments.length)}}),ce.each(["top","left"],function(e,n){ce.cssHooks[n]=Ye(le.pixelPosition,function(e,t){if(t)return t=Ge(e,n),_e.test(t)?ce(e).position()[n]+"px":t})}),ce.each({Height:"height",Width:"width"},function(a,s){ce.each({padding:"inner"+a,content:s,"":"outer"+a},function(r,o){ce.fn[o]=function(e,t){var n=arguments.length&&(r||"boolean"!=typeof e),i=r||(!0===e||!0===t?"margin":"border");return M(this,function(e,t,n){var r;return y(e)?0===o.indexOf("outer")?e["inner"+a]:e.document.documentElement["client"+a]:9===e.nodeType?(r=e.documentElement,Math.max(e.body["scroll"+a],r["scroll"+a],e.body["offset"+a],r["offset"+a],r["client"+a])):void 0===n?ce.css(e,t,i):ce.style(e,t,n,i)},s,n?e:void 0,n)}})}),ce.each(["ajaxStart","ajaxStop","ajaxComplete","ajaxError","ajaxSuccess","ajaxSend"],function(e,t){ce.fn[t]=function(e){return this.on(t,e)}}),ce.fn.extend({bind:function(e,t,n){return this.on(e,null,t,n)},unbind:function(e,t){return this.off(e,null,t)},delegate:function(e,t,n,r){return this.on(t,e,n,r)},undelegate:function(e,t,n){return 1===arguments.length?this.off(e,"**"):this.off(t,e||"**",n)},hover:function(e,t){return this.on("mouseenter",e).on("mouseleave",t||e)}}),ce.each("blur focus focusin focusout resize scroll click dblclick mousedown mouseup mousemove mouseover mouseout mouseenter mouseleave change select submit keydown keypress keyup contextmenu".split(" "),function(e,n){ce.fn[n]=function(e,t){return 0<arguments.length?this.on(n,null,e,t):this.trigger(n)}});var en=/^[\s\uFEFF\xA0]+|([^\s\uFEFF\xA0])[\s\uFEFF\xA0]+$/g;ce.proxy=function(e,t){var n,r,i;if("string"==typeof t&&(n=e[t],t=e,e=n),v(e))return r=ae.call(arguments,2),(i=function(){return e.apply(t||this,r.concat(ae.call(arguments)))}).guid=e.guid=e.guid||ce.guid++,i},ce.holdReady=function(e){e?ce.readyWait++:ce.ready(!0)},ce.isArray=Array.isArray,ce.parseJSON=JSON.parse,ce.nodeName=fe,ce.isFunction=v,ce.isWindow=y,ce.camelCase=F,ce.type=x,ce.now=Date.now,ce.isNumeric=function(e){var t=ce.type(e);return("number"===t||"string"===t)&&!isNaN(e-parseFloat(e))},ce.trim=function(e){return null==e?"":(e+"").replace(en,"$1")},"function"==typeof define&&define.amd&&define("jquery",[],function(){return ce});var tn=ie.jQuery,nn=ie.$;return ce.noConflict=function(e){return ie.$===ce&&(ie.$=nn),e&&ie.jQuery===ce&&(ie.jQuery=tn),ce},"undefined"==typeof e&&(ie.jQuery=ie.$=ce),ce});
+</script>
+<script>!function(){function n(n){return n&&(n.ownerDocument||n.document||n).documentElement}function t(n){return n&&(n.ownerDocument&&n.ownerDocument.defaultView||n.document&&n||n.defaultView)}function e(n,t){return t>n?-1:n>t?1:n>=t?0:0/0}function r(n){return null===n?0/0:+n}function u(n){return!isNaN(n)}function i(n){return{left:function(t,e,r,u){for(arguments.length<3&&(r=0),arguments.length<4&&(u=t.length);u>r;){var i=r+u>>>1;n(t[i],e)<0?r=i+1:u=i}return r},right:function(t,e,r,u){for(arguments.length<3&&(r=0),arguments.length<4&&(u=t.length);u>r;){var i=r+u>>>1;n(t[i],e)>0?u=i:r=i+1}return r}}}function o(n){return n.length}function a(n){for(var t=1;n*t%1;)t*=10;return t}function c(n,t){for(var e in t)Object.defineProperty(n.prototype,e,{value:t[e],enumerable:!1})}function l(){this._=Object.create(null)}function s(n){return(n+="")===pa||n[0]===va?va+n:n}function f(n){return(n+="")[0]===va?n.slice(1):n}function h(n){return s(n)in this._}function g(n){return(n=s(n))in this._&&delete this._[n]}function p(){var n=[];for(var t in this._)n.push(f(t));return n}function v(){var n=0;for(var t in this._)++n;return n}function d(){for(var n in this._)return!1;return!0}function m(){this._=Object.create(null)}function y(n){return n}function M(n,t,e){return function(){var r=e.apply(t,arguments);return r===t?n:r}}function x(n,t){if(t in n)return t;t=t.charAt(0).toUpperCase()+t.slice(1);for(var e=0,r=da.length;r>e;++e){var u=da[e]+t;if(u in n)return u}}function b(){}function _(){}function w(n){function t(){for(var t,r=e,u=-1,i=r.length;++u<i;)(t=r[u].on)&&t.apply(this,arguments);return n}var e=[],r=new l;return t.on=function(t,u){var i,o=r.get(t);return arguments.length<2?o&&o.on:(o&&(o.on=null,e=e.slice(0,i=e.indexOf(o)).concat(e.slice(i+1)),r.remove(t)),u&&e.push(r.set(t,{on:u})),n)},t}function S(){ta.event.preventDefault()}function k(){for(var n,t=ta.event;n=t.sourceEvent;)t=n;return t}function E(n){for(var t=new _,e=0,r=arguments.length;++e<r;)t[arguments[e]]=w(t);return t.of=function(e,r){return function(u){try{var i=u.sourceEvent=ta.event;u.target=n,ta.event=u,t[u.type].apply(e,r)}finally{ta.event=i}}},t}function A(n){return ya(n,_a),n}function N(n){return"function"==typeof n?n:function(){return Ma(n,this)}}function C(n){return"function"==typeof n?n:function(){return xa(n,this)}}function z(n,t){function e(){this.removeAttribute(n)}function r(){this.removeAttributeNS(n.space,n.local)}function u(){this.setAttribute(n,t)}function i(){this.setAttributeNS(n.space,n.local,t)}function o(){var e=t.apply(this,arguments);null==e?this.removeAttribute(n):this.setAttribute(n,e)}function a(){var e=t.apply(this,arguments);null==e?this.removeAttributeNS(n.space,n.local):this.setAttributeNS(n.space,n.local,e)}return n=ta.ns.qualify(n),null==t?n.local?r:e:"function"==typeof t?n.local?a:o:n.local?i:u}function q(n){return n.trim().replace(/\s+/g," ")}function L(n){return new RegExp("(?:^|\\s+)"+ta.requote(n)+"(?:\\s+|$)","g")}function T(n){return(n+"").trim().split(/^|\s+/)}function R(n,t){function e(){for(var e=-1;++e<u;)n[e](this,t)}function r(){for(var e=-1,r=t.apply(this,arguments);++e<u;)n[e](this,r)}n=T(n).map(D);var u=n.length;return"function"==typeof t?r:e}function D(n){var t=L(n);return function(e,r){if(u=e.classList)return r?u.add(n):u.remove(n);var u=e.getAttribute("class")||"";r?(t.lastIndex=0,t.test(u)||e.setAttribute("class",q(u+" "+n))):e.setAttribute("class",q(u.replace(t," ")))}}function P(n,t,e){function r(){this.style.removeProperty(n)}function u(){this.style.setProperty(n,t,e)}function i(){var r=t.apply(this,arguments);null==r?this.style.removeProperty(n):this.style.setProperty(n,r,e)}return null==t?r:"function"==typeof t?i:u}function U(n,t){function e(){delete this[n]}function r(){this[n]=t}function u(){var e=t.apply(this,arguments);null==e?delete this[n]:this[n]=e}return null==t?e:"function"==typeof t?u:r}function j(n){function t(){var t=this.ownerDocument,e=this.namespaceURI;return e?t.createElementNS(e,n):t.createElement(n)}function e(){return this.ownerDocument.createElementNS(n.space,n.local)}return"function"==typeof n?n:(n=ta.ns.qualify(n)).local?e:t}function F(){var n=this.parentNode;n&&n.removeChild(this)}function H(n){return{__data__:n}}function O(n){return function(){return ba(this,n)}}function I(n){return arguments.length||(n=e),function(t,e){return t&&e?n(t.__data__,e.__data__):!t-!e}}function Y(n,t){for(var e=0,r=n.length;r>e;e++)for(var u,i=n[e],o=0,a=i.length;a>o;o++)(u=i[o])&&t(u,o,e);return n}function Z(n){return ya(n,Sa),n}function V(n){var t,e;return function(r,u,i){var o,a=n[i].update,c=a.length;for(i!=e&&(e=i,t=0),u>=t&&(t=u+1);!(o=a[t])&&++t<c;);return o}}function X(n,t,e){function r(){var t=this[o];t&&(this.removeEventListener(n,t,t.$),delete this[o])}function u(){var u=c(t,ra(arguments));r.call(this),this.addEventListener(n,this[o]=u,u.$=e),u._=t}function i(){var t,e=new RegExp("^__on([^.]+)"+ta.requote(n)+"$");for(var r in this)if(t=r.match(e)){var u=this[r];this.removeEventListener(t[1],u,u.$),delete this[r]}}var o="__on"+n,a=n.indexOf("."),c=$;a>0&&(n=n.slice(0,a));var l=ka.get(n);return l&&(n=l,c=B),a?t?u:r:t?b:i}function $(n,t){return function(e){var r=ta.event;ta.event=e,t[0]=this.__data__;try{n.apply(this,t)}finally{ta.event=r}}}function B(n,t){var e=$(n,t);return function(n){var t=this,r=n.relatedTarget;r&&(r===t||8&r.compareDocumentPosition(t))||e.call(t,n)}}function W(e){var r=".dragsuppress-"+ ++Aa,u="click"+r,i=ta.select(t(e)).on("touchmove"+r,S).on("dragstart"+r,S).on("selectstart"+r,S);if(null==Ea&&(Ea="onselectstart"in e?!1:x(e.style,"userSelect")),Ea){var o=n(e).style,a=o[Ea];o[Ea]="none"}return function(n){if(i.on(r,null),Ea&&(o[Ea]=a),n){var t=function(){i.on(u,null)};i.on(u,function(){S(),t()},!0),setTimeout(t,0)}}}function J(n,e){e.changedTouches&&(e=e.changedTouches[0]);var r=n.ownerSVGElement||n;if(r.createSVGPoint){var u=r.createSVGPoint();if(0>Na){var i=t(n);if(i.scrollX||i.scrollY){r=ta.select("body").append("svg").style({position:"absolute",top:0,left:0,margin:0,padding:0,border:"none"},"important");var o=r[0][0].getScreenCTM();Na=!(o.f||o.e),r.remove()}}return Na?(u.x=e.pageX,u.y=e.pageY):(u.x=e.clientX,u.y=e.clientY),u=u.matrixTransform(n.getScreenCTM().inverse()),[u.x,u.y]}var a=n.getBoundingClientRect();return[e.clientX-a.left-n.clientLeft,e.clientY-a.top-n.clientTop]}function G(){return ta.event.changedTouches[0].identifier}function K(n){return n>0?1:0>n?-1:0}function Q(n,t,e){return(t[0]-n[0])*(e[1]-n[1])-(t[1]-n[1])*(e[0]-n[0])}function nt(n){return n>1?0:-1>n?qa:Math.acos(n)}function tt(n){return n>1?Ra:-1>n?-Ra:Math.asin(n)}function et(n){return((n=Math.exp(n))-1/n)/2}function rt(n){return((n=Math.exp(n))+1/n)/2}function ut(n){return((n=Math.exp(2*n))-1)/(n+1)}function it(n){return(n=Math.sin(n/2))*n}function ot(){}function at(n,t,e){return this instanceof at?(this.h=+n,this.s=+t,void(this.l=+e)):arguments.length<2?n instanceof at?new at(n.h,n.s,n.l):bt(""+n,_t,at):new at(n,t,e)}function ct(n,t,e){function r(n){return n>360?n-=360:0>n&&(n+=360),60>n?i+(o-i)*n/60:180>n?o:240>n?i+(o-i)*(240-n)/60:i}function u(n){return Math.round(255*r(n))}var i,o;return n=isNaN(n)?0:(n%=360)<0?n+360:n,t=isNaN(t)?0:0>t?0:t>1?1:t,e=0>e?0:e>1?1:e,o=.5>=e?e*(1+t):e+t-e*t,i=2*e-o,new mt(u(n+120),u(n),u(n-120))}function lt(n,t,e){return this instanceof lt?(this.h=+n,this.c=+t,void(this.l=+e)):arguments.length<2?n instanceof lt?new lt(n.h,n.c,n.l):n instanceof ft?gt(n.l,n.a,n.b):gt((n=wt((n=ta.rgb(n)).r,n.g,n.b)).l,n.a,n.b):new lt(n,t,e)}function st(n,t,e){return isNaN(n)&&(n=0),isNaN(t)&&(t=0),new ft(e,Math.cos(n*=Da)*t,Math.sin(n)*t)}function ft(n,t,e){return this instanceof ft?(this.l=+n,this.a=+t,void(this.b=+e)):arguments.length<2?n instanceof ft?new ft(n.l,n.a,n.b):n instanceof lt?st(n.h,n.c,n.l):wt((n=mt(n)).r,n.g,n.b):new ft(n,t,e)}function ht(n,t,e){var r=(n+16)/116,u=r+t/500,i=r-e/200;return u=pt(u)*Xa,r=pt(r)*$a,i=pt(i)*Ba,new mt(dt(3.2404542*u-1.5371385*r-.4985314*i),dt(-.969266*u+1.8760108*r+.041556*i),dt(.0556434*u-.2040259*r+1.0572252*i))}function gt(n,t,e){return n>0?new lt(Math.atan2(e,t)*Pa,Math.sqrt(t*t+e*e),n):new lt(0/0,0/0,n)}function pt(n){return n>.206893034?n*n*n:(n-4/29)/7.787037}function vt(n){return n>.008856?Math.pow(n,1/3):7.787037*n+4/29}function dt(n){return Math.round(255*(.00304>=n?12.92*n:1.055*Math.pow(n,1/2.4)-.055))}function mt(n,t,e){return this instanceof mt?(this.r=~~n,this.g=~~t,void(this.b=~~e)):arguments.length<2?n instanceof mt?new mt(n.r,n.g,n.b):bt(""+n,mt,ct):new mt(n,t,e)}function yt(n){return new mt(n>>16,n>>8&255,255&n)}function Mt(n){return yt(n)+""}function xt(n){return 16>n?"0"+Math.max(0,n).toString(16):Math.min(255,n).toString(16)}function bt(n,t,e){var r,u,i,o=0,a=0,c=0;if(r=/([a-z]+)\((.*)\)/.exec(n=n.toLowerCase()))switch(u=r[2].split(","),r[1]){case"hsl":return e(parseFloat(u[0]),parseFloat(u[1])/100,parseFloat(u[2])/100);case"rgb":return t(kt(u[0]),kt(u[1]),kt(u[2]))}return(i=Ga.get(n))?t(i.r,i.g,i.b):(null==n||"#"!==n.charAt(0)||isNaN(i=parseInt(n.slice(1),16))||(4===n.length?(o=(3840&i)>>4,o=o>>4|o,a=240&i,a=a>>4|a,c=15&i,c=c<<4|c):7===n.length&&(o=(16711680&i)>>16,a=(65280&i)>>8,c=255&i)),t(o,a,c))}function _t(n,t,e){var r,u,i=Math.min(n/=255,t/=255,e/=255),o=Math.max(n,t,e),a=o-i,c=(o+i)/2;return a?(u=.5>c?a/(o+i):a/(2-o-i),r=n==o?(t-e)/a+(e>t?6:0):t==o?(e-n)/a+2:(n-t)/a+4,r*=60):(r=0/0,u=c>0&&1>c?0:r),new at(r,u,c)}function wt(n,t,e){n=St(n),t=St(t),e=St(e);var r=vt((.4124564*n+.3575761*t+.1804375*e)/Xa),u=vt((.2126729*n+.7151522*t+.072175*e)/$a),i=vt((.0193339*n+.119192*t+.9503041*e)/Ba);return ft(116*u-16,500*(r-u),200*(u-i))}function St(n){return(n/=255)<=.04045?n/12.92:Math.pow((n+.055)/1.055,2.4)}function kt(n){var t=parseFloat(n);return"%"===n.charAt(n.length-1)?Math.round(2.55*t):t}function Et(n){return"function"==typeof n?n:function(){return n}}function At(n){return function(t,e,r){return 2===arguments.length&&"function"==typeof e&&(r=e,e=null),Nt(t,e,n,r)}}function Nt(n,t,e,r){function u(){var n,t=c.status;if(!t&&zt(c)||t>=200&&300>t||304===t){try{n=e.call(i,c)}catch(r){return void o.error.call(i,r)}o.load.call(i,n)}else o.error.call(i,c)}var i={},o=ta.dispatch("beforesend","progress","load","error"),a={},c=new XMLHttpRequest,l=null;return!this.XDomainRequest||"withCredentials"in c||!/^(http(s)?:)?\/\//.test(n)||(c=new XDomainRequest),"onload"in c?c.onload=c.onerror=u:c.onreadystatechange=function(){c.readyState>3&&u()},c.onprogress=function(n){var t=ta.event;ta.event=n;try{o.progress.call(i,c)}finally{ta.event=t}},i.header=function(n,t){return n=(n+"").toLowerCase(),arguments.length<2?a[n]:(null==t?delete a[n]:a[n]=t+"",i)},i.mimeType=function(n){return arguments.length?(t=null==n?null:n+"",i):t},i.responseType=function(n){return arguments.length?(l=n,i):l},i.response=function(n){return e=n,i},["get","post"].forEach(function(n){i[n]=function(){return i.send.apply(i,[n].concat(ra(arguments)))}}),i.send=function(e,r,u){if(2===arguments.length&&"function"==typeof r&&(u=r,r=null),c.open(e,n,!0),null==t||"accept"in a||(a.accept=t+",*/*"),c.setRequestHeader)for(var s in a)c.setRequestHeader(s,a[s]);return null!=t&&c.overrideMimeType&&c.overrideMimeType(t),null!=l&&(c.responseType=l),null!=u&&i.on("error",u).on("load",function(n){u(null,n)}),o.beforesend.call(i,c),c.send(null==r?null:r),i},i.abort=function(){return c.abort(),i},ta.rebind(i,o,"on"),null==r?i:i.get(Ct(r))}function Ct(n){return 1===n.length?function(t,e){n(null==t?e:null)}:n}function zt(n){var t=n.responseType;return t&&"text"!==t?n.response:n.responseText}function qt(){var n=Lt(),t=Tt()-n;t>24?(isFinite(t)&&(clearTimeout(tc),tc=setTimeout(qt,t)),nc=0):(nc=1,rc(qt))}function Lt(){var n=Date.now();for(ec=Ka;ec;)n>=ec.t&&(ec.f=ec.c(n-ec.t)),ec=ec.n;return n}function Tt(){for(var n,t=Ka,e=1/0;t;)t.f?t=n?n.n=t.n:Ka=t.n:(t.t<e&&(e=t.t),t=(n=t).n);return Qa=n,e}function Rt(n,t){return t-(n?Math.ceil(Math.log(n)/Math.LN10):1)}function Dt(n,t){var e=Math.pow(10,3*ga(8-t));return{scale:t>8?function(n){return n/e}:function(n){return n*e},symbol:n}}function Pt(n){var t=n.decimal,e=n.thousands,r=n.grouping,u=n.currency,i=r&&e?function(n,t){for(var u=n.length,i=[],o=0,a=r[0],c=0;u>0&&a>0&&(c+a+1>t&&(a=Math.max(1,t-c)),i.push(n.substring(u-=a,u+a)),!((c+=a+1)>t));)a=r[o=(o+1)%r.length];return i.reverse().join(e)}:y;return function(n){var e=ic.exec(n),r=e[1]||" ",o=e[2]||">",a=e[3]||"-",c=e[4]||"",l=e[5],s=+e[6],f=e[7],h=e[8],g=e[9],p=1,v="",d="",m=!1,y=!0;switch(h&&(h=+h.substring(1)),(l||"0"===r&&"="===o)&&(l=r="0",o="="),g){case"n":f=!0,g="g";break;case"%":p=100,d="%",g="f";break;case"p":p=100,d="%",g="r";break;case"b":case"o":case"x":case"X":"#"===c&&(v="0"+g.toLowerCase());case"c":y=!1;case"d":m=!0,h=0;break;case"s":p=-1,g="r"}"$"===c&&(v=u[0],d=u[1]),"r"!=g||h||(g="g"),null!=h&&("g"==g?h=Math.max(1,Math.min(21,h)):("e"==g||"f"==g)&&(h=Math.max(0,Math.min(20,h)))),g=oc.get(g)||Ut;var M=l&&f;return function(n){var e=d;if(m&&n%1)return"";var u=0>n||0===n&&0>1/n?(n=-n,"-"):"-"===a?"":a;if(0>p){var c=ta.formatPrefix(n,h);n=c.scale(n),e=c.symbol+d}else n*=p;n=g(n,h);var x,b,_=n.lastIndexOf(".");if(0>_){var w=y?n.lastIndexOf("e"):-1;0>w?(x=n,b=""):(x=n.substring(0,w),b=n.substring(w))}else x=n.substring(0,_),b=t+n.substring(_+1);!l&&f&&(x=i(x,1/0));var S=v.length+x.length+b.length+(M?0:u.length),k=s>S?new Array(S=s-S+1).join(r):"";return M&&(x=i(k+x,k.length?s-b.length:1/0)),u+=v,n=x+b,("<"===o?u+n+k:">"===o?k+u+n:"^"===o?k.substring(0,S>>=1)+u+n+k.substring(S):u+(M?n:k+n))+e}}}function Ut(n){return n+""}function jt(){this._=new Date(arguments.length>1?Date.UTC.apply(this,arguments):arguments[0])}function Ft(n,t,e){function r(t){var e=n(t),r=i(e,1);return r-t>t-e?e:r}function u(e){return t(e=n(new cc(e-1)),1),e}function i(n,e){return t(n=new cc(+n),e),n}function o(n,r,i){var o=u(n),a=[];if(i>1)for(;r>o;)e(o)%i||a.push(new Date(+o)),t(o,1);else for(;r>o;)a.push(new Date(+o)),t(o,1);return a}function a(n,t,e){try{cc=jt;var r=new jt;return r._=n,o(r,t,e)}finally{cc=Date}}n.floor=n,n.round=r,n.ceil=u,n.offset=i,n.range=o;var c=n.utc=Ht(n);return c.floor=c,c.round=Ht(r),c.ceil=Ht(u),c.offset=Ht(i),c.range=a,n}function Ht(n){return function(t,e){try{cc=jt;var r=new jt;return r._=t,n(r,e)._}finally{cc=Date}}}function Ot(n){function t(n){function t(t){for(var e,u,i,o=[],a=-1,c=0;++a<r;)37===n.charCodeAt(a)&&(o.push(n.slice(c,a)),null!=(u=sc[e=n.charAt(++a)])&&(e=n.charAt(++a)),(i=N[e])&&(e=i(t,null==u?"e"===e?" ":"0":u)),o.push(e),c=a+1);return o.push(n.slice(c,a)),o.join("")}var r=n.length;return t.parse=function(t){var r={y:1900,m:0,d:1,H:0,M:0,S:0,L:0,Z:null},u=e(r,n,t,0);if(u!=t.length)return null;"p"in r&&(r.H=r.H%12+12*r.p);var i=null!=r.Z&&cc!==jt,o=new(i?jt:cc);return"j"in r?o.setFullYear(r.y,0,r.j):"w"in r&&("W"in r||"U"in r)?(o.setFullYear(r.y,0,1),o.setFullYear(r.y,0,"W"in r?(r.w+6)%7+7*r.W-(o.getDay()+5)%7:r.w+7*r.U-(o.getDay()+6)%7)):o.setFullYear(r.y,r.m,r.d),o.setHours(r.H+(r.Z/100|0),r.M+r.Z%100,r.S,r.L),i?o._:o},t.toString=function(){return n},t}function e(n,t,e,r){for(var u,i,o,a=0,c=t.length,l=e.length;c>a;){if(r>=l)return-1;if(u=t.charCodeAt(a++),37===u){if(o=t.charAt(a++),i=C[o in sc?t.charAt(a++):o],!i||(r=i(n,e,r))<0)return-1}else if(u!=e.charCodeAt(r++))return-1}return r}function r(n,t,e){_.lastIndex=0;var r=_.exec(t.slice(e));return r?(n.w=w.get(r[0].toLowerCase()),e+r[0].length):-1}function u(n,t,e){x.lastIndex=0;var r=x.exec(t.slice(e));return r?(n.w=b.get(r[0].toLowerCase()),e+r[0].length):-1}function i(n,t,e){E.lastIndex=0;var r=E.exec(t.slice(e));return r?(n.m=A.get(r[0].toLowerCase()),e+r[0].length):-1}function o(n,t,e){S.lastIndex=0;var r=S.exec(t.slice(e));return r?(n.m=k.get(r[0].toLowerCase()),e+r[0].length):-1}function a(n,t,r){return e(n,N.c.toString(),t,r)}function c(n,t,r){return e(n,N.x.toString(),t,r)}function l(n,t,r){return e(n,N.X.toString(),t,r)}function s(n,t,e){var r=M.get(t.slice(e,e+=2).toLowerCase());return null==r?-1:(n.p=r,e)}var f=n.dateTime,h=n.date,g=n.time,p=n.periods,v=n.days,d=n.shortDays,m=n.months,y=n.shortMonths;t.utc=function(n){function e(n){try{cc=jt;var t=new cc;return t._=n,r(t)}finally{cc=Date}}var r=t(n);return e.parse=function(n){try{cc=jt;var t=r.parse(n);return t&&t._}finally{cc=Date}},e.toString=r.toString,e},t.multi=t.utc.multi=ae;var M=ta.map(),x=Yt(v),b=Zt(v),_=Yt(d),w=Zt(d),S=Yt(m),k=Zt(m),E=Yt(y),A=Zt(y);p.forEach(function(n,t){M.set(n.toLowerCase(),t)});var N={a:function(n){return d[n.getDay()]},A:function(n){return v[n.getDay()]},b:function(n){return y[n.getMonth()]},B:function(n){return m[n.getMonth()]},c:t(f),d:function(n,t){return It(n.getDate(),t,2)},e:function(n,t){return It(n.getDate(),t,2)},H:function(n,t){return It(n.getHours(),t,2)},I:function(n,t){return It(n.getHours()%12||12,t,2)},j:function(n,t){return It(1+ac.dayOfYear(n),t,3)},L:function(n,t){return It(n.getMilliseconds(),t,3)},m:function(n,t){return It(n.getMonth()+1,t,2)},M:function(n,t){return It(n.getMinutes(),t,2)},p:function(n){return p[+(n.getHours()>=12)]},S:function(n,t){return It(n.getSeconds(),t,2)},U:function(n,t){return It(ac.sundayOfYear(n),t,2)},w:function(n){return n.getDay()},W:function(n,t){return It(ac.mondayOfYear(n),t,2)},x:t(h),X:t(g),y:function(n,t){return It(n.getFullYear()%100,t,2)},Y:function(n,t){return It(n.getFullYear()%1e4,t,4)},Z:ie,"%":function(){return"%"}},C={a:r,A:u,b:i,B:o,c:a,d:Qt,e:Qt,H:te,I:te,j:ne,L:ue,m:Kt,M:ee,p:s,S:re,U:Xt,w:Vt,W:$t,x:c,X:l,y:Wt,Y:Bt,Z:Jt,"%":oe};return t}function It(n,t,e){var r=0>n?"-":"",u=(r?-n:n)+"",i=u.length;return r+(e>i?new Array(e-i+1).join(t)+u:u)}function Yt(n){return new RegExp("^(?:"+n.map(ta.requote).join("|")+")","i")}function Zt(n){for(var t=new l,e=-1,r=n.length;++e<r;)t.set(n[e].toLowerCase(),e);return t}function Vt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+1));return r?(n.w=+r[0],e+r[0].length):-1}function Xt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e));return r?(n.U=+r[0],e+r[0].length):-1}function $t(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e));return r?(n.W=+r[0],e+r[0].length):-1}function Bt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+4));return r?(n.y=+r[0],e+r[0].length):-1}function Wt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.y=Gt(+r[0]),e+r[0].length):-1}function Jt(n,t,e){return/^[+-]\d{4}$/.test(t=t.slice(e,e+5))?(n.Z=-t,e+5):-1}function Gt(n){return n+(n>68?1900:2e3)}function Kt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.m=r[0]-1,e+r[0].length):-1}function Qt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.d=+r[0],e+r[0].length):-1}function ne(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+3));return r?(n.j=+r[0],e+r[0].length):-1}function te(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.H=+r[0],e+r[0].length):-1}function ee(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.M=+r[0],e+r[0].length):-1}function re(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.S=+r[0],e+r[0].length):-1}function ue(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+3));return r?(n.L=+r[0],e+r[0].length):-1}function ie(n){var t=n.getTimezoneOffset(),e=t>0?"-":"+",r=ga(t)/60|0,u=ga(t)%60;return e+It(r,"0",2)+It(u,"0",2)}function oe(n,t,e){hc.lastIndex=0;var r=hc.exec(t.slice(e,e+1));return r?e+r[0].length:-1}function ae(n){for(var t=n.length,e=-1;++e<t;)n[e][0]=this(n[e][0]);return function(t){for(var e=0,r=n[e];!r[1](t);)r=n[++e];return r[0](t)}}function ce(){}function le(n,t,e){var r=e.s=n+t,u=r-n,i=r-u;e.t=n-i+(t-u)}function se(n,t){n&&dc.hasOwnProperty(n.type)&&dc[n.type](n,t)}function fe(n,t,e){var r,u=-1,i=n.length-e;for(t.lineStart();++u<i;)r=n[u],t.point(r[0],r[1],r[2]);t.lineEnd()}function he(n,t){var e=-1,r=n.length;for(t.polygonStart();++e<r;)fe(n[e],t,1);t.polygonEnd()}function ge(){function n(n,t){n*=Da,t=t*Da/2+qa/4;var e=n-r,o=e>=0?1:-1,a=o*e,c=Math.cos(t),l=Math.sin(t),s=i*l,f=u*c+s*Math.cos(a),h=s*o*Math.sin(a);yc.add(Math.atan2(h,f)),r=n,u=c,i=l}var t,e,r,u,i;Mc.point=function(o,a){Mc.point=n,r=(t=o)*Da,u=Math.cos(a=(e=a)*Da/2+qa/4),i=Math.sin(a)},Mc.lineEnd=function(){n(t,e)}}function pe(n){var t=n[0],e=n[1],r=Math.cos(e);return[r*Math.cos(t),r*Math.sin(t),Math.sin(e)]}function ve(n,t){return n[0]*t[0]+n[1]*t[1]+n[2]*t[2]}function de(n,t){return[n[1]*t[2]-n[2]*t[1],n[2]*t[0]-n[0]*t[2],n[0]*t[1]-n[1]*t[0]]}function me(n,t){n[0]+=t[0],n[1]+=t[1],n[2]+=t[2]}function ye(n,t){return[n[0]*t,n[1]*t,n[2]*t]}function Me(n){var t=Math.sqrt(n[0]*n[0]+n[1]*n[1]+n[2]*n[2]);n[0]/=t,n[1]/=t,n[2]/=t}function xe(n){return[Math.atan2(n[1],n[0]),tt(n[2])]}function be(n,t){return ga(n[0]-t[0])<Ca&&ga(n[1]-t[1])<Ca}function _e(n,t){n*=Da;var e=Math.cos(t*=Da);we(e*Math.cos(n),e*Math.sin(n),Math.sin(t))}function we(n,t,e){++xc,_c+=(n-_c)/xc,wc+=(t-wc)/xc,Sc+=(e-Sc)/xc}function Se(){function n(n,u){n*=Da;var i=Math.cos(u*=Da),o=i*Math.cos(n),a=i*Math.sin(n),c=Math.sin(u),l=Math.atan2(Math.sqrt((l=e*c-r*a)*l+(l=r*o-t*c)*l+(l=t*a-e*o)*l),t*o+e*a+r*c);bc+=l,kc+=l*(t+(t=o)),Ec+=l*(e+(e=a)),Ac+=l*(r+(r=c)),we(t,e,r)}var t,e,r;qc.point=function(u,i){u*=Da;var o=Math.cos(i*=Da);t=o*Math.cos(u),e=o*Math.sin(u),r=Math.sin(i),qc.point=n,we(t,e,r)}}function ke(){qc.point=_e}function Ee(){function n(n,t){n*=Da;var e=Math.cos(t*=Da),o=e*Math.cos(n),a=e*Math.sin(n),c=Math.sin(t),l=u*c-i*a,s=i*o-r*c,f=r*a-u*o,h=Math.sqrt(l*l+s*s+f*f),g=r*o+u*a+i*c,p=h&&-nt(g)/h,v=Math.atan2(h,g);Nc+=p*l,Cc+=p*s,zc+=p*f,bc+=v,kc+=v*(r+(r=o)),Ec+=v*(u+(u=a)),Ac+=v*(i+(i=c)),we(r,u,i)}var t,e,r,u,i;qc.point=function(o,a){t=o,e=a,qc.point=n,o*=Da;var c=Math.cos(a*=Da);r=c*Math.cos(o),u=c*Math.sin(o),i=Math.sin(a),we(r,u,i)},qc.lineEnd=function(){n(t,e),qc.lineEnd=ke,qc.point=_e}}function Ae(n,t){function e(e,r){return e=n(e,r),t(e[0],e[1])}return n.invert&&t.invert&&(e.invert=function(e,r){return e=t.invert(e,r),e&&n.invert(e[0],e[1])}),e}function Ne(){return!0}function Ce(n,t,e,r,u){var i=[],o=[];if(n.forEach(function(n){if(!((t=n.length-1)<=0)){var t,e=n[0],r=n[t];if(be(e,r)){u.lineStart();for(var a=0;t>a;++a)u.point((e=n[a])[0],e[1]);return void u.lineEnd()}var c=new qe(e,n,null,!0),l=new qe(e,null,c,!1);c.o=l,i.push(c),o.push(l),c=new qe(r,n,null,!1),l=new qe(r,null,c,!0),c.o=l,i.push(c),o.push(l)}}),o.sort(t),ze(i),ze(o),i.length){for(var a=0,c=e,l=o.length;l>a;++a)o[a].e=c=!c;for(var s,f,h=i[0];;){for(var g=h,p=!0;g.v;)if((g=g.n)===h)return;s=g.z,u.lineStart();do{if(g.v=g.o.v=!0,g.e){if(p)for(var a=0,l=s.length;l>a;++a)u.point((f=s[a])[0],f[1]);else r(g.x,g.n.x,1,u);g=g.n}else{if(p){s=g.p.z;for(var a=s.length-1;a>=0;--a)u.point((f=s[a])[0],f[1])}else r(g.x,g.p.x,-1,u);g=g.p}g=g.o,s=g.z,p=!p}while(!g.v);u.lineEnd()}}}function ze(n){if(t=n.length){for(var t,e,r=0,u=n[0];++r<t;)u.n=e=n[r],e.p=u,u=e;u.n=e=n[0],e.p=u}}function qe(n,t,e,r){this.x=n,this.z=t,this.o=e,this.e=r,this.v=!1,this.n=this.p=null}function Le(n,t,e,r){return function(u,i){function o(t,e){var r=u(t,e);n(t=r[0],e=r[1])&&i.point(t,e)}function a(n,t){var e=u(n,t);d.point(e[0],e[1])}function c(){y.point=a,d.lineStart()}function l(){y.point=o,d.lineEnd()}function s(n,t){v.push([n,t]);var e=u(n,t);x.point(e[0],e[1])}function f(){x.lineStart(),v=[]}function h(){s(v[0][0],v[0][1]),x.lineEnd();var n,t=x.clean(),e=M.buffer(),r=e.length;if(v.pop(),p.push(v),v=null,r)if(1&t){n=e[0];var u,r=n.length-1,o=-1;if(r>0){for(b||(i.polygonStart(),b=!0),i.lineStart();++o<r;)i.point((u=n[o])[0],u[1]);i.lineEnd()}}else r>1&&2&t&&e.push(e.pop().concat(e.shift())),g.push(e.filter(Te))}var g,p,v,d=t(i),m=u.invert(r[0],r[1]),y={point:o,lineStart:c,lineEnd:l,polygonStart:function(){y.point=s,y.lineStart=f,y.lineEnd=h,g=[],p=[]},polygonEnd:function(){y.point=o,y.lineStart=c,y.lineEnd=l,g=ta.merge(g);var n=Fe(m,p);g.length?(b||(i.polygonStart(),b=!0),Ce(g,De,n,e,i)):n&&(b||(i.polygonStart(),b=!0),i.lineStart(),e(null,null,1,i),i.lineEnd()),b&&(i.polygonEnd(),b=!1),g=p=null},sphere:function(){i.polygonStart(),i.lineStart(),e(null,null,1,i),i.lineEnd(),i.polygonEnd()}},M=Re(),x=t(M),b=!1;return y}}function Te(n){return n.length>1}function Re(){var n,t=[];return{lineStart:function(){t.push(n=[])},point:function(t,e){n.push([t,e])},lineEnd:b,buffer:function(){var e=t;return t=[],n=null,e},rejoin:function(){t.length>1&&t.push(t.pop().concat(t.shift()))}}}function De(n,t){return((n=n.x)[0]<0?n[1]-Ra-Ca:Ra-n[1])-((t=t.x)[0]<0?t[1]-Ra-Ca:Ra-t[1])}function Pe(n){var t,e=0/0,r=0/0,u=0/0;return{lineStart:function(){n.lineStart(),t=1},point:function(i,o){var a=i>0?qa:-qa,c=ga(i-e);ga(c-qa)<Ca?(n.point(e,r=(r+o)/2>0?Ra:-Ra),n.point(u,r),n.lineEnd(),n.lineStart(),n.point(a,r),n.point(i,r),t=0):u!==a&&c>=qa&&(ga(e-u)<Ca&&(e-=u*Ca),ga(i-a)<Ca&&(i-=a*Ca),r=Ue(e,r,i,o),n.point(u,r),n.lineEnd(),n.lineStart(),n.point(a,r),t=0),n.point(e=i,r=o),u=a},lineEnd:function(){n.lineEnd(),e=r=0/0},clean:function(){return 2-t}}}function Ue(n,t,e,r){var u,i,o=Math.sin(n-e);return ga(o)>Ca?Math.atan((Math.sin(t)*(i=Math.cos(r))*Math.sin(e)-Math.sin(r)*(u=Math.cos(t))*Math.sin(n))/(u*i*o)):(t+r)/2}function je(n,t,e,r){var u;if(null==n)u=e*Ra,r.point(-qa,u),r.point(0,u),r.point(qa,u),r.point(qa,0),r.point(qa,-u),r.point(0,-u),r.point(-qa,-u),r.point(-qa,0),r.point(-qa,u);else if(ga(n[0]-t[0])>Ca){var i=n[0]<t[0]?qa:-qa;u=e*i/2,r.point(-i,u),r.point(0,u),r.point(i,u)}else r.point(t[0],t[1])}function Fe(n,t){var e=n[0],r=n[1],u=[Math.sin(e),-Math.cos(e),0],i=0,o=0;yc.reset();for(var a=0,c=t.length;c>a;++a){var l=t[a],s=l.length;if(s)for(var f=l[0],h=f[0],g=f[1]/2+qa/4,p=Math.sin(g),v=Math.cos(g),d=1;;){d===s&&(d=0),n=l[d];var m=n[0],y=n[1]/2+qa/4,M=Math.sin(y),x=Math.cos(y),b=m-h,_=b>=0?1:-1,w=_*b,S=w>qa,k=p*M;if(yc.add(Math.atan2(k*_*Math.sin(w),v*x+k*Math.cos(w))),i+=S?b+_*La:b,S^h>=e^m>=e){var E=de(pe(f),pe(n));Me(E);var A=de(u,E);Me(A);var N=(S^b>=0?-1:1)*tt(A[2]);(r>N||r===N&&(E[0]||E[1]))&&(o+=S^b>=0?1:-1)}if(!d++)break;h=m,p=M,v=x,f=n}}return(-Ca>i||Ca>i&&0>yc)^1&o}function He(n){function t(n,t){return Math.cos(n)*Math.cos(t)>i}function e(n){var e,i,c,l,s;return{lineStart:function(){l=c=!1,s=1},point:function(f,h){var g,p=[f,h],v=t(f,h),d=o?v?0:u(f,h):v?u(f+(0>f?qa:-qa),h):0;if(!e&&(l=c=v)&&n.lineStart(),v!==c&&(g=r(e,p),(be(e,g)||be(p,g))&&(p[0]+=Ca,p[1]+=Ca,v=t(p[0],p[1]))),v!==c)s=0,v?(n.lineStart(),g=r(p,e),n.point(g[0],g[1])):(g=r(e,p),n.point(g[0],g[1]),n.lineEnd()),e=g;else if(a&&e&&o^v){var m;d&i||!(m=r(p,e,!0))||(s=0,o?(n.lineStart(),n.point(m[0][0],m[0][1]),n.point(m[1][0],m[1][1]),n.lineEnd()):(n.point(m[1][0],m[1][1]),n.lineEnd(),n.lineStart(),n.point(m[0][0],m[0][1])))}!v||e&&be(e,p)||n.point(p[0],p[1]),e=p,c=v,i=d},lineEnd:function(){c&&n.lineEnd(),e=null},clean:function(){return s|(l&&c)<<1}}}function r(n,t,e){var r=pe(n),u=pe(t),o=[1,0,0],a=de(r,u),c=ve(a,a),l=a[0],s=c-l*l;if(!s)return!e&&n;var f=i*c/s,h=-i*l/s,g=de(o,a),p=ye(o,f),v=ye(a,h);me(p,v);var d=g,m=ve(p,d),y=ve(d,d),M=m*m-y*(ve(p,p)-1);if(!(0>M)){var x=Math.sqrt(M),b=ye(d,(-m-x)/y);if(me(b,p),b=xe(b),!e)return b;var _,w=n[0],S=t[0],k=n[1],E=t[1];w>S&&(_=w,w=S,S=_);var A=S-w,N=ga(A-qa)<Ca,C=N||Ca>A;if(!N&&k>E&&(_=k,k=E,E=_),C?N?k+E>0^b[1]<(ga(b[0]-w)<Ca?k:E):k<=b[1]&&b[1]<=E:A>qa^(w<=b[0]&&b[0]<=S)){var z=ye(d,(-m+x)/y);return me(z,p),[b,xe(z)]}}}function u(t,e){var r=o?n:qa-n,u=0;return-r>t?u|=1:t>r&&(u|=2),-r>e?u|=4:e>r&&(u|=8),u}var i=Math.cos(n),o=i>0,a=ga(i)>Ca,c=gr(n,6*Da);return Le(t,e,c,o?[0,-n]:[-qa,n-qa])}function Oe(n,t,e,r){return function(u){var i,o=u.a,a=u.b,c=o.x,l=o.y,s=a.x,f=a.y,h=0,g=1,p=s-c,v=f-l;if(i=n-c,p||!(i>0)){if(i/=p,0>p){if(h>i)return;g>i&&(g=i)}else if(p>0){if(i>g)return;i>h&&(h=i)}if(i=e-c,p||!(0>i)){if(i/=p,0>p){if(i>g)return;i>h&&(h=i)}else if(p>0){if(h>i)return;g>i&&(g=i)}if(i=t-l,v||!(i>0)){if(i/=v,0>v){if(h>i)return;g>i&&(g=i)}else if(v>0){if(i>g)return;i>h&&(h=i)}if(i=r-l,v||!(0>i)){if(i/=v,0>v){if(i>g)return;i>h&&(h=i)}else if(v>0){if(h>i)return;g>i&&(g=i)}return h>0&&(u.a={x:c+h*p,y:l+h*v}),1>g&&(u.b={x:c+g*p,y:l+g*v}),u}}}}}}function Ie(n,t,e,r){function u(r,u){return ga(r[0]-n)<Ca?u>0?0:3:ga(r[0]-e)<Ca?u>0?2:1:ga(r[1]-t)<Ca?u>0?1:0:u>0?3:2}function i(n,t){return o(n.x,t.x)}function o(n,t){var e=u(n,1),r=u(t,1);return e!==r?e-r:0===e?t[1]-n[1]:1===e?n[0]-t[0]:2===e?n[1]-t[1]:t[0]-n[0]}return function(a){function c(n){for(var t=0,e=d.length,r=n[1],u=0;e>u;++u)for(var i,o=1,a=d[u],c=a.length,l=a[0];c>o;++o)i=a[o],l[1]<=r?i[1]>r&&Q(l,i,n)>0&&++t:i[1]<=r&&Q(l,i,n)<0&&--t,l=i;return 0!==t}function l(i,a,c,l){var s=0,f=0;if(null==i||(s=u(i,c))!==(f=u(a,c))||o(i,a)<0^c>0){do l.point(0===s||3===s?n:e,s>1?r:t);while((s=(s+c+4)%4)!==f)}else l.point(a[0],a[1])}function s(u,i){return u>=n&&e>=u&&i>=t&&r>=i}function f(n,t){s(n,t)&&a.point(n,t)}function h(){C.point=p,d&&d.push(m=[]),S=!0,w=!1,b=_=0/0}function g(){v&&(p(y,M),x&&w&&A.rejoin(),v.push(A.buffer())),C.point=f,w&&a.lineEnd()}function p(n,t){n=Math.max(-Tc,Math.min(Tc,n)),t=Math.max(-Tc,Math.min(Tc,t));var e=s(n,t);if(d&&m.push([n,t]),S)y=n,M=t,x=e,S=!1,e&&(a.lineStart(),a.point(n,t));else if(e&&w)a.point(n,t);else{var r={a:{x:b,y:_},b:{x:n,y:t}};N(r)?(w||(a.lineStart(),a.point(r.a.x,r.a.y)),a.point(r.b.x,r.b.y),e||a.lineEnd(),k=!1):e&&(a.lineStart(),a.point(n,t),k=!1)}b=n,_=t,w=e}var v,d,m,y,M,x,b,_,w,S,k,E=a,A=Re(),N=Oe(n,t,e,r),C={point:f,lineStart:h,lineEnd:g,polygonStart:function(){a=A,v=[],d=[],k=!0},polygonEnd:function(){a=E,v=ta.merge(v);var t=c([n,r]),e=k&&t,u=v.length;(e||u)&&(a.polygonStart(),e&&(a.lineStart(),l(null,null,1,a),a.lineEnd()),u&&Ce(v,i,t,l,a),a.polygonEnd()),v=d=m=null}};return C}}function Ye(n){var t=0,e=qa/3,r=ir(n),u=r(t,e);return u.parallels=function(n){return arguments.length?r(t=n[0]*qa/180,e=n[1]*qa/180):[t/qa*180,e/qa*180]},u}function Ze(n,t){function e(n,t){var e=Math.sqrt(i-2*u*Math.sin(t))/u;return[e*Math.sin(n*=u),o-e*Math.cos(n)]}var r=Math.sin(n),u=(r+Math.sin(t))/2,i=1+r*(2*u-r),o=Math.sqrt(i)/u;return e.invert=function(n,t){var e=o-t;return[Math.atan2(n,e)/u,tt((i-(n*n+e*e)*u*u)/(2*u))]},e}function Ve(){function n(n,t){Dc+=u*n-r*t,r=n,u=t}var t,e,r,u;Hc.point=function(i,o){Hc.point=n,t=r=i,e=u=o},Hc.lineEnd=function(){n(t,e)}}function Xe(n,t){Pc>n&&(Pc=n),n>jc&&(jc=n),Uc>t&&(Uc=t),t>Fc&&(Fc=t)}function $e(){function n(n,t){o.push("M",n,",",t,i)}function t(n,t){o.push("M",n,",",t),a.point=e}function e(n,t){o.push("L",n,",",t)}function r(){a.point=n}function u(){o.push("Z")}var i=Be(4.5),o=[],a={point:n,lineStart:function(){a.point=t},lineEnd:r,polygonStart:function(){a.lineEnd=u},polygonEnd:function(){a.lineEnd=r,a.point=n},pointRadius:function(n){return i=Be(n),a},result:function(){if(o.length){var n=o.join("");return o=[],n}}};return a}function Be(n){return"m0,"+n+"a"+n+","+n+" 0 1,1 0,"+-2*n+"a"+n+","+n+" 0 1,1 0,"+2*n+"z"}function We(n,t){_c+=n,wc+=t,++Sc}function Je(){function n(n,r){var u=n-t,i=r-e,o=Math.sqrt(u*u+i*i);kc+=o*(t+n)/2,Ec+=o*(e+r)/2,Ac+=o,We(t=n,e=r)}var t,e;Ic.point=function(r,u){Ic.point=n,We(t=r,e=u)}}function Ge(){Ic.point=We}function Ke(){function n(n,t){var e=n-r,i=t-u,o=Math.sqrt(e*e+i*i);kc+=o*(r+n)/2,Ec+=o*(u+t)/2,Ac+=o,o=u*n-r*t,Nc+=o*(r+n),Cc+=o*(u+t),zc+=3*o,We(r=n,u=t)}var t,e,r,u;Ic.point=function(i,o){Ic.point=n,We(t=r=i,e=u=o)},Ic.lineEnd=function(){n(t,e)}}function Qe(n){function t(t,e){n.moveTo(t+o,e),n.arc(t,e,o,0,La)}function e(t,e){n.moveTo(t,e),a.point=r}function r(t,e){n.lineTo(t,e)}function u(){a.point=t}function i(){n.closePath()}var o=4.5,a={point:t,lineStart:function(){a.point=e},lineEnd:u,polygonStart:function(){a.lineEnd=i},polygonEnd:function(){a.lineEnd=u,a.point=t},pointRadius:function(n){return o=n,a},result:b};return a}function nr(n){function t(n){return(a?r:e)(n)}function e(t){return rr(t,function(e,r){e=n(e,r),t.point(e[0],e[1])})}function r(t){function e(e,r){e=n(e,r),t.point(e[0],e[1])}function r(){M=0/0,S.point=i,t.lineStart()}function i(e,r){var i=pe([e,r]),o=n(e,r);u(M,x,y,b,_,w,M=o[0],x=o[1],y=e,b=i[0],_=i[1],w=i[2],a,t),t.point(M,x)}function o(){S.point=e,t.lineEnd()}function c(){r(),S.point=l,S.lineEnd=s}function l(n,t){i(f=n,h=t),g=M,p=x,v=b,d=_,m=w,S.point=i}function s(){u(M,x,y,b,_,w,g,p,f,v,d,m,a,t),S.lineEnd=o,o()}var f,h,g,p,v,d,m,y,M,x,b,_,w,S={point:e,lineStart:r,lineEnd:o,polygonStart:function(){t.polygonStart(),S.lineStart=c
+},polygonEnd:function(){t.polygonEnd(),S.lineStart=r}};return S}function u(t,e,r,a,c,l,s,f,h,g,p,v,d,m){var y=s-t,M=f-e,x=y*y+M*M;if(x>4*i&&d--){var b=a+g,_=c+p,w=l+v,S=Math.sqrt(b*b+_*_+w*w),k=Math.asin(w/=S),E=ga(ga(w)-1)<Ca||ga(r-h)<Ca?(r+h)/2:Math.atan2(_,b),A=n(E,k),N=A[0],C=A[1],z=N-t,q=C-e,L=M*z-y*q;(L*L/x>i||ga((y*z+M*q)/x-.5)>.3||o>a*g+c*p+l*v)&&(u(t,e,r,a,c,l,N,C,E,b/=S,_/=S,w,d,m),m.point(N,C),u(N,C,E,b,_,w,s,f,h,g,p,v,d,m))}}var i=.5,o=Math.cos(30*Da),a=16;return t.precision=function(n){return arguments.length?(a=(i=n*n)>0&&16,t):Math.sqrt(i)},t}function tr(n){var t=nr(function(t,e){return n([t*Pa,e*Pa])});return function(n){return or(t(n))}}function er(n){this.stream=n}function rr(n,t){return{point:t,sphere:function(){n.sphere()},lineStart:function(){n.lineStart()},lineEnd:function(){n.lineEnd()},polygonStart:function(){n.polygonStart()},polygonEnd:function(){n.polygonEnd()}}}function ur(n){return ir(function(){return n})()}function ir(n){function t(n){return n=a(n[0]*Da,n[1]*Da),[n[0]*h+c,l-n[1]*h]}function e(n){return n=a.invert((n[0]-c)/h,(l-n[1])/h),n&&[n[0]*Pa,n[1]*Pa]}function r(){a=Ae(o=lr(m,M,x),i);var n=i(v,d);return c=g-n[0]*h,l=p+n[1]*h,u()}function u(){return s&&(s.valid=!1,s=null),t}var i,o,a,c,l,s,f=nr(function(n,t){return n=i(n,t),[n[0]*h+c,l-n[1]*h]}),h=150,g=480,p=250,v=0,d=0,m=0,M=0,x=0,b=Lc,_=y,w=null,S=null;return t.stream=function(n){return s&&(s.valid=!1),s=or(b(o,f(_(n)))),s.valid=!0,s},t.clipAngle=function(n){return arguments.length?(b=null==n?(w=n,Lc):He((w=+n)*Da),u()):w},t.clipExtent=function(n){return arguments.length?(S=n,_=n?Ie(n[0][0],n[0][1],n[1][0],n[1][1]):y,u()):S},t.scale=function(n){return arguments.length?(h=+n,r()):h},t.translate=function(n){return arguments.length?(g=+n[0],p=+n[1],r()):[g,p]},t.center=function(n){return arguments.length?(v=n[0]%360*Da,d=n[1]%360*Da,r()):[v*Pa,d*Pa]},t.rotate=function(n){return arguments.length?(m=n[0]%360*Da,M=n[1]%360*Da,x=n.length>2?n[2]%360*Da:0,r()):[m*Pa,M*Pa,x*Pa]},ta.rebind(t,f,"precision"),function(){return i=n.apply(this,arguments),t.invert=i.invert&&e,r()}}function or(n){return rr(n,function(t,e){n.point(t*Da,e*Da)})}function ar(n,t){return[n,t]}function cr(n,t){return[n>qa?n-La:-qa>n?n+La:n,t]}function lr(n,t,e){return n?t||e?Ae(fr(n),hr(t,e)):fr(n):t||e?hr(t,e):cr}function sr(n){return function(t,e){return t+=n,[t>qa?t-La:-qa>t?t+La:t,e]}}function fr(n){var t=sr(n);return t.invert=sr(-n),t}function hr(n,t){function e(n,t){var e=Math.cos(t),a=Math.cos(n)*e,c=Math.sin(n)*e,l=Math.sin(t),s=l*r+a*u;return[Math.atan2(c*i-s*o,a*r-l*u),tt(s*i+c*o)]}var r=Math.cos(n),u=Math.sin(n),i=Math.cos(t),o=Math.sin(t);return e.invert=function(n,t){var e=Math.cos(t),a=Math.cos(n)*e,c=Math.sin(n)*e,l=Math.sin(t),s=l*i-c*o;return[Math.atan2(c*i+l*o,a*r+s*u),tt(s*r-a*u)]},e}function gr(n,t){var e=Math.cos(n),r=Math.sin(n);return function(u,i,o,a){var c=o*t;null!=u?(u=pr(e,u),i=pr(e,i),(o>0?i>u:u>i)&&(u+=o*La)):(u=n+o*La,i=n-.5*c);for(var l,s=u;o>0?s>i:i>s;s-=c)a.point((l=xe([e,-r*Math.cos(s),-r*Math.sin(s)]))[0],l[1])}}function pr(n,t){var e=pe(t);e[0]-=n,Me(e);var r=nt(-e[1]);return((-e[2]<0?-r:r)+2*Math.PI-Ca)%(2*Math.PI)}function vr(n,t,e){var r=ta.range(n,t-Ca,e).concat(t);return function(n){return r.map(function(t){return[n,t]})}}function dr(n,t,e){var r=ta.range(n,t-Ca,e).concat(t);return function(n){return r.map(function(t){return[t,n]})}}function mr(n){return n.source}function yr(n){return n.target}function Mr(n,t,e,r){var u=Math.cos(t),i=Math.sin(t),o=Math.cos(r),a=Math.sin(r),c=u*Math.cos(n),l=u*Math.sin(n),s=o*Math.cos(e),f=o*Math.sin(e),h=2*Math.asin(Math.sqrt(it(r-t)+u*o*it(e-n))),g=1/Math.sin(h),p=h?function(n){var t=Math.sin(n*=h)*g,e=Math.sin(h-n)*g,r=e*c+t*s,u=e*l+t*f,o=e*i+t*a;return[Math.atan2(u,r)*Pa,Math.atan2(o,Math.sqrt(r*r+u*u))*Pa]}:function(){return[n*Pa,t*Pa]};return p.distance=h,p}function xr(){function n(n,u){var i=Math.sin(u*=Da),o=Math.cos(u),a=ga((n*=Da)-t),c=Math.cos(a);Yc+=Math.atan2(Math.sqrt((a=o*Math.sin(a))*a+(a=r*i-e*o*c)*a),e*i+r*o*c),t=n,e=i,r=o}var t,e,r;Zc.point=function(u,i){t=u*Da,e=Math.sin(i*=Da),r=Math.cos(i),Zc.point=n},Zc.lineEnd=function(){Zc.point=Zc.lineEnd=b}}function br(n,t){function e(t,e){var r=Math.cos(t),u=Math.cos(e),i=n(r*u);return[i*u*Math.sin(t),i*Math.sin(e)]}return e.invert=function(n,e){var r=Math.sqrt(n*n+e*e),u=t(r),i=Math.sin(u),o=Math.cos(u);return[Math.atan2(n*i,r*o),Math.asin(r&&e*i/r)]},e}function _r(n,t){function e(n,t){o>0?-Ra+Ca>t&&(t=-Ra+Ca):t>Ra-Ca&&(t=Ra-Ca);var e=o/Math.pow(u(t),i);return[e*Math.sin(i*n),o-e*Math.cos(i*n)]}var r=Math.cos(n),u=function(n){return Math.tan(qa/4+n/2)},i=n===t?Math.sin(n):Math.log(r/Math.cos(t))/Math.log(u(t)/u(n)),o=r*Math.pow(u(n),i)/i;return i?(e.invert=function(n,t){var e=o-t,r=K(i)*Math.sqrt(n*n+e*e);return[Math.atan2(n,e)/i,2*Math.atan(Math.pow(o/r,1/i))-Ra]},e):Sr}function wr(n,t){function e(n,t){var e=i-t;return[e*Math.sin(u*n),i-e*Math.cos(u*n)]}var r=Math.cos(n),u=n===t?Math.sin(n):(r-Math.cos(t))/(t-n),i=r/u+n;return ga(u)<Ca?ar:(e.invert=function(n,t){var e=i-t;return[Math.atan2(n,e)/u,i-K(u)*Math.sqrt(n*n+e*e)]},e)}function Sr(n,t){return[n,Math.log(Math.tan(qa/4+t/2))]}function kr(n){var t,e=ur(n),r=e.scale,u=e.translate,i=e.clipExtent;return e.scale=function(){var n=r.apply(e,arguments);return n===e?t?e.clipExtent(null):e:n},e.translate=function(){var n=u.apply(e,arguments);return n===e?t?e.clipExtent(null):e:n},e.clipExtent=function(n){var o=i.apply(e,arguments);if(o===e){if(t=null==n){var a=qa*r(),c=u();i([[c[0]-a,c[1]-a],[c[0]+a,c[1]+a]])}}else t&&(o=null);return o},e.clipExtent(null)}function Er(n,t){return[Math.log(Math.tan(qa/4+t/2)),-n]}function Ar(n){return n[0]}function Nr(n){return n[1]}function Cr(n){for(var t=n.length,e=[0,1],r=2,u=2;t>u;u++){for(;r>1&&Q(n[e[r-2]],n[e[r-1]],n[u])<=0;)--r;e[r++]=u}return e.slice(0,r)}function zr(n,t){return n[0]-t[0]||n[1]-t[1]}function qr(n,t,e){return(e[0]-t[0])*(n[1]-t[1])<(e[1]-t[1])*(n[0]-t[0])}function Lr(n,t,e,r){var u=n[0],i=e[0],o=t[0]-u,a=r[0]-i,c=n[1],l=e[1],s=t[1]-c,f=r[1]-l,h=(a*(c-l)-f*(u-i))/(f*o-a*s);return[u+h*o,c+h*s]}function Tr(n){var t=n[0],e=n[n.length-1];return!(t[0]-e[0]||t[1]-e[1])}function Rr(){tu(this),this.edge=this.site=this.circle=null}function Dr(n){var t=el.pop()||new Rr;return t.site=n,t}function Pr(n){Xr(n),Qc.remove(n),el.push(n),tu(n)}function Ur(n){var t=n.circle,e=t.x,r=t.cy,u={x:e,y:r},i=n.P,o=n.N,a=[n];Pr(n);for(var c=i;c.circle&&ga(e-c.circle.x)<Ca&&ga(r-c.circle.cy)<Ca;)i=c.P,a.unshift(c),Pr(c),c=i;a.unshift(c),Xr(c);for(var l=o;l.circle&&ga(e-l.circle.x)<Ca&&ga(r-l.circle.cy)<Ca;)o=l.N,a.push(l),Pr(l),l=o;a.push(l),Xr(l);var s,f=a.length;for(s=1;f>s;++s)l=a[s],c=a[s-1],Kr(l.edge,c.site,l.site,u);c=a[0],l=a[f-1],l.edge=Jr(c.site,l.site,null,u),Vr(c),Vr(l)}function jr(n){for(var t,e,r,u,i=n.x,o=n.y,a=Qc._;a;)if(r=Fr(a,o)-i,r>Ca)a=a.L;else{if(u=i-Hr(a,o),!(u>Ca)){r>-Ca?(t=a.P,e=a):u>-Ca?(t=a,e=a.N):t=e=a;break}if(!a.R){t=a;break}a=a.R}var c=Dr(n);if(Qc.insert(t,c),t||e){if(t===e)return Xr(t),e=Dr(t.site),Qc.insert(c,e),c.edge=e.edge=Jr(t.site,c.site),Vr(t),void Vr(e);if(!e)return void(c.edge=Jr(t.site,c.site));Xr(t),Xr(e);var l=t.site,s=l.x,f=l.y,h=n.x-s,g=n.y-f,p=e.site,v=p.x-s,d=p.y-f,m=2*(h*d-g*v),y=h*h+g*g,M=v*v+d*d,x={x:(d*y-g*M)/m+s,y:(h*M-v*y)/m+f};Kr(e.edge,l,p,x),c.edge=Jr(l,n,null,x),e.edge=Jr(n,p,null,x),Vr(t),Vr(e)}}function Fr(n,t){var e=n.site,r=e.x,u=e.y,i=u-t;if(!i)return r;var o=n.P;if(!o)return-1/0;e=o.site;var a=e.x,c=e.y,l=c-t;if(!l)return a;var s=a-r,f=1/i-1/l,h=s/l;return f?(-h+Math.sqrt(h*h-2*f*(s*s/(-2*l)-c+l/2+u-i/2)))/f+r:(r+a)/2}function Hr(n,t){var e=n.N;if(e)return Fr(e,t);var r=n.site;return r.y===t?r.x:1/0}function Or(n){this.site=n,this.edges=[]}function Ir(n){for(var t,e,r,u,i,o,a,c,l,s,f=n[0][0],h=n[1][0],g=n[0][1],p=n[1][1],v=Kc,d=v.length;d--;)if(i=v[d],i&&i.prepare())for(a=i.edges,c=a.length,o=0;c>o;)s=a[o].end(),r=s.x,u=s.y,l=a[++o%c].start(),t=l.x,e=l.y,(ga(r-t)>Ca||ga(u-e)>Ca)&&(a.splice(o,0,new Qr(Gr(i.site,s,ga(r-f)<Ca&&p-u>Ca?{x:f,y:ga(t-f)<Ca?e:p}:ga(u-p)<Ca&&h-r>Ca?{x:ga(e-p)<Ca?t:h,y:p}:ga(r-h)<Ca&&u-g>Ca?{x:h,y:ga(t-h)<Ca?e:g}:ga(u-g)<Ca&&r-f>Ca?{x:ga(e-g)<Ca?t:f,y:g}:null),i.site,null)),++c)}function Yr(n,t){return t.angle-n.angle}function Zr(){tu(this),this.x=this.y=this.arc=this.site=this.cy=null}function Vr(n){var t=n.P,e=n.N;if(t&&e){var r=t.site,u=n.site,i=e.site;if(r!==i){var o=u.x,a=u.y,c=r.x-o,l=r.y-a,s=i.x-o,f=i.y-a,h=2*(c*f-l*s);if(!(h>=-za)){var g=c*c+l*l,p=s*s+f*f,v=(f*g-l*p)/h,d=(c*p-s*g)/h,f=d+a,m=rl.pop()||new Zr;m.arc=n,m.site=u,m.x=v+o,m.y=f+Math.sqrt(v*v+d*d),m.cy=f,n.circle=m;for(var y=null,M=tl._;M;)if(m.y<M.y||m.y===M.y&&m.x<=M.x){if(!M.L){y=M.P;break}M=M.L}else{if(!M.R){y=M;break}M=M.R}tl.insert(y,m),y||(nl=m)}}}}function Xr(n){var t=n.circle;t&&(t.P||(nl=t.N),tl.remove(t),rl.push(t),tu(t),n.circle=null)}function $r(n){for(var t,e=Gc,r=Oe(n[0][0],n[0][1],n[1][0],n[1][1]),u=e.length;u--;)t=e[u],(!Br(t,n)||!r(t)||ga(t.a.x-t.b.x)<Ca&&ga(t.a.y-t.b.y)<Ca)&&(t.a=t.b=null,e.splice(u,1))}function Br(n,t){var e=n.b;if(e)return!0;var r,u,i=n.a,o=t[0][0],a=t[1][0],c=t[0][1],l=t[1][1],s=n.l,f=n.r,h=s.x,g=s.y,p=f.x,v=f.y,d=(h+p)/2,m=(g+v)/2;if(v===g){if(o>d||d>=a)return;if(h>p){if(i){if(i.y>=l)return}else i={x:d,y:c};e={x:d,y:l}}else{if(i){if(i.y<c)return}else i={x:d,y:l};e={x:d,y:c}}}else if(r=(h-p)/(v-g),u=m-r*d,-1>r||r>1)if(h>p){if(i){if(i.y>=l)return}else i={x:(c-u)/r,y:c};e={x:(l-u)/r,y:l}}else{if(i){if(i.y<c)return}else i={x:(l-u)/r,y:l};e={x:(c-u)/r,y:c}}else if(v>g){if(i){if(i.x>=a)return}else i={x:o,y:r*o+u};e={x:a,y:r*a+u}}else{if(i){if(i.x<o)return}else i={x:a,y:r*a+u};e={x:o,y:r*o+u}}return n.a=i,n.b=e,!0}function Wr(n,t){this.l=n,this.r=t,this.a=this.b=null}function Jr(n,t,e,r){var u=new Wr(n,t);return Gc.push(u),e&&Kr(u,n,t,e),r&&Kr(u,t,n,r),Kc[n.i].edges.push(new Qr(u,n,t)),Kc[t.i].edges.push(new Qr(u,t,n)),u}function Gr(n,t,e){var r=new Wr(n,null);return r.a=t,r.b=e,Gc.push(r),r}function Kr(n,t,e,r){n.a||n.b?n.l===e?n.b=r:n.a=r:(n.a=r,n.l=t,n.r=e)}function Qr(n,t,e){var r=n.a,u=n.b;this.edge=n,this.site=t,this.angle=e?Math.atan2(e.y-t.y,e.x-t.x):n.l===t?Math.atan2(u.x-r.x,r.y-u.y):Math.atan2(r.x-u.x,u.y-r.y)}function nu(){this._=null}function tu(n){n.U=n.C=n.L=n.R=n.P=n.N=null}function eu(n,t){var e=t,r=t.R,u=e.U;u?u.L===e?u.L=r:u.R=r:n._=r,r.U=u,e.U=r,e.R=r.L,e.R&&(e.R.U=e),r.L=e}function ru(n,t){var e=t,r=t.L,u=e.U;u?u.L===e?u.L=r:u.R=r:n._=r,r.U=u,e.U=r,e.L=r.R,e.L&&(e.L.U=e),r.R=e}function uu(n){for(;n.L;)n=n.L;return n}function iu(n,t){var e,r,u,i=n.sort(ou).pop();for(Gc=[],Kc=new Array(n.length),Qc=new nu,tl=new nu;;)if(u=nl,i&&(!u||i.y<u.y||i.y===u.y&&i.x<u.x))(i.x!==e||i.y!==r)&&(Kc[i.i]=new Or(i),jr(i),e=i.x,r=i.y),i=n.pop();else{if(!u)break;Ur(u.arc)}t&&($r(t),Ir(t));var o={cells:Kc,edges:Gc};return Qc=tl=Gc=Kc=null,o}function ou(n,t){return t.y-n.y||t.x-n.x}function au(n,t,e){return(n.x-e.x)*(t.y-n.y)-(n.x-t.x)*(e.y-n.y)}function cu(n){return n.x}function lu(n){return n.y}function su(){return{leaf:!0,nodes:[],point:null,x:null,y:null}}function fu(n,t,e,r,u,i){if(!n(t,e,r,u,i)){var o=.5*(e+u),a=.5*(r+i),c=t.nodes;c[0]&&fu(n,c[0],e,r,o,a),c[1]&&fu(n,c[1],o,r,u,a),c[2]&&fu(n,c[2],e,a,o,i),c[3]&&fu(n,c[3],o,a,u,i)}}function hu(n,t,e,r,u,i,o){var a,c=1/0;return function l(n,s,f,h,g){if(!(s>i||f>o||r>h||u>g)){if(p=n.point){var p,v=t-n.x,d=e-n.y,m=v*v+d*d;if(c>m){var y=Math.sqrt(c=m);r=t-y,u=e-y,i=t+y,o=e+y,a=p}}for(var M=n.nodes,x=.5*(s+h),b=.5*(f+g),_=t>=x,w=e>=b,S=w<<1|_,k=S+4;k>S;++S)if(n=M[3&S])switch(3&S){case 0:l(n,s,f,x,b);break;case 1:l(n,x,f,h,b);break;case 2:l(n,s,b,x,g);break;case 3:l(n,x,b,h,g)}}}(n,r,u,i,o),a}function gu(n,t){n=ta.rgb(n),t=ta.rgb(t);var e=n.r,r=n.g,u=n.b,i=t.r-e,o=t.g-r,a=t.b-u;return function(n){return"#"+xt(Math.round(e+i*n))+xt(Math.round(r+o*n))+xt(Math.round(u+a*n))}}function pu(n,t){var e,r={},u={};for(e in n)e in t?r[e]=mu(n[e],t[e]):u[e]=n[e];for(e in t)e in n||(u[e]=t[e]);return function(n){for(e in r)u[e]=r[e](n);return u}}function vu(n,t){return n=+n,t=+t,function(e){return n*(1-e)+t*e}}function du(n,t){var e,r,u,i=il.lastIndex=ol.lastIndex=0,o=-1,a=[],c=[];for(n+="",t+="";(e=il.exec(n))&&(r=ol.exec(t));)(u=r.index)>i&&(u=t.slice(i,u),a[o]?a[o]+=u:a[++o]=u),(e=e[0])===(r=r[0])?a[o]?a[o]+=r:a[++o]=r:(a[++o]=null,c.push({i:o,x:vu(e,r)})),i=ol.lastIndex;return i<t.length&&(u=t.slice(i),a[o]?a[o]+=u:a[++o]=u),a.length<2?c[0]?(t=c[0].x,function(n){return t(n)+""}):function(){return t}:(t=c.length,function(n){for(var e,r=0;t>r;++r)a[(e=c[r]).i]=e.x(n);return a.join("")})}function mu(n,t){for(var e,r=ta.interpolators.length;--r>=0&&!(e=ta.interpolators[r](n,t)););return e}function yu(n,t){var e,r=[],u=[],i=n.length,o=t.length,a=Math.min(n.length,t.length);for(e=0;a>e;++e)r.push(mu(n[e],t[e]));for(;i>e;++e)u[e]=n[e];for(;o>e;++e)u[e]=t[e];return function(n){for(e=0;a>e;++e)u[e]=r[e](n);return u}}function Mu(n){return function(t){return 0>=t?0:t>=1?1:n(t)}}function xu(n){return function(t){return 1-n(1-t)}}function bu(n){return function(t){return.5*(.5>t?n(2*t):2-n(2-2*t))}}function _u(n){return n*n}function wu(n){return n*n*n}function Su(n){if(0>=n)return 0;if(n>=1)return 1;var t=n*n,e=t*n;return 4*(.5>n?e:3*(n-t)+e-.75)}function ku(n){return function(t){return Math.pow(t,n)}}function Eu(n){return 1-Math.cos(n*Ra)}function Au(n){return Math.pow(2,10*(n-1))}function Nu(n){return 1-Math.sqrt(1-n*n)}function Cu(n,t){var e;return arguments.length<2&&(t=.45),arguments.length?e=t/La*Math.asin(1/n):(n=1,e=t/4),function(r){return 1+n*Math.pow(2,-10*r)*Math.sin((r-e)*La/t)}}function zu(n){return n||(n=1.70158),function(t){return t*t*((n+1)*t-n)}}function qu(n){return 1/2.75>n?7.5625*n*n:2/2.75>n?7.5625*(n-=1.5/2.75)*n+.75:2.5/2.75>n?7.5625*(n-=2.25/2.75)*n+.9375:7.5625*(n-=2.625/2.75)*n+.984375}function Lu(n,t){n=ta.hcl(n),t=ta.hcl(t);var e=n.h,r=n.c,u=n.l,i=t.h-e,o=t.c-r,a=t.l-u;return isNaN(o)&&(o=0,r=isNaN(r)?t.c:r),isNaN(i)?(i=0,e=isNaN(e)?t.h:e):i>180?i-=360:-180>i&&(i+=360),function(n){return st(e+i*n,r+o*n,u+a*n)+""}}function Tu(n,t){n=ta.hsl(n),t=ta.hsl(t);var e=n.h,r=n.s,u=n.l,i=t.h-e,o=t.s-r,a=t.l-u;return isNaN(o)&&(o=0,r=isNaN(r)?t.s:r),isNaN(i)?(i=0,e=isNaN(e)?t.h:e):i>180?i-=360:-180>i&&(i+=360),function(n){return ct(e+i*n,r+o*n,u+a*n)+""}}function Ru(n,t){n=ta.lab(n),t=ta.lab(t);var e=n.l,r=n.a,u=n.b,i=t.l-e,o=t.a-r,a=t.b-u;return function(n){return ht(e+i*n,r+o*n,u+a*n)+""}}function Du(n,t){return t-=n,function(e){return Math.round(n+t*e)}}function Pu(n){var t=[n.a,n.b],e=[n.c,n.d],r=ju(t),u=Uu(t,e),i=ju(Fu(e,t,-u))||0;t[0]*e[1]<e[0]*t[1]&&(t[0]*=-1,t[1]*=-1,r*=-1,u*=-1),this.rotate=(r?Math.atan2(t[1],t[0]):Math.atan2(-e[0],e[1]))*Pa,this.translate=[n.e,n.f],this.scale=[r,i],this.skew=i?Math.atan2(u,i)*Pa:0}function Uu(n,t){return n[0]*t[0]+n[1]*t[1]}function ju(n){var t=Math.sqrt(Uu(n,n));return t&&(n[0]/=t,n[1]/=t),t}function Fu(n,t,e){return n[0]+=e*t[0],n[1]+=e*t[1],n}function Hu(n,t){var e,r=[],u=[],i=ta.transform(n),o=ta.transform(t),a=i.translate,c=o.translate,l=i.rotate,s=o.rotate,f=i.skew,h=o.skew,g=i.scale,p=o.scale;return a[0]!=c[0]||a[1]!=c[1]?(r.push("translate(",null,",",null,")"),u.push({i:1,x:vu(a[0],c[0])},{i:3,x:vu(a[1],c[1])})):r.push(c[0]||c[1]?"translate("+c+")":""),l!=s?(l-s>180?s+=360:s-l>180&&(l+=360),u.push({i:r.push(r.pop()+"rotate(",null,")")-2,x:vu(l,s)})):s&&r.push(r.pop()+"rotate("+s+")"),f!=h?u.push({i:r.push(r.pop()+"skewX(",null,")")-2,x:vu(f,h)}):h&&r.push(r.pop()+"skewX("+h+")"),g[0]!=p[0]||g[1]!=p[1]?(e=r.push(r.pop()+"scale(",null,",",null,")"),u.push({i:e-4,x:vu(g[0],p[0])},{i:e-2,x:vu(g[1],p[1])})):(1!=p[0]||1!=p[1])&&r.push(r.pop()+"scale("+p+")"),e=u.length,function(n){for(var t,i=-1;++i<e;)r[(t=u[i]).i]=t.x(n);return r.join("")}}function Ou(n,t){return t=(t-=n=+n)||1/t,function(e){return(e-n)/t}}function Iu(n,t){return t=(t-=n=+n)||1/t,function(e){return Math.max(0,Math.min(1,(e-n)/t))}}function Yu(n){for(var t=n.source,e=n.target,r=Vu(t,e),u=[t];t!==r;)t=t.parent,u.push(t);for(var i=u.length;e!==r;)u.splice(i,0,e),e=e.parent;return u}function Zu(n){for(var t=[],e=n.parent;null!=e;)t.push(n),n=e,e=e.parent;return t.push(n),t}function Vu(n,t){if(n===t)return n;for(var e=Zu(n),r=Zu(t),u=e.pop(),i=r.pop(),o=null;u===i;)o=u,u=e.pop(),i=r.pop();return o}function Xu(n){n.fixed|=2}function $u(n){n.fixed&=-7}function Bu(n){n.fixed|=4,n.px=n.x,n.py=n.y}function Wu(n){n.fixed&=-5}function Ju(n,t,e){var r=0,u=0;if(n.charge=0,!n.leaf)for(var i,o=n.nodes,a=o.length,c=-1;++c<a;)i=o[c],null!=i&&(Ju(i,t,e),n.charge+=i.charge,r+=i.charge*i.cx,u+=i.charge*i.cy);if(n.point){n.leaf||(n.point.x+=Math.random()-.5,n.point.y+=Math.random()-.5);var l=t*e[n.point.index];n.charge+=n.pointCharge=l,r+=l*n.point.x,u+=l*n.point.y}n.cx=r/n.charge,n.cy=u/n.charge}function Gu(n,t){return ta.rebind(n,t,"sort","children","value"),n.nodes=n,n.links=ri,n}function Ku(n,t){for(var e=[n];null!=(n=e.pop());)if(t(n),(u=n.children)&&(r=u.length))for(var r,u;--r>=0;)e.push(u[r])}function Qu(n,t){for(var e=[n],r=[];null!=(n=e.pop());)if(r.push(n),(i=n.children)&&(u=i.length))for(var u,i,o=-1;++o<u;)e.push(i[o]);for(;null!=(n=r.pop());)t(n)}function ni(n){return n.children}function ti(n){return n.value}function ei(n,t){return t.value-n.value}function ri(n){return ta.merge(n.map(function(n){return(n.children||[]).map(function(t){return{source:n,target:t}})}))}function ui(n){return n.x}function ii(n){return n.y}function oi(n,t,e){n.y0=t,n.y=e}function ai(n){return ta.range(n.length)}function ci(n){for(var t=-1,e=n[0].length,r=[];++t<e;)r[t]=0;return r}function li(n){for(var t,e=1,r=0,u=n[0][1],i=n.length;i>e;++e)(t=n[e][1])>u&&(r=e,u=t);return r}function si(n){return n.reduce(fi,0)}function fi(n,t){return n+t[1]}function hi(n,t){return gi(n,Math.ceil(Math.log(t.length)/Math.LN2+1))}function gi(n,t){for(var e=-1,r=+n[0],u=(n[1]-r)/t,i=[];++e<=t;)i[e]=u*e+r;return i}function pi(n){return[ta.min(n),ta.max(n)]}function vi(n,t){return n.value-t.value}function di(n,t){var e=n._pack_next;n._pack_next=t,t._pack_prev=n,t._pack_next=e,e._pack_prev=t}function mi(n,t){n._pack_next=t,t._pack_prev=n}function yi(n,t){var e=t.x-n.x,r=t.y-n.y,u=n.r+t.r;return.999*u*u>e*e+r*r}function Mi(n){function t(n){s=Math.min(n.x-n.r,s),f=Math.max(n.x+n.r,f),h=Math.min(n.y-n.r,h),g=Math.max(n.y+n.r,g)}if((e=n.children)&&(l=e.length)){var e,r,u,i,o,a,c,l,s=1/0,f=-1/0,h=1/0,g=-1/0;if(e.forEach(xi),r=e[0],r.x=-r.r,r.y=0,t(r),l>1&&(u=e[1],u.x=u.r,u.y=0,t(u),l>2))for(i=e[2],wi(r,u,i),t(i),di(r,i),r._pack_prev=i,di(i,u),u=r._pack_next,o=3;l>o;o++){wi(r,u,i=e[o]);var p=0,v=1,d=1;for(a=u._pack_next;a!==u;a=a._pack_next,v++)if(yi(a,i)){p=1;break}if(1==p)for(c=r._pack_prev;c!==a._pack_prev&&!yi(c,i);c=c._pack_prev,d++);p?(d>v||v==d&&u.r<r.r?mi(r,u=a):mi(r=c,u),o--):(di(r,i),u=i,t(i))}var m=(s+f)/2,y=(h+g)/2,M=0;for(o=0;l>o;o++)i=e[o],i.x-=m,i.y-=y,M=Math.max(M,i.r+Math.sqrt(i.x*i.x+i.y*i.y));n.r=M,e.forEach(bi)}}function xi(n){n._pack_next=n._pack_prev=n}function bi(n){delete n._pack_next,delete n._pack_prev}function _i(n,t,e,r){var u=n.children;if(n.x=t+=r*n.x,n.y=e+=r*n.y,n.r*=r,u)for(var i=-1,o=u.length;++i<o;)_i(u[i],t,e,r)}function wi(n,t,e){var r=n.r+e.r,u=t.x-n.x,i=t.y-n.y;if(r&&(u||i)){var o=t.r+e.r,a=u*u+i*i;o*=o,r*=r;var c=.5+(r-o)/(2*a),l=Math.sqrt(Math.max(0,2*o*(r+a)-(r-=a)*r-o*o))/(2*a);e.x=n.x+c*u+l*i,e.y=n.y+c*i-l*u}else e.x=n.x+r,e.y=n.y}function Si(n,t){return n.parent==t.parent?1:2}function ki(n){var t=n.children;return t.length?t[0]:n.t}function Ei(n){var t,e=n.children;return(t=e.length)?e[t-1]:n.t}function Ai(n,t,e){var r=e/(t.i-n.i);t.c-=r,t.s+=e,n.c+=r,t.z+=e,t.m+=e}function Ni(n){for(var t,e=0,r=0,u=n.children,i=u.length;--i>=0;)t=u[i],t.z+=e,t.m+=e,e+=t.s+(r+=t.c)}function Ci(n,t,e){return n.a.parent===t.parent?n.a:e}function zi(n){return 1+ta.max(n,function(n){return n.y})}function qi(n){return n.reduce(function(n,t){return n+t.x},0)/n.length}function Li(n){var t=n.children;return t&&t.length?Li(t[0]):n}function Ti(n){var t,e=n.children;return e&&(t=e.length)?Ti(e[t-1]):n}function Ri(n){return{x:n.x,y:n.y,dx:n.dx,dy:n.dy}}function Di(n,t){var e=n.x+t[3],r=n.y+t[0],u=n.dx-t[1]-t[3],i=n.dy-t[0]-t[2];return 0>u&&(e+=u/2,u=0),0>i&&(r+=i/2,i=0),{x:e,y:r,dx:u,dy:i}}function Pi(n){var t=n[0],e=n[n.length-1];return e>t?[t,e]:[e,t]}function Ui(n){return n.rangeExtent?n.rangeExtent():Pi(n.range())}function ji(n,t,e,r){var u=e(n[0],n[1]),i=r(t[0],t[1]);return function(n){return i(u(n))}}function Fi(n,t){var e,r=0,u=n.length-1,i=n[r],o=n[u];return i>o&&(e=r,r=u,u=e,e=i,i=o,o=e),n[r]=t.floor(i),n[u]=t.ceil(o),n}function Hi(n){return n?{floor:function(t){return Math.floor(t/n)*n},ceil:function(t){return Math.ceil(t/n)*n}}:ml}function Oi(n,t,e,r){var u=[],i=[],o=0,a=Math.min(n.length,t.length)-1;for(n[a]<n[0]&&(n=n.slice().reverse(),t=t.slice().reverse());++o<=a;)u.push(e(n[o-1],n[o])),i.push(r(t[o-1],t[o]));return function(t){var e=ta.bisect(n,t,1,a)-1;return i[e](u[e](t))}}function Ii(n,t,e,r){function u(){var u=Math.min(n.length,t.length)>2?Oi:ji,c=r?Iu:Ou;return o=u(n,t,c,e),a=u(t,n,c,mu),i}function i(n){return o(n)}var o,a;return i.invert=function(n){return a(n)},i.domain=function(t){return arguments.length?(n=t.map(Number),u()):n},i.range=function(n){return arguments.length?(t=n,u()):t},i.rangeRound=function(n){return i.range(n).interpolate(Du)},i.clamp=function(n){return arguments.length?(r=n,u()):r},i.interpolate=function(n){return arguments.length?(e=n,u()):e},i.ticks=function(t){return Xi(n,t)},i.tickFormat=function(t,e){return $i(n,t,e)},i.nice=function(t){return Zi(n,t),u()},i.copy=function(){return Ii(n,t,e,r)},u()}function Yi(n,t){return ta.rebind(n,t,"range","rangeRound","interpolate","clamp")}function Zi(n,t){return Fi(n,Hi(Vi(n,t)[2]))}function Vi(n,t){null==t&&(t=10);var e=Pi(n),r=e[1]-e[0],u=Math.pow(10,Math.floor(Math.log(r/t)/Math.LN10)),i=t/r*u;return.15>=i?u*=10:.35>=i?u*=5:.75>=i&&(u*=2),e[0]=Math.ceil(e[0]/u)*u,e[1]=Math.floor(e[1]/u)*u+.5*u,e[2]=u,e}function Xi(n,t){return ta.range.apply(ta,Vi(n,t))}function $i(n,t,e){var r=Vi(n,t);if(e){var u=ic.exec(e);if(u.shift(),"s"===u[8]){var i=ta.formatPrefix(Math.max(ga(r[0]),ga(r[1])));return u[7]||(u[7]="."+Bi(i.scale(r[2]))),u[8]="f",e=ta.format(u.join("")),function(n){return e(i.scale(n))+i.symbol}}u[7]||(u[7]="."+Wi(u[8],r)),e=u.join("")}else e=",."+Bi(r[2])+"f";return ta.format(e)}function Bi(n){return-Math.floor(Math.log(n)/Math.LN10+.01)}function Wi(n,t){var e=Bi(t[2]);return n in yl?Math.abs(e-Bi(Math.max(ga(t[0]),ga(t[1]))))+ +("e"!==n):e-2*("%"===n)}function Ji(n,t,e,r){function u(n){return(e?Math.log(0>n?0:n):-Math.log(n>0?0:-n))/Math.log(t)}function i(n){return e?Math.pow(t,n):-Math.pow(t,-n)}function o(t){return n(u(t))}return o.invert=function(t){return i(n.invert(t))},o.domain=function(t){return arguments.length?(e=t[0]>=0,n.domain((r=t.map(Number)).map(u)),o):r},o.base=function(e){return arguments.length?(t=+e,n.domain(r.map(u)),o):t},o.nice=function(){var t=Fi(r.map(u),e?Math:xl);return n.domain(t),r=t.map(i),o},o.ticks=function(){var n=Pi(r),o=[],a=n[0],c=n[1],l=Math.floor(u(a)),s=Math.ceil(u(c)),f=t%1?2:t;if(isFinite(s-l)){if(e){for(;s>l;l++)for(var h=1;f>h;h++)o.push(i(l)*h);o.push(i(l))}else for(o.push(i(l));l++<s;)for(var h=f-1;h>0;h--)o.push(i(l)*h);for(l=0;o[l]<a;l++);for(s=o.length;o[s-1]>c;s--);o=o.slice(l,s)}return o},o.tickFormat=function(n,t){if(!arguments.length)return Ml;arguments.length<2?t=Ml:"function"!=typeof t&&(t=ta.format(t));var r,a=Math.max(.1,n/o.ticks().length),c=e?(r=1e-12,Math.ceil):(r=-1e-12,Math.floor);return function(n){return n/i(c(u(n)+r))<=a?t(n):""}},o.copy=function(){return Ji(n.copy(),t,e,r)},Yi(o,n)}function Gi(n,t,e){function r(t){return n(u(t))}var u=Ki(t),i=Ki(1/t);return r.invert=function(t){return i(n.invert(t))},r.domain=function(t){return arguments.length?(n.domain((e=t.map(Number)).map(u)),r):e},r.ticks=function(n){return Xi(e,n)},r.tickFormat=function(n,t){return $i(e,n,t)},r.nice=function(n){return r.domain(Zi(e,n))},r.exponent=function(o){return arguments.length?(u=Ki(t=o),i=Ki(1/t),n.domain(e.map(u)),r):t},r.copy=function(){return Gi(n.copy(),t,e)},Yi(r,n)}function Ki(n){return function(t){return 0>t?-Math.pow(-t,n):Math.pow(t,n)}}function Qi(n,t){function e(e){return i[((u.get(e)||("range"===t.t?u.set(e,n.push(e)):0/0))-1)%i.length]}function r(t,e){return ta.range(n.length).map(function(n){return t+e*n})}var u,i,o;return e.domain=function(r){if(!arguments.length)return n;n=[],u=new l;for(var i,o=-1,a=r.length;++o<a;)u.has(i=r[o])||u.set(i,n.push(i));return e[t.t].apply(e,t.a)},e.range=function(n){return arguments.length?(i=n,o=0,t={t:"range",a:arguments},e):i},e.rangePoints=function(u,a){arguments.length<2&&(a=0);var c=u[0],l=u[1],s=n.length<2?(c=(c+l)/2,0):(l-c)/(n.length-1+a);return i=r(c+s*a/2,s),o=0,t={t:"rangePoints",a:arguments},e},e.rangeRoundPoints=function(u,a){arguments.length<2&&(a=0);var c=u[0],l=u[1],s=n.length<2?(c=l=Math.round((c+l)/2),0):(l-c)/(n.length-1+a)|0;return i=r(c+Math.round(s*a/2+(l-c-(n.length-1+a)*s)/2),s),o=0,t={t:"rangeRoundPoints",a:arguments},e},e.rangeBands=function(u,a,c){arguments.length<2&&(a=0),arguments.length<3&&(c=a);var l=u[1]<u[0],s=u[l-0],f=u[1-l],h=(f-s)/(n.length-a+2*c);return i=r(s+h*c,h),l&&i.reverse(),o=h*(1-a),t={t:"rangeBands",a:arguments},e},e.rangeRoundBands=function(u,a,c){arguments.length<2&&(a=0),arguments.length<3&&(c=a);var l=u[1]<u[0],s=u[l-0],f=u[1-l],h=Math.floor((f-s)/(n.length-a+2*c));return i=r(s+Math.round((f-s-(n.length-a)*h)/2),h),l&&i.reverse(),o=Math.round(h*(1-a)),t={t:"rangeRoundBands",a:arguments},e},e.rangeBand=function(){return o},e.rangeExtent=function(){return Pi(t.a[0])},e.copy=function(){return Qi(n,t)},e.domain(n)}function no(n,t){function i(){var e=0,r=t.length;for(a=[];++e<r;)a[e-1]=ta.quantile(n,e/r);return o}function o(n){return isNaN(n=+n)?void 0:t[ta.bisect(a,n)]}var a;return o.domain=function(t){return arguments.length?(n=t.map(r).filter(u).sort(e),i()):n},o.range=function(n){return arguments.length?(t=n,i()):t},o.quantiles=function(){return a},o.invertExtent=function(e){return e=t.indexOf(e),0>e?[0/0,0/0]:[e>0?a[e-1]:n[0],e<a.length?a[e]:n[n.length-1]]},o.copy=function(){return no(n,t)},i()}function to(n,t,e){function r(t){return e[Math.max(0,Math.min(o,Math.floor(i*(t-n))))]}function u(){return i=e.length/(t-n),o=e.length-1,r}var i,o;return r.domain=function(e){return arguments.length?(n=+e[0],t=+e[e.length-1],u()):[n,t]},r.range=function(n){return arguments.length?(e=n,u()):e},r.invertExtent=function(t){return t=e.indexOf(t),t=0>t?0/0:t/i+n,[t,t+1/i]},r.copy=function(){return to(n,t,e)},u()}function eo(n,t){function e(e){return e>=e?t[ta.bisect(n,e)]:void 0}return e.domain=function(t){return arguments.length?(n=t,e):n},e.range=function(n){return arguments.length?(t=n,e):t},e.invertExtent=function(e){return e=t.indexOf(e),[n[e-1],n[e]]},e.copy=function(){return eo(n,t)},e}function ro(n){function t(n){return+n}return t.invert=t,t.domain=t.range=function(e){return arguments.length?(n=e.map(t),t):n},t.ticks=function(t){return Xi(n,t)},t.tickFormat=function(t,e){return $i(n,t,e)},t.copy=function(){return ro(n)},t}function uo(){return 0}function io(n){return n.innerRadius}function oo(n){return n.outerRadius}function ao(n){return n.startAngle}function co(n){return n.endAngle}function lo(n){return n&&n.padAngle}function so(n,t,e,r){return(n-e)*t-(t-r)*n>0?0:1}function fo(n,t,e,r,u){var i=n[0]-t[0],o=n[1]-t[1],a=(u?r:-r)/Math.sqrt(i*i+o*o),c=a*o,l=-a*i,s=n[0]+c,f=n[1]+l,h=t[0]+c,g=t[1]+l,p=(s+h)/2,v=(f+g)/2,d=h-s,m=g-f,y=d*d+m*m,M=e-r,x=s*g-h*f,b=(0>m?-1:1)*Math.sqrt(M*M*y-x*x),_=(x*m-d*b)/y,w=(-x*d-m*b)/y,S=(x*m+d*b)/y,k=(-x*d+m*b)/y,E=_-p,A=w-v,N=S-p,C=k-v;return E*E+A*A>N*N+C*C&&(_=S,w=k),[[_-c,w-l],[_*e/M,w*e/M]]}function ho(n){function t(t){function o(){l.push("M",i(n(s),a))}for(var c,l=[],s=[],f=-1,h=t.length,g=Et(e),p=Et(r);++f<h;)u.call(this,c=t[f],f)?s.push([+g.call(this,c,f),+p.call(this,c,f)]):s.length&&(o(),s=[]);return s.length&&o(),l.length?l.join(""):null}var e=Ar,r=Nr,u=Ne,i=go,o=i.key,a=.7;return t.x=function(n){return arguments.length?(e=n,t):e},t.y=function(n){return arguments.length?(r=n,t):r},t.defined=function(n){return arguments.length?(u=n,t):u},t.interpolate=function(n){return arguments.length?(o="function"==typeof n?i=n:(i=El.get(n)||go).key,t):o},t.tension=function(n){return arguments.length?(a=n,t):a},t}function go(n){return n.join("L")}function po(n){return go(n)+"Z"}function vo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("H",(r[0]+(r=n[t])[0])/2,"V",r[1]);return e>1&&u.push("H",r[0]),u.join("")}function mo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("V",(r=n[t])[1],"H",r[0]);return u.join("")}function yo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("H",(r=n[t])[0],"V",r[1]);return u.join("")}function Mo(n,t){return n.length<4?go(n):n[1]+_o(n.slice(1,-1),wo(n,t))}function xo(n,t){return n.length<3?go(n):n[0]+_o((n.push(n[0]),n),wo([n[n.length-2]].concat(n,[n[1]]),t))}function bo(n,t){return n.length<3?go(n):n[0]+_o(n,wo(n,t))}function _o(n,t){if(t.length<1||n.length!=t.length&&n.length!=t.length+2)return go(n);var e=n.length!=t.length,r="",u=n[0],i=n[1],o=t[0],a=o,c=1;if(e&&(r+="Q"+(i[0]-2*o[0]/3)+","+(i[1]-2*o[1]/3)+","+i[0]+","+i[1],u=n[1],c=2),t.length>1){a=t[1],i=n[c],c++,r+="C"+(u[0]+o[0])+","+(u[1]+o[1])+","+(i[0]-a[0])+","+(i[1]-a[1])+","+i[0]+","+i[1];for(var l=2;l<t.length;l++,c++)i=n[c],a=t[l],r+="S"+(i[0]-a[0])+","+(i[1]-a[1])+","+i[0]+","+i[1]}if(e){var s=n[c];r+="Q"+(i[0]+2*a[0]/3)+","+(i[1]+2*a[1]/3)+","+s[0]+","+s[1]}return r}function wo(n,t){for(var e,r=[],u=(1-t)/2,i=n[0],o=n[1],a=1,c=n.length;++a<c;)e=i,i=o,o=n[a],r.push([u*(o[0]-e[0]),u*(o[1]-e[1])]);return r}function So(n){if(n.length<3)return go(n);var t=1,e=n.length,r=n[0],u=r[0],i=r[1],o=[u,u,u,(r=n[1])[0]],a=[i,i,i,r[1]],c=[u,",",i,"L",No(Cl,o),",",No(Cl,a)];for(n.push(n[e-1]);++t<=e;)r=n[t],o.shift(),o.push(r[0]),a.shift(),a.push(r[1]),Co(c,o,a);return n.pop(),c.push("L",r),c.join("")}function ko(n){if(n.length<4)return go(n);for(var t,e=[],r=-1,u=n.length,i=[0],o=[0];++r<3;)t=n[r],i.push(t[0]),o.push(t[1]);for(e.push(No(Cl,i)+","+No(Cl,o)),--r;++r<u;)t=n[r],i.shift(),i.push(t[0]),o.shift(),o.push(t[1]),Co(e,i,o);return e.join("")}function Eo(n){for(var t,e,r=-1,u=n.length,i=u+4,o=[],a=[];++r<4;)e=n[r%u],o.push(e[0]),a.push(e[1]);for(t=[No(Cl,o),",",No(Cl,a)],--r;++r<i;)e=n[r%u],o.shift(),o.push(e[0]),a.shift(),a.push(e[1]),Co(t,o,a);return t.join("")}function Ao(n,t){var e=n.length-1;if(e)for(var r,u,i=n[0][0],o=n[0][1],a=n[e][0]-i,c=n[e][1]-o,l=-1;++l<=e;)r=n[l],u=l/e,r[0]=t*r[0]+(1-t)*(i+u*a),r[1]=t*r[1]+(1-t)*(o+u*c);return So(n)}function No(n,t){return n[0]*t[0]+n[1]*t[1]+n[2]*t[2]+n[3]*t[3]}function Co(n,t,e){n.push("C",No(Al,t),",",No(Al,e),",",No(Nl,t),",",No(Nl,e),",",No(Cl,t),",",No(Cl,e))}function zo(n,t){return(t[1]-n[1])/(t[0]-n[0])}function qo(n){for(var t=0,e=n.length-1,r=[],u=n[0],i=n[1],o=r[0]=zo(u,i);++t<e;)r[t]=(o+(o=zo(u=i,i=n[t+1])))/2;return r[t]=o,r}function Lo(n){for(var t,e,r,u,i=[],o=qo(n),a=-1,c=n.length-1;++a<c;)t=zo(n[a],n[a+1]),ga(t)<Ca?o[a]=o[a+1]=0:(e=o[a]/t,r=o[a+1]/t,u=e*e+r*r,u>9&&(u=3*t/Math.sqrt(u),o[a]=u*e,o[a+1]=u*r));for(a=-1;++a<=c;)u=(n[Math.min(c,a+1)][0]-n[Math.max(0,a-1)][0])/(6*(1+o[a]*o[a])),i.push([u||0,o[a]*u||0]);return i}function To(n){return n.length<3?go(n):n[0]+_o(n,Lo(n))}function Ro(n){for(var t,e,r,u=-1,i=n.length;++u<i;)t=n[u],e=t[0],r=t[1]-Ra,t[0]=e*Math.cos(r),t[1]=e*Math.sin(r);return n}function Do(n){function t(t){function c(){v.push("M",a(n(m),f),s,l(n(d.reverse()),f),"Z")}for(var h,g,p,v=[],d=[],m=[],y=-1,M=t.length,x=Et(e),b=Et(u),_=e===r?function(){return g}:Et(r),w=u===i?function(){return p}:Et(i);++y<M;)o.call(this,h=t[y],y)?(d.push([g=+x.call(this,h,y),p=+b.call(this,h,y)]),m.push([+_.call(this,h,y),+w.call(this,h,y)])):d.length&&(c(),d=[],m=[]);return d.length&&c(),v.length?v.join(""):null}var e=Ar,r=Ar,u=0,i=Nr,o=Ne,a=go,c=a.key,l=a,s="L",f=.7;return t.x=function(n){return arguments.length?(e=r=n,t):r},t.x0=function(n){return arguments.length?(e=n,t):e},t.x1=function(n){return arguments.length?(r=n,t):r
+},t.y=function(n){return arguments.length?(u=i=n,t):i},t.y0=function(n){return arguments.length?(u=n,t):u},t.y1=function(n){return arguments.length?(i=n,t):i},t.defined=function(n){return arguments.length?(o=n,t):o},t.interpolate=function(n){return arguments.length?(c="function"==typeof n?a=n:(a=El.get(n)||go).key,l=a.reverse||a,s=a.closed?"M":"L",t):c},t.tension=function(n){return arguments.length?(f=n,t):f},t}function Po(n){return n.radius}function Uo(n){return[n.x,n.y]}function jo(n){return function(){var t=n.apply(this,arguments),e=t[0],r=t[1]-Ra;return[e*Math.cos(r),e*Math.sin(r)]}}function Fo(){return 64}function Ho(){return"circle"}function Oo(n){var t=Math.sqrt(n/qa);return"M0,"+t+"A"+t+","+t+" 0 1,1 0,"+-t+"A"+t+","+t+" 0 1,1 0,"+t+"Z"}function Io(n){return function(){var t,e;(t=this[n])&&(e=t[t.active])&&(--t.count?delete t[t.active]:delete this[n],t.active+=.5,e.event&&e.event.interrupt.call(this,this.__data__,e.index))}}function Yo(n,t,e){return ya(n,Pl),n.namespace=t,n.id=e,n}function Zo(n,t,e,r){var u=n.id,i=n.namespace;return Y(n,"function"==typeof e?function(n,o,a){n[i][u].tween.set(t,r(e.call(n,n.__data__,o,a)))}:(e=r(e),function(n){n[i][u].tween.set(t,e)}))}function Vo(n){return null==n&&(n=""),function(){this.textContent=n}}function Xo(n){return null==n?"__transition__":"__transition_"+n+"__"}function $o(n,t,e,r,u){var i=n[e]||(n[e]={active:0,count:0}),o=i[r];if(!o){var a=u.time;o=i[r]={tween:new l,time:a,delay:u.delay,duration:u.duration,ease:u.ease,index:t},u=null,++i.count,ta.timer(function(u){function c(e){if(i.active>r)return s();var u=i[i.active];u&&(--i.count,delete i[i.active],u.event&&u.event.interrupt.call(n,n.__data__,u.index)),i.active=r,o.event&&o.event.start.call(n,n.__data__,t),o.tween.forEach(function(e,r){(r=r.call(n,n.__data__,t))&&v.push(r)}),h=o.ease,f=o.duration,ta.timer(function(){return p.c=l(e||1)?Ne:l,1},0,a)}function l(e){if(i.active!==r)return 1;for(var u=e/f,a=h(u),c=v.length;c>0;)v[--c].call(n,a);return u>=1?(o.event&&o.event.end.call(n,n.__data__,t),s()):void 0}function s(){return--i.count?delete i[r]:delete n[e],1}var f,h,g=o.delay,p=ec,v=[];return p.t=g+a,u>=g?c(u-g):void(p.c=c)},0,a)}}function Bo(n,t,e){n.attr("transform",function(n){var r=t(n);return"translate("+(isFinite(r)?r:e(n))+",0)"})}function Wo(n,t,e){n.attr("transform",function(n){var r=t(n);return"translate(0,"+(isFinite(r)?r:e(n))+")"})}function Jo(n){return n.toISOString()}function Go(n,t,e){function r(t){return n(t)}function u(n,e){var r=n[1]-n[0],u=r/e,i=ta.bisect(Vl,u);return i==Vl.length?[t.year,Vi(n.map(function(n){return n/31536e6}),e)[2]]:i?t[u/Vl[i-1]<Vl[i]/u?i-1:i]:[Bl,Vi(n,e)[2]]}return r.invert=function(t){return Ko(n.invert(t))},r.domain=function(t){return arguments.length?(n.domain(t),r):n.domain().map(Ko)},r.nice=function(n,t){function e(e){return!isNaN(e)&&!n.range(e,Ko(+e+1),t).length}var i=r.domain(),o=Pi(i),a=null==n?u(o,10):"number"==typeof n&&u(o,n);return a&&(n=a[0],t=a[1]),r.domain(Fi(i,t>1?{floor:function(t){for(;e(t=n.floor(t));)t=Ko(t-1);return t},ceil:function(t){for(;e(t=n.ceil(t));)t=Ko(+t+1);return t}}:n))},r.ticks=function(n,t){var e=Pi(r.domain()),i=null==n?u(e,10):"number"==typeof n?u(e,n):!n.range&&[{range:n},t];return i&&(n=i[0],t=i[1]),n.range(e[0],Ko(+e[1]+1),1>t?1:t)},r.tickFormat=function(){return e},r.copy=function(){return Go(n.copy(),t,e)},Yi(r,n)}function Ko(n){return new Date(n)}function Qo(n){return JSON.parse(n.responseText)}function na(n){var t=ua.createRange();return t.selectNode(ua.body),t.createContextualFragment(n.responseText)}var ta={version:"3.5.6"},ea=[].slice,ra=function(n){return ea.call(n)},ua=this.document;if(ua)try{ra(ua.documentElement.childNodes)[0].nodeType}catch(ia){ra=function(n){for(var t=n.length,e=new Array(t);t--;)e[t]=n[t];return e}}if(Date.now||(Date.now=function(){return+new Date}),ua)try{ua.createElement("DIV").style.setProperty("opacity",0,"")}catch(oa){var aa=this.Element.prototype,ca=aa.setAttribute,la=aa.setAttributeNS,sa=this.CSSStyleDeclaration.prototype,fa=sa.setProperty;aa.setAttribute=function(n,t){ca.call(this,n,t+"")},aa.setAttributeNS=function(n,t,e){la.call(this,n,t,e+"")},sa.setProperty=function(n,t,e){fa.call(this,n,t+"",e)}}ta.ascending=e,ta.descending=function(n,t){return n>t?-1:t>n?1:t>=n?0:0/0},ta.min=function(n,t){var e,r,u=-1,i=n.length;if(1===arguments.length){for(;++u<i;)if(null!=(r=n[u])&&r>=r){e=r;break}for(;++u<i;)null!=(r=n[u])&&e>r&&(e=r)}else{for(;++u<i;)if(null!=(r=t.call(n,n[u],u))&&r>=r){e=r;break}for(;++u<i;)null!=(r=t.call(n,n[u],u))&&e>r&&(e=r)}return e},ta.max=function(n,t){var e,r,u=-1,i=n.length;if(1===arguments.length){for(;++u<i;)if(null!=(r=n[u])&&r>=r){e=r;break}for(;++u<i;)null!=(r=n[u])&&r>e&&(e=r)}else{for(;++u<i;)if(null!=(r=t.call(n,n[u],u))&&r>=r){e=r;break}for(;++u<i;)null!=(r=t.call(n,n[u],u))&&r>e&&(e=r)}return e},ta.extent=function(n,t){var e,r,u,i=-1,o=n.length;if(1===arguments.length){for(;++i<o;)if(null!=(r=n[i])&&r>=r){e=u=r;break}for(;++i<o;)null!=(r=n[i])&&(e>r&&(e=r),r>u&&(u=r))}else{for(;++i<o;)if(null!=(r=t.call(n,n[i],i))&&r>=r){e=u=r;break}for(;++i<o;)null!=(r=t.call(n,n[i],i))&&(e>r&&(e=r),r>u&&(u=r))}return[e,u]},ta.sum=function(n,t){var e,r=0,i=n.length,o=-1;if(1===arguments.length)for(;++o<i;)u(e=+n[o])&&(r+=e);else for(;++o<i;)u(e=+t.call(n,n[o],o))&&(r+=e);return r},ta.mean=function(n,t){var e,i=0,o=n.length,a=-1,c=o;if(1===arguments.length)for(;++a<o;)u(e=r(n[a]))?i+=e:--c;else for(;++a<o;)u(e=r(t.call(n,n[a],a)))?i+=e:--c;return c?i/c:void 0},ta.quantile=function(n,t){var e=(n.length-1)*t+1,r=Math.floor(e),u=+n[r-1],i=e-r;return i?u+i*(n[r]-u):u},ta.median=function(n,t){var i,o=[],a=n.length,c=-1;if(1===arguments.length)for(;++c<a;)u(i=r(n[c]))&&o.push(i);else for(;++c<a;)u(i=r(t.call(n,n[c],c)))&&o.push(i);return o.length?ta.quantile(o.sort(e),.5):void 0},ta.variance=function(n,t){var e,i,o=n.length,a=0,c=0,l=-1,s=0;if(1===arguments.length)for(;++l<o;)u(e=r(n[l]))&&(i=e-a,a+=i/++s,c+=i*(e-a));else for(;++l<o;)u(e=r(t.call(n,n[l],l)))&&(i=e-a,a+=i/++s,c+=i*(e-a));return s>1?c/(s-1):void 0},ta.deviation=function(){var n=ta.variance.apply(this,arguments);return n?Math.sqrt(n):n};var ha=i(e);ta.bisectLeft=ha.left,ta.bisect=ta.bisectRight=ha.right,ta.bisector=function(n){return i(1===n.length?function(t,r){return e(n(t),r)}:n)},ta.shuffle=function(n,t,e){(i=arguments.length)<3&&(e=n.length,2>i&&(t=0));for(var r,u,i=e-t;i;)u=Math.random()*i--|0,r=n[i+t],n[i+t]=n[u+t],n[u+t]=r;return n},ta.permute=function(n,t){for(var e=t.length,r=new Array(e);e--;)r[e]=n[t[e]];return r},ta.pairs=function(n){for(var t,e=0,r=n.length-1,u=n[0],i=new Array(0>r?0:r);r>e;)i[e]=[t=u,u=n[++e]];return i},ta.zip=function(){if(!(r=arguments.length))return[];for(var n=-1,t=ta.min(arguments,o),e=new Array(t);++n<t;)for(var r,u=-1,i=e[n]=new Array(r);++u<r;)i[u]=arguments[u][n];return e},ta.transpose=function(n){return ta.zip.apply(ta,n)},ta.keys=function(n){var t=[];for(var e in n)t.push(e);return t},ta.values=function(n){var t=[];for(var e in n)t.push(n[e]);return t},ta.entries=function(n){var t=[];for(var e in n)t.push({key:e,value:n[e]});return t},ta.merge=function(n){for(var t,e,r,u=n.length,i=-1,o=0;++i<u;)o+=n[i].length;for(e=new Array(o);--u>=0;)for(r=n[u],t=r.length;--t>=0;)e[--o]=r[t];return e};var ga=Math.abs;ta.range=function(n,t,e){if(arguments.length<3&&(e=1,arguments.length<2&&(t=n,n=0)),(t-n)/e===1/0)throw new Error("infinite range");var r,u=[],i=a(ga(e)),o=-1;if(n*=i,t*=i,e*=i,0>e)for(;(r=n+e*++o)>t;)u.push(r/i);else for(;(r=n+e*++o)<t;)u.push(r/i);return u},ta.map=function(n,t){var e=new l;if(n instanceof l)n.forEach(function(n,t){e.set(n,t)});else if(Array.isArray(n)){var r,u=-1,i=n.length;if(1===arguments.length)for(;++u<i;)e.set(u,n[u]);else for(;++u<i;)e.set(t.call(n,r=n[u],u),r)}else for(var o in n)e.set(o,n[o]);return e};var pa="__proto__",va="\x00";c(l,{has:h,get:function(n){return this._[s(n)]},set:function(n,t){return this._[s(n)]=t},remove:g,keys:p,values:function(){var n=[];for(var t in this._)n.push(this._[t]);return n},entries:function(){var n=[];for(var t in this._)n.push({key:f(t),value:this._[t]});return n},size:v,empty:d,forEach:function(n){for(var t in this._)n.call(this,f(t),this._[t])}}),ta.nest=function(){function n(t,o,a){if(a>=i.length)return r?r.call(u,o):e?o.sort(e):o;for(var c,s,f,h,g=-1,p=o.length,v=i[a++],d=new l;++g<p;)(h=d.get(c=v(s=o[g])))?h.push(s):d.set(c,[s]);return t?(s=t(),f=function(e,r){s.set(e,n(t,r,a))}):(s={},f=function(e,r){s[e]=n(t,r,a)}),d.forEach(f),s}function t(n,e){if(e>=i.length)return n;var r=[],u=o[e++];return n.forEach(function(n,u){r.push({key:n,values:t(u,e)})}),u?r.sort(function(n,t){return u(n.key,t.key)}):r}var e,r,u={},i=[],o=[];return u.map=function(t,e){return n(e,t,0)},u.entries=function(e){return t(n(ta.map,e,0),0)},u.key=function(n){return i.push(n),u},u.sortKeys=function(n){return o[i.length-1]=n,u},u.sortValues=function(n){return e=n,u},u.rollup=function(n){return r=n,u},u},ta.set=function(n){var t=new m;if(n)for(var e=0,r=n.length;r>e;++e)t.add(n[e]);return t},c(m,{has:h,add:function(n){return this._[s(n+="")]=!0,n},remove:g,values:p,size:v,empty:d,forEach:function(n){for(var t in this._)n.call(this,f(t))}}),ta.behavior={},ta.rebind=function(n,t){for(var e,r=1,u=arguments.length;++r<u;)n[e=arguments[r]]=M(n,t,t[e]);return n};var da=["webkit","ms","moz","Moz","o","O"];ta.dispatch=function(){for(var n=new _,t=-1,e=arguments.length;++t<e;)n[arguments[t]]=w(n);return n},_.prototype.on=function(n,t){var e=n.indexOf("."),r="";if(e>=0&&(r=n.slice(e+1),n=n.slice(0,e)),n)return arguments.length<2?this[n].on(r):this[n].on(r,t);if(2===arguments.length){if(null==t)for(n in this)this.hasOwnProperty(n)&&this[n].on(r,null);return this}},ta.event=null,ta.requote=function(n){return n.replace(ma,"\\$&")};var ma=/[\\\^\$\*\+\?\|\[\]\(\)\.\{\}]/g,ya={}.__proto__?function(n,t){n.__proto__=t}:function(n,t){for(var e in t)n[e]=t[e]},Ma=function(n,t){return t.querySelector(n)},xa=function(n,t){return t.querySelectorAll(n)},ba=function(n,t){var e=n.matches||n[x(n,"matchesSelector")];return(ba=function(n,t){return e.call(n,t)})(n,t)};"function"==typeof Sizzle&&(Ma=function(n,t){return Sizzle(n,t)[0]||null},xa=Sizzle,ba=Sizzle.matchesSelector),ta.selection=function(){return ta.select(ua.documentElement)};var _a=ta.selection.prototype=[];_a.select=function(n){var t,e,r,u,i=[];n=N(n);for(var o=-1,a=this.length;++o<a;){i.push(t=[]),t.parentNode=(r=this[o]).parentNode;for(var c=-1,l=r.length;++c<l;)(u=r[c])?(t.push(e=n.call(u,u.__data__,c,o)),e&&"__data__"in u&&(e.__data__=u.__data__)):t.push(null)}return A(i)},_a.selectAll=function(n){var t,e,r=[];n=C(n);for(var u=-1,i=this.length;++u<i;)for(var o=this[u],a=-1,c=o.length;++a<c;)(e=o[a])&&(r.push(t=ra(n.call(e,e.__data__,a,u))),t.parentNode=e);return A(r)};var wa={svg:"http://www.w3.org/2000/svg",xhtml:"http://www.w3.org/1999/xhtml",xlink:"http://www.w3.org/1999/xlink",xml:"http://www.w3.org/XML/1998/namespace",xmlns:"http://www.w3.org/2000/xmlns/"};ta.ns={prefix:wa,qualify:function(n){var t=n.indexOf(":"),e=n;return t>=0&&(e=n.slice(0,t),n=n.slice(t+1)),wa.hasOwnProperty(e)?{space:wa[e],local:n}:n}},_a.attr=function(n,t){if(arguments.length<2){if("string"==typeof n){var e=this.node();return n=ta.ns.qualify(n),n.local?e.getAttributeNS(n.space,n.local):e.getAttribute(n)}for(t in n)this.each(z(t,n[t]));return this}return this.each(z(n,t))},_a.classed=function(n,t){if(arguments.length<2){if("string"==typeof n){var e=this.node(),r=(n=T(n)).length,u=-1;if(t=e.classList){for(;++u<r;)if(!t.contains(n[u]))return!1}else for(t=e.getAttribute("class");++u<r;)if(!L(n[u]).test(t))return!1;return!0}for(t in n)this.each(R(t,n[t]));return this}return this.each(R(n,t))},_a.style=function(n,e,r){var u=arguments.length;if(3>u){if("string"!=typeof n){2>u&&(e="");for(r in n)this.each(P(r,n[r],e));return this}if(2>u){var i=this.node();return t(i).getComputedStyle(i,null).getPropertyValue(n)}r=""}return this.each(P(n,e,r))},_a.property=function(n,t){if(arguments.length<2){if("string"==typeof n)return this.node()[n];for(t in n)this.each(U(t,n[t]));return this}return this.each(U(n,t))},_a.text=function(n){return arguments.length?this.each("function"==typeof n?function(){var t=n.apply(this,arguments);this.textContent=null==t?"":t}:null==n?function(){this.textContent=""}:function(){this.textContent=n}):this.node().textContent},_a.html=function(n){return arguments.length?this.each("function"==typeof n?function(){var t=n.apply(this,arguments);this.innerHTML=null==t?"":t}:null==n?function(){this.innerHTML=""}:function(){this.innerHTML=n}):this.node().innerHTML},_a.append=function(n){return n=j(n),this.select(function(){return this.appendChild(n.apply(this,arguments))})},_a.insert=function(n,t){return n=j(n),t=N(t),this.select(function(){return this.insertBefore(n.apply(this,arguments),t.apply(this,arguments)||null)})},_a.remove=function(){return this.each(F)},_a.data=function(n,t){function e(n,e){var r,u,i,o=n.length,f=e.length,h=Math.min(o,f),g=new Array(f),p=new Array(f),v=new Array(o);if(t){var d,m=new l,y=new Array(o);for(r=-1;++r<o;)m.has(d=t.call(u=n[r],u.__data__,r))?v[r]=u:m.set(d,u),y[r]=d;for(r=-1;++r<f;)(u=m.get(d=t.call(e,i=e[r],r)))?u!==!0&&(g[r]=u,u.__data__=i):p[r]=H(i),m.set(d,!0);for(r=-1;++r<o;)m.get(y[r])!==!0&&(v[r]=n[r])}else{for(r=-1;++r<h;)u=n[r],i=e[r],u?(u.__data__=i,g[r]=u):p[r]=H(i);for(;f>r;++r)p[r]=H(e[r]);for(;o>r;++r)v[r]=n[r]}p.update=g,p.parentNode=g.parentNode=v.parentNode=n.parentNode,a.push(p),c.push(g),s.push(v)}var r,u,i=-1,o=this.length;if(!arguments.length){for(n=new Array(o=(r=this[0]).length);++i<o;)(u=r[i])&&(n[i]=u.__data__);return n}var a=Z([]),c=A([]),s=A([]);if("function"==typeof n)for(;++i<o;)e(r=this[i],n.call(r,r.parentNode.__data__,i));else for(;++i<o;)e(r=this[i],n);return c.enter=function(){return a},c.exit=function(){return s},c},_a.datum=function(n){return arguments.length?this.property("__data__",n):this.property("__data__")},_a.filter=function(n){var t,e,r,u=[];"function"!=typeof n&&(n=O(n));for(var i=0,o=this.length;o>i;i++){u.push(t=[]),t.parentNode=(e=this[i]).parentNode;for(var a=0,c=e.length;c>a;a++)(r=e[a])&&n.call(r,r.__data__,a,i)&&t.push(r)}return A(u)},_a.order=function(){for(var n=-1,t=this.length;++n<t;)for(var e,r=this[n],u=r.length-1,i=r[u];--u>=0;)(e=r[u])&&(i&&i!==e.nextSibling&&i.parentNode.insertBefore(e,i),i=e);return this},_a.sort=function(n){n=I.apply(this,arguments);for(var t=-1,e=this.length;++t<e;)this[t].sort(n);return this.order()},_a.each=function(n){return Y(this,function(t,e,r){n.call(t,t.__data__,e,r)})},_a.call=function(n){var t=ra(arguments);return n.apply(t[0]=this,t),this},_a.empty=function(){return!this.node()},_a.node=function(){for(var n=0,t=this.length;t>n;n++)for(var e=this[n],r=0,u=e.length;u>r;r++){var i=e[r];if(i)return i}return null},_a.size=function(){var n=0;return Y(this,function(){++n}),n};var Sa=[];ta.selection.enter=Z,ta.selection.enter.prototype=Sa,Sa.append=_a.append,Sa.empty=_a.empty,Sa.node=_a.node,Sa.call=_a.call,Sa.size=_a.size,Sa.select=function(n){for(var t,e,r,u,i,o=[],a=-1,c=this.length;++a<c;){r=(u=this[a]).update,o.push(t=[]),t.parentNode=u.parentNode;for(var l=-1,s=u.length;++l<s;)(i=u[l])?(t.push(r[l]=e=n.call(u.parentNode,i.__data__,l,a)),e.__data__=i.__data__):t.push(null)}return A(o)},Sa.insert=function(n,t){return arguments.length<2&&(t=V(this)),_a.insert.call(this,n,t)},ta.select=function(t){var e;return"string"==typeof t?(e=[Ma(t,ua)],e.parentNode=ua.documentElement):(e=[t],e.parentNode=n(t)),A([e])},ta.selectAll=function(n){var t;return"string"==typeof n?(t=ra(xa(n,ua)),t.parentNode=ua.documentElement):(t=n,t.parentNode=null),A([t])},_a.on=function(n,t,e){var r=arguments.length;if(3>r){if("string"!=typeof n){2>r&&(t=!1);for(e in n)this.each(X(e,n[e],t));return this}if(2>r)return(r=this.node()["__on"+n])&&r._;e=!1}return this.each(X(n,t,e))};var ka=ta.map({mouseenter:"mouseover",mouseleave:"mouseout"});ua&&ka.forEach(function(n){"on"+n in ua&&ka.remove(n)});var Ea,Aa=0;ta.mouse=function(n){return J(n,k())};var Na=this.navigator&&/WebKit/.test(this.navigator.userAgent)?-1:0;ta.touch=function(n,t,e){if(arguments.length<3&&(e=t,t=k().changedTouches),t)for(var r,u=0,i=t.length;i>u;++u)if((r=t[u]).identifier===e)return J(n,r)},ta.behavior.drag=function(){function n(){this.on("mousedown.drag",i).on("touchstart.drag",o)}function e(n,t,e,i,o){return function(){function a(){var n,e,r=t(h,v);r&&(n=r[0]-M[0],e=r[1]-M[1],p|=n|e,M=r,g({type:"drag",x:r[0]+l[0],y:r[1]+l[1],dx:n,dy:e}))}function c(){t(h,v)&&(m.on(i+d,null).on(o+d,null),y(p&&ta.event.target===f),g({type:"dragend"}))}var l,s=this,f=ta.event.target,h=s.parentNode,g=r.of(s,arguments),p=0,v=n(),d=".drag"+(null==v?"":"-"+v),m=ta.select(e(f)).on(i+d,a).on(o+d,c),y=W(f),M=t(h,v);u?(l=u.apply(s,arguments),l=[l.x-M[0],l.y-M[1]]):l=[0,0],g({type:"dragstart"})}}var r=E(n,"drag","dragstart","dragend"),u=null,i=e(b,ta.mouse,t,"mousemove","mouseup"),o=e(G,ta.touch,y,"touchmove","touchend");return n.origin=function(t){return arguments.length?(u=t,n):u},ta.rebind(n,r,"on")},ta.touches=function(n,t){return arguments.length<2&&(t=k().touches),t?ra(t).map(function(t){var e=J(n,t);return e.identifier=t.identifier,e}):[]};var Ca=1e-6,za=Ca*Ca,qa=Math.PI,La=2*qa,Ta=La-Ca,Ra=qa/2,Da=qa/180,Pa=180/qa,Ua=Math.SQRT2,ja=2,Fa=4;ta.interpolateZoom=function(n,t){function e(n){var t=n*y;if(m){var e=rt(v),o=i/(ja*h)*(e*ut(Ua*t+v)-et(v));return[r+o*l,u+o*s,i*e/rt(Ua*t+v)]}return[r+n*l,u+n*s,i*Math.exp(Ua*t)]}var r=n[0],u=n[1],i=n[2],o=t[0],a=t[1],c=t[2],l=o-r,s=a-u,f=l*l+s*s,h=Math.sqrt(f),g=(c*c-i*i+Fa*f)/(2*i*ja*h),p=(c*c-i*i-Fa*f)/(2*c*ja*h),v=Math.log(Math.sqrt(g*g+1)-g),d=Math.log(Math.sqrt(p*p+1)-p),m=d-v,y=(m||Math.log(c/i))/Ua;return e.duration=1e3*y,e},ta.behavior.zoom=function(){function n(n){n.on(q,f).on(Oa+".zoom",g).on("dblclick.zoom",p).on(R,h)}function e(n){return[(n[0]-k.x)/k.k,(n[1]-k.y)/k.k]}function r(n){return[n[0]*k.k+k.x,n[1]*k.k+k.y]}function u(n){k.k=Math.max(N[0],Math.min(N[1],n))}function i(n,t){t=r(t),k.x+=n[0]-t[0],k.y+=n[1]-t[1]}function o(t,e,r,o){t.__chart__={x:k.x,y:k.y,k:k.k},u(Math.pow(2,o)),i(d=e,r),t=ta.select(t),C>0&&(t=t.transition().duration(C)),t.call(n.event)}function a(){b&&b.domain(x.range().map(function(n){return(n-k.x)/k.k}).map(x.invert)),w&&w.domain(_.range().map(function(n){return(n-k.y)/k.k}).map(_.invert))}function c(n){z++||n({type:"zoomstart"})}function l(n){a(),n({type:"zoom",scale:k.k,translate:[k.x,k.y]})}function s(n){--z||(n({type:"zoomend"}),d=null)}function f(){function n(){f=1,i(ta.mouse(u),g),l(a)}function r(){h.on(L,null).on(T,null),p(f&&ta.event.target===o),s(a)}var u=this,o=ta.event.target,a=D.of(u,arguments),f=0,h=ta.select(t(u)).on(L,n).on(T,r),g=e(ta.mouse(u)),p=W(u);Dl.call(u),c(a)}function h(){function n(){var n=ta.touches(p);return g=k.k,n.forEach(function(n){n.identifier in d&&(d[n.identifier]=e(n))}),n}function t(){var t=ta.event.target;ta.select(t).on(x,r).on(b,a),_.push(t);for(var e=ta.event.changedTouches,u=0,i=e.length;i>u;++u)d[e[u].identifier]=null;var c=n(),l=Date.now();if(1===c.length){if(500>l-M){var s=c[0];o(p,s,d[s.identifier],Math.floor(Math.log(k.k)/Math.LN2)+1),S()}M=l}else if(c.length>1){var s=c[0],f=c[1],h=s[0]-f[0],g=s[1]-f[1];m=h*h+g*g}}function r(){var n,t,e,r,o=ta.touches(p);Dl.call(p);for(var a=0,c=o.length;c>a;++a,r=null)if(e=o[a],r=d[e.identifier]){if(t)break;n=e,t=r}if(r){var s=(s=e[0]-n[0])*s+(s=e[1]-n[1])*s,f=m&&Math.sqrt(s/m);n=[(n[0]+e[0])/2,(n[1]+e[1])/2],t=[(t[0]+r[0])/2,(t[1]+r[1])/2],u(f*g)}M=null,i(n,t),l(v)}function a(){if(ta.event.touches.length){for(var t=ta.event.changedTouches,e=0,r=t.length;r>e;++e)delete d[t[e].identifier];for(var u in d)return void n()}ta.selectAll(_).on(y,null),w.on(q,f).on(R,h),E(),s(v)}var g,p=this,v=D.of(p,arguments),d={},m=0,y=".zoom-"+ta.event.changedTouches[0].identifier,x="touchmove"+y,b="touchend"+y,_=[],w=ta.select(p),E=W(p);t(),c(v),w.on(q,null).on(R,t)}function g(){var n=D.of(this,arguments);y?clearTimeout(y):(Dl.call(this),v=e(d=m||ta.mouse(this)),c(n)),y=setTimeout(function(){y=null,s(n)},50),S(),u(Math.pow(2,.002*Ha())*k.k),i(d,v),l(n)}function p(){var n=ta.mouse(this),t=Math.log(k.k)/Math.LN2;o(this,n,e(n),ta.event.shiftKey?Math.ceil(t)-1:Math.floor(t)+1)}var v,d,m,y,M,x,b,_,w,k={x:0,y:0,k:1},A=[960,500],N=Ia,C=250,z=0,q="mousedown.zoom",L="mousemove.zoom",T="mouseup.zoom",R="touchstart.zoom",D=E(n,"zoomstart","zoom","zoomend");return Oa||(Oa="onwheel"in ua?(Ha=function(){return-ta.event.deltaY*(ta.event.deltaMode?120:1)},"wheel"):"onmousewheel"in ua?(Ha=function(){return ta.event.wheelDelta},"mousewheel"):(Ha=function(){return-ta.event.detail},"MozMousePixelScroll")),n.event=function(n){n.each(function(){var n=D.of(this,arguments),t=k;Tl?ta.select(this).transition().each("start.zoom",function(){k=this.__chart__||{x:0,y:0,k:1},c(n)}).tween("zoom:zoom",function(){var e=A[0],r=A[1],u=d?d[0]:e/2,i=d?d[1]:r/2,o=ta.interpolateZoom([(u-k.x)/k.k,(i-k.y)/k.k,e/k.k],[(u-t.x)/t.k,(i-t.y)/t.k,e/t.k]);return function(t){var r=o(t),a=e/r[2];this.__chart__=k={x:u-r[0]*a,y:i-r[1]*a,k:a},l(n)}}).each("interrupt.zoom",function(){s(n)}).each("end.zoom",function(){s(n)}):(this.__chart__=k,c(n),l(n),s(n))})},n.translate=function(t){return arguments.length?(k={x:+t[0],y:+t[1],k:k.k},a(),n):[k.x,k.y]},n.scale=function(t){return arguments.length?(k={x:k.x,y:k.y,k:+t},a(),n):k.k},n.scaleExtent=function(t){return arguments.length?(N=null==t?Ia:[+t[0],+t[1]],n):N},n.center=function(t){return arguments.length?(m=t&&[+t[0],+t[1]],n):m},n.size=function(t){return arguments.length?(A=t&&[+t[0],+t[1]],n):A},n.duration=function(t){return arguments.length?(C=+t,n):C},n.x=function(t){return arguments.length?(b=t,x=t.copy(),k={x:0,y:0,k:1},n):b},n.y=function(t){return arguments.length?(w=t,_=t.copy(),k={x:0,y:0,k:1},n):w},ta.rebind(n,D,"on")};var Ha,Oa,Ia=[0,1/0];ta.color=ot,ot.prototype.toString=function(){return this.rgb()+""},ta.hsl=at;var Ya=at.prototype=new ot;Ya.brighter=function(n){return n=Math.pow(.7,arguments.length?n:1),new at(this.h,this.s,this.l/n)},Ya.darker=function(n){return n=Math.pow(.7,arguments.length?n:1),new at(this.h,this.s,n*this.l)},Ya.rgb=function(){return ct(this.h,this.s,this.l)},ta.hcl=lt;var Za=lt.prototype=new ot;Za.brighter=function(n){return new lt(this.h,this.c,Math.min(100,this.l+Va*(arguments.length?n:1)))},Za.darker=function(n){return new lt(this.h,this.c,Math.max(0,this.l-Va*(arguments.length?n:1)))},Za.rgb=function(){return st(this.h,this.c,this.l).rgb()},ta.lab=ft;var Va=18,Xa=.95047,$a=1,Ba=1.08883,Wa=ft.prototype=new ot;Wa.brighter=function(n){return new ft(Math.min(100,this.l+Va*(arguments.length?n:1)),this.a,this.b)},Wa.darker=function(n){return new ft(Math.max(0,this.l-Va*(arguments.length?n:1)),this.a,this.b)},Wa.rgb=function(){return ht(this.l,this.a,this.b)},ta.rgb=mt;var Ja=mt.prototype=new ot;Ja.brighter=function(n){n=Math.pow(.7,arguments.length?n:1);var t=this.r,e=this.g,r=this.b,u=30;return t||e||r?(t&&u>t&&(t=u),e&&u>e&&(e=u),r&&u>r&&(r=u),new mt(Math.min(255,t/n),Math.min(255,e/n),Math.min(255,r/n))):new mt(u,u,u)},Ja.darker=function(n){return n=Math.pow(.7,arguments.length?n:1),new mt(n*this.r,n*this.g,n*this.b)},Ja.hsl=function(){return _t(this.r,this.g,this.b)},Ja.toString=function(){return"#"+xt(this.r)+xt(this.g)+xt(this.b)};var Ga=ta.map({aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074});Ga.forEach(function(n,t){Ga.set(n,yt(t))}),ta.functor=Et,ta.xhr=At(y),ta.dsv=function(n,t){function e(n,e,i){arguments.length<3&&(i=e,e=null);var o=Nt(n,t,null==e?r:u(e),i);return o.row=function(n){return arguments.length?o.response(null==(e=n)?r:u(n)):e},o}function r(n){return e.parse(n.responseText)}function u(n){return function(t){return e.parse(t.responseText,n)}}function i(t){return t.map(o).join(n)}function o(n){return a.test(n)?'"'+n.replace(/\"/g,'""')+'"':n}var a=new RegExp('["'+n+"\n]"),c=n.charCodeAt(0);return e.parse=function(n,t){var r;return e.parseRows(n,function(n,e){if(r)return r(n,e-1);var u=new Function("d","return {"+n.map(function(n,t){return JSON.stringify(n)+": d["+t+"]"}).join(",")+"}");r=t?function(n,e){return t(u(n),e)}:u})},e.parseRows=function(n,t){function e(){if(s>=l)return o;if(u)return u=!1,i;var t=s;if(34===n.charCodeAt(t)){for(var e=t;e++<l;)if(34===n.charCodeAt(e)){if(34!==n.charCodeAt(e+1))break;++e}s=e+2;var r=n.charCodeAt(e+1);return 13===r?(u=!0,10===n.charCodeAt(e+2)&&++s):10===r&&(u=!0),n.slice(t+1,e).replace(/""/g,'"')}for(;l>s;){var r=n.charCodeAt(s++),a=1;if(10===r)u=!0;else if(13===r)u=!0,10===n.charCodeAt(s)&&(++s,++a);else if(r!==c)continue;return n.slice(t,s-a)}return n.slice(t)}for(var r,u,i={},o={},a=[],l=n.length,s=0,f=0;(r=e())!==o;){for(var h=[];r!==i&&r!==o;)h.push(r),r=e();t&&null==(h=t(h,f++))||a.push(h)}return a},e.format=function(t){if(Array.isArray(t[0]))return e.formatRows(t);var r=new m,u=[];return t.forEach(function(n){for(var t in n)r.has(t)||u.push(r.add(t))}),[u.map(o).join(n)].concat(t.map(function(t){return u.map(function(n){return o(t[n])}).join(n)})).join("\n")},e.formatRows=function(n){return n.map(i).join("\n")},e},ta.csv=ta.dsv(",","text/csv"),ta.tsv=ta.dsv("	","text/tab-separated-values");var Ka,Qa,nc,tc,ec,rc=this[x(this,"requestAnimationFrame")]||function(n){setTimeout(n,17)};ta.timer=function(n,t,e){var r=arguments.length;2>r&&(t=0),3>r&&(e=Date.now());var u=e+t,i={c:n,t:u,f:!1,n:null};Qa?Qa.n=i:Ka=i,Qa=i,nc||(tc=clearTimeout(tc),nc=1,rc(qt))},ta.timer.flush=function(){Lt(),Tt()},ta.round=function(n,t){return t?Math.round(n*(t=Math.pow(10,t)))/t:Math.round(n)};var uc=["y","z","a","f","p","n","\xb5","m","","k","M","G","T","P","E","Z","Y"].map(Dt);ta.formatPrefix=function(n,t){var e=0;return n&&(0>n&&(n*=-1),t&&(n=ta.round(n,Rt(n,t))),e=1+Math.floor(1e-12+Math.log(n)/Math.LN10),e=Math.max(-24,Math.min(24,3*Math.floor((e-1)/3)))),uc[8+e/3]};var ic=/(?:([^{])?([<>=^]))?([+\- ])?([$#])?(0)?(\d+)?(,)?(\.-?\d+)?([a-z%])?/i,oc=ta.map({b:function(n){return n.toString(2)},c:function(n){return String.fromCharCode(n)},o:function(n){return n.toString(8)},x:function(n){return n.toString(16)},X:function(n){return n.toString(16).toUpperCase()},g:function(n,t){return n.toPrecision(t)},e:function(n,t){return n.toExponential(t)},f:function(n,t){return n.toFixed(t)},r:function(n,t){return(n=ta.round(n,Rt(n,t))).toFixed(Math.max(0,Math.min(20,Rt(n*(1+1e-15),t))))}}),ac=ta.time={},cc=Date;jt.prototype={getDate:function(){return this._.getUTCDate()},getDay:function(){return this._.getUTCDay()},getFullYear:function(){return this._.getUTCFullYear()},getHours:function(){return this._.getUTCHours()},getMilliseconds:function(){return this._.getUTCMilliseconds()},getMinutes:function(){return this._.getUTCMinutes()},getMonth:function(){return this._.getUTCMonth()},getSeconds:function(){return this._.getUTCSeconds()},getTime:function(){return this._.getTime()},getTimezoneOffset:function(){return 0},valueOf:function(){return this._.valueOf()},setDate:function(){lc.setUTCDate.apply(this._,arguments)},setDay:function(){lc.setUTCDay.apply(this._,arguments)},setFullYear:function(){lc.setUTCFullYear.apply(this._,arguments)},setHours:function(){lc.setUTCHours.apply(this._,arguments)},setMilliseconds:function(){lc.setUTCMilliseconds.apply(this._,arguments)},setMinutes:function(){lc.setUTCMinutes.apply(this._,arguments)},setMonth:function(){lc.setUTCMonth.apply(this._,arguments)},setSeconds:function(){lc.setUTCSeconds.apply(this._,arguments)},setTime:function(){lc.setTime.apply(this._,arguments)}};var lc=Date.prototype;ac.year=Ft(function(n){return n=ac.day(n),n.setMonth(0,1),n},function(n,t){n.setFullYear(n.getFullYear()+t)},function(n){return n.getFullYear()}),ac.years=ac.year.range,ac.years.utc=ac.year.utc.range,ac.day=Ft(function(n){var t=new cc(2e3,0);return t.setFullYear(n.getFullYear(),n.getMonth(),n.getDate()),t},function(n,t){n.setDate(n.getDate()+t)},function(n){return n.getDate()-1}),ac.days=ac.day.range,ac.days.utc=ac.day.utc.range,ac.dayOfYear=function(n){var t=ac.year(n);return Math.floor((n-t-6e4*(n.getTimezoneOffset()-t.getTimezoneOffset()))/864e5)},["sunday","monday","tuesday","wednesday","thursday","friday","saturday"].forEach(function(n,t){t=7-t;var e=ac[n]=Ft(function(n){return(n=ac.day(n)).setDate(n.getDate()-(n.getDay()+t)%7),n},function(n,t){n.setDate(n.getDate()+7*Math.floor(t))},function(n){var e=ac.year(n).getDay();return Math.floor((ac.dayOfYear(n)+(e+t)%7)/7)-(e!==t)});ac[n+"s"]=e.range,ac[n+"s"].utc=e.utc.range,ac[n+"OfYear"]=function(n){var e=ac.year(n).getDay();return Math.floor((ac.dayOfYear(n)+(e+t)%7)/7)}}),ac.week=ac.sunday,ac.weeks=ac.sunday.range,ac.weeks.utc=ac.sunday.utc.range,ac.weekOfYear=ac.sundayOfYear;var sc={"-":"",_:" ",0:"0"},fc=/^\s*\d+/,hc=/^%/;ta.locale=function(n){return{numberFormat:Pt(n),timeFormat:Ot(n)}};var gc=ta.locale({decimal:".",thousands:",",grouping:[3],currency:["$",""],dateTime:"%a %b %e %X %Y",date:"%m/%d/%Y",time:"%H:%M:%S",periods:["AM","PM"],days:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],shortDays:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],months:["January","February","March","April","May","June","July","August","September","October","November","December"],shortMonths:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]});ta.format=gc.numberFormat,ta.geo={},ce.prototype={s:0,t:0,add:function(n){le(n,this.t,pc),le(pc.s,this.s,this),this.s?this.t+=pc.t:this.s=pc.t
+},reset:function(){this.s=this.t=0},valueOf:function(){return this.s}};var pc=new ce;ta.geo.stream=function(n,t){n&&vc.hasOwnProperty(n.type)?vc[n.type](n,t):se(n,t)};var vc={Feature:function(n,t){se(n.geometry,t)},FeatureCollection:function(n,t){for(var e=n.features,r=-1,u=e.length;++r<u;)se(e[r].geometry,t)}},dc={Sphere:function(n,t){t.sphere()},Point:function(n,t){n=n.coordinates,t.point(n[0],n[1],n[2])},MultiPoint:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)n=e[r],t.point(n[0],n[1],n[2])},LineString:function(n,t){fe(n.coordinates,t,0)},MultiLineString:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)fe(e[r],t,0)},Polygon:function(n,t){he(n.coordinates,t)},MultiPolygon:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)he(e[r],t)},GeometryCollection:function(n,t){for(var e=n.geometries,r=-1,u=e.length;++r<u;)se(e[r],t)}};ta.geo.area=function(n){return mc=0,ta.geo.stream(n,Mc),mc};var mc,yc=new ce,Mc={sphere:function(){mc+=4*qa},point:b,lineStart:b,lineEnd:b,polygonStart:function(){yc.reset(),Mc.lineStart=ge},polygonEnd:function(){var n=2*yc;mc+=0>n?4*qa+n:n,Mc.lineStart=Mc.lineEnd=Mc.point=b}};ta.geo.bounds=function(){function n(n,t){M.push(x=[s=n,h=n]),f>t&&(f=t),t>g&&(g=t)}function t(t,e){var r=pe([t*Da,e*Da]);if(m){var u=de(m,r),i=[u[1],-u[0],0],o=de(i,u);Me(o),o=xe(o);var c=t-p,l=c>0?1:-1,v=o[0]*Pa*l,d=ga(c)>180;if(d^(v>l*p&&l*t>v)){var y=o[1]*Pa;y>g&&(g=y)}else if(v=(v+360)%360-180,d^(v>l*p&&l*t>v)){var y=-o[1]*Pa;f>y&&(f=y)}else f>e&&(f=e),e>g&&(g=e);d?p>t?a(s,t)>a(s,h)&&(h=t):a(t,h)>a(s,h)&&(s=t):h>=s?(s>t&&(s=t),t>h&&(h=t)):t>p?a(s,t)>a(s,h)&&(h=t):a(t,h)>a(s,h)&&(s=t)}else n(t,e);m=r,p=t}function e(){b.point=t}function r(){x[0]=s,x[1]=h,b.point=n,m=null}function u(n,e){if(m){var r=n-p;y+=ga(r)>180?r+(r>0?360:-360):r}else v=n,d=e;Mc.point(n,e),t(n,e)}function i(){Mc.lineStart()}function o(){u(v,d),Mc.lineEnd(),ga(y)>Ca&&(s=-(h=180)),x[0]=s,x[1]=h,m=null}function a(n,t){return(t-=n)<0?t+360:t}function c(n,t){return n[0]-t[0]}function l(n,t){return t[0]<=t[1]?t[0]<=n&&n<=t[1]:n<t[0]||t[1]<n}var s,f,h,g,p,v,d,m,y,M,x,b={point:n,lineStart:e,lineEnd:r,polygonStart:function(){b.point=u,b.lineStart=i,b.lineEnd=o,y=0,Mc.polygonStart()},polygonEnd:function(){Mc.polygonEnd(),b.point=n,b.lineStart=e,b.lineEnd=r,0>yc?(s=-(h=180),f=-(g=90)):y>Ca?g=90:-Ca>y&&(f=-90),x[0]=s,x[1]=h}};return function(n){g=h=-(s=f=1/0),M=[],ta.geo.stream(n,b);var t=M.length;if(t){M.sort(c);for(var e,r=1,u=M[0],i=[u];t>r;++r)e=M[r],l(e[0],u)||l(e[1],u)?(a(u[0],e[1])>a(u[0],u[1])&&(u[1]=e[1]),a(e[0],u[1])>a(u[0],u[1])&&(u[0]=e[0])):i.push(u=e);for(var o,e,p=-1/0,t=i.length-1,r=0,u=i[t];t>=r;u=e,++r)e=i[r],(o=a(u[1],e[0]))>p&&(p=o,s=e[0],h=u[1])}return M=x=null,1/0===s||1/0===f?[[0/0,0/0],[0/0,0/0]]:[[s,f],[h,g]]}}(),ta.geo.centroid=function(n){xc=bc=_c=wc=Sc=kc=Ec=Ac=Nc=Cc=zc=0,ta.geo.stream(n,qc);var t=Nc,e=Cc,r=zc,u=t*t+e*e+r*r;return za>u&&(t=kc,e=Ec,r=Ac,Ca>bc&&(t=_c,e=wc,r=Sc),u=t*t+e*e+r*r,za>u)?[0/0,0/0]:[Math.atan2(e,t)*Pa,tt(r/Math.sqrt(u))*Pa]};var xc,bc,_c,wc,Sc,kc,Ec,Ac,Nc,Cc,zc,qc={sphere:b,point:_e,lineStart:Se,lineEnd:ke,polygonStart:function(){qc.lineStart=Ee},polygonEnd:function(){qc.lineStart=Se}},Lc=Le(Ne,Pe,je,[-qa,-qa/2]),Tc=1e9;ta.geo.clipExtent=function(){var n,t,e,r,u,i,o={stream:function(n){return u&&(u.valid=!1),u=i(n),u.valid=!0,u},extent:function(a){return arguments.length?(i=Ie(n=+a[0][0],t=+a[0][1],e=+a[1][0],r=+a[1][1]),u&&(u.valid=!1,u=null),o):[[n,t],[e,r]]}};return o.extent([[0,0],[960,500]])},(ta.geo.conicEqualArea=function(){return Ye(Ze)}).raw=Ze,ta.geo.albers=function(){return ta.geo.conicEqualArea().rotate([96,0]).center([-.6,38.7]).parallels([29.5,45.5]).scale(1070)},ta.geo.albersUsa=function(){function n(n){var i=n[0],o=n[1];return t=null,e(i,o),t||(r(i,o),t)||u(i,o),t}var t,e,r,u,i=ta.geo.albers(),o=ta.geo.conicEqualArea().rotate([154,0]).center([-2,58.5]).parallels([55,65]),a=ta.geo.conicEqualArea().rotate([157,0]).center([-3,19.9]).parallels([8,18]),c={point:function(n,e){t=[n,e]}};return n.invert=function(n){var t=i.scale(),e=i.translate(),r=(n[0]-e[0])/t,u=(n[1]-e[1])/t;return(u>=.12&&.234>u&&r>=-.425&&-.214>r?o:u>=.166&&.234>u&&r>=-.214&&-.115>r?a:i).invert(n)},n.stream=function(n){var t=i.stream(n),e=o.stream(n),r=a.stream(n);return{point:function(n,u){t.point(n,u),e.point(n,u),r.point(n,u)},sphere:function(){t.sphere(),e.sphere(),r.sphere()},lineStart:function(){t.lineStart(),e.lineStart(),r.lineStart()},lineEnd:function(){t.lineEnd(),e.lineEnd(),r.lineEnd()},polygonStart:function(){t.polygonStart(),e.polygonStart(),r.polygonStart()},polygonEnd:function(){t.polygonEnd(),e.polygonEnd(),r.polygonEnd()}}},n.precision=function(t){return arguments.length?(i.precision(t),o.precision(t),a.precision(t),n):i.precision()},n.scale=function(t){return arguments.length?(i.scale(t),o.scale(.35*t),a.scale(t),n.translate(i.translate())):i.scale()},n.translate=function(t){if(!arguments.length)return i.translate();var l=i.scale(),s=+t[0],f=+t[1];return e=i.translate(t).clipExtent([[s-.455*l,f-.238*l],[s+.455*l,f+.238*l]]).stream(c).point,r=o.translate([s-.307*l,f+.201*l]).clipExtent([[s-.425*l+Ca,f+.12*l+Ca],[s-.214*l-Ca,f+.234*l-Ca]]).stream(c).point,u=a.translate([s-.205*l,f+.212*l]).clipExtent([[s-.214*l+Ca,f+.166*l+Ca],[s-.115*l-Ca,f+.234*l-Ca]]).stream(c).point,n},n.scale(1070)};var Rc,Dc,Pc,Uc,jc,Fc,Hc={point:b,lineStart:b,lineEnd:b,polygonStart:function(){Dc=0,Hc.lineStart=Ve},polygonEnd:function(){Hc.lineStart=Hc.lineEnd=Hc.point=b,Rc+=ga(Dc/2)}},Oc={point:Xe,lineStart:b,lineEnd:b,polygonStart:b,polygonEnd:b},Ic={point:We,lineStart:Je,lineEnd:Ge,polygonStart:function(){Ic.lineStart=Ke},polygonEnd:function(){Ic.point=We,Ic.lineStart=Je,Ic.lineEnd=Ge}};ta.geo.path=function(){function n(n){return n&&("function"==typeof a&&i.pointRadius(+a.apply(this,arguments)),o&&o.valid||(o=u(i)),ta.geo.stream(n,o)),i.result()}function t(){return o=null,n}var e,r,u,i,o,a=4.5;return n.area=function(n){return Rc=0,ta.geo.stream(n,u(Hc)),Rc},n.centroid=function(n){return _c=wc=Sc=kc=Ec=Ac=Nc=Cc=zc=0,ta.geo.stream(n,u(Ic)),zc?[Nc/zc,Cc/zc]:Ac?[kc/Ac,Ec/Ac]:Sc?[_c/Sc,wc/Sc]:[0/0,0/0]},n.bounds=function(n){return jc=Fc=-(Pc=Uc=1/0),ta.geo.stream(n,u(Oc)),[[Pc,Uc],[jc,Fc]]},n.projection=function(n){return arguments.length?(u=(e=n)?n.stream||tr(n):y,t()):e},n.context=function(n){return arguments.length?(i=null==(r=n)?new $e:new Qe(n),"function"!=typeof a&&i.pointRadius(a),t()):r},n.pointRadius=function(t){return arguments.length?(a="function"==typeof t?t:(i.pointRadius(+t),+t),n):a},n.projection(ta.geo.albersUsa()).context(null)},ta.geo.transform=function(n){return{stream:function(t){var e=new er(t);for(var r in n)e[r]=n[r];return e}}},er.prototype={point:function(n,t){this.stream.point(n,t)},sphere:function(){this.stream.sphere()},lineStart:function(){this.stream.lineStart()},lineEnd:function(){this.stream.lineEnd()},polygonStart:function(){this.stream.polygonStart()},polygonEnd:function(){this.stream.polygonEnd()}},ta.geo.projection=ur,ta.geo.projectionMutator=ir,(ta.geo.equirectangular=function(){return ur(ar)}).raw=ar.invert=ar,ta.geo.rotation=function(n){function t(t){return t=n(t[0]*Da,t[1]*Da),t[0]*=Pa,t[1]*=Pa,t}return n=lr(n[0]%360*Da,n[1]*Da,n.length>2?n[2]*Da:0),t.invert=function(t){return t=n.invert(t[0]*Da,t[1]*Da),t[0]*=Pa,t[1]*=Pa,t},t},cr.invert=ar,ta.geo.circle=function(){function n(){var n="function"==typeof r?r.apply(this,arguments):r,t=lr(-n[0]*Da,-n[1]*Da,0).invert,u=[];return e(null,null,1,{point:function(n,e){u.push(n=t(n,e)),n[0]*=Pa,n[1]*=Pa}}),{type:"Polygon",coordinates:[u]}}var t,e,r=[0,0],u=6;return n.origin=function(t){return arguments.length?(r=t,n):r},n.angle=function(r){return arguments.length?(e=gr((t=+r)*Da,u*Da),n):t},n.precision=function(r){return arguments.length?(e=gr(t*Da,(u=+r)*Da),n):u},n.angle(90)},ta.geo.distance=function(n,t){var e,r=(t[0]-n[0])*Da,u=n[1]*Da,i=t[1]*Da,o=Math.sin(r),a=Math.cos(r),c=Math.sin(u),l=Math.cos(u),s=Math.sin(i),f=Math.cos(i);return Math.atan2(Math.sqrt((e=f*o)*e+(e=l*s-c*f*a)*e),c*s+l*f*a)},ta.geo.graticule=function(){function n(){return{type:"MultiLineString",coordinates:t()}}function t(){return ta.range(Math.ceil(i/d)*d,u,d).map(h).concat(ta.range(Math.ceil(l/m)*m,c,m).map(g)).concat(ta.range(Math.ceil(r/p)*p,e,p).filter(function(n){return ga(n%d)>Ca}).map(s)).concat(ta.range(Math.ceil(a/v)*v,o,v).filter(function(n){return ga(n%m)>Ca}).map(f))}var e,r,u,i,o,a,c,l,s,f,h,g,p=10,v=p,d=90,m=360,y=2.5;return n.lines=function(){return t().map(function(n){return{type:"LineString",coordinates:n}})},n.outline=function(){return{type:"Polygon",coordinates:[h(i).concat(g(c).slice(1),h(u).reverse().slice(1),g(l).reverse().slice(1))]}},n.extent=function(t){return arguments.length?n.majorExtent(t).minorExtent(t):n.minorExtent()},n.majorExtent=function(t){return arguments.length?(i=+t[0][0],u=+t[1][0],l=+t[0][1],c=+t[1][1],i>u&&(t=i,i=u,u=t),l>c&&(t=l,l=c,c=t),n.precision(y)):[[i,l],[u,c]]},n.minorExtent=function(t){return arguments.length?(r=+t[0][0],e=+t[1][0],a=+t[0][1],o=+t[1][1],r>e&&(t=r,r=e,e=t),a>o&&(t=a,a=o,o=t),n.precision(y)):[[r,a],[e,o]]},n.step=function(t){return arguments.length?n.majorStep(t).minorStep(t):n.minorStep()},n.majorStep=function(t){return arguments.length?(d=+t[0],m=+t[1],n):[d,m]},n.minorStep=function(t){return arguments.length?(p=+t[0],v=+t[1],n):[p,v]},n.precision=function(t){return arguments.length?(y=+t,s=vr(a,o,90),f=dr(r,e,y),h=vr(l,c,90),g=dr(i,u,y),n):y},n.majorExtent([[-180,-90+Ca],[180,90-Ca]]).minorExtent([[-180,-80-Ca],[180,80+Ca]])},ta.geo.greatArc=function(){function n(){return{type:"LineString",coordinates:[t||r.apply(this,arguments),e||u.apply(this,arguments)]}}var t,e,r=mr,u=yr;return n.distance=function(){return ta.geo.distance(t||r.apply(this,arguments),e||u.apply(this,arguments))},n.source=function(e){return arguments.length?(r=e,t="function"==typeof e?null:e,n):r},n.target=function(t){return arguments.length?(u=t,e="function"==typeof t?null:t,n):u},n.precision=function(){return arguments.length?n:0},n},ta.geo.interpolate=function(n,t){return Mr(n[0]*Da,n[1]*Da,t[0]*Da,t[1]*Da)},ta.geo.length=function(n){return Yc=0,ta.geo.stream(n,Zc),Yc};var Yc,Zc={sphere:b,point:b,lineStart:xr,lineEnd:b,polygonStart:b,polygonEnd:b},Vc=br(function(n){return Math.sqrt(2/(1+n))},function(n){return 2*Math.asin(n/2)});(ta.geo.azimuthalEqualArea=function(){return ur(Vc)}).raw=Vc;var Xc=br(function(n){var t=Math.acos(n);return t&&t/Math.sin(t)},y);(ta.geo.azimuthalEquidistant=function(){return ur(Xc)}).raw=Xc,(ta.geo.conicConformal=function(){return Ye(_r)}).raw=_r,(ta.geo.conicEquidistant=function(){return Ye(wr)}).raw=wr;var $c=br(function(n){return 1/n},Math.atan);(ta.geo.gnomonic=function(){return ur($c)}).raw=$c,Sr.invert=function(n,t){return[n,2*Math.atan(Math.exp(t))-Ra]},(ta.geo.mercator=function(){return kr(Sr)}).raw=Sr;var Bc=br(function(){return 1},Math.asin);(ta.geo.orthographic=function(){return ur(Bc)}).raw=Bc;var Wc=br(function(n){return 1/(1+n)},function(n){return 2*Math.atan(n)});(ta.geo.stereographic=function(){return ur(Wc)}).raw=Wc,Er.invert=function(n,t){return[-t,2*Math.atan(Math.exp(n))-Ra]},(ta.geo.transverseMercator=function(){var n=kr(Er),t=n.center,e=n.rotate;return n.center=function(n){return n?t([-n[1],n[0]]):(n=t(),[n[1],-n[0]])},n.rotate=function(n){return n?e([n[0],n[1],n.length>2?n[2]+90:90]):(n=e(),[n[0],n[1],n[2]-90])},e([0,0,90])}).raw=Er,ta.geom={},ta.geom.hull=function(n){function t(n){if(n.length<3)return[];var t,u=Et(e),i=Et(r),o=n.length,a=[],c=[];for(t=0;o>t;t++)a.push([+u.call(this,n[t],t),+i.call(this,n[t],t),t]);for(a.sort(zr),t=0;o>t;t++)c.push([a[t][0],-a[t][1]]);var l=Cr(a),s=Cr(c),f=s[0]===l[0],h=s[s.length-1]===l[l.length-1],g=[];for(t=l.length-1;t>=0;--t)g.push(n[a[l[t]][2]]);for(t=+f;t<s.length-h;++t)g.push(n[a[s[t]][2]]);return g}var e=Ar,r=Nr;return arguments.length?t(n):(t.x=function(n){return arguments.length?(e=n,t):e},t.y=function(n){return arguments.length?(r=n,t):r},t)},ta.geom.polygon=function(n){return ya(n,Jc),n};var Jc=ta.geom.polygon.prototype=[];Jc.area=function(){for(var n,t=-1,e=this.length,r=this[e-1],u=0;++t<e;)n=r,r=this[t],u+=n[1]*r[0]-n[0]*r[1];return.5*u},Jc.centroid=function(n){var t,e,r=-1,u=this.length,i=0,o=0,a=this[u-1];for(arguments.length||(n=-1/(6*this.area()));++r<u;)t=a,a=this[r],e=t[0]*a[1]-a[0]*t[1],i+=(t[0]+a[0])*e,o+=(t[1]+a[1])*e;return[i*n,o*n]},Jc.clip=function(n){for(var t,e,r,u,i,o,a=Tr(n),c=-1,l=this.length-Tr(this),s=this[l-1];++c<l;){for(t=n.slice(),n.length=0,u=this[c],i=t[(r=t.length-a)-1],e=-1;++e<r;)o=t[e],qr(o,s,u)?(qr(i,s,u)||n.push(Lr(i,o,s,u)),n.push(o)):qr(i,s,u)&&n.push(Lr(i,o,s,u)),i=o;a&&n.push(n[0]),s=u}return n};var Gc,Kc,Qc,nl,tl,el=[],rl=[];Or.prototype.prepare=function(){for(var n,t=this.edges,e=t.length;e--;)n=t[e].edge,n.b&&n.a||t.splice(e,1);return t.sort(Yr),t.length},Qr.prototype={start:function(){return this.edge.l===this.site?this.edge.a:this.edge.b},end:function(){return this.edge.l===this.site?this.edge.b:this.edge.a}},nu.prototype={insert:function(n,t){var e,r,u;if(n){if(t.P=n,t.N=n.N,n.N&&(n.N.P=t),n.N=t,n.R){for(n=n.R;n.L;)n=n.L;n.L=t}else n.R=t;e=n}else this._?(n=uu(this._),t.P=null,t.N=n,n.P=n.L=t,e=n):(t.P=t.N=null,this._=t,e=null);for(t.L=t.R=null,t.U=e,t.C=!0,n=t;e&&e.C;)r=e.U,e===r.L?(u=r.R,u&&u.C?(e.C=u.C=!1,r.C=!0,n=r):(n===e.R&&(eu(this,e),n=e,e=n.U),e.C=!1,r.C=!0,ru(this,r))):(u=r.L,u&&u.C?(e.C=u.C=!1,r.C=!0,n=r):(n===e.L&&(ru(this,e),n=e,e=n.U),e.C=!1,r.C=!0,eu(this,r))),e=n.U;this._.C=!1},remove:function(n){n.N&&(n.N.P=n.P),n.P&&(n.P.N=n.N),n.N=n.P=null;var t,e,r,u=n.U,i=n.L,o=n.R;if(e=i?o?uu(o):i:o,u?u.L===n?u.L=e:u.R=e:this._=e,i&&o?(r=e.C,e.C=n.C,e.L=i,i.U=e,e!==o?(u=e.U,e.U=n.U,n=e.R,u.L=n,e.R=o,o.U=e):(e.U=u,u=e,n=e.R)):(r=n.C,n=e),n&&(n.U=u),!r){if(n&&n.C)return void(n.C=!1);do{if(n===this._)break;if(n===u.L){if(t=u.R,t.C&&(t.C=!1,u.C=!0,eu(this,u),t=u.R),t.L&&t.L.C||t.R&&t.R.C){t.R&&t.R.C||(t.L.C=!1,t.C=!0,ru(this,t),t=u.R),t.C=u.C,u.C=t.R.C=!1,eu(this,u),n=this._;break}}else if(t=u.L,t.C&&(t.C=!1,u.C=!0,ru(this,u),t=u.L),t.L&&t.L.C||t.R&&t.R.C){t.L&&t.L.C||(t.R.C=!1,t.C=!0,eu(this,t),t=u.L),t.C=u.C,u.C=t.L.C=!1,ru(this,u),n=this._;break}t.C=!0,n=u,u=u.U}while(!n.C);n&&(n.C=!1)}}},ta.geom.voronoi=function(n){function t(n){var t=new Array(n.length),r=a[0][0],u=a[0][1],i=a[1][0],o=a[1][1];return iu(e(n),a).cells.forEach(function(e,a){var c=e.edges,l=e.site,s=t[a]=c.length?c.map(function(n){var t=n.start();return[t.x,t.y]}):l.x>=r&&l.x<=i&&l.y>=u&&l.y<=o?[[r,o],[i,o],[i,u],[r,u]]:[];s.point=n[a]}),t}function e(n){return n.map(function(n,t){return{x:Math.round(i(n,t)/Ca)*Ca,y:Math.round(o(n,t)/Ca)*Ca,i:t}})}var r=Ar,u=Nr,i=r,o=u,a=ul;return n?t(n):(t.links=function(n){return iu(e(n)).edges.filter(function(n){return n.l&&n.r}).map(function(t){return{source:n[t.l.i],target:n[t.r.i]}})},t.triangles=function(n){var t=[];return iu(e(n)).cells.forEach(function(e,r){for(var u,i,o=e.site,a=e.edges.sort(Yr),c=-1,l=a.length,s=a[l-1].edge,f=s.l===o?s.r:s.l;++c<l;)u=s,i=f,s=a[c].edge,f=s.l===o?s.r:s.l,r<i.i&&r<f.i&&au(o,i,f)<0&&t.push([n[r],n[i.i],n[f.i]])}),t},t.x=function(n){return arguments.length?(i=Et(r=n),t):r},t.y=function(n){return arguments.length?(o=Et(u=n),t):u},t.clipExtent=function(n){return arguments.length?(a=null==n?ul:n,t):a===ul?null:a},t.size=function(n){return arguments.length?t.clipExtent(n&&[[0,0],n]):a===ul?null:a&&a[1]},t)};var ul=[[-1e6,-1e6],[1e6,1e6]];ta.geom.delaunay=function(n){return ta.geom.voronoi().triangles(n)},ta.geom.quadtree=function(n,t,e,r,u){function i(n){function i(n,t,e,r,u,i,o,a){if(!isNaN(e)&&!isNaN(r))if(n.leaf){var c=n.x,s=n.y;if(null!=c)if(ga(c-e)+ga(s-r)<.01)l(n,t,e,r,u,i,o,a);else{var f=n.point;n.x=n.y=n.point=null,l(n,f,c,s,u,i,o,a),l(n,t,e,r,u,i,o,a)}else n.x=e,n.y=r,n.point=t}else l(n,t,e,r,u,i,o,a)}function l(n,t,e,r,u,o,a,c){var l=.5*(u+a),s=.5*(o+c),f=e>=l,h=r>=s,g=h<<1|f;n.leaf=!1,n=n.nodes[g]||(n.nodes[g]=su()),f?u=l:a=l,h?o=s:c=s,i(n,t,e,r,u,o,a,c)}var s,f,h,g,p,v,d,m,y,M=Et(a),x=Et(c);if(null!=t)v=t,d=e,m=r,y=u;else if(m=y=-(v=d=1/0),f=[],h=[],p=n.length,o)for(g=0;p>g;++g)s=n[g],s.x<v&&(v=s.x),s.y<d&&(d=s.y),s.x>m&&(m=s.x),s.y>y&&(y=s.y),f.push(s.x),h.push(s.y);else for(g=0;p>g;++g){var b=+M(s=n[g],g),_=+x(s,g);v>b&&(v=b),d>_&&(d=_),b>m&&(m=b),_>y&&(y=_),f.push(b),h.push(_)}var w=m-v,S=y-d;w>S?y=d+w:m=v+S;var k=su();if(k.add=function(n){i(k,n,+M(n,++g),+x(n,g),v,d,m,y)},k.visit=function(n){fu(n,k,v,d,m,y)},k.find=function(n){return hu(k,n[0],n[1],v,d,m,y)},g=-1,null==t){for(;++g<p;)i(k,n[g],f[g],h[g],v,d,m,y);--g}else n.forEach(k.add);return f=h=n=s=null,k}var o,a=Ar,c=Nr;return(o=arguments.length)?(a=cu,c=lu,3===o&&(u=e,r=t,e=t=0),i(n)):(i.x=function(n){return arguments.length?(a=n,i):a},i.y=function(n){return arguments.length?(c=n,i):c},i.extent=function(n){return arguments.length?(null==n?t=e=r=u=null:(t=+n[0][0],e=+n[0][1],r=+n[1][0],u=+n[1][1]),i):null==t?null:[[t,e],[r,u]]},i.size=function(n){return arguments.length?(null==n?t=e=r=u=null:(t=e=0,r=+n[0],u=+n[1]),i):null==t?null:[r-t,u-e]},i)},ta.interpolateRgb=gu,ta.interpolateObject=pu,ta.interpolateNumber=vu,ta.interpolateString=du;var il=/[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g,ol=new RegExp(il.source,"g");ta.interpolate=mu,ta.interpolators=[function(n,t){var e=typeof t;return("string"===e?Ga.has(t.toLowerCase())||/^(#|rgb\(|hsl\()/i.test(t)?gu:du:t instanceof ot?gu:Array.isArray(t)?yu:"object"===e&&isNaN(t)?pu:vu)(n,t)}],ta.interpolateArray=yu;var al=function(){return y},cl=ta.map({linear:al,poly:ku,quad:function(){return _u},cubic:function(){return wu},sin:function(){return Eu},exp:function(){return Au},circle:function(){return Nu},elastic:Cu,back:zu,bounce:function(){return qu}}),ll=ta.map({"in":y,out:xu,"in-out":bu,"out-in":function(n){return bu(xu(n))}});ta.ease=function(n){var t=n.indexOf("-"),e=t>=0?n.slice(0,t):n,r=t>=0?n.slice(t+1):"in";return e=cl.get(e)||al,r=ll.get(r)||y,Mu(r(e.apply(null,ea.call(arguments,1))))},ta.interpolateHcl=Lu,ta.interpolateHsl=Tu,ta.interpolateLab=Ru,ta.interpolateRound=Du,ta.transform=function(n){var t=ua.createElementNS(ta.ns.prefix.svg,"g");return(ta.transform=function(n){if(null!=n){t.setAttribute("transform",n);var e=t.transform.baseVal.consolidate()}return new Pu(e?e.matrix:sl)})(n)},Pu.prototype.toString=function(){return"translate("+this.translate+")rotate("+this.rotate+")skewX("+this.skew+")scale("+this.scale+")"};var sl={a:1,b:0,c:0,d:1,e:0,f:0};ta.interpolateTransform=Hu,ta.layout={},ta.layout.bundle=function(){return function(n){for(var t=[],e=-1,r=n.length;++e<r;)t.push(Yu(n[e]));return t}},ta.layout.chord=function(){function n(){var n,l,f,h,g,p={},v=[],d=ta.range(i),m=[];for(e=[],r=[],n=0,h=-1;++h<i;){for(l=0,g=-1;++g<i;)l+=u[h][g];v.push(l),m.push(ta.range(i)),n+=l}for(o&&d.sort(function(n,t){return o(v[n],v[t])}),a&&m.forEach(function(n,t){n.sort(function(n,e){return a(u[t][n],u[t][e])})}),n=(La-s*i)/n,l=0,h=-1;++h<i;){for(f=l,g=-1;++g<i;){var y=d[h],M=m[y][g],x=u[y][M],b=l,_=l+=x*n;p[y+"-"+M]={index:y,subindex:M,startAngle:b,endAngle:_,value:x}}r[y]={index:y,startAngle:f,endAngle:l,value:(l-f)/n},l+=s}for(h=-1;++h<i;)for(g=h-1;++g<i;){var w=p[h+"-"+g],S=p[g+"-"+h];(w.value||S.value)&&e.push(w.value<S.value?{source:S,target:w}:{source:w,target:S})}c&&t()}function t(){e.sort(function(n,t){return c((n.source.value+n.target.value)/2,(t.source.value+t.target.value)/2)})}var e,r,u,i,o,a,c,l={},s=0;return l.matrix=function(n){return arguments.length?(i=(u=n)&&u.length,e=r=null,l):u},l.padding=function(n){return arguments.length?(s=n,e=r=null,l):s},l.sortGroups=function(n){return arguments.length?(o=n,e=r=null,l):o},l.sortSubgroups=function(n){return arguments.length?(a=n,e=null,l):a},l.sortChords=function(n){return arguments.length?(c=n,e&&t(),l):c},l.chords=function(){return e||n(),e},l.groups=function(){return r||n(),r},l},ta.layout.force=function(){function n(n){return function(t,e,r,u){if(t.point!==n){var i=t.cx-n.x,o=t.cy-n.y,a=u-e,c=i*i+o*o;if(c>a*a/d){if(p>c){var l=t.charge/c;n.px-=i*l,n.py-=o*l}return!0}if(t.point&&c&&p>c){var l=t.pointCharge/c;n.px-=i*l,n.py-=o*l}}return!t.charge}}function t(n){n.px=ta.event.x,n.py=ta.event.y,a.resume()}var e,r,u,i,o,a={},c=ta.dispatch("start","tick","end"),l=[1,1],s=.9,f=fl,h=hl,g=-30,p=gl,v=.1,d=.64,m=[],M=[];return a.tick=function(){if((r*=.99)<.005)return c.end({type:"end",alpha:r=0}),!0;var t,e,a,f,h,p,d,y,x,b=m.length,_=M.length;for(e=0;_>e;++e)a=M[e],f=a.source,h=a.target,y=h.x-f.x,x=h.y-f.y,(p=y*y+x*x)&&(p=r*i[e]*((p=Math.sqrt(p))-u[e])/p,y*=p,x*=p,h.x-=y*(d=f.weight/(h.weight+f.weight)),h.y-=x*d,f.x+=y*(d=1-d),f.y+=x*d);if((d=r*v)&&(y=l[0]/2,x=l[1]/2,e=-1,d))for(;++e<b;)a=m[e],a.x+=(y-a.x)*d,a.y+=(x-a.y)*d;if(g)for(Ju(t=ta.geom.quadtree(m),r,o),e=-1;++e<b;)(a=m[e]).fixed||t.visit(n(a));for(e=-1;++e<b;)a=m[e],a.fixed?(a.x=a.px,a.y=a.py):(a.x-=(a.px-(a.px=a.x))*s,a.y-=(a.py-(a.py=a.y))*s);c.tick({type:"tick",alpha:r})},a.nodes=function(n){return arguments.length?(m=n,a):m},a.links=function(n){return arguments.length?(M=n,a):M},a.size=function(n){return arguments.length?(l=n,a):l},a.linkDistance=function(n){return arguments.length?(f="function"==typeof n?n:+n,a):f},a.distance=a.linkDistance,a.linkStrength=function(n){return arguments.length?(h="function"==typeof n?n:+n,a):h},a.friction=function(n){return arguments.length?(s=+n,a):s},a.charge=function(n){return arguments.length?(g="function"==typeof n?n:+n,a):g},a.chargeDistance=function(n){return arguments.length?(p=n*n,a):Math.sqrt(p)},a.gravity=function(n){return arguments.length?(v=+n,a):v},a.theta=function(n){return arguments.length?(d=n*n,a):Math.sqrt(d)},a.alpha=function(n){return arguments.length?(n=+n,r?r=n>0?n:0:n>0&&(c.start({type:"start",alpha:r=n}),ta.timer(a.tick)),a):r},a.start=function(){function n(n,r){if(!e){for(e=new Array(c),a=0;c>a;++a)e[a]=[];for(a=0;s>a;++a){var u=M[a];e[u.source.index].push(u.target),e[u.target.index].push(u.source)}}for(var i,o=e[t],a=-1,l=o.length;++a<l;)if(!isNaN(i=o[a][n]))return i;return Math.random()*r}var t,e,r,c=m.length,s=M.length,p=l[0],v=l[1];for(t=0;c>t;++t)(r=m[t]).index=t,r.weight=0;for(t=0;s>t;++t)r=M[t],"number"==typeof r.source&&(r.source=m[r.source]),"number"==typeof r.target&&(r.target=m[r.target]),++r.source.weight,++r.target.weight;for(t=0;c>t;++t)r=m[t],isNaN(r.x)&&(r.x=n("x",p)),isNaN(r.y)&&(r.y=n("y",v)),isNaN(r.px)&&(r.px=r.x),isNaN(r.py)&&(r.py=r.y);if(u=[],"function"==typeof f)for(t=0;s>t;++t)u[t]=+f.call(this,M[t],t);else for(t=0;s>t;++t)u[t]=f;if(i=[],"function"==typeof h)for(t=0;s>t;++t)i[t]=+h.call(this,M[t],t);else for(t=0;s>t;++t)i[t]=h;if(o=[],"function"==typeof g)for(t=0;c>t;++t)o[t]=+g.call(this,m[t],t);else for(t=0;c>t;++t)o[t]=g;return a.resume()},a.resume=function(){return a.alpha(.1)},a.stop=function(){return a.alpha(0)},a.drag=function(){return e||(e=ta.behavior.drag().origin(y).on("dragstart.force",Xu).on("drag.force",t).on("dragend.force",$u)),arguments.length?void this.on("mouseover.force",Bu).on("mouseout.force",Wu).call(e):e},ta.rebind(a,c,"on")};var fl=20,hl=1,gl=1/0;ta.layout.hierarchy=function(){function n(u){var i,o=[u],a=[];for(u.depth=0;null!=(i=o.pop());)if(a.push(i),(l=e.call(n,i,i.depth))&&(c=l.length)){for(var c,l,s;--c>=0;)o.push(s=l[c]),s.parent=i,s.depth=i.depth+1;r&&(i.value=0),i.children=l}else r&&(i.value=+r.call(n,i,i.depth)||0),delete i.children;return Qu(u,function(n){var e,u;t&&(e=n.children)&&e.sort(t),r&&(u=n.parent)&&(u.value+=n.value)}),a}var t=ei,e=ni,r=ti;return n.sort=function(e){return arguments.length?(t=e,n):t},n.children=function(t){return arguments.length?(e=t,n):e},n.value=function(t){return arguments.length?(r=t,n):r},n.revalue=function(t){return r&&(Ku(t,function(n){n.children&&(n.value=0)}),Qu(t,function(t){var e;t.children||(t.value=+r.call(n,t,t.depth)||0),(e=t.parent)&&(e.value+=t.value)})),t},n},ta.layout.partition=function(){function n(t,e,r,u){var i=t.children;if(t.x=e,t.y=t.depth*u,t.dx=r,t.dy=u,i&&(o=i.length)){var o,a,c,l=-1;for(r=t.value?r/t.value:0;++l<o;)n(a=i[l],e,c=a.value*r,u),e+=c}}function t(n){var e=n.children,r=0;if(e&&(u=e.length))for(var u,i=-1;++i<u;)r=Math.max(r,t(e[i]));return 1+r}function e(e,i){var o=r.call(this,e,i);return n(o[0],0,u[0],u[1]/t(o[0])),o}var r=ta.layout.hierarchy(),u=[1,1];return e.size=function(n){return arguments.length?(u=n,e):u},Gu(e,r)},ta.layout.pie=function(){function n(o){var a,c=o.length,l=o.map(function(e,r){return+t.call(n,e,r)}),s=+("function"==typeof r?r.apply(this,arguments):r),f=("function"==typeof u?u.apply(this,arguments):u)-s,h=Math.min(Math.abs(f)/c,+("function"==typeof i?i.apply(this,arguments):i)),g=h*(0>f?-1:1),p=(f-c*g)/ta.sum(l),v=ta.range(c),d=[];return null!=e&&v.sort(e===pl?function(n,t){return l[t]-l[n]}:function(n,t){return e(o[n],o[t])}),v.forEach(function(n){d[n]={data:o[n],value:a=l[n],startAngle:s,endAngle:s+=a*p+g,padAngle:h}}),d}var t=Number,e=pl,r=0,u=La,i=0;return n.value=function(e){return arguments.length?(t=e,n):t},n.sort=function(t){return arguments.length?(e=t,n):e},n.startAngle=function(t){return arguments.length?(r=t,n):r},n.endAngle=function(t){return arguments.length?(u=t,n):u},n.padAngle=function(t){return arguments.length?(i=t,n):i},n};var pl={};ta.layout.stack=function(){function n(a,c){if(!(h=a.length))return a;var l=a.map(function(e,r){return t.call(n,e,r)}),s=l.map(function(t){return t.map(function(t,e){return[i.call(n,t,e),o.call(n,t,e)]})}),f=e.call(n,s,c);l=ta.permute(l,f),s=ta.permute(s,f);var h,g,p,v,d=r.call(n,s,c),m=l[0].length;for(p=0;m>p;++p)for(u.call(n,l[0][p],v=d[p],s[0][p][1]),g=1;h>g;++g)u.call(n,l[g][p],v+=s[g-1][p][1],s[g][p][1]);return a}var t=y,e=ai,r=ci,u=oi,i=ui,o=ii;return n.values=function(e){return arguments.length?(t=e,n):t},n.order=function(t){return arguments.length?(e="function"==typeof t?t:vl.get(t)||ai,n):e},n.offset=function(t){return arguments.length?(r="function"==typeof t?t:dl.get(t)||ci,n):r},n.x=function(t){return arguments.length?(i=t,n):i},n.y=function(t){return arguments.length?(o=t,n):o},n.out=function(t){return arguments.length?(u=t,n):u},n};var vl=ta.map({"inside-out":function(n){var t,e,r=n.length,u=n.map(li),i=n.map(si),o=ta.range(r).sort(function(n,t){return u[n]-u[t]}),a=0,c=0,l=[],s=[];for(t=0;r>t;++t)e=o[t],c>a?(a+=i[e],l.push(e)):(c+=i[e],s.push(e));return s.reverse().concat(l)},reverse:function(n){return ta.range(n.length).reverse()},"default":ai}),dl=ta.map({silhouette:function(n){var t,e,r,u=n.length,i=n[0].length,o=[],a=0,c=[];for(e=0;i>e;++e){for(t=0,r=0;u>t;t++)r+=n[t][e][1];r>a&&(a=r),o.push(r)}for(e=0;i>e;++e)c[e]=(a-o[e])/2;return c},wiggle:function(n){var t,e,r,u,i,o,a,c,l,s=n.length,f=n[0],h=f.length,g=[];for(g[0]=c=l=0,e=1;h>e;++e){for(t=0,u=0;s>t;++t)u+=n[t][e][1];for(t=0,i=0,a=f[e][0]-f[e-1][0];s>t;++t){for(r=0,o=(n[t][e][1]-n[t][e-1][1])/(2*a);t>r;++r)o+=(n[r][e][1]-n[r][e-1][1])/a;i+=o*n[t][e][1]}g[e]=c-=u?i/u*a:0,l>c&&(l=c)}for(e=0;h>e;++e)g[e]-=l;return g},expand:function(n){var t,e,r,u=n.length,i=n[0].length,o=1/u,a=[];for(e=0;i>e;++e){for(t=0,r=0;u>t;t++)r+=n[t][e][1];if(r)for(t=0;u>t;t++)n[t][e][1]/=r;else for(t=0;u>t;t++)n[t][e][1]=o}for(e=0;i>e;++e)a[e]=0;return a},zero:ci});ta.layout.histogram=function(){function n(n,i){for(var o,a,c=[],l=n.map(e,this),s=r.call(this,l,i),f=u.call(this,s,l,i),i=-1,h=l.length,g=f.length-1,p=t?1:1/h;++i<g;)o=c[i]=[],o.dx=f[i+1]-(o.x=f[i]),o.y=0;if(g>0)for(i=-1;++i<h;)a=l[i],a>=s[0]&&a<=s[1]&&(o=c[ta.bisect(f,a,1,g)-1],o.y+=p,o.push(n[i]));return c}var t=!0,e=Number,r=pi,u=hi;return n.value=function(t){return arguments.length?(e=t,n):e},n.range=function(t){return arguments.length?(r=Et(t),n):r},n.bins=function(t){return arguments.length?(u="number"==typeof t?function(n){return gi(n,t)}:Et(t),n):u},n.frequency=function(e){return arguments.length?(t=!!e,n):t},n},ta.layout.pack=function(){function n(n,i){var o=e.call(this,n,i),a=o[0],c=u[0],l=u[1],s=null==t?Math.sqrt:"function"==typeof t?t:function(){return t};if(a.x=a.y=0,Qu(a,function(n){n.r=+s(n.value)}),Qu(a,Mi),r){var f=r*(t?1:Math.max(2*a.r/c,2*a.r/l))/2;Qu(a,function(n){n.r+=f}),Qu(a,Mi),Qu(a,function(n){n.r-=f})}return _i(a,c/2,l/2,t?1:1/Math.max(2*a.r/c,2*a.r/l)),o}var t,e=ta.layout.hierarchy().sort(vi),r=0,u=[1,1];return n.size=function(t){return arguments.length?(u=t,n):u},n.radius=function(e){return arguments.length?(t=null==e||"function"==typeof e?e:+e,n):t},n.padding=function(t){return arguments.length?(r=+t,n):r},Gu(n,e)},ta.layout.tree=function(){function n(n,u){var s=o.call(this,n,u),f=s[0],h=t(f);if(Qu(h,e),h.parent.m=-h.z,Ku(h,r),l)Ku(f,i);else{var g=f,p=f,v=f;Ku(f,function(n){n.x<g.x&&(g=n),n.x>p.x&&(p=n),n.depth>v.depth&&(v=n)});var d=a(g,p)/2-g.x,m=c[0]/(p.x+a(p,g)/2+d),y=c[1]/(v.depth||1);Ku(f,function(n){n.x=(n.x+d)*m,n.y=n.depth*y})}return s}function t(n){for(var t,e={A:null,children:[n]},r=[e];null!=(t=r.pop());)for(var u,i=t.children,o=0,a=i.length;a>o;++o)r.push((i[o]=u={_:i[o],parent:t,children:(u=i[o].children)&&u.slice()||[],A:null,a:null,z:0,m:0,c:0,s:0,t:null,i:o}).a=u);return e.children[0]}function e(n){var t=n.children,e=n.parent.children,r=n.i?e[n.i-1]:null;if(t.length){Ni(n);var i=(t[0].z+t[t.length-1].z)/2;r?(n.z=r.z+a(n._,r._),n.m=n.z-i):n.z=i}else r&&(n.z=r.z+a(n._,r._));n.parent.A=u(n,r,n.parent.A||e[0])}function r(n){n._.x=n.z+n.parent.m,n.m+=n.parent.m}function u(n,t,e){if(t){for(var r,u=n,i=n,o=t,c=u.parent.children[0],l=u.m,s=i.m,f=o.m,h=c.m;o=Ei(o),u=ki(u),o&&u;)c=ki(c),i=Ei(i),i.a=n,r=o.z+f-u.z-l+a(o._,u._),r>0&&(Ai(Ci(o,n,e),n,r),l+=r,s+=r),f+=o.m,l+=u.m,h+=c.m,s+=i.m;o&&!Ei(i)&&(i.t=o,i.m+=f-s),u&&!ki(c)&&(c.t=u,c.m+=l-h,e=n)}return e}function i(n){n.x*=c[0],n.y=n.depth*c[1]}var o=ta.layout.hierarchy().sort(null).value(null),a=Si,c=[1,1],l=null;return n.separation=function(t){return arguments.length?(a=t,n):a},n.size=function(t){return arguments.length?(l=null==(c=t)?i:null,n):l?null:c},n.nodeSize=function(t){return arguments.length?(l=null==(c=t)?null:i,n):l?c:null},Gu(n,o)},ta.layout.cluster=function(){function n(n,i){var o,a=t.call(this,n,i),c=a[0],l=0;Qu(c,function(n){var t=n.children;t&&t.length?(n.x=qi(t),n.y=zi(t)):(n.x=o?l+=e(n,o):0,n.y=0,o=n)});var s=Li(c),f=Ti(c),h=s.x-e(s,f)/2,g=f.x+e(f,s)/2;return Qu(c,u?function(n){n.x=(n.x-c.x)*r[0],n.y=(c.y-n.y)*r[1]}:function(n){n.x=(n.x-h)/(g-h)*r[0],n.y=(1-(c.y?n.y/c.y:1))*r[1]}),a}var t=ta.layout.hierarchy().sort(null).value(null),e=Si,r=[1,1],u=!1;return n.separation=function(t){return arguments.length?(e=t,n):e},n.size=function(t){return arguments.length?(u=null==(r=t),n):u?null:r},n.nodeSize=function(t){return arguments.length?(u=null!=(r=t),n):u?r:null},Gu(n,t)},ta.layout.treemap=function(){function n(n,t){for(var e,r,u=-1,i=n.length;++u<i;)r=(e=n[u]).value*(0>t?0:t),e.area=isNaN(r)||0>=r?0:r}function t(e){var i=e.children;if(i&&i.length){var o,a,c,l=f(e),s=[],h=i.slice(),p=1/0,v="slice"===g?l.dx:"dice"===g?l.dy:"slice-dice"===g?1&e.depth?l.dy:l.dx:Math.min(l.dx,l.dy);for(n(h,l.dx*l.dy/e.value),s.area=0;(c=h.length)>0;)s.push(o=h[c-1]),s.area+=o.area,"squarify"!==g||(a=r(s,v))<=p?(h.pop(),p=a):(s.area-=s.pop().area,u(s,v,l,!1),v=Math.min(l.dx,l.dy),s.length=s.area=0,p=1/0);s.length&&(u(s,v,l,!0),s.length=s.area=0),i.forEach(t)}}function e(t){var r=t.children;if(r&&r.length){var i,o=f(t),a=r.slice(),c=[];for(n(a,o.dx*o.dy/t.value),c.area=0;i=a.pop();)c.push(i),c.area+=i.area,null!=i.z&&(u(c,i.z?o.dx:o.dy,o,!a.length),c.length=c.area=0);r.forEach(e)}}function r(n,t){for(var e,r=n.area,u=0,i=1/0,o=-1,a=n.length;++o<a;)(e=n[o].area)&&(i>e&&(i=e),e>u&&(u=e));return r*=r,t*=t,r?Math.max(t*u*p/r,r/(t*i*p)):1/0}function u(n,t,e,r){var u,i=-1,o=n.length,a=e.x,l=e.y,s=t?c(n.area/t):0;if(t==e.dx){for((r||s>e.dy)&&(s=e.dy);++i<o;)u=n[i],u.x=a,u.y=l,u.dy=s,a+=u.dx=Math.min(e.x+e.dx-a,s?c(u.area/s):0);u.z=!0,u.dx+=e.x+e.dx-a,e.y+=s,e.dy-=s}else{for((r||s>e.dx)&&(s=e.dx);++i<o;)u=n[i],u.x=a,u.y=l,u.dx=s,l+=u.dy=Math.min(e.y+e.dy-l,s?c(u.area/s):0);u.z=!1,u.dy+=e.y+e.dy-l,e.x+=s,e.dx-=s}}function i(r){var u=o||a(r),i=u[0];return i.x=0,i.y=0,i.dx=l[0],i.dy=l[1],o&&a.revalue(i),n([i],i.dx*i.dy/i.value),(o?e:t)(i),h&&(o=u),u}var o,a=ta.layout.hierarchy(),c=Math.round,l=[1,1],s=null,f=Ri,h=!1,g="squarify",p=.5*(1+Math.sqrt(5));
+return i.size=function(n){return arguments.length?(l=n,i):l},i.padding=function(n){function t(t){var e=n.call(i,t,t.depth);return null==e?Ri(t):Di(t,"number"==typeof e?[e,e,e,e]:e)}function e(t){return Di(t,n)}if(!arguments.length)return s;var r;return f=null==(s=n)?Ri:"function"==(r=typeof n)?t:"number"===r?(n=[n,n,n,n],e):e,i},i.round=function(n){return arguments.length?(c=n?Math.round:Number,i):c!=Number},i.sticky=function(n){return arguments.length?(h=n,o=null,i):h},i.ratio=function(n){return arguments.length?(p=n,i):p},i.mode=function(n){return arguments.length?(g=n+"",i):g},Gu(i,a)},ta.random={normal:function(n,t){var e=arguments.length;return 2>e&&(t=1),1>e&&(n=0),function(){var e,r,u;do e=2*Math.random()-1,r=2*Math.random()-1,u=e*e+r*r;while(!u||u>1);return n+t*e*Math.sqrt(-2*Math.log(u)/u)}},logNormal:function(){var n=ta.random.normal.apply(ta,arguments);return function(){return Math.exp(n())}},bates:function(n){var t=ta.random.irwinHall(n);return function(){return t()/n}},irwinHall:function(n){return function(){for(var t=0,e=0;n>e;e++)t+=Math.random();return t}}},ta.scale={};var ml={floor:y,ceil:y};ta.scale.linear=function(){return Ii([0,1],[0,1],mu,!1)};var yl={s:1,g:1,p:1,r:1,e:1};ta.scale.log=function(){return Ji(ta.scale.linear().domain([0,1]),10,!0,[1,10])};var Ml=ta.format(".0e"),xl={floor:function(n){return-Math.ceil(-n)},ceil:function(n){return-Math.floor(-n)}};ta.scale.pow=function(){return Gi(ta.scale.linear(),1,[0,1])},ta.scale.sqrt=function(){return ta.scale.pow().exponent(.5)},ta.scale.ordinal=function(){return Qi([],{t:"range",a:[[]]})},ta.scale.category10=function(){return ta.scale.ordinal().range(bl)},ta.scale.category20=function(){return ta.scale.ordinal().range(_l)},ta.scale.category20b=function(){return ta.scale.ordinal().range(wl)},ta.scale.category20c=function(){return ta.scale.ordinal().range(Sl)};var bl=[2062260,16744206,2924588,14034728,9725885,9197131,14907330,8355711,12369186,1556175].map(Mt),_l=[2062260,11454440,16744206,16759672,2924588,10018698,14034728,16750742,9725885,12955861,9197131,12885140,14907330,16234194,8355711,13092807,12369186,14408589,1556175,10410725].map(Mt),wl=[3750777,5395619,7040719,10264286,6519097,9216594,11915115,13556636,9202993,12426809,15186514,15190932,8666169,11356490,14049643,15177372,8077683,10834324,13528509,14589654].map(Mt),Sl=[3244733,7057110,10406625,13032431,15095053,16616764,16625259,16634018,3253076,7652470,10607003,13101504,7695281,10394312,12369372,14342891,6513507,9868950,12434877,14277081].map(Mt);ta.scale.quantile=function(){return no([],[])},ta.scale.quantize=function(){return to(0,1,[0,1])},ta.scale.threshold=function(){return eo([.5],[0,1])},ta.scale.identity=function(){return ro([0,1])},ta.svg={},ta.svg.arc=function(){function n(){var n=Math.max(0,+e.apply(this,arguments)),l=Math.max(0,+r.apply(this,arguments)),s=o.apply(this,arguments)-Ra,f=a.apply(this,arguments)-Ra,h=Math.abs(f-s),g=s>f?0:1;if(n>l&&(p=l,l=n,n=p),h>=Ta)return t(l,g)+(n?t(n,1-g):"")+"Z";var p,v,d,m,y,M,x,b,_,w,S,k,E=0,A=0,N=[];if((m=(+c.apply(this,arguments)||0)/2)&&(d=i===kl?Math.sqrt(n*n+l*l):+i.apply(this,arguments),g||(A*=-1),l&&(A=tt(d/l*Math.sin(m))),n&&(E=tt(d/n*Math.sin(m)))),l){y=l*Math.cos(s+A),M=l*Math.sin(s+A),x=l*Math.cos(f-A),b=l*Math.sin(f-A);var C=Math.abs(f-s-2*A)<=qa?0:1;if(A&&so(y,M,x,b)===g^C){var z=(s+f)/2;y=l*Math.cos(z),M=l*Math.sin(z),x=b=null}}else y=M=0;if(n){_=n*Math.cos(f-E),w=n*Math.sin(f-E),S=n*Math.cos(s+E),k=n*Math.sin(s+E);var q=Math.abs(s-f+2*E)<=qa?0:1;if(E&&so(_,w,S,k)===1-g^q){var L=(s+f)/2;_=n*Math.cos(L),w=n*Math.sin(L),S=k=null}}else _=w=0;if((p=Math.min(Math.abs(l-n)/2,+u.apply(this,arguments)))>.001){v=l>n^g?0:1;var T=null==S?[_,w]:null==x?[y,M]:Lr([y,M],[S,k],[x,b],[_,w]),R=y-T[0],D=M-T[1],P=x-T[0],U=b-T[1],j=1/Math.sin(Math.acos((R*P+D*U)/(Math.sqrt(R*R+D*D)*Math.sqrt(P*P+U*U)))/2),F=Math.sqrt(T[0]*T[0]+T[1]*T[1]);if(null!=x){var H=Math.min(p,(l-F)/(j+1)),O=fo(null==S?[_,w]:[S,k],[y,M],l,H,g),I=fo([x,b],[_,w],l,H,g);p===H?N.push("M",O[0],"A",H,",",H," 0 0,",v," ",O[1],"A",l,",",l," 0 ",1-g^so(O[1][0],O[1][1],I[1][0],I[1][1]),",",g," ",I[1],"A",H,",",H," 0 0,",v," ",I[0]):N.push("M",O[0],"A",H,",",H," 0 1,",v," ",I[0])}else N.push("M",y,",",M);if(null!=S){var Y=Math.min(p,(n-F)/(j-1)),Z=fo([y,M],[S,k],n,-Y,g),V=fo([_,w],null==x?[y,M]:[x,b],n,-Y,g);p===Y?N.push("L",V[0],"A",Y,",",Y," 0 0,",v," ",V[1],"A",n,",",n," 0 ",g^so(V[1][0],V[1][1],Z[1][0],Z[1][1]),",",1-g," ",Z[1],"A",Y,",",Y," 0 0,",v," ",Z[0]):N.push("L",V[0],"A",Y,",",Y," 0 0,",v," ",Z[0])}else N.push("L",_,",",w)}else N.push("M",y,",",M),null!=x&&N.push("A",l,",",l," 0 ",C,",",g," ",x,",",b),N.push("L",_,",",w),null!=S&&N.push("A",n,",",n," 0 ",q,",",1-g," ",S,",",k);return N.push("Z"),N.join("")}function t(n,t){return"M0,"+n+"A"+n+","+n+" 0 1,"+t+" 0,"+-n+"A"+n+","+n+" 0 1,"+t+" 0,"+n}var e=io,r=oo,u=uo,i=kl,o=ao,a=co,c=lo;return n.innerRadius=function(t){return arguments.length?(e=Et(t),n):e},n.outerRadius=function(t){return arguments.length?(r=Et(t),n):r},n.cornerRadius=function(t){return arguments.length?(u=Et(t),n):u},n.padRadius=function(t){return arguments.length?(i=t==kl?kl:Et(t),n):i},n.startAngle=function(t){return arguments.length?(o=Et(t),n):o},n.endAngle=function(t){return arguments.length?(a=Et(t),n):a},n.padAngle=function(t){return arguments.length?(c=Et(t),n):c},n.centroid=function(){var n=(+e.apply(this,arguments)+ +r.apply(this,arguments))/2,t=(+o.apply(this,arguments)+ +a.apply(this,arguments))/2-Ra;return[Math.cos(t)*n,Math.sin(t)*n]},n};var kl="auto";ta.svg.line=function(){return ho(y)};var El=ta.map({linear:go,"linear-closed":po,step:vo,"step-before":mo,"step-after":yo,basis:So,"basis-open":ko,"basis-closed":Eo,bundle:Ao,cardinal:bo,"cardinal-open":Mo,"cardinal-closed":xo,monotone:To});El.forEach(function(n,t){t.key=n,t.closed=/-closed$/.test(n)});var Al=[0,2/3,1/3,0],Nl=[0,1/3,2/3,0],Cl=[0,1/6,2/3,1/6];ta.svg.line.radial=function(){var n=ho(Ro);return n.radius=n.x,delete n.x,n.angle=n.y,delete n.y,n},mo.reverse=yo,yo.reverse=mo,ta.svg.area=function(){return Do(y)},ta.svg.area.radial=function(){var n=Do(Ro);return n.radius=n.x,delete n.x,n.innerRadius=n.x0,delete n.x0,n.outerRadius=n.x1,delete n.x1,n.angle=n.y,delete n.y,n.startAngle=n.y0,delete n.y0,n.endAngle=n.y1,delete n.y1,n},ta.svg.chord=function(){function n(n,a){var c=t(this,i,n,a),l=t(this,o,n,a);return"M"+c.p0+r(c.r,c.p1,c.a1-c.a0)+(e(c,l)?u(c.r,c.p1,c.r,c.p0):u(c.r,c.p1,l.r,l.p0)+r(l.r,l.p1,l.a1-l.a0)+u(l.r,l.p1,c.r,c.p0))+"Z"}function t(n,t,e,r){var u=t.call(n,e,r),i=a.call(n,u,r),o=c.call(n,u,r)-Ra,s=l.call(n,u,r)-Ra;return{r:i,a0:o,a1:s,p0:[i*Math.cos(o),i*Math.sin(o)],p1:[i*Math.cos(s),i*Math.sin(s)]}}function e(n,t){return n.a0==t.a0&&n.a1==t.a1}function r(n,t,e){return"A"+n+","+n+" 0 "+ +(e>qa)+",1 "+t}function u(n,t,e,r){return"Q 0,0 "+r}var i=mr,o=yr,a=Po,c=ao,l=co;return n.radius=function(t){return arguments.length?(a=Et(t),n):a},n.source=function(t){return arguments.length?(i=Et(t),n):i},n.target=function(t){return arguments.length?(o=Et(t),n):o},n.startAngle=function(t){return arguments.length?(c=Et(t),n):c},n.endAngle=function(t){return arguments.length?(l=Et(t),n):l},n},ta.svg.diagonal=function(){function n(n,u){var i=t.call(this,n,u),o=e.call(this,n,u),a=(i.y+o.y)/2,c=[i,{x:i.x,y:a},{x:o.x,y:a},o];return c=c.map(r),"M"+c[0]+"C"+c[1]+" "+c[2]+" "+c[3]}var t=mr,e=yr,r=Uo;return n.source=function(e){return arguments.length?(t=Et(e),n):t},n.target=function(t){return arguments.length?(e=Et(t),n):e},n.projection=function(t){return arguments.length?(r=t,n):r},n},ta.svg.diagonal.radial=function(){var n=ta.svg.diagonal(),t=Uo,e=n.projection;return n.projection=function(n){return arguments.length?e(jo(t=n)):t},n},ta.svg.symbol=function(){function n(n,r){return(zl.get(t.call(this,n,r))||Oo)(e.call(this,n,r))}var t=Ho,e=Fo;return n.type=function(e){return arguments.length?(t=Et(e),n):t},n.size=function(t){return arguments.length?(e=Et(t),n):e},n};var zl=ta.map({circle:Oo,cross:function(n){var t=Math.sqrt(n/5)/2;return"M"+-3*t+","+-t+"H"+-t+"V"+-3*t+"H"+t+"V"+-t+"H"+3*t+"V"+t+"H"+t+"V"+3*t+"H"+-t+"V"+t+"H"+-3*t+"Z"},diamond:function(n){var t=Math.sqrt(n/(2*Ll)),e=t*Ll;return"M0,"+-t+"L"+e+",0 0,"+t+" "+-e+",0Z"},square:function(n){var t=Math.sqrt(n)/2;return"M"+-t+","+-t+"L"+t+","+-t+" "+t+","+t+" "+-t+","+t+"Z"},"triangle-down":function(n){var t=Math.sqrt(n/ql),e=t*ql/2;return"M0,"+e+"L"+t+","+-e+" "+-t+","+-e+"Z"},"triangle-up":function(n){var t=Math.sqrt(n/ql),e=t*ql/2;return"M0,"+-e+"L"+t+","+e+" "+-t+","+e+"Z"}});ta.svg.symbolTypes=zl.keys();var ql=Math.sqrt(3),Ll=Math.tan(30*Da);_a.transition=function(n){for(var t,e,r=Tl||++Ul,u=Xo(n),i=[],o=Rl||{time:Date.now(),ease:Su,delay:0,duration:250},a=-1,c=this.length;++a<c;){i.push(t=[]);for(var l=this[a],s=-1,f=l.length;++s<f;)(e=l[s])&&$o(e,s,u,r,o),t.push(e)}return Yo(i,u,r)},_a.interrupt=function(n){return this.each(null==n?Dl:Io(Xo(n)))};var Tl,Rl,Dl=Io(Xo()),Pl=[],Ul=0;Pl.call=_a.call,Pl.empty=_a.empty,Pl.node=_a.node,Pl.size=_a.size,ta.transition=function(n,t){return n&&n.transition?Tl?n.transition(t):n:ta.selection().transition(n)},ta.transition.prototype=Pl,Pl.select=function(n){var t,e,r,u=this.id,i=this.namespace,o=[];n=N(n);for(var a=-1,c=this.length;++a<c;){o.push(t=[]);for(var l=this[a],s=-1,f=l.length;++s<f;)(r=l[s])&&(e=n.call(r,r.__data__,s,a))?("__data__"in r&&(e.__data__=r.__data__),$o(e,s,i,u,r[i][u]),t.push(e)):t.push(null)}return Yo(o,i,u)},Pl.selectAll=function(n){var t,e,r,u,i,o=this.id,a=this.namespace,c=[];n=C(n);for(var l=-1,s=this.length;++l<s;)for(var f=this[l],h=-1,g=f.length;++h<g;)if(r=f[h]){i=r[a][o],e=n.call(r,r.__data__,h,l),c.push(t=[]);for(var p=-1,v=e.length;++p<v;)(u=e[p])&&$o(u,p,a,o,i),t.push(u)}return Yo(c,a,o)},Pl.filter=function(n){var t,e,r,u=[];"function"!=typeof n&&(n=O(n));for(var i=0,o=this.length;o>i;i++){u.push(t=[]);for(var e=this[i],a=0,c=e.length;c>a;a++)(r=e[a])&&n.call(r,r.__data__,a,i)&&t.push(r)}return Yo(u,this.namespace,this.id)},Pl.tween=function(n,t){var e=this.id,r=this.namespace;return arguments.length<2?this.node()[r][e].tween.get(n):Y(this,null==t?function(t){t[r][e].tween.remove(n)}:function(u){u[r][e].tween.set(n,t)})},Pl.attr=function(n,t){function e(){this.removeAttribute(a)}function r(){this.removeAttributeNS(a.space,a.local)}function u(n){return null==n?e:(n+="",function(){var t,e=this.getAttribute(a);return e!==n&&(t=o(e,n),function(n){this.setAttribute(a,t(n))})})}function i(n){return null==n?r:(n+="",function(){var t,e=this.getAttributeNS(a.space,a.local);return e!==n&&(t=o(e,n),function(n){this.setAttributeNS(a.space,a.local,t(n))})})}if(arguments.length<2){for(t in n)this.attr(t,n[t]);return this}var o="transform"==n?Hu:mu,a=ta.ns.qualify(n);return Zo(this,"attr."+n,t,a.local?i:u)},Pl.attrTween=function(n,t){function e(n,e){var r=t.call(this,n,e,this.getAttribute(u));return r&&function(n){this.setAttribute(u,r(n))}}function r(n,e){var r=t.call(this,n,e,this.getAttributeNS(u.space,u.local));return r&&function(n){this.setAttributeNS(u.space,u.local,r(n))}}var u=ta.ns.qualify(n);return this.tween("attr."+n,u.local?r:e)},Pl.style=function(n,e,r){function u(){this.style.removeProperty(n)}function i(e){return null==e?u:(e+="",function(){var u,i=t(this).getComputedStyle(this,null).getPropertyValue(n);return i!==e&&(u=mu(i,e),function(t){this.style.setProperty(n,u(t),r)})})}var o=arguments.length;if(3>o){if("string"!=typeof n){2>o&&(e="");for(r in n)this.style(r,n[r],e);return this}r=""}return Zo(this,"style."+n,e,i)},Pl.styleTween=function(n,e,r){function u(u,i){var o=e.call(this,u,i,t(this).getComputedStyle(this,null).getPropertyValue(n));return o&&function(t){this.style.setProperty(n,o(t),r)}}return arguments.length<3&&(r=""),this.tween("style."+n,u)},Pl.text=function(n){return Zo(this,"text",n,Vo)},Pl.remove=function(){var n=this.namespace;return this.each("end.transition",function(){var t;this[n].count<2&&(t=this.parentNode)&&t.removeChild(this)})},Pl.ease=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].ease:("function"!=typeof n&&(n=ta.ease.apply(ta,arguments)),Y(this,function(r){r[e][t].ease=n}))},Pl.delay=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].delay:Y(this,"function"==typeof n?function(r,u,i){r[e][t].delay=+n.call(r,r.__data__,u,i)}:(n=+n,function(r){r[e][t].delay=n}))},Pl.duration=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].duration:Y(this,"function"==typeof n?function(r,u,i){r[e][t].duration=Math.max(1,n.call(r,r.__data__,u,i))}:(n=Math.max(1,n),function(r){r[e][t].duration=n}))},Pl.each=function(n,t){var e=this.id,r=this.namespace;if(arguments.length<2){var u=Rl,i=Tl;try{Tl=e,Y(this,function(t,u,i){Rl=t[r][e],n.call(t,t.__data__,u,i)})}finally{Rl=u,Tl=i}}else Y(this,function(u){var i=u[r][e];(i.event||(i.event=ta.dispatch("start","end","interrupt"))).on(n,t)});return this},Pl.transition=function(){for(var n,t,e,r,u=this.id,i=++Ul,o=this.namespace,a=[],c=0,l=this.length;l>c;c++){a.push(n=[]);for(var t=this[c],s=0,f=t.length;f>s;s++)(e=t[s])&&(r=e[o][u],$o(e,s,o,i,{time:r.time,ease:r.ease,delay:r.delay+r.duration,duration:r.duration})),n.push(e)}return Yo(a,o,i)},ta.svg.axis=function(){function n(n){n.each(function(){var n,l=ta.select(this),s=this.__chart__||e,f=this.__chart__=e.copy(),h=null==c?f.ticks?f.ticks.apply(f,a):f.domain():c,g=null==t?f.tickFormat?f.tickFormat.apply(f,a):y:t,p=l.selectAll(".tick").data(h,f),v=p.enter().insert("g",".domain").attr("class","tick").style("opacity",Ca),d=ta.transition(p.exit()).style("opacity",Ca).remove(),m=ta.transition(p.order()).style("opacity",1),M=Math.max(u,0)+o,x=Ui(f),b=l.selectAll(".domain").data([0]),_=(b.enter().append("path").attr("class","domain"),ta.transition(b));v.append("line"),v.append("text");var w,S,k,E,A=v.select("line"),N=m.select("line"),C=p.select("text").text(g),z=v.select("text"),q=m.select("text"),L="top"===r||"left"===r?-1:1;if("bottom"===r||"top"===r?(n=Bo,w="x",k="y",S="x2",E="y2",C.attr("dy",0>L?"0em":".71em").style("text-anchor","middle"),_.attr("d","M"+x[0]+","+L*i+"V0H"+x[1]+"V"+L*i)):(n=Wo,w="y",k="x",S="y2",E="x2",C.attr("dy",".32em").style("text-anchor",0>L?"end":"start"),_.attr("d","M"+L*i+","+x[0]+"H0V"+x[1]+"H"+L*i)),A.attr(E,L*u),z.attr(k,L*M),N.attr(S,0).attr(E,L*u),q.attr(w,0).attr(k,L*M),f.rangeBand){var T=f,R=T.rangeBand()/2;s=f=function(n){return T(n)+R}}else s.rangeBand?s=f:d.call(n,f,s);v.call(n,s,f),m.call(n,f,f)})}var t,e=ta.scale.linear(),r=jl,u=6,i=6,o=3,a=[10],c=null;return n.scale=function(t){return arguments.length?(e=t,n):e},n.orient=function(t){return arguments.length?(r=t in Fl?t+"":jl,n):r},n.ticks=function(){return arguments.length?(a=arguments,n):a},n.tickValues=function(t){return arguments.length?(c=t,n):c},n.tickFormat=function(e){return arguments.length?(t=e,n):t},n.tickSize=function(t){var e=arguments.length;return e?(u=+t,i=+arguments[e-1],n):u},n.innerTickSize=function(t){return arguments.length?(u=+t,n):u},n.outerTickSize=function(t){return arguments.length?(i=+t,n):i},n.tickPadding=function(t){return arguments.length?(o=+t,n):o},n.tickSubdivide=function(){return arguments.length&&n},n};var jl="bottom",Fl={top:1,right:1,bottom:1,left:1};ta.svg.brush=function(){function n(t){t.each(function(){var t=ta.select(this).style("pointer-events","all").style("-webkit-tap-highlight-color","rgba(0,0,0,0)").on("mousedown.brush",i).on("touchstart.brush",i),o=t.selectAll(".background").data([0]);o.enter().append("rect").attr("class","background").style("visibility","hidden").style("cursor","crosshair"),t.selectAll(".extent").data([0]).enter().append("rect").attr("class","extent").style("cursor","move");var a=t.selectAll(".resize").data(v,y);a.exit().remove(),a.enter().append("g").attr("class",function(n){return"resize "+n}).style("cursor",function(n){return Hl[n]}).append("rect").attr("x",function(n){return/[ew]$/.test(n)?-3:null}).attr("y",function(n){return/^[ns]/.test(n)?-3:null}).attr("width",6).attr("height",6).style("visibility","hidden"),a.style("display",n.empty()?"none":null);var c,f=ta.transition(t),h=ta.transition(o);l&&(c=Ui(l),h.attr("x",c[0]).attr("width",c[1]-c[0]),r(f)),s&&(c=Ui(s),h.attr("y",c[0]).attr("height",c[1]-c[0]),u(f)),e(f)})}function e(n){n.selectAll(".resize").attr("transform",function(n){return"translate("+f[+/e$/.test(n)]+","+h[+/^s/.test(n)]+")"})}function r(n){n.select(".extent").attr("x",f[0]),n.selectAll(".extent,.n>rect,.s>rect").attr("width",f[1]-f[0])}function u(n){n.select(".extent").attr("y",h[0]),n.selectAll(".extent,.e>rect,.w>rect").attr("height",h[1]-h[0])}function i(){function i(){32==ta.event.keyCode&&(C||(M=null,q[0]-=f[1],q[1]-=h[1],C=2),S())}function v(){32==ta.event.keyCode&&2==C&&(q[0]+=f[1],q[1]+=h[1],C=0,S())}function d(){var n=ta.mouse(b),t=!1;x&&(n[0]+=x[0],n[1]+=x[1]),C||(ta.event.altKey?(M||(M=[(f[0]+f[1])/2,(h[0]+h[1])/2]),q[0]=f[+(n[0]<M[0])],q[1]=h[+(n[1]<M[1])]):M=null),A&&m(n,l,0)&&(r(k),t=!0),N&&m(n,s,1)&&(u(k),t=!0),t&&(e(k),w({type:"brush",mode:C?"move":"resize"}))}function m(n,t,e){var r,u,i=Ui(t),c=i[0],l=i[1],s=q[e],v=e?h:f,d=v[1]-v[0];return C&&(c-=s,l-=d+s),r=(e?p:g)?Math.max(c,Math.min(l,n[e])):n[e],C?u=(r+=s)+d:(M&&(s=Math.max(c,Math.min(l,2*M[e]-r))),r>s?(u=r,r=s):u=s),v[0]!=r||v[1]!=u?(e?a=null:o=null,v[0]=r,v[1]=u,!0):void 0}function y(){d(),k.style("pointer-events","all").selectAll(".resize").style("display",n.empty()?"none":null),ta.select("body").style("cursor",null),L.on("mousemove.brush",null).on("mouseup.brush",null).on("touchmove.brush",null).on("touchend.brush",null).on("keydown.brush",null).on("keyup.brush",null),z(),w({type:"brushend"})}var M,x,b=this,_=ta.select(ta.event.target),w=c.of(b,arguments),k=ta.select(b),E=_.datum(),A=!/^(n|s)$/.test(E)&&l,N=!/^(e|w)$/.test(E)&&s,C=_.classed("extent"),z=W(b),q=ta.mouse(b),L=ta.select(t(b)).on("keydown.brush",i).on("keyup.brush",v);if(ta.event.changedTouches?L.on("touchmove.brush",d).on("touchend.brush",y):L.on("mousemove.brush",d).on("mouseup.brush",y),k.interrupt().selectAll("*").interrupt(),C)q[0]=f[0]-q[0],q[1]=h[0]-q[1];else if(E){var T=+/w$/.test(E),R=+/^n/.test(E);x=[f[1-T]-q[0],h[1-R]-q[1]],q[0]=f[T],q[1]=h[R]}else ta.event.altKey&&(M=q.slice());k.style("pointer-events","none").selectAll(".resize").style("display",null),ta.select("body").style("cursor",_.style("cursor")),w({type:"brushstart"}),d()}var o,a,c=E(n,"brushstart","brush","brushend"),l=null,s=null,f=[0,0],h=[0,0],g=!0,p=!0,v=Ol[0];return n.event=function(n){n.each(function(){var n=c.of(this,arguments),t={x:f,y:h,i:o,j:a},e=this.__chart__||t;this.__chart__=t,Tl?ta.select(this).transition().each("start.brush",function(){o=e.i,a=e.j,f=e.x,h=e.y,n({type:"brushstart"})}).tween("brush:brush",function(){var e=yu(f,t.x),r=yu(h,t.y);return o=a=null,function(u){f=t.x=e(u),h=t.y=r(u),n({type:"brush",mode:"resize"})}}).each("end.brush",function(){o=t.i,a=t.j,n({type:"brush",mode:"resize"}),n({type:"brushend"})}):(n({type:"brushstart"}),n({type:"brush",mode:"resize"}),n({type:"brushend"}))})},n.x=function(t){return arguments.length?(l=t,v=Ol[!l<<1|!s],n):l},n.y=function(t){return arguments.length?(s=t,v=Ol[!l<<1|!s],n):s},n.clamp=function(t){return arguments.length?(l&&s?(g=!!t[0],p=!!t[1]):l?g=!!t:s&&(p=!!t),n):l&&s?[g,p]:l?g:s?p:null},n.extent=function(t){var e,r,u,i,c;return arguments.length?(l&&(e=t[0],r=t[1],s&&(e=e[0],r=r[0]),o=[e,r],l.invert&&(e=l(e),r=l(r)),e>r&&(c=e,e=r,r=c),(e!=f[0]||r!=f[1])&&(f=[e,r])),s&&(u=t[0],i=t[1],l&&(u=u[1],i=i[1]),a=[u,i],s.invert&&(u=s(u),i=s(i)),u>i&&(c=u,u=i,i=c),(u!=h[0]||i!=h[1])&&(h=[u,i])),n):(l&&(o?(e=o[0],r=o[1]):(e=f[0],r=f[1],l.invert&&(e=l.invert(e),r=l.invert(r)),e>r&&(c=e,e=r,r=c))),s&&(a?(u=a[0],i=a[1]):(u=h[0],i=h[1],s.invert&&(u=s.invert(u),i=s.invert(i)),u>i&&(c=u,u=i,i=c))),l&&s?[[e,u],[r,i]]:l?[e,r]:s&&[u,i])},n.clear=function(){return n.empty()||(f=[0,0],h=[0,0],o=a=null),n},n.empty=function(){return!!l&&f[0]==f[1]||!!s&&h[0]==h[1]},ta.rebind(n,c,"on")};var Hl={n:"ns-resize",e:"ew-resize",s:"ns-resize",w:"ew-resize",nw:"nwse-resize",ne:"nesw-resize",se:"nwse-resize",sw:"nesw-resize"},Ol=[["n","e","s","w","nw","ne","se","sw"],["e","w"],["n","s"],[]],Il=ac.format=gc.timeFormat,Yl=Il.utc,Zl=Yl("%Y-%m-%dT%H:%M:%S.%LZ");Il.iso=Date.prototype.toISOString&&+new Date("2000-01-01T00:00:00.000Z")?Jo:Zl,Jo.parse=function(n){var t=new Date(n);return isNaN(t)?null:t},Jo.toString=Zl.toString,ac.second=Ft(function(n){return new cc(1e3*Math.floor(n/1e3))},function(n,t){n.setTime(n.getTime()+1e3*Math.floor(t))},function(n){return n.getSeconds()}),ac.seconds=ac.second.range,ac.seconds.utc=ac.second.utc.range,ac.minute=Ft(function(n){return new cc(6e4*Math.floor(n/6e4))},function(n,t){n.setTime(n.getTime()+6e4*Math.floor(t))},function(n){return n.getMinutes()}),ac.minutes=ac.minute.range,ac.minutes.utc=ac.minute.utc.range,ac.hour=Ft(function(n){var t=n.getTimezoneOffset()/60;return new cc(36e5*(Math.floor(n/36e5-t)+t))},function(n,t){n.setTime(n.getTime()+36e5*Math.floor(t))},function(n){return n.getHours()}),ac.hours=ac.hour.range,ac.hours.utc=ac.hour.utc.range,ac.month=Ft(function(n){return n=ac.day(n),n.setDate(1),n},function(n,t){n.setMonth(n.getMonth()+t)},function(n){return n.getMonth()}),ac.months=ac.month.range,ac.months.utc=ac.month.utc.range;var Vl=[1e3,5e3,15e3,3e4,6e4,3e5,9e5,18e5,36e5,108e5,216e5,432e5,864e5,1728e5,6048e5,2592e6,7776e6,31536e6],Xl=[[ac.second,1],[ac.second,5],[ac.second,15],[ac.second,30],[ac.minute,1],[ac.minute,5],[ac.minute,15],[ac.minute,30],[ac.hour,1],[ac.hour,3],[ac.hour,6],[ac.hour,12],[ac.day,1],[ac.day,2],[ac.week,1],[ac.month,1],[ac.month,3],[ac.year,1]],$l=Il.multi([[".%L",function(n){return n.getMilliseconds()}],[":%S",function(n){return n.getSeconds()}],["%I:%M",function(n){return n.getMinutes()}],["%I %p",function(n){return n.getHours()}],["%a %d",function(n){return n.getDay()&&1!=n.getDate()}],["%b %d",function(n){return 1!=n.getDate()}],["%B",function(n){return n.getMonth()}],["%Y",Ne]]),Bl={range:function(n,t,e){return ta.range(Math.ceil(n/e)*e,+t,e).map(Ko)},floor:y,ceil:y};Xl.year=ac.year,ac.scale=function(){return Go(ta.scale.linear(),Xl,$l)};var Wl=Xl.map(function(n){return[n[0].utc,n[1]]}),Jl=Yl.multi([[".%L",function(n){return n.getUTCMilliseconds()}],[":%S",function(n){return n.getUTCSeconds()}],["%I:%M",function(n){return n.getUTCMinutes()}],["%I %p",function(n){return n.getUTCHours()}],["%a %d",function(n){return n.getUTCDay()&&1!=n.getUTCDate()}],["%b %d",function(n){return 1!=n.getUTCDate()}],["%B",function(n){return n.getUTCMonth()}],["%Y",Ne]]);Wl.year=ac.year.utc,ac.scale.utc=function(){return Go(ta.scale.linear(),Wl,Jl)},ta.text=At(function(n){return n.responseText}),ta.json=function(n,t){return Nt(n,"application/json",Qo,t)},ta.html=function(n,t){return Nt(n,"text/html",na,t)},ta.xml=At(function(n){return n.responseXML}),"function"==typeof define&&define.amd?define(ta):"object"==typeof module&&module.exports&&(module.exports=ta),this.d3=ta}();</script>
+<style type="text/css">.profvis {
+position: relative;
+}
+.profvis * {
+
+-webkit-box-sizing: content-box;
+-moz-box-sizing: content-box;
+box-sizing: content-box;
+}
+.profvis-footer .info-label {
+cursor: default;
+}
+.profvis-panel1 {
+left: 0px;
+top: 23px;
+position: absolute;
+}
+.profvis-panel1-vertical {
+bottom: 0px;
+width: 500px;
+margin-bottom: 20px;
+}
+.profvis-panel1-horizontal {
+height: 378px;
+right: 0px;
+}
+.profvis-panel2 {
+position: absolute;
+right: 0px;
+bottom: 0px;
+}
+.profvis-panel2-vertical {
+top: 23px;
+left: 508px;
+margin-bottom: 20px;
+}
+.profvis-panel2-horizontal {
+left: 0px;
+top: 408px;
+margin-bottom: 20px;
+}
+.profvis-splitbar {
+position: absolute;
+background-color: rgb(224, 224, 224);
+border-color: #ddd;
+border-style: solid;
+background-repeat: no-repeat;
+background-position: center;
+}
+.profvis-splitbar-vertical {
+cursor: col-resize;
+left: 500px;
+width: 8px;
+top: 23px;
+bottom: 0px;
+border-width: 0 1px;
+background-image: url('data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAMAAAAHCAYAAADNufepAAAACXBIWXMAAAsTAAALEwEAmpwYAAAKT2lDQ1BQaG90b3Nob3AgSUNDIHByb2ZpbGUAAHjanVNnVFPpFj333vRCS4iAlEtvUhUIIFJCi4AUkSYqIQkQSoghodkVUcERRUUEG8igiAOOjoCMFVEsDIoK2AfkIaKOg6OIisr74Xuja9a89+bN/rXXPues852zzwfACAyWSDNRNYAMqUIeEeCDx8TG4eQuQIEKJHAAEAizZCFz/SMBAPh+PDwrIsAHvgABeNMLCADATZvAMByH/w/qQplcAYCEAcB0kThLCIAUAEB6jkKmAEBGAYCdmCZTAKAEAGDLY2LjAFAtAGAnf+bTAICd+Jl7AQBblCEVAaCRACATZYhEAGg7AKzPVopFAFgwABRmS8Q5ANgtADBJV2ZIALC3AMDOEAuyAAgMADBRiIUpAAR7AGDIIyN4AISZABRG8lc88SuuEOcqAAB4mbI8uSQ5RYFbCC1xB1dXLh4ozkkXKxQ2YQJhmkAuwnmZGTKBNA/g88wAAKCRFRHgg/P9eM4Ors7ONo62Dl8t6r8G/yJiYuP+5c+rcEAAAOF0ftH+LC+zGoA7BoBt/qIl7gRoXgugdfeLZrIPQLUAoOnaV/Nw+H48PEWhkLnZ2eXk5NhKxEJbYcpXff5nwl/AV/1s+X48/Pf14L7iJIEyXYFHBPjgwsz0TKUcz5IJhGLc5o9H/LcL//wd0yLESWK5WCoU41EScY5EmozzMqUiiUKSKcUl0v9k4t8s+wM+3zUAsGo+AXuRLahdYwP2SycQWHTA4vcAAPK7b8HUKAgDgGiD4c93/+8//UegJQCAZkmScQAAXkQkLlTKsz/HCAAARKCBKrBBG/TBGCzABhzBBdzBC/xgNoRCJMTCQhBCCmSAHHJgKayCQiiGzbAdKmAv1EAdNMBRaIaTcA4uwlW4Dj1wD/phCJ7BKLyBCQRByAgTYSHaiAFiilgjjggXmYX4IcFIBBKLJCDJiBRRIkuRNUgxUopUIFVIHfI9cgI5h1xGupE7yAAygvyGvEcxlIGyUT3UDLVDuag3GoRGogvQZHQxmo8WoJvQcrQaPYw2oefQq2gP2o8+Q8cwwOgYBzPEbDAuxsNCsTgsCZNjy7EirAyrxhqwVqwDu4n1Y8+xdwQSgUXACTYEd0IgYR5BSFhMWE7YSKggHCQ0EdoJNwkDhFHCJyKTqEu0JroR+cQYYjIxh1hILCPWEo8TLxB7iEPENyQSiUMyJ7mQAkmxpFTSEtJG0m5SI+ksqZs0SBojk8naZGuyBzmULCAryIXkneTD5DPkG+Qh8lsKnWJAcaT4U+IoUspqShnlEOU05QZlmDJBVaOaUt2ooVQRNY9aQq2htlKvUYeoEzR1mjnNgxZJS6WtopXTGmgXaPdpr+h0uhHdlR5Ol9BX0svpR+iX6AP0dwwNhhWDx4hnKBmbGAcYZxl3GK+YTKYZ04sZx1QwNzHrmOeZD5lvVVgqtip8FZHKCpVKlSaVGyovVKmqpqreqgtV81XLVI+pXlN9rkZVM1PjqQnUlqtVqp1Q61MbU2epO6iHqmeob1Q/pH5Z/YkGWcNMw09DpFGgsV/jvMYgC2MZs3gsIWsNq4Z1gTXEJrHN2Xx2KruY/R27iz2qqaE5QzNKM1ezUvOUZj8H45hx+Jx0TgnnKKeX836K3hTvKeIpG6Y0TLkxZVxrqpaXllirSKtRq0frvTau7aedpr1Fu1n7gQ5Bx0onXCdHZ4/OBZ3nU9lT3acKpxZNPTr1ri6qa6UbobtEd79up+6Ynr5egJ5Mb6feeb3n+hx9L/1U/W36p/VHDFgGswwkBtsMzhg8xTVxbzwdL8fb8VFDXcNAQ6VhlWGX4YSRudE8o9VGjUYPjGnGXOMk423GbcajJgYmISZLTepN7ppSTbmmKaY7TDtMx83MzaLN1pk1mz0x1zLnm+eb15vft2BaeFostqi2uGVJsuRaplnutrxuhVo5WaVYVVpds0atna0l1rutu6cRp7lOk06rntZnw7Dxtsm2qbcZsOXYBtuutm22fWFnYhdnt8Wuw+6TvZN9un2N/T0HDYfZDqsdWh1+c7RyFDpWOt6azpzuP33F9JbpL2dYzxDP2DPjthPLKcRpnVOb00dnF2e5c4PziIuJS4LLLpc+Lpsbxt3IveRKdPVxXeF60vWdm7Obwu2o26/uNu5p7ofcn8w0nymeWTNz0MPIQ+BR5dE/C5+VMGvfrH5PQ0+BZ7XnIy9jL5FXrdewt6V3qvdh7xc+9j5yn+M+4zw33jLeWV/MN8C3yLfLT8Nvnl+F30N/I/9k/3r/0QCngCUBZwOJgUGBWwL7+Hp8Ib+OPzrbZfay2e1BjKC5QRVBj4KtguXBrSFoyOyQrSH355jOkc5pDoVQfujW0Adh5mGLw34MJ4WHhVeGP45wiFga0TGXNXfR3ENz30T6RJZE3ptnMU85ry1KNSo+qi5qPNo3ujS6P8YuZlnM1VidWElsSxw5LiquNm5svt/87fOH4p3iC+N7F5gvyF1weaHOwvSFpxapLhIsOpZATIhOOJTwQRAqqBaMJfITdyWOCnnCHcJnIi/RNtGI2ENcKh5O8kgqTXqS7JG8NXkkxTOlLOW5hCepkLxMDUzdmzqeFpp2IG0yPTq9MYOSkZBxQqohTZO2Z+pn5mZ2y6xlhbL+xW6Lty8elQfJa7OQrAVZLQq2QqboVFoo1yoHsmdlV2a/zYnKOZarnivN7cyzytuQN5zvn//tEsIS4ZK2pYZLVy0dWOa9rGo5sjxxedsK4xUFK4ZWBqw8uIq2Km3VT6vtV5eufr0mek1rgV7ByoLBtQFr6wtVCuWFfevc1+1dT1gvWd+1YfqGnRs+FYmKrhTbF5cVf9go3HjlG4dvyr+Z3JS0qavEuWTPZtJm6ebeLZ5bDpaql+aXDm4N2dq0Dd9WtO319kXbL5fNKNu7g7ZDuaO/PLi8ZafJzs07P1SkVPRU+lQ27tLdtWHX+G7R7ht7vPY07NXbW7z3/T7JvttVAVVN1WbVZftJ+7P3P66Jqun4lvttXa1ObXHtxwPSA/0HIw6217nU1R3SPVRSj9Yr60cOxx++/p3vdy0NNg1VjZzG4iNwRHnk6fcJ3/ceDTradox7rOEH0x92HWcdL2pCmvKaRptTmvtbYlu6T8w+0dbq3nr8R9sfD5w0PFl5SvNUyWna6YLTk2fyz4ydlZ19fi753GDborZ752PO32oPb++6EHTh0kX/i+c7vDvOXPK4dPKy2+UTV7hXmq86X23qdOo8/pPTT8e7nLuarrlca7nuer21e2b36RueN87d9L158Rb/1tWeOT3dvfN6b/fF9/XfFt1+cif9zsu72Xcn7q28T7xf9EDtQdlD3YfVP1v+3Njv3H9qwHeg89HcR/cGhYPP/pH1jw9DBY+Zj8uGDYbrnjg+OTniP3L96fynQ89kzyaeF/6i/suuFxYvfvjV69fO0ZjRoZfyl5O/bXyl/erA6xmv28bCxh6+yXgzMV70VvvtwXfcdx3vo98PT+R8IH8o/2j5sfVT0Kf7kxmTk/8EA5jz/GMzLdsAAAAgY0hSTQAAeiUAAICDAAD5/wAAgOkAAHUwAADqYAAAOpgAABdvkl/FRgAAADdJREFUeNpMi7ENADAIwwz/H8TEhMQz/JAupWqmyHGI7JoZIrscxMbBbhX+MMbTpG+x/UgCgzMA+a4RzyZ2yIIAAAAASUVORK5CYII=');
+}
+.profvis-splitbar-horizontal {
+cursor: row-resize;
+top: 400px;
+height: 8px;
+left: 0px;
+right: 0px;
+border-width: 0px 0;
+background-image: url('data:image/png;base64,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');
+}
+.profvis-status-bar {
+position: absolute;
+padding: 0px 0px;
+top: 0;
+left: 0;
+right: 0;
+height: 22px;
+line-height: 18px;
+border-bottom: 1px solid rgb(196, 201, 204);
+background-color: rgb(248, 249, 248);
+color: #444;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-footer {
+position: absolute;
+padding: 0px 0px;
+bottom: 0px;
+left: 0;
+right: 0;
+height: 19px;
+line-height: 18px;
+border-top: 1px solid rgb(196, 201, 204);
+background-color: rgb(248, 249, 248);
+color: #444;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-status-bar .info-block {
+display: inline-block;
+vertical-align: top;
+width: 140px;
+padding: 2px 11px 2px 11px;
+}
+.profvis-footer .info-block {
+display: inline-block;
+vertical-align: top;
+padding: 1px 11px 1px 11px;
+}
+.profvis-footer .info-block-right {
+display: inline-block;
+vertical-align: top;
+padding: 1px 11px 1px 11px;
+float: right;
+}
+.profvis-status-bar .result-block {
+width: auto;
+cursor: pointer;
+}
+.profvis-status-bar .result-block-active {
+width: auto;
+background: rgb(227, 229, 230);
+}
+.profvis-status-bar .spacing-block {
+display: inline-block;
+width: 25px;
+}
+.profvis-status-bar .separator-block {
+display: inline-block;
+width: 1px;
+text-align: center;
+}
+.profvis-status-bar .separator-block .separator-image {
+width: 2px;
+height: 26px;
+margin-top: -2px;
+}
+.profvis-status-bar .options-button {
+float: right;
+color: #444;
+text-decoration: none;
+cursor: pointer;
+padding: 2px 11px 2px 11px;
+}
+.profvis-options-panel {
+float: left;
+position: absolute;
+right: 0;
+top: 21px;
+padding: 3px 6px;
+border: 1px solid #999;
+background-color: #fff;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+line-height: 170%;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+cursor: pointer;
+}
+.profvis-code {
+position: absolute;
+top: 0px;
+left: 0;
+bottom: 0;
+right: 0;
+overflow-y: auto;
+border: 0px solid #ddd;
+}
+.profvis-flamegraph {
+position: absolute;
+right: 0;
+top: 0;
+bottom: 0;
+left: 0;
+overflow: hidden;
+border: 0px solid #ddd;
+background: rgb(249, 249, 250);
+}
+table.profvis-table {
+border-collapse: collapse;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+width: 100%;
+text-align: left;
+cursor: default;
+}
+table.profvis-table th {
+background-color: rgb(249, 249, 250);
+width: 14%;
+}
+table.profvis-table th.spacing {
+width: 20px;
+}
+table.profvis-table th.filename {
+font-family: monospace;
+padding-left: 10px;
+width: auto;
+}
+table.profvis-table th.percent {
+text-align: center;
+}
+table.profvis-table tr {
+border-top: 1px solid transparent;
+border-bottom: 1px solid transparent;
+vertical-align: top;
+}
+
+table.profvis-table tr.locked > td {
+border-top: 1px solid #444;
+border-bottom: 1px solid #444;
+}
+table.profvis-table tr > td {
+padding-top: 0;
+padding-bottom: 0;
+}
+table.profvis-table tr.active {
+background-color: #fdb;
+}
+table.profvis-table .linenum {
+color: #aaa;
+padding: 0 15px;
+font-family: monospace;
+width: 25px;
+}
+
+table.profvis-table [data-pseudo-content]::before {
+content: attr(data-pseudo-content);
+}
+table.profvis-table .code {
+white-space: pre-wrap;
+margin: 0;
+min-height: 1.25em;
+line-height: 1.25;
+width: auto;
+font-family: monospace;
+background: transparent;
+}
+table.profvis-table .time, table.profvis-table .percent {
+padding: 0 5px;
+text-align: right;
+min-width: 2em;
+max-width: 2em;
+overflow: hidden;
+padding-right: 10px;
+}
+table.profvis-table .memory {
+padding-right: 5px;
+}
+table.profvis-table th.time {
+text-align: center;
+}
+table.profvis-table .memory {
+padding: 0 5px;
+text-align: right;
+min-width: 2em;
+max-width: 4em;
+overflow: hidden;
+padding-right: 10px;
+}
+table.profvis-table .memory-right {
+text-align: left;
+}
+table.profvis-table th.memory {
+text-align: center;
+}
+table.profvis-table .timebar-cell {
+padding-left: 0;
+border-left: 1px solid #444;
+min-width: 3em;
+width: 3em;
+}
+table.profvis-table .timebar-cell > .timebar {
+background-color: #5A5A5A;
+border-radius: 0px 2px 2px 0px;
+line-height: 15px;
+}
+table.profvis-table .membar-left-cell {
+padding-left: 0;
+padding-right: 0;
+border-left: 0px solid black;
+min-width: 0.5em;
+width: 0.5em;
+}
+table.profvis-table .membar-left-cell > .membar {
+background-color: #A7A7A7;
+float: right;
+border-radius: 2px 0px 0px 2px;
+line-height: 15px;
+}
+table.profvis-table .membar-right-cell {
+padding-left: 0;
+border-left: 1px solid black;
+min-width: 1em;
+width: 1em;
+}
+table.profvis-table .membar-right-cell > .membar {
+background-color: #5A5A5A;
+border-radius: 0px 2px 2px 0px;
+line-height: 15px;
+}
+.profvis-flamegraph .background {
+fill: rgb(249, 249, 250);
+}
+.profvis-flamegraph .cell .rect {
+stroke: #000;
+stroke-width: 0.25px;
+fill: #fff;
+}
+.profvis-flamegraph .cell.active .rect {
+stroke-width: 0.75px;
+fill: #ddd;
+}
+.profvis-flamegraph .cell.highlighted .rect {
+fill: #ffc;
+}
+.profvis-flamegraph .cell.highlighted.active .rect {
+fill: #fdb;
+}
+.profvis-flamegraph .cell.output .rect {
+fill: #eef;
+}
+.profvis-flamegraph .cell.gc .rect {
+fill: #ccc;
+}
+.profvis-flamegraph .cell.stacktrace .rect {
+fill: #eee;
+}
+.profvis-flamegraph .cell.stacktrace .profvis-label {
+fill: #666;
+}
+.profvis-flamegraph .cell.locked {
+font-weight: bold;
+}
+.profvis-flamegraph .cell.locked .rect {
+stroke-width: 2px;
+}
+.profvis-flamegraph .cell .profvis-label {
+font-family: monospace;
+font-size: 11px;
+cursor: default;
+}
+.profvis-flamegraph .axis text {
+font: 10px sans-serif;
+}
+.profvis-flamegraph .axis path,
+.profvis-flamegraph .axis line {
+fill: none;
+stroke: #000;
+shape-rendering: crispEdges;
+}
+.profvis-flamegraph .profvis-tooltip rect {
+fill: rgb(249, 249, 250);
+stroke: #000;
+opacity: 0.75;
+stroke-opacity: 0.75;
+stroke-width: 0.5;
+}
+.profvis-flamegraph .profvis-tooltip text {
+text-anchor: middle;
+font-family: monospace;
+font-size: 11px;
+}
+.profvis-infobox {
+position: absolute;
+left: 8px;
+top: 8px;
+opacity: 0.8;
+border-radius: 3px;
+color: #f8f8f8;
+background-color: #333;
+padding: 5px 10px;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+line-height: 100%;
+pointer-events: none;
+min-width: 280px;
+}
+.profvis-infobox table {
+border-collapse: separate;
+border-spacing: 2px;
+}
+.profvis-infobox table td {
+padding: 1px;
+}
+.profvis-infobox .infobox-title {
+font-weight: bold;
+}
+.profvis-message {
+width: 100%;
+height: 100%;
+display: -ms-flexbox;
+display: -webkit-flex;
+display: flex;
+-ms-flex-pack: center;
+-webkit-justify-content: center;
+justify-content: center;
+-ms-flex-align: center;
+-webkit-align-items: center;
+align-items: center;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+}
+.profvis-message div {
+color: #444;
+height: 25%;
+}
+.profvis-treetable {
+top: 0px;
+bottom: 0px;
+left: 0px;
+right: 0px;
+position: absolute;
+margin-top: 23px;
+margin-bottom: 21px;
+margin-right: 0px;
+overflow: hidden;
+font: 10px sans-serif;
+color: #161616;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+overflow-y: auto;
+}
+.profvis-treetable .results {
+width: 100%;
+table-layout: fixed;
+}
+.profvis-treetable th {
+font-weight: normal;
+height: 18px;
+background-color: #F8F9F8;
+border-bottom: solid 1px #E4E4E4;
+border-right: solid 1px #E4E4E4;
+padding-left: 3px;
+padding-right: 3px;
+}
+.profvis-treetable td {
+height: 18px;
+border-bottom: solid 1px #E4E4E4;
+border-right: solid 1px #E4E4E4;
+padding-left: 3px;
+padding-right: 3px;
+overflow: hidden;
+text-overflow: ellipsis;
+}
+.profvis-treetable .action {
+width: 18px;
+}
+.profvis-treetable .memory {
+width: 100px;
+text-align: right;
+}
+.profvis-treetable th {
+cursor: default;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-treetable th.memory {
+text-align: center;
+}
+.profvis-treetable .time {
+width: 100px;
+text-align: right;
+}
+.profvis-treetable th.time {
+text-align: center;
+}
+.profvis-treetable .count {
+text-align: right;
+}
+.profvis-treetable th.count {
+text-align: center;
+}
+.profvis-treetable th.code-label {
+text-align: left;
+padding-left: 5px;
+}
+.profvis-treetable td.label-pointer {
+cursor: pointer;
+}
+.profvis-treetable .label-text {
+display: inline-block;
+-webkit-user-select: none;
+-khtml-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+}
+.profvis-treetable .path {
+text-align: left;
+}
+.profvis-treetable .treetable-expand > div {
+display: inline-block;
+width: 15px;
+}
+.profvis-treetable .treetable-expand > div > div{
+width: 0px;
+height: 0px;
+margin-left: 3px;
+margin-right: 6px;
+border-top: 4px solid transparent;
+border-left: 6px solid #161616;
+border-bottom: 4px solid transparent;
+}
+.profvis-treetable .treetable-collapse > div {
+display: inline-block;
+width: 15px;
+}
+.profvis-treetable .treetable-collapse > div > div {
+width: 0px;
+height: 0px;
+margin-left: 3px;
+margin-right: 6px;
+border-right: 4px solid transparent;
+border-top: 6px solid #161616;
+border-left: 4px solid transparent;
+display: inline-block;
+}
+.profvis-treetable .time-info {
+padding: 0px;
+padding-right: 2px;
+text-align: right;
+}
+.profvis-treetable .timebar {
+width: 0px;
+height: 14px;
+background-color: #5A5A5A;
+float: left;
+border-radius: 2px 2px 2px 2px;
+padding-top: 0px;
+margin-top: 1px;
+}
+.profvis-treetable .timecell {
+padding-top: 2px;
+padding-right: 3px;
+}
+.profvis-treetable .memory-info {
+padding-left: 0px;
+padding-right: 2px;
+text-align: right;
+}
+.profvis-treetable .memory-info-right {
+padding-left: 2px;
+padding-right: 0px;
+text-align: left;
+}
+.profvis-treetable .memory-leftbar-wrapper {
+float: left;
+height: 14px;
+width: 5px;
+}
+.profvis-treetable .memory-leftbar {
+width: 2px;
+height: 14px;
+background-color: #A7A7A7;
+float: right;
+border-radius: 1px 0px 0px 1px;
+}
+.profvis-treetable .memory-rightbar {
+width: 2px;
+float: left;
+height: 14px;
+background-color: #5A5A5A;
+border-radius: 0px 1px 1px 0px;
+}
+.profvis-treetable .memory-cell {
+}
+.profvis-treetable .memory-bar-container {
+margin-right: 3px;
+}
+.profvis-treetable .time-bar-container {
+margin-right: 3px;
+}
+</style>
+<script>/*jshint
+  undef:true,
+  browser:true,
+  devel: true,
+  jquery:true,
+  strict:false,
+  curly:false,
+  indent:2
+*/
+/*global profvis:true, d3, hljs */
+
+profvis = (function() {
+  var profvis = {};
+
+  profvis.render = function(el, message) {
+
+    function generateStatusBarButton(id, caption, active) {
+      var spacerImage = 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAIAAAAUCAYAAACnOeyiAAAAXklEQVR42mNgAIL///8zMYSGhjIDGYIMIiIMvECGMwMDN4M4kFEDUqIIZKwDMdSBjAsghj6Q8QPEMAAy/lOBoQekv4AYKkDGfgZeXl4RICOLQUtLiw3IUAJJMQIZ7AC2tU2tXJxOYgAAAABJRU5ErkJggg==';
+
+      var buttonHtml =
+        '<div id="' + id  + '" class="info-block ' +
+        (active ? 'result-block-active' : 'result-block') +
+        '"><span class="info-label">' + caption + '</span></div>' +
+        '<div class="separator-block"><img class="separator-image" src="' + spacerImage + '"></div>';
+
+      return buttonHtml;
+    }
+
+    function generateStatusBar(el, onToogle) {
+      var $el = $(el);
+
+      el.innerHTML =
+        generateStatusBarButton('flameGraphButton', 'Flame Graph', true) +
+        generateStatusBarButton('treetableButton', 'Data', false) +
+        '<span role="button" class="options-button">Options &#x25BE;</span>';
+
+      $el.find("span.options-button").on("click", function(e) {
+        e.preventDefault();
+        e.stopPropagation();
+
+        vis.optionsPanel.toggleVisibility();
+      });
+
+      var setStatusBarButtons = function(e) {
+        $(".info-block").removeClass("result-block-active");
+        $(".info-block").addClass("result-block");
+        e.addClass("result-block-active");
+      };
+
+      $el.find("#flameGraphButton").on("click", function() {
+        setStatusBarButtons($(this));
+        onToogle("flamegraph");
+      });
+
+      $el.find("#treetableButton").on("click", function() {
+        setStatusBarButtons($(this));
+        onToogle("treetable");
+      });
+
+      return {
+        el: el
+      };
+    }
+
+    function generateFooter(el, onToogle) {
+      var $el = $(el);
+
+      el.innerHTML =
+        '<div class="info-block"><span class="info-label">Sample Interval: ' +
+          vis.interval + 'ms</span></div>' +
+        '<div class="info-block-right">' +
+        // '<span class="info-label" title="Peak memory allocation">' + (Math.round(vis.totalMem * 100) / 100) + 'MB</span>' +
+        // ' / ' +
+        '<span class="info-label" title="Total time">' + vis.totalTime + 'ms</span>' +
+        '</div>';
+
+      return {
+        el: el
+      };
+    }
+
+    function generateOptionsPanel(el, onOptionsChange) {
+      var $el = $(el);
+
+      el.innerHTML =
+        '<div role="button" class="split-horizontal">' +
+          '<span class="options-checkbox" data-checked="1">' +
+          (vis.splitDir === "h" ? '&#x2612;' : '&#x2610;') +
+          '</span> Split horizontally' +
+        '</div>' +
+        '<div role="button" class="hide-internal">' +
+          '<span class="options-checkbox" data-checked="1">&#x2612;</span> Hide internal function calls' +
+        '</div>' +
+        '<div role="button" class="hide-zero-row">' +
+          '<span class="options-checkbox" data-checked="0">&#x2610;</span> Hide lines of code with zero time' +
+        '</div>' +
+        '<div role="button" class="hide-memory">' +
+          '<span class="options-checkbox" data-checked="0">&#x2610;</span> Hide memory results' +
+        '</div>';
+
+      // Toggle the appearance of a checkbox and return the new checked state.
+      function toggleCheckbox($checkbox) {
+        // Use attr() instead of data(), because the latter tries to coerce to
+        // numbers, which complicates our comparisons.
+        var checked = $checkbox.attr("data-checked");
+
+        if (checked === "0") {
+          $checkbox.attr("data-checked", "1");
+          $checkbox.html("&#x2612;");
+          return true;
+
+        } else {
+          $checkbox.attr("data-checked", "0");
+          $checkbox.html("&#x2610;");
+          return false;
+        }
+      }
+
+      $el.find(".split-horizontal")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("split", checked);
+        });
+
+      $el.find(".hide-internal")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("internals", checked);
+        });
+
+      $el.find(".hide-memory")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("memory", checked);
+        });
+
+      // Make the "hide internal" option available or unavailable to users
+      function enableHideInternal() {
+        $el.find(".hide-internal").css("display", "");
+      }
+      function disableHideInternal() {
+        $el.find(".hide-internal").css("display", "none");
+      }
+      // By default, start with it unavailable; it's only relevant for Shiny
+      // apps.
+      disableHideInternal();
+
+
+      $el.find(".hide-zero-row")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+
+          if (checked) {
+            vis.codeTable.hideZeroTimeRows();
+          } else {
+            vis.codeTable.showZeroTimeRows();
+          }
+        });
+
+      el.style.visibility = "hidden";
+      function toggleVisibility(offset) {
+        if (el.style.visibility === "visible") {
+          el.style.visibility = "hidden";
+        } else {
+          el.style.visibility = "visible";
+          $(document).on("click", hideOnClickOutside);
+        }
+      }
+
+      // Hide the panel when a click happens outside. This handler also removes
+      // itself after it fires.
+      function hideOnClickOutside(e) {
+        var $el = $(el);
+        if (!$el.is(e.target) && $el.has(e.target).length === 0) {
+          el.style.visibility = "hidden";
+          // Unregister this event listener
+          $(document).off("click", hideOnClickOutside);
+        }
+      }
+
+      return {
+        el: el,
+        toggleVisibility: toggleVisibility,
+        enableHideInternal: enableHideInternal,
+        disableHideInternal: disableHideInternal
+      };
+    }
+
+    function notifySourceFileMessage(d, details) {
+      if (window.parent.postMessage) {
+        window.parent.postMessage({
+          source: "profvis",
+          message: "sourcefile",
+          file: d.filename,
+          normpath: d.normpath ? d.normpath : getNormPath(vis.files, d.filename),
+          line: d.linenum,
+          details: details
+        }, window.location.origin);
+      }
+    }
+
+    function roundOneDecimalNum(number, decimals) {
+      return Math.round(number * 10) / 10;
+    }
+
+    function roundOneDecimal(number, decimals) {
+      if (!number) return 0;
+      return roundOneDecimalNum(number).toFixed(1);
+    }
+
+    // Generate the code table ----------------------------------------
+    function generateCodeTable(el) {
+      var useMemory = false;
+      var content = d3.select(el);
+
+      if (vis.fileLineStats.length === 0) {
+        content.append("div")
+          .attr("class", "profvis-message")
+          .append("div")
+            .text("(Sources not available)");
+      }
+
+      // One table for each file
+      var tables = content.selectAll("table")
+          .data(vis.fileLineStats)
+        .enter()
+          .append("table")
+          .attr("class", "profvis-table");
+
+      // Table headers
+      var headerRows = tables.append("tr");
+      headerRows.append("th")
+        .attr("colspan", "2")
+        .attr("class", "filename")
+        .text(function(d) { return d.filename; });
+
+      var percentTooltip = "Percentage of tracked execution time";
+      var percentMemTooltip = "Percentage of peak memory deallocation and allocation";
+
+      headerRows.append("th")
+        .attr("class", "table-memory memory")
+        .attr("colspan", "4")
+        .text("Memory");
+
+      headerRows.append("th")
+        .attr("class", "time")
+        .attr("colspan", "2")
+        .text("Time");
+
+      headerRows.append("th")
+        .attr("class", "spacing")
+        .attr("data-pseudo-content", "\u00a0");
+
+      // Insert each line of code
+      var rows = tables.selectAll("tr.code-row")
+          .data(function(d) { return d.lineData; })
+        .enter()
+          .append("tr")
+          .attr("class", "code-row");
+
+      // Use pseudo-content and CSS content rule to make text unselectable and
+      // uncopyable. See https://danoc.me/blog/css-prevent-copy/
+      rows.append("td")
+        .attr("class", "linenum")
+        .attr("data-pseudo-content", function(d) { return d.linenum; });
+
+      rows.append("td")
+        .attr("class", "code r")
+        .text(function(d) { return d.content; })
+        .each(function() { hljs.highlightElement(this); });
+
+      rows.append("td")
+        .attr("class", "table-memory memory")
+        .attr("title", "Memory deallocation (MB)")
+        .attr("data-pseudo-content",
+              function(d) { return roundOneDecimalNum(d.sumMemDealloc) !== 0 ? roundOneDecimal(d.sumMemDealloc) : ""; });
+
+      rows.append("td")
+        .attr("class", "table-memory membar-left-cell")
+        .append("div")
+          .attr("class", "membar")
+          .attr("title", percentMemTooltip)
+          .style("width", function(d) {
+            var p = Math.min(Math.abs(Math.min(Math.round(d.propMemDealloc * 100), 0)), 100);
+
+            // 8% is the minimal size that looks visually appealing while drawing an almost empty bar
+            p = roundOneDecimalNum(d.sumMemDealloc) !== 0 ? Math.max(p, 8) : 0;
+            return p + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "table-memory membar-right-cell")
+        .append("div")
+          .attr("class", "membar")
+          .attr("title", percentMemTooltip)
+          .style("width", function(d) {
+            var p = Math.min(Math.max(Math.round(d.propMemAlloc * 100), 0), 100);
+
+            // 4% is the minimal size that looks visually appealing while drawing an almost empty bar
+            p = roundOneDecimalNum(d.sumMemAlloc) !== 0 ? Math.max(p, 4) : 0;
+            return p + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "table-memory memory memory-right")
+        .attr("title", "Memory allocation (MB)")
+        .attr("data-pseudo-content",
+              function(d) { return roundOneDecimalNum(d.sumMemAlloc) !== 0 ? roundOneDecimal(d.sumMemAlloc) : ""; });
+
+      rows.append("td")
+        .attr("class", "time")
+        .attr("title", "Total time (ms)")
+        .attr("data-pseudo-content",
+              function(d) { return Math.round(d.sumTime * 100) !== 0 ? (Math.round(d.sumTime * 100) / 100) : ""; });
+
+      rows.append("td")
+        .attr("class", "timebar-cell")
+        .append("div")
+          .attr("class", "timebar")
+          .attr("title", percentTooltip)
+          .style("width", function(d) {
+            return Math.round(d.propTime * 100) + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "spacing")
+        .attr("data-pseudo-content", "\u00a0");
+
+      rows
+        .on("click", function(d) {
+          // Info box is only relevant when mousing over flamegraph
+          vis.infoBox.hide();
+          highlighter.click(d);
+          notifySourceFileMessage(d, "select");
+        })
+        .on("mouseover", function(d) {
+          if (highlighter.isLocked()) return;
+
+          // Info box is only relevant when mousing over flamegraph
+          vis.infoBox.hide();
+          highlighter.hover(d);
+        })
+        .on("mouseout", function(d) {
+          if (highlighter.isLocked()) return;
+
+          highlighter.hover(null);
+        })
+        .on("dblclick", function(d) {
+          notifySourceFileMessage(d, "open");
+        });
+
+      function hideZeroTimeRows() {
+        rows
+          .filter(function(d) { return d.sumTime === 0; })
+          .style("display", "none");
+      }
+
+      function showZeroTimeRows() {
+        rows
+          .filter(function(d) { return d.sumTime === 0; })
+          .style("display", "");
+      }
+
+      function addLockHighlight(d) {
+        var target = d;
+        rows
+          .filter(function(d) { return d === target; } )
+          .classed({ locked: true });
+      }
+
+      function clearLockHighlight() {
+        rows
+          .filter(".locked")
+          .classed({ locked: false });
+      }
+
+      function addActiveHighlight(d) {
+        // If we have filename and linenum, search for cells that match, and
+        // set them as "active".
+        var target = d;
+        if (target.filename && target.linenum) {
+          var tr = rows
+            .filter(function(d) {
+              return d.linenum === target.linenum &&
+                     d.filename === target.filename;
+            })
+            .classed({ active: true });
+
+          tr.node().scrollIntoViewIfNeeded();
+        }
+      }
+
+      function clearActiveHighlight() {
+        rows
+          .filter(".active")
+          .classed({ active: false });
+      }
+
+      function enableScroll() {
+        // TODO: implement this
+      }
+
+      function disableScroll() {
+      }
+
+      function useMemoryResults() {
+        d3.selectAll(".table-memory").style("display", vis.hideMemory ? "none" : "");
+      }
+
+      return {
+        el: el,
+        hideZeroTimeRows: hideZeroTimeRows,
+        showZeroTimeRows: showZeroTimeRows,
+        addLockHighlight: addLockHighlight,
+        clearLockHighlight: clearLockHighlight,
+        addActiveHighlight: addActiveHighlight,
+        clearActiveHighlight: clearActiveHighlight,
+        enableScroll: enableScroll,
+        disableScroll: disableScroll,
+        useMemoryResults: useMemoryResults
+      };
+    }
+
+
+    var highlighter = (function() {
+      // D3 data objects for the currently locked and active items
+      var lockItem = null;
+      var activeItem = null;
+
+      function isLocked() {
+        return lockItem !== null;
+      }
+
+      function currentLock() {
+        return lockItem;
+      }
+
+      function currentActive() {
+        return activeItem;
+      }
+
+
+      // This is called when a flamegraph cell or a line of code is clicked on.
+      // Clicks also should trigger hover events.
+      function click(d) {
+        // If d is null (background is clicked), or if locked and this click
+        // is on the currently locked selection, just unlock and return.
+        if (d === null || (lockItem && d === lockItem)) {
+          lockItem = null;
+          vis.flameGraph.clearLockHighlight();
+          vis.codeTable.clearLockHighlight();
+          return;
+        }
+
+        // If nothing currently locked, or if locked and this click is on
+        // something other than the currently locked selection, then lock the
+        // current selection.
+        lockItem = d;
+
+        vis.flameGraph.clearLockHighlight();
+        vis.codeTable.clearLockHighlight();
+        hover(null);
+
+        vis.flameGraph.addLockHighlight(d);
+        vis.codeTable.addLockHighlight(d);
+        hover(d);
+      }
+
+
+      function hover(d) {
+        activeItem = d;
+
+        if (activeItem) {
+          vis.flameGraph.addActiveHighlight(activeItem);
+          vis.codeTable.addActiveHighlight(activeItem);
+          return;
+        }
+
+        vis.flameGraph.clearActiveHighlight();
+        vis.codeTable.clearActiveHighlight();
+      }
+
+      return {
+        isLocked: isLocked,
+        currentLock: currentLock,
+        currentActive: currentActive,
+
+        click: click,
+        hover: hover
+      };
+    })();
+
+
+    // Generate the flame graph -----------------------------------------------
+    function generateFlameGraph(el) {
+      el.innerHTML = "";
+
+      var stackHeight = 15;   // Height of each layer on the stack, in pixels
+      var zoomMargin = 0.02;  // Extra margin on sides when zooming to fit
+
+      // Dimensions -----------------------------------------------------------
+
+      // Margin inside the svg where the plotting occurs
+      var dims = {
+        margin: { top: 0, right: 0, left: 0, bottom: 30 }
+      };
+      dims.width = el.clientWidth - dims.margin.left - dims.margin.right;
+      dims.height = el.clientHeight - dims.margin.top - dims.margin.bottom;
+
+      var domains = {
+        x: [
+          d3.min(vis.prof, function(d) { return d.startTime; }),
+          d3.max(vis.prof, function(d) { return d.endTime; })
+        ],
+        y: [
+          d3.min(vis.prof, function(d) { return d.depth; }) - 1,
+          d3.max(vis.prof, function(d) { return d.depth; })
+        ]
+      };
+      // Slightly expand x domain
+      domains.x = expandRange(domains.x, zoomMargin);
+
+      // Scales ---------------------------------------------------------------
+      var scales = {
+        x: d3.scale.linear()
+            .domain(domains.x)
+            .range([0, dims.width]),
+
+        y: d3.scale.linear()
+            .domain(domains.y)
+            .range([dims.height, dims.height - (domains.y[1] - domains.y[0]) * stackHeight]),
+
+        // This will be a function that, given a data point, returns the depth.
+        // This function can change; sometimes it returns the original depth,
+        // and sometimes it returns the collapsed depth. This isn't exactly a
+        // scale function, but it's close enough for our purposes.
+        getDepth: null
+      };
+
+      function useCollapsedDepth() {
+        scales.getDepth = function(d) { return d.depthCollapsed; };
+      }
+      function useUncollapsedDepth() {
+        scales.getDepth = function(d) { return d.depth; };
+      }
+
+      useCollapsedDepth();
+
+      // SVG container objects ------------------------------------------------
+      var svg = d3.select(el).append('svg');
+
+      var clipRect = svg.append("clipPath")
+          .attr("id", "clip-" + vis.el.id)
+        .append("rect");
+
+      var container = svg.append('g')
+        .attr("transform", "translate(" + dims.margin.left + "," + dims.margin.top + ")")
+        .attr("clip-path", "url(" + urlNoHash() + "#clip-" + vis.el.id + ")");
+
+      // Add a background rect so we have something to grab for zooming/panning
+      var backgroundRect = container.append("rect")
+        .attr("class", "background");
+
+      // Axes ------------------------------------------------------------
+      var xAxis = d3.svg.axis()
+        .scale(scales.x)
+        .orient("bottom");
+
+      svg.append("g")
+        .attr("class", "x axis")
+        .call(xAxis);
+
+      // Container sizing -----------------------------------------------------
+      // Update dimensions of various container elements, based on the overall
+      // dimensions of the containing div.
+      function updateContainerSize() {
+        dims.width = el.clientWidth - dims.margin.left - dims.margin.right;
+        dims.height = el.clientHeight - dims.margin.top - dims.margin.bottom;
+
+        svg
+          .attr('width', dims.width + dims.margin.left + dims.margin.right)
+          .attr('height', dims.height + dims.margin.top + dims.margin.bottom);
+
+        clipRect
+          .attr("x", dims.margin.left)
+          .attr("y", dims.margin.top)
+          .attr("width", dims.width)
+          .attr("height", dims.height);
+
+        backgroundRect
+          .attr("width", dims.width)
+          .attr("height", dims.height);
+
+        svg.select(".x.axis")
+          .attr("transform", "translate(" + dims.margin.left + "," + dims.height + ")");
+      }
+
+
+      // Redrawing ------------------------------------------------------------
+
+      // Redrawing is a little complicated. For performance reasons, the
+      // flamegraph cells that are offscreen aren't rendered; they're removed
+      // from the D3 selection of cells. However, when transitions are
+      // involved, it may be necssary to add objects in their correct
+      // off-screen starting locations before the transition, and then do the
+      // transition. Similarly, it may be necssary to transition objects to
+      // their correct off-screen ending positions.
+      //
+      // In order to handle this, whenever there's a transition, we need to
+      // have the scales for before the transition, and after. When a function
+      // invokes a transition, it will generally do the following: (1) save the
+      // previous scales, (2) modify the current scales, (3) call a redraw
+      // function. The redraw functions are customized for different types of
+      // transitions, and they will use the saved previous scales to position
+      // objects correctly for the transition. When there's no transition, the
+      // previous scales aren't needed, and the redrawImmediate() function
+      // should be used.
+
+      // Cache cells for faster access (avoid a d3.select())
+      var cells;
+
+      // For a data element, return identifying key
+      function dataKey(d) {
+        return d.depth + "-" + d.startTime + "-" + d.endTime;
+      }
+
+      // For transitions with animation, we need to have a copy of the previous
+      // scales in addition to the current ones.
+      var prevScales = {};
+      function savePrevScales() {
+        prevScales = {
+          x:        scales.x.copy(),
+          y:        scales.y.copy(),
+          getDepth: scales.getDepth
+        };
+      }
+      savePrevScales();
+
+
+      // Returns a D3 selection of the cells that are within the plotting
+      // region, using a set of scales.
+      function selectActiveCells(scales) {
+        var xScale = scales.x;
+        var yScale = scales.y;
+        var depth = scales.getDepth;
+        var width = dims.width;
+        var height = dims.height;
+
+        var data = vis.prof.filter(function(d) {
+          var depthVal = depth(d);
+          return !(xScale(d.endTime)    < 0      ||
+                   xScale(d.startTime)  > width  ||
+                   depthVal           === null   ||
+                   yScale(depthVal - 1) < 0      ||
+                   yScale(depthVal)     > height);
+        });
+
+        cells = container.selectAll("g.cell").data(data, dataKey);
+
+        return cells;
+      }
+
+      // Given an enter selection, add the rect and text objects, but don't
+      // position them. Returns a selection of the new <g> elements.
+      // This should usually be called with addItems(sel.enter()) instead
+      // of sel.enter().call(addItems), because the latter returns the original
+      // enter selection, not the selection of <g> elements, and can't be
+      // used for chaining more function calls on the <g> selection.
+      function addItems(enterSelection) {
+        var cells = enterSelection.append("g")
+          .attr("class", "cell")
+          .classed("highlighted", function(d) { return d.filename !== null; })
+          .call(addMouseEventHandlers);
+
+        // Add CSS classes for highlighting cells with labels that match particular
+        // regex patterns.
+        var highlightPatterns = d3.entries(message.highlight);
+        highlightPatterns.map(function(item) {
+          var cssClass = item.key;
+          var regexp = new RegExp(item.value);
+
+          cells.classed(cssClass, function(d) {
+            return d.label.search(regexp) !== -1;
+          });
+        });
+
+        cells.append("rect")
+          .attr("class", "rect");
+
+        cells.append("text")
+          .attr("class", "profvis-label")
+          .text(function(d) { return d.label; });
+
+        return cells;
+      }
+
+      // Given a selection, position the rects and labels, using a set of
+      // scales.
+      function positionItems(cells, scales) {
+        var xScale = scales.x;
+        var yScale = scales.y;
+        var depth = scales.getDepth;
+
+        cells.select("rect")
+          .attr("width", function(d) {
+            return xScale(d.endTime) - xScale(d.startTime);
+          })
+          .attr("height", yScale(0) - yScale(1))
+          .attr("x", function(d) { return xScale(d.startTime); })
+          .attr("y", function(d) { return yScale(depth(d)); });
+
+        cells.select("text")
+          .attr("x", function(d) {
+            // To place the labels, check if there's enough space to fit the
+            // label plus padding in the rect. (We already know the label fits
+            // without padding if we got here.)
+            // * If there's not enough space, simply center the label in the
+            //   rect.
+            // * If there is enough space, keep the label within the rect, with
+            //   padding. Try to left-align, keeping the label within the
+            //   viewing area if possible.
+
+            // Padding on left and right
+            var pad = 2;
+
+            var textWidth = getLabelWidth(this, d.label.length);
+            var rectWidth = xScale(d.endTime) - xScale(d.startTime);
+
+            if (textWidth + pad*2 > rectWidth) {
+              return xScale(d.startTime) + (rectWidth - textWidth) / 2;
+            } else {
+              return Math.min(
+                Math.max(0, xScale(d.startTime)) + pad,
+                xScale(d.endTime) - textWidth - pad
+              );
+            }
+          })
+          .attr("y", function(d) { return yScale(depth(d) - 0.8); });
+
+        return cells;
+      }
+
+
+      // Redraw without a transition (regular panning and zooming)
+      function redrawImmediate() {
+        cells = selectActiveCells(scales);
+
+        cells.exit().remove();
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive());
+        cells.call(positionItems, scales);
+        cells.select('text')
+          .call(updateLabelVisibility);
+        svg.select(".x.axis").call(xAxis);
+      }
+
+      // Redraw for double-click zooming, where there's a transition
+      function redrawZoom(duration) {
+        // Figure out if we're zooming in or out. This will determine when we
+        // recalculate the label visibility: before or after the transition.
+        var prevExtent = prevScales.x.domain()[1] - prevScales.x.domain()[0];
+        var curExtent = scales.x.domain()[1] - scales.x.domain()[0];
+        var zoomIn = curExtent < prevExtent;
+
+        cells = selectActiveCells(scales);
+
+        // Phase 1
+        // Add the enter items, highlight them, and position them using the
+        // previous scales
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        // If zooming out, update label visibility. This will hide some labels
+        // now, before the transition, ensuring that they will never be larger
+        // than the box.
+        if (!zoomIn) {
+          cells.select('text')
+            .call(updateLabelVisibility);
+        }
+
+        // Phase 2
+        // Position the update (and enter) items using the new scales
+        cells
+          .transition().duration(duration)
+            .call(positionItems, scales);
+
+        // Position the exit items using the new scales
+        cells.exit()
+          .transition().duration(duration)
+            .call(positionItems, scales);
+
+        // Update x axis
+        svg.select(".x.axis")
+          .transition().duration(duration)
+            .call(xAxis);
+
+        // Phase 3
+        // If zooming in, update label visibility. This will hide some labels
+        // now, after the transition, ensuring that they will never be larger
+        // than the box.
+        if (zoomIn) {
+          cells.select('text')
+            .transition().delay(duration)
+            .call(updateLabelVisibility);
+        }
+
+        // Remove the exit items
+        cells.exit()
+          .transition().delay(duration)
+            .remove();
+      }
+
+      // Redraw when internal functions are hidden
+      function redrawCollapse(exitDuration, updateDuration) {
+        cells = selectActiveCells(scales);
+
+        // There are two subsets of the exit items:
+        //   1. Those that exit because depth is null. These should fade out.
+        //   2. Those that exit because they move off screen. These should wait
+        //      for subset 1 to fade out, then move with a transition.
+        var fadeOutCells = cells.exit()
+          .filter(function(d) { return scales.getDepth(d) === null; });
+        var moveOutCells = cells.exit()
+          .filter(function(d) { return scales.getDepth(d) !== null; });
+
+        // Phase 1
+        // Add the enter items, highlight them, and position them using the
+        // previous scales
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        cells.select('text')
+          .call(updateLabelVisibility);
+
+        // Phase 2
+        // Fade out the items that have a null depth
+        fadeOutCells
+          .transition().duration(exitDuration)
+            .style("opacity", 0);
+
+        // Phase 3
+        // Position the update (and enter) items using the new scales
+        cells
+          .transition().delay(exitDuration).duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Position the exit items that move out, using the new scales
+        moveOutCells
+          .transition().delay(exitDuration).duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Phase 4
+        // Remove all the exit items
+        cells.exit()
+          .transition().delay(exitDuration + updateDuration)
+          .remove();
+      }
+
+      // Redraw when internal functions are un-hidden
+      function redrawUncollapse(updateDuration, enterDuration) {
+        cells = selectActiveCells(scales);
+
+        var enterCells = addItems(cells.enter());
+        // There are two subsets of the enter items:
+        //   1. Those that enter because they move on screen (but the previous
+        //      depth was not null). These should move with a transition.
+        //   2. Those that enter because the previous depth was null. These
+        //      should wait for subset 1 to move, then fade in.
+        var moveInCells = enterCells
+          .filter(function(d) { return prevScales.getDepth(d) !== null; });
+        var fadeInCells = enterCells
+          .filter(function(d) { return prevScales.getDepth(d) === null; });
+
+        // Phase 1
+        // Highlight and position the move-in items with the old scales
+        moveInCells
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        cells.select('text')
+          .call(updateLabelVisibility);
+
+        // Phase 2
+        // Position the move-in, update, and exit items with a transition
+        moveInCells
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+        cells
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+        cells.exit()
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Phase 3
+        // Highlight and position the fade-in items, then fade in
+        fadeInCells
+            .call(addLockHighlightSelection, highlighter.currentLock())
+            .call(addActiveHighlightSelection, highlighter.currentActive())
+            .call(positionItems, scales)
+            .style("opacity", 0)
+          .transition().delay(updateDuration).duration(enterDuration)
+            .style("opacity", 1);
+
+        // Phase 4
+        // Remove the exit items
+        cells.exit()
+          .transition().delay(updateDuration + enterDuration)
+            .remove();
+      }
+
+
+      // Calculate whether to display label in each cell ----------------------
+
+      // Finding the dimensions of SVG elements is expensive. We'll reduce the
+      // calls getBoundingClientRect() by caching the dimensions.
+
+      // Cache the width of labels. This is a lookup table which, given the
+      // number of characters, gives the number of pixels. The label width
+      // never changes, so we can keep it outside of updateLabelVisibility().
+      var labelWidthTable = {};
+      function getLabelWidth(el, nchar) {
+        // Add entry if it doesn't already exist
+        if (labelWidthTable[nchar] === undefined) {
+          // If the text isn't displayed, then we can't get its width. Make
+          // sure it's visible, get the width, and then restore original
+          // display state.
+          var oldDisplay = el.style.display;
+          el.style.display = "inline";
+          labelWidthTable[nchar] = el.getBoundingClientRect().width;
+          el.style.display = oldDisplay;
+        }
+        return labelWidthTable[nchar];
+      }
+
+      // Show labels that fit in the corresponding rectangle, and hide others.
+      function updateLabelVisibility(labels) {
+        // Cache the width of rects. This is a lookup table which, given the
+        // timespan (width in data), gives the number of pixels. The width of
+        // rects changes with the x scale, so we have to rebuild the table each
+        // time the scale changes.
+        var rectWidthTable = {};
+        var x0 = scales.x(0);
+        function getRectWidth(time) {
+          // Add entry if it doesn't already exist
+          if (rectWidthTable[time] === undefined) {
+            rectWidthTable[time] = scales.x(time) - x0;
+          }
+          return rectWidthTable[time];
+        }
+
+        // Now calculate text and rect width for each cell.
+        labels.style("display", function(d) {
+          var labelWidth = getLabelWidth(this, d.label.length);
+          var boxWidth = getRectWidth(d.endTime - d.startTime);
+
+          return (labelWidth <= boxWidth) ? "" : "none";
+        });
+
+        return labels;
+      }
+
+
+      function onResize() {
+        updateContainerSize();
+
+        scales.x.range([0, dims.width]);
+        zoom.x(scales.x);
+
+        // Preserve distance from bottom, instead of from top (which is the
+        // default behavior).
+        scales.y.range([
+          dims.height,
+          dims.height - (domains.y[1] - domains.y[0]) * stackHeight
+        ]);
+        redrawImmediate();
+      }
+
+      // Attach mouse event handlers ------------------------------------
+      var dragging = false;
+
+      function addMouseEventHandlers(cells) {
+        cells
+          .on("mouseup", function(d) {
+            if (dragging) return;
+
+            // If it wasn't a drag, treat it as a click
+            vis.infoBox.show(d);
+            highlighter.click(d);
+            notifySourceFileMessage(d, "select");
+          })
+          .on("mouseover", function(d) {
+            if (dragging) return;
+
+            // If no label currently shown, display a tooltip
+            var label = this.querySelector(".profvis-label");
+            if (label.style.display === "none") {
+              var box = this.getBBox();
+              showTooltip(
+                d.label,
+                box.x + box.width / 2,
+                box.y - box.height
+              );
+            }
+
+            if (!highlighter.isLocked()) {
+              vis.infoBox.show(d);
+              highlighter.hover(d);
+            }
+          })
+          .on("mouseout", function(d) {
+            if (dragging) return;
+
+            hideTooltip();
+
+            if (!highlighter.isLocked()) {
+              vis.infoBox.hide();
+              highlighter.hover(null);
+            }
+          })
+          .on("dblclick.zoomcell", function(d) {
+            // When a cell is double-clicked, zoom x to that cell's width.
+            savePrevScales();
+
+            scales.x.domain(expandRange([d.startTime, d.endTime], zoomMargin));
+            zoom.x(scales.x);
+
+            redrawZoom(250);
+
+            notifySourceFileMessage(d, "open");
+          });
+
+        return cells;
+      }
+
+      // Tooltip --------------------------------------------------------
+      function showTooltip(label, x, y) {
+        var tooltip = container.append("g").attr("class", "profvis-tooltip");
+        var tooltipRect = tooltip.append("rect");
+        var tooltipLabel = tooltip.append("text")
+          .text(label)
+          .attr("x", x)
+          .attr("y", y + stackHeight * 0.2); // Shift down slightly for baseline
+
+        // Add box around label
+        var labelBox = tooltipLabel.node().getBBox();
+        var rectWidth = labelBox.width + 10;
+        var rectHeight = labelBox.height + 4;
+        tooltipRect
+          .attr("width", rectWidth)
+          .attr("height", rectHeight)
+          .attr("x", x - rectWidth / 2)
+          .attr("y", y - rectHeight / 2)
+          .attr("rx", 4)    // Rounded corners -- can't set this in CSS
+          .attr("ry", 4);
+      }
+
+      function hideTooltip() {
+        container.select("g.profvis-tooltip").remove();
+      }
+
+
+      // Highlighting ---------------------------------------------------------
+
+      function addLockHighlight(d) {
+        addLockHighlightSelection(cells, d);
+      }
+
+      function clearLockHighlight() {
+        cells
+          .filter(".locked")
+          .classed({ locked: false });
+      }
+
+
+      function addActiveHighlight(d) {
+        if (!d) return;
+        addActiveHighlightSelection(cells, d);
+      }
+
+      function clearActiveHighlight() {
+        cells
+          .filter(".active")
+          .classed({ active: false });
+      }
+
+      // These are versions of addLockHighlight and addActiveHighlight which
+      // are only internally visible. It must be passed a selection of cells to
+      // perform the highlighting on. This can be more efficient because it can
+      // operate on just an enter selection instead of all cells.
+      function addLockHighlightSelection(selection, d) {
+        if (!d) return;
+
+        var target = d;
+        selection
+          .filter(function(d) { return d === target; } )
+          .classed({ locked: true })
+          .call(moveToFront);
+      }
+
+      function addActiveHighlightSelection(selection, d) {
+        if (!d) return;
+
+        var target = d;
+        if (target.filename && target.linenum) {
+          selection
+            .filter(function(d) {
+              // Check for filename and linenum match, and if provided, a label match.
+              var match = d.filename === target.filename &&
+                          d.linenum === target.linenum;
+              if (!!target.label) {
+                match = match && (d.label === target.label);
+              }
+              return match;
+            })
+            .classed({ active: true });
+
+        } else if (target.label) {
+          // Don't highlight blocks for these labels
+          var exclusions = ["<Anonymous>", "FUN"];
+          if (exclusions.some(function(x) { return target.label === x; })) {
+            return;
+          }
+
+          // If we only have the label, search for cells that match, but make sure
+          // to not select ones that have a filename and linenum.
+          selection
+            .filter(function(d) {
+              return d.label === target.label &&
+                     d.filename === null &&
+                     d.linenum === null;
+            })
+            .classed({ active: true });
+        }
+      }
+
+      // Move a D3 selection to front. If this is called on a selection, that
+      // selection should have been created with a data indexing function (e.g.
+      // data(data, function(d) { return ... })). Otherwise, the wrong object
+      // may be moved to the front.
+      function moveToFront(selection) {
+        return selection.each(function() {
+          this.parentNode.appendChild(this);
+        });
+      }
+
+
+      // Panning and zooming --------------------------------------------
+      // For panning and zooming x, d3.behavior.zoom does most of what we want
+      // automatically. For panning y, we can't use d3.behavior.zoom becuase it
+      // will also automatically add zooming, which we don't want. Instead, we
+      // need to use d3.behavior.drag and set the y domain appropriately.
+      var drag = d3.behavior.drag()
+        .on("drag", function() {
+          dragging = true;
+          var y = scales.y;
+          var ydom = y.domain();
+          var ydiff = y.invert(d3.event.dy) - y.invert(0);
+          y.domain([ydom[0] - ydiff, ydom[1] - ydiff]);
+        });
+
+
+      // For mousewheel zooming, we need to limit zoom amount. This is needed
+      // because in Firefox, zoom increments are too big. To do this, we limit
+      // scaleExtent before the first zoom event, and after each subsequent
+      // one.
+      //
+      // When zooming out, there's an additional limit: never zoom out past
+      // the original zoom span. The reason it's necessary to calculate this
+      // each time, instead of simply setting the scaleExtent() so that the
+      // lower bound is 1, is because other zoom events (like
+      // dblclick.zoomcell) are able to change the domain of scales.x, without
+      // changing the value of zoom.scale(). This means that the relationship
+      // between the zoom.scale() does not have a fixed linear relationship to
+      // the span of scales.x, and we have to recalculate it.
+      var maxZoomPerStep = 1.1;
+
+      function zoomOutLimit() {
+        var span = scales.x.domain()[1] - scales.x.domain()[0];
+        var startSpan = domains.x[1] - domains.x[0];
+        return Math.min(maxZoomPerStep, startSpan/span);
+      }
+
+      var zoom = d3.behavior.zoom()
+        .x(scales.x)
+        .on("zoomstart", function() {
+          zoom.scaleExtent([zoom.scale() / zoomOutLimit(), zoom.scale() * maxZoomPerStep]);
+        })
+        .on("zoom", function(e) {
+          redrawImmediate();
+          zoom.scaleExtent([zoom.scale() / zoomOutLimit(), zoom.scale() * maxZoomPerStep]);
+        });
+
+      // Register drag before zooming, because we need the drag to set the y
+      // scale before the zoom triggers a redraw.
+      svg
+        .on("mouseup", function(d) {
+          dragging = false;
+        })
+        .call(drag);
+
+      // Unlock selection when background is clicked, and zoom out when
+      // background is double-clicked.
+      backgroundRect
+        .on("mouseup", function(d) {
+          if (dragging) return;
+
+          // If it wasn't a drag, hide info box and unlock.
+          vis.infoBox.hide();
+          highlighter.click(null);
+        })
+        .on("dblclick.zoombackground", function() {
+          savePrevScales();
+
+          scales.x.domain(domains.x);
+          zoom.x(scales.x);
+
+          redrawZoom(250);
+        });
+
+
+      var zoomEnabled = false;
+      function disableZoom() {
+        if (zoomEnabled) {
+          svg.on(".zoom", null);
+          zoomEnabled = false;
+        }
+      }
+      function enableZoom() {
+        if (!zoomEnabled) {
+          svg
+            .call(zoom)
+            .on("dblclick.zoom", null); // Disable zoom's built-in double-click behavior
+          zoomEnabled = true;
+        }
+      }
+      enableZoom();
+
+      onResize();
+
+      return {
+        el: el,
+        onResize: onResize,
+        onUpdateInternals: onResize,
+        redrawImmediate: redrawImmediate,
+        redrawZoom: redrawZoom,
+        redrawCollapse: redrawCollapse,
+        redrawUncollapse: redrawUncollapse,
+        savePrevScales: savePrevScales,
+        useCollapsedDepth: useCollapsedDepth,
+        useUncollapsedDepth: useUncollapsedDepth,
+        addLockHighlight: addLockHighlight,
+        clearLockHighlight: clearLockHighlight,
+        addActiveHighlight: addActiveHighlight,
+        clearActiveHighlight: clearActiveHighlight,
+        disableZoom: disableZoom,
+        enableZoom: enableZoom
+      };
+    } // generateFlameGraph
+
+
+    function initInfoBox(el) {
+
+      function show(d) {
+        var label = d.label ? d.label : "";
+        var ref = (d.filename && d.linenum) ?
+          (d.filename + "#" + d.linenum) :
+          "(source unavailable)";
+
+        el.style.visibility = "";
+
+        el.innerHTML =
+          "<table>" +
+          "<tr><td class='infobox-title'>Label</td><td>" + escapeHTML(label) + "</td></tr>" +
+          "<tr><td class='infobox-title'>Called from</td><td>" + escapeHTML(ref) + "</td></tr>" +
+          "<tr><td class='infobox-title'>Total time</td><td>" + (d.endTime - d.startTime) + "ms</td></tr>" +
+          "<tr><td class='infobox-title'>Memory</td><td>" +
+            roundOneDecimal(d.sumMemDealloc) + " / " + roundOneDecimal(d.sumMemAlloc) +
+            " MB</td></tr>" +
+          "<tr><td class='infobox-title'>Agg. total time</td><td>" + vis.aggLabelTimes[label] + "ms</td></tr>" +
+          "<tr><td class='infobox-title'>Call stack depth</td><td>" + d.depth + "</td></tr>" +
+          "</table>";
+      }
+
+      function hide() {
+        el.style.visibility = "hidden";
+      }
+
+      hide();
+
+      return {
+        el: el,
+        show: show,
+        hide: hide
+      };
+    }
+
+    // Generate the tree table ----------------------------------------
+    function generateTreetable(el) {
+      var content = d3.select(el);
+
+      var table = content.append("table")
+          .attr("class", "results")
+          .attr("cellspacing", "0")
+          .attr("cellpadding", "0");
+
+      table.append("col");
+      table.append("col")
+        .style("width", "120px");
+      table.append("col")
+        .style("width", "50px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "26px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "50px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "50px");
+      table.append("col")
+        .style("width", "40px");
+
+      var tableBody = table.append("tbody");
+
+      var headerRows = tableBody.append("tr");
+
+      headerRows.append("th")
+        .attr("class", "code-label")
+        .text("Code");
+
+      headerRows.append("th")
+        .attr("class", "path")
+        .text("File");
+
+      headerRows.append("th")
+        .attr("class", "treetable-memory memory")
+        .attr("colspan", "3")
+        .text("Memory (MB)");
+
+      headerRows.append("th")
+        .attr("class", "time")
+        .attr("colspan", "2")
+        .text("Time (ms)");
+
+      // Retrieve all nodes (n), recursevely, where check(n) == true.
+      function allTopNodes(nodes, check) {
+        var included = [];
+        nodes = nodes.slice();
+
+        while (nodes.length > 0) {
+          var node = nodes.shift();
+
+          if (check(node))
+            included.push(node);
+          else {
+            node.sumChildren.forEach(function(c1) {
+              nodes.unshift(c1);
+            });
+          }
+        }
+        return included;
+      }
+
+      // Is there one node (n), including root, where check(n) == true?
+      function oneNode(root, check) {
+        var nodes = [root];
+
+        while (nodes.length > 0) {
+          var n = nodes.shift();
+          if (check(n))
+            return true;
+
+          n.sumChildren.forEach(function(x) {
+            nodes.unshift(x);
+          });
+        }
+
+        return false;
+      }
+
+      function updateRowsDisplay(d) {
+        if (vis.hideInternals && d.isInternal)
+          return "none";
+        else if (!vis.hideInternals && d.isDescendant)
+          return "none";
+
+        var collapsed = false;
+        while (d.parent) {
+          d = d.parent;
+          if (d.collapsed) {
+            collapsed = true;
+            break;
+          }
+        }
+        return collapsed ? "none" : "";
+      }
+
+      function toggleTreeNode(d) {
+        if (!d.canExpand)
+          return;
+
+        var collapsed = d.collapsed;
+        if (collapsed === undefined) {
+          // Create a copy since we might insert the same node twice: once
+          // for the normal leaf the other one for a collapsed node.
+          var sumChildren = d.sumChildren.map(function(x) {
+            return jQuery.extend({}, x);
+          });
+
+          var childNodes = sumChildren.filter(function(x) {
+            return x.depthCollapsed !== null;
+          });
+
+          childNodes.forEach(function(x) {
+            x.isInternal = d.isInternal ? d.isInternal : false;
+            x.isDescendant = d.isDescendant ? d.isDescendant : false;
+          });
+
+          var internalChildNodes = sumChildren.filter(function(x) {
+            return x.depthCollapsed === null;
+          });
+
+          internalChildNodes.forEach(function(x) {
+            x.isInternal = true;
+            x.isDescendant = false;
+          });
+
+          var notInternalDescendantNodes = [];
+          if (!d.isInternal) {
+            notInternalDescendantNodes = allTopNodes(internalChildNodes, function(x) {
+              return x.depthCollapsed !== null && d.depth < x.depth;
+            });
+          }
+
+          notInternalDescendantNodes.forEach(function(x) {
+            x.isInternal = false;
+            x.isDescendant = true;
+          });
+
+          childNodes = childNodes.concat(internalChildNodes);
+          childNodes = childNodes.concat(notInternalDescendantNodes);
+
+          childNodes.forEach(function(n) {
+            n.visualDepth = d.visualDepth + 1;
+            n.parent = d;
+          });
+
+          vis.profTable = vis.profTable.concat(childNodes);
+          d.collapsed = false;
+
+          updateRows();
+
+          // Nodes are sorted "heaviest first"
+          if (childNodes.length == 1) toggleTreeNode(childNodes[0]);
+        }
+        else {
+          d.collapsed = !collapsed;
+          updateRows();
+        }
+      }
+
+      function updateLabelCells(labelCell) {
+        labelCell
+          .attr("nowrap", "true")
+          .style("padding-left", function(d) {
+            return (8 + 15 * (d.visualDepth - 1)) + "px";
+          })
+          .on("click", toggleTreeNode)
+          .attr("class", function(d) {
+            d.canExpand = false;
+            if (d.sumChildren) {
+              d.sumChildren.forEach(function(c) {
+                if (c.sumChildren.length > 0) {
+                  if (!vis.hideInternals || oneNode(c, function(c1) { return c1.depthCollapsed !== null; }))
+                    d.canExpand = true;
+                }
+              });
+            }
+
+            var collapsedClass = "";
+            if (d.canExpand)
+              collapsedClass = d.collapsed === undefined ? "treetable-expand" : d.collapsed ? "treetable-expand" : "treetable-collapse";
+
+            return "code-label " + (d.canExpand ? "label-pointer " + collapsedClass : "");
+          });
+      }
+
+      function updateRows() {
+        var rows = tableBody.selectAll("tr.treetable-row")
+          .data(vis.profTable, function(d) {
+            return d.id;
+          });
+
+        rows.exit()
+          .remove();
+
+        var updatedRows = rows
+          .style("display", updateRowsDisplay);
+
+        var updatedLabelCells = updatedRows.selectAll("td.code-label");
+        updateLabelCells(updatedLabelCells);
+
+        var newRows = rows.enter()
+          .append("tr")
+          .filter(function(d) {
+            if (vis.hideInternals && d.depthCollapsed === null)
+              return false;
+
+            return true;
+          })
+          .on("click", function(d) {
+            table.selectAll("tr")
+              .style("background-color", null);
+
+            this.style.backgroundColor = "rgb(241, 241, 241)";
+            notifySourceFileMessage(d, "select");
+          })
+          .style("display", updateRowsDisplay);
+
+        newRows
+          .attr("class", "treetable-row");
+
+        var labelCell = newRows.append("td");
+        updateLabelCells(labelCell);
+
+        var cellWrapper = labelCell.append("div");
+        cellWrapper.append("div");
+
+        labelCell.append("div")
+          .attr("class", "label-text")
+          .text(function(d) { return d.label; });
+
+        newRows.append("td")
+          .attr("class", "path")
+          .text(function(d) {
+            var lastSlash = d.filename ? d.filename.lastIndexOf("/") : -1;
+            if (lastSlash >= 0)
+              return d.filename.substr(lastSlash + 1);
+
+            return d.filename;
+          });
+
+        newRows.append("td")
+          .attr("class", "treetable-memory memory-info")
+          .text(function(d) {
+            return roundOneDecimal(d.sumMemDealloc);
+          });
+
+        var memoryBarContainer = newRows.append("td")
+          .attr("class", "treetable-memory memory-bar-container");
+
+        var memoryLeftCell = memoryBarContainer.append("div")
+          .attr("class", "memory-leftbar-wrapper");
+
+        memoryLeftCell.append("div")
+          .attr("class", "memory-leftbar")
+          .style("width", function(d) {
+            return  1 + Math.min(Math.abs(Math.min(Math.round(d.propMemDealloc * 5), 0)), 5) + "px";
+          });
+
+        memoryBarContainer.append("div")
+          .attr("class", "memory-rightbar")
+          .style("width", function(d) {
+            return 1 + Math.min(Math.max(Math.round(d.propMemAlloc * 13), 0), 13) + "px";
+          });
+
+        newRows.append("td")
+          .attr("class", "treetable-memory memory-info-right")
+          .text(function(d) {
+            return roundOneDecimal(d.sumMemAlloc);
+          });
+
+        newRows.append("td")
+          .attr("class", "time-info")
+          .text(function(d) {
+            return d.sumTime;
+          });
+
+        var timeCell = newRows.append("td")
+          .attr("class", "time-bar-container");
+
+        timeCell.append("div")
+          .attr("class", "timebar")
+          .style("width", function(d) {
+            return Math.round(d.propTime * 20) + "px";
+          });
+
+        var unorderedRows = d3.selectAll("tr.treetable-row")
+          .data(vis.profTable, function(d) {
+            return d.id;
+          });
+
+        unorderedRows.sort(function(a,b) {
+          return (a.id < b.id) ? -1 : (a.id == b.id ? 0 : 1);
+        });
+
+        useMemoryResults();
+      }
+
+      var buildProfTable = function (profTree) {
+        var head = jQuery.extend({}, profTree);
+        var nodes = [head];
+
+        var aggregateChildren = function(node) {
+          var nameMap = {};
+          node.children.forEach(function(c) {
+            var nameMapEntry = nameMap[c.label];
+            if (!nameMapEntry) {
+              nameMapEntry = jQuery.extend({}, c);
+              nameMapEntry.sumTime     = c.endTime - c.startTime;
+              nameMapEntry.sumChildren = [];
+              nameMapEntry.children    = [];
+              nameMapEntry.parent      = node;
+              nameMapEntry.sumCount    = 1;
+            }
+            else {
+              nameMapEntry.sumMem        = nameMapEntry.sumMem        + c.sumMem;
+              nameMapEntry.sumMemDealloc = nameMapEntry.sumMemDealloc + c.sumMemDealloc;
+              nameMapEntry.sumMemAlloc   = nameMapEntry.sumMemAlloc   + c.sumMemAlloc;
+              nameMapEntry.sumTime       = nameMapEntry.sumTime       + (c.endTime - c.startTime);
+              nameMapEntry.sumCount      = nameMapEntry.sumCount      + 1;
+            }
+
+            nameMapEntry.propMem        = nameMapEntry.sumMem        / vis.totalMem;
+            nameMapEntry.propMemDealloc = nameMapEntry.sumMemDealloc / vis.totalMem;
+            nameMapEntry.propMemAlloc   = nameMapEntry.sumMemAlloc   / vis.totalMem;
+            nameMapEntry.propTime       = nameMapEntry.sumTime       / vis.totalTime;
+
+            c.children.forEach(function(e) {
+              nameMapEntry.children.push(e);
+            });
+
+            nameMap[c.label] = nameMapEntry;
+          });
+
+          var childrenSum = [];
+          for (var label in nameMap) {
+            childrenSum.push(nameMap[label]);
+          }
+
+          // Sort by time descending
+          childrenSum.sort(function(a, b) { return b.sumTime - a.sumTime });
+          return childrenSum;
+        };
+
+        function addToNodesAt(c, i) {
+          nodes.splice(i, 0, c);
+        }
+
+        var id = 0;
+        while (nodes.length > 0) {
+          var node = nodes.shift();
+
+          node.id = id;
+          id = id + 1;
+
+          node.sumChildren = aggregateChildren(node);
+
+          // Processing in order is important to preserve order of IDs!
+          node.sumChildren.forEach(addToNodesAt);
+        }
+
+        return head.sumChildren;
+      };
+
+      function useMemoryResults() {
+        d3.selectAll(".treetable-memory").style("display", vis.hideMemory ? "none" : "");
+      }
+
+      vis.profTable = buildProfTable(vis.profTree);
+      vis.profTable.forEach(function(e) {
+        e.visualDepth = 1;
+      });
+
+      updateRows();
+
+      return {
+        el: el,
+        onResize: updateRows,
+        onOptionsChange: updateRows,
+        onUpdateInternals: function() {
+
+        },
+        useMemoryResults: useMemoryResults
+      };
+    }
+
+    function enableScroll() {
+      vis.codeTable.enableScroll();
+      vis.flameGraph.enableZoom();
+    }
+
+    function disableScroll() {
+      vis.codeTable.disableScroll();
+      vis.flameGraph.disableZoom();
+    }
+
+
+    // Set up resizing --------------------------------------------------------
+
+    // This is used as a jQuery event namespace so that we can remove the window
+    // resize handler on subsequent calls to initResizing(). Not elegant, but it
+    // gets the job done.
+    var resizeCallbackNamespace = randomString(10);
+
+    // Resize panel1 and panel2 to 50% of available space and add callback
+    // for window resizing.
+    function initResizing() {
+      var $el = $(vis.el);
+      var $panel1 = $el.children(".profvis-panel1");
+      var $panel2 = $el.children(".profvis-panel2");
+      var $splitBar = $el.children(".profvis-splitbar");
+      var $statusBar = $el.children(".profvis-status-bar");
+
+      // Clear any existing positioning that may have happened from previous
+      // calls to this function and the callbacks that it sets up.
+      $panel1.removeAttr("style");
+      $panel2.removeAttr("style");
+      $splitBar.removeAttr("style");
+      $statusBar.removeAttr("style");
+
+      // CSS class suffix for split direction
+      var splitClass = (vis.splitDir === "h") ? "horizontal" : "vertical";
+
+      // Remove existing horizontal/vertical class and add the correct class back.
+      $panel1.removeClass("profvis-panel1-horizontal profvis-panel1-vertical");
+      $panel2.removeClass("profvis-panel2-horizontal profvis-panel2-vertical");
+      $splitBar.removeClass("profvis-splitbar-horizontal profvis-splitbar-vertical");
+      $panel1.addClass("profvis-panel1-" + splitClass);
+      $panel2.addClass("profvis-panel2-" + splitClass);
+      $splitBar.addClass("profvis-splitbar-" + splitClass);
+
+
+      var splitBarGap;
+      var margin;
+      // Record the proportions from the previous call to resizePanels. This is
+      // needed when we resize the window to preserve the same proportions.
+      var lastSplitProportion;
+
+      if (vis.splitDir === "v") {
+        // Record the gap between the split bar and the objects to left and right
+        splitBarGap = {
+          left: $splitBar.offset().left - offsetRight($panel1),
+          right: $panel2.offset().left - offsetRight($splitBar)
+        };
+
+        // Capture the initial distance from the left and right of container element
+        margin = {
+          left: $panel1.position().left,
+          right: $el.innerWidth() - positionRight($panel2)
+        };
+
+      } else if (vis.splitDir === "h") {
+        splitBarGap = {
+          top: $splitBar.offset().top - offsetBottom($panel1),
+          bottom: $panel2.offset().top - offsetBottom($splitBar)
+        };
+
+        margin = {
+          top: $panel1.position().top,
+          bottom: $el.innerWidth() - positionBottom($panel2)
+        };
+      }
+
+      // Resize the panels. splitProportion is a number from 0-1 representing the
+      // horizontal position of the split bar.
+      function resizePanels(splitProportion) {
+        if (!splitProportion)
+          splitProportion = lastSplitProportion;
+
+        if (vis.splitDir === "v") {
+          var innerWidth = offsetRight($panel2) - $panel1.offset().left;
+
+          $splitBar.offset({
+            left: $panel1.offset().left + innerWidth * splitProportion -
+                  $splitBar.outerWidth()/2
+          });
+
+          // Size and position the panels
+          $panel1.outerWidth($splitBar.position().left - splitBarGap.left -
+                             margin.left);
+          $panel2.offset({ left: offsetRight($splitBar) + splitBarGap.right });
+
+        } else if (vis.splitDir === "h") {
+          var innerHeight = offsetBottom($panel2) - $panel1.offset().top;
+
+          $splitBar.offset({
+            top: $panel1.offset().top + innerHeight * splitProportion -
+                 $splitBar.outerHeight()/2
+          });
+
+          // Size and position the panels
+          $panel1.outerHeight($splitBar.position().top - splitBarGap.top -
+                             margin.top);
+          $panel2.offset({ top: offsetBottom($splitBar) + splitBarGap.bottom });
+        }
+
+        lastSplitProportion = splitProportion;
+      }
+
+      // Initially, set widths to 50/50
+      // For the first sizing, we don't need to call vis.flameGraph.onResize()
+      // because this happens before the flame graph is generated.
+      resizePanels(0.5);
+
+      var resizePanelsDebounced = debounce(function() {
+        resizePanels(lastSplitProportion);
+        vis.activeViews.forEach(function(e) {
+          if (e.onResize) e.onResize();
+        });
+      }, 250);
+
+      // Clear old resize handler and add new one. We use a namespace for this
+      // visualization to make sure not to delete handlers for other profvis
+      // visualizations on the same page (this can happen with Rmd documents).
+      $(window).off("resize.profvis." + resizeCallbackNamespace);
+      $(window).on("resize.profvis." + resizeCallbackNamespace, resizePanelsDebounced);
+
+      // Get current proportional position of split bar
+      function splitProportion() {
+        var splitCenter;
+
+        if (vis.splitDir === "v") {
+          splitCenter = $splitBar.offset().left - $panel1.offset().left +
+                            $splitBar.outerWidth()/2;
+          var innerWidth = offsetRight($panel2) - $panel1.offset().left;
+          return splitCenter / innerWidth;
+
+        } else if (vis.splitDir === "h") {
+          splitCenter = $splitBar.offset().top - $panel1.offset().top +
+                            $splitBar.outerHeight()/2;
+          var innerHeight = offsetBottom($panel2) - $panel1.offset().top;
+          return splitCenter / innerHeight;
+        }
+      }
+
+      function positionRight($el) {
+        return $el.position().left + $el.outerWidth();
+      }
+      function offsetRight($el) {
+        return $el.offset().left + $el.outerWidth();
+      }
+      function positionBottom($el) {
+        return $el.position().top + $el.outerHeight();
+      }
+      function offsetBottom($el) {
+        return $el.offset().top + $el.outerHeight();
+      }
+
+      // Enable dragging of the split bar ---------------------------------------
+      (function() {
+        var dragging = false;
+        // For vertical split (left-right dragging)
+        var startDragX;
+        var startOffsetLeft;
+        // For horizontal split (up-down dragging)
+        var startDragY;
+        var startOffsetTop;
+
+        var stopDrag = function(e) {
+          if (!dragging) return;
+          dragging = false;
+
+          document.removeEventListener("mousemove", drag);
+          document.removeEventListener("mouseup", stopDrag);
+
+          $splitBar.css("opacity", "");
+
+          if ((vis.splitDir === "v" && e.pageX - startDragX === 0) ||
+              (vis.splitDir === "h" && e.pageY - startDragY === 0)) {
+            return;
+          }
+
+          resizePanels(splitProportion());
+          vis.flameGraph.onResize();
+        };
+
+        var startDrag = function(e) {
+          // Don't start another drag if we're already in one.
+          if (dragging) return;
+          dragging = true;
+          pauseEvent(e);
+
+          $splitBar.css("opacity", 0.75);
+
+          if (vis.splitDir === "v") {
+            startDragX = e.pageX;
+            startOffsetLeft = $splitBar.offset().left;
+          } else {
+            startDragY = e.pageY;
+            startOffsetTop = $splitBar.offset().top;
+          }
+
+          document.addEventListener("mousemove", drag);
+          document.addEventListener("mouseup", stopDrag);
+        };
+
+        var drag = function(e) {
+          if (!dragging) return;
+          pauseEvent(e);
+
+          if (vis.splitDir === "v") {
+            var dx = e.pageX - startDragX;
+            if (dx === 0)
+              return;
+
+            // Move the split bar
+            $splitBar.offset({ left: startOffsetLeft + dx });
+
+          } else if (vis.splitDir === "h") {
+            var dy = e.pageY - startDragY;
+            if (dy === 0)
+              return;
+
+            // Move the split bar
+            $splitBar.offset({ top: startOffsetTop + dy });
+          }
+        };
+
+        // Stop propogation so that we don't select text while dragging
+        function pauseEvent(e){
+          if(e.stopPropagation) e.stopPropagation();
+          if(e.preventDefault) e.preventDefault();
+          e.cancelBubble = true;
+          e.returnValue = false;
+          return false;
+        }
+
+        // Remove existing event listener from previous calls to initResizing().
+        $splitBar.off("mousedown.profvis");
+        $splitBar.on("mousedown.profvis", startDrag);
+      })();
+
+
+      return {
+        resizePanels: resizePanels
+      };
+    }
+
+
+    var prof = prepareProfData(message.prof, message.interval);
+
+    var vis = {
+      el: el,
+      prof: prof,
+      profTree: getProfTree(prof),
+      interval: message.interval,
+      totalTime: getTotalTime(prof),
+      totalMem: getTotalMemory(prof),
+      files: message.files,
+      aggLabelTimes: getAggregatedLabelTimes(prof),
+      fileLineStats: getFileLineStats(prof, message.files),
+      profTable: [],
+
+      // Objects representing each component
+      statusBar: null,
+      optionsPanel: null,
+      codeTable: null,
+      flameGraph: null,
+      infoBox: null,
+      treetable: null,
+      activeViews: [],
+
+      // Functions to enable/disable responding to scrollwheel events
+      enableScroll: enableScroll,
+      disableScroll: disableScroll,
+
+      splitDir: message.split,
+      hideInternals: true,
+      hideMemory: false,
+
+      resizePanels: null
+    };
+
+
+    // Render the objects ---------------------------------------------
+
+    var statusBarEl = document.createElement("div");
+    statusBarEl.className = "profvis-status-bar";
+    vis.el.appendChild(statusBarEl);
+
+    // Container panels - top/bottom or left/right
+    var panel1 = document.createElement("div");
+    panel1.className = "profvis-panel1";
+    vis.el.appendChild(panel1);
+
+    var panel2 = document.createElement("div");
+    panel2.className = "profvis-panel2";
+    vis.el.appendChild(panel2);
+
+    var splitBarEl = document.createElement("div");
+    splitBarEl.className = "profvis-splitbar";
+    vis.el.appendChild(splitBarEl);
+
+    var footerEl = document.createElement("div");
+    footerEl.className = "profvis-footer";
+    vis.el.appendChild(footerEl);
+
+    // Items in the panels
+    var codeTableEl = document.createElement("div");
+    codeTableEl.className = "profvis-code";
+    panel1.appendChild(codeTableEl);
+
+    var flameGraphEl = document.createElement("div");
+    flameGraphEl.className = "profvis-flamegraph";
+    panel2.appendChild(flameGraphEl);
+
+    var infoBoxEl = document.createElement("div");
+    infoBoxEl.className = "profvis-infobox";
+    panel2.appendChild(infoBoxEl);
+
+    var treetableEl = document.createElement("div");
+    treetableEl.className = "profvis-treetable";
+    treetableEl.style.display = "none";
+    vis.el.appendChild(treetableEl);
+
+    var optionsPanelEl = document.createElement("div");
+    optionsPanelEl.className = "profvis-options-panel";
+    vis.el.appendChild(optionsPanelEl);
+
+    // Efficient to properly size panels before the code + flamegraph are
+    // rendered, so that we don't have to re-render.
+    var resize = initResizing();
+    vis.resizePanels = resize.resizePanels;
+
+    var hideViews = function() {
+      splitBarEl.style.display = "none";
+      panel1.style.display = "none";
+      panel2.style.display = "none";
+      treetableEl.style.display = "none";
+    };
+
+    var toggleViews = function(view) {
+      hideViews();
+
+      switch (view) {
+        case "flamegraph":
+          splitBarEl.style.display = "block";
+          panel1.style.display = "block";
+          panel2.style.display = "block";
+
+          vis.activeViews = [vis.flameGraph, vis.codeTable];
+          vis.resizePanels();
+          break;
+        case "treetable":
+          if (!vis.treetable) {
+            vis.treetable = generateTreetable(treetableEl);
+          }
+
+          treetableEl.style.display = "block";
+
+          vis.activeViews = [vis.treetable];
+          break;
+      }
+
+      vis.activeViews.forEach(function(e) {
+        if (e.onResize) e.onResize();
+      });
+    };
+
+    var onOptionsChange = function(option, checked) {
+      switch (option)
+      {
+        case "split": {
+          vis.splitDir = checked ? "h" : "v";
+          // Check that flame graph is visible
+          if ($.inArray(vis.flameGraph, vis.activeViews) !== -1) {
+            initResizing();
+            vis.flameGraph.onResize();
+          }
+          break;
+        }
+        case "internals": {
+          vis.flameGraph.savePrevScales();
+
+          vis.hideInternals = checked;
+          if (checked) {
+            vis.flameGraph.useCollapsedDepth();
+            vis.flameGraph.redrawCollapse(400, 400);
+          } else {
+            vis.flameGraph.useUncollapsedDepth();
+            vis.flameGraph.redrawUncollapse(400, 250);
+          }
+
+          vis.activeViews.forEach(function(e) {
+            if (e.onOptionsChange) e.onOptionsChange();
+          });
+
+          break;
+        }
+        case "memory": {
+          vis.hideMemory = checked;
+          vis.activeViews.forEach(function(e) {
+            if (e.useMemoryResults) e.useMemoryResults();
+          });
+          break;
+        }
+      }
+    };
+
+    // Create the UI components
+    vis.statusBar = generateStatusBar(statusBarEl, toggleViews);
+    vis.footer = generateFooter(footerEl);
+    vis.optionsPanel = generateOptionsPanel(optionsPanelEl, onOptionsChange);
+    vis.codeTable = generateCodeTable(codeTableEl);
+    vis.flameGraph = generateFlameGraph(flameGraphEl);
+    vis.infoBox = initInfoBox(infoBoxEl);
+    vis.treetable = null;
+    vis.activeViews = [vis.flameGraph, vis.codeTable];
+
+    // If any depth collapsing occured, enable the "hide internal" checkbox.
+    if (prof.some(function(d) { return d.depth !== d.depthCollapsed; })) {
+      vis.optionsPanel.enableHideInternal();
+    }
+
+    // Start with scrolling disabled because of mousewheel scrolling issue
+    disableScroll();
+
+    // Make the vis object accessible via the DOM element
+    $(el).data("profvis", vis);
+
+    return vis;
+  };  // profvis.render()
+
+  // Calculate amount of time spent on each line of code. Returns nested objects
+  // grouped by file, and then by line number.
+  function getFileLineStats(prof, files) {
+    // Drop entries with null or "" filename
+    prof = prof.filter(function(row) {
+      return row.filename !== null && row.filename !== "";
+    });
+
+    // Gather line-by-line file contents
+    var fileLineStats = files.map(function(file) {
+      // Create array of objects with info for each line of code.
+      var lines = file.content.split("\n");
+      var lineData = [];
+      var filename = file.filename;
+      var normpath = file.normpath;
+      for (var i=0; i<lines.length; i++) {
+        lineData[i] = {
+          filename: filename,
+          normpath: normpath,
+          linenum: i + 1,
+          content: lines[i],
+          sumTime: 0,
+          sumMem: 0,
+          sumMemAlloc: 0,
+          sumMemDealloc: 0
+        };
+      }
+
+      return {
+        filename: filename,
+        lineData: lineData
+      };
+    });
+
+    // Get timing data for each line
+    var statsData = d3.nest()
+      .key(function(d) { return d.filename; })
+      .key(function(d) { return d.linenum; })
+      .rollup(function(leaves) {
+        var sumTime = leaves.reduce(function(sum, d) {
+          // Add this node's time only if no ancestor node has the same
+          // filename and linenum. This is to avoid double-counting times for
+          // a line.
+          var incTime = 0;
+          if (!ancestorHasFilenameLinenum(d.filename, d.linenum, d.parent)) {
+            incTime = d.endTime - d.startTime;
+          }
+          return sum + incTime;
+        }, 0);
+
+        var sumMem = leaves.reduce(function(sum, d) {
+          return sum + d.sumMem;
+        }, 0);
+
+        var sumMemDealloc = leaves.reduce(function(sum, d) {
+          return sum + d.sumMemDealloc;
+        }, 0);
+
+        var sumMemAlloc = leaves.reduce(function(sum, d) {
+          return sum + d.sumMemAlloc;
+        }, 0);
+
+        return {
+          filename: leaves[0].filename,
+          linenum: leaves[0].linenum,
+          sumTime: sumTime,
+          sumMem: sumMem,
+          sumMemAlloc: sumMemAlloc,
+          sumMemDealloc: sumMemDealloc
+        };
+      })
+      .entries(prof);
+
+    // Insert the sumTimes into line content data
+    statsData.forEach(function(fileInfo) {
+      // Find item in fileTimes that matches the file of this fileInfo object
+      var fileLineData = fileLineStats.filter(function(d) {
+        return d.filename === fileInfo.key;
+      })[0].lineData;
+
+      fileInfo.values.forEach(function(lineInfo) {
+        lineInfo = lineInfo.values;
+        fileLineData[lineInfo.linenum - 1].sumTime = lineInfo.sumTime;
+        fileLineData[lineInfo.linenum - 1].sumMem = lineInfo.sumMem;
+        fileLineData[lineInfo.linenum - 1].sumMemDealloc = lineInfo.sumMemDealloc;
+        fileLineData[lineInfo.linenum - 1].sumMemAlloc = lineInfo.sumMemAlloc;
+      });
+    });
+
+    // Calculate proportional times, relative to the longest time in the data
+    // set. Modifies data in place.
+    var fileMaxTimes = fileLineStats.map(function(lines) {
+      var lineTimes = lines.lineData.map(function(x) { return x.sumTime; });
+      return d3.max(lineTimes);
+    });
+
+    var maxTime = d3.max(fileMaxTimes);
+
+    fileLineStats.map(function(lines) {
+      lines.lineData.map(function(line) {
+        line.propTime = line.sumTime / maxTime;
+      });
+    });
+
+    var totalMem = getTotalMemory(prof);
+
+    fileLineStats.map(function(lines) {
+      lines.lineData.map(function(line) {
+        line.propMem = line.sumMem / totalMem;
+        line.propMemDealloc = line.sumMemDealloc / totalMem;
+        line.propMemAlloc = line.sumMemAlloc / totalMem;
+      });
+    });
+
+    return fileLineStats;
+
+    // Returns true if the given node or one of its ancestors has the given
+    // filename and linenum; false otherwise.
+    function ancestorHasFilenameLinenum(filename, linenum, node) {
+      if (!node) {
+        return false;
+      }
+      if (node.filename === filename && node.linenum === linenum) {
+        return true;
+      }
+      return ancestorHasFilenameLinenum(filename, linenum, node.parent);
+    }
+  }
+
+  function prepareProfData(prof, interval) {
+    // Convert object-with-arrays format prof data to array-of-objects format
+    var data = colToRows(prof);
+    data = addParentChildLinks(data);
+    data = consolidateRuns(data);
+    data = applyInterval(data, interval);
+    data = findCollapsedDepths(data);
+
+    return data;
+  }
+
+  // Given the raw profiling data, convert `time` and `lastTime` fields to
+  // `startTime` and `endTime`, and use the supplied interval. Modifies data
+  // in place.
+  function applyInterval(prof, interval) {
+    prof.forEach(function(d) {
+      d.startTime = interval * (d.time - 1);
+      d.endTime = interval * (d.lastTime);
+      delete d.time;
+      delete d.lastTime;
+    });
+
+    return prof;
+  }
+
+  // Find the total time spanned in the data
+  function getTotalTime(prof) {
+    return d3.max(prof, function(d) { return d.endTime; }) -
+           d3.min(prof, function(d) { return d.startTime; });
+  }
+
+  // Find the total memory spanned in the data
+  function getTotalMemory(prof) {
+    return d3.max(prof, function(d) { return d.memalloc; });
+  }
+
+  // Calculate the total amount of time spent in each function label
+  function getAggregatedLabelTimes(prof) {
+    var labelTimes = {};
+    var tree = getProfTree(prof);
+    calcLabelTimes(tree);
+
+    return labelTimes;
+
+    // Traverse the tree with the following strategy:
+    // * Check if current label is used in an ancestor.
+    //   * If yes, don't add to times for that label.
+    //   * If no, do add to times for that label.
+    // * Recurse into children.
+    function calcLabelTimes(node) {
+      var label = node.label;
+      if (!ancestorHasLabel(label, node.parent)) {
+        if (labelTimes[label] === undefined)
+          labelTimes[label] = 0;
+
+        labelTimes[label] += node.endTime - node.startTime;
+      }
+
+      node.children.forEach(calcLabelTimes);
+    }
+
+    // Returns true if the given node or one of its ancestors has the given
+    // label; false otherwise.
+    function ancestorHasLabel(label, node) {
+      if (node) {
+        if (node.label === label) {
+          return true;
+        }
+        return ancestorHasLabel(label, node.parent);
+      } else {
+        return false;
+      }
+    }
+  }
+
+
+  // Given profiling data, add parent and child links to indicate stack
+  // relationships.
+  function addParentChildLinks(prof) {
+    var data = d3.nest()
+      .key(function(d) { return d.time; })
+      .rollup(function(leaves) {
+        leaves = leaves.sort(function(a, b) { return a.depth - b.depth; });
+
+        leaves[0].parent = null;
+        leaves[0].children = [];
+
+        for (var i=1; i<leaves.length; i++) {
+          leaves[i-1].children.push(leaves[i]);
+          leaves[i].parent = leaves[i-1];
+          leaves[i].children = [];
+        }
+
+        return leaves;
+      })
+      .map(prof);
+
+    // Convert data from object of arrays to array of arrays
+    data = d3.map(data).values();
+    // Flatten data
+    return d3.merge(data);
+  }
+
+
+  // Given profiling data, consolidate consecutive blocks for a flamegraph.
+  // This function also assigns correct parent-child relationships to form a
+  // tree of data objects, with a hidden root node at depth 0.
+  function consolidateRuns(prof) {
+    // Create a special top-level leaf whose only purpose is to point to its
+    // children, the items at depth 1.
+    var topLeaf = {
+      depth: 0,
+      parent: null,
+      children: prof.filter(function(d) { return d.depth === 1; })
+    };
+
+    var tree = consolidateTree(topLeaf);
+    var data = treeToArray(tree);
+    // Remove the root node from the flattened data
+    data = data.filter(function(d) { return d.depth !== 0; });
+    return data;
+
+    function consolidateTree(tree) {
+      var leaves = tree.children;
+      leaves = leaves.sort(function(a, b) { return a.time - b.time; });
+
+      // Collapse consecutive leaves, with some conditions
+      var startLeaf = null;  // leaf starting this run
+      var lastLeaf = null;   // The last leaf we've looked at
+      var newLeaves = [];
+      var collectedChildren = [];
+      var sumMem = 0;
+      var sumMemDealloc = 0;
+      var sumMemAlloc = 0;
+
+      // This takes the start leaf, end leaf, and the set of children for the
+      // new leaf, and creates a new leaf which copies all its properties from
+      // the startLeaf, except lastTime and children.
+      function addNewLeaf(startLeaf, endLeaf, newLeafChildren, sumMem, sumMemDealloc, sumMemAlloc) {
+        var newLeaf = $.extend({}, startLeaf);
+        newLeaf.lastTime = endLeaf.time;
+        newLeaf.parent = tree;
+        newLeaf.children = newLeafChildren;
+
+        // Recurse into children
+        newLeaf = consolidateTree(newLeaf);
+
+        // Aggregate memory from this consolidation batch and their children
+        aggregateMemory(newLeaf, sumMem, sumMemDealloc, sumMemAlloc);
+
+        newLeaves.push(newLeaf);
+      }
+
+      function aggregateMemory(leaf, sumMem, sumMemDealloc, sumMemAlloc) {
+        leaf.sumMem = sumMem;
+        leaf.sumMemDealloc = sumMemDealloc;
+        leaf.sumMemAlloc = sumMemAlloc;
+        if (leaf.children) {
+          leaf.children.forEach(function(child) {
+            leaf.sumMem += child.sumMem ? child.sumMem : 0;
+            leaf.sumMemDealloc += child.sumMemDealloc ? child.sumMemDealloc : 0;
+            leaf.sumMemAlloc += child.sumMemAlloc ? child.sumMemAlloc : 0;
+          });
+        }
+      }
+
+      for (var i=0; i<leaves.length; i++) {
+        var leaf = leaves[i];
+
+        if (i === 0) {
+          startLeaf = leaf;
+          sumMem = sumMemAlloc = sumMemDealloc = 0;
+        } else if (leaf.label !== startLeaf.label ||
+                   leaf.filename !== startLeaf.filename ||
+                   leaf.linenum !== startLeaf.linenum ||
+                   leaf.depth !== startLeaf.depth)
+        {
+          addNewLeaf(startLeaf, lastLeaf, collectedChildren, sumMem, sumMemDealloc, sumMemAlloc);
+
+          collectedChildren = [];
+          startLeaf = leaf;
+          sumMem = sumMemAlloc = sumMemDealloc = 0;
+        }
+
+        sumMem += leaf.meminc;
+        sumMemDealloc += Math.min(leaf.meminc, 0);
+        sumMemAlloc += Math.max(leaf.meminc, 0);
+        collectedChildren = collectedChildren.concat(leaf.children);
+        lastLeaf = leaf;
+      }
+
+      // Add the last one, if there were any at all
+      if (i !== 0) {
+        addNewLeaf(startLeaf, lastLeaf, collectedChildren, sumMem, sumMemDealloc, sumMemAlloc);
+      }
+
+      tree.children = newLeaves;
+      return tree;
+    }
+
+    // Given a tree, pull out all the leaves and put them in a flat array
+    function treeToArray(tree) {
+      var allLeaves = [];
+
+      function pushLeaves(leaf) {
+        allLeaves.push(leaf);
+        leaf.children.forEach(pushLeaves);
+      }
+
+      pushLeaves(tree);
+      return allLeaves;
+    }
+  }
+
+
+  // Given profiling data with parent-child information, get the root node.
+  function getProfTree(prof) {
+    if (prof.length === 0)
+      return null;
+
+    // Climb up to the top of the tree
+    var node = prof[0];
+    while (node.parent) {
+      node = node.parent;
+    }
+    return node;
+  }
+
+
+  // Given profiling data, find depth of items after hiding items between
+  // items with labels "..stacktraceoff.." and "..stacktraceon..". Modifies
+  // data in place.
+  function findCollapsedDepths(data) {
+    var tree = getProfTree(data);
+    calculateDepths(tree, tree.depth, 0);
+    return data;
+
+    function calculateDepths(node, curCollapsedDepth, stacktraceOffCount) {
+      if (node.label === "..stacktraceoff..") {
+        stacktraceOffCount++;
+      }
+
+      if (stacktraceOffCount > 0) {
+        node.depthCollapsed = null;
+      } else {
+        node.depthCollapsed = curCollapsedDepth;
+        curCollapsedDepth++;
+      }
+
+      if (node.label === "..stacktraceon..") {
+        stacktraceOffCount--;
+      }
+
+      // Recurse
+      node.children.forEach(function(x) {
+        calculateDepths(x, curCollapsedDepth, stacktraceOffCount);
+      });
+    }
+  }
+
+
+  // Transform column-oriented data (an object with arrays) to row-oriented data
+  // (an array of objects).
+  function colToRows(x) {
+    var colnames = d3.keys(x);
+    if (colnames.length === 0)
+      return [];
+
+    var newdata = [];
+    for (var i=0; i < x[colnames[0]].length; i++) {
+      var row = {};
+      for (var j=0; j < colnames.length; j++) {
+        var colname = colnames[j];
+        row[colname] = x[colname][i];
+      }
+      newdata[i] = row;
+    }
+
+    return newdata;
+  }
+
+  // Given an array with two values (a min and max), return an array with the
+  // range expanded by `amount`.
+  function expandRange(range, amount) {
+    var adjust = amount * (range[1] - range[0]);
+    return [
+      range[0] - adjust,
+      range[1] + adjust
+    ];
+  }
+
+
+  // Escape an HTML string.
+  function escapeHTML(text) {
+    return text
+      .replace(/&/g, "&amp;")
+      .replace(/</g, "&lt;")
+      .replace(/>/g, "&gt;")
+      .replace(/"/g, "&quot;")
+      .replace(/'/g, "&#039;");
+  }
+
+  // This returns the current page URL without any trailing hash. Should be
+  // used in url() references in SVGs to avoid problems when there's a <base>
+  // tag in the document.
+  function urlNoHash() {
+    return window.location.href.split("#")[0];
+  }
+
+  function debounce(f, delay) {
+    var timer = null;
+    return function() {
+      var context = this;
+      var args = arguments;
+      clearTimeout(timer);
+      timer = setTimeout(function () {
+        f.apply(context, args);
+      }, delay);
+    };
+  }
+
+  function randomString(length) {
+    var chars = 'abcdefghijklmnopqrstuvwxyz';
+    var result = '';
+    for (var i = length; i > 0; --i)
+      result += chars[Math.floor(Math.random() * chars.length)];
+    return result;
+  }
+
+  var getNormPath = function(files, filename) {
+    var normpath = null;
+    files.forEach(function(e) {
+      if (e.filename == filename) {
+        normpath = e.normpath;
+      }
+    });
+    return normpath;
+  };
+
+
+  (function() {
+    // Prevent unwanted scroll capturing. Based on the corresponding code in
+    // https://github.com/rstudio/leaflet
+
+    // The rough idea is that we disable scroll wheel zooming inside each
+    // profvis object, until the user moves the mouse cursor or clicks on the
+    // visualization. This is trickier than just listening for mousemove,
+    // because mousemove is fired when the page is scrolled, even if the user
+    // did not physically move the mouse. We handle this by examining the
+    // mousemove event's screenX and screenY properties; if they change, we know
+    // it's a "true" move.
+    //
+    // There's a complication to this: when the mouse wheel is scrolled quickly,
+    // on the step where the profvis DOM object overlaps the cursor, sometimes
+    // the mousemove event happens before the mousewheel event, and sometimes
+    // it's the reverse (at least on Chrome 46 on Linux). This means that we
+    // can't rely on the mousemove handler disabling the profvis object's zoom
+    // before a scroll event is triggered on the profvis object (cauzing
+    // zooming). In order to deal with this, we start each profvis object with
+    // zooming disabled, and also disable zooming when the cursor leaves the
+    // profvis div. That way, even if a mousewheel event gets triggered on the
+    // object before the mousemove, it won't cause zooming.
+
+    // lastScreen can never be null, but its x and y can.
+    var lastScreen = { x: null, y: null };
+
+    $(document)
+      .on("mousewheel DOMMouseScroll", function(e) {
+        // Any mousemove events at this screen position will be ignored.
+        lastScreen = { x: e.originalEvent.screenX, y: e.originalEvent.screenY };
+      })
+      .on("mousemove", ".profvis", function(e) {
+        // Did the mouse really move?
+        if (lastScreen.x !== null && e.screenX !== lastScreen.x || e.screenY !== lastScreen.y) {
+          $(this).data("profvis").flameGraph.enableZoom();
+          lastScreen = { x: null, y: null };
+        }
+      })
+      .on("mousedown", ".profvis", function(e) {
+        // Clicking always enables zooming.
+        $(this).data("profvis").flameGraph.enableZoom();
+        lastScreen = { x: null, y: null };
+      })
+      .on("mouseleave", ".profvis", function(e) {
+        $(this).data("profvis").flameGraph.disableZoom();
+      });
+  })();
+
+  return profvis;
+})();
+</script>
+<script>(function() {
+
+  // Polyfill for scrollIntoViewIfNeeded()
+  // From https://gist.github.com/jocki84/6ffafd003387179a988e
+  // License: ISC
+  if (!Element.prototype.scrollIntoViewIfNeeded) {
+    Element.prototype.scrollIntoViewIfNeeded = function (centerIfNeeded) {
+      "use strict";
+
+      function makeRange(start, length) {
+        return {"start": start, "length": length, "end": start + length};
+      }
+
+      function coverRange(inner, outer) {
+        if (
+          false === centerIfNeeded ||
+          (outer.start < inner.end && inner.start < outer.end)
+        ) {
+          return Math.max(
+              inner.end - outer.length,
+              Math.min(outer.start, inner.start)
+          );
+        }
+        return (inner.start + inner.end - outer.length) / 2;
+      }
+
+      function makePoint(x, y) {
+        return {
+          "x": x,
+          "y": y,
+          "translate": function translate(dX, dY) {
+            return makePoint(x + dX, y + dY);
+          }
+        };
+      }
+
+      function absolute(elem, pt) {
+        while (elem) {
+          pt = pt.translate(elem.offsetLeft, elem.offsetTop);
+          elem = elem.offsetParent;
+        }
+        return pt;
+      }
+
+      var target = absolute(this, makePoint(0, 0)),
+          extent = makePoint(this.offsetWidth, this.offsetHeight),
+          elem = this.parentNode,
+          origin;
+
+      while (elem instanceof HTMLElement) {
+        // Apply desired scroll amount.
+        origin = absolute(elem, makePoint(elem.clientLeft, elem.clientTop));
+        elem.scrollLeft = coverRange(
+          makeRange(target.x - origin.x, extent.x),
+          makeRange(elem.scrollLeft, elem.clientWidth)
+        );
+        elem.scrollTop = coverRange(
+          makeRange(target.y - origin.y, extent.y),
+          makeRange(elem.scrollTop, elem.clientHeight)
+        );
+
+        // Determine actual scroll amount by reading back scroll properties.
+        target = target.translate(-elem.scrollLeft, -elem.scrollTop);
+        elem = elem.parentNode;
+      }
+    };
+  }
+
+})()</script>
+<style type="text/css">.profvis-code span.hljs-operator,
+.profvis-code span.hljs-paren {
+color: rgb(104, 118, 135)
+}
+.profvis-code span.hljs-literal {
+color: rgb(88, 72, 246)
+}
+.profvis-code span.hljs-number {
+color: rgb(0, 0, 205);
+}
+.profvis-code span.hljs-comment {
+color: rgb(76, 136, 107);
+}
+.profvis-code span.hljs-keyword {
+color: rgb(0, 0, 255);
+}
+.profvis-code span.hljs-identifier {
+color: rgb(0, 0, 0);
+}
+.profvis-code span.hljs-string {
+color: rgb(3, 106, 7);
+}
+</style>
+<script>/*!
+  Highlight.js v11.10.0 (git: 366a8bd012)
+  (c) 2006-2024 Josh Goebel <hello@joshgoebel.com> and other contributors
+  License: BSD-3-Clause
+ */
+var hljs=function(){"use strict";function e(t){
+return t instanceof Map?t.clear=t.delete=t.set=()=>{
+throw Error("map is read-only")}:t instanceof Set&&(t.add=t.clear=t.delete=()=>{
+throw Error("set is read-only")
+}),Object.freeze(t),Object.getOwnPropertyNames(t).forEach((n=>{
+const i=t[n],s=typeof i;"object"!==s&&"function"!==s||Object.isFrozen(i)||e(i)
+})),t}class t{constructor(e){
+void 0===e.data&&(e.data={}),this.data=e.data,this.isMatchIgnored=!1}
+ignoreMatch(){this.isMatchIgnored=!0}}function n(e){
+return e.replace(/&/g,"&amp;").replace(/</g,"&lt;").replace(/>/g,"&gt;").replace(/"/g,"&quot;").replace(/'/g,"&#x27;")
+}function i(e,...t){const n=Object.create(null);for(const t in e)n[t]=e[t]
+;return t.forEach((e=>{for(const t in e)n[t]=e[t]})),n}const s=e=>!!e.scope
+;class o{constructor(e,t){
+this.buffer="",this.classPrefix=t.classPrefix,e.walk(this)}addText(e){
+this.buffer+=n(e)}openNode(e){if(!s(e))return;const t=((e,{prefix:t})=>{
+if(e.startsWith("language:"))return e.replace("language:","language-")
+;if(e.includes(".")){const n=e.split(".")
+;return[`${t}${n.shift()}`,...n.map(((e,t)=>`${e}${"_".repeat(t+1)}`))].join(" ")
+}return`${t}${e}`})(e.scope,{prefix:this.classPrefix});this.span(t)}
+closeNode(e){s(e)&&(this.buffer+="</span>")}value(){return this.buffer}span(e){
+this.buffer+=`<span class="${e}">`}}const r=(e={})=>{const t={children:[]}
+;return Object.assign(t,e),t};class a{constructor(){
+this.rootNode=r(),this.stack=[this.rootNode]}get top(){
+return this.stack[this.stack.length-1]}get root(){return this.rootNode}add(e){
+this.top.children.push(e)}openNode(e){const t=r({scope:e})
+;this.add(t),this.stack.push(t)}closeNode(){
+if(this.stack.length>1)return this.stack.pop()}closeAllNodes(){
+for(;this.closeNode(););}toJSON(){return JSON.stringify(this.rootNode,null,4)}
+walk(e){return this.constructor._walk(e,this.rootNode)}static _walk(e,t){
+return"string"==typeof t?e.addText(t):t.children&&(e.openNode(t),
+t.children.forEach((t=>this._walk(e,t))),e.closeNode(t)),e}static _collapse(e){
+"string"!=typeof e&&e.children&&(e.children.every((e=>"string"==typeof e))?e.children=[e.children.join("")]:e.children.forEach((e=>{
+a._collapse(e)})))}}class c extends a{constructor(e){super(),this.options=e}
+addText(e){""!==e&&this.add(e)}startScope(e){this.openNode(e)}endScope(){
+this.closeNode()}__addSublanguage(e,t){const n=e.root
+;t&&(n.scope="language:"+t),this.add(n)}toHTML(){
+return new o(this,this.options).value()}finalize(){
+return this.closeAllNodes(),!0}}function l(e){
+return e?"string"==typeof e?e:e.source:null}function g(e){return h("(?=",e,")")}
+function u(e){return h("(?:",e,")*")}function d(e){return h("(?:",e,")?")}
+function h(...e){return e.map((e=>l(e))).join("")}function f(...e){const t=(e=>{
+const t=e[e.length-1]
+;return"object"==typeof t&&t.constructor===Object?(e.splice(e.length-1,1),t):{}
+})(e);return"("+(t.capture?"":"?:")+e.map((e=>l(e))).join("|")+")"}
+function p(e){return RegExp(e.toString()+"|").exec("").length-1}
+const b=/\[(?:[^\\\]]|\\.)*\]|\(\??|\\([1-9][0-9]*)|\\./
+;function m(e,{joinWith:t}){let n=0;return e.map((e=>{n+=1;const t=n
+;let i=l(e),s="";for(;i.length>0;){const e=b.exec(i);if(!e){s+=i;break}
+s+=i.substring(0,e.index),
+i=i.substring(e.index+e[0].length),"\\"===e[0][0]&&e[1]?s+="\\"+(Number(e[1])+t):(s+=e[0],
+"("===e[0]&&n++)}return s})).map((e=>`(${e})`)).join(t)}
+const E="[a-zA-Z]\\w*",x="[a-zA-Z_]\\w*",w="\\b\\d+(\\.\\d+)?",y="(-?)(\\b0[xX][a-fA-F0-9]+|(\\b\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)",_="\\b(0b[01]+)",O={
+begin:"\\\\[\\s\\S]",relevance:0},v={scope:"string",begin:"'",end:"'",
+illegal:"\\n",contains:[O]},k={scope:"string",begin:'"',end:'"',illegal:"\\n",
+contains:[O]},N=(e,t,n={})=>{const s=i({scope:"comment",begin:e,end:t,
+contains:[]},n);s.contains.push({scope:"doctag",
+begin:"[ ]*(?=(TODO|FIXME|NOTE|BUG|OPTIMIZE|HACK|XXX):)",
+end:/(TODO|FIXME|NOTE|BUG|OPTIMIZE|HACK|XXX):/,excludeBegin:!0,relevance:0})
+;const o=f("I","a","is","so","us","to","at","if","in","it","on",/[A-Za-z]+['](d|ve|re|ll|t|s|n)/,/[A-Za-z]+[-][a-z]+/,/[A-Za-z][a-z]{2,}/)
+;return s.contains.push({begin:h(/[ ]+/,"(",o,/[.]?[:]?([.][ ]|[ ])/,"){3}")}),s
+},S=N("//","$"),M=N("/\\*","\\*/"),R=N("#","$");var j=Object.freeze({
+__proto__:null,APOS_STRING_MODE:v,BACKSLASH_ESCAPE:O,BINARY_NUMBER_MODE:{
+scope:"number",begin:_,relevance:0},BINARY_NUMBER_RE:_,COMMENT:N,
+C_BLOCK_COMMENT_MODE:M,C_LINE_COMMENT_MODE:S,C_NUMBER_MODE:{scope:"number",
+begin:y,relevance:0},C_NUMBER_RE:y,END_SAME_AS_BEGIN:e=>Object.assign(e,{
+"on:begin":(e,t)=>{t.data._beginMatch=e[1]},"on:end":(e,t)=>{
+t.data._beginMatch!==e[1]&&t.ignoreMatch()}}),HASH_COMMENT_MODE:R,IDENT_RE:E,
+MATCH_NOTHING_RE:/\b\B/,METHOD_GUARD:{begin:"\\.\\s*"+x,relevance:0},
+NUMBER_MODE:{scope:"number",begin:w,relevance:0},NUMBER_RE:w,
+PHRASAL_WORDS_MODE:{
+begin:/\b(a|an|the|are|I'm|isn't|don't|doesn't|won't|but|just|should|pretty|simply|enough|gonna|going|wtf|so|such|will|you|your|they|like|more)\b/
+},QUOTE_STRING_MODE:k,REGEXP_MODE:{scope:"regexp",begin:/\/(?=[^/\n]*\/)/,
+end:/\/[gimuy]*/,contains:[O,{begin:/\[/,end:/\]/,relevance:0,contains:[O]}]},
+RE_STARTERS_RE:"!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|-|-=|/=|/|:|;|<<|<<=|<=|<|===|==|=|>>>=|>>=|>=|>>>|>>|>|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~",
+SHEBANG:(e={})=>{const t=/^#![ ]*\//
+;return e.binary&&(e.begin=h(t,/.*\b/,e.binary,/\b.*/)),i({scope:"meta",begin:t,
+end:/$/,relevance:0,"on:begin":(e,t)=>{0!==e.index&&t.ignoreMatch()}},e)},
+TITLE_MODE:{scope:"title",begin:E,relevance:0},UNDERSCORE_IDENT_RE:x,
+UNDERSCORE_TITLE_MODE:{scope:"title",begin:x,relevance:0}});function A(e,t){
+"."===e.input[e.index-1]&&t.ignoreMatch()}function I(e,t){
+void 0!==e.className&&(e.scope=e.className,delete e.className)}function T(e,t){
+t&&e.beginKeywords&&(e.begin="\\b("+e.beginKeywords.split(" ").join("|")+")(?!\\.)(?=\\b|\\s)",
+e.__beforeBegin=A,e.keywords=e.keywords||e.beginKeywords,delete e.beginKeywords,
+void 0===e.relevance&&(e.relevance=0))}function L(e,t){
+Array.isArray(e.illegal)&&(e.illegal=f(...e.illegal))}function B(e,t){
+if(e.match){
+if(e.begin||e.end)throw Error("begin & end are not supported with match")
+;e.begin=e.match,delete e.match}}function P(e,t){
+void 0===e.relevance&&(e.relevance=1)}const D=(e,t)=>{if(!e.beforeMatch)return
+;if(e.starts)throw Error("beforeMatch cannot be used with starts")
+;const n=Object.assign({},e);Object.keys(e).forEach((t=>{delete e[t]
+})),e.keywords=n.keywords,e.begin=h(n.beforeMatch,g(n.begin)),e.starts={
+relevance:0,contains:[Object.assign(n,{endsParent:!0})]
+},e.relevance=0,delete n.beforeMatch
+},H=["of","and","for","in","not","or","if","then","parent","list","value"],C="keyword"
+;function $(e,t,n=C){const i=Object.create(null)
+;return"string"==typeof e?s(n,e.split(" ")):Array.isArray(e)?s(n,e):Object.keys(e).forEach((n=>{
+Object.assign(i,$(e[n],t,n))})),i;function s(e,n){
+t&&(n=n.map((e=>e.toLowerCase()))),n.forEach((t=>{const n=t.split("|")
+;i[n[0]]=[e,U(n[0],n[1])]}))}}function U(e,t){
+return t?Number(t):(e=>H.includes(e.toLowerCase()))(e)?0:1}const z={},W=e=>{
+console.error(e)},X=(e,...t)=>{console.log("WARN: "+e,...t)},G=(e,t)=>{
+z[`${e}/${t}`]||(console.log(`Deprecated as of ${e}. ${t}`),z[`${e}/${t}`]=!0)
+},K=Error();function F(e,t,{key:n}){let i=0;const s=e[n],o={},r={}
+;for(let e=1;e<=t.length;e++)r[e+i]=s[e],o[e+i]=!0,i+=p(t[e-1])
+;e[n]=r,e[n]._emit=o,e[n]._multi=!0}function Z(e){(e=>{
+e.scope&&"object"==typeof e.scope&&null!==e.scope&&(e.beginScope=e.scope,
+delete e.scope)})(e),"string"==typeof e.beginScope&&(e.beginScope={
+_wrap:e.beginScope}),"string"==typeof e.endScope&&(e.endScope={_wrap:e.endScope
+}),(e=>{if(Array.isArray(e.begin)){
+if(e.skip||e.excludeBegin||e.returnBegin)throw W("skip, excludeBegin, returnBegin not compatible with beginScope: {}"),
+K
+;if("object"!=typeof e.beginScope||null===e.beginScope)throw W("beginScope must be object"),
+K;F(e,e.begin,{key:"beginScope"}),e.begin=m(e.begin,{joinWith:""})}})(e),(e=>{
+if(Array.isArray(e.end)){
+if(e.skip||e.excludeEnd||e.returnEnd)throw W("skip, excludeEnd, returnEnd not compatible with endScope: {}"),
+K
+;if("object"!=typeof e.endScope||null===e.endScope)throw W("endScope must be object"),
+K;F(e,e.end,{key:"endScope"}),e.end=m(e.end,{joinWith:""})}})(e)}function V(e){
+function t(t,n){
+return RegExp(l(t),"m"+(e.case_insensitive?"i":"")+(e.unicodeRegex?"u":"")+(n?"g":""))
+}class n{constructor(){
+this.matchIndexes={},this.regexes=[],this.matchAt=1,this.position=0}
+addRule(e,t){
+t.position=this.position++,this.matchIndexes[this.matchAt]=t,this.regexes.push([t,e]),
+this.matchAt+=p(e)+1}compile(){0===this.regexes.length&&(this.exec=()=>null)
+;const e=this.regexes.map((e=>e[1]));this.matcherRe=t(m(e,{joinWith:"|"
+}),!0),this.lastIndex=0}exec(e){this.matcherRe.lastIndex=this.lastIndex
+;const t=this.matcherRe.exec(e);if(!t)return null
+;const n=t.findIndex(((e,t)=>t>0&&void 0!==e)),i=this.matchIndexes[n]
+;return t.splice(0,n),Object.assign(t,i)}}class s{constructor(){
+this.rules=[],this.multiRegexes=[],
+this.count=0,this.lastIndex=0,this.regexIndex=0}getMatcher(e){
+if(this.multiRegexes[e])return this.multiRegexes[e];const t=new n
+;return this.rules.slice(e).forEach((([e,n])=>t.addRule(e,n))),
+t.compile(),this.multiRegexes[e]=t,t}resumingScanAtSamePosition(){
+return 0!==this.regexIndex}considerAll(){this.regexIndex=0}addRule(e,t){
+this.rules.push([e,t]),"begin"===t.type&&this.count++}exec(e){
+const t=this.getMatcher(this.regexIndex);t.lastIndex=this.lastIndex
+;let n=t.exec(e)
+;if(this.resumingScanAtSamePosition())if(n&&n.index===this.lastIndex);else{
+const t=this.getMatcher(0);t.lastIndex=this.lastIndex+1,n=t.exec(e)}
+return n&&(this.regexIndex+=n.position+1,
+this.regexIndex===this.count&&this.considerAll()),n}}
+if(e.compilerExtensions||(e.compilerExtensions=[]),
+e.contains&&e.contains.includes("self"))throw Error("ERR: contains `self` is not supported at the top-level of a language.  See documentation.")
+;return e.classNameAliases=i(e.classNameAliases||{}),function n(o,r){const a=o
+;if(o.isCompiled)return a
+;[I,B,Z,D].forEach((e=>e(o,r))),e.compilerExtensions.forEach((e=>e(o,r))),
+o.__beforeBegin=null,[T,L,P].forEach((e=>e(o,r))),o.isCompiled=!0;let c=null
+;return"object"==typeof o.keywords&&o.keywords.$pattern&&(o.keywords=Object.assign({},o.keywords),
+c=o.keywords.$pattern,
+delete o.keywords.$pattern),c=c||/\w+/,o.keywords&&(o.keywords=$(o.keywords,e.case_insensitive)),
+a.keywordPatternRe=t(c,!0),
+r&&(o.begin||(o.begin=/\B|\b/),a.beginRe=t(a.begin),o.end||o.endsWithParent||(o.end=/\B|\b/),
+o.end&&(a.endRe=t(a.end)),
+a.terminatorEnd=l(a.end)||"",o.endsWithParent&&r.terminatorEnd&&(a.terminatorEnd+=(o.end?"|":"")+r.terminatorEnd)),
+o.illegal&&(a.illegalRe=t(o.illegal)),
+o.contains||(o.contains=[]),o.contains=[].concat(...o.contains.map((e=>(e=>(e.variants&&!e.cachedVariants&&(e.cachedVariants=e.variants.map((t=>i(e,{
+variants:null},t)))),e.cachedVariants?e.cachedVariants:q(e)?i(e,{
+starts:e.starts?i(e.starts):null
+}):Object.isFrozen(e)?i(e):e))("self"===e?o:e)))),o.contains.forEach((e=>{n(e,a)
+})),o.starts&&n(o.starts,r),a.matcher=(e=>{const t=new s
+;return e.contains.forEach((e=>t.addRule(e.begin,{rule:e,type:"begin"
+}))),e.terminatorEnd&&t.addRule(e.terminatorEnd,{type:"end"
+}),e.illegal&&t.addRule(e.illegal,{type:"illegal"}),t})(a),a}(e)}function q(e){
+return!!e&&(e.endsWithParent||q(e.starts))}class J extends Error{
+constructor(e,t){super(e),this.name="HTMLInjectionError",this.html=t}}
+const Y=n,Q=i,ee=Symbol("nomatch"),te=n=>{
+const i=Object.create(null),s=Object.create(null),o=[];let r=!0
+;const a="Could not find the language '{}', did you forget to load/include a language module?",l={
+disableAutodetect:!0,name:"Plain text",contains:[]};let p={
+ignoreUnescapedHTML:!1,throwUnescapedHTML:!1,noHighlightRe:/^(no-?highlight)$/i,
+languageDetectRe:/\blang(?:uage)?-([\w-]+)\b/i,classPrefix:"hljs-",
+cssSelector:"pre code",languages:null,__emitter:c};function b(e){
+return p.noHighlightRe.test(e)}function m(e,t,n){let i="",s=""
+;"object"==typeof t?(i=e,
+n=t.ignoreIllegals,s=t.language):(G("10.7.0","highlight(lang, code, ...args) has been deprecated."),
+G("10.7.0","Please use highlight(code, options) instead.\nhttps://github.com/highlightjs/highlight.js/issues/2277"),
+s=e,i=t),void 0===n&&(n=!0);const o={code:i,language:s};N("before:highlight",o)
+;const r=o.result?o.result:E(o.language,o.code,n)
+;return r.code=o.code,N("after:highlight",r),r}function E(e,n,s,o){
+const c=Object.create(null);function l(){if(!N.keywords)return void M.addText(R)
+;let e=0;N.keywordPatternRe.lastIndex=0;let t=N.keywordPatternRe.exec(R),n=""
+;for(;t;){n+=R.substring(e,t.index)
+;const s=_.case_insensitive?t[0].toLowerCase():t[0],o=(i=s,N.keywords[i]);if(o){
+const[e,i]=o
+;if(M.addText(n),n="",c[s]=(c[s]||0)+1,c[s]<=7&&(j+=i),e.startsWith("_"))n+=t[0];else{
+const n=_.classNameAliases[e]||e;u(t[0],n)}}else n+=t[0]
+;e=N.keywordPatternRe.lastIndex,t=N.keywordPatternRe.exec(R)}var i
+;n+=R.substring(e),M.addText(n)}function g(){null!=N.subLanguage?(()=>{
+if(""===R)return;let e=null;if("string"==typeof N.subLanguage){
+if(!i[N.subLanguage])return void M.addText(R)
+;e=E(N.subLanguage,R,!0,S[N.subLanguage]),S[N.subLanguage]=e._top
+}else e=x(R,N.subLanguage.length?N.subLanguage:null)
+;N.relevance>0&&(j+=e.relevance),M.__addSublanguage(e._emitter,e.language)
+})():l(),R=""}function u(e,t){
+""!==e&&(M.startScope(t),M.addText(e),M.endScope())}function d(e,t){let n=1
+;const i=t.length-1;for(;n<=i;){if(!e._emit[n]){n++;continue}
+const i=_.classNameAliases[e[n]]||e[n],s=t[n];i?u(s,i):(R=s,l(),R=""),n++}}
+function h(e,t){
+return e.scope&&"string"==typeof e.scope&&M.openNode(_.classNameAliases[e.scope]||e.scope),
+e.beginScope&&(e.beginScope._wrap?(u(R,_.classNameAliases[e.beginScope._wrap]||e.beginScope._wrap),
+R=""):e.beginScope._multi&&(d(e.beginScope,t),R="")),N=Object.create(e,{parent:{
+value:N}}),N}function f(e,n,i){let s=((e,t)=>{const n=e&&e.exec(t)
+;return n&&0===n.index})(e.endRe,i);if(s){if(e["on:end"]){const i=new t(e)
+;e["on:end"](n,i),i.isMatchIgnored&&(s=!1)}if(s){
+for(;e.endsParent&&e.parent;)e=e.parent;return e}}
+if(e.endsWithParent)return f(e.parent,n,i)}function b(e){
+return 0===N.matcher.regexIndex?(R+=e[0],1):(T=!0,0)}function m(e){
+const t=e[0],i=n.substring(e.index),s=f(N,e,i);if(!s)return ee;const o=N
+;N.endScope&&N.endScope._wrap?(g(),
+u(t,N.endScope._wrap)):N.endScope&&N.endScope._multi?(g(),
+d(N.endScope,e)):o.skip?R+=t:(o.returnEnd||o.excludeEnd||(R+=t),
+g(),o.excludeEnd&&(R=t));do{
+N.scope&&M.closeNode(),N.skip||N.subLanguage||(j+=N.relevance),N=N.parent
+}while(N!==s.parent);return s.starts&&h(s.starts,e),o.returnEnd?0:t.length}
+let w={};function y(i,o){const a=o&&o[0];if(R+=i,null==a)return g(),0
+;if("begin"===w.type&&"end"===o.type&&w.index===o.index&&""===a){
+if(R+=n.slice(o.index,o.index+1),!r){const t=Error(`0 width match regex (${e})`)
+;throw t.languageName=e,t.badRule=w.rule,t}return 1}
+if(w=o,"begin"===o.type)return(e=>{
+const n=e[0],i=e.rule,s=new t(i),o=[i.__beforeBegin,i["on:begin"]]
+;for(const t of o)if(t&&(t(e,s),s.isMatchIgnored))return b(n)
+;return i.skip?R+=n:(i.excludeBegin&&(R+=n),
+g(),i.returnBegin||i.excludeBegin||(R=n)),h(i,e),i.returnBegin?0:n.length})(o)
+;if("illegal"===o.type&&!s){
+const e=Error('Illegal lexeme "'+a+'" for mode "'+(N.scope||"<unnamed>")+'"')
+;throw e.mode=N,e}if("end"===o.type){const e=m(o);if(e!==ee)return e}
+if("illegal"===o.type&&""===a)return 1
+;if(I>1e5&&I>3*o.index)throw Error("potential infinite loop, way more iterations than matches")
+;return R+=a,a.length}const _=O(e)
+;if(!_)throw W(a.replace("{}",e)),Error('Unknown language: "'+e+'"')
+;const v=V(_);let k="",N=o||v;const S={},M=new p.__emitter(p);(()=>{const e=[]
+;for(let t=N;t!==_;t=t.parent)t.scope&&e.unshift(t.scope)
+;e.forEach((e=>M.openNode(e)))})();let R="",j=0,A=0,I=0,T=!1;try{
+if(_.__emitTokens)_.__emitTokens(n,M);else{for(N.matcher.considerAll();;){
+I++,T?T=!1:N.matcher.considerAll(),N.matcher.lastIndex=A
+;const e=N.matcher.exec(n);if(!e)break;const t=y(n.substring(A,e.index),e)
+;A=e.index+t}y(n.substring(A))}return M.finalize(),k=M.toHTML(),{language:e,
+value:k,relevance:j,illegal:!1,_emitter:M,_top:N}}catch(t){
+if(t.message&&t.message.includes("Illegal"))return{language:e,value:Y(n),
+illegal:!0,relevance:0,_illegalBy:{message:t.message,index:A,
+context:n.slice(A-100,A+100),mode:t.mode,resultSoFar:k},_emitter:M};if(r)return{
+language:e,value:Y(n),illegal:!1,relevance:0,errorRaised:t,_emitter:M,_top:N}
+;throw t}}function x(e,t){t=t||p.languages||Object.keys(i);const n=(e=>{
+const t={value:Y(e),illegal:!1,relevance:0,_top:l,_emitter:new p.__emitter(p)}
+;return t._emitter.addText(e),t})(e),s=t.filter(O).filter(k).map((t=>E(t,e,!1)))
+;s.unshift(n);const o=s.sort(((e,t)=>{
+if(e.relevance!==t.relevance)return t.relevance-e.relevance
+;if(e.language&&t.language){if(O(e.language).supersetOf===t.language)return 1
+;if(O(t.language).supersetOf===e.language)return-1}return 0})),[r,a]=o,c=r
+;return c.secondBest=a,c}function w(e){let t=null;const n=(e=>{
+let t=e.className+" ";t+=e.parentNode?e.parentNode.className:""
+;const n=p.languageDetectRe.exec(t);if(n){const t=O(n[1])
+;return t||(X(a.replace("{}",n[1])),
+X("Falling back to no-highlight mode for this block.",e)),t?n[1]:"no-highlight"}
+return t.split(/\s+/).find((e=>b(e)||O(e)))})(e);if(b(n))return
+;if(N("before:highlightElement",{el:e,language:n
+}),e.dataset.highlighted)return void console.log("Element previously highlighted. To highlight again, first unset `dataset.highlighted`.",e)
+;if(e.children.length>0&&(p.ignoreUnescapedHTML||(console.warn("One of your code blocks includes unescaped HTML. This is a potentially serious security risk."),
+console.warn("https://github.com/highlightjs/highlight.js/wiki/security"),
+console.warn("The element with unescaped HTML:"),
+console.warn(e)),p.throwUnescapedHTML))throw new J("One of your code blocks includes unescaped HTML.",e.innerHTML)
+;t=e;const i=t.textContent,o=n?m(i,{language:n,ignoreIllegals:!0}):x(i)
+;e.innerHTML=o.value,e.dataset.highlighted="yes",((e,t,n)=>{const i=t&&s[t]||n
+;e.classList.add("hljs"),e.classList.add("language-"+i)
+})(e,n,o.language),e.result={language:o.language,re:o.relevance,
+relevance:o.relevance},o.secondBest&&(e.secondBest={
+language:o.secondBest.language,relevance:o.secondBest.relevance
+}),N("after:highlightElement",{el:e,result:o,text:i})}let y=!1;function _(){
+"loading"!==document.readyState?document.querySelectorAll(p.cssSelector).forEach(w):y=!0
+}function O(e){return e=(e||"").toLowerCase(),i[e]||i[s[e]]}
+function v(e,{languageName:t}){"string"==typeof e&&(e=[e]),e.forEach((e=>{
+s[e.toLowerCase()]=t}))}function k(e){const t=O(e)
+;return t&&!t.disableAutodetect}function N(e,t){const n=e;o.forEach((e=>{
+e[n]&&e[n](t)}))}
+"undefined"!=typeof window&&window.addEventListener&&window.addEventListener("DOMContentLoaded",(()=>{
+y&&_()}),!1),Object.assign(n,{highlight:m,highlightAuto:x,highlightAll:_,
+highlightElement:w,
+highlightBlock:e=>(G("10.7.0","highlightBlock will be removed entirely in v12.0"),
+G("10.7.0","Please use highlightElement now."),w(e)),configure:e=>{p=Q(p,e)},
+initHighlighting:()=>{
+_(),G("10.6.0","initHighlighting() deprecated.  Use highlightAll() now.")},
+initHighlightingOnLoad:()=>{
+_(),G("10.6.0","initHighlightingOnLoad() deprecated.  Use highlightAll() now.")
+},registerLanguage:(e,t)=>{let s=null;try{s=t(n)}catch(t){
+if(W("Language definition for '{}' could not be registered.".replace("{}",e)),
+!r)throw t;W(t),s=l}
+s.name||(s.name=e),i[e]=s,s.rawDefinition=t.bind(null,n),s.aliases&&v(s.aliases,{
+languageName:e})},unregisterLanguage:e=>{delete i[e]
+;for(const t of Object.keys(s))s[t]===e&&delete s[t]},
+listLanguages:()=>Object.keys(i),getLanguage:O,registerAliases:v,
+autoDetection:k,inherit:Q,addPlugin:e=>{(e=>{
+e["before:highlightBlock"]&&!e["before:highlightElement"]&&(e["before:highlightElement"]=t=>{
+e["before:highlightBlock"](Object.assign({block:t.el},t))
+}),e["after:highlightBlock"]&&!e["after:highlightElement"]&&(e["after:highlightElement"]=t=>{
+e["after:highlightBlock"](Object.assign({block:t.el},t))})})(e),o.push(e)},
+removePlugin:e=>{const t=o.indexOf(e);-1!==t&&o.splice(t,1)}}),n.debugMode=()=>{
+r=!1},n.safeMode=()=>{r=!0},n.versionString="11.10.0",n.regex={concat:h,
+lookahead:g,either:f,optional:d,anyNumberOfTimes:u}
+;for(const t in j)"object"==typeof j[t]&&e(j[t]);return Object.assign(n,j),n
+},ne=te({});return ne.newInstance=()=>te({}),ne}()
+;"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=hljs);/*! `r` grammar compiled for Highlight.js 11.10.0 */
+(()=>{var e=(()=>{"use strict";return e=>{
+const a=e.regex,n=/(?:(?:[a-zA-Z]|\.[._a-zA-Z])[._a-zA-Z0-9]*)|\.(?!\d)/,i=a.either(/0[xX][0-9a-fA-F]+\.[0-9a-fA-F]*[pP][+-]?\d+i?/,/0[xX][0-9a-fA-F]+(?:[pP][+-]?\d+)?[Li]?/,/(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][+-]?\d+)?[Li]?/),s=/[=!<>:]=|\|\||&&|:::?|<-|<<-|->>|->|\|>|[-+*\/?!$&|:<=>@^~]|\*\*/,t=a.either(/[()]/,/[{}]/,/\[\[/,/[[\]]/,/\\/,/,/)
+;return{name:"R",keywords:{$pattern:n,
+keyword:"function if in break next repeat else for while",
+literal:"NULL NA TRUE FALSE Inf NaN NA_integer_|10 NA_real_|10 NA_character_|10 NA_complex_|10",
+built_in:"LETTERS letters month.abb month.name pi T F abs acos acosh all any anyNA Arg as.call as.character as.complex as.double as.environment as.integer as.logical as.null.default as.numeric as.raw asin asinh atan atanh attr attributes baseenv browser c call ceiling class Conj cos cosh cospi cummax cummin cumprod cumsum digamma dim dimnames emptyenv exp expression floor forceAndCall gamma gc.time globalenv Im interactive invisible is.array is.atomic is.call is.character is.complex is.double is.environment is.expression is.finite is.function is.infinite is.integer is.language is.list is.logical is.matrix is.na is.name is.nan is.null is.numeric is.object is.pairlist is.raw is.recursive is.single is.symbol lazyLoadDBfetch length lgamma list log max min missing Mod names nargs nzchar oldClass on.exit pos.to.env proc.time prod quote range Re rep retracemem return round seq_along seq_len seq.int sign signif sin sinh sinpi sqrt standardGeneric substitute sum switch tan tanh tanpi tracemem trigamma trunc unclass untracemem UseMethod xtfrm"
+},contains:[e.COMMENT(/#'/,/$/,{contains:[{scope:"doctag",match:/@examples/,
+starts:{end:a.lookahead(a.either(/\n^#'\s*(?=@[a-zA-Z]+)/,/\n^(?!#')/)),
+endsParent:!0}},{scope:"doctag",begin:"@param",end:/$/,contains:[{
+scope:"variable",variants:[{match:n},{match:/`(?:\\.|[^`\\])+`/}],endsParent:!0
+}]},{scope:"doctag",match:/@[a-zA-Z]+/},{scope:"keyword",match:/\\[a-zA-Z]+/}]
+}),e.HASH_COMMENT_MODE,{scope:"string",contains:[e.BACKSLASH_ESCAPE],
+variants:[e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\(/,end:/\)(-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\{/,end:/\}(-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\[/,end:/\](-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\(/,end:/\)(-*)'/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\{/,end:/\}(-*)'/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\[/,end:/\](-*)'/}),{begin:'"',end:'"',
+relevance:0},{begin:"'",end:"'",relevance:0}]},{relevance:0,variants:[{scope:{
+1:"operator",2:"number"},match:[s,i]},{scope:{1:"operator",2:"number"},
+match:[/%[^%]*%/,i]},{scope:{1:"punctuation",2:"number"},match:[t,i]},{scope:{
+2:"number"},match:[/[^a-zA-Z0-9._]|^/,i]}]},{scope:{3:"operator"},
+match:[n,/\s+/,/<-/,/\s+/]},{scope:"operator",relevance:0,variants:[{match:s},{
+match:/%[^%]*%/}]},{scope:"punctuation",relevance:0,match:t},{begin:"`",end:"`",
+contains:[{begin:/\\./}]}]}}})();hljs.registerLanguage("r",e)})();</script>
+<script>HTMLWidgets.widget({
+
+  name: 'profvis',
+
+  type: 'output',
+
+  initialize: function(el, width, height) {
+
+    return {
+      // TODO: add instance fields as required
+    };
+
+  },
+
+  renderValue: function(el, x, instance) {
+    profvis.render(el, x.message);
+  },
+
+  resize: function(el, width, height, instance) {
+
+  }
+
+});
+</script>
+
+</head>
+<body style="background-color: white;">
+<div id="htmlwidget_container">
+  <div class="profvis html-widget html-fill-item" id="htmlwidget-f9b31029362fa85527f7" style="width:960px;height:500px;"></div>
+</div>
+<script type="application/json" data-for="htmlwidget-f9b31029362fa85527f7">{"x":{"message":{"prof":{"time":[1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,10,10,11,11,11,11,11,11,12,12,12,12,12,13,13,14,14,15,15,16,16,16,17,17,17,17,17,18,18,19,19,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,27,27,28,28,29,29,30,30,31,31,32,32,33,33,34,34,35,35,36,36,37,37,37,37,37,37,37,38,38,39,39,40,40,41,41,42,42,42,42,42,42,42,43,43,44,44,44,44,44,44,44,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,46,46,46,46,46,46,46,46,47,47,48,48,48,48,48,48,49,49,49,49,49,49,49,49,49,49,49,50,50,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,54,54,54,54,54,54,54,54,54,54,54,54,54,54,54,54,54,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,55,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,57,57,57,57,57,57,57,57,57,57,57,57,57,57,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,61,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,89,89,89,89,89,89,89,90,90,91,91,91,91,91,91,91,92,92,92,92,92,92,93,93,93,93,93,94,94,95,95,95,95,95,95,95,95,95,95,95,95,95,95,96,96,96,96,96,97,97,97,97,97,97,97,98,98,99,99,100,100,100,100,100,100,100,101,101,101,102,102,102,102,102,102,102,102,103,103,103,103,103,104,104,104,104,104,105,105,105,105,105,105,105,106,106,107,107,107,107,107,107,107,107,107,108,108,108,108,108,108,109,109,109,109,109,109,109,109,110,110,110,110,110,110,110,110,110,110,110,110,110,110,110,111,111,112,112,112,112,112,112,112,113,113,113,113,113,113,114,114,115,115,115,115,115,115,115,116,116,116,116,116,116,116,117,117,117,117,117,117,117,117,118,118,118,119,119,120,120,120,120,121,121,122,122,122,122,122,122,122,123,123,124,124,124,124,124,124,124,124,125,125,126,126,126,126,126,126,126,126,126,126,126,127,127,127,127,127,127,127,128,128,128,129,129,130,130,131,131,132,132,133,133,134,134,135,135,136,136,136,136,136,136,136,136,137,137,138,138,139,139,140,140,141,141,142,142,143,143,144,144,145,145,146,146,147,147,148,148,149,149,149,149,150,150,151,151,152,152,153,153,154,154,155,155,156,156,157,157,158,158,159,159,160,160,160,160,160,160,160,160,161,161,162,162,163,163,164,164,164,164,165,165,166,166,166,166,166,166,166,166,167,167,167,167,167,167,168,168,168,168,168,168,168,168,169,169,169,169,169,169,170,170,170,170,170,170,170,171,171,171,171,171,171,172,172,172,172,172,172,172,172,172,173,173,173,174,174,174,175,175,176,176,177,177,178,178,179,179,180,180,180,180,180,180,180,180,180,181,182,182,182,183,183,183,183,183,183,183,184,184,184,184,184,184,184,184,184,184,185,185,186,186,187,187,188,188,188,188,188,188,188,188,188,189,189,189,189,189,189,189,189,189,190,190,191,191,191,191,191,191,191,192,192,192,192,192,192,192,192,193,193,193,193,193,193,193,194,194,195,195,195,195,195,195,195,196,196,196,196,196,196,196,196,197,197,197,197,197,197,198,198,199,199,199,199,199,199,199,200,200,200,200,200,200,200,201,201,202,202,203,203,204,204,204,204,205,205,206,206,207,207,208,208,208,209,209,210,210,211,211,212,212,212,212,212,212,212,212,213,213,214,214,215,215,216,216,217,217,217,217,217,217,217,217,217,218,218,218,219,219,220,220,221,221,222,222,223,223,223,224,224,225,225,226,226,227,227,227,228,228,228,228,228,228,228,229,229,229,229,229,229,230,230,230,230,230,230,230,231,231,231,231,231,231,232,232,232,232,232,232,232,233,233,234,234,234,234,234,234,234,234,235,235,235,236,236,236,236,236,237,237,238,238,239,239,240,240,241,241,242,242,243,243,244,244,245,245,246,246,247,247,247,248,248,249,249,250,250,251,251,252,252,252,252,252,252,252,253,253,254,254,254,254,254,255,255,255,255,255,255,255,256,256,256,256,256,257,257,257,257,257,257,257,258,258,258,258,258,258,258,259,259,259,259,259,259,260,260,260,260,260,260,260,260,261,261,261,261,261,261,261,261,261,261,261,261,261,261,262,262,262,262,262,262,262,263,263,263,263,263,263,264,264,265,265,265,265,266,266,266,266,266,266,267,267,267,267,267,267,267,267,268,268,268,268,268,268,268,268,268,269,269,269,269,269,269,270,270,271,271,271,271,271,271,271,271,272,272,272,272,272,272,272,272,273,273,273,273,273,273,273,273,273,273,274,274,274,274,274,274,275,275,276,276,277,277,277,277,277,277,277,278,278,278,278,278,278,278,278,279,279,279,279,279,279,279,280,280,281,281,281,281,281,281,282,282,282,282,282,283,283,283,283,283,283,283,283,283,284,284,284,284,284,285,286,286,286,286,286,286,286,287,287,287,287,287,287,287,288,288,288,288,288,288,288,289,289,289,289,289,289,289,290,290,290,290,290,290,291,291,291,291,291,292,292,293,293,293,293,293,293,293,293,294,294,295,295,296,296,297,297,297,297,297,297,297,297,297,297,297,297,297,297,298,298,298,298,298,298,298,298,299,299,299,299,299,299,299,299,299,299,300,300,300,300,300,300,300,300,300,300,300,300,300,301,301,302,302,303,303,304,304,305,305,306,306,307,307,307,307,308,308,309,309,310,310,311,311,312,312,313,313,314,314,314,315,315,316,316,317,317,318,318,319,319,320,320,320,320,320,320,320,320,321,321,322,322,323,323,324,324,325,325,326,326,327,327,327,327,327,327,327,327,328,328,329,329,330,330,331,331,332,332,333,333,334,334,334,334,335,335,335,335,335,336,336,336,336,336,336,336,337,337,337,337,337,337,337,337,338,338,339,339,339,339,339,339,339,339,339,340,340,341,341,342,342,343,343,343,343,343,343,343,343,343,343,343,343,343,344,344,344,344,344,344,344,344,344,344,344,344,344,345,345,345,345,345,345,345,346,346,346,346,346,346,346,346,347,347,347,347,347,347,347,347,348,348,348,348,348,348,348,348,349,349,350,350,351,351,351,351,351,351,352,352,352,352,352,352,352,352,352,352,353,353,353,354,354,354,354,354,354,354,354,354,354,355,355,355,356,356,356,356,356,356,356,356,357,357,358,358,359,359,360,360,360,360,360,361,361,362,362,362,362,362,362,362,362,363,363,363,363,363,363,363,364,364,365,365,365,366,366,366,366,366,367,367,368,368,369,369,370,370,370,370,370,370,370,370,371,371,371,371,371,371,371,372,372,372,373,373,374,374,374,374,374,374,374,374,375,375,376,376,377,377,377,377,377,377,377,377,378,378,379,379,379,379,379,379,380,380,381,381,382,382,383,383,383,383,383,383,383,384,384,385,385,386,386,387,387,388,388,389,389,390,390,391,391,392,392,392,393,393,394,394,395,395,396,396,397,397,398,398,398,398,398,398,398,398,399,399,400,400,400,401,401,401,401,401,401,401,401,402,402,403,403,404,404,405,405,406,406,407,407,408,408,409,409,410,410,411,411,412,412,413,413,414,414,415,415,416,416,417,417,418,418,419,419,419,419,419,419,419,419,420,420,421,421,422,422,423,423,424,424,424,424,424,424,424,424,424,425,425,426,426,427,427,427,427,427,428,428,429,429,429,429,429,430,430,431,431,432,432,433,433,434,434,435,435,435,435,435,435,435,436,436,436,437,437,437,437,437,437,437,437,438,438,438,438,438,438,438,439,439,440,440,441,441,441,441,441,441,441,441,442,442,443,443,443,443,443,443,443,443,444,444,444,444,444,444,444,444,445,445,446,446,446,446,446,446,446,446,446,446,446,446,447,447,447,447,447,447,447,447,448,448,449,449,450,450,450,450,450,450,450,451,451,451,451,451,451,451,451,452,452,452,452,452,452,452,452,453,453,453,453,453,453,453,454,454,454,454,454,454,454,454,454,454,454,454,455,455,455,455,455,455,455,455,455,456,456,456,456,456,456,456,457,457,458,458,459,459,459,459,459,459,459,460,460,460,460,460,460,460,460,460,460,460,461,461,462,462,462,462,462,462,462,462,463,463,464,464,464,464,464,464,464,464,464,465,465,465,465,465,465,465,465,465,466,466,467,467,467,467,467,467,467,467,468,468,468,468,468,468,468,468,469,469,470,470,471,471,472,472,473,473,474,474,474,474,474,474,475,475,476,476,477,477,478,478,479,479,480,480,481,481,482,482,483,483,484,484,485,485,486,486,487,487,488,488,489,489,490,490,490,490,490,490,490,490,491,491,492,492,493,493,494,494,495,495,496,496,497,497,497,498,498,499,499,500,500,501,501,502,502,503,503,504,504,505,505,506,506,507,507,508,508,509,509,510,510,511,511,512,512,512,512,512,513,513,513,513,513,514,514,514,514,514,514,514,514,514,514,515,515,515,515,515,515,515,515,515,515,515,515,515,515,516,516,516,516,516,516,516,516,516,516,516,516,516,516,517,517,517,517,517,517,517,518,518,519,519,520,520,520,520,520,520,520,520,520,521,521,521,521,521,521,521,521,521,522,522,523,523,523,523,523,523,523,524,524,524,524,524,524,524,524,525,525,526,526,526,526,526,526,526,526,527,527,528,528,528,528,528,528,528,529,529,529,529,529,529,529,529,530,530,530,530,530,530,530,530,530,531,531,531,532,532,533,533,533,533,533,533,533,533,534,534,534,534,534,534,534,534,535,535,536,536,536,536,536,536,536,536,536,536,537,537,538,538,539,539,540,540,540,540,540,541,541,542,542,542,542,542,542,542,543,543,543,543,543,543,544,544,545,545,545,545,545,545,545,545,546,546,546,546,546,546,546,547,547,548,548,549,549,549,549,549,549,549,549,549,549,549,549,550,550,551,551,552,552,552,552,552,552,552,553,553,554,554,555,555,555,555,555,555,555,555,556,556,557,557,558,558,558,558,558,558,558,559,559,559,559,559,559,559,559,559,559,559,559,559,560,560,561,561,562,562,563,563,564,564,565,565,566,566,567,567,568,568,568,568,568,568,569,569,570,570,571,571,572,572,572,572,572,573,573,574,574,575,575,576,576,577,577,578,578,579,579,580,580,581,581,582,582,582,582,583,583,584,584,584,584,584,585,585,585,586,586,587,587,588,588,589,589,589,589,589,589,589,590,590,590,590,590,590,591,591,592,592,593,593,594,594,595,595,596,596,597,597,598,598,599,599,600,600,601,601,602,602,603,603,604,604,605,605,606,606,607,607,608,608,609,609,610,610,610,610,610,610,610,610,610,611,611,612,612,613,613,613,613,613,613,613,614,614,614,614,614,614,615,615,615,615,615,615,615,615,616,616,616,616,616,616,616,616,617,617,617,617,617,617,617,618,618,619,619,619,619,619,619,619,619,620,620,621,621,622,622,622,622,622,622,622,622,623,623,623,623,624,624,624,624,624,624,624,625,625,626,626,626,626,626,626,626,626,627,627,627,627,627,627,627,628,628,628,628,628,628,628,629,629,630,630,630,630,630,630,630,630,631,631,632,632,633,633,634,634,634,634,634,634,634,634,634,634,635,635,635,635,635,635,635,636,636,636,636,636,636,636,636,636,636,637,637,637,637,637,637,637,637,638,638,638,638,638,638,638,638,638,638,638,638,639,639,640,640,640,640,640,640,640,640,641,641,641,641,641,642,642,643,643,643,643,643,643,643,643,643,643,643,643,643,643,644,644,644,645,645,646,646,646,646,646,646,646,646,646,646,647,647,647,647,647,647,647,648,648,649,649,649,649,649,649,649,649,650,650,651,651,651,651,651,651,652,652,653,653,654,654,654,654,654,655,655,655,655,655,655,655,656,656,657,657,657,657,657,657,657,657,658,658,658,658,658,658,658,658,659,659,660,660,661,661,661,661,661,661,661,661,661,661,662,662,663,663,664,664,665,665,666,666,667,667,668,668,669,669,669,670,670,671,671,672,672,673,673,674,674,675,675,676,676,676,676,676,676,676,676,677,677,678,678,679,679,680,680,680,680,680,680,680,680,681,681,682,682,683,683,683,683,683,683,683,683,684,684,685,685,686,686,687,687,688,688,689,689,689,689,689,689,689,690,690,691,691,692,692,693,693,693,693,693,693,693,693,694,694,695,695,696,696,696,696,696,696,696,697,697,697,697,697,698,698,698,698,698,698,698,698,698,698,698,698,699,699,699,699,699,700,700,701,701,702,702,703,703,703,703,703,703,703,704,704,704,704,704,704,704,704,704,704,704,704,704,705,705,705,705,705,705,705,705,706,706,707,707,707,707,708,708,709,709,710,710,710,710,710,710,710,710,710,711,711,711,711,711,711,711,711,712,712,712,712,712,712,712,713,713,714,714,714,714,715,715,715,715,715,715,715,715,716,716,716,716,716,716,716,716,716,717,717,717,717,717,717,717,717,717,718,718,718,718,718,718,718,719,719,719,719,719,719,719,719,719,719,719,719,720,720,720,720,720,720,720,720,720,720,720,721,721,721,721,721,721,721,722,722,722,722,722,722,722,722,723,723,724,724,724,724,724,724,724,724,724,725,725,726,726,727,727,727,727,727,727,727,727,728,728,728,728,728,729,729,729,730,730,731,731,732,732,732,732,732,732,732,733,733,733,733,733,733,734,734,735,735,735,735,735,735,735,735,736,736,737,737,737,738,738,739,739,739,739,739,739,739,739,739,739,740,740,740,740,740,740,741,741,742,742,742,742,742,742,743,743,743,743,743,744,744,744,744,744,744,744,744,744,745,745,745,745,745,745,745,745,746,746,746,746,746,746,746,746,746,746,746,747,747,747,747,747,747,747,747,748,748,749,749,749,749,749,749,749,750,750,751,751,752,752,753,753,754,754,755,755,755,755,755,755,755,755,756,756,757,757,757,757,757,757,757,757,758,758,759,759,760,760,760,760,760,761,761,762,762,763,763,764,764,765,765,765,766,766,767,767,768,768,769,769,770,770,770,770,770,771,771,772,772,772,772,772,772,772,772,773,773,774,774,775,775,776,776,776,777,777,777,778,778,778,778,778,778,778,778,778,778,778,778,778,779,779,779,779,779,779,780,780,780,780,780,780,780,781,781,782,782,782,782,782,782,782,782,783,783,784,784,784,784,784,785,785,786,786,787,787,788,788,789,789,790,790,791,791,792,792,793,793,794,794,795,795,796,796,797,797,798,798,799,799,800,800,801,801,802,802,802,802,803,803,803,803,803,803,803,804,804,804,804,804,804,804,804,804,805,805,805,805,805,805,805,805,806,806,806,806,806,806,806,807,807,808,808,808,808,808,808,808,808,808,808,809,809,809,809,809,809,809,809,810,810,810,810,810,810,810,810,811,811,811,811,811,811,811,811,812,812,812,812,812,812,812,812,813,813,813,813,813,813,813,813,814,814,814,814,814,814,814,814,815,815,815,815,815,815,815,815,816,816,816,816,816,816,816,816,817,817,817,817,817,817,817,817,818,818,818,818,818,818,818,818,819,819,820,820,820,820,820,820,820,820,820,820,820,820,820,820,821,821,822,822,823,823,823,823,823,823,823,824,824,825,825,825,825,825,826,826,827,827,827,827,827,827,827,827,828,828,829,829,829,829,829,829,829,829,830,830,830,831,831,831,831,831,831,831,832,832,833,833,833,833,833,833,833,833,834,834,834,834,834,834,834,835,835,835,835,835,835,835,835,835,835,835,835,836,836,836,837,837,837,837,837,837,837,838,838,839,839,839,839,839,839,839,839,840,840,840,840,840,840,841,841,841,841,841,841,841,841,842,842,842,843,843,843,843,843,843,843,843,844,844,844,844,845,845,846,846,846,846,847,847,847,847,847,847,847,848,848,848,848,848,848,848,848,848,848,848,849,849,849,849,849,849,849,850,850,850,850,850,850,850,850,850,850,850,851,851,851,851,851,851,851,852,852,853,853,854,854,855,855,856,856,856,856,856,856,856,856,857,857,857,857,857,857,857,858,858,859,859,859,859,859,859,859,859,859,859,859,859,860,860,861,861,861,861,861,861,862,862,863,863,864,864,865,865,866,866,867,867,868,868,868,868,868,868,868,869,869,870,870,871,871,872,872,873,873,874,874,875,875,876,876,876,877,877,878,878,879,879,880,880,881,881,882,882,883,883,884,884,884,885,885,886,886,887,887,888,888,888,889,889,890,890,891,891,892,892,893,893,894,894,895,895,896,896,897,897,898,898,899,899,900,900,900,900,901,901,902,902,903,903,903,903,903,903,903,903,904,904,904,904,904,904,904,905,905,905,905,905,905,905,906,906,906,906,906,906,906,907,907,908,908,909,909,910,910,910,910,911,911,912,912,912,912,912,912,912,912,912,912,912,912,912,912,913,913,913,913,913,913,913,913,914,914,914,914,914,914,914,914,915,915,916,916,916,916,916,916,916,916,917,917,917,917,917,917,917,917,918,918,919,919,920,920,921,921,921,921,921,921,921,922,923,923,924,924,924,924,924,925,925,925,925,925,925,925,926,926,926,926,926,926,926,926,927,927,927,927,927,927,927,927,927,927,928,928,928,928,928,928,928,928,929,929,930,930,930,931,931,931,931,931,931,931,931,932,932,933,933,933,933,933,933,933,933,934,934,934,934,934,934,934,934,934,935,935,936,936,937,937,937,937,937,937,937,937,937,938,938,938,938,938,938,938,938,938,938,939,939,939,939,939,940,940,941,941,941,941,941,941,941,942,942,942,942,942,942,943,943,943,943,943,943,943,943,944,944,944,944,944,944,944,944,945,945,946,946,947,947,948,948,949,949,949,950,950,951,951,952,952,953,953,953,954,954,955,955,956,956,957,957,958,958,959,959,960,960,960,960,960,961,961,962,962,963,963,964,964,964,964,964,965,965,965,965,965,965,966,966,966,966,966,966,967,967,968,968,968,968,968,968,968,969,969,970,970,971,971,971,971,971,971,971,971,972,972,972,972,972,972,972,972,973,973,974,974,975,975,976,976,977,977,978,978,979,979,980,980,981,981,982,982,983,983,983,983,983,983,983,984,984,985,985,986,986,987,987,988,988,989,989,990,990,990,990,990,990,990,991,991,991,991,991,991,991,991,991,992,992,992,992,993,993,994,994,994,994,994,994,995,995,996,996,996,996,996,996,997,997,997,997,997,997,997,997,997,998,998,999,999,999,999,999,999,999,999,999,999,999,999,1000,1000,1000,1000,1000,1000,1001,1001,1001,1001,1001,1002,1002,1002,1002,1002,1002,1003,1003,1004,1004,1004,1004,1004,1004,1004,1004,1005,1005,1005,1005,1005,1005,1005,1006,1006,1007,1007,1008,1008,1008,1008,1008,1008,1008,1008,1009,1009,1009,1009,1009,1009,1009,1009,1010,1010,1010,1010,1010,1010,1010,1010,1011,1011,1012,1012,1012,1012,1012,1012,1012,1013,1013,1014,1014,1015,1015,1015,1015,1015,1015,1015,1015,1016,1016,1017,1017,1017,1017,1017,1018,1018,1018,1018,1019,1019,1020,1020,1021,1021,1022,1022,1023,1023,1024,1024,1025,1025,1025,1025,1025,1026,1026,1026,1026,1026,1026,1026,1026,1027,1027,1027,1027,1027,1027,1027,1027,1028,1028,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1029,1030,1030,1030,1030,1030,1030,1030,1031,1031,1031,1031,1031,1031,1032,1032,1032,1033,1033,1033,1033,1033,1033,1033,1033,1034,1034,1034,1034,1034,1034,1034,1034,1035,1035,1036,1036,1037,1037,1038,1038,1039,1039,1040,1040,1041,1041,1041,1041,1042,1042,1043,1043,1044,1044,1045,1045,1046,1046,1047,1047,1048,1048,1049,1049,1050,1050,1051,1051,1051,1051,1051,1051,1051,1051,1052,1052,1053,1053,1054,1054,1054,1054,1054,1054,1054,1055,1055,1056,1056,1057,1057,1058,1058,1059,1059,1059,1059,1059,1059,1059,1059,1060,1060,1061,1061,1061,1061,1061,1061,1061,1061,1062,1062,1063,1063,1064,1064,1065,1065,1065,1065,1065,1065,1065,1065,1065,1065,1066,1066,1067,1067,1068,1068,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1069,1070,1070,1071,1071,1071,1071,1071,1071,1071,1072,1072,1073,1073,1074,1074,1074,1074,1074,1074,1075,1075,1075,1076,1076,1077,1077,1078,1078,1078,1078,1078,1078,1078,1079,1079,1079,1079,1080,1080,1080,1080,1080,1081,1081,1081,1082,1082,1082,1083,1083,1083,1083,1083,1083,1083,1083,1084,1084,1084,1084,1084,1084,1085,1085,1085,1085,1085,1085,1085,1086,1086,1087,1087,1087,1087,1087,1087,1087,1088,1088,1089,1089,1090,1090,1091,1091,1092,1092,1093,1093,1094,1094,1094,1094,1094,1094,1094,1094,1095,1095,1095,1095,1095,1095,1096,1096,1096,1096,1096,1096,1096,1096,1096,1097,1097,1097,1097,1097,1097,1097,1098,1098,1098,1098,1098,1098,1098,1098,1098,1098,1098,1099,1099,1099,1099,1099,1099,1099,1099,1100,1100,1100,1100,1100,1100,1100,1101,1101,1101,1102,1102,1102,1102,1102,1102,1102,1102,1103,1103,1103,1103,1103,1103,1103,1103,1104,1104,1105,1105,1105,1105,1105,1106,1106,1107,1107,1108,1108,1109,1109,1110,1110,1110,1110,1111,1111,1112,1112,1113,1113,1114,1114,1115,1115,1115,1115,1115,1115,1115,1115,1116,1116,1117,1117,1118,1118,1119,1119,1120,1120,1121,1121,1122,1122,1123,1123,1124,1124,1124,1124,1124,1124,1124,1125,1125,1126,1126,1127,1127,1128,1128,1129,1129,1130,1130,1131,1131,1131,1131,1131,1131,1132,1132,1132,1133,1133,1133,1133,1133,1133,1133,1134,1134,1134,1134,1134,1134,1135,1135,1135,1136,1136,1136,1136,1136,1136,1136,1136,1137,1137,1138,1138,1139,1139,1140,1140,1141,1141,1142,1142,1143,1143,1144,1144,1145,1145,1146,1146,1147,1147,1148,1148,1149,1149,1149,1149,1149,1149,1149,1150,1150,1151,1151,1152,1152,1153,1153,1154,1154,1155,1155,1156,1156,1156,1157,1157,1157,1157,1157,1157,1157,1158,1158,1159,1159,1160,1160,1160,1160,1160,1160,1160,1161,1161,1161,1161,1161,1161,1161,1162,1162,1162,1162,1162,1162,1162,1162,1162,1163,1163,1164,1164,1164,1164,1164,1164,1164,1165,1165,1165,1165,1165,1166,1166,1166,1166,1166,1166,1166,1166,1167,1167,1167,1167,1167,1167,1167,1168,1168,1168,1169,1169,1169,1169,1169,1169,1170,1170,1170,1170,1170,1170,1170,1170,1171,1171,1172,1172,1172,1172,1172,1172,1172,1173,1173,1173,1173,1173,1173,1173,1174,1174,1174,1174,1174,1174,1174,1174,1174,1175,1175,1175,1175,1175,1175,1176,1176,1177,1177,1178,1178,1179,1179,1179,1179,1179,1179,1179,1180,1180,1180,1180,1180,1180,1180,1180,1180,1181,1181,1182,1182,1182,1182,1182,1182,1182,1182,1182,1183,1183,1183,1183,1183,1184,1184,1185,1185,1186,1186,1187,1187,1187,1187,1187,1187,1187,1187,1188,1188,1188,1188,1188,1188,1188,1188,1188,1188,1188,1188,1189,1189,1190,1190,1190,1190,1190,1190,1190,1191,1191,1192,1192,1192,1193,1193,1194,1194,1195,1195,1195,1196,1196,1197,1197,1198,1198,1199,1199,1200,1200,1201,1201,1202,1202,1202,1202,1203,1203,1204,1204,1204,1204,1204,1204,1204,1204,1205,1205,1206,1206,1207,1207,1208,1208,1209,1209,1210,1210,1211,1211,1211,1211,1211,1211,1211,1211,1212,1212,1213,1213,1214,1214,1214,1215,1215,1216,1216,1217,1217,1218,1218,1219,1219,1220,1220,1221,1221,1222,1222,1222,1223,1223,1224,1224,1225,1225,1226,1226,1227,1227,1228,1228,1229,1229,1230,1230,1230,1231,1231,1232,1232,1233,1233,1234,1234,1235,1235,1236,1236,1237,1237,1237,1237,1237,1238,1238,1239,1239,1240,1240,1240,1240,1240,1241,1241,1241,1241,1241,1241,1241,1242,1242,1242,1242,1242,1242,1242,1242,1242,1242,1243,1243,1243,1243,1243,1243,1243,1243,1243,1244,1244,1244,1244,1244,1244,1244,1245,1245,1245,1245,1245,1245,1245,1245,1245,1246,1246,1246,1246,1246,1246,1246,1247,1247,1247,1247,1248,1248,1248,1248,1248,1248,1248,1248,1249,1249,1249,1249,1249,1249,1249,1250,1250,1250,1250,1250,1250,1250,1250,1251,1251,1252,1252,1253,1253,1254,1254,1254,1254,1254,1254,1254,1254,1254,1254,1255,1255,1256,1256,1256,1256,1257,1257,1257,1257,1257,1258,1258,1258,1258,1258,1258,1258,1258,1259,1259,1259,1259,1259,1259,1259,1259,1259,1259,1260,1260,1260,1260,1260,1260,1260,1261,1261,1261,1262,1262,1263,1263,1264,1264,1264,1264,1264,1265,1265,1265,1265,1265,1265,1265,1265,1266,1266,1267,1267,1267,1267,1267,1267,1267,1267,1268,1268,1269,1269,1269,1269,1269,1269,1269,1269,1269,1269,1269,1269,1269,1270,1270,1270,1270,1270,1270,1270,1270,1270,1270,1270,1270,1270,1271,1271,1271,1271,1271,1271,1271,1272,1272,1272,1273,1273,1274,1274,1274,1274,1274,1275,1275,1275,1275,1275,1275,1275,1275,1276,1276,1276,1276,1276,1277,1277,1278,1278,1278,1279,1279,1280,1280,1280,1280,1280,1280,1281,1281,1282,1282,1283,1283,1284,1284,1284,1284,1284,1284,1284,1284,1285,1285,1286,1286,1287,1287,1288,1288,1288,1289,1289,1290,1290,1291,1291,1291,1291,1291,1291,1291,1291,1292,1292,1293,1293,1294,1294,1295,1295,1295,1295,1295,1295,1295,1295,1296,1296,1296,1296,1296,1297,1297,1297,1297,1297,1297,1297,1297,1298,1298,1298,1298,1298,1298,1298,1299,1299,1300,1300,1300,1300,1301,1301,1301,1302,1302,1302,1302,1302,1303,1303,1303,1303,1303,1304,1304,1305,1305,1306,1306,1307,1307,1308,1308,1309,1309,1310,1310,1311,1311,1312,1312,1313,1313,1314,1314,1315,1315,1315,1315,1315,1315,1315,1316,1316,1317,1317,1318,1318,1319,1319,1320,1320,1320,1320,1320,1320,1320,1321,1321,1321,1321,1321,1321,1321,1321,1322,1322,1322,1322,1322,1322,1322,1322,1323,1323,1323,1323,1324,1324,1324,1324,1324,1324,1324,1325,1325,1325,1325,1325,1325,1326,1326,1327,1327,1327,1327,1327,1327,1328,1328,1328,1328,1328,1328,1328,1328,1329,1329,1329,1329,1329,1330,1330,1331,1331,1331,1331,1331,1331,1332,1332,1332,1332,1332,1332,1333,1333,1333,1333,1333,1333,1333,1333,1334,1334,1334,1334,1334,1334,1334,1335,1335,1335,1335,1335,1335,1335,1335,1335,1336,1336,1336,1336,1336,1336,1336,1337,1337,1337,1337,1337,1337,1337,1338,1338,1338,1338,1338,1338,1338,1338,1339,1339,1339,1339,1339,1339,1339,1339,1339,1339,1339,1339,1340,1340,1340,1340,1340,1340,1340,1340,1340,1341,1341,1341,1341,1341,1341,1341,1342,1342,1343,1343,1343,1343,1343,1343,1343,1344,1344,1344,1344,1344,1344,1344,1344,1344,1344,1345,1345,1345,1345,1345,1345,1346,1346,1346,1346,1346,1346,1346,1346,1347,1347,1347,1347,1347,1347,1348,1349,1349,1349,1349,1349,1349,1349,1350,1350,1350,1350,1350,1350,1350,1350,1351,1351,1352,1352,1352,1352,1352,1352,1352,1352,1353,1353,1353,1353,1354,1354,1355,1355,1355,1355,1355,1355,1355,1355,1356,1356,1356,1357,1357,1358,1358,1358,1358,1358,1358,1358,1358,1358,1358,1358,1358,1358,1359,1359,1359,1360,1360,1361,1361,1362,1362,1363,1363,1364,1364,1365,1365,1365,1365,1365,1365,1365,1365,1366,1366,1367,1367,1368,1368,1369,1369,1370,1370,1371,1371,1372,1372,1373,1373,1373,1374,1374,1375,1375,1376,1376,1377,1377,1378,1378,1379,1379,1380,1380,1381,1381,1382,1382,1383,1383,1383,1384,1384,1385,1385,1386,1386,1387,1387,1388,1388,1389,1389,1389,1389,1389,1389,1389,1389,1390,1390,1391,1391,1391,1391,1391,1391,1392,1392,1393,1393,1394,1394,1395,1395,1396,1396,1397,1397,1398,1398,1399,1399,1399,1399,1399,1400,1400,1400,1400,1400,1400,1401,1401,1401,1401,1401,1401,1401,1402,1402,1402,1402,1402,1402,1402,1403,1403,1403,1403,1403,1403,1404,1404,1405,1405,1405,1405,1405,1406,1406,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1407,1408,1408,1409,1409,1409,1409,1409,1410,1410,1411,1411,1412,1412,1413,1413,1413,1414,1414,1414,1414,1415,1415,1415,1415,1415,1416,1416,1416,1416,1416,1416,1416,1417,1417,1418,1418,1419,1419,1419,1419,1419,1419,1419,1419,1419,1419,1419,1420,1420,1420,1421,1421,1421,1422,1422,1423,1423,1423,1424,1424,1425,1425,1425,1425,1425,1425,1426,1426,1427,1427,1427,1427,1427,1427,1427,1427,1427,1427,1427,1428,1428,1429,1429,1430,1430,1430,1430,1431,1431,1431,1432,1432,1432,1432,1432,1432,1433,1433,1434,1434,1435,1435,1435,1436,1436,1437,1437,1437,1437,1437,1437,1438,1438,1439,1439,1440,1440,1441,1441,1442,1442,1443,1443,1444,1444,1445,1445,1446,1446,1447,1447,1448,1448,1449,1449,1449,1449,1449,1449,1449,1449,1450,1450,1451,1451,1451,1451,1451,1451,1451,1452,1452,1453,1453,1454,1454,1455,1455,1456,1456,1456,1456,1457,1457,1458,1458,1459,1459,1460,1460,1461,1461,1462,1462,1462,1462,1462,1462,1462,1463,1463,1463,1463,1463,1463,1464,1464,1464,1464,1465,1465,1465,1465,1465,1465,1465,1465,1466,1466,1466,1466,1466,1466,1467,1467,1467,1467,1467,1467,1467,1467,1468,1468,1468,1469,1469,1470,1470,1471,1471,1472,1472,1473,1473,1474,1474,1475,1475,1476,1476,1477,1477,1478,1478,1479,1479,1480,1480,1481,1481,1482,1482,1482,1482,1482,1482,1482,1482,1482,1483,1483,1484,1484,1485,1485,1486,1486,1487,1487,1487,1488,1488,1488,1488,1488,1488,1489,1489,1490,1490,1490,1490,1491,1491,1491,1491,1491,1491,1491,1491,1492,1492,1492,1492,1492,1492,1493,1493,1493,1493,1493,1493,1493,1493,1494,1494,1494,1494,1494,1494,1494,1494,1495,1495,1496,1496,1497,1497,1498,1498,1499,1499,1499,1499,1499,1499,1499,1499,1499,1499,1499,1499,1500,1500,1500,1500,1500,1500,1500,1500,1501,1501,1501,1501,1501,1501,1501,1501,1501,1501,1501,1502,1502,1503,1503,1503,1503,1503,1503,1503,1503,1504,1504,1505,1505,1505,1505,1505,1505,1505,1506,1506,1506,1506,1506,1506,1507,1507,1508,1508,1508,1509,1509,1509,1509,1509,1509,1509,1509,1509,1509,1509,1510,1510,1511,1511,1511,1511,1511,1512,1512,1512,1512,1512,1512,1512,1512,1513,1513,1514,1514,1514,1514,1514,1515,1515,1516,1516,1516,1516,1516,1516,1516,1516,1516,1517,1517,1517,1517,1517,1517,1518,1518,1518,1518,1518,1518,1518,1518,1519,1519,1520,1520,1520,1520,1521,1521,1522,1522,1522,1522,1522,1522,1522,1522,1522,1523,1523,1523,1524,1524,1524,1524,1524,1525,1525,1526,1526,1526,1526,1526,1527,1527,1528,1528,1528,1528,1528,1528,1528,1528,1529,1529,1530,1530,1531,1531,1532,1532,1532,1532,1532,1532,1532,1532,1532,1532,1532,1532,1533,1533,1533,1534,1534,1535,1535,1536,1536,1537,1537,1538,1538,1539,1539,1540,1540,1541,1541,1542,1542,1542,1542,1542,1542,1542,1543,1543,1544,1544,1545,1545,1546,1546,1547,1547,1548,1548,1548,1548,1549,1549,1550,1550,1550,1550,1550,1550,1550,1550,1551,1551,1552,1552,1553,1553,1554,1554,1555,1555,1556,1556,1557,1557,1558,1558,1559,1559,1559,1560,1560,1561,1561,1562,1562,1563,1563,1564,1564,1565,1565,1566,1566,1567,1567,1568,1568,1568,1568,1568,1568,1569,1569,1570,1570,1571,1571,1572,1572,1573,1573,1574,1574,1575,1575,1576,1576,1576,1577,1577,1577,1577,1577,1577,1577,1577,1578,1578,1578,1578,1578,1578,1578,1579,1579,1579,1579,1579,1580,1580,1581,1581,1582,1582,1583,1583,1584,1584,1585,1585,1586,1586,1586,1586,1586,1586,1586,1587,1587,1587,1587,1587,1588,1588,1589,1589,1590,1590,1590,1590,1590,1591,1591,1591,1591,1591,1591,1591,1591,1591,1592,1592,1592,1592,1592,1593,1593,1593,1593,1593,1593,1593,1593,1594,1594,1594,1594,1594,1594,1594,1595,1595,1595,1596,1596,1596,1596,1596,1596,1596,1597,1597,1597,1597,1597,1597,1597,1597,1597,1598,1598,1599,1599,1599,1599,1599,1599,1599,1600,1600,1600,1600,1600,1600,1601,1601,1602,1602,1602,1602,1602,1602,1603,1603,1603,1603,1603,1603,1603,1603,1603,1603,1604,1604,1604,1604,1604,1604,1604,1604,1604,1605,1605,1605,1605,1605,1605,1605,1605,1606,1606,1606,1606,1606,1606,1606,1606,1607,1607,1608,1608,1609,1609,1609,1609,1609,1609,1609,1609,1610,1610,1611,1611,1612,1612,1613,1613,1614,1614,1614,1614,1614,1615,1615,1615,1615,1615,1615,1615,1616,1616,1617,1617,1617,1617,1618,1618,1618,1618,1618,1618,1618,1618,1619,1619,1619,1619,1619,1619,1619,1619,1619,1620,1620,1621,1621,1621,1621,1621,1621,1621,1622,1622,1622,1622,1622,1622,1623,1623,1623,1623,1623,1623,1623,1623,1624,1624,1625,1625,1626,1626,1627,1627,1628,1628,1629,1629,1629,1629,1629,1629,1629,1630,1630,1631,1631,1631,1631,1631,1631,1631,1631,1631,1632,1632,1632,1632,1632,1632,1632,1633,1633,1634,1634,1635,1635,1636,1636,1636,1637,1637,1638,1638,1639,1639,1640,1640,1641,1641,1641,1641,1641,1641,1641,1641,1641,1642,1642,1643,1643,1643,1644,1644,1644,1644,1644,1644,1644,1644,1645,1645,1646,1646,1646,1646,1646,1646,1647,1647,1647,1647,1647,1647,1647,1647,1647,1648,1648,1648,1648,1648,1648,1649,1649,1649,1649,1649,1649,1649,1650,1650,1650,1650,1650,1650,1650,1651,1651,1652,1652,1653,1653,1654,1654,1654,1654,1654,1654,1655,1655,1656,1656,1657,1657,1658,1658,1659,1659,1660,1660,1661,1661,1662,1662,1663,1663,1664,1664,1665,1665,1666,1666,1666,1666,1667,1667,1668,1668,1669,1669,1669,1669,1670,1670,1671,1671,1671,1671,1671,1671,1671,1672,1672,1673,1673,1674,1674,1674,1674,1674,1674,1675,1675,1675,1675,1675,1675,1675,1675,1675,1675,1676,1676,1677,1677,1678,1678,1678,1678,1678,1678,1678,1678,1679,1679,1679,1679,1680,1680,1680,1680,1680,1680,1680,1680,1680,1680,1680,1680,1681,1681,1681,1681,1681,1681,1681,1682,1682,1683,1683,1683,1683,1683,1683,1683,1683,1684,1684,1685,1685,1685,1685,1685,1685,1685,1686,1686,1687,1687,1687,1687,1687,1688,1688,1688,1688,1688,1688,1688,1689,1689,1690,1690,1690,1690,1690,1690,1690,1690,1691,1691,1692,1692,1693,1693,1694,1694,1695,1695,1695,1695,1695,1695,1695,1696,1696,1696,1696,1696,1696,1696,1697,1697,1698,1698,1698,1698,1698,1698,1698,1698,1699,1699,1699,1699,1699,1699,1699,1700,1700,1700,1700,1700,1700,1700,1700,1701,1701,1702,1702,1702,1702,1702,1702,1702,1702,1702,1702,1703,1703,1704,1704,1705,1705,1705,1705,1705,1705,1706,1706,1707,1707,1707,1707,1707,1707,1707,1707,1707,1707,1707,1707,1707,1707,1708,1708,1708,1708,1708,1709,1709,1709,1709,1709,1709,1709,1709,1709,1709,1709,1709,1709,1710,1710,1710,1710,1710,1711,1711,1711,1712,1712,1712,1712,1712,1712,1712,1712,1712,1713,1713,1714,1714,1714,1714,1714,1715,1715,1716,1716,1717,1717,1718,1718,1719,1719,1720,1720,1720,1720,1720,1720,1720,1720,1721,1721,1722,1722,1723,1723,1724,1724,1725,1725,1726,1726,1727,1727,1728,1728,1729,1729,1730,1730,1731,1731,1731,1731,1731,1731,1731,1732,1732,1733,1733,1734,1734,1735,1735,1736,1736,1737,1737,1738,1738,1739,1739,1739,1739,1739,1739,1739,1739,1740,1740,1741,1741,1742,1742,1743,1743,1744,1744,1745,1745,1746,1746,1746,1746,1746,1746,1746,1746,1747,1747,1748,1748,1748,1749,1749,1750,1750,1751,1751,1752,1752,1753,1753,1754,1754,1754,1754,1755,1755,1756,1756,1756,1756,1756,1757,1757,1757,1757,1757,1757,1757,1757,1757,1757,1758,1758,1758,1758,1758,1758,1759,1759,1759,1759,1759,1759,1759,1759,1760,1760,1760,1760,1760,1760,1760,1760,1761,1761,1761,1761,1761,1761,1761,1761,1761,1762,1762,1762,1762,1762,1762,1762,1762,1762,1762,1763,1763,1764,1764,1764,1765,1765,1766,1766,1767,1767,1768,1768,1768,1768,1768,1768,1768,1768,1769,1769,1769,1769,1769,1769,1769,1769,1770,1770,1770,1770,1770,1770,1770,1770,1771,1771,1771,1772,1772,1772,1772,1772,1772,1772,1772,1773,1773,1773,1774,1774,1774,1774,1774,1774,1774,1774,1775,1775,1776,1776,1776,1777,1777,1777,1778,1778,1778,1779,1779,1779,1780,1780,1780,1781,1781,1781,1782,1782,1782,1783,1783,1783,1784,1784,1784,1785,1785,1785,1786,1786,1786,1787,1787,1788,1788,1789,1789,1790,1790,1791,1791,1792,1792,1792,1792,1792,1792,1792,1793,1793,1793,1793,1793,1793,1793,1793,1793,1794,1794,1794,1794,1794,1794,1794,1795,1795,1796,1796,1797,1797,1797,1797,1797,1797,1798,1798,1799,1799,1800,1800,1800,1800,1800,1800,1800,1801,1801,1801,1801,1801,1801,1801,1801,1801,1802,1802,1802,1802,1802,1802,1802,1802,1803,1803,1803,1803,1803,1803,1803,1803,1804,1804,1804,1804,1804,1804,1804,1804,1805,1805,1806,1806,1807,1807,1808,1808,1809,1809,1810,1810,1811,1811,1812,1812,1813,1813,1813,1813,1813,1813,1813,1813,1814,1814,1815,1815,1815,1815,1815,1815,1815,1815,1815,1816,1816,1816,1816,1816,1817,1817,1818,1818,1819,1819,1820,1820,1820,1820,1820,1821,1821,1822,1822,1823,1823,1824,1824,1825,1825,1825,1825,1825,1825,1825,1826,1826,1826,1826,1826,1826,1826,1827,1827,1827,1827,1827,1827,1827,1828,1828,1829,1829,1829,1829,1829,1829,1830,1830,1831,1831,1832,1832,1833,1833,1834,1834,1835,1835,1836,1836,1837,1837,1838,1838,1839,1839,1840,1840,1841,1841,1842,1842,1843,1843,1844,1844,1844,1845,1845,1846,1846,1847,1847,1848,1848,1849,1849,1850,1850,1850,1850,1850,1850,1850,1851,1851,1851,1851,1852,1852,1852,1853,1853,1853,1853,1853,1853,1853,1853,1854,1854,1854,1854,1855,1855,1855,1855,1855,1855,1855,1855,1856,1856,1857,1857,1858,1858,1858,1858,1858,1858,1858,1858,1859,1859,1859,1859,1860,1860,1860,1860,1860,1860,1861,1861,1861,1861,1861,1861,1861,1862,1862,1862,1862,1862,1862,1862,1862,1862,1863,1863,1863,1863,1863,1863,1863,1863,1864,1864,1865,1865,1865,1865,1865,1865,1865,1865,1865,1865,1865,1865,1865,1866,1866,1867,1867,1867,1867,1867,1868,1868,1868,1868,1868,1868,1868,1869,1869,1869,1869,1869,1870,1870,1871,1871,1871,1871,1871,1871,1871,1872,1872,1872,1872,1872,1872,1872,1873,1873,1874,1874,1874,1874,1874,1874,1874,1874,1874,1875,1875,1875,1875,1875,1875,1875,1876,1876,1877,1877,1877,1877,1877,1877,1878,1878,1879,1879,1879,1879,1879,1879,1879,1879,1880,1880,1881,1881,1882,1882,1882,1882,1882,1882,1882,1883,1883,1883,1883,1883,1883,1883,1884,1884,1884,1884,1885,1885,1886,1886,1886,1886,1887,1887,1887,1888,1888,1888,1888,1888,1888,1888,1889,1889,1889,1889,1889,1889,1889,1890,1890,1890,1890,1890,1890,1890,1890,1891,1891,1891,1891,1892,1892,1892,1892,1893,1893,1893,1893,1894,1894,1894,1894,1894,1894,1894,1894,1894,1894,1895,1895,1896,1896,1897,1897,1898,1898,1899,1899,1900,1900,1901,1901,1901,1901,1901,1901,1901,1901,1902,1902,1903,1903,1903,1903,1904,1904,1905,1905,1906,1906,1907,1907,1908,1908,1909,1909,1910,1910,1910,1910,1911,1911,1912,1912,1913,1913,1914,1914,1915,1915,1916,1916,1917,1917,1918,1918,1919,1919,1920,1920,1921,1921,1921,1921,1921,1921,1921,1922,1922,1923,1923,1924,1924,1925,1925,1926,1926,1927,1927,1928,1928,1929,1929,1929,1929,1930,1930,1931,1931,1932,1932,1933,1933,1934,1934,1935,1935,1936,1936,1937,1937,1938,1938,1938,1938,1938,1938,1938,1939,1939,1939,1939,1939,1939,1939,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1940,1941,1941,1941,1941,1941,1941,1941,1941,1941,1942,1942,1942,1942,1942,1942,1942,1943,1943,1944,1944,1944,1944,1944,1944,1944,1944,1944,1945,1945,1945,1945,1946,1946,1946,1946,1947,1947,1947,1947,1947,1947,1947,1947,1948,1948,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1950,1950,1950,1950,1950,1950,1950,1951,1951,1951,1951,1951,1951,1951,1952,1952,1952,1952,1953,1953,1954,1954,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1958,1958,1958,1958,1958,1959,1959,1959,1959,1959,1959,1959,1959,1959,1959,1960,1960,1960,1960,1960,1960,1960,1960,1961,1961,1961,1961,1961,1961,1961,1962,1962,1962,1962,1962,1962,1962,1962,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1964,1964,1964,1964,1964,1964,1964,1965,1965,1965,1965,1965,1965,1965,1965,1966,1966,1966,1966,1966,1966,1967,1967,1967,1967,1967,1967,1967,1967,1967,1968,1968,1968,1968,1968,1968,1968,1968,1969,1969,1970,1970,1970,1970,1970,1970,1970,1970,1971,1971,1971,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1973,1974,1974,1974,1974,1974,1974,1974,1975,1975,1975,1976,1976,1976,1976,1976,1976,1976,1976,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1977,1978,1978,1978,1978,1978,1978,1979,1979,1979,1979,1979,1979,1979,1979,1980,1980,1980,1980,1980,1980,1980,1981,1981,1981,1981,1981,1981,1982,1982,1983,1983,1984,1984,1985,1985,1985,1986,1986,1987,1987,1988,1988,1989,1989,1989,1990,1990,1991,1991,1992,1992,1993,1993,1993,1993,1993,1993,1993,1993,1994,1994,1995,1995,1996,1996,1997,1997,1998,1998,1998,1998,1998,1999,1999,2000,2000,2001,2001,2002,2002,2003,2003,2004,2004,2005,2005,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2007,2007,2008,2008,2009,2009,2010,2010,2011,2011,2012,2012,2013,2013,2014,2014,2015,2015,2016,2016,2017,2017,2018,2018,2019,2019,2020,2020,2021,2021,2022,2022,2022,2022,2022,2022,2022,2023,2023,2024,2024,2025,2025,2026,2026,2027,2027,2027,2027,2027,2027,2027,2028,2028,2029,2029,2029,2029,2029,2029,2029,2030,2030,2031,2031,2031,2031,2031,2031,2031,2031,2031,2032,2032,2032,2032,2032,2032,2032,2032,2032,2032,2032,2033,2034,2034,2035,2035,2035,2035,2036,2036,2036,2036,2036,2037,2037,2037,2037,2037,2037,2037,2038,2038,2038,2038,2038,2038,2038,2039,2039,2039,2039,2039,2039,2039,2040,2040,2041,2041,2041,2041,2041,2041,2041,2041,2042,2042,2042,2042,2042,2042,2042,2042,2043,2043,2043,2043,2043,2043,2043,2043,2044,2044,2045,2045,2045,2045,2045,2045,2045,2045,2046,2046,2046,2046,2046,2046,2047,2047,2047,2047,2047,2047,2047,2048,2048,2048,2048,2048,2048,2048,2049,2049,2049,2049,2049,2049,2049,2049,2049,2049,2049,2050,2050,2050,2050,2050,2050,2051,2051,2051,2051,2051,2051,2051,2051,2051,2051,2051,2051,2052,2052,2053,2053,2053,2053,2053,2053,2053,2053,2054,2054,2055,2055,2056,2056,2056,2056,2056,2056,2056,2057,2057,2057,2057,2058,2058,2058,2058,2058,2058,2059,2059,2060,2060,2060,2060,2060,2061,2061,2061,2061,2062,2062,2062,2062,2062,2062,2062,2062,2062,2063,2063,2064,2064,2065,2065,2066,2066,2067,2067,2068,2068,2069,2069,2070,2070,2071,2071,2072,2072,2073,2073,2074,2074,2075,2075,2076,2076,2077,2077,2078,2078,2079,2079,2079,2079,2079,2079,2079,2080,2080,2081,2081,2082,2082,2083,2083,2084,2084,2085,2085,2086,2086,2086,2086,2086,2086,2086,2086,2087,2087,2088,2088,2089,2089,2090,2090,2091,2091,2092,2092,2093,2093,2094,2094,2094,2094,2094,2094,2095,2095,2096,2096,2096,2097,2097,2098,2098,2099,2099,2100,2100,2101,2101,2102,2102,2103,2103,2103,2103,2103,2103,2103,2103,2104,2104,2105,2105,2105,2105,2105,2105,2105,2106,2106,2106,2106,2106,2106,2106,2107,2107,2107,2107,2107,2107,2107,2107,2107,2108,2108,2108,2108,2109,2109,2109,2109,2109,2109,2109,2110,2110,2110,2110,2110,2110,2111,2111,2111,2111,2111,2111,2111,2111,2111,2112,2112,2113,2114,2114,2114,2114,2114,2114,2114,2114,2115,2115,2115,2115,2115,2115,2115,2115,2115,2115,2116,2116,2117,2117,2117,2117,2117,2117,2117,2118,2118,2119,2119,2119,2119,2120,2120,2120,2120,2120,2120,2120,2121,2121,2121,2122,2122,2122,2122,2122,2122,2122,2123,2123,2123,2123,2123,2123,2123,2123,2123,2123,2124,2124,2125,2125,2125,2125,2125,2125,2125,2126,2126,2127,2127,2127,2127,2127,2127,2127,2128,2128,2128,2128,2128,2128,2128,2128,2129,2129,2130,2130,2130,2130,2130,2130,2131,2131,2132,2132,2132,2132,2132,2132,2132,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2133,2134,2134,2134,2134,2134,2134,2134,2134,2134,2134,2134,2134,2135,2135,2136,2136,2136,2136,2136,2137,2137,2137,2137,2137,2137,2137,2137,2137,2138,2138,2138,2139,2140,2140,2140,2140,2140,2140,2140,2141,2141,2141,2141,2141,2142,2142,2143,2143,2144,2144,2145,2145,2145,2145,2145,2145,2145,2146,2146,2147,2147,2147,2147,2147,2147,2148,2148,2149,2149,2149,2149,2150,2150,2151,2151,2152,2152,2153,2153,2153,2154,2154,2155,2155,2156,2156,2157,2157,2157,2157,2157,2157,2157,2158,2158,2159,2159,2160,2160,2161],"depth":[3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,3,2,1,5,4,3,2,1,2,1,2,1,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,72,71,70,69,68,67,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,68,67,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,2,1,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,4,3,2,1,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,1,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,3,2,1,10,9,8,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,3,2,1,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,5,4,3,2,1,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,3,2,1,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,4,3,2,1,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,3,2,1,2,1,2,1,7,6,5,4,3,2,1,4,3,2,1,5,4,3,2,1,3,2,1,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,3,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,3,2,1,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,2,1,8,7,6,5,4,3,2,1,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,3,2,1,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,3,2,1,3,2,1,2,1,3,2,1,2,1,6,5,4,3,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,4,3,2,1,3,2,1,6,5,4,3,2,1,2,1,2,1,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,3,2,1,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,3,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,3,2,1,5,4,3,2,1,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,2,1,4,3,2,1,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,4,3,2,1,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,1,2,1,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,4,3,2,1,6,5,4,3,2,1,2,1,5,4,3,2,1,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,1],"label":["caller_env","dplyr_error_call","select.data.frame","findCenvVar","findLocVar","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","findFunDef","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findVar","cmpSym","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","$","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpDispatch","h","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cmpCallSymFun","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putcode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","smoothCon","gam.setup","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","pmax","quantile.default","variable.summary","mgcv::gam","pboot",".C","profvis","mgcv::gam","pboot",".C","profvis","<GC>",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis",".C","profvis","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpTag","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","as.list","lapply","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","as.list","lapply","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","as.list","lapply","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot","cb$patchlabels","codeBufCode","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian ","dnorm","K","FUN","lapply","sapply","NW_new","pboot","apply","pboot","deparse1","as.data.frame.numeric","data.frame","cbind","cbind","pboot","FUN","lapply","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","cmpfun","compiler:::tryCmpfun","profvis","c","profvis","as.list","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","cmpfun","compiler:::tryCmpfun","profvis","getExprSrcref","cb$setcurexpr","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","<GC>","%in%","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putcode","cmpSym","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","getInlineHandler","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","as.list","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putcode","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","getInlineInfo","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","match.call","checkCall","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putcode","cmpSym","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpDispatch","h","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim1","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","as.list","constantFoldCall","constantFold","cmp","cmpPrim1","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","constantFoldSym","constantFold","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putlabel","cmpSubassignDispatch","h","trySetterInline","cmpSetterCall","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSubassignDispatch","h","trySetterInline","cmpSetterCall","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","new.env","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","<GC>","%in%","getFoldFun","constantFoldCall","constantFold","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","%in%","getFoldFun","constantFoldCall","constantFold","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","delayedAssign","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$setcurexpr","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","cmpSym","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","$","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSym","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSym","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","offset","cb$patchlabels","codeBufCode","genCode","cmpfun","compiler:::tryCmpfun","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unique","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","%in%","[[.data.frame","model.frame.default","est_psi","fit_one","%*%","profvis","formals","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[[<-.data.frame","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.character","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","is.na","profvis","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","model.frame.default","predict.gam","est_psi","fit_one","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","<GC>","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","NextMethod","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mode","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","[.data.frame","na.exclude.data.frame","model.frame.default","predict.gam","est_psi","fit_one","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","as.integer","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ncol","eigen","totalPenaltySpace","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis",".C","profvis","pain_bq_R1_temp <- c(rep(0, length(X_in_fold_t_R0$pain_bq)+length(X_in_fold_t0_R0$pain_bq)), X_in_fold_R1$pain_bq)/prop.R1","$","est_psi","fit_one","names","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","mean","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","colSums","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","sum","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","var_R0_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))  ","matrix","est_psi","fit_one",".C","profvis","null.space.dimension","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","anyDuplicated.default","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.list","vapply","model.frame.default","predict.gam","est_psi","fit_one","isTRUE","mean.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","<GC>",".C","profvis",".C","profvis","standardGeneric","profvis",".C","profvis",".C","profvis",".C","profvis","<GC>","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","profvis","eta_T_R1 <- predict(M_R1.fit, newdata=X_with_T_in_fold_R1, type=\"response\")","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.integer","profvis",".C","profvis","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","doTryCatch","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one",".External2","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","t.default","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","pmin","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","aperm.default","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","else{names(data[i]) }","[","FUN","lapply","sapply","single.index.variables","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","$","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot",".C","profvis","unlist","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>",".C","profvis","match.arg","sort.int","sort.default","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis","levels","unique.default","factor","predict.gam","pboot","dnorm","K","FUN","lapply","sapply","NW_new","pboot","isTRUE","which","FUN","apply","pboot","[[.data.frame","[.data.frame","na.omit.data.frame","model.frame.default","model.matrix.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","rowSums","predict.gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","qr","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","base::colSums","colSums","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","NextMethod","[.data.frame","model.matrix.default","predict.gam","est_psi","fit_one","[[","na.omit.data.frame","model.frame.default","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.side","gam.setup","mgcv::gam","est_psi","fit_one","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.list.default","vapply","model.frame.default","predict.gam","est_psi","fit_one","binomInitialize","family","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","length","profvis",".C","profvis","as.vector","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","factor","as.factor","split.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","get0","dynGet","loadNamespace","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","match.fun","vapply","rm","predict.gam","est_psi","fit_one","all.equal","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","as.double","profvis","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","ncol","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","standardGeneric","profvis","[[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one",".C","profvis",".C","profvis","names","profvis","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis",".C","profvis","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","FUN","vapply","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","array","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","apply","est_psi","fit_one","<GC>","array","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot",".C","profvis",".C","profvis",".C","profvis",".C","profvis","%*%","profvis",".C","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis","unlist","simplify2array","sapply","NW_new","pboot","apply","pboot","formula","reformulate","mgcv::s","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","standardGeneric","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".C","profvis",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.vector","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","doTryCatch","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","matrix","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".signalSimpleWarning","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one","length","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","family$d2link","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","force","factor","unique.default","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis",".C","profvis",".C","profvis","[[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","FUN","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","min","profvis",".Call","profvis",".Call","profvis","dim","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","truncate","uniroot","est_psi","fit_one","matrix","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","t.default","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","stopifnot","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","colSums","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one","c","profvis",".C","profvis","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","formals","match.arg","order","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","is.na","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mean","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t.default","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","FUN","lapply","assign_func_envs","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","as.double","profvis",".C","profvis","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","[[.data.frame","model.frame.default","predict.gam","est_psi","fit_one","standardGeneric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply",".getXlevels","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","eval","match.arg","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.atomic","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","c","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","eq","est_psi","fit_one",".C","profvis","qr.default","smoothCon","gam.setup","mgcv::gam","pboot","<GC>",".C","profvis","mgcv::s","pboot",".C","profvis",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian ","dnorm","K","FUN","lapply","sapply","NW_new","pboot","FUN","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sort","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$<-","fix.family.var","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","abs","profvis",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","terms.default","predict.gam","est_psi","fit_one","names","profvis","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis",".C","profvis","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.atomic","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","[[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","est_psi","fit_one","any","profvis",".Call","profvis","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","array","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.double","profvis","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","var_R1_temp_trunc[k, g] <- sum((if_R1_temp_trunc - vector_mean_R1_temp)^2)/(nk_in_fold-1)","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","return (sum((Imat - Fhat)^2)/length(Fhat)^2)","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","isTRUE","mean.default","f","<Anonymous>","uniroot","est_psi","fit_one","[[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","all.equal","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.list.default","vapply","model.frame.default","est_psi","fit_one","as.integer","profvis",".C","profvis","c","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","factor","predict.gam","est_psi","fit_one",".C","profvis",".Fortran","profvis","<GC>","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","variable.summary","mgcv::gam","est_psi","fit_one","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ncol","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","diag","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","initialize","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sys.call","[[<-.data.frame","predict.gam","est_psi","fit_one","<GC>",".Fortran","profvis",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>",".C","profvis",".C","profvis","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.side","gam.setup","mgcv::gam","est_psi","fit_one","diag","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","withCallingHandlers","suppressWarnings","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".External2","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","mean","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mu_exp_t_R0_X_t0_R0 <- c(dF_t_R0_X_t0_R0 %*% (exp(gamma[g]*pnorm((y_t_R0-60)/25))+","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","rm","mgcv::gam","pboot","<GC>","as.double","profvis","paste0","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","PredictMat","predict.gam","pboot","dnorm","K","FUN","lapply","sapply","NW_new","pboot","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","pboot","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","mode","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","sum","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","qr.qty","PredictMat","predict.gam","est_psi","fit_one","is.na","profvis","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sum","profvis","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","environment","obj_check_vector","vec_data","dplyr_col_modify.data.frame","mutate.data.frame","est_psi","fit_one","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","qr.default","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","factor","predict.gam","est_psi","fit_one",".C","profvis","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","stopifnot","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one",".External","profvis","tcrossprod","profvis",".C","profvis",".C","profvis","family$variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","match.fun","vapply","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","match.fun","vapply","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","%*%","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","eq","est_psi","fit_one",".C","profvis",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$<-","fix.family.var","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rev.default","eigen","totalPenaltySpace","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","%*%","profvis","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","paste0","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.integer","profvis",".C","profvis","deparse","mode","formula.default","reformulate","mgcv::gam","est_psi","fit_one","profvis",".C","profvis","str2lang","reformulate","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","paste0","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","<GC>",".Fortran","profvis","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","%*%","profvis","eval","match.arg","order","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.side","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","names","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pnorm","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis","FUN","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","truncate","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","eq","est_psi","fit_one","sys.call","[.data.frame",".getXlevels","gam.setup","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis",".C","profvis","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","pboot","<GC>","K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian ","dnorm","K","FUN","lapply","sapply","NW_new","pboot","Y.new_t0_R0 <- apply(F_X_t0_R0, 1, function(x){","FUN","apply","pboot","!=","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","all.equal","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","eval","get.var","predict.gam","est_psi","fit_one","$<-","gam.setup","mgcv::gam","est_psi","fit_one","lapply","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","family$variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","get0","dynGet","loadNamespace","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","$","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","[[.data.frame","get.var","predict.gam","est_psi","fit_one","do.call","mgcv::gam","est_psi","fit_one",".C","profvis","abs","profvis",".C","profvis",".C","profvis",".C","profvis",".C","profvis","NextMethod","variable.summary","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","%in%","deparse","mode","deparse","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","do.call","order","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","aperm.default","apply","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","<GC>","array","simplify2array","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","sys.function","match.arg","order","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","c","profvis","is.factor","FUN","vapply","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Fortran","profvis",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis",".Fortran","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","estimate.gam","mgcv::gam","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","mgcv::gam","est_psi","fit_one","pmatch",".deparseOpts","deparse","FUN","vapply","model.frame.default","est_psi","fit_one","NextMethod","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","is.na","profvis","as.double","profvis",".C","profvis","sum","profvis",".C","profvis","as.vector","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","norm","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","paste","FUN","vapply","model.matrix.default","predict.gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","*","profvis","matrix","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","pmax","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one",".C","profvis","<Anonymous>","[[.data.frame","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","fyxb <- (denom!=0)*crossprod(Kxb, Ylty)/(denom + (denom==0))","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","aperm.default","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","sum","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>",".C","profvis","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>","standardGeneric","profvis","rep.int","family$d2var","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","standardGeneric","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","standardGeneric","profvis","dnorm","K","FUN","lapply","sapply","NW_new","pboot","min","profvis","is.numeric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mutate_col","mutate_cols","mutate.data.frame","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sort.int","sort.default","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","<GC>","*","profvis","qr.default","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","lapply","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","stopifnot","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","[","[.data.frame","na.exclude.data.frame","model.frame.default","predict.gam","est_psi","fit_one","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","doTryCatch","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","...elt","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>",".C","profvis",".C","profvis","as.double","profvis","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","Fhat[is.nan(Fhat)] <- 0","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","vector_mean_R0_temp_diff <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pnorm","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vector_mean_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","aperm.default","sweep","scale.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","which","ifelse","addindex","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","deparse","FUN","vapply","model.frame.default","predict.gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","eval","match.arg","order","order","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","paste","mgcv::gam","est_psi","fit_one","quantile","variable.summary","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","deparse","mode","formula.default","reformulate","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","prop.R1 <- mean(R_in_fold)","est_psi","fit_one",".External","profvis",".C","profvis","paste","gam.setup","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".Call","profvis",".C","profvis","model.matrix","gam.setup","mgcv::gam","est_psi","fit_one","family$variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","local_error_context","mutate_cols","mutate.data.frame","est_psi","fit_one",".Call","profvis","<GC>","%*%","profvis",".Call","profvis","mean","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","X_out_fold <- X[out_fold_id_list, ]","est_psi","fit_one",".Call","profvis",".Call","profvis","array","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","sys.call","match.call","rm","mgcv::gam","pboot","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","all","profvis","rm","gam.setup","mgcv::gam","pboot","<GC>","as.double","profvis","$","smoothCon","gam.setup","mgcv::gam","pboot","notnull","formula.default","reformulate","mgcv::gam","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","return (sum((Imat - Fhat)^2)/length(Fhat)^2)","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot","K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian ","dnorm","K","FUN","lapply","sapply","NW_new","pboot","<GC>","dnorm","K","FUN","lapply","sapply","NW_new","pboot","y_t0_R1[min(which(ecdf<=x))]","FUN","apply","pboot","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","mgcv::gam","est_psi","fit_one",".C","profvis","qr.default","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.setup","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","NCOL","qr.qty","PredictMat","predict.gam","est_psi","fit_one","$<-","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rep.int","family$d2var","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","unique","factor","unique.default","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","dynGet","loadNamespace","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply",".getXlevels","gam.setup","mgcv::gam","est_psi","fit_one","unlist","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%",".deparseOpts","deparse","mgcv::s","est_psi","fit_one","profvis","tryCatch","try","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","cbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mutate_cols","mutate.data.frame","est_psi","fit_one",".C","profvis","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis",".C","profvis","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","array","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","is.nan","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","if_R0_temp <- c(M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","is.nan","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one","[.factor","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","deparse","mode","deparse","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","is.na","profvis","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","%*%","profvis",".C","profvis",".C","profvis","<GC>",".Fortran","profvis","NextMethod","[.data.frame","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","model.frame.default","est_psi","fit_one",".Fortran","profvis","<GC>",".C","profvis",".C","profvis","norm","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","c","profvis","as.matrix","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all","profvis","standardGeneric","profvis","gam.setup","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","$","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","any","profvis","%*%","profvis","<GC>","*","profvis",".C","profvis","sys.call","[[<-.data.frame","model.matrix.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","<GC>","array","simplify2array","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","truncate","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","quantile.default","variable.summary","mgcv::gam","pboot","<GC>","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","names","[.data.frame",".getXlevels","gam.setup","mgcv::gam","pboot","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>","%*%","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","sort.int","sort.default","pboot","Kxb <- sapply(xb, function(x, Xb) K(Xb-x, h), Xb=Xb)","FUN","lapply","sapply","NW_new","pboot","apply","pboot","unique.default","model.frame.default","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis",".C","profvis","is.expression","profvis","mode","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ncol","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","<GC>",".C","profvis","mode","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","$","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","factor","unique.default","model.frame.default","est_psi","fit_one",".C","profvis","levels","nlevels","unique.default","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one","fix.family.link","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","any","profvis","na.omit.data.frame","model.frame.default","est_psi","fit_one","max","profvis","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","as.double","profvis","qr.qty","PredictMat","predict.gam","est_psi","fit_one",".C","profvis","quantile","variable.summary","mgcv::gam","est_psi","fit_one",".C","profvis","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis",".C","profvis",".C","profvis","sys.function","match.arg","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","if(single_index_method==\"fixed_bandwidth\"){","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","as.integer","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","order","sort.int","sort.default","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), ","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[[","na.omit.data.frame","model.frame.default","est_psi","fit_one",".C","profvis","sum","profvis","any","profvis","sum","profvis",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","makepredictcall","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","is.na","profvis","[.formula","variable.summary","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","all_vars1","mgcv::gam","est_psi","fit_one","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","pqr.R","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.data.frame","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","mgcv::gam","est_psi","fit_one","any","profvis","[","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","<GC>","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[[.data.frame","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","lapply","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","^","profvis","names","profvis","mean","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","any","profvis",".C","profvis","context_poke","mutate_cols","mutate.data.frame","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","max","profvis","[[","model.frame.default","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".External2","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[[.data.frame","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","diag","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","nargs","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","Fhat[is.nan(Fhat)] <- 0","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","<GC>","aperm.default","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","pi_R0_weight <- pi_R0_weight_l[which(fold_index_pi_R0_l==k)]","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","get","match.fun","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","mean","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","isTRUE","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","mean","initial.sp","initial.spg","estimate.gam","mgcv::gam","pboot","ncol","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","$","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot","max","profvis",".Call","profvis",".Call","profvis","W <- K(D/exp(log_bandwidth)) * Id_neq","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","outer","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis","Predict.matrix3","PredictMat","predict.gam","pboot","FUN","profvis",".deparseOpts","deparse","FUN","vapply","model.frame.default","predict.gam","pboot",".C","profvis","standardGeneric","profvis","mode","attr.all.equal","all.equal.numeric","mgcv::s","est_psi","fit_one","FUN","vapply","pmax","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","ncol","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","model.frame.default","predict.gam","est_psi","fit_one","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.double","profvis","[[<-","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr","profvis",".C","profvis",".C","profvis",".C","profvis","obj_is_list","new_list_of","group_data.data.frame","compute_by","mutate.data.frame","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","mode","deparse","mode","formula.default","reformulate","mgcv::gam","est_psi","fit_one","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.factor","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","t.default","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.setup","mgcv::gam","est_psi","fit_one","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","as.double","profvis","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","[[","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","attributes","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","denom <- rowSums(W)","rowSums","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","pmin","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","pmin","f","uniroot","est_psi","fit_one","t","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","%*%","profvis","[.data.frame","est_psi","fit_one",".C","profvis",".C","profvis","is.numeric","profvis","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","predict.gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","^","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","max","profvis",".C","profvis",".C","profvis","names","profvis","standardGeneric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","formula.character","as.formula","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","[[.data.frame","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one",".C","profvis",".C","profvis","diag","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.data.frame","rowSums","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","order","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","<GC>","aperm.default","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mostattributes<-","pmin","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmatch",".deparseOpts","deparse","FUN","vapply","model.frame.default","pboot","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis","sort.int","sort.default","quantile.default","variable.summary","mgcv::gam","pboot",".C","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","as.numeric","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","pboot","which","FUN","apply","pboot","split.default","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.factor","model.frame.default","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","PredictMat","predict.gam","est_psi","fit_one","qr.qty","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","ncol","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","totalPenaltySpace","estimate.gam","mgcv::gam","est_psi","fit_one","/","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.vector","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","colMeans","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","%*%","profvis","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","PredictMat","predict.gam","est_psi","fit_one",".C","profvis","variable.summary","mgcv::gam","est_psi","fit_one","<GC>","standardGeneric","profvis","base::colMeans","colMeans","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","withCallingHandlers","suppressWarnings","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","dplyr_quosures","mutate.data.frame","est_psi","fit_one","dplyr_quosures","mutate.data.frame","est_psi","fit_one","dplyr_quosures","mutate.data.frame","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","match.arg","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","all","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","mean","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","is.nan","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","data.class","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","get.var","predict.gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","as.vector","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","c","profvis","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","%in%",".deparseOpts","deparse","FUN","vapply","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","mean.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".POSIXct","Sys.time","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one","asNamespace","make.link","family","mgcv::gam","est_psi","fit_one","<GC>","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unlist","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.double","profvis","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","qr.qty","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mode","data.class","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$<-","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dplyr_reconstruct_dispatch","dplyr_reconstruct","dplyr_col_modify.data.frame","mutate.data.frame","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis",".C","profvis",".Call","profvis",".C","profvis","as.vector","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot",".C","profvis",".C","profvis",".C","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","pboot","apply","pboot","NextMethod","[.factor","[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","pboot",".C","profvis","vapply","pmax","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","as.matrix","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","profvis","any","profvis","length","model.frame.default","est_psi","fit_one","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".POSIXct","Sys.time","srcfilecopy","parse","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rowSums","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","ifelse","addindex","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","linkinv","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dim","nrow","initialize","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","paste","FUN","vapply","model.frame.default","est_psi","fit_one","as.matrix.default","qr.coef","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","match.arg","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","<GC>","as.vector","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","$<-","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","<GC>","ctrfn","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","estimate.gam","mgcv::gam","est_psi","fit_one","[[<-.data.frame","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","as.list.data.frame","vapply","model.frame.default","est_psi","fit_one","delete.response","predict.gam","est_psi","fit_one","%in%",".deparseOpts","deparse","FUN","vapply","model.matrix.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","sum","profvis",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","apply","scale.default","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","mean.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","sort.int","sort.default","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","names","profvis","sys.call","[[.data.frame","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one",".C","profvis","$","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","*","profvis","pmax","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mode","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".C","profvis","$<-","gam.setup","mgcv::gam","est_psi","fit_one","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","%*%","profvis","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sys.call","[[<-.data.frame","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis","rownames<-","M3d2list","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","fyxb <- (denom!=0)*crossprod(Kxb, Ylty)/(denom + (denom==0))","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","var_R0_temp_diff[k, g] <- sum((if_R0_temp_diff - vector_mean_R0_temp_diff)^2)/(nk_in_fold-1)","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","print.default"],"filenum":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,2,1,null,null,null,null,2,1,null,null,null,2,1,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,4,4,4,null,null,4,2,1,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,2,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,5,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,2,2,null,null,2,2,1,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,1,4,4,null,null,4,2,1,null,2,null,2,1,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,2,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,2,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,3,3,3,null,null,3,2,1,null,null,null,null,null,null,4,2,1,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,null,null,5,null,null,null,null,null,null,null,null,null,2,5,2,1,null,null,null,null,null,2,1,null,null,null,null,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,4,4,null,null,4,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,4,4,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,3,3,null,null,3,5,2,1,null,null,null,null,2,2,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,4,5,2,1,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,4,4,null,null,4,2,1,null,null,null,null,null,null,null,null,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,5,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,5,2,1,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,4,null,null,4,2,1,null,4,4,4,null,null,4,2,1,2,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,5,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,5,2,1,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,5,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,4,null,null,4,2,1,2,null,2,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,3,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,4,4,null,null,4,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,4,4,4,null,null,4,2,1,null,4,4,null,null,4,2,1,2,null,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,2,1,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,4,5,2,1,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,5,2,1,null,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,1,4,null,null,4,2,1,2,1,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,3,null,null,3,5,2,1,2,2,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,2,1,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,2,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,5,2,1,null,null,null,null,3,null,null,3,5,2,1,null,2,5,2,1,null,null,null,null,null,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,4,4,null,null,4,2,1,2,null,2,1,null,2,1,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,2,1,null,null,2,1,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,4,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,2,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,2,1,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,5,2,1,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,2,5,2,1,null,null,null,null,null,null,5,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,4,4,null,null,4,2,1,2,1,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,2,1,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,2,1,null,null,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,2,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,5,2,1,null,null,null,2,null,null,5,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,5,2,1,null,null,null,null,5,2,1,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,null,null,5,2,1,null,null,null,2,1,null,null,null,null,null,null,null,2,null,null,5,2,1,null,null,null,null,3,5,2,1,null,null,4,5,2,1,null,null,null,null,null,null,5,2,1,null,null,null,null,null,null,2,2,null,null,5,2,1,null,null,null,null,null,null,null],"linenum":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,230,12,null,null,null,null,230,12,null,null,null,231,12,null,null,232,12,null,null,null,null,null,null,null,null,232,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,235,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,248,12,null,null,null,null,null,null,null,null,28,59,null,null,94,261,12,null,null,28,59,null,null,94,274,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,320,null,382,382,389,null,null,389,320,12,349,12,null,null,null,null,379,12,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,null,null,null,null,null,null,389,null,null,null,null,null,null,null,128,389,14,null,null,null,130,389,14,null,null,null,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,14,null,null,null,389,14,null,null,null,null,127,389,14,null,null,null,null,null,null,null,null,130,389,14,null,null,null,null,null,null,null,null,131,389,14,null,null,null,389,14,null,null,127,389,14,null,null,null,null,127,389,14,null,null,null,null,null,null,null,null,128,389,14,null,null,null,null,389,14,null,null,null,null,null,130,389,14,null,null,null,null,null,null,null,null,null,null,null,null,131,389,14,null,null,null,null,null,null,null,389,14,null,null,null,null,389,14,null,null,null,null,null,null,128,389,14,null,null,null,null,130,389,14,null,null,null,null,null,131,389,14,null,null,null,null,null,156,156,389,14,null,null,null,null,null,null,127,389,14,null,null,null,null,null,null,null,128,389,14,null,null,null,null,null,null,null,null,null,null,131,389,14,null,null,null,null,131,389,14,null,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,16,null,null,489,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,393,346,389,14,null,null,null,null,null,null,63,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,14,null,null,null,null,null,null,38,38,389,15,null,null,null,null,null,null,null,128,389,15,null,null,null,128,389,15,null,null,null,null,null,130,389,15,null,null,null,null,389,15,null,null,null,null,131,389,15,null,null,null,null,389,15,null,null,null,null,null,null,127,389,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,15,null,146,389,15,null,null,null,null,127,389,15,null,null,null,null,null,null,null,128,389,15,null,null,null,null,null,null,null,null,null,null,null,null,131,389,15,null,null,null,null,null,null,null,389,15,null,null,null,null,null,null,127,389,15,null,null,null,null,null,128,389,15,null,null,null,null,130,389,15,null,null,null,null,null,null,131,389,15,null,null,null,null,null,131,389,15,null,null,null,127,389,15,null,null,null,null,null,null,128,389,15,null,null,null,null,128,389,15,null,null,null,null,null,null,null,null,389,15,null,null,null,null,null,null,499,389,15,null,null,null,null,null,null,28,59,null,null,94,321,389,15,null,null,null,null,null,null,null,null,null,null,61,null,null,94,321,389,15,497,389,15,null,null,null,null,null,null,null,null,525,389,15,null,null,null,null,null,null,321,389,15,11,11,null,null,9,205,20,null,null,null,null,230,20,null,null,null,null,null,231,20,null,null,null,null,231,20,null,null,null,null,null,232,20,null,null,null,null,null,null,null,null,233,20,null,null,null,null,null,null,235,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,53,248,20,null,null,null,null,null,null,null,null,28,59,null,null,94,261,20,null,null,null,null,null,null,20,382,389,null,null,389,329,20,null,355,null,353,20,null,null,null,null,null,389,23,null,null,null,null,127,389,23,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,131,389,23,null,null,null,null,389,23,null,null,null,127,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,null,128,389,23,null,null,null,128,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,389,23,null,null,null,127,389,23,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,130,389,23,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,389,23,null,null,null,null,null,null,127,389,23,null,null,128,389,23,null,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,131,389,23,null,null,null,null,389,23,null,null,127,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,16,486,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,321,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,59,null,null,94,321,389,23,null,null,null,null,null,null,null,null,null,null,null,null,53,321,389,23,null,null,null,389,24,null,null,null,null,127,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,128,389,24,128,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,128,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,null,null,null,16,16,null,null,489,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,286,389,24,null,null,359,389,24,null,null,null,null,null,null,230,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,59,28,59,null,null,94,248,20,null,null,null,null,null,null,null,null,null,59,28,59,null,null,94,261,20,null,null,null,null,null,null,389,320,20,357,20,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,505,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,458,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,489,389,23,null,null,127,389,24,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,127,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,127,389,24,null,null,null,128,389,24,null,null,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,489,389,24,null,null,null,null,null,null,null,391,340,389,24,null,null,null,null,null,null,null,null,422,null,null,null,null,null,null,null,null,null,16,494,389,24,null,null,null,null,null,231,20,null,null,null,null,20,null,null,null,null,null,null,null,null,null,233,20,null,null,null,null,233,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,382,382,389,null,null,389,323,20,null,null,null,null,null,null,null,null,127,389,23,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,null,null,null,128,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,529,389,23,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,321,389,23,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,null,null,382,389,null,null,389,346,389,23,null,null,null,null,null,null,null,null,null,null,null,16,null,null,489,389,23,null,null,null,null,null,null,null,63,null,null,94,286,389,23,null,null,null,null,null,null,null,null,497,389,23,null,null,null,389,24,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,127,389,24,null,null,null,null,null,127,389,24,null,null,128,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,321,389,24,null,null,28,59,null,null,94,286,389,24,null,null,null,null,16,16,502,389,24,null,null,null,null,null,null,null,null,399,389,24,null,null,null,null,null,null,null,null,null,391,346,389,24,null,null,28,59,null,null,94,286,389,24,null,null,null,null,null,null,null,230,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,231,20,null,null,null,null,231,20,null,null,null,null,null,232,20,null,null,null,null,null,null,null,null,233,20,null,null,null,null,null,233,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,20,382,389,null,null,389,329,20,null,null,null,null,null,null,null,null,20,null,null,null,null,null,127,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,127,389,23,128,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,131,389,23,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,389,23,null,null,null,128,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,391,null,null,391,337,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,535,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,441,389,23,null,null,null,null,null,null,null,61,null,null,null,null,null,null,null,457,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,502,389,23,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,130,389,24,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,130,389,24,null,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,127,389,24,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,391,389,24,null,null,null,null,null,null,528,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,489,389,24,null,null,null,null,null,null,null,16,478,389,24,null,null,null,null,230,20,null,null,null,null,230,20,null,null,null,null,null,null,null,231,20,null,null,null,null,null,null,null,null,null,null,233,20,null,null,null,null,null,null,233,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,248,20,null,null,null,null,null,null,null,null,null,null,null,null,382,389,null,null,389,320,20,null,382,382,389,null,null,389,323,20,357,null,357,20,null,null,null,null,null,127,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,389,23,null,null,127,389,23,null,null,null,128,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,389,23,null,127,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,131,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,351,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,null,null,null,null,null,389,337,389,23,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,28,59,null,null,94,321,389,23,null,null,null,null,null,null,null,null,null,61,null,null,94,286,389,23,null,null,null,null,508,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,130,389,24,null,null,131,389,24,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,null,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,131,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,127,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,395,346,389,24,null,null,null,null,null,null,null,null,null,61,null,null,94,321,389,24,null,null,null,null,null,null,63,null,null,null,null,null,null,null,null,null,null,16,null,null,505,389,24,null,null,null,null,null,null,null,null,513,null,null,null,null,null,null,null,230,12,null,null,null,null,null,null,null,null,231,12,null,null,null,null,232,12,null,null,null,null,null,null,null,null,null,232,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,248,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,382,389,null,null,389,323,12,355,null,10,null,null,null,null,null,127,389,14,null,null,null,null,128,389,14,null,null,null,null,null,null,128,389,14,null,null,null,null,null,null,131,389,14,null,null,null,389,14,null,null,null,null,null,127,389,14,null,null,null,null,128,389,14,null,null,null,null,null,null,130,389,14,null,null,null,null,null,130,389,14,null,null,null,null,null,null,null,389,14,null,null,null,null,127,389,14,null,null,null,null,null,null,128,389,14,null,null,null,128,389,14,null,null,null,null,null,null,null,null,null,null,null,389,14,null,null,null,null,null,null,127,389,14,null,null,null,null,null,null,null,null,127,389,14,null,null,128,389,14,null,null,null,null,null,null,null,null,null,null,null,131,389,14,null,null,null,null,null,null,null,null,null,null,389,14,null,null,null,null,null,null,127,389,14,null,null,null,null,null,null,null,null,null,null,389,14,null,null,null,null,null,null,null,null,null,null,null,null,53,286,389,14,null,null,28,59,null,null,94,321,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,62,null,null,94,286,389,14,null,null,null,null,443,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,null,404,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,null,451,389,14,null,null,null,null,null,null,null,null,null,null,null,null,null,53,286,389,14,null,null,null,null,null,null,null,389,15,null,null,null,null,127,389,15,null,null,null,null,null,null,null,128,389,15,null,null,null,null,null,null,128,389,15,null,null,null,null,130,389,15,null,null,null,null,null,null,131,389,15,null,null,null,null,null,389,15,null,127,389,15,null,null,null,null,null,127,389,15,null,null,null,null,128,389,15,null,null,null,null,null,130,389,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,15,null,null,null,128,389,15,null,null,130,389,15,null,null,null,null,null,130,389,15,null,null,null,null,null,null,null,131,389,15,null,null,null,null,131,389,15,133,389,15,null,null,null,null,null,null,128,389,15,null,null,null,null,null,128,389,15,null,null,null,null,null,null,null,130,389,15,null,null,null,null,null,null,null,null,null,null,null,null,null,389,15,null,null,null,null,null,null,null,null,null,null,127,389,15,null,null,null,null,128,389,15,null,null,null,null,null,null,null,131,389,15,null,null,null,null,null,131,389,15,null,null,null,389,15,null,null,null,61,null,null,null,16,null,null,481,389,15,null,null,null,null,null,null,382,389,null,null,389,337,389,15,null,null,null,null,null,null,204,389,15,null,null,null,null,null,61,null,null,94,321,389,15,null,null,null,null,null,null,28,59,null,null,94,321,389,15,null,null,null,230,20,null,null,null,null,null,null,230,20,null,null,null,null,null,230,20,null,null,null,null,232,20,null,null,null,null,null,null,233,20,null,null,null,233,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,63,null,null,94,248,20,null,null,null,null,null,null,null,null,28,59,null,null,94,274,20,382,382,389,null,null,389,326,20,null,382,389,null,null,389,329,20,363,null,361,20,null,null,null,null,127,389,23,null,null,null,128,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,127,389,23,null,null,null,null,null,128,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,131,389,23,null,null,null,null,null,131,389,23,null,null,null,null,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,131,389,23,null,null,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,23,null,389,23,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,286,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,62,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,413,389,23,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,16,null,null,481,389,23,null,null,null,null,null,null,null,null,null,null,62,null,null,null,null,391,340,389,23,null,null,null,null,389,24,null,null,null,null,127,389,24,null,null,null,null,128,389,24,null,null,null,130,389,24,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,null,103,389,24,null,null,128,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,null,null,null,131,389,24,131,389,24,null,389,24,null,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,24,null,null,null,null,null,389,346,389,24,null,null,null,null,null,null,null,null,null,489,389,24,null,null,null,null,null,null,null,null,513,null,null,null,null,null,null,230,20,null,null,null,null,230,20,null,null,231,20,null,null,null,null,null,null,231,20,null,null,null,null,232,20,null,null,null,null,null,null,232,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,59,28,59,null,null,94,248,20,null,null,null,null,null,null,null,null,null,null,20,389,null,null,389,326,20,361,20,null,null,389,23,null,null,null,null,null,127,389,23,null,null,null,127,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,131,389,23,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,389,23,null,null,null,127,389,23,null,null,null,null,null,127,389,23,null,null,null,null,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,23,254,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,505,389,23,null,null,null,null,null,null,null,null,null,null,48,286,389,23,null,null,28,59,null,null,94,321,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,286,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,515,389,23,null,null,null,null,null,127,389,24,null,null,null,null,127,389,24,null,null,null,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,130,389,24,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,131,389,24,116,389,24,null,null,null,null,127,389,24,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,128,389,24,null,null,null,130,389,24,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,127,389,24,null,null,null,null,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,62,null,null,94,286,389,24,null,null,null,null,61,null,null,94,321,389,24,16,16,null,null,505,389,24,null,null,null,null,null,null,242,389,24,null,null,null,null,null,null,null,null,null,null,61,null,null,94,286,389,24,null,null,522,389,24,null,null,null,null,null,null,230,20,null,null,null,null,null,null,230,20,null,null,null,null,null,null,null,231,20,null,null,null,null,232,20,null,null,null,null,null,232,20,null,null,null,null,null,233,20,null,null,null,null,null,null,59,null,null,94,235,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,49,261,20,null,null,null,null,null,null,null,20,null,null,null,null,null,null,null,null,20,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,389,23,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,130,389,23,null,null,null,null,null,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,null,127,389,23,null,null,null,null,128,389,23,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,23,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,128,389,23,null,null,128,389,23,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,489,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,60,60,null,null,94,321,389,23,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,483,389,23,null,null,null,null,null,null,null,null,null,null,53,286,389,23,null,null,16,null,489,389,23,null,null,null,null,null,null,null,127,389,24,null,null,null,127,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,131,389,24,null,null,118,389,24,null,null,null,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,389,24,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,389,24,null,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,286,389,24,null,null,null,null,61,null,null,94,321,389,24,null,16,502,389,24,null,null,null,null,null,null,null,391,346,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,null,20,null,null,null,null,null,230,20,null,null,null,null,null,230,20,null,null,null,null,null,null,232,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,48,null,null,null,null,null,null,null,null,null,null,null,382,389,null,null,389,320,20,355,null,353,20,null,389,23,null,null,null,null,null,127,389,23,null,null,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,131,389,23,null,null,389,23,null,null,null,127,389,23,null,null,null,null,127,389,23,null,null,null,null,null,null,128,389,23,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,389,23,null,null,null,null,127,389,23,null,null,128,389,23,null,null,null,null,null,null,128,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,131,389,23,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,130,389,23,null,null,null,null,131,389,23,null,null,389,23,null,null,null,128,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,null,131,389,23,null,null,389,23,null,null,389,23,null,null,389,23,null,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,389,337,389,23,null,null,null,null,null,null,null,null,null,null,null,null,55,286,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,16,null,null,505,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,453,389,23,null,null,null,null,null,null,null,null,null,null,null,null,62,null,null,null,null,16,null,null,489,389,23,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,131,389,24,null,null,389,24,null,127,389,24,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,null,128,389,24,null,null,null,null,128,389,24,null,130,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,131,389,24,null,null,null,null,131,389,24,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,128,389,24,null,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,127,389,24,null,null,null,null,null,null,127,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,389,24,null,null,null,null,127,389,24,127,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,null,null,null,null,null,128,389,24,null,null,null,130,389,24,null,null,null,null,null,130,389,24,null,null,null,null,131,389,24,null,null,null,null,389,24,null,null,null,null,null,null,526,389,24,null,null,null,null,null,null,null,513,null,null,null,null,null,null,null,28,59,null,null,94,321,389,24,null,null,null,null,null,null,null,null,null,16,502,389,24,null,null,null,null,null,null,492,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,231,20,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,248,20,null,null,null,null,null,null,null,null,382,389,null,null,389,320,20,357,20,null,null,null,null,null,null,20,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,null,null,null,128,389,23,null,null,null,null,null,389,23,null,null,131,389,23,null,null,null,null,127,389,23,null,null,null,null,127,389,23,null,null,null,null,128,389,23,null,null,null,null,null,null,null,131,389,23,null,null,null,null,null,131,389,23,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,127,389,23,null,null,null,null,389,23,null,null,null,null,130,389,23,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,131,389,23,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,127,389,23,null,null,null,null,null,null,null,130,389,23,null,null,null,null,null,null,null,null,null,389,23,null,127,389,23,null,null,null,128,389,23,null,null,null,null,null,389,23,null,null,389,23,null,null,null,null,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,63,null,null,null,null,16,null,null,481,389,23,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,38,321,389,23,null,null,null,389,23,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,286,389,23,null,null,null,16,null,null,505,389,23,null,null,null,null,127,389,24,null,null,null,null,null,null,127,389,24,null,128,389,24,null,null,null,null,130,389,24,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,127,389,24,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,389,24,null,null,null,null,389,24,null,null,null,null,127,389,24,null,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,389,24,null,null,null,null,null,128,389,24,null,null,null,null,null,null,130,389,24,null,null,null,null,null,null,null,null,null,null,null,null,131,389,24,null,null,null,null,null,null,null,null,null,null,389,24,null,null,null,null,128,389,24,null,null,null,null,null,null,128,389,24,null,null,null,null,null,null,null,null,131,389,24,null,null,null,389,24,null,null,null,null,null,null,null,16,null,null,489,389,24,null,null,null,null,38,286,389,24,null,null,395,337,389,24,null,null,null,null,null,null,474,389,24,null,null,null,null,null,null,16,16,null,null,481,389,24,null,null,null,null,null,null,null],"memalloc":[48.8447265625,48.8447265625,48.8447265625,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,49.98320007324219,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,50.62909698486328,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.25335693359375,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,51.87723541259766,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,52.45448303222656,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.04742431640625,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,53.59303283691406,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,54.11610412597656,56.57493591308594,56.57493591308594,56.57493591308594,56.57493591308594,49.90025329589844,49.90025329589844,49.90025329589844,49.90025329589844,49.90025329589844,49.90025329589844,61.82327270507812,61.82327270507812,61.82327270507812,61.82327270507812,61.82327270507812,69.30770874023438,69.30770874023438,76.95468139648438,76.95468139648438,86.43399047851562,86.43399047851562,93.50889587402344,93.50889587402344,93.50889587402344,56.85702514648438,56.85702514648438,56.85702514648438,56.85702514648438,56.85702514648438,65.62423706054688,65.62423706054688,76.96456909179688,76.96456909179688,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.16031646728516,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,78.74000549316406,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.30430603027344,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,79.7318115234375,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.11483764648438,80.41854095458984,80.41854095458984,80.41854095458984,80.41854095458984,80.41854095458984,80.41854095458984,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,84.50040435791016,93.43374633789062,93.43374633789062,93.43374633789062,93.43374633789062,93.43374633789062,93.43374633789062,93.43374633789062,51.67382049560547,51.67382049560547,51.67382049560547,51.67382049560547,51.67382049560547,51.67382049560547,51.67382049560547,51.67382049560547,52.71979522705078,52.71979522705078,52.71979522705078,52.71979522705078,52.71979522705078,52.71979522705078,52.71979522705078,57.65564727783203,57.65564727783203,59.94340515136719,59.94340515136719,59.94340515136719,59.94340515136719,59.94340515136719,59.94340515136719,59.94340515136719,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,63.20912933349609,64.62802886962891,64.62802886962891,64.62802886962891,64.62802886962891,64.62802886962891,64.62802886962891,64.62802886962891,64.62802886962891,80.10540771484375,80.10540771484375,87.35495758056641,87.35495758056641,87.35495758056641,87.35495758056641,87.35495758056641,87.35495758056641,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,88.66050720214844,90.59447479248047,90.59447479248047,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.09615325927734,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,92.98703765869141,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,93.509033203125,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,52.74582672119141,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,53.50844573974609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.19936370849609,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,54.95729827880859,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,55.66626739501953,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,56.38090515136719,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.09957885742188,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,57.75627136230469,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,58.44853210449219,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.15186309814453,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,59.81113433837891,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,60.39743041992188,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,52.61712646484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,53.2728271484375,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.17024993896484,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,54.80271911621094,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,55.43484497070312,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.0828857421875,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,56.77581787109375,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,57.43839263916016,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.04934692382812,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,58.58240509033203,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.1607666015625,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,59.70639801025391,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.23918914794922,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,60.63310241699219,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,52.87914276123047,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.44871520996094,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,53.99335479736328,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,54.49739074707031,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.00977325439453,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.49951171875,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,55.87836456298828,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.55686950683594,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,56.83556365966797,57.0469970703125,57.0469970703125,57.0469970703125,57.0469970703125,57.0469970703125,57.0469970703125,57.0469970703125,60.21373748779297,60.21373748779297,67.32159423828125,67.32159423828125,67.32159423828125,67.32159423828125,67.32159423828125,67.32159423828125,67.32159423828125,74.72198486328125,74.72198486328125,74.72198486328125,74.72198486328125,74.72198486328125,74.72198486328125,81.90267944335938,81.90267944335938,81.90267944335938,81.90267944335938,81.90267944335938,90.59979248046875,90.59979248046875,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,55.07378387451172,58.02349090576172,58.02349090576172,58.02349090576172,58.02349090576172,58.02349090576172,65.31949615478516,65.31949615478516,65.31949615478516,65.31949615478516,65.31949615478516,65.31949615478516,65.31949615478516,73.08187866210938,73.08187866210938,82.76081085205078,82.76081085205078,89.54107666015625,89.54107666015625,89.54107666015625,89.54107666015625,89.54107666015625,89.54107666015625,89.54107666015625,59.07804870605469,59.07804870605469,59.07804870605469,61.90377044677734,61.90377044677734,61.90377044677734,61.90377044677734,61.90377044677734,61.90377044677734,61.90377044677734,61.90377044677734,67.99130249023438,67.99130249023438,67.99130249023438,67.99130249023438,67.99130249023438,69.59006500244141,69.59006500244141,69.59006500244141,69.59006500244141,69.59006500244141,79.27446746826172,79.27446746826172,79.27446746826172,79.27446746826172,79.27446746826172,79.27446746826172,79.27446746826172,86.76315307617188,86.76315307617188,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,93.49485778808594,60.93202209472656,60.93202209472656,60.93202209472656,60.93202209472656,60.93202209472656,60.93202209472656,69.71283721923828,69.71283721923828,69.71283721923828,69.71283721923828,69.71283721923828,69.71283721923828,69.71283721923828,69.71283721923828,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,76.02723693847656,87.64592742919922,87.64592742919922,93.50914764404297,93.50914764404297,93.50914764404297,93.50914764404297,93.50914764404297,93.50914764404297,93.50914764404297,55.81558227539062,55.81558227539062,55.81558227539062,55.81558227539062,55.81558227539062,55.81558227539062,62.09792327880859,62.09792327880859,69.81742858886719,69.81742858886719,69.81742858886719,69.81742858886719,69.81742858886719,69.81742858886719,69.81742858886719,76.52810668945312,76.52810668945312,76.52810668945312,76.52810668945312,76.52810668945312,76.52810668945312,76.52810668945312,85.92649841308594,85.92649841308594,85.92649841308594,85.92649841308594,85.92649841308594,85.92649841308594,85.92649841308594,85.92649841308594,93.49977111816406,93.49977111816406,93.49977111816406,59.99999237060547,59.99999237060547,62.2381591796875,62.2381591796875,62.2381591796875,62.2381591796875,69.75064849853516,69.75064849853516,80.69420623779297,80.69420623779297,80.69420623779297,80.69420623779297,80.69420623779297,80.69420623779297,80.69420623779297,88.28112030029297,88.28112030029297,93.50888824462891,93.50888824462891,93.50888824462891,93.50888824462891,93.50888824462891,93.50888824462891,93.50888824462891,93.50888824462891,61.53702545166016,61.53702545166016,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,69.27908325195312,79.13296508789062,79.13296508789062,79.13296508789062,79.13296508789062,79.13296508789062,79.13296508789062,79.13296508789062,82.78504180908203,82.78504180908203,82.78504180908203,83.29548645019531,83.29548645019531,83.29548645019531,83.29548645019531,83.29548645019531,83.29548645019531,83.29548645019531,83.29548645019531,88.01417541503906,88.01417541503906,88.01417541503906,88.01417541503906,88.01417541503906,88.01417541503906,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,57.93669128417969,57.93669128417969,57.93669128417969,57.93669128417969,57.93669128417969,57.93669128417969,62.01220703125,62.01220703125,62.01220703125,62.01220703125,62.01220703125,62.01220703125,68.71654510498047,68.71654510498047,68.71654510498047,68.71654510498047,68.71654510498047,68.71654510498047,68.71654510498047,68.71654510498047,73.24082183837891,73.24082183837891,73.24082183837891,73.24082183837891,77.08135986328125,77.08135986328125,77.08135986328125,77.08135986328125,79.89656829833984,79.89656829833984,79.89656829833984,79.89656829833984,79.89656829833984,79.89656829833984,83.03268432617188,83.03268432617188,84.28550720214844,84.28550720214844,84.28550720214844,84.28550720214844,90.26176452636719,90.26176452636719,90.26176452636719,90.26176452636719,90.26176452636719,90.26176452636719,90.26176452636719,90.26176452636719,91.86077117919922,91.86077117919922,91.86077117919922,91.86077117919922,91.86077117919922,91.86077117919922,91.86077117919922,91.86077117919922,59.8333740234375,59.8333740234375,59.8333740234375,59.8333740234375,59.8333740234375,59.8333740234375,67.40077209472656,67.40077209472656,67.40077209472656,67.40077209472656,74.60231018066406,74.60231018066406,83.03456878662109,83.03456878662109,83.03456878662109,83.03456878662109,83.03456878662109,83.03456878662109,83.03456878662109,83.03456878662109,91.93929290771484,91.93929290771484,91.93929290771484,91.93929290771484,91.93929290771484,91.93929290771484,66.93357849121094,66.93357849121094,66.93357849121094,66.93357849121094,66.93357849121094,66.93357849121094,66.93357849121094,66.93357849121094,67.86374664306641,67.86374664306641,67.86374664306641,67.86374664306641,67.86374664306641,67.86374664306641,77.32661437988281,77.32661437988281,77.32661437988281,77.32661437988281,77.32661437988281,77.32661437988281,77.32661437988281,81.72950744628906,81.72950744628906,81.72950744628906,81.72950744628906,81.72950744628906,81.72950744628906,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,87.14895629882812,93.50863647460938,93.50863647460938,93.50863647460938,49.62555694580078,49.62555694580078,49.62555694580078,54.04206848144531,54.04206848144531,64.31092834472656,64.31092834472656,71.74428558349609,71.74428558349609,81.24676513671875,81.24676513671875,87.57096099853516,87.57096099853516,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,79.60712432861328,58.62339019775391,62.09245300292969,62.09245300292969,62.09245300292969,68.39176177978516,68.39176177978516,68.39176177978516,68.39176177978516,68.39176177978516,68.39176177978516,68.39176177978516,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,76.22952270507812,84.93517303466797,84.93517303466797,90.70850372314453,90.70850372314453,51.93827056884766,51.93827056884766,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,59.04869079589844,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,68.80458068847656,69.99323272705078,69.99323272705078,78.82511138916016,78.82511138916016,78.82511138916016,78.82511138916016,78.82511138916016,78.82511138916016,78.82511138916016,86.02609252929688,86.02609252929688,86.02609252929688,86.02609252929688,86.02609252929688,86.02609252929688,86.02609252929688,86.02609252929688,93.49715423583984,93.49715423583984,93.49715423583984,93.49715423583984,93.49715423583984,93.49715423583984,93.49715423583984,54.59809112548828,54.59809112548828,61.53910827636719,61.53910827636719,61.53910827636719,61.53910827636719,61.53910827636719,61.53910827636719,61.53910827636719,71.72825622558594,71.72825622558594,71.72825622558594,71.72825622558594,71.72825622558594,71.72825622558594,71.72825622558594,71.72825622558594,73.4879150390625,73.4879150390625,73.4879150390625,73.4879150390625,73.4879150390625,73.4879150390625,80.10926818847656,80.10926818847656,85.65283966064453,85.65283966064453,85.65283966064453,85.65283966064453,85.65283966064453,85.65283966064453,85.65283966064453,93.50043487548828,93.50043487548828,93.50043487548828,93.50043487548828,93.50043487548828,93.50043487548828,93.50043487548828,54.99337768554688,54.99337768554688,62.27095031738281,62.27095031738281,71.9393310546875,71.9393310546875,74.82302856445312,74.82302856445312,74.82302856445312,74.82302856445312,75.24887084960938,75.24887084960938,76.45328521728516,76.45328521728516,76.45328521728516,76.45328521728516,80.95166015625,80.95166015625,80.95166015625,82.72664642333984,82.72664642333984,83.95546722412109,83.95546722412109,83.95546722412109,83.95546722412109,84.55120086669922,84.55120086669922,84.55120086669922,84.55120086669922,84.55120086669922,84.55120086669922,84.55120086669922,84.55120086669922,89.81404876708984,89.81404876708984,89.81404876708984,89.81404876708984,91.29706573486328,91.29706573486328,91.29706573486328,91.29706573486328,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,93.49665832519531,56.58473205566406,56.58473205566406,56.58473205566406,57.97217559814453,57.97217559814453,59.48089599609375,59.48089599609375,59.48089599609375,59.48089599609375,59.48089599609375,59.48089599609375,65.87670135498047,65.87670135498047,65.87670135498047,66.0877685546875,66.0877685546875,67.57585144042969,67.57585144042969,67.57585144042969,67.57585144042969,67.59649658203125,67.59649658203125,67.59649658203125,74.84595489501953,74.84595489501953,74.84595489501953,74.84595489501953,74.84595489501953,74.84595489501953,74.84595489501953,84.81769561767578,84.81769561767578,84.81769561767578,84.81769561767578,84.81769561767578,84.81769561767578,93.50836944580078,93.50836944580078,93.50836944580078,93.50836944580078,93.50836944580078,93.50836944580078,93.50836944580078,60.263671875,60.263671875,60.263671875,60.263671875,60.263671875,60.263671875,69.16230773925781,69.16230773925781,69.16230773925781,69.16230773925781,69.16230773925781,69.16230773925781,69.16230773925781,78.37950897216797,78.37950897216797,86.74998474121094,86.74998474121094,86.74998474121094,86.74998474121094,86.74998474121094,86.74998474121094,86.74998474121094,86.74998474121094,93.48421478271484,93.48421478271484,93.48421478271484,62.19854736328125,62.19854736328125,62.19854736328125,62.19854736328125,62.19854736328125,62.25955963134766,62.25955963134766,62.25955963134766,62.25955963134766,62.25955963134766,62.25955963134766,62.25955963134766,62.25955963134766,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,66.60797882080078,67.25995635986328,67.25995635986328,67.25995635986328,73.29093170166016,73.29093170166016,73.29093170166016,73.29093170166016,73.29093170166016,73.29093170166016,73.29093170166016,73.29093170166016,77.56017303466797,77.56017303466797,77.56017303466797,77.56017303466797,77.56017303466797,77.56017303466797,77.56017303466797,78.09055328369141,78.09055328369141,80.27506256103516,80.27506256103516,80.27506256103516,80.27506256103516,80.27506256103516,90.49271392822266,90.49271392822266,90.49271392822266,90.49271392822266,90.49271392822266,90.49271392822266,90.49271392822266,60.31739807128906,60.31739807128906,60.31739807128906,60.31739807128906,60.31739807128906,65.67695617675781,65.67695617675781,65.67695617675781,65.67695617675781,65.67695617675781,65.67695617675781,65.67695617675781,72.31732940673828,72.31732940673828,72.31732940673828,72.31732940673828,72.31732940673828,72.31732940673828,72.31732940673828,75.59297943115234,75.59297943115234,75.59297943115234,75.59297943115234,75.59297943115234,75.59297943115234,84.60771942138672,84.60771942138672,84.60771942138672,84.60771942138672,84.60771942138672,84.60771942138672,84.60771942138672,84.60771942138672,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,91.40923309326172,60.30921936035156,60.30921936035156,60.30921936035156,60.30921936035156,60.30921936035156,60.30921936035156,60.30921936035156,67.25778198242188,67.25778198242188,67.25778198242188,67.25778198242188,67.25778198242188,67.25778198242188,77.52009582519531,77.52009582519531,84.40464019775391,84.40464019775391,84.40464019775391,84.40464019775391,86.18895721435547,86.18895721435547,86.18895721435547,86.18895721435547,86.18895721435547,86.18895721435547,93.50856781005859,93.50856781005859,93.50856781005859,93.50856781005859,93.50856781005859,93.50856781005859,93.50856781005859,93.50856781005859,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,61.54339599609375,71.23471832275391,71.23471832275391,71.23471832275391,71.23471832275391,71.23471832275391,71.23471832275391,78.53236389160156,78.53236389160156,85.25373077392578,85.25373077392578,85.25373077392578,85.25373077392578,85.25373077392578,85.25373077392578,85.25373077392578,85.25373077392578,93.50901031494141,93.50901031494141,93.50901031494141,93.50901031494141,93.50901031494141,93.50901031494141,93.50901031494141,93.50901031494141,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,63.38565826416016,64.70445251464844,64.70445251464844,64.70445251464844,64.70445251464844,64.70445251464844,64.70445251464844,73.95871734619141,73.95871734619141,81.75111389160156,81.75111389160156,91.49807739257812,91.49807739257812,91.49807739257812,91.49807739257812,91.49807739257812,91.49807739257812,91.49807739257812,60.26891326904297,60.26891326904297,60.26891326904297,60.26891326904297,60.26891326904297,60.26891326904297,60.26891326904297,60.26891326904297,67.12600708007812,67.12600708007812,67.12600708007812,67.12600708007812,67.12600708007812,67.12600708007812,67.12600708007812,77.20286560058594,77.20286560058594,85.76814270019531,85.76814270019531,85.76814270019531,85.76814270019531,85.76814270019531,85.76814270019531,86.89488983154297,86.89488983154297,86.89488983154297,86.89488983154297,86.89488983154297,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,93.49916839599609,63.68989562988281,63.68989562988281,63.68989562988281,63.68989562988281,63.68989562988281,72.99354553222656,81.198486328125,81.198486328125,81.198486328125,81.198486328125,81.198486328125,81.198486328125,81.198486328125,91.08594512939453,91.08594512939453,91.08594512939453,91.08594512939453,91.08594512939453,91.08594512939453,91.08594512939453,62.05509948730469,62.05509948730469,62.05509948730469,62.05509948730469,62.05509948730469,62.05509948730469,62.05509948730469,70.18109130859375,70.18109130859375,70.18109130859375,70.18109130859375,70.18109130859375,70.18109130859375,70.18109130859375,79.50306701660156,79.50306701660156,79.50306701660156,79.50306701660156,79.50306701660156,79.50306701660156,80.71862030029297,80.71862030029297,80.71862030029297,80.71862030029297,80.71862030029297,88.62424468994141,88.62424468994141,93.47401428222656,93.47401428222656,93.47401428222656,93.47401428222656,93.47401428222656,93.47401428222656,93.47401428222656,93.47401428222656,67.43936920166016,67.43936920166016,74.44431304931641,74.44431304931641,82.66734313964844,82.66734313964844,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.99579620361328,89.38016510009766,89.38016510009766,89.38016510009766,89.38016510009766,89.38016510009766,89.38016510009766,89.38016510009766,89.38016510009766,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,57.78789520263672,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,59.76598358154297,60.17784118652344,60.17784118652344,60.17784118652344,60.17784118652344,60.17784118652344,60.17784118652344,60.17784118652344,60.17784118652344,64.07763671875,64.07763671875,64.07763671875,64.07763671875,68.29199981689453,68.29199981689453,68.29199981689453,68.29199981689453,69.15269470214844,69.15269470214844,69.15269470214844,69.15269470214844,69.15269470214844,69.15269470214844,72.82102966308594,72.82102966308594,72.82102966308594,72.82102966308594,72.82102966308594,72.82102966308594,78.12491607666016,78.12491607666016,78.12491607666016,78.60985565185547,78.60985565185547,78.60985565185547,78.60985565185547,78.60985565185547,78.60985565185547,82.02481842041016,82.02481842041016,82.02481842041016,82.02481842041016,83.41539001464844,83.41539001464844,83.41539001464844,83.41539001464844,83.41539001464844,83.41539001464844,83.41539001464844,83.41539001464844,87.89344024658203,87.89344024658203,87.89344024658203,87.89344024658203,87.89344024658203,87.89344024658203,91.15093231201172,91.15093231201172,91.15093231201172,91.15093231201172,91.15093231201172,91.15093231201172,92.96967315673828,92.96967315673828,92.96967315673828,92.96967315673828,92.96967315673828,92.96967315673828,92.96967315673828,92.96967315673828,56.80386352539062,56.80386352539062,56.80386352539062,56.80386352539062,56.80386352539062,56.80386352539062,56.80386352539062,56.80386352539062,60.39362335205078,60.39362335205078,60.39362335205078,60.39362335205078,60.711181640625,60.711181640625,60.711181640625,60.711181640625,68.02986145019531,68.02986145019531,68.02986145019531,68.02986145019531,68.02986145019531,74.45735168457031,74.45735168457031,74.45735168457031,74.45735168457031,74.45735168457031,74.45735168457031,74.45735168457031,81.23640441894531,81.23640441894531,81.23640441894531,81.23640441894531,81.23640441894531,81.23640441894531,81.23640441894531,81.23640441894531,90.27915954589844,90.27915954589844,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,81.98641967773438,60.69623565673828,60.69623565673828,66.50292205810547,66.50292205810547,74.04212951660156,74.04212951660156,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,75.77394104003906,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,80.66897583007812,86.45558929443359,86.45558929443359,86.45558929443359,86.45558929443359,86.45558929443359,86.45558929443359,86.45558929443359,93.38961791992188,93.38961791992188,93.38961791992188,93.38961791992188,93.38961791992188,93.38961791992188,93.38961791992188,93.38961791992188,56.25328063964844,56.25328063964844,56.25328063964844,56.25328063964844,56.25328063964844,56.25328063964844,56.25328063964844,56.25328063964844,64.44850921630859,64.44850921630859,64.44850921630859,64.44850921630859,64.44850921630859,64.44850921630859,64.44850921630859,64.44850921630859,70.74894714355469,70.74894714355469,78.72325897216797,78.72325897216797,81.57761383056641,81.57761383056641,81.57761383056641,81.57761383056641,81.57761383056641,81.57761383056641,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,87.44623565673828,93.50575256347656,93.50575256347656,93.50575256347656,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,60.42335510253906,70.14920806884766,70.14920806884766,70.14920806884766,76.325927734375,76.325927734375,76.325927734375,76.325927734375,76.325927734375,76.325927734375,76.325927734375,76.325927734375,82.61362457275391,82.61362457275391,92.41506958007812,92.41506958007812,58.47480773925781,58.47480773925781,60.13372802734375,60.13372802734375,60.13372802734375,60.13372802734375,60.13372802734375,65.96861267089844,65.96861267089844,72.98995971679688,72.98995971679688,72.98995971679688,72.98995971679688,72.98995971679688,72.98995971679688,72.98995971679688,72.98995971679688,82.42176055908203,82.42176055908203,82.42176055908203,82.42176055908203,82.42176055908203,82.42176055908203,82.42176055908203,88.95756530761719,88.95756530761719,93.50675201416016,93.50675201416016,93.50675201416016,56.45735168457031,56.45735168457031,56.45735168457031,56.45735168457031,56.45735168457031,64.69114685058594,64.69114685058594,72.71879577636719,72.71879577636719,74.23982238769531,74.23982238769531,81.84430694580078,81.84430694580078,81.84430694580078,81.84430694580078,81.84430694580078,81.84430694580078,81.84430694580078,81.84430694580078,90.32712554931641,90.32712554931641,90.32712554931641,90.32712554931641,90.32712554931641,90.32712554931641,90.32712554931641,65.02384948730469,65.02384948730469,65.02384948730469,59.35999298095703,59.35999298095703,66.05004119873047,66.05004119873047,66.05004119873047,66.05004119873047,66.05004119873047,66.05004119873047,66.05004119873047,66.05004119873047,75.08258056640625,75.08258056640625,80.85683441162109,80.85683441162109,90.49126434326172,90.49126434326172,90.49126434326172,90.49126434326172,90.49126434326172,90.49126434326172,90.49126434326172,90.49126434326172,55.08136749267578,55.08136749267578,56.26734161376953,56.26734161376953,56.26734161376953,56.26734161376953,56.26734161376953,56.26734161376953,56.69294738769531,56.69294738769531,58.00114440917969,58.00114440917969,58.00114440917969,58.00114440917969,61.36978912353516,61.36978912353516,61.36978912353516,61.36978912353516,61.36978912353516,61.36978912353516,61.36978912353516,63.50666046142578,63.50666046142578,63.50666046142578,63.50666046142578,65.01111602783203,65.01111602783203,65.01111602783203,65.01111602783203,70.61979675292969,70.61979675292969,70.61979675292969,70.61979675292969,71.93754577636719,71.93754577636719,71.93754577636719,71.93754577636719,76.94849395751953,76.94849395751953,76.94849395751953,77.87371063232422,77.87371063232422,79.4632568359375,79.4632568359375,79.4632568359375,79.4632568359375,79.4632568359375,79.4632568359375,85.27152252197266,85.27152252197266,85.64406585693359,85.64406585693359,85.64406585693359,85.64406585693359,85.64406585693359,85.64406585693359,85.64406585693359,85.64406585693359,86.52280426025391,86.52280426025391,89.23383331298828,89.23383331298828,89.23383331298828,93.50080871582031,93.50080871582031,93.50080871582031,93.50080871582031,93.50080871582031,93.50080871582031,93.50080871582031,93.50080871582031,63.36238861083984,63.36238861083984,73.02790832519531,73.02790832519531,84.06887054443359,84.06887054443359,91.56404876708984,91.56404876708984,59.07169342041016,59.07169342041016,67.79663848876953,67.79663848876953,78.53748321533203,78.53748321533203,81.60889434814453,81.60889434814453,81.60889434814453,81.60889434814453,81.60889434814453,81.60889434814453,81.60889434814453,81.60889434814453,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,85.95731353759766,90.86485290527344,90.86485290527344,90.86485290527344,90.86485290527344,90.86485290527344,90.86485290527344,90.86485290527344,90.86485290527344,92.64026641845703,92.64026641845703,92.64026641845703,92.64026641845703,92.64026641845703,92.64026641845703,92.64026641845703,92.64026641845703,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,86.46820068359375,61.00032806396484,61.00032806396484,61.00032806396484,61.00032806396484,67.55027008056641,67.55027008056641,67.55027008056641,67.55027008056641,67.55027008056641,80.65862274169922,80.65862274169922,85.86404418945312,85.86404418945312,85.86404418945312,85.86404418945312,85.86404418945312,91.47239685058594,91.47239685058594,59.92160034179688,59.92160034179688,67.2628173828125,67.2628173828125,76.98992156982422,76.98992156982422,82.70193481445312,82.70193481445312,90.32752227783203,90.32752227783203,90.32752227783203,90.32752227783203,90.32752227783203,90.32752227783203,90.32752227783203,83.53341674804688,83.53341674804688,83.53341674804688,67.03411102294922,67.03411102294922,67.03411102294922,67.03411102294922,67.03411102294922,67.03411102294922,67.03411102294922,67.03411102294922,72.028076171875,72.028076171875,72.028076171875,72.028076171875,72.028076171875,72.028076171875,72.028076171875,76.28324890136719,76.28324890136719,83.57776641845703,83.57776641845703,93.47786712646484,93.47786712646484,93.47786712646484,93.47786712646484,93.47786712646484,93.47786712646484,93.47786712646484,93.47786712646484,63.75933837890625,63.75933837890625,71.22445678710938,71.22445678710938,71.22445678710938,71.22445678710938,71.22445678710938,71.22445678710938,71.22445678710938,71.22445678710938,78.18563079833984,78.18563079833984,78.18563079833984,78.18563079833984,78.18563079833984,78.18563079833984,78.18563079833984,78.18563079833984,88.6412353515625,88.6412353515625,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,92.64311981201172,60.08168029785156,60.08168029785156,60.08168029785156,60.08168029785156,60.08168029785156,60.08168029785156,60.08168029785156,60.08168029785156,68.87773895263672,68.87773895263672,75.80260467529297,75.80260467529297,86.18306732177734,86.18306732177734,86.18306732177734,86.18306732177734,86.18306732177734,86.18306732177734,86.18306732177734,93.50625610351562,93.50625610351562,93.50625610351562,93.50625610351562,93.50625610351562,93.50625610351562,93.50625610351562,93.50625610351562,68.58309936523438,68.58309936523438,68.58309936523438,68.58309936523438,68.58309936523438,68.58309936523438,68.58309936523438,68.58309936523438,76.81168365478516,76.81168365478516,76.81168365478516,76.81168365478516,76.81168365478516,76.81168365478516,76.81168365478516,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,86.98482513427734,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,93.49144744873047,66.43617248535156,66.43617248535156,66.43617248535156,66.43617248535156,66.43617248535156,66.43617248535156,66.43617248535156,67.64743041992188,67.64743041992188,76.18366241455078,76.18366241455078,83.68055725097656,83.68055725097656,83.68055725097656,83.68055725097656,83.68055725097656,83.68055725097656,83.68055725097656,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,91.66897583007812,64.32966613769531,64.32966613769531,74.43008422851562,74.43008422851562,74.43008422851562,74.43008422851562,74.43008422851562,74.43008422851562,74.43008422851562,74.43008422851562,81.49343109130859,81.49343109130859,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,90.07016754150391,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,92.01239776611328,65.00926971435547,65.00926971435547,74.75789642333984,74.75789642333984,74.75789642333984,74.75789642333984,74.75789642333984,74.75789642333984,74.75789642333984,74.75789642333984,83.0897216796875,83.0897216796875,83.0897216796875,83.0897216796875,83.0897216796875,83.0897216796875,83.0897216796875,83.0897216796875,90.72132873535156,90.72132873535156,64.54538726806641,64.54538726806641,72.02775573730469,72.02775573730469,83.20520782470703,83.20520782470703,93.30758666992188,93.30758666992188,64.28062438964844,64.28062438964844,64.28062438964844,64.28062438964844,64.28062438964844,64.28062438964844,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,65.26565551757812,69.88307189941406,69.88307189941406,69.88307189941406,69.88307189941406,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,74.87474822998047,79.93443298339844,79.93443298339844,79.93443298339844,79.93443298339844,84.01944732666016,84.01944732666016,84.01944732666016,84.01944732666016,84.01944732666016,84.01944732666016,84.01944732666016,84.01944732666016,85.64749908447266,85.64749908447266,85.64749908447266,85.64749908447266,85.64749908447266,85.64749908447266,89.56269836425781,89.56269836425781,89.56269836425781,89.56269836425781,89.56269836425781,89.56269836425781,73.02622222900391,73.02622222900391,73.02622222900391,65.76905059814453,65.76905059814453,65.76905059814453,65.76905059814453,65.76905059814453,65.76905059814453,65.76905059814453,65.76905059814453,67.53262329101562,67.53262329101562,70.20562744140625,70.20562744140625,70.20562744140625,70.20562744140625,75.89164733886719,75.89164733886719,76.13132476806641,76.13132476806641,76.13132476806641,76.13132476806641,76.13132476806641,76.13132476806641,76.13132476806641,76.13132476806641,80.58908843994141,80.58908843994141,80.58908843994141,80.58908843994141,84.26808166503906,84.26808166503906,84.26808166503906,84.26808166503906,84.26808166503906,88.55105590820312,88.55105590820312,88.55105590820312,88.55105590820312,88.55105590820312,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,86.76372528076172,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,70.83463287353516,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,81.62221527099609,88.61209869384766,88.61209869384766,88.61209869384766,88.61209869384766,88.61209869384766,88.61209869384766,88.61209869384766,65.86896514892578,65.86896514892578,75.02179718017578,75.02179718017578,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,83.03622436523438,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,86.54811859130859,91.6435546875,91.6435546875,68.90618896484375,68.90618896484375,68.90618896484375,68.90618896484375,68.90618896484375,68.90618896484375,68.90618896484375,77.21785736083984,77.21785736083984,77.21785736083984,77.21785736083984,77.21785736083984,77.21785736083984,77.21785736083984,77.21785736083984,87.81324005126953,87.81324005126953,93.50533294677734,93.50533294677734,93.50533294677734,93.50533294677734,93.50533294677734,93.50533294677734,93.50533294677734,93.50533294677734,73.31687927246094,73.31687927246094,80.44448089599609,80.44448089599609,80.44448089599609,80.44448089599609,80.44448089599609,80.44448089599609,80.44448089599609,88.31233215332031,88.31233215332031,88.31233215332031,88.31233215332031,88.31233215332031,88.31233215332031,88.31233215332031,88.31233215332031,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,91.22542572021484,70.09912109375,70.09912109375,70.09912109375,63.03936767578125,63.03936767578125,70.48725891113281,70.48725891113281,70.48725891113281,70.48725891113281,70.48725891113281,70.48725891113281,70.48725891113281,70.48725891113281,80.67311859130859,80.67311859130859,80.67311859130859,80.67311859130859,80.67311859130859,80.67311859130859,80.67311859130859,80.67311859130859,88.53079223632812,88.53079223632812,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,60.72499084472656,64.54467010498047,64.54467010498047,70.94651794433594,70.94651794433594,80.89250183105469,80.89250183105469,87.66527557373047,87.66527557373047,87.66527557373047,87.66527557373047,87.66527557373047,89.65005493164062,89.65005493164062,56.66415405273438,56.66415405273438,56.66415405273438,56.66415405273438,56.66415405273438,56.66415405273438,56.66415405273438,63.56136322021484,63.56136322021484,63.56136322021484,63.56136322021484,63.56136322021484,63.56136322021484,73.11252593994141,73.11252593994141,83.03131103515625,83.03131103515625,83.03131103515625,83.03131103515625,83.03131103515625,83.03131103515625,83.03131103515625,83.03131103515625,90.51451873779297,90.51451873779297,90.51451873779297,90.51451873779297,90.51451873779297,90.51451873779297,90.51451873779297,57.50711059570312,57.50711059570312,64.53062438964844,64.53062438964844,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,75.47454071044922,80.64588165283203,80.64588165283203,84.87081146240234,84.87081146240234,91.91138458251953,91.91138458251953,91.91138458251953,91.91138458251953,91.91138458251953,91.91138458251953,91.91138458251953,60.072509765625,60.072509765625,69.27068328857422,69.27068328857422,76.41706085205078,76.41706085205078,76.41706085205078,76.41706085205078,76.41706085205078,76.41706085205078,76.41706085205078,76.41706085205078,84.06797027587891,84.06797027587891,93.02738952636719,93.02738952636719,61.73857879638672,61.73857879638672,61.73857879638672,61.73857879638672,61.73857879638672,61.73857879638672,61.73857879638672,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,68.2197265625,69.12873077392578,69.12873077392578,70.47400665283203,70.47400665283203,70.47400665283203,70.47400665283203,70.47400665283203,70.47400665283203,75.4862060546875,75.4862060546875,76.72000122070312,76.72000122070312,76.72000122070312,76.72000122070312,76.72000122070312,76.72000122070312,80.89197540283203,80.89197540283203,80.89197540283203,80.89197540283203,80.89197540283203,80.89197540283203,82.86827850341797,82.86827850341797,84.40201568603516,84.40201568603516,84.40201568603516,84.40201568603516,86.86290740966797,86.86290740966797,86.86290740966797,86.86290740966797,86.86290740966797,89.55381011962891,89.55381011962891,90.87355804443359,90.87355804443359,90.87355804443359,90.87355804443359,90.87355804443359,90.87355804443359,59.80887603759766,59.80887603759766,62.69879150390625,62.69879150390625,63.85877227783203,63.85877227783203,63.85877227783203,63.85877227783203,63.85877227783203,63.85877227783203,68.34971618652344,68.34971618652344,68.34971618652344,68.34971618652344,75.93006134033203,75.93006134033203,87.27474975585938,87.27474975585938,87.27474975585938,87.27474975585938,87.27474975585938,91.51683044433594,91.51683044433594,91.51683044433594,69.48294067382812,69.48294067382812,77.30452728271484,77.30452728271484,85.48491668701172,85.48491668701172,93.50751495361328,93.50751495361328,93.50751495361328,93.50751495361328,93.50751495361328,93.50751495361328,93.50751495361328,68.13674163818359,68.13674163818359,68.13674163818359,68.13674163818359,68.13674163818359,68.13674163818359,68.94052124023438,68.94052124023438,68.94052124023438,68.94052124023438,68.94052124023438,68.94052124023438,68.94052124023438,68.94052124023438,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,73.2889404296875,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,79.97189331054688,84.77151489257812,84.77151489257812,84.77151489257812,84.77151489257812,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,93.50868988037109,70.03861236572266,70.03861236572266,76.75630187988281,76.75630187988281,83.03983306884766,83.03983306884766,83.03983306884766,83.03983306884766,83.03983306884766,83.03983306884766,83.03983306884766,92.09913635253906,92.09913635253906,92.09913635253906,92.09913635253906,92.09913635253906,92.09913635253906,66.03365325927734,66.03365325927734,66.03365325927734,66.03365325927734,66.03365325927734,66.03365325927734,66.03365325927734,66.03365325927734,75.44303894042969,75.44303894042969,75.44303894042969,75.44303894042969,75.44303894042969,75.44303894042969,75.44303894042969,75.44303894042969,82.04724884033203,82.04724884033203,82.04724884033203,82.04724884033203,82.04724884033203,82.04724884033203,82.04724884033203,91.51971435546875,91.51971435546875,66.74604797363281,66.74604797363281,66.74604797363281,66.74604797363281,66.74604797363281,66.74604797363281,66.74604797363281,66.74604797363281,74.04712677001953,74.04712677001953,85.74478912353516,85.74478912353516,93.48866271972656,93.48866271972656,93.48866271972656,93.48866271972656,93.48866271972656,93.48866271972656,93.48866271972656,93.48866271972656,68.58683776855469,68.58683776855469,68.58683776855469,68.58683776855469,70.93360137939453,70.93360137939453,70.93360137939453,70.93360137939453,70.93360137939453,70.93360137939453,70.93360137939453,80.62937927246094,80.62937927246094,89.01512908935547,89.01512908935547,89.01512908935547,89.01512908935547,89.01512908935547,89.01512908935547,89.01512908935547,89.01512908935547,66.66761016845703,66.66761016845703,66.66761016845703,66.66761016845703,66.66761016845703,66.66761016845703,66.66761016845703,72.99156951904297,72.99156951904297,72.99156951904297,72.99156951904297,72.99156951904297,72.99156951904297,72.99156951904297,83.78636169433594,83.78636169433594,91.66681671142578,91.66681671142578,91.66681671142578,91.66681671142578,91.66681671142578,91.66681671142578,91.66681671142578,91.66681671142578,69.32276916503906,69.32276916503906,75.70343017578125,75.70343017578125,77.85988616943359,77.85988616943359,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,84.73233795166016,90.50077819824219,90.50077819824219,90.50077819824219,90.50077819824219,90.50077819824219,90.50077819824219,90.50077819824219,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,67.35358428955078,73.47650909423828,73.47650909423828,73.47650909423828,73.47650909423828,73.47650909423828,73.47650909423828,73.47650909423828,73.47650909423828,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,83.41915130615234,90.43563842773438,90.43563842773438,69.19962310791016,69.19962310791016,69.19962310791016,69.19962310791016,69.19962310791016,69.19962310791016,69.19962310791016,69.19962310791016,76.19036102294922,76.19036102294922,76.19036102294922,76.19036102294922,76.19036102294922,77.77864074707031,77.77864074707031,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,87.91800689697266,78.98310089111328,78.98310089111328,78.98310089111328,74.18768310546875,74.18768310546875,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,85.20058441162109,92.71154022216797,92.71154022216797,92.71154022216797,92.71154022216797,92.71154022216797,92.71154022216797,92.71154022216797,71.97221374511719,71.97221374511719,79.78122711181641,79.78122711181641,79.78122711181641,79.78122711181641,79.78122711181641,79.78122711181641,79.78122711181641,79.78122711181641,91.05268096923828,91.05268096923828,70.52313995361328,70.52313995361328,70.52313995361328,70.52313995361328,70.52313995361328,70.52313995361328,71.65408325195312,71.65408325195312,80.95565032958984,80.95565032958984,88.51836395263672,88.51836395263672,88.51836395263672,88.51836395263672,88.51836395263672,69.74201965332031,69.74201965332031,69.74201965332031,69.74201965332031,69.74201965332031,69.74201965332031,69.74201965332031,79.81557464599609,79.81557464599609,87.87705993652344,87.87705993652344,87.87705993652344,87.87705993652344,87.87705993652344,87.87705993652344,87.87705993652344,87.87705993652344,93.47882843017578,93.47882843017578,93.47882843017578,93.47882843017578,93.47882843017578,93.47882843017578,93.47882843017578,93.47882843017578,60.72151184082031,60.72151184082031,66.75293731689453,66.75293731689453,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,76.43819427490234,86.56311798095703,86.56311798095703,88.23362731933594,88.23362731933594,88.23362731933594,88.23362731933594,88.23362731933594,88.23362731933594,91.52608489990234,91.52608489990234,91.52608489990234,91.52608489990234,91.52608489990234,91.52608489990234,59.28102874755859,59.28102874755859,59.28102874755859,61.61688995361328,61.61688995361328,61.61688995361328,61.61688995361328,61.61688995361328,61.61688995361328,65.00170135498047,65.00170135498047,65.00170135498047,65.00170135498047,65.00170135498047,65.00170135498047,68.01817321777344,68.01817321777344,68.01817321777344,68.01817321777344,68.01817321777344,68.01817321777344,68.01817321777344,68.01817321777344,71.58223724365234,71.58223724365234,71.58223724365234,71.58223724365234,71.58223724365234,71.58223724365234,73.50276947021484,73.50276947021484,73.50276947021484,73.50276947021484,73.50276947021484,73.50276947021484,73.50276947021484,73.50276947021484,75.54170227050781,75.54170227050781,75.54170227050781,75.54170227050781,79.07663726806641,79.07663726806641,79.07663726806641,79.07663726806641,79.07663726806641,79.07663726806641,79.07663726806641,79.07663726806641,81.44186401367188,81.44186401367188,81.44186401367188,81.44186401367188,84.02812194824219,84.02812194824219,84.02812194824219,84.02812194824219,84.02812194824219,84.02812194824219,88.67240905761719,88.67240905761719,88.67240905761719,88.67240905761719,88.67240905761719,88.67240905761719,88.67240905761719,90.51644897460938,90.51644897460938,90.51644897460938,90.51644897460938,90.51644897460938,90.51644897460938,71.02232360839844,71.02232360839844,71.02232360839844,71.02232360839844,71.02232360839844,71.02232360839844,71.02232360839844,71.02232360839844,59.42634582519531,59.42634582519531,59.42634582519531,59.42634582519531,63.53160095214844,63.53160095214844,63.53160095214844,63.53160095214844,63.53160095214844,63.53160095214844,63.53160095214844,67.18070220947266,67.18070220947266,67.18070220947266,67.18070220947266,67.18070220947266,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,75.34752655029297,83.32682037353516,83.32682037353516,83.32682037353516,83.32682037353516,83.32682037353516,91.33798980712891,91.33798980712891,63.19078063964844,63.19078063964844,72.03448486328125,72.03448486328125,79.39531707763672,79.39531707763672,79.39531707763672,79.39531707763672,79.39531707763672,79.39531707763672,79.39531707763672,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,87.85916900634766,88.16561126708984,88.16561126708984,88.16561126708984,88.16561126708984,88.16561126708984,88.16561126708984,88.16561126708984,88.16561126708984,69.33412170410156,69.33412170410156,71.28590393066406,71.28590393066406,71.28590393066406,71.28590393066406,77.72646331787109,77.72646331787109,84.99192810058594,84.99192810058594,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,93.50878143310547,67.99485778808594,67.99485778808594,67.99485778808594,67.99485778808594,67.99485778808594,67.99485778808594,67.99485778808594,67.99485778808594,74.25265502929688,74.25265502929688,74.25265502929688,74.25265502929688,74.25265502929688,74.25265502929688,74.25265502929688,84.54963684082031,84.54963684082031,90.80158233642578,90.80158233642578,90.80158233642578,90.80158233642578,62.94834136962891,62.94834136962891,62.94834136962891,62.94834136962891,62.94834136962891,62.94834136962891,62.94834136962891,62.94834136962891,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,73.11503601074219,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,83.02025604248047,87.40826416015625,87.40826416015625,87.40826416015625,87.40826416015625,87.40826416015625,87.40826416015625,87.40826416015625,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,91.80188751220703,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,65.18490600585938,71.50273132324219,71.50273132324219,71.50273132324219,71.50273132324219,71.50273132324219,71.50273132324219,71.50273132324219,81.47611999511719,81.47611999511719,81.47611999511719,81.47611999511719,81.47611999511719,81.47611999511719,81.47611999511719,81.47611999511719,87.69133758544922,87.69133758544922,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,93.49978637695312,70.57017517089844,70.57017517089844,76.92537689208984,76.92537689208984,87.64176177978516,87.64176177978516,87.64176177978516,87.64176177978516,87.64176177978516,87.64176177978516,87.64176177978516,87.64176177978516,91.97518920898438,91.97518920898438,91.97518920898438,91.97518920898438,91.97518920898438,87.18685913085938,87.18685913085938,87.18685913085938,72.27439880371094,72.27439880371094,81.96144104003906,81.96144104003906,89.01717376708984,89.01717376708984,89.01717376708984,89.01717376708984,89.01717376708984,89.01717376708984,89.01717376708984,65.32305145263672,65.32305145263672,65.32305145263672,65.32305145263672,65.32305145263672,65.32305145263672,74.77120208740234,74.77120208740234,81.48777008056641,81.48777008056641,81.48777008056641,81.48777008056641,81.48777008056641,81.48777008056641,81.48777008056641,81.48777008056641,89.30294036865234,89.30294036865234,93.50907897949219,93.50907897949219,93.50907897949219,72.31034851074219,72.31034851074219,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,79.15107727050781,81.03224182128906,81.03224182128906,81.03224182128906,81.03224182128906,81.03224182128906,81.03224182128906,91.50125885009766,91.50125885009766,68.18024444580078,68.18024444580078,68.18024444580078,68.18024444580078,68.18024444580078,68.18024444580078,74.62014007568359,74.62014007568359,74.62014007568359,74.62014007568359,74.62014007568359,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,84.6802978515625,92.27972412109375,92.27972412109375,92.27972412109375,92.27972412109375,92.27972412109375,92.27972412109375,92.27972412109375,92.27972412109375,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,68.46572113037109,76.91586303710938,76.91586303710938,76.91586303710938,76.91586303710938,76.91586303710938,76.91586303710938,76.91586303710938,76.91586303710938,82.73468780517578,82.73468780517578,91.86362457275391,91.86362457275391,91.86362457275391,91.86362457275391,91.86362457275391,91.86362457275391,91.86362457275391,69.14235687255859,69.14235687255859,71.17290496826172,71.17290496826172,71.63955688476562,71.63955688476562,72.8067626953125,72.8067626953125,72.8067626953125,72.8067626953125,74.28997802734375,74.28997802734375,74.28997802734375,74.28997802734375,74.28997802734375,74.28997802734375,74.28997802734375,74.28997802734375,78.76998138427734,78.76998138427734,79.23577880859375,79.23577880859375,79.23577880859375,79.23577880859375,79.23577880859375,79.23577880859375,79.23577880859375,79.23577880859375,80.00933074951172,80.00933074951172,80.00933074951172,80.00933074951172,84.47960662841797,84.47960662841797,84.47960662841797,84.47960662841797,84.47960662841797,86.2100830078125,86.2100830078125,87.55686187744141,87.55686187744141,87.55686187744141,87.55686187744141,87.55686187744141,87.55686187744141,92.37212371826172,92.37212371826172,92.37212371826172,66.83811187744141,66.83811187744141,67.87387847900391,67.87387847900391,67.87387847900391,67.87387847900391,67.87387847900391,67.87387847900391,71.7452392578125,71.7452392578125,71.7452392578125,71.7452392578125,71.7452392578125,74.59374237060547,74.59374237060547,75.38993072509766,75.38993072509766,75.38993072509766,75.38993072509766,75.38993072509766,75.38993072509766,75.38993072509766,75.38993072509766,75.87841033935547,75.87841033935547,75.87841033935547,75.87841033935547,75.87841033935547,75.87841033935547,83.79144287109375,83.79144287109375,83.79144287109375,93.50871276855469,93.50871276855469,93.50871276855469,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,75.42973327636719,85.16568756103516,85.16568756103516,85.16568756103516,85.16568756103516,85.16568756103516,85.16568756103516,92.94384002685547,92.94384002685547,92.94384002685547,92.94384002685547,92.94384002685547,92.94384002685547,92.94384002685547,73.7950439453125,73.7950439453125,80.93919372558594,80.93919372558594,80.93919372558594,80.93919372558594,80.93919372558594,80.93919372558594,80.93919372558594,80.93919372558594,92.90096282958984,92.90096282958984,74.13681030273438,74.13681030273438,74.13681030273438,74.13681030273438,74.13681030273438,74.61128234863281,74.61128234863281,74.61128234863281,74.61128234863281,74.61128234863281,74.61128234863281,74.61128234863281,74.61128234863281,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,78.95970153808594,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,85.64265441894531,90.44227600097656,90.44227600097656,90.44227600097656,90.44227600097656,89.73764801025391,89.73764801025391,89.73764801025391,89.73764801025391,79.54387664794922,79.54387664794922,79.54387664794922,79.54387664794922,79.54387664794922,79.54387664794922,79.54387664794922,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,88.68721771240234,93.50839996337891,93.50839996337891,93.50839996337891,93.50839996337891,93.50839996337891,93.50839996337891,93.50839996337891,93.50839996337891,76.48551177978516,76.48551177978516,76.48551177978516,76.48551177978516,76.48551177978516,76.48551177978516,76.48551177978516,83.13825988769531,83.13825988769531,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,90.60643005371094,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,93.48860168457031,48.52798461914062,48.52798461914062,48.52798461914062,48.52798461914062,48.52798461914062,48.52798461914062,48.52798461914062,48.52798461914062,53.33538818359375,53.33538818359375,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,62.79693603515625,70.5697021484375,70.5697021484375,81.86783599853516,81.86783599853516,92.78266143798828,92.78266143798828,92.78266143798828,92.78266143798828,92.78266143798828,92.78266143798828,92.78266143798828,51.97110748291016,51.97110748291016,59.49669647216797,59.49669647216797,59.49669647216797,59.49669647216797,59.49669647216797,61.73386383056641,61.73386383056641,71.78677368164062,71.78677368164062,71.78677368164062,71.78677368164062,71.78677368164062,71.78677368164062,71.78677368164062,71.78677368164062,79.19760894775391,79.19760894775391,86.38594818115234,86.38594818115234,86.38594818115234,86.38594818115234,86.38594818115234,86.38594818115234,86.38594818115234,86.38594818115234,93.48544311523438,93.48544311523438,93.48544311523438,57.13991546630859,57.13991546630859,57.13991546630859,57.13991546630859,57.13991546630859,57.13991546630859,57.13991546630859,63.82923126220703,63.82923126220703,72.75338745117188,72.75338745117188,72.75338745117188,72.75338745117188,72.75338745117188,72.75338745117188,72.75338745117188,72.75338745117188,80.12559509277344,80.12559509277344,80.12559509277344,80.12559509277344,80.12559509277344,80.12559509277344,80.12559509277344,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,83.02497100830078,90.46289825439453,90.46289825439453,90.46289825439453,51.70716857910156,51.70716857910156,51.70716857910156,51.70716857910156,51.70716857910156,51.70716857910156,51.70716857910156,61.75144195556641,61.75144195556641,68.83266448974609,68.83266448974609,68.83266448974609,68.83266448974609,68.83266448974609,68.83266448974609,68.83266448974609,68.83266448974609,75.94693756103516,75.94693756103516,75.94693756103516,75.94693756103516,75.94693756103516,75.94693756103516,85.85157775878906,85.85157775878906,85.85157775878906,85.85157775878906,85.85157775878906,85.85157775878906,85.85157775878906,85.85157775878906,93.50843811035156,93.50843811035156,93.50843811035156,60.09709930419922,60.09709930419922,60.09709930419922,60.09709930419922,60.09709930419922,60.09709930419922,60.09709930419922,60.09709930419922,64.53888702392578,64.53888702392578,64.53888702392578,64.53888702392578,69.82286834716797,69.82286834716797,77.16671752929688,77.16671752929688,77.16671752929688,77.16671752929688,86.98599243164062,86.98599243164062,86.98599243164062,86.98599243164062,86.98599243164062,86.98599243164062,86.98599243164062,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,93.50921630859375,56.41932678222656,56.41932678222656,56.41932678222656,56.41932678222656,56.41932678222656,56.41932678222656,56.41932678222656,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,64.56163024902344,76.29594421386719,76.29594421386719,76.29594421386719,76.29594421386719,76.29594421386719,76.29594421386719,76.29594421386719,77.48968505859375,77.48968505859375,86.06780242919922,86.06780242919922,93.20376586914062,93.20376586914062,56.53888702392578,56.53888702392578,66.04573822021484,66.04573822021484,66.04573822021484,66.04573822021484,66.04573822021484,66.04573822021484,66.04573822021484,66.04573822021484,74.15716552734375,74.15716552734375,74.15716552734375,74.15716552734375,74.15716552734375,74.15716552734375,74.15716552734375,82.38082122802734,82.38082122802734,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,89.08772277832031,53.38248443603516,53.38248443603516,60.04488372802734,60.04488372802734,60.04488372802734,60.04488372802734,60.04488372802734,60.04488372802734,60.80176544189453,60.80176544189453,60.80176544189453,60.80176544189453,60.80176544189453,60.80176544189453,64.51638793945312,64.51638793945312,64.51638793945312,64.51638793945312,64.51638793945312,64.51638793945312,68.02175903320312,68.02175903320312,68.02175903320312,68.02175903320312,68.02175903320312,68.02175903320312,68.02175903320312,70.41510009765625,70.41510009765625,70.41510009765625,70.41510009765625,70.41510009765625,70.41510009765625,70.41510009765625,70.41510009765625,74.15294647216797,74.15294647216797,74.15294647216797,74.15294647216797,74.15294647216797,74.15294647216797,79.15451812744141,79.15451812744141,79.15451812744141,80.14786529541016,80.14786529541016,80.14786529541016,80.14786529541016,80.14786529541016,80.14786529541016,80.14786529541016,80.14786529541016,84.23004150390625,84.23004150390625,84.23004150390625,84.23004150390625,84.23004150390625,84.23004150390625,89.61907958984375,89.61907958984375,89.61907958984375,91.14070892333984,91.14070892333984,91.14070892333984,91.14070892333984,91.14070892333984,91.14070892333984,93.47447967529297,93.47447967529297,93.47447967529297,54.85903930664062,54.85903930664062,54.85903930664062,54.85903930664062,54.85903930664062,54.85903930664062,60.73307037353516,60.73307037353516,61.83038330078125,61.83038330078125,61.83038330078125,61.83038330078125,61.83038330078125,61.83038330078125,61.83038330078125,61.83038330078125,66.11115264892578,66.11115264892578,66.11115264892578,66.11115264892578,66.11115264892578,66.11115264892578,71.35794067382812,71.35794067382812,71.35794067382812,71.35794067382812,77.11920166015625,77.11920166015625,84.25230407714844,84.25230407714844,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,93.50873565673828,58.65733337402344,58.65733337402344,58.65733337402344,58.65733337402344,58.65733337402344,58.65733337402344,58.65733337402344,67.94125366210938,67.94125366210938,67.94125366210938,67.94125366210938,67.94125366210938,67.94125366210938,67.94125366210938,73.55596923828125,73.55596923828125,73.55596923828125,73.55596923828125,73.55596923828125,73.55596923828125,73.55596923828125,82.48876953125,82.48876953125,91.63693237304688,91.63693237304688,57.9249267578125,57.9249267578125,62.82148742675781,62.82148742675781,62.82148742675781,62.82148742675781,68.12004089355469,68.12004089355469,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,76.24860382080078,86.67207336425781,86.67207336425781,86.67207336425781,86.67207336425781,86.67207336425781,86.67207336425781,86.67207336425781,86.67207336425781,93.48214721679688,93.48214721679688,93.48214721679688,93.48214721679688,93.48214721679688,93.48214721679688,93.48214721679688,93.48214721679688,62.06871032714844,62.06871032714844,71.37964630126953,71.37964630126953,71.37964630126953,71.37964630126953,71.37964630126953,71.37964630126953,71.37964630126953,71.37964630126953,78.98793792724609,78.98793792724609,78.98793792724609,78.98793792724609,78.98793792724609,78.98793792724609,78.98793792724609,78.98793792724609,90.39234161376953,90.39234161376953,57.10166168212891,57.10166168212891,58.37552642822266,58.37552642822266,67.09228515625,67.09228515625,67.09228515625,67.09228515625,67.09228515625,67.09228515625,67.09228515625,75.70082092285156,83.36519622802734,83.36519622802734,91.37837982177734,91.37837982177734,91.37837982177734,91.37837982177734,91.37837982177734,57.39413452148438,57.39413452148438,57.39413452148438,57.39413452148438,57.39413452148438,57.39413452148438,57.39413452148438,68.90221405029297,68.90221405029297,68.90221405029297,68.90221405029297,68.90221405029297,68.90221405029297,68.90221405029297,68.90221405029297,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,75.89766693115234,78.96022796630859,78.96022796630859,78.96022796630859,78.96022796630859,78.96022796630859,78.96022796630859,78.96022796630859,78.96022796630859,90.21089172363281,90.21089172363281,70.79109954833984,70.79109954833984,70.79109954833984,68.23877716064453,68.23877716064453,68.23877716064453,68.23877716064453,68.23877716064453,68.23877716064453,68.23877716064453,68.23877716064453,75.33599090576172,75.33599090576172,85.22245788574219,85.22245788574219,85.22245788574219,85.22245788574219,85.22245788574219,85.22245788574219,85.22245788574219,85.22245788574219,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,92.27271270751953,61.97052001953125,61.97052001953125,73.65029907226562,73.65029907226562,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,77.99960327148438,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,83.47109222412109,91.19878387451172,91.19878387451172,91.19878387451172,91.19878387451172,91.19878387451172,61.55335998535156,61.55335998535156,69.46726226806641,69.46726226806641,69.46726226806641,69.46726226806641,69.46726226806641,69.46726226806641,69.46726226806641,80.32315063476562,80.32315063476562,80.32315063476562,80.32315063476562,80.32315063476562,80.32315063476562,87.64028167724609,87.64028167724609,87.64028167724609,87.64028167724609,87.64028167724609,87.64028167724609,87.64028167724609,87.64028167724609,66.58894348144531,66.58894348144531,66.58894348144531,66.58894348144531,66.58894348144531,66.58894348144531,66.58894348144531,66.58894348144531,65.61347198486328,65.61347198486328,66.37126159667969,66.37126159667969,67.16757202148438,67.16757202148438,67.16757202148438,67.16757202148438,71.7991943359375,71.7991943359375,71.7991943359375,72.94160461425781,72.94160461425781,73.88080596923828,73.88080596923828,73.88080596923828,73.88080596923828,78.98590087890625,78.98590087890625,78.98590087890625,79.37297058105469,79.37297058105469,80.43740844726562,80.43740844726562,82.94112396240234,82.94112396240234,85.26226806640625,85.26226806640625,86.28215789794922,86.28215789794922,86.28215789794922,86.28215789794922,91.25646209716797,91.25646209716797,91.25646209716797,91.25646209716797,91.25646209716797,92.01301574707031,92.01301574707031,93.04525756835938,93.04525756835938,93.04525756835938,93.04525756835938,63.30695343017578,63.30695343017578,63.30695343017578,63.30695343017578,63.30695343017578,67.68080139160156,67.68080139160156,67.68080139160156,67.68080139160156,67.68080139160156,67.68080139160156,80.77651977539062,80.77651977539062,80.77651977539062,80.77651977539062,80.77651977539062,80.77651977539062,89.64201354980469,89.64201354980469,63.50682067871094,63.50682067871094,63.50682067871094,63.50682067871094,63.50682067871094,63.50682067871094,63.50682067871094,72.13749694824219,72.13749694824219,80.36345672607422,80.36345672607422,91.69549560546875,91.69549560546875,91.69549560546875,91.69549560546875,91.69549560546875,91.69549560546875,91.69549560546875,91.69549560546875,66.30690002441406,66.30690002441406,66.30690002441406,66.30690002441406,66.30690002441406,66.30690002441406,66.30690002441406,66.30690002441406,68.89080810546875,68.89080810546875,68.89080810546875,68.89080810546875,68.89080810546875,68.89080810546875,68.89080810546875,68.89080810546875,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,73.23922729492188,79.17974090576172,79.17974090576172,79.17974090576172,79.17974090576172,79.17974090576172,79.17974090576172,79.17974090576172,79.92218017578125,79.92218017578125,79.92218017578125,79.92218017578125,79.92218017578125,79.92218017578125,79.92218017578125,79.92218017578125,84.7218017578125,84.7218017578125,84.7218017578125,84.7218017578125,90.18229675292969,90.18229675292969,90.18229675292969,90.18229675292969,90.18229675292969,90.18229675292969,90.18229675292969,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,83.86569976806641,61.74758911132812,61.74758911132812,61.74758911132812,61.74758911132812,67.07053375244141,67.07053375244141,73.94512176513672,73.94512176513672,73.94512176513672,73.94512176513672,73.94512176513672,73.94512176513672,80.82358551025391,80.82358551025391,86.22087860107422,86.22087860107422,86.22087860107422,86.22087860107422,86.22087860107422,86.22087860107422,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,93.5089111328125,57.45014953613281,57.45014953613281,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,64.87563323974609,72.68321228027344,72.68321228027344,72.68321228027344,72.68321228027344,72.68321228027344,72.68321228027344,74.28592681884766,74.28592681884766,74.28592681884766,74.28592681884766,74.28592681884766,81.82250213623047,81.82250213623047,81.82250213623047,81.82250213623047,81.82250213623047,81.82250213623047,89.16246032714844,89.16246032714844,74.92617797851562,74.92617797851562,74.92617797851562,74.92617797851562,74.92617797851562,74.92617797851562,74.92617797851562,74.92617797851562,58.80307006835938,58.80307006835938,58.80307006835938,58.80307006835938,58.80307006835938,58.80307006835938,58.80307006835938,68.28121185302734,68.28121185302734,76.11257934570312,76.11257934570312,85.91675567626953,85.91675567626953,85.91675567626953,85.91675567626953,85.91675567626953,85.91675567626953,85.91675567626953,85.91675567626953,87.64865875244141,87.64865875244141,87.64865875244141,87.64865875244141,87.64865875244141,87.64865875244141,87.64865875244141,87.64865875244141,93.49091339111328,93.49091339111328,93.49091339111328,93.49091339111328,93.49091339111328,93.49091339111328,93.49091339111328,93.49091339111328,57.67705535888672,57.67705535888672,66.62889099121094,66.62889099121094,66.62889099121094,66.62889099121094,66.62889099121094,66.62889099121094,66.62889099121094,74.45856475830078,74.45856475830078,84.89068603515625,84.89068603515625,93.23954772949219,93.23954772949219,93.23954772949219,93.23954772949219,93.23954772949219,93.23954772949219,93.23954772949219,93.23954772949219,58.20891571044922,58.20891571044922,68.10604858398438,68.10604858398438,68.10604858398438,68.10604858398438,68.10604858398438,69.32563781738281,69.32563781738281,69.32563781738281,69.32563781738281,77.42308807373047,77.42308807373047,85.43338775634766,85.43338775634766,91.63299560546875,91.63299560546875,57.35814666748047,57.35814666748047,64.68743133544922,64.68743133544922,74.65161895751953,74.65161895751953,76.28011322021484,76.28011322021484,76.28011322021484,76.28011322021484,76.28011322021484,83.93386840820312,83.93386840820312,83.93386840820312,83.93386840820312,83.93386840820312,83.93386840820312,83.93386840820312,83.93386840820312,91.84986877441406,91.84986877441406,91.84986877441406,91.84986877441406,91.84986877441406,91.84986877441406,91.84986877441406,91.84986877441406,59.11917114257812,59.11917114257812,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,67.42864227294922,76.64109802246094,76.64109802246094,76.64109802246094,76.64109802246094,76.64109802246094,76.64109802246094,76.64109802246094,83.59554290771484,83.59554290771484,83.59554290771484,83.59554290771484,83.59554290771484,83.59554290771484,93.50278472900391,93.50278472900391,93.50278472900391,62.86522674560547,62.86522674560547,62.86522674560547,62.86522674560547,62.86522674560547,62.86522674560547,62.86522674560547,62.86522674560547,67.51409912109375,67.51409912109375,67.51409912109375,67.51409912109375,67.51409912109375,67.51409912109375,67.51409912109375,67.51409912109375,68.10732269287109,68.10732269287109,68.10732269287109,68.10732269287109,68.10732269287109,68.10732269287109,68.10732269287109,68.10732269287109,72.3238525390625,72.3238525390625,72.3238525390625,72.3238525390625,75.56200408935547,75.56200408935547,75.56200408935547,75.56200408935547,77.34271240234375,77.34271240234375,77.34271240234375,77.34271240234375,77.34271240234375,77.34271240234375,81.10801696777344,81.10801696777344,81.10801696777344,81.10801696777344,81.10801696777344,81.10801696777344,86.83139038085938,86.83139038085938,86.83139038085938,86.83139038085938,86.83139038085938,86.83139038085938,87.66870880126953,87.66870880126953,87.66870880126953,87.66870880126953,87.66870880126953,87.66870880126953,87.66870880126953,87.66870880126953,90.69708251953125,90.69708251953125,90.69708251953125,90.69708251953125,93.50818634033203,93.50818634033203,93.50818634033203,93.50818634033203,93.50818634033203,93.50818634033203,93.50818634033203,60.43444061279297,60.43444061279297,60.43444061279297,60.43444061279297,60.43444061279297,60.43444061279297,60.43444061279297,60.43444061279297,62.47344970703125,62.47344970703125,62.47344970703125,62.47344970703125,62.47344970703125,62.47344970703125,62.47344970703125,62.47344970703125,64.57698059082031,64.57698059082031,65.06957244873047,65.06957244873047,65.06957244873047,65.06957244873047,65.06957244873047,65.06957244873047,65.06957244873047,65.06957244873047,69.73750305175781,69.73750305175781,69.73750305175781,69.73750305175781,69.73750305175781,69.73750305175781,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,72.92931365966797,73.68505096435547,73.68505096435547,73.68505096435547,73.68505096435547,79.20462036132812,79.20462036132812,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,84.8367919921875,93.20026397705078,93.20026397705078,61.46640014648438,61.46640014648438,61.46640014648438,61.46640014648438,61.46640014648438,61.46640014648438,61.46640014648438,68.56741333007812,68.56741333007812,78.01949310302734,78.01949310302734,84.88909912109375,84.88909912109375,84.88909912109375,84.88909912109375,84.88909912109375,84.88909912109375,93.50669860839844,93.50669860839844,93.50669860839844,61.06346130371094,61.06346130371094,65.05674743652344,65.05674743652344,72.25282287597656,72.25282287597656,72.25282287597656,72.25282287597656,72.25282287597656,72.25282287597656,72.25282287597656,79.45522308349609,79.45522308349609,79.45522308349609,79.45522308349609,87.26455688476562,87.26455688476562,87.26455688476562,87.26455688476562,87.26455688476562,90.04270935058594,90.04270935058594,90.04270935058594,68.57448577880859,68.57448577880859,68.57448577880859,69.71600341796875,69.71600341796875,69.71600341796875,69.71600341796875,69.71600341796875,69.71600341796875,69.71600341796875,69.71600341796875,77.15511322021484,77.15511322021484,77.15511322021484,77.15511322021484,77.15511322021484,77.15511322021484,85.40296173095703,85.40296173095703,85.40296173095703,85.40296173095703,85.40296173095703,85.40296173095703,85.40296173095703,92.77066040039062,92.77066040039062,64.64795684814453,64.64795684814453,64.64795684814453,64.64795684814453,64.64795684814453,64.64795684814453,64.64795684814453,72.22097015380859,72.22097015380859,82.34239959716797,82.34239959716797,85.85646820068359,85.85646820068359,91.27615356445312,91.27615356445312,63.57787322998047,63.57787322998047,70.86335754394531,70.86335754394531,78.26471710205078,78.26471710205078,78.26471710205078,78.26471710205078,78.26471710205078,78.26471710205078,78.26471710205078,78.26471710205078,86.75569152832031,86.75569152832031,86.75569152832031,86.75569152832031,86.75569152832031,86.75569152832031,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,93.50896453857422,69.28784942626953,69.28784942626953,69.28784942626953,69.28784942626953,69.28784942626953,69.28784942626953,69.28784942626953,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,70.67617797851562,79.78276062011719,79.78276062011719,79.78276062011719,79.78276062011719,79.78276062011719,79.78276062011719,79.78276062011719,79.78276062011719,87.72046661376953,87.72046661376953,87.72046661376953,87.72046661376953,87.72046661376953,87.72046661376953,87.72046661376953,71.11249542236328,71.11249542236328,71.11249542236328,69.87138366699219,69.87138366699219,69.87138366699219,69.87138366699219,69.87138366699219,69.87138366699219,69.87138366699219,69.87138366699219,77.65231323242188,77.65231323242188,77.65231323242188,77.65231323242188,77.65231323242188,77.65231323242188,77.65231323242188,77.65231323242188,87.0291748046875,87.0291748046875,91.52388763427734,91.52388763427734,91.52388763427734,91.52388763427734,91.52388763427734,92.14019775390625,92.14019775390625,93.2021484375,93.2021484375,93.2021484375,93.2021484375,93.2021484375,93.2021484375,66.91941070556641,66.91941070556641,66.91941070556641,66.91941070556641,68.37362670898438,68.37362670898438,69.58396148681641,69.58396148681641,69.58396148681641,69.58396148681641,69.58396148681641,69.58396148681641,72.81594085693359,72.81594085693359,72.81594085693359,72.81594085693359,72.81594085693359,72.81594085693359,72.81594085693359,72.81594085693359,75.91875457763672,75.91875457763672,76.78553009033203,76.78553009033203,76.78553009033203,76.78553009033203,78.11288452148438,78.11288452148438,82.34741973876953,82.34741973876953,83.54668426513672,83.54668426513672,83.54668426513672,83.54668426513672,83.54668426513672,83.54668426513672,88.52044677734375,88.52044677734375,88.52044677734375,88.52044677734375,88.52044677734375,88.52044677734375,88.52044677734375,89.65625762939453,89.65625762939453,90.71395111083984,90.71395111083984,90.71395111083984,90.71395111083984,90.71395111083984,90.71395111083984,66.93077850341797,66.93077850341797,74.58354949951172,74.58354949951172,87.06214904785156,87.06214904785156,87.06214904785156,87.06214904785156,87.06214904785156,87.06214904785156,93.50836181640625,93.50836181640625,93.50836181640625,73.72405242919922,73.72405242919922,73.72405242919922,73.72405242919922,73.72405242919922,73.72405242919922,73.72405242919922,81.91637420654297,81.91637420654297,81.91637420654297,81.91637420654297,81.91637420654297,81.91637420654297,93.49001312255859,93.49001312255859,93.49001312255859,72.74322509765625,72.74322509765625,72.74322509765625,72.74322509765625,72.74322509765625,72.74322509765625,72.74322509765625,72.74322509765625,80.15763854980469,80.15763854980469,92.19709777832031,92.19709777832031,68.61463165283203,68.61463165283203,68.61463165283203,68.61463165283203,68.61463165283203,68.61463165283203,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,72.69403076171875,81.62737274169922,81.62737274169922,81.62737274169922,81.62737274169922,81.62737274169922,81.62737274169922,81.62737274169922,82.84236907958984,82.84236907958984,82.84236907958984,82.84236907958984,82.84236907958984,82.84236907958984,82.84236907958984,82.84236907958984,88.82419586181641,88.82419586181641,88.82419586181641,88.82419586181641,93.49220275878906,93.49220275878906,93.49220275878906,56.63543701171875,56.63543701171875,56.63543701171875,56.63543701171875,56.63543701171875,56.63543701171875,56.63543701171875,70.40644073486328,70.40644073486328,76.72380828857422,76.72380828857422,83.26821136474609,83.26821136474609,83.26821136474609,83.26821136474609,83.26821136474609,83.26821136474609,83.26821136474609,90.33937835693359,90.33937835693359,90.33937835693359,90.33937835693359,90.33937835693359,90.33937835693359,90.33937835693359,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,55.0814208984375,61.80010223388672,61.80010223388672,69.16123199462891,69.16123199462891,69.16123199462891,69.16123199462891,69.16123199462891,69.16123199462891,69.16123199462891,76.35797119140625,76.35797119140625,76.35797119140625,76.35797119140625,76.35797119140625,79.19723510742188,79.19723510742188,79.19723510742188,79.19723510742188,79.19723510742188,79.19723510742188,79.19723510742188,79.19723510742188,87.21720886230469,87.21720886230469,87.21720886230469,87.21720886230469,87.21720886230469,87.21720886230469,87.21720886230469,93.50824737548828,93.50824737548828,93.50824737548828,57.93944549560547,57.93944549560547,57.93944549560547,57.93944549560547,57.93944549560547,57.93944549560547,68.51593017578125,68.51593017578125,68.51593017578125,68.51593017578125,68.51593017578125,68.51593017578125,68.51593017578125,68.51593017578125,75.86525726318359,75.86525726318359,82.43242645263672,82.43242645263672,82.43242645263672,82.43242645263672,82.43242645263672,82.43242645263672,82.43242645263672,85.59273529052734,85.59273529052734,85.59273529052734,85.59273529052734,85.59273529052734,85.59273529052734,85.59273529052734,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,93.50662994384766,58.15925598144531,58.15925598144531,58.15925598144531,58.15925598144531,58.15925598144531,58.15925598144531,64.82730102539062,64.82730102539062,74.37235260009766,74.37235260009766,81.41110229492188,81.41110229492188,87.68700408935547,87.68700408935547,87.68700408935547,87.68700408935547,87.68700408935547,87.68700408935547,87.68700408935547,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,90.84065246582031,58.11635589599609,58.11635589599609,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,67.24236297607422,74.21088409423828,74.21088409423828,74.21088409423828,74.21088409423828,74.21088409423828,84.00054931640625,84.00054931640625,90.41156005859375,90.41156005859375,57.21218109130859,57.21218109130859,62.96091461181641,62.96091461181641,62.96091461181641,62.96091461181641,62.96091461181641,62.96091461181641,62.96091461181641,62.96091461181641,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,69.85250854492188,71.92008972167969,71.92008972167969,80.36225128173828,80.36225128173828,80.36225128173828,80.36225128173828,80.36225128173828,80.36225128173828,80.36225128173828,86.72292327880859,86.72292327880859,93.47692108154297,93.47692108154297,93.47692108154297,62.41876220703125,62.41876220703125,68.37586212158203,68.37586212158203,77.43415069580078,77.43415069580078,77.43415069580078,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,78.59282684326172,79.36070251464844,79.36070251464844,79.36070251464844,79.36070251464844,85.30361938476562,85.30361938476562,87.07817077636719,87.07817077636719,87.07817077636719,87.07817077636719,87.07817077636719,87.07817077636719,87.07817077636719,87.07817077636719,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,90.69066619873047,93.48021697998047,93.48021697998047,93.48021697998047,93.48021697998047,93.48021697998047,93.48021697998047,93.48021697998047,93.48021697998047,62.58539581298828,62.58539581298828,62.58539581298828,62.58539581298828,67.94198608398438,67.94198608398438,67.94198608398438,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,68.48152923583984,74.46376800537109,74.46376800537109,74.46376800537109,74.46376800537109,78.93837738037109,78.93837738037109,78.93837738037109,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,81.02901458740234,86.44919586181641,86.44919586181641,86.44919586181641,86.44919586181641,91.7432861328125,91.7432861328125,91.7432861328125,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,92.74003601074219,93.42889404296875,93.42889404296875,93.42889404296875,93.42889404296875,93.42889404296875,66.27374267578125,66.27374267578125,66.27374267578125,66.27374267578125,72.67619323730469,72.67619323730469,72.67619323730469,72.67619323730469,72.67619323730469,79.67026519775391,79.67026519775391,79.67026519775391,79.67026519775391,79.67026519775391,79.67026519775391,79.67026519775391,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,87.02632141113281,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,84.55933380126953,66.91442108154297,66.91442108154297,66.91442108154297,66.91442108154297,66.91442108154297,66.91442108154297,66.91442108154297,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,75.65371704101562,84.27504730224609,84.27504730224609,84.27504730224609,84.27504730224609,84.27504730224609,84.27504730224609,84.27504730224609,85.48163604736328,85.48163604736328,85.48163604736328,85.48163604736328,93.48609924316406,93.48609924316406,93.48609924316406,93.48609924316406,93.48609924316406,93.48609924316406,93.48609924316406,93.48609924316406,64.87343597412109,64.87343597412109,64.87343597412109,64.87343597412109,64.87343597412109,64.87343597412109,64.87343597412109,73.89485168457031,73.89485168457031,73.89485168457031,73.89485168457031,73.89485168457031,73.89485168457031,73.89485168457031,73.89485168457031,81.66745758056641,81.66745758056641,89.04007720947266,89.04007720947266,63.51982116699219,63.51982116699219,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,66.57359313964844,72.44865417480469,72.44865417480469,81.21454620361328,81.21454620361328,81.21454620361328,81.21454620361328,88.51576995849609,88.51576995849609,88.51576995849609,88.51576995849609,88.51576995849609,88.61073303222656,88.61073303222656,88.61073303222656,88.61073303222656,88.61073303222656,88.61073303222656,88.61073303222656,88.61073303222656,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,69.40592193603516,78.83147430419922,78.83147430419922,78.83147430419922,78.83147430419922,78.83147430419922,78.83147430419922,78.83147430419922,88.50312042236328,88.50312042236328,88.50312042236328,89.66563415527344,89.66563415527344,64.40575408935547,64.40575408935547,71.04622650146484,71.04622650146484,71.04622650146484,71.04622650146484,71.04622650146484,81.33678436279297,81.33678436279297,81.33678436279297,81.33678436279297,81.33678436279297,81.33678436279297,81.33678436279297,81.33678436279297,88.74613952636719,88.74613952636719,64.90092468261719,64.90092468261719,64.90092468261719,64.90092468261719,64.90092468261719,64.90092468261719,64.90092468261719,64.90092468261719,70.38565063476562,70.38565063476562,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,72.37506103515625,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,79.76658630371094,87.29946136474609,87.29946136474609,87.29946136474609,87.29946136474609,87.29946136474609,87.29946136474609,87.29946136474609,93.00812530517578,93.00812530517578,93.00812530517578,70.96790313720703,70.96790313720703,79.78973388671875,79.78973388671875,79.78973388671875,79.78973388671875,79.78973388671875,86.30601501464844,86.30601501464844,86.30601501464844,86.30601501464844,86.30601501464844,86.30601501464844,86.30601501464844,86.30601501464844,91.50898742675781,91.50898742675781,91.50898742675781,91.50898742675781,91.50898742675781,92.29766082763672,92.29766082763672,93.5062255859375,93.5062255859375,93.5062255859375,66.31209564208984,66.31209564208984,68.92984008789062,68.92984008789062,68.92984008789062,68.92984008789062,68.92984008789062,68.92984008789062,71.44081878662109,71.44081878662109,71.44081878662109,71.44081878662109,73.44092559814453,73.44092559814453,75.42965698242188,75.42965698242188,75.42965698242188,75.42965698242188,75.42965698242188,75.42965698242188,75.42965698242188,75.42965698242188,78.45682525634766,78.45682525634766,80.10415649414062,80.10415649414062,80.10415649414062,80.10415649414062,85.20263671875,85.20263671875,85.20263671875,85.37726593017578,85.37726593017578,86.99295806884766,86.99295806884766,88.130615234375,88.130615234375,88.130615234375,88.130615234375,88.130615234375,88.130615234375,88.130615234375,88.130615234375,92.80005645751953,92.80005645751953,92.80005645751953,92.80005645751953,68.24365997314453,68.24365997314453,69.01784515380859,69.01784515380859,69.01784515380859,69.01784515380859,69.01784515380859,69.01784515380859,69.01784515380859,69.01784515380859,74.39889526367188,74.39889526367188,74.39889526367188,74.39889526367188,74.39889526367188,87.18772888183594,87.18772888183594,87.18772888183594,87.18772888183594,87.18772888183594,87.18772888183594,87.18772888183594,87.18772888183594,69.93163299560547,69.93163299560547,69.93163299560547,69.93163299560547,69.93163299560547,69.93163299560547,69.93163299560547,78.35899353027344,78.35899353027344,87.07958221435547,87.07958221435547,87.07958221435547,87.07958221435547,79.61468505859375,79.61468505859375,79.61468505859375,76.56344604492188,76.56344604492188,76.56344604492188,76.56344604492188,76.56344604492188,87.44798278808594,87.44798278808594,87.44798278808594,87.44798278808594,87.44798278808594,87.51380157470703,87.51380157470703,87.51380157470703,87.51380157470703,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,90.78617095947266,93.50463104248047,93.50463104248047,93.50463104248047,93.50463104248047,93.50463104248047,93.50463104248047,93.50463104248047,77.45353698730469,77.45353698730469,77.45353698730469,77.45353698730469,80.26046752929688,80.26046752929688,80.26046752929688,80.26046752929688,81.14904022216797,81.14904022216797,81.14904022216797,81.14904022216797,81.14904022216797,81.14904022216797,81.14904022216797,91.26907348632812,91.26907348632812,91.26907348632812,91.26907348632812,91.26907348632812,91.26907348632812,91.26907348632812,91.26907348632812,71.91046142578125,71.91046142578125,71.91046142578125,71.91046142578125,71.91046142578125,71.91046142578125,71.91046142578125,71.91046142578125,63.09599304199219,63.09599304199219,63.09599304199219,63.09599304199219,67.45494079589844,67.45494079589844,67.45494079589844,67.45494079589844,67.45494079589844,67.45494079589844,67.45494079589844,75.74832153320312,75.74832153320312,75.74832153320312,75.74832153320312,75.74832153320312,75.74832153320312,82.79592132568359,82.79592132568359,89.79356384277344,89.79356384277344,89.79356384277344,89.79356384277344,89.79356384277344,89.79356384277344,58.23111724853516,58.23111724853516,58.23111724853516,58.23111724853516,58.23111724853516,58.23111724853516,58.23111724853516,58.23111724853516,65.73999786376953,65.73999786376953,65.73999786376953,65.73999786376953,65.73999786376953,73.70323181152344,73.70323181152344,82.04879760742188,82.04879760742188,82.04879760742188,82.04879760742188,82.04879760742188,82.04879760742188,83.54972839355469,83.54972839355469,83.54972839355469,83.54972839355469,83.54972839355469,83.54972839355469,90.18264770507812,90.18264770507812,90.18264770507812,90.18264770507812,90.18264770507812,90.18264770507812,90.18264770507812,90.18264770507812,59.21446228027344,59.21446228027344,59.21446228027344,59.21446228027344,59.21446228027344,59.21446228027344,59.21446228027344,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,68.28956604003906,76.83590698242188,76.83590698242188,76.83590698242188,76.83590698242188,76.83590698242188,76.83590698242188,76.83590698242188,85.58667755126953,85.58667755126953,85.58667755126953,85.58667755126953,85.58667755126953,85.58667755126953,85.58667755126953,93.50929260253906,93.50929260253906,93.50929260253906,93.50929260253906,93.50929260253906,93.50929260253906,93.50929260253906,93.50929260253906,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,62.13462066650391,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,69.60113525390625,70.94612121582031,70.94612121582031,70.94612121582031,70.94612121582031,70.94612121582031,70.94612121582031,70.94612121582031,79.43783569335938,79.43783569335938,88.5595703125,88.5595703125,88.5595703125,88.5595703125,88.5595703125,88.5595703125,88.5595703125,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,93.50855255126953,64.47011566162109,64.47011566162109,64.47011566162109,64.47011566162109,64.47011566162109,64.47011566162109,72.20448303222656,72.20448303222656,72.20448303222656,72.20448303222656,72.20448303222656,72.20448303222656,72.20448303222656,72.20448303222656,73.83097839355469,73.83097839355469,73.83097839355469,73.83097839355469,73.83097839355469,73.83097839355469,81.51328277587891,89.24421691894531,89.24421691894531,89.24421691894531,89.24421691894531,89.24421691894531,89.24421691894531,89.24421691894531,92.54747772216797,92.54747772216797,92.54747772216797,92.54747772216797,92.54747772216797,92.54747772216797,92.54747772216797,92.54747772216797,67.02298736572266,67.02298736572266,73.15083312988281,73.15083312988281,73.15083312988281,73.15083312988281,73.15083312988281,73.15083312988281,73.15083312988281,73.15083312988281,77.83857727050781,77.83857727050781,77.83857727050781,77.83857727050781,81.77220916748047,81.77220916748047,87.97907257080078,87.97907257080078,87.97907257080078,87.97907257080078,87.97907257080078,87.97907257080078,87.97907257080078,87.97907257080078,67.53330230712891,67.53330230712891,67.53330230712891,65.79177856445312,65.79177856445312,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,73.66121673583984,79.24185943603516,79.24185943603516,79.24185943603516,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,80.08096313476562,85.0072021484375,85.0072021484375,85.0072021484375,85.0072021484375,85.0072021484375,85.0072021484375,85.0072021484375,85.0072021484375,85.26937866210938,85.26937866210938,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,90.29144287109375,93.49311065673828,93.49311065673828,93.49311065673828,64.38494110107422,64.38494110107422,64.38494110107422,64.38494110107422,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,69.34905242919922,74.46053314208984,74.46053314208984,77.26385498046875,77.26385498046875,77.26385498046875,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,79.04856872558594,80.25772857666016,80.25772857666016,80.25772857666016,80.25772857666016,80.25772857666016,80.25772857666016,80.25772857666016,80.25772857666016,84.43984985351562,84.43984985351562,88.48767852783203,88.48767852783203,88.48767852783203,88.48767852783203,88.48767852783203,88.48767852783203,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,90.03798675537109,91.54133605957031,91.54133605957031,64.84723663330078,64.84723663330078,66.67344665527344,66.67344665527344,66.67344665527344,66.67344665527344,66.67344665527344,70.83978271484375,70.83978271484375,70.83978271484375,70.83978271484375,70.83978271484375,70.83978271484375,79.13318634033203,79.13318634033203,79.13318634033203,79.13318634033203,79.13318634033203,79.13318634033203,79.13318634033203,85.41320037841797,85.41320037841797,85.41320037841797,85.41320037841797,85.41320037841797,85.41320037841797,85.41320037841797,92.8536376953125,92.8536376953125,92.8536376953125,92.8536376953125,92.8536376953125,92.8536376953125,67.33124542236328,67.33124542236328,76.13301086425781,76.13301086425781,76.13301086425781,76.13301086425781,76.13301086425781,82.95585632324219,82.95585632324219,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,86.35337829589844,92.43044281005859,92.43044281005859,66.88749694824219,66.88749694824219,66.88749694824219,66.88749694824219,66.88749694824219,75.34181213378906,75.34181213378906,82.68632507324219,82.68632507324219,89.71383666992188,89.71383666992188,93.50615692138672,93.50615692138672,93.50615692138672,66.31912994384766,66.31912994384766,66.31912994384766,66.31912994384766,72.32748413085938,72.32748413085938,72.32748413085938,72.32748413085938,72.32748413085938,81.80950927734375,81.80950927734375,81.80950927734375,81.80950927734375,81.80950927734375,81.80950927734375,81.80950927734375,88.72893524169922,88.72893524169922,66.35747528076172,66.35747528076172,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,72.66663360595703,80.50530242919922,80.50530242919922,80.50530242919922,81.64727020263672,81.64727020263672,81.64727020263672,88.05218505859375,88.05218505859375,75.63911437988281,75.63911437988281,75.63911437988281,75.96956634521484,75.96956634521484,82.49423980712891,82.49423980712891,82.49423980712891,82.49423980712891,82.49423980712891,82.49423980712891,92.25149536132812,92.25149536132812,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,67.93972778320312,74.5516357421875,74.5516357421875,76.19365692138672,76.19365692138672,84.54554748535156,84.54554748535156,84.54554748535156,84.54554748535156,93.50656127929688,93.50656127929688,93.50656127929688,69.62924194335938,69.62924194335938,69.62924194335938,69.62924194335938,69.62924194335938,69.62924194335938,78.83895111083984,78.83895111083984,85.88874816894531,85.88874816894531,93.50846862792969,93.50846862792969,93.50846862792969,73.07688140869141,73.07688140869141,74.62193298339844,74.62193298339844,74.62193298339844,74.62193298339844,74.62193298339844,74.62193298339844,74.9996337890625,74.9996337890625,74.9996337890625,74.9996337890625,77.68000793457031,77.68000793457031,77.68000793457031,77.68000793457031,81.46829223632812,81.46829223632812,81.46829223632812,81.46829223632812,81.46829223632812,81.46829223632812,84.23079681396484,84.23079681396484,84.23079681396484,84.23079681396484,88.68523406982422,88.68523406982422,88.68523406982422,88.68523406982422,89.87217712402344,89.87217712402344,89.87217712402344,89.87217712402344,89.87217712402344,89.87217712402344,89.87217712402344,89.87217712402344,91.06680297851562,91.06680297851562,93.50863647460938,93.50863647460938,93.50863647460938,93.50863647460938,93.50863647460938,93.50863647460938,93.50863647460938,70.95787048339844,70.95787048339844,70.95787048339844,70.95787048339844,73.03721618652344,73.03721618652344,73.03721618652344,73.03721618652344,76.62187194824219,76.62187194824219,76.62187194824219,76.62187194824219,78.24460601806641,78.24460601806641,78.24460601806641,78.24460601806641,80.47006988525391,80.47006988525391,80.47006988525391,80.47006988525391,85.50090789794922,85.50090789794922,93.50801086425781,93.50801086425781,93.50801086425781,93.50801086425781,93.50801086425781,93.50801086425781,93.50801086425781,78.14169311523438,78.14169311523438,78.14169311523438,78.14169311523438,78.14169311523438,78.14169311523438,88.88733673095703,88.88733673095703,88.88733673095703,88.88733673095703,74.34870910644531,74.34870910644531,74.34870910644531,74.34870910644531,74.34870910644531,74.34870910644531,74.34870910644531,74.34870910644531,78.94854736328125,78.94854736328125,78.94854736328125,78.94854736328125,78.94854736328125,78.94854736328125,86.49115753173828,86.49115753173828,86.49115753173828,86.49115753173828,86.49115753173828,86.49115753173828,86.49115753173828,86.49115753173828,93.508056640625,93.508056640625,93.508056640625,78.65340423583984,78.65340423583984,82.05811309814453,82.05811309814453,82.05811309814453,82.05811309814453,82.05811309814453,82.05811309814453,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,85.33048248291016,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,93.44351196289062,58.16840362548828,58.16840362548828,58.16840362548828,58.16840362548828,60.97533416748047,60.97533416748047,60.97533416748047,60.97533416748047,63.5478515625,63.5478515625,63.5478515625,72.10741424560547,72.10741424560547,72.10741424560547,72.10741424560547,72.10741424560547,72.10741424560547,81.82009124755859,81.82009124755859,86.35029602050781,86.35029602050781,86.35029602050781,86.35029602050781,93.49313354492188,93.49313354492188,93.49313354492188,93.49313354492188,93.49313354492188,93.49313354492188,93.49313354492188,93.49313354492188,63.44261169433594,63.44261169433594,63.44261169433594,63.44261169433594,63.44261169433594,63.44261169433594,69.72813415527344,69.72813415527344,69.72813415527344,69.72813415527344,69.72813415527344,69.72813415527344,69.72813415527344,69.72813415527344,79.2647705078125,79.2647705078125,79.2647705078125,79.2647705078125,79.2647705078125,79.2647705078125,79.2647705078125,79.2647705078125,85.94558715820312,85.94558715820312,91.98194122314453,91.98194122314453,62.17171478271484,62.17171478271484,65.5047607421875,65.5047607421875,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,69.45114898681641,78.51490783691406,78.51490783691406,78.51490783691406,78.51490783691406,78.51490783691406,78.51490783691406,78.51490783691406,78.51490783691406,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,85.74067687988281,93.11941528320312,93.11941528320312,63.18942260742188,63.18942260742188,63.18942260742188,63.18942260742188,63.18942260742188,63.18942260742188,63.18942260742188,63.18942260742188,69.20459747314453,69.20459747314453,78.52744293212891,78.52744293212891,78.52744293212891,78.52744293212891,78.52744293212891,78.52744293212891,78.52744293212891,82.0262451171875,82.0262451171875,82.0262451171875,82.0262451171875,82.0262451171875,82.0262451171875,87.91020202636719,87.91020202636719,66.26177215576172,66.26177215576172,66.26177215576172,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,66.28754425048828,75.49616241455078,75.49616241455078,82.93771362304688,82.93771362304688,82.93771362304688,82.93771362304688,82.93771362304688,93.47134399414062,93.47134399414062,93.47134399414062,93.47134399414062,93.47134399414062,93.47134399414062,93.47134399414062,93.47134399414062,65.99952697753906,65.99952697753906,73.35713195800781,73.35713195800781,73.35713195800781,73.35713195800781,73.35713195800781,79.48401641845703,79.48401641845703,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,85.83170318603516,87.83732604980469,87.83732604980469,87.83732604980469,87.83732604980469,87.83732604980469,87.83732604980469,93.48589324951172,93.48589324951172,93.48589324951172,93.48589324951172,93.48589324951172,93.48589324951172,93.48589324951172,93.48589324951172,64.98686218261719,64.98686218261719,72.78691101074219,72.78691101074219,72.78691101074219,72.78691101074219,80.38034057617188,80.38034057617188,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,87.63648223876953,93.50884246826172,93.50884246826172,93.50884246826172,62.20217132568359,62.20217132568359,62.20217132568359,62.20217132568359,62.20217132568359,68.49436950683594,68.49436950683594,78.06396484375,78.06396484375,78.06396484375,78.06396484375,78.06396484375,86.28520965576172,86.28520965576172,93.18800354003906,93.18800354003906,93.18800354003906,93.18800354003906,93.18800354003906,93.18800354003906,93.18800354003906,93.18800354003906,65.63232421875,65.63232421875,71.66915893554688,71.66915893554688,81.0245361328125,81.0245361328125,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,90.14889526367188,92.34142303466797,92.34142303466797,92.34142303466797,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,92.41928863525391,68.055908203125,68.055908203125,68.055908203125,68.055908203125,71.53131866455078,71.53131866455078,71.53131866455078,71.53131866455078,71.53131866455078,71.53131866455078,71.53131866455078,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.00323486328125,73.14422607421875,73.14422607421875,73.14422607421875,73.14422607421875,78.55086517333984,78.55086517333984,79.94274139404297,79.94274139404297,79.94274139404297,79.94274139404297,79.94274139404297,79.94274139404297,79.94274139404297,79.94274139404297,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,84.05813598632812,89.81314086914062,89.81314086914062,89.81314086914062,89.81314086914062,93.5093994140625,93.5093994140625,93.5093994140625,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,65.79454803466797,70.91385650634766,70.91385650634766,70.91385650634766,70.91385650634766,76.37015533447266,76.37015533447266,76.37015533447266,76.37015533447266,76.37015533447266,76.37015533447266,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,76.43656921386719,81.56590270996094,81.56590270996094,81.56590270996094,81.56590270996094,87.16443634033203,87.16443634033203,87.16443634033203,93.00196838378906,93.00196838378906,93.00196838378906,93.00196838378906,93.00196838378906,93.00196838378906,93.00196838378906,93.00196838378906,69.23543548583984,69.23543548583984,69.23543548583984,69.23543548583984,69.23543548583984,69.23543548583984,69.23543548583984,77.44818115234375,77.44818115234375,77.44818115234375,77.44818115234375,77.44818115234375,83.73145294189453,83.73145294189453,90.52847290039062,90.52847290039062,67.62559509277344,67.62559509277344,76.74042510986328,76.74042510986328,82.95327758789062,82.95327758789062,90.90505981445312,90.90505981445312,67.58818054199219,67.58818054199219,67.58818054199219,67.58818054199219,67.58818054199219,67.58818054199219,67.58818054199219,69.20902252197266,69.20902252197266,69.20902252197266,69.20902252197266,69.20902252197266,73.96853637695312,73.96853637695312,80.88487243652344,80.88487243652344,88.92584991455078,88.92584991455078,88.92584991455078,88.92584991455078,88.92584991455078,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,85.27581024169922,74.22745513916016,74.22745513916016,74.22745513916016,74.22745513916016,74.22745513916016,80.17765808105469,80.17765808105469,80.17765808105469,80.17765808105469,80.17765808105469,80.17765808105469,80.17765808105469,80.17765808105469,90.92427062988281,90.92427062988281,90.92427062988281,90.92427062988281,90.92427062988281,90.92427062988281,90.92427062988281,92.01621246337891,92.01621246337891,92.01621246337891,68.28473663330078,68.28473663330078,68.28473663330078,68.28473663330078,68.28473663330078,68.28473663330078,68.28473663330078,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,78.22047424316406,84.22358703613281,84.22358703613281,92.396728515625,92.396728515625,92.396728515625,92.396728515625,92.396728515625,92.396728515625,92.396728515625,70.07420349121094,70.07420349121094,70.07420349121094,70.07420349121094,70.07420349121094,70.07420349121094,77.59532928466797,77.59532928466797,86.60655975341797,86.60655975341797,86.60655975341797,86.60655975341797,86.60655975341797,86.60655975341797,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,93.50901794433594,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,73.12343597412109,74.81356048583984,74.81356048583984,74.81356048583984,74.81356048583984,74.81356048583984,74.81356048583984,74.81356048583984,74.81356048583984,81.39372253417969,81.39372253417969,81.39372253417969,81.39372253417969,81.39372253417969,81.39372253417969,81.39372253417969,81.39372253417969,92.18844604492188,92.18844604492188,71.49728393554688,71.49728393554688,77.97372436523438,77.97372436523438,77.97372436523438,77.97372436523438,77.97372436523438,77.97372436523438,77.97372436523438,77.97372436523438,85.11788177490234,85.11788177490234,92.63351440429688,92.63351440429688,73.51922607421875,73.51922607421875,81.69974517822266,81.69974517822266,84.61199188232422,84.61199188232422,84.61199188232422,84.61199188232422,84.61199188232422,89.67212677001953,89.67212677001953,89.67212677001953,89.67212677001953,89.67212677001953,89.67212677001953,89.67212677001953,71.64255523681641,71.64255523681641,80.19517517089844,80.19517517089844,80.19517517089844,80.19517517089844,86.93282318115234,86.93282318115234,86.93282318115234,86.93282318115234,86.93282318115234,86.93282318115234,86.93282318115234,86.93282318115234,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,93.50909423828125,59.95425415039062,59.95425415039062,67.14511871337891,67.14511871337891,67.14511871337891,67.14511871337891,67.14511871337891,67.14511871337891,67.14511871337891,73.72919464111328,73.72919464111328,73.72919464111328,73.72919464111328,73.72919464111328,73.72919464111328,81.88193511962891,81.88193511962891,81.88193511962891,81.88193511962891,81.88193511962891,81.88193511962891,81.88193511962891,81.88193511962891,85.12745666503906,85.12745666503906,85.56494903564453,85.56494903564453,86.97100830078125,86.97100830078125,86.97100830078125,86.97100830078125,91.50656127929688,91.50656127929688,92.64937591552734,92.64937591552734,92.64937591552734,92.64937591552734,92.64937591552734,92.64937591552734,92.64937591552734,92.72090911865234,92.72090911865234,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,93.50350952148438,62.41983795166016,62.41983795166016,62.41983795166016,62.41983795166016,62.41983795166016,62.41983795166016,62.41983795166016,63.14693450927734,63.14693450927734,64.49828338623047,64.49828338623047,64.49828338623047,64.49828338623047,69.79619598388672,69.79619598388672,69.79619598388672,69.86065673828125,69.86065673828125,71.38359069824219,71.38359069824219,71.38359069824219,71.38359069824219,76.63821411132812,76.63821411132812,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.13178253173828,77.96756744384766,77.96756744384766,81.72055816650391,81.72055816650391,81.72055816650391,88.48771667480469,88.48771667480469,88.48771667480469,88.48771667480469,88.48771667480469,88.48771667480469,88.48771667480469,88.48771667480469,62.54366302490234,62.54366302490234,74.80691528320312,74.80691528320312,74.80691528320312,74.80691528320312,74.80691528320312,74.80691528320312,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,81.83284759521484,88.69641876220703,88.69641876220703,88.69641876220703,88.69641876220703,88.69641876220703,88.69641876220703,61.95558166503906,61.95558166503906,61.95558166503906,61.95558166503906,61.95558166503906,61.95558166503906,61.95558166503906,69.38043212890625,69.38043212890625,69.38043212890625,69.38043212890625,69.38043212890625,69.38043212890625,69.38043212890625,78.37043762207031,78.37043762207031,80.60752105712891,80.60752105712891,80.60752105712891,80.60752105712891,81.37672424316406,81.37672424316406,81.37672424316406,81.37672424316406,81.37672424316406,81.37672424316406,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,83.87989044189453,93.33857727050781,93.33857727050781,93.33857727050781,93.33857727050781,88.67875671386719,88.67875671386719,88.67875671386719,88.67875671386719,64.45037078857422,64.45037078857422,64.45037078857422,64.45037078857422,68.87252044677734,68.87252044677734,68.87252044677734,68.87252044677734,79.70970153808594,79.70970153808594,87.22366333007812,87.22366333007812,87.22366333007812,87.22366333007812,87.22366333007812,87.22366333007812,87.22366333007812,91.598388671875,91.598388671875,65.07277679443359,65.07277679443359,73.3961181640625,73.3961181640625,73.3961181640625,73.3961181640625,73.3961181640625,73.3961181640625,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,78.16390991210938,85.28681182861328,85.28681182861328,92.21700286865234,92.21700286865234,66.38563537597656,66.38563537597656,66.38563537597656,66.38563537597656,66.38563537597656,66.38563537597656,66.38563537597656,66.38563537597656,68.66226196289062,68.66226196289062,68.66226196289062,68.66226196289062,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,72.67803192138672,82.86661529541016,82.86661529541016,82.86661529541016,82.86661529541016,82.86661529541016,82.86661529541016,82.86661529541016,89.83429718017578,89.83429718017578,65.50291442871094,65.50291442871094,65.50291442871094,65.50291442871094,65.50291442871094,65.50291442871094,65.50291442871094,65.50291442871094,71.20049285888672,71.20049285888672,79.79291534423828,79.79291534423828,79.79291534423828,79.79291534423828,79.79291534423828,79.79291534423828,79.79291534423828,85.00043487548828,85.00043487548828,89.22918701171875,89.22918701171875,89.22918701171875,89.22918701171875,89.22918701171875,93.28390502929688,93.28390502929688,93.28390502929688,93.28390502929688,93.28390502929688,93.28390502929688,93.28390502929688,69.44059753417969,69.44059753417969,75.28988647460938,75.28988647460938,75.28988647460938,75.28988647460938,75.28988647460938,75.28988647460938,75.28988647460938,75.28988647460938,83.82438659667969,83.82438659667969,92.11514282226562,92.11514282226562,69.16120147705078,69.16120147705078,75.10197448730469,75.10197448730469,79.16442108154297,79.16442108154297,79.16442108154297,79.16442108154297,79.16442108154297,79.16442108154297,79.16442108154297,82.98799896240234,82.98799896240234,82.98799896240234,82.98799896240234,82.98799896240234,82.98799896240234,82.98799896240234,93.08518218994141,93.08518218994141,69.48207855224609,69.48207855224609,69.48207855224609,69.48207855224609,69.48207855224609,69.48207855224609,69.48207855224609,69.48207855224609,74.49935913085938,74.49935913085938,74.49935913085938,74.49935913085938,74.49935913085938,74.49935913085938,74.49935913085938,81.23579406738281,81.23579406738281,81.23579406738281,81.23579406738281,81.23579406738281,81.23579406738281,81.23579406738281,81.23579406738281,88.91640472412109,88.91640472412109,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,66.85222625732422,75.51212310791016,75.51212310791016,80.25389099121094,80.25389099121094,81.34953308105469,81.34953308105469,81.34953308105469,81.34953308105469,81.34953308105469,81.34953308105469,90.61724853515625,90.61724853515625,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,68.55580139160156,73.81369018554688,73.81369018554688,73.81369018554688,73.81369018554688,73.81369018554688,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,81.47403717041016,90.11975860595703,90.11975860595703,90.11975860595703,90.11975860595703,90.11975860595703,93.50714874267578,93.50714874267578,93.50714874267578,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,74.31478881835938,79.91544342041016,79.91544342041016,83.17845916748047,83.17845916748047,83.17845916748047,83.17845916748047,83.17845916748047,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,83.75148010253906,86.28263092041016,86.28263092041016,86.28263092041016,86.28263092041016,86.28263092041016,86.28263092041016,86.28263092041016,86.28263092041016,88.85279083251953,88.85279083251953,92.39255523681641,92.39255523681641,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,68.90792846679688,75.10008239746094,75.10008239746094,78.06192016601562,78.06192016601562,78.06192016601562,78.06192016601562,78.06192016601562,78.06192016601562,78.06192016601562,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,79.67050170898438,85.57670593261719,85.57670593261719,86.33943939208984,86.33943939208984,86.33943939208984,86.33943939208984,86.33943939208984,86.33943939208984,86.33943939208984,86.33943939208984,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,90.550048828125,71.88206481933594,71.88206481933594,71.88206481933594,71.88206481933594,71.88206481933594,71.88206481933594,71.88206481933594,71.88206481933594,72.47339630126953,72.47339630126953,76.15148162841797,76.15148162841797,76.15148162841797,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,78.43162536621094,79.25571441650391,79.25571441650391,79.25571441650391,79.25571441650391,83.48021697998047,83.48021697998047,87.05231475830078,87.05231475830078,87.05231475830078,87.05231475830078,87.05231475830078,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,91.16448974609375,74.19734954833984,74.19734954833984,74.19734954833984,74.19734954833984,74.19734954833984,74.19734954833984,82.56098937988281,82.56098937988281,82.56098937988281,82.56098937988281,82.56098937988281,82.56098937988281,82.56098937988281,82.56098937988281,88.32588958740234,88.32588958740234,88.32588958740234,88.32588958740234,88.32588958740234,88.32588958740234,88.32588958740234,88.32588958740234,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,93.50231170654297,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,76.31186676025391,83.93753051757812,83.93753051757812,85.2493896484375,85.2493896484375,85.2493896484375,93.46425628662109,93.46425628662109,76.38253784179688,76.38253784179688,81.68891143798828,81.68891143798828,87.98647308349609,87.98647308349609,87.98647308349609,87.98647308349609,87.98647308349609,87.98647308349609,87.98647308349609,87.98647308349609,76.58720397949219,76.58720397949219,76.58720397949219,76.58720397949219,76.58720397949219,76.58720397949219,76.58720397949219,76.58720397949219,78.62590026855469,78.62590026855469,78.62590026855469,78.62590026855469,78.62590026855469,78.62590026855469,78.62590026855469,78.62590026855469,84.16794586181641,84.16794586181641,84.16794586181641,86.17794036865234,86.17794036865234,86.17794036865234,86.17794036865234,86.17794036865234,86.17794036865234,86.17794036865234,86.17794036865234,93.47396087646484,93.47396087646484,93.47396087646484,80.61841583251953,80.61841583251953,80.61841583251953,80.61841583251953,80.61841583251953,80.61841583251953,80.61841583251953,80.61841583251953,86.68803405761719,86.68803405761719,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,93.50828552246094,64.90573883056641,64.90573883056641,64.90573883056641,48.91092681884766,48.91092681884766,48.91092681884766,56.33938598632812,56.33938598632812,63.72026824951172,63.72026824951172,71.02570343017578,71.02570343017578,74.06891632080078,74.06891632080078,79.67918395996094,79.67918395996094,87.6512451171875,87.6512451171875,87.6512451171875,87.6512451171875,87.6512451171875,87.6512451171875,87.6512451171875,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,92.92605590820312,52.07098388671875,52.07098388671875,52.07098388671875,52.07098388671875,52.07098388671875,52.07098388671875,52.07098388671875,60.36202239990234,60.36202239990234,67.70755767822266,67.70755767822266,69.44808197021484,69.44808197021484,69.44808197021484,69.44808197021484,69.44808197021484,69.44808197021484,77.68470764160156,77.68470764160156,85.17053985595703,85.17053985595703,92.5225830078125,92.5225830078125,92.5225830078125,92.5225830078125,92.5225830078125,92.5225830078125,92.5225830078125,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,51.63616943359375,61.74228668212891,61.74228668212891,61.74228668212891,61.74228668212891,61.74228668212891,61.74228668212891,61.74228668212891,61.74228668212891,69.51335906982422,69.51335906982422,69.51335906982422,69.51335906982422,69.51335906982422,69.51335906982422,69.51335906982422,69.51335906982422,77.77753448486328,77.77753448486328,77.77753448486328,77.77753448486328,77.77753448486328,77.77753448486328,77.77753448486328,77.77753448486328,79.07561492919922,79.07561492919922,80.27252960205078,80.27252960205078,80.27252960205078,80.27252960205078,84.01369476318359,84.01369476318359,84.01369476318359,84.01369476318359,85.71197509765625,85.71197509765625,85.71197509765625,85.71197509765625,91.05570220947266,91.05570220947266,92.04252624511719,92.04252624511719,92.04252624511719,92.04252624511719,92.04252624511719,92.04252624511719,92.04252624511719,92.04252624511719,92.30960845947266,92.30960845947266,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,93.49790954589844,52.99027252197266,52.99027252197266,52.99027252197266,52.99027252197266,52.99027252197266,54.19874572753906,54.19874572753906,55.92366790771484,55.92366790771484,55.92366790771484,55.92366790771484,58.70924377441406,58.70924377441406,58.70924377441406,58.70924377441406,58.70924377441406,61.64174652099609,61.64174652099609,63.08646392822266,63.08646392822266,63.08646392822266,63.08646392822266,63.08646392822266,63.08646392822266,69.96701812744141,69.96701812744141,69.96701812744141,69.96701812744141,69.96701812744141,69.96701812744141,69.96701812744141,82.02242279052734,82.02242279052734,82.02242279052734,82.02242279052734,82.02242279052734,82.02242279052734,82.02242279052734,93.50853729248047,93.50853729248047,93.50853729248047,93.50853729248047,93.50853729248047,93.50853729248047,93.50853729248047,54.91182708740234,54.91182708740234,64.95714569091797,64.95714569091797,64.95714569091797,64.95714569091797,64.95714569091797,64.95714569091797,74.39729309082031,74.39729309082031,82.58925628662109,82.58925628662109,89.91421508789062,89.91421508789062,89.91421508789062,89.91421508789062,89.91421508789062,89.91421508789062,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.18658447265625,93.48887634277344,93.48887634277344,93.48887634277344,61.82488250732422,61.82488250732422,61.82488250732422,61.82488250732422,61.82488250732422,61.82488250732422,64.63181304931641,64.63181304931641,64.63181304931641,64.63181304931641,71.12117767333984,71.12117767333984,71.12117767333984,71.12117767333984,71.12117767333984,71.12117767333984,71.12117767333984,84.27761077880859,84.27761077880859,84.27761077880859,84.27761077880859,89.68987274169922,89.68987274169922,89.68987274169922,91.48021697998047,91.48021697998047,91.48021697998047,91.48021697998047,91.48021697998047,91.48021697998047,91.48021697998047,91.48021697998047,60.73918151855469,60.73918151855469,60.73918151855469,60.73918151855469,68.51331329345703,68.51331329345703,68.51331329345703,68.51331329345703,68.51331329345703,68.51331329345703,68.51331329345703,68.51331329345703,75.396240234375,75.396240234375,81.75944519042969,81.75944519042969,91.54377746582031,91.54377746582031,91.54377746582031,91.54377746582031,91.54377746582031,91.54377746582031,91.54377746582031,91.54377746582031,56.16452789306641,56.16452789306641,56.16452789306641,56.16452789306641,57.5277099609375,57.5277099609375,57.5277099609375,57.5277099609375,57.5277099609375,57.5277099609375,67.33205413818359,67.33205413818359,67.33205413818359,67.33205413818359,67.33205413818359,67.33205413818359,67.33205413818359,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,74.72331237792969,84.26665496826172,84.26665496826172,84.26665496826172,84.26665496826172,84.26665496826172,84.26665496826172,84.26665496826172,84.26665496826172,90.72798156738281,90.72798156738281,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,56.49872589111328,63.75749969482422,63.75749969482422,69.33106231689453,69.33106231689453,69.33106231689453,69.33106231689453,69.33106231689453,73.43535614013672,73.43535614013672,73.43535614013672,73.43535614013672,73.43535614013672,73.43535614013672,73.43535614013672,80.79256439208984,80.79256439208984,80.79256439208984,80.79256439208984,80.79256439208984,91.302978515625,91.302978515625,57.81845855712891,57.81845855712891,57.81845855712891,57.81845855712891,57.81845855712891,57.81845855712891,57.81845855712891,65.8634033203125,65.8634033203125,65.8634033203125,65.8634033203125,65.8634033203125,65.8634033203125,65.8634033203125,76.61532592773438,76.61532592773438,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,84.19864654541016,92.38075256347656,92.38075256347656,92.38075256347656,92.38075256347656,92.38075256347656,92.38075256347656,92.38075256347656,58.23807525634766,58.23807525634766,59.82582092285156,59.82582092285156,59.82582092285156,59.82582092285156,59.82582092285156,59.82582092285156,69.14432525634766,69.14432525634766,76.21096038818359,76.21096038818359,76.21096038818359,76.21096038818359,76.21096038818359,76.21096038818359,76.21096038818359,76.21096038818359,85.22982788085938,85.22982788085938,92.93917846679688,92.93917846679688,61.03679656982422,61.03679656982422,61.03679656982422,61.03679656982422,61.03679656982422,61.03679656982422,61.03679656982422,68.29836273193359,68.29836273193359,68.29836273193359,68.29836273193359,68.29836273193359,68.29836273193359,68.29836273193359,74.88548278808594,74.88548278808594,74.88548278808594,74.88548278808594,77.30839538574219,77.30839538574219,86.96513366699219,86.96513366699219,86.96513366699219,86.96513366699219,93.49072265625,93.49072265625,93.49072265625,62.74423980712891,62.74423980712891,62.74423980712891,62.74423980712891,62.74423980712891,62.74423980712891,62.74423980712891,73.52912139892578,73.52912139892578,73.52912139892578,73.52912139892578,73.52912139892578,73.52912139892578,73.52912139892578,80.32795715332031,80.32795715332031,80.32795715332031,80.32795715332031,80.32795715332031,80.32795715332031,80.32795715332031,80.32795715332031,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.16133880615234,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,85.32401275634766,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,86.02415466308594,89.80355834960938,89.80355834960938,89.80355834960938,89.80355834960938,89.80355834960938,89.80355834960938,89.80355834960938,89.80355834960938,92.0302734375,92.0302734375,58.36362457275391,58.36362457275391,58.36362457275391,58.36362457275391,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,61.71178436279297,62.85533142089844,62.85533142089844,62.85533142089844,62.85533142089844,67.99650573730469,67.99650573730469,71.06489562988281,71.06489562988281,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,73.34151458740234,79.44912719726562,79.44912719726562,79.44912719726562,79.44912719726562,83.61780548095703,83.61780548095703,83.61780548095703,83.61780548095703,83.61780548095703,83.61780548095703,83.61780548095703,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,85.00279998779297,90.87848663330078,90.87848663330078,93.51046752929688,93.51046752929688,93.51046752929688,93.51046752929688,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,61.97473907470703,63.72738647460938,63.72738647460938,68.15251159667969,68.15251159667969,72.40130615234375,72.40130615234375,72.40130615234375,72.40130615234375,72.40130615234375,72.40130615234375,72.40130615234375,77.67347717285156,77.67347717285156,77.67347717285156,77.67347717285156,77.67347717285156,77.67347717285156,77.67347717285156,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,84.79274749755859,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,93.50479888916016,64.5184326171875,64.5184326171875,64.5184326171875,64.5184326171875,64.5184326171875,64.5184326171875,64.5184326171875,75.32638549804688,75.32638549804688,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,82.92041778564453,91.0611572265625,91.0611572265625,91.0611572265625,91.0611572265625,92.62881469726562,92.62881469726562,92.62881469726562,92.62881469726562,66.22408294677734,66.22408294677734,66.22408294677734,66.22408294677734,66.22408294677734,66.22408294677734,66.22408294677734,66.22408294677734,67.18124389648438,67.18124389648438,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,70.30667114257812,79.03555297851562,79.03555297851562,79.03555297851562,79.03555297851562,79.03555297851562,79.03555297851562,79.03555297851562,86.55928039550781,86.55928039550781,86.55928039550781,86.55928039550781,86.55928039550781,86.55928039550781,86.55928039550781,92.12553405761719,92.12553405761719,92.12553405761719,92.12553405761719,63.45279693603516,63.45279693603516,74.64846801757812,74.64846801757812,74.64846801757812,74.64846801757812,74.64846801757812,74.64846801757812,74.64846801757812,81.44313049316406,81.44313049316406,81.44313049316406,81.44313049316406,81.44313049316406,81.44313049316406,81.44313049316406,81.44313049316406,90.78179168701172,90.78179168701172,90.78179168701172,90.78179168701172,90.78179168701172,90.78179168701172,90.78179168701172,79.97785949707031,79.97785949707031,79.97785949707031,63.33695220947266,63.33695220947266,63.33695220947266,63.33695220947266,63.33695220947266,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,71.46308135986328,79.97566986083984,79.97566986083984,79.97566986083984,79.97566986083984,79.97566986083984,79.97566986083984,79.97566986083984,79.97566986083984,87.47430419921875,87.47430419921875,87.47430419921875,87.47430419921875,87.47430419921875,87.47430419921875,87.47430419921875,77.71641540527344,77.71641540527344,77.71641540527344,77.71641540527344,77.71641540527344,77.71641540527344,77.71641540527344,77.71641540527344,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,69.56724548339844,79.36802673339844,79.36802673339844,79.36802673339844,79.36802673339844,79.36802673339844,79.36802673339844,79.36802673339844,88.49156951904297,88.49156951904297,88.49156951904297,88.49156951904297,88.49156951904297,88.49156951904297,88.49156951904297,88.49156951904297,89.67906188964844,89.67906188964844,89.67906188964844,89.67906188964844,89.67906188964844,89.67906188964844,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,75.49411773681641,70.09905242919922,70.09905242919922,70.09905242919922,70.09905242919922,70.09905242919922,70.09905242919922,70.09905242919922,70.09905242919922,80.00225830078125,80.00225830078125,87.16666412353516,87.16666412353516,87.16666412353516,87.16666412353516,87.16666412353516,87.16666412353516,87.16666412353516,87.16666412353516,93.51065063476562,93.51065063476562,93.51065063476562,93.51065063476562,93.51065063476562,93.51065063476562,93.51065063476562,93.51065063476562,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,69.46741485595703,74.84104919433594,74.84104919433594,74.84104919433594,74.84104919433594,74.84104919433594,79.66034698486328,79.66034698486328,79.66034698486328,79.66034698486328,79.66034698486328,79.66034698486328,79.66034698486328,88.26055145263672,88.26055145263672,88.26055145263672,93.510498046875,93.510498046875,93.510498046875,93.510498046875,93.510498046875,93.510498046875,93.510498046875,93.510498046875,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,52.59642028808594,59.80084991455078,59.80084991455078,59.80084991455078,59.80084991455078,59.80084991455078,59.80084991455078,69.17033386230469,69.17033386230469,69.17033386230469,69.17033386230469,69.17033386230469,69.17033386230469,69.17033386230469,69.17033386230469,76.3975830078125,76.3975830078125,76.3975830078125,76.3975830078125,76.3975830078125,76.3975830078125,76.3975830078125,81.44087219238281,81.44087219238281,81.44087219238281,81.44087219238281,81.44087219238281,81.44087219238281,82.08149719238281,82.08149719238281,83.01270294189453,83.01270294189453,83.01270294189453,83.01270294189453,86.79311370849609,86.79311370849609,86.79311370849609,88.60801696777344,88.60801696777344,89.85898590087891,89.85898590087891,89.85898590087891,89.85898590087891,93.509521484375,93.509521484375,93.509521484375,52.75053405761719,52.75053405761719,53.72210693359375,53.72210693359375,53.72210693359375,53.72210693359375,54.29611968994141,54.29611968994141,54.29611968994141,54.29611968994141,54.29611968994141,54.29611968994141,54.29611968994141,54.29611968994141,59.3223876953125,59.3223876953125,60.29792022705078,60.29792022705078,60.29792022705078,60.29792022705078,60.29792022705078,60.29792022705078,66.35051727294922,66.35051727294922,66.35051727294922,66.35051727294922,66.35051727294922,67.08780670166016,67.08780670166016,68.11917114257812,68.11917114257812,68.11917114257812,68.11917114257812,72.80890655517578,72.80890655517578,79.77725219726562,79.77725219726562,92.72026824951172,92.72026824951172,58.97597503662109,58.97597503662109,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,67.18102264404297,75.47929382324219,75.47929382324219,84.69758605957031,84.69758605957031,91.79943084716797,91.79943084716797,57.28118133544922,57.28118133544922,57.83388519287109,57.83388519287109,57.83388519287109,57.83388519287109,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,61.10625457763672,69.57183837890625,69.57183837890625,69.57183837890625,69.57183837890625,69.57183837890625,69.57183837890625,69.57183837890625,70.56494140625,70.56494140625,70.56494140625,70.56494140625,73.37187194824219,73.37187194824219,73.37187194824219,73.37187194824219,80.09516906738281,80.09516906738281,80.09516906738281,80.09516906738281,80.09516906738281,80.09516906738281,80.09516906738281,93.37981414794922,93.37981414794922,57.35648345947266,57.35648345947266,57.35648345947266,57.35648345947266,57.35648345947266,57.35648345947266,57.35648345947266,62.50576019287109,62.50576019287109,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,71.91320037841797,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,80.61256408691406,91.04147338867188,56.74749755859375,56.74749755859375,66.488525390625,66.488525390625,66.488525390625,66.488525390625,74.52940368652344,74.52940368652344,74.52940368652344,74.52940368652344,74.52940368652344,75.98422241210938,75.98422241210938,75.98422241210938,75.98422241210938,75.98422241210938,75.98422241210938,75.98422241210938,84.56497955322266,84.56497955322266,84.56497955322266,84.56497955322266,84.56497955322266,84.56497955322266,84.56497955322266,91.70403289794922,91.70403289794922,91.70403289794922,91.70403289794922,91.70403289794922,91.70403289794922,91.70403289794922,57.97212219238281,57.97212219238281,65.80618286132812,65.80618286132812,65.80618286132812,65.80618286132812,65.80618286132812,65.80618286132812,65.80618286132812,65.80618286132812,73.29469299316406,73.29469299316406,73.29469299316406,73.29469299316406,73.29469299316406,73.29469299316406,73.29469299316406,73.29469299316406,78.35512542724609,78.35512542724609,78.35512542724609,78.35512542724609,78.35512542724609,78.35512542724609,78.35512542724609,78.35512542724609,83.83642578125,83.83642578125,93.50963592529297,93.50963592529297,93.50963592529297,93.50963592529297,93.50963592529297,93.50963592529297,93.50963592529297,93.50963592529297,63.20020294189453,63.20020294189453,63.20020294189453,63.20020294189453,63.20020294189453,63.20020294189453,69.32367706298828,69.32367706298828,69.32367706298828,69.32367706298828,69.32367706298828,69.32367706298828,69.32367706298828,80.94120788574219,80.94120788574219,80.94120788574219,80.94120788574219,80.94120788574219,80.94120788574219,80.94120788574219,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,88.0628662109375,91.79177856445312,91.79177856445312,91.79177856445312,91.79177856445312,91.79177856445312,91.79177856445312,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,70.69120025634766,67.79534149169922,67.79534149169922,73.36681365966797,73.36681365966797,73.36681365966797,73.36681365966797,73.36681365966797,73.36681365966797,73.36681365966797,73.36681365966797,83.66591644287109,83.66591644287109,91.01446533203125,91.01446533203125,93.51066589355469,93.51066589355469,93.51066589355469,93.51066589355469,93.51066589355469,93.51066589355469,93.51066589355469,59.87913513183594,59.87913513183594,59.87913513183594,59.87913513183594,69.15676879882812,69.15676879882812,69.15676879882812,69.15676879882812,69.15676879882812,69.15676879882812,76.39563751220703,76.39563751220703,85.72482299804688,85.72482299804688,85.72482299804688,85.72482299804688,85.72482299804688,93.45812225341797,93.45812225341797,93.45812225341797,93.45812225341797,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,59.29463195800781,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,60.05771636962891,65.86895751953125,65.86895751953125,65.86895751953125,65.86895751953125,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,70.66348266601562,75.61440277099609,75.61440277099609,76.43390655517578,76.43390655517578,79.8287353515625,79.8287353515625,79.8287353515625,79.8287353515625,79.8287353515625,79.8287353515625,79.8287353515625,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,82.58760070800781,87.14512634277344,87.14512634277344,87.14512634277344,87.14512634277344,87.14512634277344,87.14512634277344,87.14512634277344,87.14512634277344,88.53409576416016,88.53409576416016,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,92.82366943359375,65.05973052978516,65.05973052978516,65.05973052978516,65.05973052978516,65.05973052978516,65.05973052978516,65.085693359375,65.085693359375,68.78922271728516,68.78922271728516,68.78922271728516,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,70.71134185791016,74.66033172607422,74.66033172607422,74.66033172607422,74.66033172607422,74.66033172607422,74.66033172607422,74.66033172607422,74.66033172607422,76.9683837890625,76.9683837890625,80.5587158203125,80.5587158203125,80.5587158203125,80.5587158203125,80.5587158203125,80.5587158203125,80.5587158203125,85.46026611328125,85.46026611328125,85.46026611328125,85.46026611328125,85.46026611328125,85.46026611328125,85.46026611328125,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,93.49515533447266,66.64208221435547,66.64208221435547,66.64208221435547,66.64208221435547,75.38709259033203,75.38709259033203,75.38709259033203,75.38709259033203,75.38709259033203,75.38709259033203,75.38709259033203,85.32777404785156,85.32777404785156,85.32777404785156,85.32777404785156,85.32777404785156,85.32777404785156,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,93.17498779296875,66.39984130859375,66.39984130859375,70.01146697998047,76.87314605712891,76.87314605712891,76.87314605712891,76.87314605712891,76.87314605712891,76.87314605712891,76.87314605712891,76.87314605712891,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,84.70840454101562,93.10535430908203,93.10535430908203,66.70182800292969,66.70182800292969,66.70182800292969,66.70182800292969,66.70182800292969,66.70182800292969,66.70182800292969,74.71038818359375,74.71038818359375,78.29547119140625,78.29547119140625,78.29547119140625,78.29547119140625,85.39414978027344,85.39414978027344,85.39414978027344,85.39414978027344,85.39414978027344,85.39414978027344,85.39414978027344,93.51039123535156,93.51039123535156,93.51039123535156,67.97920989990234,67.97920989990234,67.97920989990234,67.97920989990234,67.97920989990234,67.97920989990234,67.97920989990234,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,76.13011169433594,88.74471282958984,88.74471282958984,65.17276000976562,65.17276000976562,65.17276000976562,65.17276000976562,65.17276000976562,65.17276000976562,65.17276000976562,72.47437286376953,72.47437286376953,82.91720581054688,82.91720581054688,82.91720581054688,82.91720581054688,82.91720581054688,82.91720581054688,82.91720581054688,85.46082305908203,85.46082305908203,85.46082305908203,85.46082305908203,85.46082305908203,85.46082305908203,85.46082305908203,85.46082305908203,93.01530456542969,93.01530456542969,68.15657806396484,68.15657806396484,68.15657806396484,68.15657806396484,68.15657806396484,68.15657806396484,74.12865447998047,74.12865447998047,85.40299224853516,85.40299224853516,85.40299224853516,85.40299224853516,85.40299224853516,85.40299224853516,85.40299224853516,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,92.44172668457031,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,66.11126708984375,68.65210723876953,68.65210723876953,77.18035888671875,77.18035888671875,77.18035888671875,77.18035888671875,77.18035888671875,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,87.01368713378906,93.50788879394531,93.50788879394531,93.50788879394531,71.54064178466797,79.26318359375,79.26318359375,79.26318359375,79.26318359375,79.26318359375,79.26318359375,79.26318359375,86.74477386474609,86.74477386474609,86.74477386474609,86.74477386474609,86.74477386474609,87.70113372802734,87.70113372802734,87.70113372802734,87.70113372802734,89.34449768066406,89.34449768066406,92.42809295654297,92.42809295654297,92.42809295654297,92.42809295654297,92.42809295654297,92.42809295654297,92.42809295654297,66.85545349121094,66.85545349121094,66.85933685302734,66.85933685302734,66.85933685302734,66.85933685302734,66.85933685302734,66.85933685302734,68.20760345458984,68.20760345458984,70.39962768554688,70.39962768554688,70.39962768554688,70.39962768554688,73.15919494628906,73.15919494628906,73.15919494628906,73.15919494628906,74.78974151611328,74.78974151611328,78.21605682373047,78.21605682373047,78.21605682373047,79.63694763183594,79.63694763183594,81.35150146484375,81.35150146484375,81.35150146484375,81.35150146484375,85.20622253417969,85.20622253417969,85.20622253417969,85.20622253417969,85.20622253417969,85.20622253417969,85.20622253417969,86.74385070800781,86.74385070800781,88.41789245605469,88.41789245605469,88.41789245605469,88.41789245605469,93.27214050292969],"meminc":[0,0,0,1.138473510742188,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6458969116210938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6242599487304688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6238784790039062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5772476196289062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5929412841796875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5456085205078125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5230712890625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.458831787109375,0,0,0,-6.6746826171875,0,0,0,0,0,11.92301940917969,0,0,0,0,7.48443603515625,0,7.64697265625,0,9.47930908203125,0,7.074905395507812,0,0,-36.65187072753906,0,0,0,0,8.7672119140625,0,11.34033203125,0,1.195747375488281,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5796890258789062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.564300537109375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.4275054931640625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.383026123046875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3037033081054688,0,0,0,0,0,4.081863403320312,0,0,0,0,0,0,0,0,0,0,0,0,0,8.933341979980469,0,0,0,0,0,0,-41.75992584228516,0,0,0,0,0,0,0,1.045974731445312,0,0,0,0,0,0,4.93585205078125,0,2.287757873535156,0,0,0,0,0,0,3.265724182128906,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.418899536132812,0,0,0,0,0,0,0,15.47737884521484,0,7.249549865722656,0,0,0,0,0,1.305549621582031,0,0,0,0,0,0,0,0,0,0,1.933967590332031,0,1.501678466796875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.8908843994140625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5219955444335938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-40.76320648193359,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7626190185546875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.69091796875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7579345703125,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7089691162109375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7146377563476562,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7186737060546875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6566925048828125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6922607421875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7033309936523438,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.659271240234375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5862960815429688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-7.780303955078125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.65570068359375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.8974227905273438,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6324691772460938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6321258544921875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.648040771484375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.69293212890625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6625747680664062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6109542846679688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5330581665039062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5783615112304688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5456314086914062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5327911376953125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3939132690429688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-7.753959655761719,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5695724487304688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5446395874023438,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5040359497070312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5123825073242188,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.4897384643554688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3788528442382812,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6785049438476562,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.2786941528320312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.2114334106445312,0,0,0,0,0,0,3.166740417480469,0,7.107856750488281,0,0,0,0,0,0,7.400390625,0,0,0,0,0,7.180694580078125,0,0,0,0,8.697113037109375,0,-35.52600860595703,0,0,0,0,0,0,0,0,0,0,0,0,0,2.94970703125,0,0,0,0,7.296005249023438,0,0,0,0,0,0,7.762382507324219,0,9.678932189941406,0,6.780265808105469,0,0,0,0,0,0,-30.46302795410156,0,0,2.825721740722656,0,0,0,0,0,0,0,6.087532043457031,0,0,0,0,1.598762512207031,0,0,0,0,9.684402465820312,0,0,0,0,0,0,7.488685607910156,0,6.731704711914062,0,0,0,0,0,0,0,0,-32.56283569335938,0,0,0,0,0,8.780815124511719,0,0,0,0,0,0,0,6.314399719238281,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11.61869049072266,0,5.86322021484375,0,0,0,0,0,0,-37.69356536865234,0,0,0,0,0,6.282341003417969,0,7.719505310058594,0,0,0,0,0,0,6.710678100585938,0,0,0,0,0,0,9.398391723632812,0,0,0,0,0,0,0,7.573272705078125,0,0,-33.49977874755859,0,2.238166809082031,0,0,0,7.512489318847656,0,10.94355773925781,0,0,0,0,0,0,7.5869140625,0,5.227767944335938,0,0,0,0,0,0,0,-31.97186279296875,0,7.742057800292969,0,0,0,0,0,0,0,0,0,0,9.8538818359375,0,0,0,0,0,0,3.652076721191406,0,0,0.5104446411132812,0,0,0,0,0,0,0,4.71868896484375,0,0,0,0,0,5.494560241699219,0,0,0,0,0,0,0,-35.57204437255859,0,0,0,0,0,4.075515747070312,0,0,0,0,0,6.704338073730469,0,0,0,0,0,0,0,4.524276733398438,0,0,0,3.840538024902344,0,0,0,2.815208435058594,0,0,0,0,0,3.136116027832031,0,1.252822875976562,0,0,0,5.97625732421875,0,0,0,0,0,0,0,1.599006652832031,0,0,0,0,0,0,0,-32.02739715576172,0,0,0,0,0,7.567398071289062,0,0,0,7.2015380859375,0,8.432258605957031,0,0,0,0,0,0,0,8.90472412109375,0,0,0,0,0,-25.00571441650391,0,0,0,0,0,0,0,0.9301681518554688,0,0,0,0,0,9.462867736816406,0,0,0,0,0,0,4.40289306640625,0,0,0,0,0,5.419448852539062,0,0,0,0,0,0,0,0,6.35968017578125,0,0,-43.88307952880859,0,0,4.416511535644531,0,10.26885986328125,0,7.433357238769531,0,9.502479553222656,0,6.324195861816406,0,-7.963836669921875,0,0,0,0,0,0,0,0,-20.98373413085938,3.469062805175781,0,0,6.299308776855469,0,0,0,0,0,0,7.837760925292969,0,0,0,0,0,0,0,0,0,8.705650329589844,0,5.773330688476562,0,-38.77023315429688,0,7.110420227050781,0,0,0,0,0,0,0,0,9.755889892578125,0,0,0,0,0,0,0,0,1.188652038574219,0,8.831878662109375,0,0,0,0,0,0,7.200981140136719,0,0,0,0,0,0,0,7.471061706542969,0,0,0,0,0,0,-38.89906311035156,0,6.941017150878906,0,0,0,0,0,0,10.18914794921875,0,0,0,0,0,0,0,1.759658813476562,0,0,0,0,0,6.621353149414062,0,5.543571472167969,0,0,0,0,0,0,7.84759521484375,0,0,0,0,0,0,-38.50705718994141,0,7.277572631835938,0,9.668380737304688,0,2.883697509765625,0,0,0,0.42584228515625,0,1.204414367675781,0,0,0,4.498374938964844,0,0,1.774986267089844,0,1.22882080078125,0,0,0,0.595733642578125,0,0,0,0,0,0,0,5.262847900390625,0,0,0,1.483016967773438,0,0,0,2.199592590332031,0,0,0,0,0,0,0,0,-36.91192626953125,0,0,1.387443542480469,0,1.508720397949219,0,0,0,0,0,6.395805358886719,0,0,0.2110671997070312,0,1.488082885742188,0,0,0,0.0206451416015625,0,0,7.249458312988281,0,0,0,0,0,0,9.97174072265625,0,0,0,0,0,8.690673828125,0,0,0,0,0,0,-33.24469757080078,0,0,0,0,0,8.898635864257812,0,0,0,0,0,0,9.217201232910156,0,8.370475769042969,0,0,0,0,0,0,0,6.734230041503906,0,0,-31.28566741943359,0,0,0,0,0.06101226806640625,0,0,0,0,0,0,0,4.348419189453125,0,0,0,0,0,0,0,0,0,0,0,0.6519775390625,0,0,6.030975341796875,0,0,0,0,0,0,0,4.269241333007812,0,0,0,0,0,0,0.5303802490234375,0,2.18450927734375,0,0,0,0,10.2176513671875,0,0,0,0,0,0,-30.17531585693359,0,0,0,0,5.35955810546875,0,0,0,0,0,0,6.640373229980469,0,0,0,0,0,0,3.275650024414062,0,0,0,0,0,9.014739990234375,0,0,0,0,0,0,0,6.801513671875,0,0,0,0,0,0,0,0,0,0,0,0,0,-31.10001373291016,0,0,0,0,0,0,6.948562622070312,0,0,0,0,0,10.26231384277344,0,6.884544372558594,0,0,0,1.784317016601562,0,0,0,0,0,7.319610595703125,0,0,0,0,0,0,0,-31.96517181396484,0,0,0,0,0,0,0,0,9.691322326660156,0,0,0,0,0,7.297645568847656,0,6.721366882324219,0,0,0,0,0,0,0,8.255279541015625,0,0,0,0,0,0,0,-30.12335205078125,0,0,0,0,0,0,0,0,0,1.318794250488281,0,0,0,0,0,9.254264831542969,0,7.792396545410156,0,9.746963500976562,0,0,0,0,0,0,-31.22916412353516,0,0,0,0,0,0,0,6.857093811035156,0,0,0,0,0,0,10.07685852050781,0,8.565277099609375,0,0,0,0,0,1.126747131347656,0,0,0,0,6.604278564453125,0,0,0,0,0,0,0,0,-29.80927276611328,0,0,0,0,9.30364990234375,8.204940795898438,0,0,0,0,0,0,9.887458801269531,0,0,0,0,0,0,-29.03084564208984,0,0,0,0,0,0,8.125991821289062,0,0,0,0,0,0,9.321975708007812,0,0,0,0,0,1.215553283691406,0,0,0,0,7.905624389648438,0,4.849769592285156,0,0,0,0,0,0,0,-26.03464508056641,0,7.00494384765625,0,8.223030090332031,0,7.328453063964844,0,0,0,0,0,0,0,0,0,0,0,0,0,-0.615631103515625,0,0,0,0,0,0,0,-31.59226989746094,0,0,0,0,0,0,0,0,0,1.97808837890625,0,0,0,0,0,0,0,0,0,0,0,0,0.4118576049804688,0,0,0,0,0,0,0,3.899795532226562,0,0,0,4.214363098144531,0,0,0,0.8606948852539062,0,0,0,0,0,3.6683349609375,0,0,0,0,0,5.303886413574219,0,0,0.4849395751953125,0,0,0,0,0,3.414962768554688,0,0,0,1.390571594238281,0,0,0,0,0,0,0,4.478050231933594,0,0,0,0,0,3.257492065429688,0,0,0,0,0,1.818740844726562,0,0,0,0,0,0,0,-36.16580963134766,0,0,0,0,0,0,0,3.589759826660156,0,0,0,0.3175582885742188,0,0,0,7.318679809570312,0,0,0,0,6.427490234375,0,0,0,0,0,0,6.779052734375,0,0,0,0,0,0,0,9.042755126953125,0,-8.292739868164062,0,0,0,0,0,0,0,0,-21.29018402099609,0,5.806686401367188,0,7.539207458496094,0,1.7318115234375,0,0,0,0,0,0,0,0,0,0,0,0,4.895034790039062,0,0,0,0,0,0,0,0,0,0,0,0,5.786613464355469,0,0,0,0,0,0,6.934028625488281,0,0,0,0,0,0,0,-37.13633728027344,0,0,0,0,0,0,0,8.195228576660156,0,0,0,0,0,0,0,6.300437927246094,0,7.974311828613281,0,2.854354858398438,0,0,0,0,0,5.868621826171875,0,0,0,0,0,0,0,0,0,6.059516906738281,0,0,-33.0823974609375,0,0,0,0,0,0,0,0,0,9.725852966308594,0,0,6.176719665527344,0,0,0,0,0,0,0,6.287696838378906,0,9.801445007324219,0,-33.94026184082031,0,1.658920288085938,0,0,0,0,5.834884643554688,0,7.021347045898438,0,0,0,0,0,0,0,9.431800842285156,0,0,0,0,0,0,6.535804748535156,0,4.549186706542969,0,0,-37.04940032958984,0,0,0,0,8.233795166015625,0,8.02764892578125,0,1.521026611328125,0,7.604484558105469,0,0,0,0,0,0,0,8.482818603515625,0,0,0,0,0,0,-25.30327606201172,0,0,-5.663856506347656,0,6.690048217773438,0,0,0,0,0,0,0,9.032539367675781,0,5.774253845214844,0,9.634429931640625,0,0,0,0,0,0,0,-35.40989685058594,0,1.18597412109375,0,0,0,0,0,0.4256057739257812,0,1.308197021484375,0,0,0,3.368644714355469,0,0,0,0,0,0,2.136871337890625,0,0,0,1.50445556640625,0,0,0,5.608680725097656,0,0,0,1.3177490234375,0,0,0,5.010948181152344,0,0,0.9252166748046875,0,1.589546203613281,0,0,0,0,0,5.808265686035156,0,0.3725433349609375,0,0,0,0,0,0,0,0.8787384033203125,0,2.711029052734375,0,0,4.266975402832031,0,0,0,0,0,0,0,-30.13842010498047,0,9.665519714355469,0,11.04096221923828,0,7.49517822265625,0,-32.49235534667969,0,8.724945068359375,0,10.7408447265625,0,3.0714111328125,0,0,0,0,0,0,0,4.348419189453125,0,0,0,0,0,0,0,0,0,0,0,4.907539367675781,0,0,0,0,0,0,0,1.775413513183594,0,0,0,0,0,0,0,-6.172065734863281,0,0,0,0,0,0,0,0,-25.46787261962891,0,0,0,6.549942016601562,0,0,0,0,13.10835266113281,0,5.205421447753906,0,0,0,0,5.608352661132812,0,-31.55079650878906,0,7.341217041015625,0,9.727104187011719,0,5.712013244628906,0,7.625587463378906,0,0,0,0,0,0,-6.794105529785156,0,0,-16.49930572509766,0,0,0,0,0,0,0,4.993965148925781,0,0,0,0,0,0,4.255172729492188,0,7.294517517089844,0,9.900100708007812,0,0,0,0,0,0,0,-29.71852874755859,0,7.465118408203125,0,0,0,0,0,0,0,6.961174011230469,0,0,0,0,0,0,0,10.45560455322266,0,4.001884460449219,0,0,0,0,0,0,0,0,0,0,0,-32.56143951416016,0,0,0,0,0,0,0,8.796058654785156,0,6.92486572265625,0,10.38046264648438,0,0,0,0,0,0,7.323188781738281,0,0,0,0,0,0,0,-24.92315673828125,0,0,0,0,0,0,0,8.228584289550781,0,0,0,0,0,0,10.17314147949219,0,0,0,0,0,0,0,0,0,0,0,6.506622314453125,0,0,0,0,0,0,0,0,-27.05527496337891,0,0,0,0,0,0,1.211257934570312,0,8.536231994628906,0,7.496894836425781,0,0,0,0,0,0,7.988418579101562,0,0,0,0,0,0,0,0,0,0,-27.33930969238281,0,10.10041809082031,0,0,0,0,0,0,0,7.063346862792969,0,8.576736450195312,0,0,0,0,0,0,0,0,1.942230224609375,0,0,0,0,0,0,0,0,-27.00312805175781,0,9.748626708984375,0,0,0,0,0,0,0,8.331825256347656,0,0,0,0,0,0,0,7.631607055664062,0,-26.17594146728516,0,7.482368469238281,0,11.17745208740234,0,10.10237884521484,0,-29.02696228027344,0,0,0,0,0,0.9850311279296875,0,0,0,0,0,0,0,0,0,4.617416381835938,0,0,0,4.991676330566406,0,0,0,0,0,0,0,0,0,0,0,5.059684753417969,0,0,0,4.085014343261719,0,0,0,0,0,0,0,1.6280517578125,0,0,0,0,0,3.915199279785156,0,0,0,0,0,-16.53647613525391,0,0,-7.257171630859375,0,0,0,0,0,0,0,1.763572692871094,0,2.673004150390625,0,0,0,5.686019897460938,0,0.2396774291992188,0,0,0,0,0,0,0,4.457763671875,0,0,0,3.678993225097656,0,0,0,0,4.282974243164062,0,0,0,0,-1.787330627441406,0,0,0,0,0,0,0,0,0,-15.92909240722656,0,0,0,0,0,0,0,0,0,0,0,0,0,10.78758239746094,0,0,0,0,0,0,0,0,0,0,0,0,0,6.989883422851562,0,0,0,0,0,0,-22.74313354492188,0,9.15283203125,0,8.014427185058594,0,0,0,0,0,0,0,0,3.511894226074219,0,0,0,0,0,0,0,0,5.095436096191406,0,-22.73736572265625,0,0,0,0,0,0,8.311668395996094,0,0,0,0,0,0,0,10.59538269042969,0,5.692092895507812,0,0,0,0,0,0,0,-20.18845367431641,0,7.127601623535156,0,0,0,0,0,0,7.867851257324219,0,0,0,0,0,0,0,2.913093566894531,0,0,0,0,0,0,0,0,-21.12630462646484,0,0,-7.05975341796875,0,7.447891235351562,0,0,0,0,0,0,0,10.18585968017578,0,0,0,0,0,0,0,7.857673645019531,0,-27.80580139160156,0,0,0,0,0,0,0,0,0,3.819679260253906,0,6.401847839355469,0,9.94598388671875,0,6.772773742675781,0,0,0,0,1.984779357910156,0,-32.98590087890625,0,0,0,0,0,0,6.897209167480469,0,0,0,0,0,9.551162719726562,0,9.918785095214844,0,0,0,0,0,0,0,7.483207702636719,0,0,0,0,0,0,-33.00740814208984,0,7.023513793945312,0,10.94391632080078,0,0,0,0,0,0,0,0,0,0,0,5.171340942382812,0,4.224929809570312,0,7.040573120117188,0,0,0,0,0,0,-31.83887481689453,0,9.198173522949219,0,7.146377563476562,0,0,0,0,0,0,0,7.650909423828125,0,8.959419250488281,0,-31.28881072998047,0,0,0,0,0,0,6.481147766113281,0,0,0,0,0,0,0,0,0,0,0,0,0.9090042114257812,0,1.34527587890625,0,0,0,0,0,5.012199401855469,0,1.233795166015625,0,0,0,0,0,4.171974182128906,0,0,0,0,0,1.976303100585938,0,1.533737182617188,0,0,0,2.460891723632812,0,0,0,0,2.690902709960938,0,1.319747924804688,0,0,0,0,0,-31.06468200683594,0,2.889915466308594,0,1.159980773925781,0,0,0,0,0,4.490943908691406,0,0,0,7.580345153808594,0,11.34468841552734,0,0,0,0,4.242080688476562,0,0,-22.03388977050781,0,7.821586608886719,0,8.180389404296875,0,8.022598266601562,0,0,0,0,0,0,-25.37077331542969,0,0,0,0,0,0.8037796020507812,0,0,0,0,0,0,0,4.348419189453125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.682952880859375,0,0,0,0,0,0,0,0,0,4.79962158203125,0,0,0,8.737174987792969,0,0,0,0,0,0,0,0,-23.47007751464844,0,6.717689514160156,0,6.283531188964844,0,0,0,0,0,0,9.059303283691406,0,0,0,0,0,-26.06548309326172,0,0,0,0,0,0,0,9.409385681152344,0,0,0,0,0,0,0,6.604209899902344,0,0,0,0,0,0,9.472465515136719,0,-24.77366638183594,0,0,0,0,0,0,0,7.301078796386719,0,11.69766235351562,0,7.743873596191406,0,0,0,0,0,0,0,-24.90182495117188,0,0,0,2.346763610839844,0,0,0,0,0,0,9.695777893066406,0,8.385749816894531,0,0,0,0,0,0,0,-22.34751892089844,0,0,0,0,0,0,6.323959350585938,0,0,0,0,0,0,10.79479217529297,0,7.880455017089844,0,0,0,0,0,0,0,-22.34404754638672,0,6.380661010742188,0,2.156455993652344,0,6.872451782226562,0,0,0,0,0,0,0,0,0,5.768440246582031,0,0,0,0,0,0,-23.14719390869141,0,0,0,0,0,0,0,0,0,6.1229248046875,0,0,0,0,0,0,0,9.942642211914062,0,0,0,0,0,0,0,0,0,0,0,7.016487121582031,0,-21.23601531982422,0,0,0,0,0,0,0,6.990737915039062,0,0,0,0,1.588279724121094,0,10.13936614990234,0,0,0,0,0,0,0,0,0,0,0,0,0,-8.934906005859375,0,0,-4.795417785644531,0,11.01290130615234,0,0,0,0,0,0,0,0,0,7.510955810546875,0,0,0,0,0,0,-20.73932647705078,0,7.809013366699219,0,0,0,0,0,0,0,11.27145385742188,0,-20.529541015625,0,0,0,0,0,1.130943298339844,0,9.301567077636719,0,7.562713623046875,0,0,0,0,-18.77634429931641,0,0,0,0,0,0,10.07355499267578,0,8.061485290527344,0,0,0,0,0,0,0,5.601768493652344,0,0,0,0,0,0,0,-32.75731658935547,0,6.031425476074219,0,9.685256958007812,0,0,0,0,0,0,0,0,0,10.12492370605469,0,1.670509338378906,0,0,0,0,0,3.292457580566406,0,0,0,0,0,-32.24505615234375,0,0,2.335861206054688,0,0,0,0,0,3.384811401367188,0,0,0,0,0,3.016471862792969,0,0,0,0,0,0,0,3.564064025878906,0,0,0,0,0,1.9205322265625,0,0,0,0,0,0,0,2.038932800292969,0,0,0,3.534934997558594,0,0,0,0,0,0,0,2.365226745605469,0,0,0,2.586257934570312,0,0,0,0,0,4.644287109375,0,0,0,0,0,0,1.844039916992188,0,0,0,0,0,-19.49412536621094,0,0,0,0,0,0,0,-11.59597778320312,0,0,0,4.105255126953125,0,0,0,0,0,0,3.649101257324219,0,0,0,0,8.166824340820312,0,0,0,0,0,0,0,0,0,0,0,7.979293823242188,0,0,0,0,8.01116943359375,0,-28.14720916748047,0,8.843704223632812,0,7.360832214355469,0,0,0,0,0,0,8.463851928710938,0,0,0,0,0,0,0,0,0,0,0,0,0.3064422607421875,0,0,0,0,0,0,0,-18.83148956298828,0,1.9517822265625,0,0,0,6.440559387207031,0,7.265464782714844,0,8.516853332519531,0,0,0,0,0,0,0,0,-25.51392364501953,0,0,0,0,0,0,0,6.257797241210938,0,0,0,0,0,0,10.29698181152344,0,6.251945495605469,0,0,0,-27.85324096679688,0,0,0,0,0,0,0,10.16669464111328,0,0,0,0,0,0,0,0,9.905220031738281,0,0,0,0,0,0,0,0,4.388008117675781,0,0,0,0,0,0,4.393623352050781,0,0,0,0,0,0,0,0,0,0,0,-26.61698150634766,0,0,0,0,0,0,0,0,0,0,6.317825317382812,0,0,0,0,0,0,9.973388671875,0,0,0,0,0,0,0,6.215217590332031,0,5.808448791503906,0,0,0,0,0,0,0,0,-22.92961120605469,0,6.355201721191406,0,10.71638488769531,0,0,0,0,0,0,0,4.333427429199219,0,0,0,0,-4.788330078125,0,0,-14.91246032714844,0,9.687042236328125,0,7.055732727050781,0,0,0,0,0,0,-23.69412231445312,0,0,0,0,0,9.448150634765625,0,6.716567993164062,0,0,0,0,0,0,0,7.815170288085938,0,4.206138610839844,0,0,-21.19873046875,0,6.840728759765625,0,0,0,0,0,0,0,0,0,1.88116455078125,0,0,0,0,0,10.46901702880859,0,-23.32101440429688,0,0,0,0,0,6.439895629882812,0,0,0,0,10.06015777587891,0,0,0,0,0,0,0,0,7.59942626953125,0,0,0,0,0,0,0,-23.81400299072266,0,0,0,0,0,0,0,0,0,0,8.450141906738281,0,0,0,0,0,0,0,5.818824768066406,0,9.128936767578125,0,0,0,0,0,0,-22.72126770019531,0,2.030548095703125,0,0.4666519165039062,0,1.167205810546875,0,0,0,1.48321533203125,0,0,0,0,0,0,0,4.480003356933594,0,0.4657974243164062,0,0,0,0,0,0,0,0.7735519409179688,0,0,0,4.47027587890625,0,0,0,0,1.730476379394531,0,1.346778869628906,0,0,0,0,0,4.815261840820312,0,0,-25.53401184082031,0,1.0357666015625,0,0,0,0,0,3.871360778808594,0,0,0,0,2.848503112792969,0,0.7961883544921875,0,0,0,0,0,0,0,0.4884796142578125,0,0,0,0,0,7.913032531738281,0,0,9.717269897460938,0,0,-18.0789794921875,0,0,0,0,0,0,0,0,0,0,0,0,9.735954284667969,0,0,0,0,0,7.778152465820312,0,0,0,0,0,0,-19.14879608154297,0,7.144149780273438,0,0,0,0,0,0,0,11.96176910400391,0,-18.76415252685547,0,0,0,0,0.4744720458984375,0,0,0,0,0,0,0,4.348419189453125,0,0,0,0,0,0,0,0,0,0,0,6.682952880859375,0,0,0,0,0,0,0,0,0,4.79962158203125,0,0,0,-0.7046279907226562,0,0,0,-10.19377136230469,0,0,0,0,0,0,9.143341064453125,0,0,0,0,0,0,0,0,4.821182250976562,0,0,0,0,0,0,0,-17.02288818359375,0,0,0,0,0,0,6.652748107910156,0,7.468170166015625,0,0,0,0,0,0,0,0,0,2.882171630859375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-44.96061706542969,0,0,0,0,0,0,0,4.807403564453125,0,9.4615478515625,0,0,0,0,0,0,0,0,0,0,0,0,0,7.77276611328125,0,11.29813385009766,0,10.91482543945312,0,0,0,0,0,0,-40.81155395507812,0,7.525588989257812,0,0,0,0,2.237167358398438,0,10.05290985107422,0,0,0,0,0,0,0,7.410835266113281,0,7.188339233398438,0,0,0,0,0,0,0,7.099494934082031,0,0,-36.34552764892578,0,0,0,0,0,0,6.689315795898438,0,8.924156188964844,0,0,0,0,0,0,0,7.372207641601562,0,0,0,0,0,0,2.899375915527344,0,0,0,0,0,0,0,0,0,0,0,7.43792724609375,0,0,-38.75572967529297,0,0,0,0,0,0,10.04427337646484,0,7.081222534179688,0,0,0,0,0,0,0,7.114273071289062,0,0,0,0,0,9.904640197753906,0,0,0,0,0,0,0,7.6568603515625,0,0,-33.41133880615234,0,0,0,0,0,0,0,4.441787719726562,0,0,0,5.283981323242188,0,7.343849182128906,0,0,0,9.81927490234375,0,0,0,0,0,0,6.523223876953125,0,0,0,0,0,0,0,0,0,0,-37.08988952636719,0,0,0,0,0,0,8.142303466796875,0,0,0,0,0,0,0,0,0,0,11.73431396484375,0,0,0,0,0,0,1.193740844726562,0,8.578117370605469,0,7.135963439941406,0,-36.66487884521484,0,9.506851196289062,0,0,0,0,0,0,0,8.111427307128906,0,0,0,0,0,0,8.223655700683594,0,6.706901550292969,0,0,0,0,0,0,0,0,0,0,0,-35.70523834228516,0,6.662399291992188,0,0,0,0,0,0.7568817138671875,0,0,0,0,0,3.714622497558594,0,0,0,0,0,3.50537109375,0,0,0,0,0,0,2.393341064453125,0,0,0,0,0,0,0,3.737846374511719,0,0,0,0,0,5.001571655273438,0,0,0.99334716796875,0,0,0,0,0,0,0,4.082176208496094,0,0,0,0,0,5.3890380859375,0,0,1.521629333496094,0,0,0,0,0,2.333770751953125,0,0,-38.61544036865234,0,0,0,0,0,5.874031066894531,0,1.097312927246094,0,0,0,0,0,0,0,4.280769348144531,0,0,0,0,0,5.246788024902344,0,0,0,5.761260986328125,0,7.133102416992188,0,9.256431579589844,0,0,0,0,0,0,0,-34.85140228271484,0,0,0,0,0,0,9.283920288085938,0,0,0,0,0,0,5.614715576171875,0,0,0,0,0,0,8.93280029296875,0,9.148162841796875,0,-33.71200561523438,0,4.896560668945312,0,0,0,5.298553466796875,0,8.128562927246094,0,0,0,0,0,0,0,0,0,0,0,0,0,10.42346954345703,0,0,0,0,0,0,0,6.810073852539062,0,0,0,0,0,0,0,-31.41343688964844,0,9.310935974121094,0,0,0,0,0,0,0,7.608291625976562,0,0,0,0,0,0,0,11.40440368652344,0,-33.29067993164062,0,1.27386474609375,0,8.716758728027344,0,0,0,0,0,0,8.608535766601562,7.664375305175781,0,8.01318359375,0,0,0,0,-33.98424530029297,0,0,0,0,0,0,11.50807952880859,0,0,0,0,0,0,0,6.995452880859375,0,0,0,0,0,0,0,0,0,3.06256103515625,0,0,0,0,0,0,0,11.25066375732422,0,-19.41979217529297,0,0,-2.552322387695312,0,0,0,0,0,0,0,7.097213745117188,0,9.886466979980469,0,0,0,0,0,0,0,7.050254821777344,0,0,0,0,0,0,0,0,-30.30219268798828,0,11.67977905273438,0,4.34930419921875,0,0,0,0,0,0,0,0,5.471488952636719,0,0,0,0,0,0,0,0,0,7.727691650390625,0,0,0,0,-29.64542388916016,0,7.913902282714844,0,0,0,0,0,0,10.85588836669922,0,0,0,0,0,7.317131042480469,0,0,0,0,0,0,0,-21.05133819580078,0,0,0,0,0,0,0,-0.9754714965820312,0,0.7577896118164062,0,0.7963104248046875,0,0,0,4.631622314453125,0,0,1.142410278320312,0,0.9392013549804688,0,0,0,5.105094909667969,0,0,0.3870697021484375,0,1.064437866210938,0,2.503715515136719,0,2.321144104003906,0,1.019889831542969,0,0,0,4.97430419921875,0,0,0,0,0.7565536499023438,0,1.032241821289062,0,0,0,-29.73830413818359,0,0,0,0,4.373847961425781,0,0,0,0,0,13.09571838378906,0,0,0,0,0,8.865493774414062,0,-26.13519287109375,0,0,0,0,0,0,8.63067626953125,0,8.225959777832031,0,11.33203887939453,0,0,0,0,0,0,0,-25.38859558105469,0,0,0,0,0,0,0,2.583908081054688,0,0,0,0,0,0,0,4.348419189453125,0,0,0,0,0,0,0,0,0,0,0,5.940513610839844,0,0,0,0,0,0,0.7424392700195312,0,0,0,0,0,0,0,4.79962158203125,0,0,0,5.460494995117188,0,0,0,0,0,0,-6.316596984863281,0,0,0,0,0,0,0,0,-22.11811065673828,0,0,0,5.322944641113281,0,6.874588012695312,0,0,0,0,0,6.878463745117188,0,5.397293090820312,0,0,0,0,0,7.288032531738281,0,0,0,0,0,0,0,0,-36.05876159667969,0,7.425483703613281,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.602714538574219,0,0,0,0,7.536575317382812,0,0,0,0,0,7.339958190917969,0,-14.23628234863281,0,0,0,0,0,0,0,-16.12310791015625,0,0,0,0,0,0,9.478141784667969,0,7.831367492675781,0,9.804176330566406,0,0,0,0,0,0,0,1.731903076171875,0,0,0,0,0,0,0,5.842254638671875,0,0,0,0,0,0,0,-35.81385803222656,0,8.951835632324219,0,0,0,0,0,0,7.829673767089844,0,10.43212127685547,0,8.348861694335938,0,0,0,0,0,0,0,-35.03063201904297,0,9.897132873535156,0,0,0,0,1.219589233398438,0,0,0,8.097450256347656,0,8.010299682617188,0,6.199607849121094,0,-34.27484893798828,0,7.32928466796875,0,9.964187622070312,0,1.628494262695312,0,0,0,0,7.653755187988281,0,0,0,0,0,0,0,7.916000366210938,0,0,0,0,0,0,0,-32.73069763183594,0,8.309471130371094,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9.212455749511719,0,0,0,0,0,0,6.954444885253906,0,0,0,0,0,9.907241821289062,0,0,-30.63755798339844,0,0,0,0,0,0,0,4.648872375488281,0,0,0,0,0,0,0,0.5932235717773438,0,0,0,0,0,0,0,4.216529846191406,0,0,0,3.238151550292969,0,0,0,1.780708312988281,0,0,0,0,0,3.765304565429688,0,0,0,0,0,5.723373413085938,0,0,0,0,0,0.8373184204101562,0,0,0,0,0,0,0,3.028373718261719,0,0,0,2.811103820800781,0,0,0,0,0,0,-33.07374572753906,0,0,0,0,0,0,0,2.039009094238281,0,0,0,0,0,0,0,2.103530883789062,0,0.4925918579101562,0,0,0,0,0,0,0,4.667930603027344,0,0,0,0,0,3.191810607910156,0,0,0,0,0,0,0,0,0,0.7557373046875,0,0,0,5.519569396972656,0,5.632171630859375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.363471984863281,0,-31.73386383056641,0,0,0,0,0,0,7.10101318359375,0,9.452079772949219,0,6.869606018066406,0,0,0,0,0,8.617599487304688,0,0,-32.4432373046875,0,3.9932861328125,0,7.196075439453125,0,0,0,0,0,0,7.202400207519531,0,0,0,7.809333801269531,0,0,0,0,2.778152465820312,0,0,-21.46822357177734,0,0,1.141517639160156,0,0,0,0,0,0,0,7.439109802246094,0,0,0,0,0,8.247848510742188,0,0,0,0,0,0,7.367698669433594,0,-28.12270355224609,0,0,0,0,0,0,7.573013305664062,0,10.12142944335938,0,3.514068603515625,0,5.419685363769531,0,-27.69828033447266,0,7.285484313964844,0,7.401359558105469,0,0,0,0,0,0,0,8.490974426269531,0,0,0,0,0,6.753273010253906,0,0,0,0,0,0,0,0,-24.22111511230469,0,0,0,0,0,0,1.388328552246094,0,0,0,0,0,0,0,0,0,0,9.106582641601562,0,0,0,0,0,0,0,7.937705993652344,0,0,0,0,0,0,-16.60797119140625,0,0,-1.241111755371094,0,0,0,0,0,0,0,7.780929565429688,0,0,0,0,0,0,0,9.376861572265625,0,4.494712829589844,0,0,0,0,0.6163101196289062,0,1.06195068359375,0,0,0,0,0,-26.28273773193359,0,0,0,1.454216003417969,0,1.210334777832031,0,0,0,0,0,3.231979370117188,0,0,0,0,0,0,0,3.102813720703125,0,0.8667755126953125,0,0,0,1.327354431152344,0,4.234535217285156,0,1.199264526367188,0,0,0,0,0,4.973762512207031,0,0,0,0,0,0,1.135810852050781,0,1.057693481445312,0,0,0,0,0,-23.78317260742188,0,7.65277099609375,0,12.47859954833984,0,0,0,0,0,6.446212768554688,0,0,-19.78430938720703,0,0,0,0,0,0,8.19232177734375,0,0,0,0,0,11.57363891601562,0,0,-20.74678802490234,0,0,0,0,0,0,0,7.414413452148438,0,12.03945922851562,0,-23.58246612548828,0,0,0,0,0,4.079399108886719,0,0,0,0,0,0,0,0,0,0,0,0,0,8.933341979980469,0,0,0,0,0,0,1.214996337890625,0,0,0,0,0,0,0,5.981826782226562,0,0,0,4.668006896972656,0,0,-36.85676574707031,0,0,0,0,0,0,13.77100372314453,0,6.317367553710938,0,6.544403076171875,0,0,0,0,0,0,7.0711669921875,0,0,0,0,0,0,-35.25795745849609,0,0,0,0,0,0,0,0,6.718681335449219,0,7.361129760742188,0,0,0,0,0,0,7.196739196777344,0,0,0,0,2.839263916015625,0,0,0,0,0,0,0,8.019973754882812,0,0,0,0,0,0,6.291038513183594,0,0,-35.56880187988281,0,0,0,0,0,10.57648468017578,0,0,0,0,0,0,0,7.349327087402344,0,6.567169189453125,0,0,0,0,0,0,3.160308837890625,0,0,0,0,0,0,7.913894653320312,0,0,0,0,0,0,0,0,-35.34737396240234,0,0,0,0,0,6.668045043945312,0,9.545051574707031,0,7.038749694824219,0,6.275901794433594,0,0,0,0,0,0,3.153648376464844,0,0,0,0,0,0,0,0,-32.72429656982422,0,9.126007080078125,0,0,0,0,0,0,0,0,6.968521118164062,0,0,0,0,9.789665222167969,0,6.4110107421875,0,-33.19937896728516,0,5.748733520507812,0,0,0,0,0,0,0,6.891593933105469,0,0,0,0,0,0,0,0,0,0,0,2.067581176757812,0,8.442161560058594,0,0,0,0,0,0,6.360671997070312,0,6.753997802734375,0,0,-31.05815887451172,0,5.957099914550781,0,9.05828857421875,0,0,1.158676147460938,0,0,0,0,0,0,0,0,0,0,0,0.7678756713867188,0,0,0,5.942916870117188,0,1.774551391601562,0,0,0,0,0,0,0,3.612495422363281,0,0,0,0,0,0,0,0,0,0,0,2.78955078125,0,0,0,0,0,0,0,-30.89482116699219,0,0,0,5.356590270996094,0,0,0.5395431518554688,0,0,0,0,0,0,0,0,0,5.98223876953125,0,0,0,4.474609375,0,0,2.09063720703125,0,0,0,0,0,0,0,0,0,5.420181274414062,0,0,0,5.294090270996094,0,0,0.9967498779296875,0,0,0,0,0,0,0,0,0,0,0,0.6888580322265625,0,0,0,0,-27.1551513671875,0,0,0,6.402450561523438,0,0,0,0,6.994071960449219,0,0,0,0,0,0,7.356056213378906,0,0,0,0,0,0,0,0,0,-2.466987609863281,0,0,0,0,0,0,0,0,-17.64491271972656,0,0,0,0,0,0,8.739295959472656,0,0,0,0,0,0,0,0,8.621330261230469,0,0,0,0,0,0,1.206588745117188,0,0,0,8.004463195800781,0,0,0,0,0,0,0,-28.61266326904297,0,0,0,0,0,0,9.021415710449219,0,0,0,0,0,0,0,7.772605895996094,0,7.37261962890625,0,-25.52025604248047,0,3.05377197265625,0,0,0,0,0,0,0,0,0,5.87506103515625,0,8.765892028808594,0,0,0,7.301223754882812,0,0,0,0,0.09496307373046875,0,0,0,0,0,0,0,-19.20481109619141,0,0,0,0,0,0,0,0,0,9.425552368164062,0,0,0,0,0,0,9.671646118164062,0,0,1.162513732910156,0,-25.25988006591797,0,6.640472412109375,0,0,0,0,10.29055786132812,0,0,0,0,0,0,0,7.409355163574219,0,-23.84521484375,0,0,0,0,0,0,0,5.484725952148438,0,1.989410400390625,0,0,0,0,0,0,0,0,0,0,0,0,7.391525268554688,0,0,0,0,0,0,0,0,0,0,0,0,7.532875061035156,0,0,0,0,0,0,5.708663940429688,0,0,-22.04022216796875,0,8.821830749511719,0,0,0,0,6.516281127929688,0,0,0,0,0,0,0,5.202972412109375,0,0,0,0,0.7886734008789062,0,1.208564758300781,0,0,-27.19412994384766,0,2.617744445800781,0,0,0,0,0,2.510978698730469,0,0,0,2.000106811523438,0,1.988731384277344,0,0,0,0,0,0,0,3.027168273925781,0,1.647331237792969,0,0,0,5.098480224609375,0,0,0.1746292114257812,0,1.615692138671875,0,1.137657165527344,0,0,0,0,0,0,0,4.669441223144531,0,0,0,-24.556396484375,0,0.7741851806640625,0,0,0,0,0,0,0,5.381050109863281,0,0,0,0,12.78883361816406,0,0,0,0,0,0,0,-17.25609588623047,0,0,0,0,0,0,8.427360534667969,0,8.720588684082031,0,0,0,-7.464897155761719,0,0,-3.051239013671875,0,0,0,0,10.88453674316406,0,0,0,0,0.06581878662109375,0,0,0,3.272369384765625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.718460083007812,0,0,0,0,0,0,-16.05109405517578,0,0,0,2.806930541992188,0,0,0,0.8885726928710938,0,0,0,0,0,0,10.12003326416016,0,0,0,0,0,0,0,-19.35861206054688,0,0,0,0,0,0,0,-8.814468383789062,0,0,0,4.35894775390625,0,0,0,0,0,0,8.293380737304688,0,0,0,0,0,7.047599792480469,0,6.997642517089844,0,0,0,0,0,-31.56244659423828,0,0,0,0,0,0,0,7.508880615234375,0,0,0,0,7.963233947753906,0,8.345565795898438,0,0,0,0,0,1.500930786132812,0,0,0,0,0,6.632919311523438,0,0,0,0,0,0,0,-30.96818542480469,0,0,0,0,0,0,9.075103759765625,0,0,0,0,0,0,0,0,8.546340942382812,0,0,0,0,0,0,8.750770568847656,0,0,0,0,0,0,7.922615051269531,0,0,0,0,0,0,0,-31.37467193603516,0,0,0,0,0,0,0,0,0,0,0,7.466514587402344,0,0,0,0,0,0,0,0,1.344985961914062,0,0,0,0,0,0,8.491714477539062,0,9.121734619140625,0,0,0,0,0,0,4.948982238769531,0,0,0,0,0,0,0,0,0,-29.03843688964844,0,0,0,0,0,7.734367370605469,0,0,0,0,0,0,0,1.626495361328125,0,0,0,0,0,7.682304382324219,7.730934143066406,0,0,0,0,0,0,3.303260803222656,0,0,0,0,0,0,0,-25.52449035644531,0,6.127845764160156,0,0,0,0,0,0,0,4.687744140625,0,0,0,3.933631896972656,0,6.206863403320312,0,0,0,0,0,0,0,-20.44577026367188,0,0,-1.741523742675781,0,7.869438171386719,0,0,0,0,0,0,0,0,0,0,0,0,5.580642700195312,0,0,0.8391036987304688,0,0,0,0,0,0,0,0,0,4.926239013671875,0,0,0,0,0,0,0,0.262176513671875,0,5.022064208984375,0,0,0,0,0,0,0,0,0,0,0,3.201667785644531,0,0,-29.10816955566406,0,0,0,4.964111328125,0,0,0,0,0,0,0,0,0,0,0,5.111480712890625,0,2.803321838378906,0,0,1.784713745117188,0,0,0,0,0,0,0,0,0,1.209159851074219,0,0,0,0,0,0,0,4.182121276855469,0,4.047828674316406,0,0,0,0,0,1.550308227539062,0,0,0,0,0,0,0,0,0,1.503349304199219,0,-26.69409942626953,0,1.826210021972656,0,0,0,0,4.166336059570312,0,0,0,0,0,8.293403625488281,0,0,0,0,0,0,6.280014038085938,0,0,0,0,0,0,7.440437316894531,0,0,0,0,0,-25.52239227294922,0,8.801765441894531,0,0,0,0,6.822845458984375,0,3.39752197265625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.077064514160156,0,-25.54294586181641,0,0,0,0,8.454315185546875,0,7.344512939453125,0,7.027511596679688,0,3.792320251464844,0,0,-27.18702697753906,0,0,0,6.008354187011719,0,0,0,0,9.482025146484375,0,0,0,0,0,0,6.919425964355469,0,-22.3714599609375,0,6.309158325195312,0,0,0,0,0,0,0,0,0,0,7.838668823242188,0,0,1.1419677734375,0,0,6.404914855957031,0,-12.41307067871094,0,0,0.3304519653320312,0,6.524673461914062,0,0,0,0,0,9.757255554199219,0,-24.311767578125,0,0,0,0,0,0,0,0,0,0,6.611907958984375,0,1.642021179199219,0,8.351890563964844,0,0,0,8.961013793945312,0,0,-23.8773193359375,0,0,0,0,0,9.209709167480469,0,7.049797058105469,0,7.619720458984375,0,0,-20.43158721923828,0,1.545051574707031,0,0,0,0,0,0.3777008056640625,0,0,0,2.680374145507812,0,0,0,3.788284301757812,0,0,0,0,0,2.762504577636719,0,0,0,4.454437255859375,0,0,0,1.186943054199219,0,0,0,0,0,0,0,1.194625854492188,0,2.44183349609375,0,0,0,0,0,0,-22.55076599121094,0,0,0,2.079345703125,0,0,0,3.58465576171875,0,0,0,1.622734069824219,0,0,0,2.2254638671875,0,0,0,5.030838012695312,0,8.007102966308594,0,0,0,0,0,0,-15.36631774902344,0,0,0,0,0,10.74564361572266,0,0,0,-14.53862762451172,0,0,0,0,0,0,0,4.599838256835938,0,0,0,0,0,7.542610168457031,0,0,0,0,0,0,0,7.016899108886719,0,0,-14.85465240478516,0,3.404708862304688,0,0,0,0,0,3.272369384765625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.113029479980469,0,0,0,0,0,0,0,0,-35.27510833740234,0,0,0,2.806930541992188,0,0,0,2.572517395019531,0,0,8.559562683105469,0,0,0,0,0,9.712677001953125,0,4.530204772949219,0,0,0,7.142837524414062,0,0,0,0,0,0,0,-30.05052185058594,0,0,0,0,0,6.2855224609375,0,0,0,0,0,0,0,9.536636352539062,0,0,0,0,0,0,0,6.680816650390625,0,6.036354064941406,0,-29.81022644042969,0,3.333045959472656,0,3.946388244628906,0,0,0,0,0,0,0,0,0,0,0,9.063758850097656,0,0,0,0,0,0,0,7.22576904296875,0,0,0,0,0,0,0,0,0,0,7.378738403320312,0,-29.92999267578125,0,0,0,0,0,0,0,6.015174865722656,0,9.322845458984375,0,0,0,0,0,0,3.498802185058594,0,0,0,0,0,5.883956909179688,0,-21.64842987060547,0,0,0.0257720947265625,0,0,0,0,0,0,0,0,0,0,9.2086181640625,0,7.441551208496094,0,0,0,0,10.53363037109375,0,0,0,0,0,0,0,-27.47181701660156,0,7.35760498046875,0,0,0,0,6.126884460449219,0,6.347686767578125,0,0,0,0,0,0,0,0,2.005622863769531,0,0,0,0,0,5.648567199707031,0,0,0,0,0,0,0,-28.49903106689453,0,7.800048828125,0,0,0,7.593429565429688,0,7.256141662597656,0,0,0,0,0,0,0,0,5.872360229492188,0,0,-31.30667114257812,0,0,0,0,6.292198181152344,0,9.569595336914062,0,0,0,0,8.221244812011719,0,6.902793884277344,0,0,0,0,0,0,0,-27.55567932128906,0,6.036834716796875,0,9.355377197265625,0,9.124359130859375,0,0,0,0,0,0,0,0,0,0,0,2.192527770996094,0,0,0.0778656005859375,0,0,0,0,0,0,0,0,0,0,0,-24.36338043212891,0,0,0,3.475410461425781,0,0,0,0,0,0,1.471916198730469,0,0,0,0,0,0,0,0,0,0.1409912109375,0,0,0,5.406639099121094,0,1.391876220703125,0,0,0,0,0,0,0,4.115394592285156,0,0,0,0,0,0,0,0,0,0,0,5.7550048828125,0,0,0,3.696258544921875,0,0,-27.71485137939453,0,0,0,0,0,0,0,0,0,0,0,5.119308471679688,0,0,0,5.456298828125,0,0,0,0,0,0.06641387939453125,0,0,0,0,0,0,0,0,0,5.12933349609375,0,0,0,5.598533630371094,0,0,5.837532043457031,0,0,0,0,0,0,0,-23.76653289794922,0,0,0,0,0,0,8.212745666503906,0,0,0,0,6.283271789550781,0,6.797019958496094,0,-22.90287780761719,0,9.114830017089844,0,6.212852478027344,0,7.9517822265625,0,-23.31687927246094,0,0,0,0,0,0,1.620841979980469,0,0,0,0,4.759513854980469,0,6.916336059570312,0,8.040977478027344,0,0,0,0,-3.650039672851562,0,0,0,0,0,0,0,0,-11.04835510253906,0,0,0,0,5.950202941894531,0,0,0,0,0,0,0,10.74661254882812,0,0,0,0,0,0,1.091941833496094,0,0,-23.73147583007812,0,0,0,0,0,0,9.935737609863281,0,0,0,0,0,0,0,0,6.00311279296875,0,8.173141479492188,0,0,0,0,0,0,-22.32252502441406,0,0,0,0,0,7.521125793457031,0,9.01123046875,0,0,0,0,0,6.902458190917969,0,0,0,0,0,0,0,0,0,-20.38558197021484,0,0,0,0,0,0,0,0,1.69012451171875,0,0,0,0,0,0,0,6.580162048339844,0,0,0,0,0,0,0,10.79472351074219,0,-20.691162109375,0,6.4764404296875,0,0,0,0,0,0,0,7.144157409667969,0,7.515632629394531,0,-19.11428833007812,0,8.180519104003906,0,2.912246704101562,0,0,0,0,5.060134887695312,0,0,0,0,0,0,-18.02957153320312,0,8.552619934082031,0,0,0,6.737648010253906,0,0,0,0,0,0,0,6.576271057128906,0,0,0,0,0,0,0,0,-33.55484008789062,0,7.190864562988281,0,0,0,0,0,0,6.584075927734375,0,0,0,0,0,8.152740478515625,0,0,0,0,0,0,0,3.245521545410156,0,0.4374923706054688,0,1.406059265136719,0,0,0,4.535552978515625,0,1.142814636230469,0,0,0,0,0,0,0.071533203125,0,0.7826004028320312,0,0,0,0,0,0,0,0,-31.08367156982422,0,0,0,0,0,0,0.7270965576171875,0,1.351348876953125,0,0,0,5.29791259765625,0,0,0.06446075439453125,0,1.522933959960938,0,0,0,5.254623413085938,0,0.4935684204101562,0,0,0,0,0,0,0,0,0.835784912109375,0,3.75299072265625,0,0,6.767158508300781,0,0,0,0,0,0,0,-25.94405364990234,0,12.26325225830078,0,0,0,0,0,7.025932312011719,0,0,0,0,0,0,0,0,6.863571166992188,0,0,0,0,0,-26.74083709716797,0,0,0,0,0,0,7.424850463867188,0,0,0,0,0,0,8.990005493164062,0,2.237083435058594,0,0,0,0.7692031860351562,0,0,0,0,0,2.503166198730469,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9.458686828613281,0,0,0,-4.659820556640625,0,0,0,-24.22838592529297,0,0,0,4.422149658203125,0,0,0,10.83718109130859,0,7.513961791992188,0,0,0,0,0,0,4.374725341796875,0,-26.52561187744141,0,8.323341369628906,0,0,0,0,0,4.767791748046875,0,0,0,0,0,0,0,0,0,7.122901916503906,0,6.930191040039062,0,-25.83136749267578,0,0,0,0,0,0,0,2.276626586914062,0,0,0,4.015769958496094,0,0,0,0,0,0,0,0,0,0,0,10.18858337402344,0,0,0,0,0,0,6.967681884765625,0,-24.33138275146484,0,0,0,0,0,0,0,5.697578430175781,0,8.592422485351562,0,0,0,0,0,0,5.20751953125,0,4.228752136230469,0,0,0,0,4.054718017578125,0,0,0,0,0,0,-23.84330749511719,0,5.849288940429688,0,0,0,0,0,0,0,8.534500122070312,0,8.290756225585938,0,-22.95394134521484,0,5.940773010253906,0,4.062446594238281,0,0,0,0,0,0,3.823577880859375,0,0,0,0,0,0,10.09718322753906,0,-23.60310363769531,0,0,0,0,0,0,0,5.017280578613281,0,0,0,0,0,0,6.736434936523438,0,0,0,0,0,0,0,7.680610656738281,0,-22.06417846679688,0,0,0,0,0,0,0,0,0,8.659896850585938,0,4.741767883300781,0,1.09564208984375,0,0,0,0,0,9.267715454101562,0,-22.06144714355469,0,0,0,0,0,0,0,0,0,0,0,0,0,5.257888793945312,0,0,0,0,7.660346984863281,0,0,0,0,0,0,0,0,0,0,0,0,8.645721435546875,0,0,0,0,3.38739013671875,0,0,-19.19235992431641,0,0,0,0,0,0,0,0,5.600654602050781,0,3.263015747070312,0,0,0,0,0.5730209350585938,0,0,0,0,0,0,0,0,0,2.531150817871094,0,0,0,0,0,0,0,2.570159912109375,0,3.539764404296875,0,-23.48462677001953,0,0,0,0,0,0,0,0,0,0,0,0,0,6.192153930664062,0,2.961837768554688,0,0,0,0,0,0,1.60858154296875,0,0,0,0,0,0,0,0,0,0,0,5.906204223632812,0,0.7627334594726562,0,0,0,0,0,0,0,4.210609436035156,0,0,0,0,0,0,0,0,0,0,0,-18.66798400878906,0,0,0,0,0,0,0,0.5913314819335938,0,3.678085327148438,0,0,2.280143737792969,0,0,0,0,0,0,0,0,0,0.8240890502929688,0,0,0,4.224502563476562,0,3.572097778320312,0,0,0,0,4.112174987792969,0,0,0,0,0,0,0,0,0,-16.96714019775391,0,0,0,0,0,8.363639831542969,0,0,0,0,0,0,0,5.764900207519531,0,0,0,0,0,0,0,5.176422119140625,0,0,0,0,0,0,0,0,-17.19044494628906,0,0,0,0,0,0,0,0,0,7.625663757324219,0,1.311859130859375,0,0,8.214866638183594,0,-17.08171844482422,0,5.306373596191406,0,6.297561645507812,0,0,0,0,0,0,0,-11.39926910400391,0,0,0,0,0,0,0,2.0386962890625,0,0,0,0,0,0,0,5.542045593261719,0,0,2.009994506835938,0,0,0,0,0,0,0,7.2960205078125,0,0,-12.85554504394531,0,0,0,0,0,0,0,6.069618225097656,0,6.82025146484375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-28.60254669189453,0,0,-15.99481201171875,0,0,7.428459167480469,0,7.380882263183594,0,7.305435180664062,0,3.043212890625,0,5.610267639160156,0,7.972061157226562,0,0,0,0,0,0,5.274810791015625,0,0,0,0,0,0,0,0,-40.85507202148438,0,0,0,0,0,0,8.291038513183594,0,7.345535278320312,0,1.740524291992188,0,0,0,0,0,8.236625671386719,0,7.485832214355469,0,7.352043151855469,0,0,0,0,0,0,-40.88641357421875,0,0,0,0,0,0,0,0,10.10611724853516,0,0,0,0,0,0,0,7.771072387695312,0,0,0,0,0,0,0,8.264175415039062,0,0,0,0,0,0,0,1.298080444335938,0,1.196914672851562,0,0,0,3.741165161132812,0,0,0,1.698280334472656,0,0,0,5.343727111816406,0,0.9868240356445312,0,0,0,0,0,0,0,0.2670822143554688,0,1.188301086425781,0,0,0,0,0,0,0,0,-40.50763702392578,0,0,0,0,1.208473205566406,0,1.724922180175781,0,0,0,2.785575866699219,0,0,0,0,2.932502746582031,0,1.444717407226562,0,0,0,0,0,6.88055419921875,0,0,0,0,0,0,12.05540466308594,0,0,0,0,0,0,11.48611450195312,0,0,0,0,0,0,-38.59671020507812,0,10.04531860351562,0,0,0,0,0,9.440147399902344,0,8.191963195800781,0,7.324958801269531,0,0,0,0,0,3.272369384765625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3022918701171875,0,0,-31.66399383544922,0,0,0,0,0,2.806930541992188,0,0,0,6.489364624023438,0,0,0,0,0,0,13.15643310546875,0,0,0,5.412261962890625,0,0,1.79034423828125,0,0,0,0,0,0,0,-30.74103546142578,0,0,0,7.774131774902344,0,0,0,0,0,0,0,6.882926940917969,0,6.363204956054688,0,9.784332275390625,0,0,0,0,0,0,0,-35.37924957275391,0,0,0,1.363182067871094,0,0,0,0,0,9.804344177246094,0,0,0,0,0,0,7.391258239746094,0,0,0,0,0,0,0,0,9.543342590332031,0,0,0,0,0,0,0,6.461326599121094,0,-34.22925567626953,0,0,0,0,0,0,0,0,0,0,0,0,7.258773803710938,0,5.573562622070312,0,0,0,0,4.104293823242188,0,0,0,0,0,0,7.357208251953125,0,0,0,0,10.51041412353516,0,-33.48451995849609,0,0,0,0,0,0,8.044944763183594,0,0,0,0,0,0,10.75192260742188,0,7.583320617675781,0,0,0,0,0,0,0,0,8.182106018066406,0,0,0,0,0,0,-34.14267730712891,0,1.587745666503906,0,0,0,0,0,9.318504333496094,0,7.066635131835938,0,0,0,0,0,0,0,9.018867492675781,0,7.7093505859375,0,-31.90238189697266,0,0,0,0,0,0,7.261566162109375,0,0,0,0,0,0,6.587120056152344,0,0,0,2.42291259765625,0,9.65673828125,0,0,0,6.525588989257812,0,0,-30.74648284912109,0,0,0,0,0,0,10.78488159179688,0,0,0,0,0,0,6.798835754394531,0,0,0,0,0,0,0,4.833381652832031,0,0,0,0,0,0,0,0,0,0,0,0.1626739501953125,0,0,0,0,0,0,0,0,0,0.7001419067382812,0,0,0,0,0,0,0,0,0,0,0,3.779403686523438,0,0,0,0,0,0,0,2.226715087890625,0,-33.66664886474609,0,0,0,3.348159790039062,0,0,0,0,0,0,0,0,0,0,0,1.143547058105469,0,0,0,5.14117431640625,0,3.068389892578125,0,2.276618957519531,0,0,0,0,0,0,0,0,0,0,0,6.107612609863281,0,0,0,4.168678283691406,0,0,0,0,0,0,1.384994506835938,0,0,0,0,0,0,0,0,0,0,0,5.875686645507812,0,2.631980895996094,0,0,0,-31.53572845458984,0,0,0,0,0,0,0,0,0,0,0,1.752647399902344,0,4.425125122070312,0,4.248794555664062,0,0,0,0,0,0,5.272171020507812,0,0,0,0,0,0,7.119270324707031,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.712051391601562,0,0,0,0,0,0,0,0,-28.98636627197266,0,0,0,0,0,0,10.80795288085938,0,7.594032287597656,0,0,0,0,0,0,0,0,8.140739440917969,0,0,0,1.567657470703125,0,0,0,-26.40473175048828,0,0,0,0,0,0,0,0.9571609497070312,0,3.12542724609375,0,0,0,0,0,0,0,0,0,0,8.7288818359375,0,0,0,0,0,0,7.523727416992188,0,0,0,0,0,0,5.566253662109375,0,0,0,-28.67273712158203,0,11.19567108154297,0,0,0,0,0,0,6.794662475585938,0,0,0,0,0,0,0,9.338661193847656,0,0,0,0,0,0,-10.80393218994141,0,0,-16.64090728759766,0,0,0,0,8.126129150390625,0,0,0,0,0,0,0,0,0,8.512588500976562,0,0,0,0,0,0,0,7.498634338378906,0,0,0,0,0,0,-9.757888793945312,0,0,0,0,0,0,0,-8.149169921875,0,0,0,0,0,0,0,0,0,0,9.80078125,0,0,0,0,0,0,9.123542785644531,0,0,0,0,0,0,0,1.187492370605469,0,0,0,0,0,-14.18494415283203,0,0,0,0,0,0,0,0,-5.395065307617188,0,0,0,0,0,0,0,9.903205871582031,0,7.164405822753906,0,0,0,0,0,0,0,6.343986511230469,0,0,0,0,0,0,0,-24.04323577880859,0,0,0,0,0,0,0,0,5.373634338378906,0,0,0,0,4.819297790527344,0,0,0,0,0,0,8.600204467773438,0,0,5.249946594238281,0,0,0,0,0,0,0,-40.91407775878906,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.204429626464844,0,0,0,0,0,9.369483947753906,0,0,0,0,0,0,0,7.227249145507812,0,0,0,0,0,0,5.043289184570312,0,0,0,0,0,0.640625,0,0.9312057495117188,0,0,0,3.780410766601562,0,0,1.814903259277344,0,1.250968933105469,0,0,0,3.650535583496094,0,0,-40.75898742675781,0,0.9715728759765625,0,0,0,0.5740127563476562,0,0,0,0,0,0,0,5.026268005371094,0,0.9755325317382812,0,0,0,0,0,6.052597045898438,0,0,0,0,0.7372894287109375,0,1.031364440917969,0,0,0,4.689735412597656,0,6.968345642089844,0,12.94301605224609,0,-33.74429321289062,0,8.205047607421875,0,0,0,0,0,0,0,0,0,8.298271179199219,0,9.218292236328125,0,7.101844787597656,0,-34.51824951171875,0,0.552703857421875,0,0,0,3.272369384765625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.465583801269531,0,0,0,0,0,0,0.99310302734375,0,0,0,2.806930541992188,0,0,0,6.723297119140625,0,0,0,0,0,0,13.28464508056641,0,-36.02333068847656,0,0,0,0,0,0,5.149276733398438,0,9.407440185546875,0,0,0,0,0,0,0,0,8.699363708496094,0,0,0,0,0,0,0,0,0,0,10.42890930175781,-34.29397583007812,0,9.74102783203125,0,0,0,8.040878295898438,0,0,0,0,1.454818725585938,0,0,0,0,0,0,8.580757141113281,0,0,0,0,0,0,7.139053344726562,0,0,0,0,0,0,-33.73191070556641,0,7.834060668945312,0,0,0,0,0,0,0,7.488510131835938,0,0,0,0,0,0,0,5.060432434082031,0,0,0,0,0,0,0,5.481300354003906,0,9.673210144042969,0,0,0,0,0,0,0,-30.30943298339844,0,0,0,0,0,6.12347412109375,0,0,0,0,0,0,11.61753082275391,0,0,0,0,0,0,7.121658325195312,0,0,0,0,0,0,0,0,0,0,3.728912353515625,0,0,0,0,0,-21.10057830810547,0,0,0,0,0,0,0,0,0,0,0,-2.895858764648438,0,5.57147216796875,0,0,0,0,0,0,0,10.29910278320312,0,7.348548889160156,0,2.496200561523438,0,0,0,0,0,0,-33.63153076171875,0,0,0,9.277633666992188,0,0,0,0,0,7.238868713378906,0,9.329185485839844,0,0,0,0,7.733299255371094,0,0,0,-34.16349029541016,0,0,0,0,0,0,0,0,0.7630844116210938,0,0,0,0,0,0,0,0,0,0,0,5.811241149902344,0,0,0,4.794525146484375,0,0,0,0,0,0,0,0,0,0,0,4.950920104980469,0,0.8195037841796875,0,3.394828796386719,0,0,0,0,0,0,2.758865356445312,0,0,0,0,0,0,0,0,0,0,0,4.557525634765625,0,0,0,0,0,0,0,1.388969421386719,0,4.289573669433594,0,0,0,0,0,0,0,0,0,0,0,-27.76393890380859,0,0,0,0,0,0.02596282958984375,0,3.703529357910156,0,0,1.922119140625,0,0,0,0,0,0,0,0,0,0,0,3.948989868164062,0,0,0,0,0,0,0,2.308052062988281,0,3.59033203125,0,0,0,0,0,0,4.90155029296875,0,0,0,0,0,0,8.034889221191406,0,0,0,0,0,0,0,0,-26.85307312011719,0,0,0,8.745010375976562,0,0,0,0,0,0,9.940681457519531,0,0,0,0,0,7.847213745117188,0,0,0,0,0,0,0,0,-26.775146484375,0,3.611625671386719,6.861679077148438,0,0,0,0,0,0,0,7.835258483886719,0,0,0,0,0,0,0,0,0,8.396949768066406,0,-26.40352630615234,0,0,0,0,0,0,8.008560180664062,0,3.5850830078125,0,0,0,7.098678588867188,0,0,0,0,0,0,8.116241455078125,0,0,-25.53118133544922,0,0,0,0,0,0,8.150901794433594,0,0,0,0,0,0,0,0,0,12.61460113525391,0,-23.57195281982422,0,0,0,0,0,0,7.301612854003906,0,10.44283294677734,0,0,0,0,0,0,2.543617248535156,0,0,0,0,0,0,0,7.554481506347656,0,-24.85872650146484,0,0,0,0,0,5.972076416015625,0,11.27433776855469,0,0,0,0,0,0,7.038734436035156,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-26.33045959472656,0,0,0,0,0,0,0,0,0,0,0,2.540840148925781,0,8.528251647949219,0,0,0,0,9.833328247070312,0,0,0,0,0,0,0,0,6.49420166015625,0,0,-21.96724700927734,7.722541809082031,0,0,0,0,0,0,7.481590270996094,0,0,0,0,0.95635986328125,0,0,0,1.643363952636719,0,3.083595275878906,0,0,0,0,0,0,-25.57263946533203,0,0.00388336181640625,0,0,0,0,0,1.3482666015625,0,2.192024230957031,0,0,0,2.759567260742188,0,0,0,1.630546569824219,0,3.426315307617188,0,0,1.420890808105469,0,1.714553833007812,0,0,0,3.854721069335938,0,0,0,0,0,0,1.537628173828125,0,1.674041748046875,0,0,0,4.854248046875],"filename":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/HelperFunction.R","/HelperFunction.R",null,null,"/HelperFunction.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,"/HelperFunction.R",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"<expr>","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/HelperFunction.R","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null]},"interval":10,"files":[{"filename":"<expr>","content":"pv <- profvis({\n\n## empty containers\nBoot.Est <- matrix(NA, nrow=nrow(grid), ncol=264)\n\n## parametric bootstrap\nload(\"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/simData/imputed1/n500/sim1.rds\")\nX_sim = data.frame(dplyr::select(data, c(age, pain_bq, expectationb, ChronicPainb)))\n\nfor(i in 1:nboot_B){\n  \n  data.new <- pboot(data=data, X_sim=X_sim, sim.size=500, seed=NULL)\n  X.new <- data.frame(dplyr::select(data.new, c(age, pain_bq, expectationb, ChronicPainb)))\n  topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1)\n  oral_vals    <- fit_one(data=data.new, X=X.new, trt_val=0)\n  Boot.Est[which(grid$b==i&grid$c==1), ] <- c(topical_vals, oral_vals)\n  \n  for(j in 1:nboot_C){\n    \n    data.new2 <- pboot(data=data.new, X_sim=X.new, sim.size=500, seed=NULL)\n    X.new2 <- data.frame(dplyr::select(data.new2, c(age, pain_bq, expectationb, ChronicPainb)))\n    ## inner estimator\n    temp_topical <- fit_one(data=data.new2, X=X.new2, trt_val=1)\n    temp_oral <- fit_one(data=data.new2, X=X.new2, trt_val=0)\n    Boot.Est[which(grid$b==i&grid$c==j), 133:264] <- c(temp_topical, temp_oral)\n    \n  }\n  \n  print(i)\n  \n}\n\n})\n","normpath":"<expr>"},{"filename":"/HelperFunction.R","content":"gam.variables <- function(data){\n  sapply(1:ncol(data), function(i){\n    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste(\"s\", \"(\",names(data)[i], \")\", sep=\"\")}\n    else{names(data[i]) }\n  })\n}\n\nsingle.index.variables <- function(data){\n  sapply(1:ncol(data), function(i){\n    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste(\"ns\", \"(\",names(data[i]), \")\", sep=\"\")}\n    else{names(data[i]) }\n  })\n}\n\neq <- function(theta,z) {\n  mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)\n}\n\n## Induced estimates\ncounterfactual <- function(Y, Y0, M, R, X, t, trt, gamma, est){\n  \n  result <- vector(length=length(gamma))\n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model and \n  index.var.Y <- single.index.variables(X)\n  X_adjust <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(t==trt & R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(t==trt & R==1), ]\n  X_R0 <- X[which(R==0), ]\n  X_R1 <- X[which(R==1), ]\n  Y_t_R0 <- Y[which(t==trt & R==0)]\n  Y_t_R1 <- Y[which(t==trt & R==1)]\n  M_t_R0 <- M[which(t==trt & R==0)]\n  M_t_R1 <- M[which(t==trt & R==1)]\n  trt.ind_R0 <- trt.ind[which(R==0)]\n  trt.ind_R1 <- trt.ind[which(R==1)]\n  \n  ## fit outcome model\n  requireNamespace('MAVE', quietly = TRUE)\n  SDR_t_R0 <- coef(MAVE::mave.compute(X_adjust_scale_t_R0[which(M_t_R0==1), ], Y_t_R0[which(M_t_R0==1)], max.dim = 1), 1)\n  # SDR_t_R0 <- cumuSIR(X=X_adjust_scale_t_R0[which(M_t_R0==1), ], Y=Y_t_R0[which(M_t_R0==1)])\n  fit_t_R0_h <- SIDRnew_fixed_bandwidth(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                        Y = Y_t_R0[which(M_t_R0==1)],\n                                        initial = SDR_t_R0,\n                                        kernel = \"K2_Biweight\",\n                                        method = \"optim\",\n                                        ids = 1:length(Y_t_R0[which(M_t_R0==1)]))\n  SDR_t_R1 <- coef(MAVE::mave.compute(X_adjust_scale_t_R1[which(M_t_R1==1), ], Y_t_R1[which(M_t_R1==1)], max.dim = 1), 1)\n  # SDR_t_R1 <- cumuSIR(X=X_adjust_scale_t_R1[which(M_t_R1==1), ], Y=Y_t_R1[which(M_t_R1==1)])\n  fit_t_R1_h <- SIDRnew_fixed_bandwidth(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                        Y = Y_t_R1[which(M_t_R1==1)],\n                                        initial = SDR_t_R1,\n                                        kernel = \"K2_Biweight\",\n                                        method = \"optim\",\n                                        ids = 1:length(Y_t_R1[which(M_t_R1==1)]))\n  \n  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)\n  X_beta_t_R0 <- as.vector(X_adjust_scale %*% fit_t_R0_h$coef)\n  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)\n  X_beta_t_R1 <- as.vector(X_adjust_scale %*% fit_t_R1_h$coef)\n  \n  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    \n  ny_t_R0 = length(y_t_R0) \n  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], \n                     xb=X_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                     kernel = \"K2_Biweight\")\n  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    \n  ny_t_R1 = length(y_t_R1) \n  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], \n                     xb=X_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                     kernel = \"K2_Biweight\")\n  \n  i1 = which(apply(F_X_t_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X_beta_t_R0[i1], X_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X_beta_t_R1[i1], X_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]\n  \n  dF_X_t_R0 <- F_X_t_R0-c(0, F_X_t_R0[,-ny_t_R0])\n  dF_X_t_R1 <- F_X_t_R1-c(0, F_X_t_R1[,-ny_t_R1])\n  \n  ## conditional expectation of Y given R=0, T=t and X\n  mu_X_t_R0 <- c(dF_X_t_R0 %*% (y_t_R0+c(0, y_t_R0[-ny_t_R0]))/2)\n  ## conditional expectation of Y given R=1, T=t and X\n  mu_X_t_R1 <- c(dF_X_t_R1 %*% (y_t_R1+c(0, y_t_R1[-ny_t_R1]))/2)\n  \n  ## fit g model\n  g.fit <- mgcv::gam(as.formula(paste(\"R ~\", gam.var)), data=cbind(R, X), family=binomial) \n  g1 <- predict(g.fit, newdata=X, type=\"response\") \n  g0 <- 1-g1\n  \n  ## fit treatment assignment model\n  t_R0.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  t_R1.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R1 ~\", gam.var)), data=X_R1, family=binomial) ## treatment model\n  pi_R0 <- predict(t_R0.fit, newdata=X, type=\"response\") \n  pi_R1 <- predict(t_R1.fit, newdata=X, type=\"response\")\n\n  ## empirical mean\n  prop_t <- sum(trt.ind)/n\n  mean_Y0_t0 <- mean(Y0[which(t!=trt)])\n  mean_Y0_t <- mean(Y0[which(t==trt)])\n  \n  result_t0 <- (est-mean(mu_X_t_R0*pi_R0*g0+mu_X_t_R1*pi_R1*g1))/(1-prop_t)-mean_Y0_t0\n  result_t <- mean(mu_X_t_R0*pi_R0*g0+mu_X_t_R1*pi_R1*g1)/prop_t-mean_Y0_t\n  return(c(result_t0, result_t))\n  \n}\n\n\n## truth: single index or beta regression\ntruth <- function(Y, Y0, M, R, t, X, trt, gamma){\n  \n  truth_t <- c()\n  truth_t_R1 <- c()\n  truth_t_R0 <- c()\n  \n  truth_t_diff <- c()\n  truth_t_R1_diff <- c()\n  truth_t_R0_diff <- c()\n  \n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model and \n  index.var.Y <- single.index.variables(X)\n  \n  X_R0 <- X[which(R==0), ]\n  X_R1 <- X[which(R==1), ]\n  Y_t_R0 <- Y[which(t==trt & R==0)]\n  Y_t_R1 <- Y[which(t==trt & R==1)]\n  M_t_R0 <- M[which(t==trt & R==0)]\n  M_t_R1 <- M[which(t==trt & R==1)]\n  trt.ind_R0 <- trt.ind[which(R==0)]\n  trt.ind_R1 <- trt.ind[which(R==1)]\n  \n  ## fit outcome model\n    # rescale outcome to (0,1)\n    eps <- 1e-6\n    Y01 <- Y/100\n    # nudge any 0/1 slightly inside (only needed if any exact 0 or 100)\n    Y01[Y01 <= 0] <- eps\n    Y01[Y01 >= 1] <- 1 - eps\n    \n    Y_t_R0.fit <- betareg(as.formula(paste(\"Y01 ~\", paste(index.var.Y, collapse = \"+\"))), data=cbind(Y01, X)[which(t==trt & R==0 & M==1), ])\n    Y_t_R1.fit <- betareg(as.formula(paste(\"Y01 ~\", paste(index.var.Y, collapse = \"+\"))), data=cbind(Y01, X)[which(t==trt & R==1 & M==1), ])\n    \n    phi_t_R0 <- Y_t_R0.fit$coefficients$precision\n    phi_t_R1 <- Y_t_R1.fit$coefficients$precision\n    \n    mu_X_t_R0 <- 100*predict(Y_t_R0.fit, newdata=X, type=\"response\")\n    mu_X_t_R1 <- 100*predict(Y_t_R1.fit, newdata=X, type=\"response\")\n  \n  ## fit g model\n  g.fit <- mgcv::gam(as.formula(paste(\"R ~\", gam.var)), data=cbind(R, X), family=binomial) \n  g1 <- predict(g.fit, newdata=X, type=\"response\") \n  g0 <- 1-g1\n  \n  ## fit treatment assignment model\n  t_R0.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  pi_R0 <- predict(t_R0.fit, newdata=X, type=\"response\") \n\n  for(g in 1:length(gamma)){\n      \n      mu_Yexp_X_t_R0 <- mapply(function(a,b) {\n        integrate(function(y) 100*y * exp(gamma[g]*pnorm((100*y-60)/25)) * dbeta(y, shape1 = a, shape2 = b), lower = 0, upper = 1)$value\n      }, mu_X_t_R0/100*phi_t_R0, (1-mu_X_t_R0/100)*phi_t_R0)\n      \n      mu_exp_X_t_R0 <- mapply(function(a,b) {\n        integrate(function(y) exp(gamma[g]*pnorm((100*y-60)/25)) * dbeta(y, shape1 = a, shape2 = b), lower = 0, upper = 1)$value\n      }, mu_X_t_R0/100*phi_t_R0, (1-mu_X_t_R0/100)*phi_t_R0)\n      \n\n      truth_t <- c(truth_t, mean(g1*mu_X_t_R1+g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0))))\n      truth_t_R0 <- c(truth_t_R0, mean(g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))/mean(g0))\n      truth_t_diff <- c(truth_t_diff, mean(g1*mu_X_t_R1+g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))-mean(Y0))\n      truth_t_R0_diff <- c(truth_t_R0_diff, mean(g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))/mean(g0)-mean(Y0[which(R==0)]))\n      \n  }\n  \n  truth_t_R1 <- mean(mu_X_t_R1*g1)/mean(g1)\n  truth_t_R1_diff <- mean(mu_X_t_R1*g1)/mean(g1)-mean(Y0[which(R==1)])\n  \n  return(list(t=truth_t, t_R0=truth_t_R0, t_R1=truth_t_R1, \n              t_diff=truth_t_diff, t_R0_diff=truth_t_R0_diff, \n              t_R1_diff=truth_t_R1_diff))\n  \n}\n\n## parametric bootstrap: simulate new data based on models from original data\npboot <- function(data, X_sim, sim.size, seed){\n  \n  ## fit models\n  X_with_t <- cbind(as.factor(data$t), X_sim)\n  colnames(X_with_t)[1] <- \"treatment\"\n  gam.var <- paste(gam.variables(X_sim), collapse = \"+\") ## gam variables for treatment assignment model\n  gam.var.M <- paste(gam.variables(X_with_t), collapse = \"+\") ## gam variables for missing data model\n  index.var.Y <- paste(single.index.variables(X_sim), collapse = \"+\")\n  X_adjust <- model.matrix(as.formula(paste(\"~\", index.var.Y)), data = X_sim)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]\n  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]\n  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]\n  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]\n  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]\n  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]\n  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]\n  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]\n  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]\n  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]\n  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]\n  \n  X_R0 <- X_sim[which(data$R==0), ]\n  t_R0 <- data$t[which(data$R==0)]\n  \n  X_with_t_R0 <- X_with_t[which(data$R==0), ]\n  X_with_t_R1 <- X_with_t[which(data$R==1), ]\n  M_R0 <- data$M[which(data$R==0)]\n  M_R1 <- data$M[which(data$R==1)]\n  \n  g.fit <- mgcv::gam(as.formula(paste(\"data$R ~\", gam.var)), data=X_sim, family=binomial) \n  t_R0.fit <- mgcv::gam(as.formula(paste(\"t_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  M_R0.fit <- mgcv::gam(as.formula(paste(\"M_R0 ~\", gam.var.M)), data=X_with_t_R0, family=binomial) ## missing data model\n  M_R1.fit <- mgcv::gam(as.formula(paste(\"M_R1 ~\", gam.var.M)), data=X_with_t_R1, family=binomial) ## missing data model\n  \n  fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                              Y = Y_t_R1[which(M_t_R1==1)],\n                                                              ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R1_h, \"try-error\")) {\n    fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                                Y = Y_t_R1[which(M_t_R1==1)],\n                                                                ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                              Y = Y_t_R0[which(M_t_R0==1)],\n                                                              ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R0_h, \"try-error\")) {\n    fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                                Y = Y_t_R0[which(M_t_R0==1)],\n                                                                ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                               Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                               ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R1_h, \"try-error\")) {\n    fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                                 Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                                 ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                               Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                               ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R0_h, \"try-error\")) {\n    fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                                 Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                                 ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)\n  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)\n  X_t0_R0_beta_t0_R0 <- as.vector(X_adjust_scale_t0_R0[which(M_t0_R0==1), ] %*% fit_t0_R0_h$coef)\n  X_t0_R1_beta_t0_R1 <- as.vector(X_adjust_scale_t0_R1[which(M_t0_R1==1), ] %*% fit_t0_R1_h$coef)\n  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    \n  ny_t_R0 = length(y_t_R0) \n  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    \n  ny_t_R1 = length(y_t_R1) \n  y_t0_R0 = sort(unique(Y_t0_R0[which(M_t0_R0==1)]))    \n  ny_t0_R0 = length(y_t0_R0) \n  y_t0_R1 = sort(unique(Y_t0_R1[which(M_t0_R1==1)]))    \n  ny_t0_R1 = length(y_t0_R1) \n  \n  ## simulate data\n  if(!is.null(seed)){set.seed(seed)}\n  boot.indices <- sample(1:sim.size, size=sim.size, replace = T)\n  X.new <- X_sim[boot.indices,]\n  X_adjust_scale.new <- X_adjust_scale[boot.indices, ]\n  ## new R\n  prob.R <- predict(g.fit, newdata=X.new, type=\"response\") \n  R.new <- rbinom(n=sim.size, size=1, prob=prob.R)\n  ## new T\n  T.new_R1 <- rbinom(n=sim.size,size=1,prob=0.5)\n  prob.T_R0 <- predict(t_R0.fit, newdata=X.new, type=\"response\")\n  T.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.T_R0)\n  T.new <- T.new_R1*R.new+T.new_R0*(1-R.new)\n  \n  ## new Y\n  X.new_beta_t_R0 <- as.vector(X_adjust_scale.new %*% fit_t_R0_h$coef)\n  X.new_beta_t_R1 <- as.vector(X_adjust_scale.new %*% fit_t_R1_h$coef)\n  X.new_beta_t0_R0 <- as.vector(X_adjust_scale.new %*% fit_t0_R0_h$coef)\n  X.new_beta_t0_R1 <- as.vector(X_adjust_scale.new %*% fit_t0_R1_h$coef)\n  \n  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], \n                     xb=X.new_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], \n                     xb=X.new_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t0_R0 <- NW_new(Xb=X_t0_R0_beta_t0_R0, Y=Y_t0_R0[which(M_t0_R0==1)], \n                      xb=X.new_beta_t0_R0, y=y_t0_R0, h=fit_t0_R0_h$bandwidth, \n                      kernel = \"dnorm\")\n  F_X_t0_R1 <- NW_new(Xb=X_t0_R1_beta_t0_R1, Y=Y_t0_R1[which(M_t0_R1==1)], \n                      xb=X.new_beta_t0_R1, y=y_t0_R1, h=fit_t0_R1_h$bandwidth, \n                      kernel = \"dnorm\")\n  \n  i1 = which(apply(F_X_t_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R0[i1], X.new_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R1[i1], X.new_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R0[i1], X.new_beta_t0_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R0[i1, ] <- F_X_t0_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R1[i1], X.new_beta_t0_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R1[i1, ] <- F_X_t0_R1[-i1, ][i1.closest, ]\n  \n  Y.new_t_R0 <- apply(F_X_t_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t_R1 <- apply(F_X_t_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R1[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R0 <- apply(F_X_t0_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R1 <- apply(F_X_t0_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R1[min(which(ecdf<=x))]\n  })\n  Y.new <- Y.new_t_R0*T.new*(1-R.new)+Y.new_t_R1*T.new*R.new+\n    Y.new_t0_R0*(1-T.new)*(1-R.new)+Y.new_t0_R1*(1-T.new)*R.new\n  \n  ## new M\n  X_with_t.new <- cbind(T.new, X.new)\n  colnames(X_with_t.new)[1] <- \"treatment\"\n  prob.M_R0 <- predict(M_R0.fit, newdata=X_with_t.new, type=\"response\")\n  prob.M_R1 <- predict(M_R1.fit, newdata=X_with_t.new, type=\"response\")\n  M.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.M_R0)\n  M.new_R1 <- rbinom(n=sim.size,size=1,prob=prob.M_R1)\n  M.new <- M.new_R0*(1-R.new)+M.new_R1*R.new\n  \n  Y.new[M.new==0] <- NA\n  \n  data.new <- data.frame(cbind(Y.new, M.new, R.new, T.new, X.new))\n  colnames(data.new) <- c(\"Y\", \"M\", \"R\", \"t\", colnames(X.new))  \n  \n  return(data.new)\n  \n}\n\n## run algorithm\nfit_one <- function(data, X, trt_val) {\n  # try mave first\n  out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, \n                     X=X,\n                     t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,\n                     IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel=\"dnorm\",\n                     method=\"optim\", single_index_method=\"norm1coef\",\n                     use_mave=TRUE, seed=NULL),\n             silent = TRUE)\n  \n  if (inherits(out, \"try-error\")) {\n    # fallback cumSIR\n    out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, \n                       X=X,\n                       t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,\n                       IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel=\"dnorm\",\n                       method=\"optim\", single_index_method=\"norm1coef\",\n                       use_mave=FALSE, seed=NULL),\n               silent = TRUE)\n  }\n  \n  if (inherits(out, \"try-error\") || is.null(out)) {\n    return(rep(NA_real_, 6*length(seq(-5, 5, by=1))))\n  }else{\n    return(c(out$est_trunc, out$est_trunc_R1, out$est_trunc_R0, \n             out$var_trunc, out$var_trunc_R1, out$var_trunc_R0))\n  }\n}\n\n\n\n\n\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/HelperFunction.R"},{"filename":"/SensIAT_sim_outcome_modeler_mave.R","content":"# Single Index Model using MAVE and Optimizing Bandwidth.\n#\n# Single index model estimation using minimum average variance estimation (MAVE).\n# A direction is estimated using MAVE, and then the bandwidth is selected by\n# minimization of the cross-validated pseudo-integrated squared error.\n# Optionally, the initial coefficients of the outcome model can be re-estimated\n# by optimization on a spherical manifold.  This option requires the\n# [ManifoldOptim][ManifoldOptim::manifold.optim] package.\n\nfit_SensIAT_single_index_norm1coef_model <-\nfunction(X, Y, ids, \n         kernel = \"K2_Biweight\",\n         mave.method = \"meanMAVE\",\n         use_mave,\n         id = ..id..,\n         bw.selection = c('ise', 'mse'),\n         bw.method = c('optim', 'grid', 'optimize'),\n         bw.range = c(0.01, 1.5),\n         reestimate.coef = 0,\n         ...\n){\n    unique_y <- sort(unique(Y))\n\n    if (kernel==\"K2_Biweight\"){\n        K <- function(x) 15/16*(1-(x)^2)^2 * (abs(x) <= 1)\n        K1<- function(x) 3/4*(1-(x)^2) * (abs(x) <= 1)\n    } else if (kernel==\"dnorm\") {\n        K <- function(x) dnorm(x,0,1)\n        K1 <- function(x) -x*dnorm(x, 0, 1)\n    } else if (kernel==\"K4_Biweight\"){\n        K <- function(x) 105/64*(1-3*((x)^2)) * (1-(x)^2)^2 * (abs(x) <= 1)\n    } else{\n        stop(\"Unknown kernel type. Please use either 'K2_Biweight', 'dnorm', or 'K4_Biweight'.\")\n    }\n\n    if(use_mave){\n      assertthat::assert_that(requireNamespace(\"MAVE\", quietly = TRUE))\n      mave_fit <- MAVE::mave.compute(X, Y, max.dim = 1, method = mave.method)\n      beta_hat <- mave_fit$dir[[1]][,1,drop=TRUE]\n    }else{\n      beta_hat <- cumuSIR(X = X, Y = Y)\n    }\n\n    bw_old <- 1\n    delta_beta = NA_real_\n    res <- NULL\n\n    Id_neq <- outer(ids, ids, \\(x,y)as.numeric(x!=y))\n    Imat <- outer(Y, unique_y, `<=`)\n    repeat{\n        Xbeta <- (X %*% beta_hat)[,]\n        sigma <- sd(Xbeta)\n        D <- outer(Xbeta, Xbeta, FUN = `-`)\n\n        bw.selection <- match.arg(bw.selection)\n        if(bw.selection == 'ise'){\n            # Use Integrated Squared Error (ISE) for bandwidth selection\n            err <- function(log_bandwidth){\n                W <- K(D/exp(log_bandwidth)) * Id_neq\n                denom <- rowSums(W)\n                Fhat <- sweep(W %*% Imat, 1, denom, \"/\")\n                Fhat[is.nan(Fhat)] <- 0\n                return (sum((Imat - Fhat)^2)/length(Fhat)^2)\n            }\n        } else if(bw.selection == 'mse'){\n            # Use Mean Squared Error (MSE) for bandwidth selection\n            err <- function(log_bandwidth){\n                W <- K(D/exp(log_bandwidth)) * Id_neq\n                denom <- rowSums(W)\n                mean_Y <- c(W %*% Y) / denom\n                return (mean((Y - mean_Y)^2, na.rm = TRUE))\n            }\n        } else {\n            stop(\"Unknown bw.selection type. Please use either 'ise' or 'mse'.\")\n        }\n\n        bw.method <- match.arg(bw.method)\n        if(bw.method == 'grid'){\n            # Use grid search for bandwidth selection\n            log_bw_seq <- log(seq(min(bw.range), max(bw.range), length.out = 100) * sigma)\n            err_values <- purrr::map_dbl(log_bw_seq, err)\n            bw_opt <- log_bw_seq[which.min(err_values)]\n            bw.details <- list(par = bw_opt,\n                           value = min(err_values),\n                           convergence = 0,\n                           message = \"Grid search completed successfully.\",\n                           bw.method = bw.method,\n                           log_bw_seq = log_bw_seq,\n                           err_values = err_values\n                           )\n        } else if(bw.method == 'optim'){\n            # Use optimization for bandwidth selection\n            initial <- log(sigma * 0.30)\n            bw.details <- optim(initial, err, method = \"L-BFGS-B\", lower = log(sigma * min(bw.range)), upper = log(sigma * max(bw.range)), ...)\n            bw.details$initial = initial\n            bw.details$bw.method = bw.method\n            bw_opt <- bw.details$par\n        } else if(bw.method == 'optimize'){\n            # Use optimize for bandwidth selection\n            result <- stats::optimize(err,\n                               interval = c(log(sigma * min(bw.range)), log(sigma * max(bw.range))),\n                               ...)\n            bw_opt <- result$minimum\n            bw.details <- list(minimum = result$minimum,\n                               value = result$objective,\n                               bw.method  = bw.method,\n                               interval = c(log(sigma * 0.05), log(sigma * 1.5)))\n        } else{\n            stop(\"Unknown bw.method type. Please use either 'optim' or 'grid'.\")\n        }\n\n\n        delta_bw = abs(bw_opt - bw_old)\n\n        if(!is.null(res) && res$fval <= bw.details$value) break\n        last.optimized = 'bandwidth'\n\n        if(reestimate.coef <= 0) break\n        reestimate.coef <- reestimate.coef - 1\n\n\n        bw_old <- bw_opt\n        rlang::check_installed(\"ManifoldOptim\")\n        requireNamespace(\"ManifoldOptim\", quietly = TRUE)\n\n        beta_hat_old <- beta_hat\n        if(bw.selection == \"ise\") {\n            objFun <- function(beta){\n                Xbeta <- (X %*% beta)[,]\n                D <- outer(Xbeta, Xbeta, FUN = `-`)\n                W <- K(D/exp(bw_opt)) * Id_neq\n                denom <- rowSums(W)\n                Fhat <- sweep(W %*% Imat, 1, denom, \"/\")\n                Fhat[is.nan(Fhat)] <- 0\n                return (sum((Imat - Fhat)^2)/length(Fhat)^2)\n            }\n        } else if(bw.selection == \"mse\") {\n            objFun <- function(beta){\n                Xbeta <- (X %*% beta)[,]\n                D <- outer(Xbeta, Xbeta, FUN = `-`)\n                W <- K1(D/exp(bw_opt)) * Id_neq\n                denom <- rowSums(W)\n                mean_Y <- c(W %*% Y) / denom\n                return (mean((Y - mean_Y)^2, na.rm = TRUE))\n            }\n        } else {\n            stop(\"Unknown bw.selection type. Please use either 'ise' or 'mse'.\")\n        }\n        mod <- Rcpp::Module(\"ManifoldOptim_module\", PACKAGE = \"ManifoldOptim\")\n        prob <- new(mod$RProblem, objFun)\n        mani.params <- ManifoldOptim::get.manifold.params(IsCheckParams = FALSE)\n        solver.params <- ManifoldOptim::get.solver.params(IsCheckParams = FALSE)\n        maniDef <- ManifoldOptim::get.sphere.defn(length(beta_hat))\n\n        res <- ManifoldOptim::manifold.optim(prob, maniDef,\n                              mani.params = mani.params,\n                              solver.params = solver.params, x0 = beta_hat)\n        if(res$fval >= bw.details$value) break\n        last.optimized = 'beta'\n\n        beta_hat <- as.vector(res$xopt)\n        delta_beta = abs(beta_hat - beta_hat_old)\n    }\n    return(\n            list(\n                coef = beta_hat,\n                bandwidth = exp(bw_opt),\n                details = list(bw.last = bw.details,\n                               bw.delta = delta_bw,\n                               bw.unscaled = bw_opt/sigma,\n                               beta.delta = delta_beta,\n                               beta.last  = res,\n                               last.optimized = last.optimized\n                               )\n            )\n    )\n}\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/SensIAT_sim_outcome_modeler_mave.R"},{"filename":"/singleindexmodelfunctions.R","content":"# single index model's function\n\n# return the initial value for beta\ncumuSIR <- function(X, Y, eps = 1e-7){\n  X <- as.matrix(X)\n  Y <- as.matrix(Y)\n  \n  number_n <- dim(X)[1]\n  number_p <- dim(X)[2]\n  \n  Y.CP <- matrix(\n    Y[rep(1:number_n, times = number_n), ]<=\n      Y[rep(1:number_n, each = number_n), ],\n    nrow = number_n, ncol = number_n\n  )\n  \n  # centralizing covariates\n  X.cs <- t(t(X)-colMeans(X))\n  \n  # calculating m(y)=\\E[X_i 1(Y_i\\leq y)]\n  m.y <- t(X.cs) %*% Y.CP/number_n\n  # calculating K=\\E[m(Y_i)m(Y_i)^T]\n  Km <- m.y %*% t(m.y)/number_n\n  \n  Bhat <- eigen(solve(var(X) + eps*diag(number_p), Km))$vectors[, 1]\n  \n  return(Bhat)\n}\n\n\n# find the optimal bandwidth, default set for kernel is \nSIDRnew_h2 <- function(X, Y,\n                       Y.CP = NULL,\n                       beta = NULL,\n                       kernel = \"K2_Biweight\",\n                       method = \"optim\",\n                       optim_method = \"BFGS\",\n                       abs.tol = 1e-4,\n                       initial_bandwidth = NULL,\n                       wi.boot = NULL, penalty=0)\n{\n  X <- as.matrix(X)\n  Y <- as.matrix(Y)\n  \n  number_n <- dim(X)[1]\n  number_p <- dim(X)[2]\n  \n  if (is.null(beta))\n  {\n    beta <- c(1, rep(0, number_p-1))\n  }else\n  {\n    beta <- as.vector(beta)\n    beta <- beta/beta[1]\n  }\n  \n  if (is.null(initial_bandwidth))\n  {\n    if (kernel==\"K2_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)\n          b <- beta\n          h <- exp(parameter)\n          xb <- c(X%*%b) \n          y <- Y\n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(xb-xb[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2+penalty*h)\n        }\n        \n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                  h = h))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K2_Biweight kernel.\")\n      }\n    }else if (kernel == \"dnorm\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) dnorm(x/h, 0, 1)\n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = h))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        # wi.boot <- as.vector(wi.boot)\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = h, w = wi.boot))^2)\n        #   return(cv)\n        # }\n        stop(\"There's no weighted version of the dnorm kernel.\")\n      }\n    }else if (kernel==\"K4_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                            h = h), 0), 1))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K4_Biweight kernel.\")\n      }\n    }\n    \n    if(method == \"nlminb\")\n    {\n      esti <- nlminb(start = 0, \n                     objective = Eij3,\n                     control = list(abs.tol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }else if (method == \"optim\")\n    {\n      # the new optimize function using optim, you can change the lower and upper\n      esti <- optim(par = 0, \n                    fn = Eij3,\n                    method = optim_method,\n                    control = list(abstol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }\n    else if (method == \"optimize\")\n    {\n      #   # esti <- nmk(par = 0, \n      #   #             fn = Eij3,\n      #   #             control = list(tol = abs.tol))\n      esti <- optimize(Eij3,\n                       interval = c(-10, 10))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$minimum),\n                      details = esti)\n    }\n    \n  }else\n  {\n    if (kernel==\"K2_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)\n          b <- beta\n          h <- exp(parameter)\n          xb <- c(X%*%b) \n          y <- Y\n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(xb-xb[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2+penalty*h)\n        }\n        \n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                  h = bandwidth))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K2_Biweight kernel.\")\n      }\n    }else if (kernel==\"dnorm\") \n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) dnorm(x/h,0,1) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        \n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = bandwidth))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        # wi.boot <- as.vector(wi.boot)\n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = bandwidth, w = wi.boot))^2)\n        #   return(cv)\n        # }\n        stop(\"There's no weighted version of the dnorm kernel.\")\n      }\n    }else if (kernel==\"K4_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                            h = bandwidth), 0), 1))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K4_Biweight kernel.\")\n      }\n    }\n    \n    if(method == \"nlminb\")\n    {\n      esti <- nlminb(start = initial_bandwidth, \n                     objective = Eij3,\n                     control = list(abs.tol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }else if (method == \"optim\")\n    {\n      # the new optimize function using optim, you can change the lower and upper\n      esti <- optim(par = initial_bandwidth, \n                    fn = Eij3,\n                    method = optim_method,\n                    control = list(abstol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }\n    else if (method == \"optimize\")\n    {\n      #   # esti <- nmk(par = initial_bandwidth, \n      #   #             fn = Eij3,\n      #   #             control = list(tol = abs.tol))\n      esti <- optimize(Eij3,\n                       interval = c(-10, 10))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$minimum),\n                      details = esti)\n      \n    }\n  }\n  \n  return(results)\n}\n\n\n# return the prediction using \"K2_Biweight\" kernel\nNW_new <- function(Xb, Y, xb, y, h, kernel = \"K2_Biweight\"){\n  \n  if(kernel == \"dnorm\"){\n    K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian \n  } else if(kernel == \"K2_Biweight\"){\n    K <- function(x, h){15/16*(1-(x/h)^2)^2 * (abs(x) <= h)} # K2_Biweight\n  } else if(kernel==\"K4_Biweight\"){\n    K <- function(x, h){105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) }# K4_Biweight\n  }\n  \n  Kxb <- sapply(xb, function(x, Xb) K(Xb-x, h), Xb=Xb)\n  \n  Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)\n  \n  denom <- colSums(Kxb)\n  \n  fyxb <- (denom!=0)*crossprod(Kxb, Ylty)/(denom + (denom==0))\n  \n  return(fyxb)\n  \n}\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/singleindexmodelfunctions.R"},{"filename":"/est_s_t_y.R","content":"\nest_psi <- function(Y, M, R, X, t, trt, gamma, fold, seed, IF_output, \n                    simple_trunc, quant, kernel, method, single_index_method, \n                    use_mave=TRUE){\n  \n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  \n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  ## set up covariates list and design matrix for modeling\n  X_with_T <- cbind(as.factor(t), X)\n  colnames(X_with_T)[1] <- \"treatment\"\n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model\n  gam.var.M <- paste(gam.variables(X_with_T), collapse = \"+\") ## gam variables for missing data model\n  index.var.Y <- single.index.variables(X)\n  X_adjust <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  ## empty containers\n  IF <- vector(mode = \"list\", length = length(gamma))\n  IF_R1 <- vector(mode = \"list\", length = length(gamma))\n  IF_R0 <- vector(mode = \"list\", length = length(gamma))\n  est_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R1_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R0_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R1_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R0_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  IF_diff <- vector(mode = \"list\", length = length(gamma))\n  IF_R1_diff <- vector(mode = \"list\", length = length(gamma))\n  IF_R0_diff <- vector(mode = \"list\", length = length(gamma))\n  est_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R1_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R0_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R1_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R0_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))  \n  vector_R1 <- vector_R0 <- c()\n  id_list <- c()\n  if(!simple_trunc){\n    IF_trunc <- vector(mode = \"list\", length = length(gamma))\n    IF_R1_trunc <- vector(mode = \"list\", length = length(gamma))\n    IF_R0_trunc <- vector(mode = \"list\", length = length(gamma))\n    est_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R1_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R0_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R1_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R0_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    IF_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    IF_R1_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    IF_R0_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    est_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R1_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R0_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R1_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R0_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  \n  }\n  \n  ## cross fit\n  if(!is.null(seed)){set.seed(seed)}\n  indx <- sample(1:n)\n  fold_list <- split(1:n, indx %% fold)\n  fold_nk_list <- vector(length=fold)\n  \n  ## containers\n  pain_bq_reordered <- c()\n  pain_bq_reordered_R1 <- c()\n  pain_bq_reordered_R0 <- c()\n  pi_R0_l <- c()\n  pi_R1_l <- c()\n  eta_t_R0_l <- c()\n  eta_t0_R0_l <- c()\n  eta_T_R1_l <- c()\n  fold_index_pi_R0_l <- c()\n  fold_index_pi_R1_l <- c()\n  fold_index_eta_t_R0_l <- c()\n  fold_index_eta_t0_R0_l <- c()\n  fold_index_eta_T_R1_l <- c()\n  fold_index_pain <- c()\n  \n  ## compute weights across folds\n  for (k in 1:fold){\n    ## out-of-fold data\n    if(fold>1){\n      out_fold_id_list <- setdiff(1:n, fold_list[[k]])\n    }else{\n      out_fold_id_list <- 1:n\n    }\n    M_out_fold <- M[out_fold_id_list]\n    R_out_fold <- R[out_fold_id_list]\n    t_out_fold <- t[out_fold_id_list]\n    trt.ind_out_fold <- trt.ind[out_fold_id_list]\n    X_out_fold <- X[out_fold_id_list, ]\n    X_with_T_out_fold <- X_with_T[out_fold_id_list, ]\n    \n    trt.ind_out_fold_R0 <- trt.ind_out_fold[which(R_out_fold==0)]\n    X_out_fold_R0 <- X_out_fold[which(R_out_fold==0), ]\n    trt.ind_out_fold_R1 <- trt.ind_out_fold[which(R_out_fold==1)]\n    X_out_fold_R1 <- X_out_fold[which(R_out_fold==1), ]\n    \n    M_out_fold_R0 <- M_out_fold[which(R_out_fold==0)]\n    X_with_T_out_fold_R0 <- X_with_T_out_fold[which(R_out_fold==0), ]\n    M_out_fold_R1 <- M_out_fold[which(R_out_fold==1)]\n    X_with_T_out_fold_R1 <- X_with_T_out_fold[which(R_out_fold==1), ]\n    \n    ## in-fold data\n    nk_in_fold <- length(fold_list[[k]])\n    fold_nk_list[k] <- nk_in_fold\n    R_in_fold <- R[fold_list[[k]]]\n    t_in_fold <- t[fold_list[[k]]]\n    X_in_fold <- X[fold_list[[k]], ]\n    X_with_T_in_fold <- X_with_T[fold_list[[k]], ]\n    \n    X_in_fold_t_R0 <- X_in_fold[which(t_in_fold==trt & R_in_fold==0), ]\n    X_in_fold_t0_R0 <- X_in_fold[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_in_fold_R1 <- X_in_fold[which(R_in_fold==1), ]\n    \n    X_with_T_in_fold_t_R0 <- X_with_T_in_fold[which(t_in_fold==trt & R_in_fold==0), ]\n    X_with_T_in_fold_t0_R0 <- X_with_T_in_fold[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_with_T_in_fold_R1 <- X_with_T_in_fold[which(R_in_fold==1), ]\n    \n    ## fit models\n    t_R0.fit <- mgcv::gam(as.formula(paste(\"trt.ind_out_fold_R0 ~\", gam.var)), data=X_out_fold_R0, family=binomial) ## treatment model\n    t_R1.fit <- mgcv::gam(as.formula(paste(\"trt.ind_out_fold_R1 ~\", gam.var)), data=X_out_fold_R1, family=binomial) ## treatment model\n    \n    M_R0.fit <- mgcv::gam(as.formula(paste(\"M_out_fold_R0 ~\", gam.var.M)), data=X_with_T_out_fold_R0, family=binomial) ## missing data model\n    M_R1.fit <- mgcv::gam(as.formula(paste(\"M_out_fold_R1 ~\", gam.var.M)), data=X_with_T_out_fold_R1, family=binomial) ## missing data model\n    \n    prop.R1 <- mean(R_in_fold)\n    \n    ## get predictions for pi\n    pi_R0 <- predict(t_R0.fit, newdata=X_in_fold_t_R0, type=\"response\") \n    pi_R1 <- predict(t_R1.fit, newdata=X_in_fold_R1, type=\"response\")\n    pi_R0_l <- c(pi_R0_l, pi_R0)\n    pi_R1_l <- c(pi_R1_l, pi_R1)\n    fold_index_pi_R0_l <- c(fold_index_pi_R0_l, rep(k, length(pi_R0)))\n    fold_index_pi_R1_l <- c(fold_index_pi_R1_l, rep(k, length(pi_R1)))\n    \n    ## get predictions for eta\n    eta_t_R0 <- predict(M_R0.fit, newdata=mutate(X_with_T_in_fold_t_R0, treatment=trt), type=\"response\")\n    eta_t0_R0 <- predict(M_R0.fit, newdata=mutate(X_with_T_in_fold_t0_R0, treatment=1-trt), type=\"response\")\n    eta_T_R1 <- predict(M_R1.fit, newdata=X_with_T_in_fold_R1, type=\"response\")\n    eta_t_R0_l <- c(eta_t_R0_l, eta_t_R0)\n    eta_t0_R0_l <- c(eta_t0_R0_l, eta_t0_R0)\n    eta_T_R1_l <- c(eta_T_R1_l, eta_T_R1)\n    fold_index_eta_t_R0_l <- c(fold_index_eta_t_R0_l, rep(k, length(eta_t_R0)))\n    fold_index_eta_t0_R0_l <- c(fold_index_eta_t0_R0_l, rep(k, length(eta_t0_R0)))\n    fold_index_eta_T_R1_l <- c(fold_index_eta_T_R1_l, rep(k, length(eta_T_R1)))\n    \n    if(trt==1){\n      pain_bq_temp <- c(X_in_fold_t_R0$pain_bq, X_in_fold_t0_R0$pain_bq, X_in_fold_R1$pain_bq)\n      pain_bq_R1_temp <- c(rep(0, length(X_in_fold_t_R0$pain_bq)+length(X_in_fold_t0_R0$pain_bq)), X_in_fold_R1$pain_bq)/prop.R1\n      pain_bq_R0_temp <- c(X_in_fold_t_R0$pain_bq, X_in_fold_t0_R0$pain_bq, rep(0, length(X_in_fold_R1$pain_bq)))/(1-prop.R1)\n    }else{\n      pain_bq_temp <- c(X_in_fold_t0_R0$pain_bq, X_in_fold_t_R0$pain_bq, X_in_fold_R1$pain_bq)\n      pain_bq_R1_temp <- c(rep(0, length(X_in_fold_t0_R0$pain_bq)+length(X_in_fold_t_R0$pain_bq)), X_in_fold_R1$pain_bq)/prop.R1\n      pain_bq_R0_temp <- c(X_in_fold_t0_R0$pain_bq, X_in_fold_t_R0$pain_bq, rep(0, length(X_in_fold_R1$pain_bq)))/(1-prop.R1)\n    }\n    pain_bq_reordered <- c(pain_bq_reordered, pain_bq_temp)\n    pain_bq_reordered_R1 <- c(pain_bq_reordered_R1, pain_bq_R1_temp)\n    pain_bq_reordered_R0 <- c(pain_bq_reordered_R0, pain_bq_R0_temp)\n    fold_index_pain <- c(fold_index_pain, rep(k, length(pain_bq_temp)))\n  }\n  \n  ## weight truncation\n  if(!simple_trunc){\n  pi_R0_l <- pmin(pmax(pi_R0_l,0.01),0.99)\n  pi_R1_l <- pmin(pmax(pi_R1_l,0.01),0.99)\n  eta_t_R0_l <- pmin(pmax(eta_t_R0_l,0.01),0.99)\n  eta_t0_R0_l <- pmin(pmax(eta_t0_R0_l,0.01),0.99)\n  eta_T_R1_l <- pmin(pmax(eta_T_R1_l,0.01),0.99)\n  }\n  pi_R0_weight_l <- 1/pi_R0_l\n  pi_R1_weight_l <- 1/pi_R1_l\n  eta_t_R0_weight_l <- 1/eta_t_R0_l\n  eta_t0_R0_weight_l <- 1/eta_t0_R0_l\n  eta_T_R1_weight_l <- 1/eta_T_R1_l\n  if(simple_trunc){\n  pi_R0_weight_l[which(pi_R0_weight_l >= quantile(pi_R0_weight_l, probs = quant))] <- quantile(pi_R0_weight_l, probs = quant)\n  pi_R1_weight_l[which(pi_R1_weight_l >= quantile(pi_R1_weight_l, probs = quant))] <- quantile(pi_R1_weight_l, probs = quant)\n  quant_eta_T_R0_weight <- quantile(c(eta_t_R0_weight_l, eta_t0_R0_weight_l), probs = quant)\n  eta_t_R0_weight_l[which(eta_t_R0_weight_l>=quant_eta_T_R0_weight)] <- quant_eta_T_R0_weight\n  eta_t0_R0_weight_l[which(eta_t0_R0_weight_l>=quant_eta_T_R0_weight)] <- quant_eta_T_R0_weight\n  eta_T_R1_weight_l[which(eta_T_R1_weight_l >= quantile(eta_T_R1_weight_l, probs = quant))] <- quantile(eta_T_R1_weight_l, probs = quant)\n  }\n  \n  ## compute outcome model and influence function for each fold\n  for (k in 1:fold){\n    \n    ## out-of-fold data\n    if(fold>1){\n      out_fold_id_list <- setdiff(1:n, fold_list[[k]])\n    }else{\n      out_fold_id_list <- 1:n\n    }\n    Y_out_fold <- Y[out_fold_id_list]\n    M_out_fold <- M[out_fold_id_list]\n    R_out_fold <- R[out_fold_id_list]\n    t_out_fold <- t[out_fold_id_list]\n    X_out_fold <- X[out_fold_id_list, ]\n    X_out_fold_adjust_scale <- X_adjust_scale[out_fold_id_list, ]\n\n    Y_out_fold_t_R0 <- Y_out_fold[which(t_out_fold==trt & R_out_fold==0)]\n    Y_out_fold_t_R1 <- Y_out_fold[which(t_out_fold==trt & R_out_fold==1)]\n    X_out_fold_t_R0_adjust_scale <- X_out_fold_adjust_scale[which(t_out_fold==trt & R_out_fold==0), ]\n    X_out_fold_t_R1_adjust_scale <- X_out_fold_adjust_scale[which(t_out_fold==trt & R_out_fold==1), ]\n    M_out_fold_t_R0 <- M_out_fold[which(t_out_fold==trt & R_out_fold==0)]\n    M_out_fold_t_R1 <- M_out_fold[which(t_out_fold==trt & R_out_fold==1)]\n    #X_out_fold_t_R0 <- X_out_fold[which(t_out_fold==trt & R_out_fold==0), ]\n    #X_out_fold_t_R1 <- X_out_fold[which(t_out_fold==trt & R_out_fold==1), ]\n    #X_out_fold_t_R0_adjust_scale <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n\n    ## in-fold data\n    nk_in_fold <- length(fold_list[[k]])\n    Y_in_fold <- Y[fold_list[[k]]]\n    M_in_fold <- M[fold_list[[k]]]\n    R_in_fold <- R[fold_list[[k]]]\n    t_in_fold <- t[fold_list[[k]]]\n    trt.ind_in_fold <- trt.ind[fold_list[[k]]]\n    X_in_fold_adjust_scale <- X_adjust_scale[fold_list[[k]], ]\n\n    X_in_fold_t_R0_adjust_scale <- X_in_fold_adjust_scale[which(t_in_fold==trt & R_in_fold==0), ]\n    X_in_fold_t0_R0_adjust_scale <- X_in_fold_adjust_scale[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_in_fold_R1_adjust_scale <- X_in_fold_adjust_scale[which(R_in_fold==1), ]\n    \n    M_in_fold_t_R0 <- M_in_fold[which(t_in_fold==trt & R_in_fold==0)]\n    M_in_fold_t0_R0 <- M_in_fold[which(t_in_fold!=trt & R_in_fold==0)]\n    M_in_fold_R1 <- M_in_fold[which(R_in_fold==1)]\n\n    Y_in_fold_t_R0 <- Y_in_fold[which(t_in_fold==trt & R_in_fold==0)]\n    Y_in_fold_R1 <- Y_in_fold[which(R_in_fold==1)]\n    \n    trt.ind_in_fold_R1 <- trt.ind_in_fold[which(R_in_fold==1)]\n    \n    id_list <- c(id_list, fold_list[[k]])\n    \n    ## get the weights in fold k\n    pi_R0_weight <- pi_R0_weight_l[which(fold_index_pi_R0_l==k)]\n    pi_R1_weight <- pi_R1_weight_l[which(fold_index_pi_R1_l==k)]\n    eta_t_R0_weight <- eta_t_R0_weight_l[which(fold_index_eta_t_R0_l==k)]\n    eta_t0_R0_weight <- eta_t0_R0_weight_l[which(fold_index_eta_t0_R0_l==k)]\n    eta_T_R1_weight <- eta_T_R1_weight_l[which(fold_index_eta_T_R1_l==k)]\n    \n    ## get baseline pain score in fold k\n    pain_bq_temp <- pain_bq_reordered[which(fold_index_pain==k)]\n    pain_bq_R1_temp <- pain_bq_reordered_R1[which(fold_index_pain==k)]\n    pain_bq_R0_temp <- pain_bq_reordered_R0[which(fold_index_pain==k)]\n    \n    ## fit models\n    if(single_index_method==\"fixed_bandwidth\"){\n      if(use_mave){\n        requireNamespace('MAVE', quietly = TRUE)\n        SDR_t_R0 <- coef(MAVE::mave.compute(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                            Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], max.dim = 1), 1)\n      }else{\n        SDR_t_R0 <- cumuSIR(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)])\n      }\n      fit_t_R0_h <- SIDRnew_fixed_bandwidth(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)],\n                                            initial = SDR_t_R0,\n                                            kernel = kernel,\n                                            method = method,\n                                            ids = 1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))\n\n    }else if(single_index_method==\"fixed_coef\"){\n    if(use_mave){\n      requireNamespace('MAVE', quietly = TRUE)\n      SDR_t_R0 <- coef(MAVE::mave.compute(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                          Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], max.dim = 1), 1)\n    }else{\n      SDR_t_R0 <- cumuSIR(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                          Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)])\n    }\n    fit_t_R0_h <- SIDR_Ravinew(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                               Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)],\n                               initial=c(1,as.vector(SDR_t_R0[-1]/SDR_t_R0[1])), \n                               kernel = kernel,\n                               method = method, \n                               index_ID=1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))\n    }else if(single_index_method==\"norm1coef\"){\n    fit_t_R0_h  <- fit_SensIAT_single_index_norm1coef_model(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                                                            ids=1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]), \n                                                            kernel=kernel, bw.selection=\"ise\", bw.method=\"optim\", use_mave=use_mave)\n    }\n    \n    if(single_index_method==\"fixed_bandwidth\"){\n    if(use_mave){\n    SDR_t_R1 <- coef(MAVE::mave.compute(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                        Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], max.dim = 1), 1)\n    }else{\n    SDR_t_R1 <- cumuSIR(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                        Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)])\n    }\n    fit_t_R1_h <- SIDRnew_fixed_bandwidth(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                          Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                                          initial = SDR_t_R1,\n                                          kernel = kernel,\n                                          method = method,\n                                          ids = 1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))\n    }else if(single_index_method==\"fixed_coef\"){\n      if(use_mave){\n        SDR_t_R1 <- coef(MAVE::mave.compute(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                            Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], max.dim = 1), 1)\n      }else{\n        SDR_t_R1 <- cumuSIR(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                            Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)])\n      }\n    fit_t_R1_h <- SIDR_Ravinew(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                               Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                               initial=c(1,as.vector(SDR_t_R1[-1]/SDR_t_R1[1])), \n                               kernel = kernel,\n                               method = method, \n                               index_ID=1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))\n    }else if(single_index_method==\"norm1coef\"){\n    fit_t_R1_h  <- fit_SensIAT_single_index_norm1coef_model(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                                            Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                                                            ids=1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]), \n                                                            kernel=kernel, bw.selection=\"ise\", bw.method=\"optim\", use_mave=use_mave)\n    }\n    \n    ## get prediction for X'beta\n    X_in_fold_t_R0_beta_t_R0 <- as.vector(X_in_fold_t_R0_adjust_scale %*% fit_t_R0_h$coef)\n    X_in_fold_t0_R0_beta_t_R0 <- as.vector(X_in_fold_t0_R0_adjust_scale %*% fit_t_R0_h$coef)\n    X_in_fold_R1_beta_t_R1 <- as.vector(X_in_fold_R1_adjust_scale %*% fit_t_R1_h$coef)\n    X_out_fold_t_R0_beta_t_R0 <- as.vector(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ] %*% fit_t_R0_h$coef)\n    X_out_fold_t_R1_beta_t_R1 <- as.vector(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ] %*% fit_t_R1_h$coef)\n    \n    ## compute CDF\n    y_t_R0 = sort(unique(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))    \n    ny_t_R0 = length(y_t_R0) \n    F_t_R0_X_t_R0 <- NW_new(Xb=X_out_fold_t_R0_beta_t_R0, Y=Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                            xb=X_in_fold_t_R0_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                            kernel = kernel)\n    F_t_R0_X_t0_R0 <- NW_new(Xb=X_out_fold_t_R0_beta_t_R0, Y=Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                             xb=X_in_fold_t0_R0_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                             kernel = kernel)\n    \n    y_t_R1 = sort(unique(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))    \n    ny_t_R1 = length(y_t_R1) \n    F_t_R1_X_R1 <- NW_new(Xb=X_out_fold_t_R1_beta_t_R1, Y=Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], \n                          xb=X_in_fold_R1_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                          kernel = kernel)\n    \n    #fix up cases where CDF is improper by finding closest people with closest X'beta\n    i1 = which(apply(F_t_R0_X_t_R0==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_t_R0_beta_t_R0[i1], X_in_fold_t_R0_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R0_X_t_R0[i1, ] <- F_t_R0_X_t_R0[-i1, ,drop = FALSE][i1.closest, ]\n\n    i1 = which(apply(F_t_R0_X_t0_R0==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_t0_R0_beta_t_R0[i1], X_in_fold_t0_R0_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R0_X_t0_R0[i1, ] <- F_t_R0_X_t0_R0[-i1, ,drop = FALSE][i1.closest, ]\n\n    i1 = which(apply(F_t_R1_X_R1==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_R1_beta_t_R1[i1], X_in_fold_R1_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R1_X_R1[i1, ] <- F_t_R1_X_R1[-i1, ,drop = FALSE][i1.closest, ]\n\n    #compute PDF\n    dF_t_R0_X_t_R0 <- F_t_R0_X_t_R0-cbind(rep(0, dim(F_t_R0_X_t_R0)[1]), F_t_R0_X_t_R0[,-ny_t_R0, drop = FALSE])\n    dF_t_R0_X_t0_R0 <- F_t_R0_X_t0_R0-cbind(rep(0, dim(F_t_R0_X_t0_R0)[1]), F_t_R0_X_t0_R0[,-ny_t_R0, drop = FALSE])\n    dF_t_R1_X_R1 <- F_t_R1_X_R1-cbind(rep(0, dim(F_t_R1_X_R1)[1]), F_t_R1_X_R1[,-ny_t_R1, drop = FALSE])\n    \n    ## conditional expectation of Y given R=0, T=t and X, for I(R=0, T=t)\n    mu_Y_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0+c(0, y_t_R0[-ny_t_R0]))/2)\n    \n    ## conditional expectation of Y given R=1, T=t and X, for I(R=1)\n    mu_Y_t_R1_X_R1 <- c(dF_t_R1_X_R1 %*% (y_t_R1+c(0, y_t_R1[-ny_t_R1]))/2)\n    \n    ## P(R=1)\n    prop.R1 <- mean(R_in_fold)\n    \n    ## vector_R1 and vector_R0\n    vector_R1 <- c(vector_R1, c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                rep(1/prop.R1, length(M_in_fold_R1))))\n    vector_R0 <- c(vector_R0, c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                rep(0, length(M_in_fold_R1))))\n    \n    ## Compute influence function for each gamma_t\n    for (g in 1:length(gamma)){\n      \n    ## conditional expectation of Y * exp given R=0, T=t and X, for I(R=0, T=t)\n    mu_Yexp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                     c(0, y_t_R0[-ny_t_R0])*exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n      \n    ## conditional expectation of exp given R=0, T=t and X, for I(R=0, T=t)\n    mu_exp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                  exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## conditional expectation of Y * exp given R=0, T=t and X, for I(R=0, T=1-t)\n    mu_Yexp_t_R0_X_t0_R0 <- c(dF_t_R0_X_t0_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                     c(0, y_t_R0[-ny_t_R0])*exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## conditional expectation of exp given R=0, T=t and X, for I(R=0, T=1-t)\n    mu_exp_t_R0_X_t0_R0 <- c(dF_t_R0_X_t0_R0 %*% (exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                    exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## IF+psi within each fold\n    if(trt==1){\n      if_temp <- c(M_in_fold_t_R0*eta_t_R0_weight*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                              (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                   M_in_fold_t0_R0*eta_t0_R0_weight*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                   M_in_fold_R1*eta_T_R1_weight*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n        c((1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0, \n          (1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0,\n          (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1)\n      if_temp_diff <- if_temp-pain_bq_temp\n      \n      if_R0_temp <- c(M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                                 (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                      M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                      rep(0, length(M_in_fold_R1)))+\n        c((1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0/(1-prop.R1), \n          (1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/(mu_exp_t_R0_X_t0_R0*(1-prop.R1)),\n          rep(0, length(M_in_fold_R1)))\n      if_R0_temp_diff <- if_R0_temp-pain_bq_R0_temp\n    }else{\n      if_temp <- c(M_in_fold_t0_R0*eta_t0_R0_weight*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                   M_in_fold_t_R0*eta_t_R0_weight*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                              (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                   M_in_fold_R1*eta_T_R1_weight*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n        c((1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0,\n          (1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0, \n          (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1)\n      if_temp_diff <- if_temp-pain_bq_temp\n      \n      if_R0_temp  <- c(M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                         M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                                    (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                         rep(0, length(M_in_fold_R1)))+\n        c((1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/(mu_exp_t_R0_X_t0_R0*(1-prop.R1)),\n          (1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0/(1-prop.R1), \n          rep(0, length(M_in_fold_R1)))\n      if_R0_temp_diff <- if_R0_temp-pain_bq_R0_temp\n    }\n    \n    vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                             rep(0, length(M_in_fold_R1)))*mean(if_R0_temp)\n    vector_mean_R0_temp_diff <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                  rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_diff)\n    \n    if_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                    M_in_fold_R1*eta_T_R1_weight/prop.R1*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n      c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1/prop.R1)\n    if_R1_temp_diff <- if_R1_temp-pain_bq_R1_temp\n    \n    vector_mean_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                             rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp)\n    vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                  rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_diff)\n    \n    IF[[g]] <- c(IF[[g]], if_temp)\n    IF_R1[[g]] <- c(IF_R1[[g]], if_R1_temp)\n    IF_R0[[g]] <- c(IF_R0[[g]], if_R0_temp)\n    IF_diff[[g]] <- c(IF_diff[[g]], if_temp_diff)\n    IF_R1_diff[[g]] <- c(IF_R1_diff[[g]], if_R1_temp_diff)\n    IF_R0_diff[[g]] <- c(IF_R0_diff[[g]], if_R0_temp_diff)\n    \n    est_temp[k, g] <- mean(if_temp)\n    est_R1_temp[k, g] <- mean(if_R1_temp)\n    est_R0_temp[k, g] <- mean(if_R0_temp)\n    var_temp[k, g] <- sum((if_temp - mean(if_temp))^2)/(nk_in_fold-1)\n    var_R1_temp[k, g] <- sum((if_R1_temp - vector_mean_R1_temp)^2)/(nk_in_fold-1)\n    var_R0_temp[k, g] <- sum((if_R0_temp - vector_mean_R0_temp)^2)/(nk_in_fold-1)\n    est_temp_diff[k, g] <- mean(if_temp_diff)\n    est_R1_temp_diff[k, g] <- mean(if_R1_temp_diff)\n    est_R0_temp_diff[k, g] <- mean(if_R0_temp_diff)\n    var_temp_diff[k, g] <- sum((if_temp_diff - mean(if_temp_diff))^2)/(nk_in_fold-1)\n    var_R1_temp_diff[k, g] <- sum((if_R1_temp_diff - vector_mean_R1_temp_diff)^2)/(nk_in_fold-1)\n    var_R0_temp_diff[k, g] <- sum((if_R0_temp_diff - vector_mean_R0_temp_diff)^2)/(nk_in_fold-1)\n    \n    if(!simple_trunc){\n      \n      if (eq(max(abs(if_R1_temp)),z=if_R1_temp)>0) {\n        trunc <- max(abs(if_R1_temp))\n      } else {\n        trunc <- uniroot(eq, z=if_R1_temp, interval=c(0.01, max(abs(if_R1_temp))))$root\n      }\n      if_R1_temp_trunc <- pmin(abs(if_R1_temp),trunc) *  sign(if_R1_temp)\n      IF_R1_trunc[[g]] <- c(IF_R1_trunc[[g]], if_R1_temp_trunc)\n      \n      if (eq(max(abs(if_R1_temp_diff)),z=if_R1_temp_diff)>0) {\n        trunc <- max(abs(if_R1_temp_diff))\n      } else {\n        trunc <- uniroot(eq, z=if_R1_temp_diff, interval=c(0.01, max(abs(if_R1_temp_diff))))$root\n      }\n      if_R1_temp_trunc_diff <- pmin(abs(if_R1_temp_diff),trunc) * sign(if_R1_temp_diff)\n      IF_R1_trunc_diff[[g]] <- c(IF_R1_trunc_diff[[g]], if_R1_temp_trunc_diff)\n      \n      if (eq(max(abs(if_R0_temp)),z=if_R0_temp)>0) {\n        trunc <- max(abs(if_R0_temp))\n      } else {\n        trunc <- uniroot(eq, z=if_R0_temp, interval=c(0.01, max(abs(if_R0_temp))))$root\n      }\n      if_R0_temp_trunc <- pmin(abs(if_R0_temp),trunc) * sign(if_R0_temp)\n      IF_R0_trunc[[g]] <- c(IF_R0_trunc[[g]], if_R0_temp_trunc)\n      \n      if (eq(max(abs(if_R0_temp_diff)),z=if_R0_temp_diff)>0) {\n        trunc <- max(abs(if_R0_temp_diff))\n      } else {\n        trunc <- uniroot(eq, z=if_R0_temp_diff, interval=c(0.01, max(abs(if_R0_temp_diff))))$root\n      }\n      if_R0_temp_trunc_diff <- pmin(abs(if_R0_temp_diff),trunc) * sign(if_R0_temp_diff)\n      IF_R0_trunc_diff[[g]] <- c(IF_R0_trunc_diff[[g]], if_R0_temp_trunc_diff)\n      \n      if_temp_trunc <- if_R1_temp_trunc*prop.R1+if_R0_temp_trunc*(1-prop.R1)\n      IF_trunc[[g]] <- c(IF_trunc[[g]], if_temp_trunc)\n      if_temp_trunc_diff <- if_R1_temp_trunc_diff*prop.R1+if_R0_temp_trunc_diff*(1-prop.R1)\n      IF_trunc_diff[[g]] <- c(IF_trunc_diff[[g]], if_temp_trunc_diff)\n      \n      vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                               rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_trunc)\n      vector_mean_R0_temp_diff <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                    rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_trunc_diff)\n      \n      vector_mean_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                               rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_trunc)\n      vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                    rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_trunc_diff)\n      # \n      est_temp_trunc[k, g] <- mean(if_temp_trunc)\n      est_R1_temp_trunc[k, g] <- mean(if_R1_temp_trunc)\n      est_R0_temp_trunc[k, g] <- mean(if_R0_temp_trunc)\n      var_temp_trunc[k, g] <- sum((if_temp_trunc - mean(if_temp_trunc))^2)/(nk_in_fold-1)\n      var_R1_temp_trunc[k, g] <- sum((if_R1_temp_trunc - vector_mean_R1_temp)^2)/(nk_in_fold-1)\n      var_R0_temp_trunc[k, g] <- sum((if_R0_temp_trunc - vector_mean_R0_temp)^2)/(nk_in_fold-1)\n      \n      est_temp_trunc_diff[k, g] <- mean(if_temp_trunc_diff)\n      est_R1_temp_trunc_diff[k, g] <- mean(if_R1_temp_trunc_diff)\n      est_R0_temp_trunc_diff[k, g] <- mean(if_R0_temp_trunc_diff)\n      var_temp_trunc_diff[k, g] <- sum((if_temp_trunc_diff - mean(if_temp_trunc_diff))^2)/(nk_in_fold-1)\n      var_R1_temp_trunc_diff[k, g] <- sum((if_R1_temp_trunc_diff - vector_mean_R1_temp_diff)^2)/(nk_in_fold-1)\n      var_R0_temp_trunc_diff[k, g] <- sum((if_R0_temp_trunc_diff - vector_mean_R0_temp_diff)^2)/(nk_in_fold-1)\n      \n    }\n    }\n  }\n  \n  ## output containers\n  r_est <- colMeans(est_temp)\n  r_est_R1 <- colMeans(est_R1_temp)\n  r_est_R0 <- colMeans(est_R0_temp)\n  r_var <- colSums(var_temp)/(fold*n)\n  r_var_R1 <- colSums(var_R1_temp)/(fold*n)\n  r_var_R0 <- colSums(var_R0_temp)/(fold*n)\n  r_lowerCI <- r_est-qnorm(0.975)*sqrt(r_var)\n  r_lowerCI_R1 <- r_est_R1-qnorm(0.975)*sqrt(r_var_R1)\n  r_lowerCI_R0 <- r_est_R0-qnorm(0.975)*sqrt(r_var_R0)\n  r_upperCI <- r_est+qnorm(0.975)*sqrt(r_var) \n  r_upperCI_R1 <- r_est_R1+qnorm(0.975)*sqrt(r_var_R1) \n  r_upperCI_R0 <- r_est_R0+qnorm(0.975)*sqrt(r_var_R0) \n  r_est_diff <- colMeans(est_temp_diff)\n  r_est_R1_diff <- colMeans(est_R1_temp_diff)\n  r_est_R0_diff <- colMeans(est_R0_temp_diff)\n  r_var_diff <- colSums(var_temp_diff)/(fold*n)\n  r_var_R1_diff <- colSums(var_R1_temp_diff)/(fold*n)\n  r_var_R0_diff <- colSums(var_R0_temp_diff)/(fold*n)\n  r_lowerCI_diff <- r_est_diff-qnorm(0.975)*sqrt(r_var_diff)\n  r_lowerCI_R1_diff <- r_est_R1_diff-qnorm(0.975)*sqrt(r_var_R1_diff)\n  r_lowerCI_R0_diff <- r_est_R0_diff-qnorm(0.975)*sqrt(r_var_R0_diff)\n  r_upperCI_diff <- r_est_diff+qnorm(0.975)*sqrt(r_var_diff) \n  r_upperCI_R1_diff <- r_est_R1_diff+qnorm(0.975)*sqrt(r_var_R1_diff) \n  r_upperCI_R0_diff <- r_est_R0_diff+qnorm(0.975)*sqrt(r_var_R0_diff)\n  if(!simple_trunc){\n    r_est_trunc <- colMeans(est_temp_trunc)\n    r_est_trunc_R1 <- colMeans(est_R1_temp_trunc)\n    r_est_trunc_R0 <- colMeans(est_R0_temp_trunc)\n    r_var_trunc <- colSums(var_temp_trunc)/(fold*n)\n    r_var_trunc_R1 <- colSums(var_R1_temp_trunc)/(fold*n)\n    r_var_trunc_R0 <- colSums(var_R0_temp_trunc)/(fold*n)\n    r_lowerCI_trunc <- r_est_trunc-qnorm(0.975)*sqrt(r_var_trunc)\n    r_lowerCI_trunc_R1 <- r_est_trunc_R1-qnorm(0.975)*sqrt(r_var_trunc_R1)\n    r_lowerCI_trunc_R0 <- r_est_trunc_R0-qnorm(0.975)*sqrt(r_var_trunc_R0)\n    r_upperCI_trunc <- r_est_trunc+qnorm(0.975)*sqrt(r_var_trunc) \n    r_upperCI_trunc_R1 <- r_est_trunc_R1+qnorm(0.975)*sqrt(r_var_trunc_R1) \n    r_upperCI_trunc_R0 <- r_est_trunc_R0+qnorm(0.975)*sqrt(r_var_trunc_R0) \n    r_est_trunc_diff <- colMeans(est_temp_trunc_diff)\n    r_est_trunc_R1_diff <- colMeans(est_R1_temp_trunc_diff)\n    r_est_trunc_R0_diff <- colMeans(est_R0_temp_trunc_diff)\n    r_var_trunc_diff <- colSums(var_temp_trunc_diff)/(fold*n)\n    r_var_trunc_R1_diff <- colSums(var_R1_temp_trunc_diff)/(fold*n)\n    r_var_trunc_R0_diff <- colSums(var_R0_temp_trunc_diff)/(fold*n)\n    r_lowerCI_trunc_diff <- r_est_trunc_diff-qnorm(0.975)*sqrt(r_var_trunc_diff)\n    r_lowerCI_trunc_R1_diff <- r_est_trunc_R1_diff-qnorm(0.975)*sqrt(r_var_trunc_R1_diff)\n    r_lowerCI_trunc_R0_diff <- r_est_trunc_R0_diff-qnorm(0.975)*sqrt(r_var_trunc_R0_diff)\n    r_upperCI_trunc_diff <- r_est_trunc_diff+qnorm(0.975)*sqrt(r_var_trunc_diff) \n    r_upperCI_trunc_R1_diff <- r_est_trunc_R1_diff+qnorm(0.975)*sqrt(r_var_trunc_R1_diff) \n    r_upperCI_trunc_R0_diff <- r_est_trunc_R0_diff+qnorm(0.975)*sqrt(r_var_trunc_R0_diff) \n\n  }\n  \n  ## another variance estimation & skewness & multiplier bootstrap: empty container\n  # r_var_2 <- r_var_R1_2 <- r_var_R0_2 <- c()\n  # r_var_diff_2 <- r_var_R1_diff_2 <- r_var_R0_diff_2 <- c()\n  # skew <- skew_R1 <- skew_R0 <- c()\n  # skew_diff <- skew_R1_diff <- skew_R0_diff <- c()\n  # if(!simple_trunc){\n  #   r_var_trunc_2 <- r_var_trunc_R1_2 <- r_var_trunc_R0_2 <- c()\n  #   r_var_trunc_diff_2 <- r_var_trunc_R1_diff_2 <- r_var_trunc_R0_diff_2 <- c()\n  #   skew_trunc <- skew_trunc_R1 <- skew_trunc_R0 <- c()\n  #   skew_trunc_diff <- skew_trunc_R1_diff <- skew_trunc_R0_diff <- c()\n  #   \n  #   B <- 2000\n  #   q <- q_R1 <- q_R0 <- c()\n  #   q_diff <- q_R1_diff <- q_R0_diff <- c()\n  # }\n\n  ## another variance estimation & skewness & multiplier bootstrap\n  # for (g in 1:length(gamma)){\n  #   \n  #   r_var_2 <- c(r_var_2, sum((IF[[g]]-mean(IF[[g]]))^2)/(n*(n-1)))\n  #   r_var_R1_2 <- c(r_var_R1_2, sum((IF_R1[[g]]-vector_R1*mean(IF_R1[[g]]))^2)/(n*(n-1)))\n  #   r_var_R0_2 <- c(r_var_R0_2, sum((IF_R0[[g]]-vector_R0*mean(IF_R0[[g]]))^2)/(n*(n-1)))\n  #   r_var_diff_2 <- c(r_var_diff_2, sum((IF_diff[[g]]-mean(IF_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_R1_diff_2 <- c(r_var_R1_diff_2, sum((IF_R1_diff[[g]]-vector_R1*mean(IF_R1_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_R0_diff_2 <- c(r_var_R0_diff_2, sum((IF_R0_diff[[g]]-vector_R0*mean(IF_R0_diff[[g]]))^2)/(n*(n-1)))\n  #   \n  #   skew <- c(skew, mean(IF[[g]]^3)/(mean(IF[[g]]^2)^(3/2)))\n  #   skew_R1 <- c(skew_R1, mean(IF_R1[[g]]^3)/(mean(IF_R1[[g]]^2)^(3/2)))\n  #   skew_R0 <- c(skew_R0, mean(IF_R0[[g]]^3)/(mean(IF_R0[[g]]^2)^(3/2)))\n  #   skew_diff <- c(skew_diff, mean(IF_diff[[g]]^3)/(mean(IF_diff[[g]]^2)^(3/2)))\n  #   skew_R1_diff <- c(skew_R1_diff, mean(IF_R1_diff[[g]]^3)/(mean(IF_R1_diff[[g]]^2)^(3/2)))\n  #   skew_R0_diff <- c(skew_R0_diff, mean(IF_R0_diff[[g]]^3)/(mean(IF_R0_diff[[g]]^2)^(3/2)))\n  #   \n  #   if(!simple_trunc){\n  #     \n  #   r_var_trunc_2 <- c(r_var_trunc_2, sum((IF_trunc[[g]]-mean(IF_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R1_2 <- c(r_var_trunc_R1_2, sum((IF_R1_trunc[[g]]-vector_R1*mean(IF_R1_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R0_2 <- c(r_var_trunc_R0_2, sum((IF_R0_trunc[[g]]-vector_R0*mean(IF_R0_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_diff_2 <- c(r_var_trunc_diff_2, sum((IF_trunc_diff[[g]]-mean(IF_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R1_diff_2 <- c(r_var_trunc_R1_diff_2, sum((IF_R1_trunc_diff[[g]]-vector_R1*mean(IF_R1_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R0_diff_2 <- c(r_var_trunc_R0_diff_2, sum((IF_R0_trunc_diff[[g]]-vector_R0*mean(IF_R0_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   \n  #   skew_trunc <- c(skew_trunc, mean(IF_trunc[[g]]^3)/(mean(IF_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_R1 <- c(skew_trunc_R1, mean(IF_R1_trunc[[g]]^3)/(mean(IF_R1_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_R0 <- c(skew_trunc_R0, mean(IF_R0_trunc[[g]]^3)/(mean(IF_R0_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_diff <- c(skew_trunc_diff, mean(IF_trunc_diff[[g]]^3)/(mean(IF_trunc_diff[[g]]^2)^(3/2)))\n  #   skew_trunc_R1_diff <- c(skew_trunc_R1_diff, mean(IF_R1_trunc_diff[[g]]^3)/(mean(IF_R1_trunc_diff[[g]]^2)^(3/2)))\n  #   skew_trunc_R0_diff <- c(skew_trunc_R0_diff, mean(IF_R0_trunc_diff[[g]]^3)/(mean(IF_R0_trunc_diff[[g]]^2)^(3/2)))\n  #   \n  #   wi <- matrix(sample(c(-1, 1), n*B, replace=TRUE), nrow=B, ncol=n)\n  #   est_star <- r_est_trunc[g]+rowMeans(wi*(IF_trunc[[g]]-mean(IF[[g]])))\n  #   est_R1_star <- r_est_trunc_R1[g]+rowMeans(wi*(IF_R1_trunc[[g]]-vector_R1*mean(IF_R1_trunc[[g]])))\n  #   est_R0_star <- r_est_trunc_R0[g]+rowMeans(wi*(IF_R0_trunc[[g]]-vector_R0*mean(IF_R0_trunc[[g]])))\n  #   est_diff_star <- r_est_trunc_diff[g]+rowMeans(wi*(IF_trunc_diff[[g]]-mean(IF_trunc_diff[[g]])))\n  #   est_R1_diff_star <- r_est_trunc_R1_diff[g]+rowMeans(wi*(IF_R1_trunc_diff[[g]]-vector_R1*mean(IF_R1_trunc_diff[[g]])))\n  #   est_R0_diff_star <- r_est_trunc_R0_diff[g]+rowMeans(wi*(IF_R0_trunc_diff[[g]]-vector_R0*mean(IF_R0_trunc_diff[[g]])))\n  #   \n  #   t_star <- (est_star-r_est_trunc[g])/sqrt(r_var_trunc[g])\n  #   t_R1_star <- (est_R1_star-r_est_trunc_R1[g])/sqrt(r_var_trunc_R1[g])\n  #   t_R0_star <- (est_R0_star-r_est_trunc_R0[g])/sqrt(r_var_trunc_R0[g])\n  #   t_diff_star <- (est_diff_star-r_est_trunc_diff[g])/sqrt(r_var_trunc_diff[g])\n  #   t_R1_diff_star <- (est_R1_diff_star-r_est_trunc_R1_diff[g])/sqrt(r_var_trunc_R1_diff[g])\n  #   t_R0_diff_star <- (est_R0_diff_star-r_est_trunc_R0_diff[g])/sqrt(r_var_trunc_R0_diff[g])\n  #   \n  #   q <- c(q, quantile(abs(t_star), 1-0.05))\n  #   q_R1 <- c(q_R1, quantile(abs(t_R1_star), 1-0.05))\n  #   q_R0 <- c(q_R0, quantile(abs(t_R0_star), 1-0.05))\n  #   q_diff <- c(q_diff, quantile(abs(t_diff_star), 1-0.05))\n  #   q_R1_diff <- c(q_R1_diff, quantile(abs(t_R1_diff_star), 1-0.05))\n  #   q_R0_diff <- c(q_R0_diff, quantile(abs(t_R0_diff_star), 1-0.05))\n  #   \n  #   }\n  # }\n  \n  ## one-step jackknife\n  # jack_est_trunc <- c()\n  # jack_est_trunc_R0 <- c()\n  # jack_est_trunc_R1 <- c()\n  # for (g in 1:length(gamma)){\n  #   jack_est_trunc <- cbind(jack_est_trunc, r_est_trunc[g]-IF_trunc[[g]]/(n-1))\n  #   jack_est_trunc_R0 <- cbind(jack_est_trunc_R0, r_est_trunc_R0[g]-IF_R0_trunc[[g]]/(n-1))\n  #   jack_est_trunc_R1 <- cbind(jack_est_trunc_R1, r_est_trunc_R1[g]-IF_R1_trunc[[g]]/(n-1))\n  # }\n  # jack_var_trunc <- (n-1)/n*colSums((jack_est_trunc-matrix(colMeans(jack_est_trunc), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # jack_var_trunc_R0 <- (n-1)/n*colSums((jack_est_trunc_R0-matrix(colMeans(jack_est_trunc_R0), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # jack_var_trunc_R1 <- (n-1)/n*colSums((jack_est_trunc_R1-matrix(colMeans(jack_est_trunc_R1), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # \n  ## output final results\n  if(IF_output){\n    if(simple_trunc){\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0, \n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0, \n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0, \n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff, \n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff, \n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     IF=IF, IF_R1=IF_R1, IF_R0=IF_R0, \n                     IF_diff=IF_diff, IF_R1_diff=IF_R1_diff, IF_R0_diff=IF_R0_diff, \n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1, \n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n    }else{\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     est_mat=est_temp, est_R1_mat=est_R1_temp, est_R0_mat=est_R0_temp, \n                     est_trunc=r_est_trunc, est_trunc_R1=r_est_trunc_R1, est_trunc_R0=r_est_trunc_R0,\n                     est_trunc_mat=est_temp_trunc, est_trunc_R1_mat=est_R1_temp_trunc, est_trunc_R0_mat=est_R0_temp_trunc, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0,\n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     var_trunc=r_var_trunc, var_trunc_R1=r_var_trunc_R1, var_trunc_R0=r_var_trunc_R0,\n                     # var_trunc_2=r_var_trunc_2, var_trunc_R1_2=r_var_trunc_R1_2, var_trunc_R0_2=r_var_trunc_R0_2, \n                     # skew_trunc=skew_trunc, skew_trunc_R1=skew_trunc_R1, skew_trunc_R0=skew_trunc_R0,\n                     # jack_var_trunc=jack_var_trunc, jack_var_trunc_R0=jack_var_trunc_R0, jack_var_trunc_R1=jack_var_trunc_R1, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0,\n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0,\n                     lowerCI_trunc=r_lowerCI_trunc, lowerCI_trunc_R1=r_lowerCI_trunc_R1, lowerCI_trunc_R0=r_lowerCI_trunc_R0,\n                     upperCI_trunc=r_upperCI_trunc, upperCI_trunc_R1=r_upperCI_trunc_R1, upperCI_trunc_R0=r_upperCI_trunc_R0,\n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff,\n                     est_diff_mat=est_temp_diff, est_R1_diff_mat=est_R1_temp_diff, est_R0_diff_mat=est_R0_temp_diff, \n                     est_trunc_diff=r_est_trunc_diff, est_trunc_R1_diff=r_est_trunc_R1_diff, est_trunc_R0_diff=r_est_trunc_R0_diff,\n                     est_trunc_diff_mat=est_temp_trunc_diff, est_R1_trunc_diff_mat=est_R1_temp_trunc_diff, est_R0_trunc_diff_mat=est_R0_temp_trunc_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff,\n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     var_trunc_diff=r_var_trunc_diff, var_trunc_R1_diff=r_var_trunc_R1_diff, var_trunc_R0_diff=r_var_trunc_R0_diff,\n                     # var_trunc_diff_2=r_var_trunc_diff_2, var_trunc_R1_diff_2=r_var_trunc_R1_diff_2, var_trunc_R0_diff_2=r_var_trunc_R0_diff_2, \n                     # skew_trunc_diff=skew_trunc_diff, skew_trunc_R1_diff=skew_trunc_R1_diff, skew_trunc_R0_diff=skew_trunc_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff,\n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     lowerCI_trunc_diff=r_lowerCI_trunc_diff, lowerCI_trunc_R1_diff=r_lowerCI_trunc_R1_diff, lowerCI_trunc_R0_diff=r_lowerCI_trunc_R0_diff, \n                     upperCI_trunc_diff=r_upperCI_trunc_diff, upperCI_trunc_R1_diff=r_upperCI_trunc_R1_diff, upperCI_trunc_R0_diff=r_upperCI_trunc_R0_diff, \n                     IF=IF, IF_R1=IF_R1, IF_R0=IF_R0,\n                     IF_trunc=IF_trunc, IF_trunc_R1=IF_R1_trunc, IF_trunc_R0=IF_R0_trunc,\n                     IF_diff=IF_diff, IF_R1_diff=IF_R1_diff, IF_R0_diff=IF_R0_diff,\n                     IF_trunc_diff=IF_trunc_diff, IF_trunc_R1_diff=IF_R1_trunc_diff, IF_trunc_R0_diff=IF_R0_trunc_diff,\n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1,\n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n                     # q=q, q_R1=q_R1, q_R0=q_R0, q_diff=q_diff, q_R1_diff=q_R1_diff, q_R0_diff=q_R0_diff)\n    }\n  }else{\n    if(simple_trunc){\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0, \n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0, \n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0, \n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff, \n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff, \n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1, \n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n    }else{\n        result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0,\n                       est_mat=est_temp, est_R1_mat=est_R1_temp, est_R0_mat=est_R0_temp, \n                       est_trunc=r_est_trunc, est_trunc_R1=r_est_trunc_R1, est_trunc_R0=r_est_trunc_R0,\n                       est_trunc_mat=est_temp_trunc, est_trunc_R1_mat=est_R1_temp_trunc, est_trunc_R0_mat=est_R0_temp_trunc, \n                       var=r_var, var_R1=r_var_R1, var_R0=r_var_R0,\n                       # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                       # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                       var_trunc=r_var_trunc, var_trunc_R1=r_var_trunc_R1, var_trunc_R0=r_var_trunc_R0,\n                       # var_trunc_2=r_var_trunc_2, var_trunc_R1_2=r_var_trunc_R1_2, var_trunc_R0_2=r_var_trunc_R0_2, \n                       # skew_trunc=skew_trunc, skew_trunc_R1=skew_trunc_R1, skew_trunc_R0=skew_trunc_R0,\n                       # jack_var_trunc=jack_var_trunc, jack_var_trunc_R0=jack_var_trunc_R0, jack_var_trunc_R1=jack_var_trunc_R1, \n                       lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0,\n                       upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0,\n                       lowerCI_trunc=r_lowerCI_trunc, lowerCI_trunc_R1=r_lowerCI_trunc_R1, lowerCI_trunc_R0=r_lowerCI_trunc_R0,\n                       upperCI_trunc=r_upperCI_trunc, upperCI_trunc_R1=r_upperCI_trunc_R1, upperCI_trunc_R0=r_upperCI_trunc_R0,\n                       est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff,\n                       est_diff_mat=est_temp_diff, est_R1_diff_mat=est_R1_temp_diff, est_R0_diff_mat=est_R0_temp_diff, \n                       est_trunc_diff=r_est_trunc_diff, est_trunc_R1_diff=r_est_trunc_R1_diff, est_trunc_R0_diff=r_est_trunc_R0_diff,\n                       est_trunc_diff_mat=est_temp_trunc_diff, est_R1_trunc_diff_mat=est_R1_temp_trunc_diff, est_R0_trunc_diff_mat=est_R0_temp_trunc_diff, \n                       var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff,\n                       # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                       # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                       var_trunc_diff=r_var_trunc_diff, var_trunc_R1_diff=r_var_trunc_R1_diff, var_trunc_R0_diff=r_var_trunc_R0_diff,\n                       # var_trunc_diff_2=r_var_trunc_diff_2, var_trunc_R1_diff_2=r_var_trunc_R1_diff_2, var_trunc_R0_diff_2=r_var_trunc_R0_diff_2, \n                       # skew_trunc_diff=skew_trunc_diff, skew_trunc_R1_diff=skew_trunc_R1_diff, skew_trunc_R0_diff=skew_trunc_R0_diff, \n                       lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff,\n                       upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff,\n                       lowerCI_trunc_diff=r_lowerCI_trunc_diff, lowerCI_trunc_R1_diff=r_lowerCI_trunc_R1_diff, lowerCI_trunc_R0_diff=r_lowerCI_trunc_R0_diff,\n                       upperCI_trunc_diff=r_upperCI_trunc_diff, upperCI_trunc_R1_diff=r_upperCI_trunc_R1_diff, upperCI_trunc_R0_diff=r_upperCI_trunc_R0_diff,\n                       pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1,\n                       pain_bq_reordered_R0=pain_bq_reordered_R0,\n                       id_list=id_list)\n                       # q=q, q_R1=q_R1, q_R0=q_R0, q_diff=q_diff, q_R1_diff=q_R1_diff, q_R0_diff=q_R0_diff)\n    }\n  }\n  \n}\n\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/est_s_t_y.R"}],"prof_output":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/.Rproj.user/8F38D36A/profiles-cache/fileb330769ac05e.Rprof","highlight":{"output":["^output\\$"],"gc":["^<GC>$"],"stacktrace":["^\\.\\.stacktraceo(n|ff)\\.\\.$"]},"split":"h"}},"evals":[],"jsHooks":[]}</script>
+<script type="application/htmlwidget-sizing" data-for="htmlwidget-f9b31029362fa85527f7">{"viewer":{"width":450,"height":350,"padding":0,"fill":true},"browser":{"width":960,"height":500,"padding":0,"fill":true}}</script>
+</body>
+</html>
diff --git a/profvis_initial_coef_k5.html b/profvis_initial_coef_k5.html
new file mode 100644
index 0000000..b79bf3d
--- /dev/null
+++ b/profvis_initial_coef_k5.html
@@ -0,0 +1,4637 @@
+<!DOCTYPE html>
+<html>
+<head>
+<meta charset="utf-8" />
+<title>profvis</title>
+<style type="text/css">@layer htmltools {
+.html-fill-container {
+display: flex;
+flex-direction: column;
+
+min-height: 0;
+min-width: 0;
+}
+.html-fill-container > .html-fill-item {
+
+flex: 1 1 auto;
+min-height: 0;
+min-width: 0;
+}
+.html-fill-container > :not(.html-fill-item) {
+
+flex: 0 0 auto;
+}
+}
+</style>
+<script>(function() {
+  // If window.HTMLWidgets is already defined, then use it; otherwise create a
+  // new object. This allows preceding code to set options that affect the
+  // initialization process (though none currently exist).
+  window.HTMLWidgets = window.HTMLWidgets || {};
+
+  // See if we're running in a viewer pane. If not, we're in a web browser.
+  var viewerMode = window.HTMLWidgets.viewerMode =
+      /\bviewer_pane=1\b/.test(window.location);
+
+  // See if we're running in Shiny mode. If not, it's a static document.
+  // Note that static widgets can appear in both Shiny and static modes, but
+  // obviously, Shiny widgets can only appear in Shiny apps/documents.
+  var shinyMode = window.HTMLWidgets.shinyMode =
+      typeof(window.Shiny) !== "undefined" && !!window.Shiny.outputBindings;
+
+  // We can't count on jQuery being available, so we implement our own
+  // version if necessary.
+  function querySelectorAll(scope, selector) {
+    if (typeof(jQuery) !== "undefined" && scope instanceof jQuery) {
+      return scope.find(selector);
+    }
+    if (scope.querySelectorAll) {
+      return scope.querySelectorAll(selector);
+    }
+  }
+
+  function asArray(value) {
+    if (value === null)
+      return [];
+    if ($.isArray(value))
+      return value;
+    return [value];
+  }
+
+  // Implement jQuery's extend
+  function extend(target /*, ... */) {
+    if (arguments.length == 1) {
+      return target;
+    }
+    for (var i = 1; i < arguments.length; i++) {
+      var source = arguments[i];
+      for (var prop in source) {
+        if (source.hasOwnProperty(prop)) {
+          target[prop] = source[prop];
+        }
+      }
+    }
+    return target;
+  }
+
+  // IE8 doesn't support Array.forEach.
+  function forEach(values, callback, thisArg) {
+    if (values.forEach) {
+      values.forEach(callback, thisArg);
+    } else {
+      for (var i = 0; i < values.length; i++) {
+        callback.call(thisArg, values[i], i, values);
+      }
+    }
+  }
+
+  // Replaces the specified method with the return value of funcSource.
+  //
+  // Note that funcSource should not BE the new method, it should be a function
+  // that RETURNS the new method. funcSource receives a single argument that is
+  // the overridden method, it can be called from the new method. The overridden
+  // method can be called like a regular function, it has the target permanently
+  // bound to it so "this" will work correctly.
+  function overrideMethod(target, methodName, funcSource) {
+    var superFunc = target[methodName] || function() {};
+    var superFuncBound = function() {
+      return superFunc.apply(target, arguments);
+    };
+    target[methodName] = funcSource(superFuncBound);
+  }
+
+  // Add a method to delegator that, when invoked, calls
+  // delegatee.methodName. If there is no such method on
+  // the delegatee, but there was one on delegator before
+  // delegateMethod was called, then the original version
+  // is invoked instead.
+  // For example:
+  //
+  // var a = {
+  //   method1: function() { console.log('a1'); }
+  //   method2: function() { console.log('a2'); }
+  // };
+  // var b = {
+  //   method1: function() { console.log('b1'); }
+  // };
+  // delegateMethod(a, b, "method1");
+  // delegateMethod(a, b, "method2");
+  // a.method1();
+  // a.method2();
+  //
+  // The output would be "b1", "a2".
+  function delegateMethod(delegator, delegatee, methodName) {
+    var inherited = delegator[methodName];
+    delegator[methodName] = function() {
+      var target = delegatee;
+      var method = delegatee[methodName];
+
+      // The method doesn't exist on the delegatee. Instead,
+      // call the method on the delegator, if it exists.
+      if (!method) {
+        target = delegator;
+        method = inherited;
+      }
+
+      if (method) {
+        return method.apply(target, arguments);
+      }
+    };
+  }
+
+  // Implement a vague facsimilie of jQuery's data method
+  function elementData(el, name, value) {
+    if (arguments.length == 2) {
+      return el["htmlwidget_data_" + name];
+    } else if (arguments.length == 3) {
+      el["htmlwidget_data_" + name] = value;
+      return el;
+    } else {
+      throw new Error("Wrong number of arguments for elementData: " +
+        arguments.length);
+    }
+  }
+
+  // http://stackoverflow.com/questions/3446170/escape-string-for-use-in-javascript-regex
+  function escapeRegExp(str) {
+    return str.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g, "\\$&");
+  }
+
+  function hasClass(el, className) {
+    var re = new RegExp("\\b" + escapeRegExp(className) + "\\b");
+    return re.test(el.className);
+  }
+
+  // elements - array (or array-like object) of HTML elements
+  // className - class name to test for
+  // include - if true, only return elements with given className;
+  //   if false, only return elements *without* given className
+  function filterByClass(elements, className, include) {
+    var results = [];
+    for (var i = 0; i < elements.length; i++) {
+      if (hasClass(elements[i], className) == include)
+        results.push(elements[i]);
+    }
+    return results;
+  }
+
+  function on(obj, eventName, func) {
+    if (obj.addEventListener) {
+      obj.addEventListener(eventName, func, false);
+    } else if (obj.attachEvent) {
+      obj.attachEvent(eventName, func);
+    }
+  }
+
+  function off(obj, eventName, func) {
+    if (obj.removeEventListener)
+      obj.removeEventListener(eventName, func, false);
+    else if (obj.detachEvent) {
+      obj.detachEvent(eventName, func);
+    }
+  }
+
+  // Translate array of values to top/right/bottom/left, as usual with
+  // the "padding" CSS property
+  // https://developer.mozilla.org/en-US/docs/Web/CSS/padding
+  function unpackPadding(value) {
+    if (typeof(value) === "number")
+      value = [value];
+    if (value.length === 1) {
+      return {top: value[0], right: value[0], bottom: value[0], left: value[0]};
+    }
+    if (value.length === 2) {
+      return {top: value[0], right: value[1], bottom: value[0], left: value[1]};
+    }
+    if (value.length === 3) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[1]};
+    }
+    if (value.length === 4) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[3]};
+    }
+  }
+
+  // Convert an unpacked padding object to a CSS value
+  function paddingToCss(paddingObj) {
+    return paddingObj.top + "px " + paddingObj.right + "px " + paddingObj.bottom + "px " + paddingObj.left + "px";
+  }
+
+  // Makes a number suitable for CSS
+  function px(x) {
+    if (typeof(x) === "number")
+      return x + "px";
+    else
+      return x;
+  }
+
+  // Retrieves runtime widget sizing information for an element.
+  // The return value is either null, or an object with fill, padding,
+  // defaultWidth, defaultHeight fields.
+  function sizingPolicy(el) {
+    var sizingEl = document.querySelector("script[data-for='" + el.id + "'][type='application/htmlwidget-sizing']");
+    if (!sizingEl)
+      return null;
+    var sp = JSON.parse(sizingEl.textContent || sizingEl.text || "{}");
+    if (viewerMode) {
+      return sp.viewer;
+    } else {
+      return sp.browser;
+    }
+  }
+
+  // @param tasks Array of strings (or falsy value, in which case no-op).
+  //   Each element must be a valid JavaScript expression that yields a
+  //   function. Or, can be an array of objects with "code" and "data"
+  //   properties; in this case, the "code" property should be a string
+  //   of JS that's an expr that yields a function, and "data" should be
+  //   an object that will be added as an additional argument when that
+  //   function is called.
+  // @param target The object that will be "this" for each function
+  //   execution.
+  // @param args Array of arguments to be passed to the functions. (The
+  //   same arguments will be passed to all functions.)
+  function evalAndRun(tasks, target, args) {
+    if (tasks) {
+      forEach(tasks, function(task) {
+        var theseArgs = args;
+        if (typeof(task) === "object") {
+          theseArgs = theseArgs.concat([task.data]);
+          task = task.code;
+        }
+        var taskFunc = tryEval(task);
+        if (typeof(taskFunc) !== "function") {
+          throw new Error("Task must be a function! Source:\n" + task);
+        }
+        taskFunc.apply(target, theseArgs);
+      });
+    }
+  }
+
+  // Attempt eval() both with and without enclosing in parentheses.
+  // Note that enclosing coerces a function declaration into
+  // an expression that eval() can parse
+  // (otherwise, a SyntaxError is thrown)
+  function tryEval(code) {
+    var result = null;
+    try {
+      result = eval("(" + code + ")");
+    } catch(error) {
+      if (!(error instanceof SyntaxError)) {
+        throw error;
+      }
+      try {
+        result = eval(code);
+      } catch(e) {
+        if (e instanceof SyntaxError) {
+          throw error;
+        } else {
+          throw e;
+        }
+      }
+    }
+    return result;
+  }
+
+  function initSizing(el) {
+    var sizing = sizingPolicy(el);
+    if (!sizing)
+      return;
+
+    var cel = document.getElementById("htmlwidget_container");
+    if (!cel)
+      return;
+
+    if (typeof(sizing.padding) !== "undefined") {
+      document.body.style.margin = "0";
+      document.body.style.padding = paddingToCss(unpackPadding(sizing.padding));
+    }
+
+    if (sizing.fill) {
+      document.body.style.overflow = "hidden";
+      document.body.style.width = "100%";
+      document.body.style.height = "100%";
+      document.documentElement.style.width = "100%";
+      document.documentElement.style.height = "100%";
+      cel.style.position = "absolute";
+      var pad = unpackPadding(sizing.padding);
+      cel.style.top = pad.top + "px";
+      cel.style.right = pad.right + "px";
+      cel.style.bottom = pad.bottom + "px";
+      cel.style.left = pad.left + "px";
+      el.style.width = "100%";
+      el.style.height = "100%";
+
+      return {
+        getWidth: function() { return cel.getBoundingClientRect().width; },
+        getHeight: function() { return cel.getBoundingClientRect().height; }
+      };
+
+    } else {
+      el.style.width = px(sizing.width);
+      el.style.height = px(sizing.height);
+
+      return {
+        getWidth: function() { return cel.getBoundingClientRect().width; },
+        getHeight: function() { return cel.getBoundingClientRect().height; }
+      };
+    }
+  }
+
+  // Default implementations for methods
+  var defaults = {
+    find: function(scope) {
+      return querySelectorAll(scope, "." + this.name);
+    },
+    renderError: function(el, err) {
+      var $el = $(el);
+
+      this.clearError(el);
+
+      // Add all these error classes, as Shiny does
+      var errClass = "shiny-output-error";
+      if (err.type !== null) {
+        // use the classes of the error condition as CSS class names
+        errClass = errClass + " " + $.map(asArray(err.type), function(type) {
+          return errClass + "-" + type;
+        }).join(" ");
+      }
+      errClass = errClass + " htmlwidgets-error";
+
+      // Is el inline or block? If inline or inline-block, just display:none it
+      // and add an inline error.
+      var display = $el.css("display");
+      $el.data("restore-display-mode", display);
+
+      if (display === "inline" || display === "inline-block") {
+        $el.hide();
+        if (err.message !== "") {
+          var errorSpan = $("<span>").addClass(errClass);
+          errorSpan.text(err.message);
+          $el.after(errorSpan);
+        }
+      } else if (display === "block") {
+        // If block, add an error just after the el, set visibility:none on the
+        // el, and position the error to be on top of the el.
+        // Mark it with a unique ID and CSS class so we can remove it later.
+        $el.css("visibility", "hidden");
+        if (err.message !== "") {
+          var errorDiv = $("<div>").addClass(errClass).css("position", "absolute")
+            .css("top", el.offsetTop)
+            .css("left", el.offsetLeft)
+            // setting width can push out the page size, forcing otherwise
+            // unnecessary scrollbars to appear and making it impossible for
+            // the element to shrink; so use max-width instead
+            .css("maxWidth", el.offsetWidth)
+            .css("height", el.offsetHeight);
+          errorDiv.text(err.message);
+          $el.after(errorDiv);
+
+          // Really dumb way to keep the size/position of the error in sync with
+          // the parent element as the window is resized or whatever.
+          var intId = setInterval(function() {
+            if (!errorDiv[0].parentElement) {
+              clearInterval(intId);
+              return;
+            }
+            errorDiv
+              .css("top", el.offsetTop)
+              .css("left", el.offsetLeft)
+              .css("maxWidth", el.offsetWidth)
+              .css("height", el.offsetHeight);
+          }, 500);
+        }
+      }
+    },
+    clearError: function(el) {
+      var $el = $(el);
+      var display = $el.data("restore-display-mode");
+      $el.data("restore-display-mode", null);
+
+      if (display === "inline" || display === "inline-block") {
+        if (display)
+          $el.css("display", display);
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      } else if (display === "block"){
+        $el.css("visibility", "inherit");
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      }
+    },
+    sizing: {}
+  };
+
+  // Called by widget bindings to register a new type of widget. The definition
+  // object can contain the following properties:
+  // - name (required) - A string indicating the binding name, which will be
+  //   used by default as the CSS classname to look for.
+  // - initialize (optional) - A function(el) that will be called once per
+  //   widget element; if a value is returned, it will be passed as the third
+  //   value to renderValue.
+  // - renderValue (required) - A function(el, data, initValue) that will be
+  //   called with data. Static contexts will cause this to be called once per
+  //   element; Shiny apps will cause this to be called multiple times per
+  //   element, as the data changes.
+  window.HTMLWidgets.widget = function(definition) {
+    if (!definition.name) {
+      throw new Error("Widget must have a name");
+    }
+    if (!definition.type) {
+      throw new Error("Widget must have a type");
+    }
+    // Currently we only support output widgets
+    if (definition.type !== "output") {
+      throw new Error("Unrecognized widget type '" + definition.type + "'");
+    }
+    // TODO: Verify that .name is a valid CSS classname
+
+    // Support new-style instance-bound definitions. Old-style class-bound
+    // definitions have one widget "object" per widget per type/class of
+    // widget; the renderValue and resize methods on such widget objects
+    // take el and instance arguments, because the widget object can't
+    // store them. New-style instance-bound definitions have one widget
+    // object per widget instance; the definition that's passed in doesn't
+    // provide renderValue or resize methods at all, just the single method
+    //   factory(el, width, height)
+    // which returns an object that has renderValue(x) and resize(w, h).
+    // This enables a far more natural programming style for the widget
+    // author, who can store per-instance state using either OO-style
+    // instance fields or functional-style closure variables (I guess this
+    // is in contrast to what can only be called C-style pseudo-OO which is
+    // what we required before).
+    if (definition.factory) {
+      definition = createLegacyDefinitionAdapter(definition);
+    }
+
+    if (!definition.renderValue) {
+      throw new Error("Widget must have a renderValue function");
+    }
+
+    // For static rendering (non-Shiny), use a simple widget registration
+    // scheme. We also use this scheme for Shiny apps/documents that also
+    // contain static widgets.
+    window.HTMLWidgets.widgets = window.HTMLWidgets.widgets || [];
+    // Merge defaults into the definition; don't mutate the original definition.
+    var staticBinding = extend({}, defaults, definition);
+    overrideMethod(staticBinding, "find", function(superfunc) {
+      return function(scope) {
+        var results = superfunc(scope);
+        // Filter out Shiny outputs, we only want the static kind
+        return filterByClass(results, "html-widget-output", false);
+      };
+    });
+    window.HTMLWidgets.widgets.push(staticBinding);
+
+    if (shinyMode) {
+      // Shiny is running. Register the definition with an output binding.
+      // The definition itself will not be the output binding, instead
+      // we will make an output binding object that delegates to the
+      // definition. This is because we foolishly used the same method
+      // name (renderValue) for htmlwidgets definition and Shiny bindings
+      // but they actually have quite different semantics (the Shiny
+      // bindings receive data that includes lots of metadata that it
+      // strips off before calling htmlwidgets renderValue). We can't
+      // just ignore the difference because in some widgets it's helpful
+      // to call this.renderValue() from inside of resize(), and if
+      // we're not delegating, then that call will go to the Shiny
+      // version instead of the htmlwidgets version.
+
+      // Merge defaults with definition, without mutating either.
+      var bindingDef = extend({}, defaults, definition);
+
+      // This object will be our actual Shiny binding.
+      var shinyBinding = new Shiny.OutputBinding();
+
+      // With a few exceptions, we'll want to simply use the bindingDef's
+      // version of methods if they are available, otherwise fall back to
+      // Shiny's defaults. NOTE: If Shiny's output bindings gain additional
+      // methods in the future, and we want them to be overrideable by
+      // HTMLWidget binding definitions, then we'll need to add them to this
+      // list.
+      delegateMethod(shinyBinding, bindingDef, "getId");
+      delegateMethod(shinyBinding, bindingDef, "onValueChange");
+      delegateMethod(shinyBinding, bindingDef, "onValueError");
+      delegateMethod(shinyBinding, bindingDef, "renderError");
+      delegateMethod(shinyBinding, bindingDef, "clearError");
+      delegateMethod(shinyBinding, bindingDef, "showProgress");
+
+      // The find, renderValue, and resize are handled differently, because we
+      // want to actually decorate the behavior of the bindingDef methods.
+
+      shinyBinding.find = function(scope) {
+        var results = bindingDef.find(scope);
+
+        // Only return elements that are Shiny outputs, not static ones
+        var dynamicResults = results.filter(".html-widget-output");
+
+        // It's possible that whatever caused Shiny to think there might be
+        // new dynamic outputs, also caused there to be new static outputs.
+        // Since there might be lots of different htmlwidgets bindings, we
+        // schedule execution for later--no need to staticRender multiple
+        // times.
+        if (results.length !== dynamicResults.length)
+          scheduleStaticRender();
+
+        return dynamicResults;
+      };
+
+      // Wrap renderValue to handle initialization, which unfortunately isn't
+      // supported natively by Shiny at the time of this writing.
+
+      shinyBinding.renderValue = function(el, data) {
+        Shiny.renderDependencies(data.deps);
+        // Resolve strings marked as javascript literals to objects
+        if (!(data.evals instanceof Array)) data.evals = [data.evals];
+        for (var i = 0; data.evals && i < data.evals.length; i++) {
+          window.HTMLWidgets.evaluateStringMember(data.x, data.evals[i]);
+        }
+        if (!bindingDef.renderOnNullValue) {
+          if (data.x === null) {
+            el.style.visibility = "hidden";
+            return;
+          } else {
+            el.style.visibility = "inherit";
+          }
+        }
+        if (!elementData(el, "initialized")) {
+          initSizing(el);
+
+          elementData(el, "initialized", true);
+          if (bindingDef.initialize) {
+            var rect = el.getBoundingClientRect();
+            var result = bindingDef.initialize(el, rect.width, rect.height);
+            elementData(el, "init_result", result);
+          }
+        }
+        bindingDef.renderValue(el, data.x, elementData(el, "init_result"));
+        evalAndRun(data.jsHooks.render, elementData(el, "init_result"), [el, data.x]);
+      };
+
+      // Only override resize if bindingDef implements it
+      if (bindingDef.resize) {
+        shinyBinding.resize = function(el, width, height) {
+          // Shiny can call resize before initialize/renderValue have been
+          // called, which doesn't make sense for widgets.
+          if (elementData(el, "initialized")) {
+            bindingDef.resize(el, width, height, elementData(el, "init_result"));
+          }
+        };
+      }
+
+      Shiny.outputBindings.register(shinyBinding, bindingDef.name);
+    }
+  };
+
+  var scheduleStaticRenderTimerId = null;
+  function scheduleStaticRender() {
+    if (!scheduleStaticRenderTimerId) {
+      scheduleStaticRenderTimerId = setTimeout(function() {
+        scheduleStaticRenderTimerId = null;
+        window.HTMLWidgets.staticRender();
+      }, 1);
+    }
+  }
+
+  // Render static widgets after the document finishes loading
+  // Statically render all elements that are of this widget's class
+  window.HTMLWidgets.staticRender = function() {
+    var bindings = window.HTMLWidgets.widgets || [];
+    forEach(bindings, function(binding) {
+      var matches = binding.find(document.documentElement);
+      forEach(matches, function(el) {
+        var sizeObj = initSizing(el, binding);
+
+        var getSize = function(el) {
+          if (sizeObj) {
+            return {w: sizeObj.getWidth(), h: sizeObj.getHeight()}
+          } else {
+            var rect = el.getBoundingClientRect();
+            return {w: rect.width, h: rect.height}
+          }
+        };
+
+        if (hasClass(el, "html-widget-static-bound"))
+          return;
+        el.className = el.className + " html-widget-static-bound";
+
+        var initResult;
+        if (binding.initialize) {
+          var size = getSize(el);
+          initResult = binding.initialize(el, size.w, size.h);
+          elementData(el, "init_result", initResult);
+        }
+
+        if (binding.resize) {
+          var lastSize = getSize(el);
+          var resizeHandler = function(e) {
+            var size = getSize(el);
+            if (size.w === 0 && size.h === 0)
+              return;
+            if (size.w === lastSize.w && size.h === lastSize.h)
+              return;
+            lastSize = size;
+            binding.resize(el, size.w, size.h, initResult);
+          };
+
+          on(window, "resize", resizeHandler);
+
+          // This is needed for cases where we're running in a Shiny
+          // app, but the widget itself is not a Shiny output, but
+          // rather a simple static widget. One example of this is
+          // an rmarkdown document that has runtime:shiny and widget
+          // that isn't in a render function. Shiny only knows to
+          // call resize handlers for Shiny outputs, not for static
+          // widgets, so we do it ourselves.
+          if (window.jQuery) {
+            window.jQuery(document).on(
+              "shown.htmlwidgets shown.bs.tab.htmlwidgets shown.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+            window.jQuery(document).on(
+              "hidden.htmlwidgets hidden.bs.tab.htmlwidgets hidden.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+          }
+
+          // This is needed for the specific case of ioslides, which
+          // flips slides between display:none and display:block.
+          // Ideally we would not have to have ioslide-specific code
+          // here, but rather have ioslides raise a generic event,
+          // but the rmarkdown package just went to CRAN so the
+          // window to getting that fixed may be long.
+          if (window.addEventListener) {
+            // It's OK to limit this to window.addEventListener
+            // browsers because ioslides itself only supports
+            // such browsers.
+            on(document, "slideenter", resizeHandler);
+            on(document, "slideleave", resizeHandler);
+          }
+        }
+
+        var scriptData = document.querySelector("script[data-for='" + el.id + "'][type='application/json']");
+        if (scriptData) {
+          var data = JSON.parse(scriptData.textContent || scriptData.text);
+          // Resolve strings marked as javascript literals to objects
+          if (!(data.evals instanceof Array)) data.evals = [data.evals];
+          for (var k = 0; data.evals && k < data.evals.length; k++) {
+            window.HTMLWidgets.evaluateStringMember(data.x, data.evals[k]);
+          }
+          binding.renderValue(el, data.x, initResult);
+          evalAndRun(data.jsHooks.render, initResult, [el, data.x]);
+        }
+      });
+    });
+
+    invokePostRenderHandlers();
+  }
+
+
+  function has_jQuery3() {
+    if (!window.jQuery) {
+      return false;
+    }
+    var $version = window.jQuery.fn.jquery;
+    var $major_version = parseInt($version.split(".")[0]);
+    return $major_version >= 3;
+  }
+
+  /*
+  / Shiny 1.4 bumped jQuery from 1.x to 3.x which means jQuery's
+  / on-ready handler (i.e., $(fn)) is now asyncronous (i.e., it now
+  / really means $(setTimeout(fn)).
+  / https://jquery.com/upgrade-guide/3.0/#breaking-change-document-ready-handlers-are-now-asynchronous
+  /
+  / Since Shiny uses $() to schedule initShiny, shiny>=1.4 calls initShiny
+  / one tick later than it did before, which means staticRender() is
+  / called renderValue() earlier than (advanced) widget authors might be expecting.
+  / https://github.com/rstudio/shiny/issues/2630
+  /
+  / For a concrete example, leaflet has some methods (e.g., updateBounds)
+  / which reference Shiny methods registered in initShiny (e.g., setInputValue).
+  / Since leaflet is privy to this life-cycle, it knows to use setTimeout() to
+  / delay execution of those methods (until Shiny methods are ready)
+  / https://github.com/rstudio/leaflet/blob/18ec981/javascript/src/index.js#L266-L268
+  /
+  / Ideally widget authors wouldn't need to use this setTimeout() hack that
+  / leaflet uses to call Shiny methods on a staticRender(). In the long run,
+  / the logic initShiny should be broken up so that method registration happens
+  / right away, but binding happens later.
+  */
+  function maybeStaticRenderLater() {
+    if (shinyMode && has_jQuery3()) {
+      window.jQuery(window.HTMLWidgets.staticRender);
+    } else {
+      window.HTMLWidgets.staticRender();
+    }
+  }
+
+  if (document.addEventListener) {
+    document.addEventListener("DOMContentLoaded", function() {
+      document.removeEventListener("DOMContentLoaded", arguments.callee, false);
+      maybeStaticRenderLater();
+    }, false);
+  } else if (document.attachEvent) {
+    document.attachEvent("onreadystatechange", function() {
+      if (document.readyState === "complete") {
+        document.detachEvent("onreadystatechange", arguments.callee);
+        maybeStaticRenderLater();
+      }
+    });
+  }
+
+
+  window.HTMLWidgets.getAttachmentUrl = function(depname, key) {
+    // If no key, default to the first item
+    if (typeof(key) === "undefined")
+      key = 1;
+
+    var link = document.getElementById(depname + "-" + key + "-attachment");
+    if (!link) {
+      throw new Error("Attachment " + depname + "/" + key + " not found in document");
+    }
+    return link.getAttribute("href");
+  };
+
+  window.HTMLWidgets.dataframeToD3 = function(df) {
+    var names = [];
+    var length;
+    for (var name in df) {
+        if (df.hasOwnProperty(name))
+            names.push(name);
+        if (typeof(df[name]) !== "object" || typeof(df[name].length) === "undefined") {
+            throw new Error("All fields must be arrays");
+        } else if (typeof(length) !== "undefined" && length !== df[name].length) {
+            throw new Error("All fields must be arrays of the same length");
+        }
+        length = df[name].length;
+    }
+    var results = [];
+    var item;
+    for (var row = 0; row < length; row++) {
+        item = {};
+        for (var col = 0; col < names.length; col++) {
+            item[names[col]] = df[names[col]][row];
+        }
+        results.push(item);
+    }
+    return results;
+  };
+
+  window.HTMLWidgets.transposeArray2D = function(array) {
+      if (array.length === 0) return array;
+      var newArray = array[0].map(function(col, i) {
+          return array.map(function(row) {
+              return row[i]
+          })
+      });
+      return newArray;
+  };
+  // Split value at splitChar, but allow splitChar to be escaped
+  // using escapeChar. Any other characters escaped by escapeChar
+  // will be included as usual (including escapeChar itself).
+  function splitWithEscape(value, splitChar, escapeChar) {
+    var results = [];
+    var escapeMode = false;
+    var currentResult = "";
+    for (var pos = 0; pos < value.length; pos++) {
+      if (!escapeMode) {
+        if (value[pos] === splitChar) {
+          results.push(currentResult);
+          currentResult = "";
+        } else if (value[pos] === escapeChar) {
+          escapeMode = true;
+        } else {
+          currentResult += value[pos];
+        }
+      } else {
+        currentResult += value[pos];
+        escapeMode = false;
+      }
+    }
+    if (currentResult !== "") {
+      results.push(currentResult);
+    }
+    return results;
+  }
+  // Function authored by Yihui/JJ Allaire
+  window.HTMLWidgets.evaluateStringMember = function(o, member) {
+    var parts = splitWithEscape(member, '.', '\\');
+    for (var i = 0, l = parts.length; i < l; i++) {
+      var part = parts[i];
+      // part may be a character or 'numeric' member name
+      if (o !== null && typeof o === "object" && part in o) {
+        if (i == (l - 1)) { // if we are at the end of the line then evalulate
+          if (typeof o[part] === "string")
+            o[part] = tryEval(o[part]);
+        } else { // otherwise continue to next embedded object
+          o = o[part];
+        }
+      }
+    }
+  };
+
+  // Retrieve the HTMLWidget instance (i.e. the return value of an
+  // HTMLWidget binding's initialize() or factory() function)
+  // associated with an element, or null if none.
+  window.HTMLWidgets.getInstance = function(el) {
+    return elementData(el, "init_result");
+  };
+
+  // Finds the first element in the scope that matches the selector,
+  // and returns the HTMLWidget instance (i.e. the return value of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with that element, if any. If no element matches the
+  // selector, or the first matching element has no HTMLWidget
+  // instance associated with it, then null is returned.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.find = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var el = scope.querySelector(selector);
+    if (el === null) {
+      return null;
+    } else {
+      return window.HTMLWidgets.getInstance(el);
+    }
+  };
+
+  // Finds all elements in the scope that match the selector, and
+  // returns the HTMLWidget instances (i.e. the return values of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with the elements, in an array. If elements that
+  // match the selector don't have an associated HTMLWidget
+  // instance, the returned array will contain nulls.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.findAll = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var nodes = scope.querySelectorAll(selector);
+    var results = [];
+    for (var i = 0; i < nodes.length; i++) {
+      results.push(window.HTMLWidgets.getInstance(nodes[i]));
+    }
+    return results;
+  };
+
+  var postRenderHandlers = [];
+  function invokePostRenderHandlers() {
+    while (postRenderHandlers.length) {
+      var handler = postRenderHandlers.shift();
+      if (handler) {
+        handler();
+      }
+    }
+  }
+
+  // Register the given callback function to be invoked after the
+  // next time static widgets are rendered.
+  window.HTMLWidgets.addPostRenderHandler = function(callback) {
+    postRenderHandlers.push(callback);
+  };
+
+  // Takes a new-style instance-bound definition, and returns an
+  // old-style class-bound definition. This saves us from having
+  // to rewrite all the logic in this file to accomodate both
+  // types of definitions.
+  function createLegacyDefinitionAdapter(defn) {
+    var result = {
+      name: defn.name,
+      type: defn.type,
+      initialize: function(el, width, height) {
+        return defn.factory(el, width, height);
+      },
+      renderValue: function(el, x, instance) {
+        return instance.renderValue(x);
+      },
+      resize: function(el, width, height, instance) {
+        return instance.resize(width, height);
+      }
+    };
+
+    if (defn.find)
+      result.find = defn.find;
+    if (defn.renderError)
+      result.renderError = defn.renderError;
+    if (defn.clearError)
+      result.clearError = defn.clearError;
+
+    return result;
+  }
+})();
+</script>
+<script>/*! jQuery v3.7.1 | (c) OpenJS Foundation and other contributors | jquery.org/license */
+!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(ie,e){"use strict";var oe=[],r=Object.getPrototypeOf,ae=oe.slice,g=oe.flat?function(e){return oe.flat.call(e)}:function(e){return oe.concat.apply([],e)},s=oe.push,se=oe.indexOf,n={},i=n.toString,ue=n.hasOwnProperty,o=ue.toString,a=o.call(Object),le={},v=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},y=function(e){return null!=e&&e===e.window},C=ie.document,u={type:!0,src:!0,nonce:!0,noModule:!0};function m(e,t,n){var r,i,o=(n=n||C).createElement("script");if(o.text=e,t)for(r in u)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function x(e){return null==e?e+"":"object"==typeof e||"function"==typeof e?n[i.call(e)]||"object":typeof e}var t="3.7.1",l=/HTML$/i,ce=function(e,t){return new ce.fn.init(e,t)};function c(e){var t=!!e&&"length"in e&&e.length,n=x(e);return!v(e)&&!y(e)&&("array"===n||0===t||"number"==typeof t&&0<t&&t-1 in e)}function fe(e,t){return e.nodeName&&e.nodeName.toLowerCase()===t.toLowerCase()}ce.fn=ce.prototype={jquery:t,constructor:ce,length:0,toArray:function(){return ae.call(this)},get:function(e){return null==e?ae.call(this):e<0?this[e+this.length]:this[e]},pushStack:function(e){var t=ce.merge(this.constructor(),e);return t.prevObject=this,t},each:function(e){return ce.each(this,e)},map:function(n){return this.pushStack(ce.map(this,function(e,t){return n.call(e,t,e)}))},slice:function(){return this.pushStack(ae.apply(this,arguments))},first:function(){return this.eq(0)},last:function(){return this.eq(-1)},even:function(){return this.pushStack(ce.grep(this,function(e,t){return(t+1)%2}))},odd:function(){return this.pushStack(ce.grep(this,function(e,t){return t%2}))},eq:function(e){var t=this.length,n=+e+(e<0?t:0);return this.pushStack(0<=n&&n<t?[this[n]]:[])},end:function(){return this.prevObject||this.constructor()},push:s,sort:oe.sort,splice:oe.splice},ce.extend=ce.fn.extend=function(){var e,t,n,r,i,o,a=arguments[0]||{},s=1,u=arguments.length,l=!1;for("boolean"==typeof a&&(l=a,a=arguments[s]||{},s++),"object"==typeof a||v(a)||(a={}),s===u&&(a=this,s--);s<u;s++)if(null!=(e=arguments[s]))for(t in e)r=e[t],"__proto__"!==t&&a!==r&&(l&&r&&(ce.isPlainObject(r)||(i=Array.isArray(r)))?(n=a[t],o=i&&!Array.isArray(n)?[]:i||ce.isPlainObject(n)?n:{},i=!1,a[t]=ce.extend(l,o,r)):void 0!==r&&(a[t]=r));return a},ce.extend({expando:"jQuery"+(t+Math.random()).replace(/\D/g,""),isReady:!0,error:function(e){throw new Error(e)},noop:function(){},isPlainObject:function(e){var t,n;return!(!e||"[object Object]"!==i.call(e))&&(!(t=r(e))||"function"==typeof(n=ue.call(t,"constructor")&&t.constructor)&&o.call(n)===a)},isEmptyObject:function(e){var t;for(t in e)return!1;return!0},globalEval:function(e,t,n){m(e,{nonce:t&&t.nonce},n)},each:function(e,t){var n,r=0;if(c(e)){for(n=e.length;r<n;r++)if(!1===t.call(e[r],r,e[r]))break}else for(r in e)if(!1===t.call(e[r],r,e[r]))break;return e},text:function(e){var t,n="",r=0,i=e.nodeType;if(!i)while(t=e[r++])n+=ce.text(t);return 1===i||11===i?e.textContent:9===i?e.documentElement.textContent:3===i||4===i?e.nodeValue:n},makeArray:function(e,t){var n=t||[];return null!=e&&(c(Object(e))?ce.merge(n,"string"==typeof e?[e]:e):s.call(n,e)),n},inArray:function(e,t,n){return null==t?-1:se.call(t,e,n)},isXMLDoc:function(e){var t=e&&e.namespaceURI,n=e&&(e.ownerDocument||e).documentElement;return!l.test(t||n&&n.nodeName||"HTML")},merge:function(e,t){for(var n=+t.length,r=0,i=e.length;r<n;r++)e[i++]=t[r];return e.length=i,e},grep:function(e,t,n){for(var r=[],i=0,o=e.length,a=!n;i<o;i++)!t(e[i],i)!==a&&r.push(e[i]);return r},map:function(e,t,n){var r,i,o=0,a=[];if(c(e))for(r=e.length;o<r;o++)null!=(i=t(e[o],o,n))&&a.push(i);else for(o in e)null!=(i=t(e[o],o,n))&&a.push(i);return g(a)},guid:1,support:le}),"function"==typeof Symbol&&(ce.fn[Symbol.iterator]=oe[Symbol.iterator]),ce.each("Boolean Number String Function Array Date RegExp Object Error Symbol".split(" "),function(e,t){n["[object "+t+"]"]=t.toLowerCase()});var pe=oe.pop,de=oe.sort,he=oe.splice,ge="[\\x20\\t\\r\\n\\f]",ve=new RegExp("^"+ge+"+|((?:^|[^\\\\])(?:\\\\.)*)"+ge+"+$","g");ce.contains=function(e,t){var n=t&&t.parentNode;return e===n||!(!n||1!==n.nodeType||!(e.contains?e.contains(n):e.compareDocumentPosition&&16&e.compareDocumentPosition(n)))};var f=/([\0-\x1f\x7f]|^-?\d)|^-$|[^\x80-\uFFFF\w-]/g;function p(e,t){return t?"\0"===e?"\ufffd":e.slice(0,-1)+"\\"+e.charCodeAt(e.length-1).toString(16)+" ":"\\"+e}ce.escapeSelector=function(e){return(e+"").replace(f,p)};var ye=C,me=s;!function(){var e,b,w,o,a,T,r,C,d,i,k=me,S=ce.expando,E=0,n=0,s=W(),c=W(),u=W(),h=W(),l=function(e,t){return e===t&&(a=!0),0},f="checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|ismap|loop|multiple|open|readonly|required|scoped",t="(?:\\\\[\\da-fA-F]{1,6}"+ge+"?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+",p="\\["+ge+"*("+t+")(?:"+ge+"*([*^$|!~]?=)"+ge+"*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|("+t+"))|)"+ge+"*\\]",g=":("+t+")(?:\\((('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|((?:\\\\.|[^\\\\()[\\]]|"+p+")*)|.*)\\)|)",v=new RegExp(ge+"+","g"),y=new RegExp("^"+ge+"*,"+ge+"*"),m=new RegExp("^"+ge+"*([>+~]|"+ge+")"+ge+"*"),x=new RegExp(ge+"|>"),j=new RegExp(g),A=new RegExp("^"+t+"$"),D={ID:new RegExp("^#("+t+")"),CLASS:new RegExp("^\\.("+t+")"),TAG:new RegExp("^("+t+"|[*])"),ATTR:new RegExp("^"+p),PSEUDO:new RegExp("^"+g),CHILD:new RegExp("^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\("+ge+"*(even|odd|(([+-]|)(\\d*)n|)"+ge+"*(?:([+-]|)"+ge+"*(\\d+)|))"+ge+"*\\)|)","i"),bool:new RegExp("^(?:"+f+")$","i"),needsContext:new RegExp("^"+ge+"*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\("+ge+"*((?:-\\d)?\\d*)"+ge+"*\\)|)(?=[^-]|$)","i")},N=/^(?:input|select|textarea|button)$/i,q=/^h\d$/i,L=/^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/,H=/[+~]/,O=new RegExp("\\\\[\\da-fA-F]{1,6}"+ge+"?|\\\\([^\\r\\n\\f])","g"),P=function(e,t){var n="0x"+e.slice(1)-65536;return t||(n<0?String.fromCharCode(n+65536):String.fromCharCode(n>>10|55296,1023&n|56320))},M=function(){V()},R=J(function(e){return!0===e.disabled&&fe(e,"fieldset")},{dir:"parentNode",next:"legend"});try{k.apply(oe=ae.call(ye.childNodes),ye.childNodes),oe[ye.childNodes.length].nodeType}catch(e){k={apply:function(e,t){me.apply(e,ae.call(t))},call:function(e){me.apply(e,ae.call(arguments,1))}}}function I(t,e,n,r){var i,o,a,s,u,l,c,f=e&&e.ownerDocument,p=e?e.nodeType:9;if(n=n||[],"string"!=typeof t||!t||1!==p&&9!==p&&11!==p)return n;if(!r&&(V(e),e=e||T,C)){if(11!==p&&(u=L.exec(t)))if(i=u[1]){if(9===p){if(!(a=e.getElementById(i)))return n;if(a.id===i)return k.call(n,a),n}else if(f&&(a=f.getElementById(i))&&I.contains(e,a)&&a.id===i)return k.call(n,a),n}else{if(u[2])return k.apply(n,e.getElementsByTagName(t)),n;if((i=u[3])&&e.getElementsByClassName)return k.apply(n,e.getElementsByClassName(i)),n}if(!(h[t+" "]||d&&d.test(t))){if(c=t,f=e,1===p&&(x.test(t)||m.test(t))){(f=H.test(t)&&U(e.parentNode)||e)==e&&le.scope||((s=e.getAttribute("id"))?s=ce.escapeSelector(s):e.setAttribute("id",s=S)),o=(l=Y(t)).length;while(o--)l[o]=(s?"#"+s:":scope")+" "+Q(l[o]);c=l.join(",")}try{return k.apply(n,f.querySelectorAll(c)),n}catch(e){h(t,!0)}finally{s===S&&e.removeAttribute("id")}}}return re(t.replace(ve,"$1"),e,n,r)}function W(){var r=[];return function e(t,n){return r.push(t+" ")>b.cacheLength&&delete e[r.shift()],e[t+" "]=n}}function F(e){return e[S]=!0,e}function $(e){var t=T.createElement("fieldset");try{return!!e(t)}catch(e){return!1}finally{t.parentNode&&t.parentNode.removeChild(t),t=null}}function B(t){return function(e){return fe(e,"input")&&e.type===t}}function _(t){return function(e){return(fe(e,"input")||fe(e,"button"))&&e.type===t}}function z(t){return function(e){return"form"in e?e.parentNode&&!1===e.disabled?"label"in e?"label"in e.parentNode?e.parentNode.disabled===t:e.disabled===t:e.isDisabled===t||e.isDisabled!==!t&&R(e)===t:e.disabled===t:"label"in e&&e.disabled===t}}function X(a){return F(function(o){return o=+o,F(function(e,t){var n,r=a([],e.length,o),i=r.length;while(i--)e[n=r[i]]&&(e[n]=!(t[n]=e[n]))})})}function U(e){return e&&"undefined"!=typeof e.getElementsByTagName&&e}function V(e){var t,n=e?e.ownerDocument||e:ye;return n!=T&&9===n.nodeType&&n.documentElement&&(r=(T=n).documentElement,C=!ce.isXMLDoc(T),i=r.matches||r.webkitMatchesSelector||r.msMatchesSelector,r.msMatchesSelector&&ye!=T&&(t=T.defaultView)&&t.top!==t&&t.addEventListener("unload",M),le.getById=$(function(e){return r.appendChild(e).id=ce.expando,!T.getElementsByName||!T.getElementsByName(ce.expando).length}),le.disconnectedMatch=$(function(e){return i.call(e,"*")}),le.scope=$(function(){return T.querySelectorAll(":scope")}),le.cssHas=$(function(){try{return T.querySelector(":has(*,:jqfake)"),!1}catch(e){return!0}}),le.getById?(b.filter.ID=function(e){var t=e.replace(O,P);return function(e){return e.getAttribute("id")===t}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&C){var n=t.getElementById(e);return n?[n]:[]}}):(b.filter.ID=function(e){var n=e.replace(O,P);return function(e){var t="undefined"!=typeof e.getAttributeNode&&e.getAttributeNode("id");return t&&t.value===n}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&C){var n,r,i,o=t.getElementById(e);if(o){if((n=o.getAttributeNode("id"))&&n.value===e)return[o];i=t.getElementsByName(e),r=0;while(o=i[r++])if((n=o.getAttributeNode("id"))&&n.value===e)return[o]}return[]}}),b.find.TAG=function(e,t){return"undefined"!=typeof t.getElementsByTagName?t.getElementsByTagName(e):t.querySelectorAll(e)},b.find.CLASS=function(e,t){if("undefined"!=typeof t.getElementsByClassName&&C)return t.getElementsByClassName(e)},d=[],$(function(e){var t;r.appendChild(e).innerHTML="<a id='"+S+"' href='' disabled='disabled'></a><select id='"+S+"-\r\\' disabled='disabled'><option selected=''></option></select>",e.querySelectorAll("[selected]").length||d.push("\\["+ge+"*(?:value|"+f+")"),e.querySelectorAll("[id~="+S+"-]").length||d.push("~="),e.querySelectorAll("a#"+S+"+*").length||d.push(".#.+[+~]"),e.querySelectorAll(":checked").length||d.push(":checked"),(t=T.createElement("input")).setAttribute("type","hidden"),e.appendChild(t).setAttribute("name","D"),r.appendChild(e).disabled=!0,2!==e.querySelectorAll(":disabled").length&&d.push(":enabled",":disabled"),(t=T.createElement("input")).setAttribute("name",""),e.appendChild(t),e.querySelectorAll("[name='']").length||d.push("\\["+ge+"*name"+ge+"*="+ge+"*(?:''|\"\")")}),le.cssHas||d.push(":has"),d=d.length&&new RegExp(d.join("|")),l=function(e,t){if(e===t)return a=!0,0;var n=!e.compareDocumentPosition-!t.compareDocumentPosition;return n||(1&(n=(e.ownerDocument||e)==(t.ownerDocument||t)?e.compareDocumentPosition(t):1)||!le.sortDetached&&t.compareDocumentPosition(e)===n?e===T||e.ownerDocument==ye&&I.contains(ye,e)?-1:t===T||t.ownerDocument==ye&&I.contains(ye,t)?1:o?se.call(o,e)-se.call(o,t):0:4&n?-1:1)}),T}for(e in I.matches=function(e,t){return I(e,null,null,t)},I.matchesSelector=function(e,t){if(V(e),C&&!h[t+" "]&&(!d||!d.test(t)))try{var n=i.call(e,t);if(n||le.disconnectedMatch||e.document&&11!==e.document.nodeType)return n}catch(e){h(t,!0)}return 0<I(t,T,null,[e]).length},I.contains=function(e,t){return(e.ownerDocument||e)!=T&&V(e),ce.contains(e,t)},I.attr=function(e,t){(e.ownerDocument||e)!=T&&V(e);var n=b.attrHandle[t.toLowerCase()],r=n&&ue.call(b.attrHandle,t.toLowerCase())?n(e,t,!C):void 0;return void 0!==r?r:e.getAttribute(t)},I.error=function(e){throw new Error("Syntax error, unrecognized expression: "+e)},ce.uniqueSort=function(e){var t,n=[],r=0,i=0;if(a=!le.sortStable,o=!le.sortStable&&ae.call(e,0),de.call(e,l),a){while(t=e[i++])t===e[i]&&(r=n.push(i));while(r--)he.call(e,n[r],1)}return o=null,e},ce.fn.uniqueSort=function(){return this.pushStack(ce.uniqueSort(ae.apply(this)))},(b=ce.expr={cacheLength:50,createPseudo:F,match:D,attrHandle:{},find:{},relative:{">":{dir:"parentNode",first:!0}," ":{dir:"parentNode"},"+":{dir:"previousSibling",first:!0},"~":{dir:"previousSibling"}},preFilter:{ATTR:function(e){return e[1]=e[1].replace(O,P),e[3]=(e[3]||e[4]||e[5]||"").replace(O,P),"~="===e[2]&&(e[3]=" "+e[3]+" "),e.slice(0,4)},CHILD:function(e){return e[1]=e[1].toLowerCase(),"nth"===e[1].slice(0,3)?(e[3]||I.error(e[0]),e[4]=+(e[4]?e[5]+(e[6]||1):2*("even"===e[3]||"odd"===e[3])),e[5]=+(e[7]+e[8]||"odd"===e[3])):e[3]&&I.error(e[0]),e},PSEUDO:function(e){var t,n=!e[6]&&e[2];return D.CHILD.test(e[0])?null:(e[3]?e[2]=e[4]||e[5]||"":n&&j.test(n)&&(t=Y(n,!0))&&(t=n.indexOf(")",n.length-t)-n.length)&&(e[0]=e[0].slice(0,t),e[2]=n.slice(0,t)),e.slice(0,3))}},filter:{TAG:function(e){var t=e.replace(O,P).toLowerCase();return"*"===e?function(){return!0}:function(e){return fe(e,t)}},CLASS:function(e){var t=s[e+" "];return t||(t=new RegExp("(^|"+ge+")"+e+"("+ge+"|$)"))&&s(e,function(e){return t.test("string"==typeof e.className&&e.className||"undefined"!=typeof e.getAttribute&&e.getAttribute("class")||"")})},ATTR:function(n,r,i){return function(e){var t=I.attr(e,n);return null==t?"!="===r:!r||(t+="","="===r?t===i:"!="===r?t!==i:"^="===r?i&&0===t.indexOf(i):"*="===r?i&&-1<t.indexOf(i):"$="===r?i&&t.slice(-i.length)===i:"~="===r?-1<(" "+t.replace(v," ")+" ").indexOf(i):"|="===r&&(t===i||t.slice(0,i.length+1)===i+"-"))}},CHILD:function(d,e,t,h,g){var v="nth"!==d.slice(0,3),y="last"!==d.slice(-4),m="of-type"===e;return 1===h&&0===g?function(e){return!!e.parentNode}:function(e,t,n){var r,i,o,a,s,u=v!==y?"nextSibling":"previousSibling",l=e.parentNode,c=m&&e.nodeName.toLowerCase(),f=!n&&!m,p=!1;if(l){if(v){while(u){o=e;while(o=o[u])if(m?fe(o,c):1===o.nodeType)return!1;s=u="only"===d&&!s&&"nextSibling"}return!0}if(s=[y?l.firstChild:l.lastChild],y&&f){p=(a=(r=(i=l[S]||(l[S]={}))[d]||[])[0]===E&&r[1])&&r[2],o=a&&l.childNodes[a];while(o=++a&&o&&o[u]||(p=a=0)||s.pop())if(1===o.nodeType&&++p&&o===e){i[d]=[E,a,p];break}}else if(f&&(p=a=(r=(i=e[S]||(e[S]={}))[d]||[])[0]===E&&r[1]),!1===p)while(o=++a&&o&&o[u]||(p=a=0)||s.pop())if((m?fe(o,c):1===o.nodeType)&&++p&&(f&&((i=o[S]||(o[S]={}))[d]=[E,p]),o===e))break;return(p-=g)===h||p%h==0&&0<=p/h}}},PSEUDO:function(e,o){var t,a=b.pseudos[e]||b.setFilters[e.toLowerCase()]||I.error("unsupported pseudo: "+e);return a[S]?a(o):1<a.length?(t=[e,e,"",o],b.setFilters.hasOwnProperty(e.toLowerCase())?F(function(e,t){var n,r=a(e,o),i=r.length;while(i--)e[n=se.call(e,r[i])]=!(t[n]=r[i])}):function(e){return a(e,0,t)}):a}},pseudos:{not:F(function(e){var r=[],i=[],s=ne(e.replace(ve,"$1"));return s[S]?F(function(e,t,n,r){var i,o=s(e,null,r,[]),a=e.length;while(a--)(i=o[a])&&(e[a]=!(t[a]=i))}):function(e,t,n){return r[0]=e,s(r,null,n,i),r[0]=null,!i.pop()}}),has:F(function(t){return function(e){return 0<I(t,e).length}}),contains:F(function(t){return t=t.replace(O,P),function(e){return-1<(e.textContent||ce.text(e)).indexOf(t)}}),lang:F(function(n){return A.test(n||"")||I.error("unsupported lang: "+n),n=n.replace(O,P).toLowerCase(),function(e){var t;do{if(t=C?e.lang:e.getAttribute("xml:lang")||e.getAttribute("lang"))return(t=t.toLowerCase())===n||0===t.indexOf(n+"-")}while((e=e.parentNode)&&1===e.nodeType);return!1}}),target:function(e){var t=ie.location&&ie.location.hash;return t&&t.slice(1)===e.id},root:function(e){return e===r},focus:function(e){return e===function(){try{return T.activeElement}catch(e){}}()&&T.hasFocus()&&!!(e.type||e.href||~e.tabIndex)},enabled:z(!1),disabled:z(!0),checked:function(e){return fe(e,"input")&&!!e.checked||fe(e,"option")&&!!e.selected},selected:function(e){return e.parentNode&&e.parentNode.selectedIndex,!0===e.selected},empty:function(e){for(e=e.firstChild;e;e=e.nextSibling)if(e.nodeType<6)return!1;return!0},parent:function(e){return!b.pseudos.empty(e)},header:function(e){return q.test(e.nodeName)},input:function(e){return N.test(e.nodeName)},button:function(e){return fe(e,"input")&&"button"===e.type||fe(e,"button")},text:function(e){var t;return fe(e,"input")&&"text"===e.type&&(null==(t=e.getAttribute("type"))||"text"===t.toLowerCase())},first:X(function(){return[0]}),last:X(function(e,t){return[t-1]}),eq:X(function(e,t,n){return[n<0?n+t:n]}),even:X(function(e,t){for(var n=0;n<t;n+=2)e.push(n);return e}),odd:X(function(e,t){for(var n=1;n<t;n+=2)e.push(n);return e}),lt:X(function(e,t,n){var r;for(r=n<0?n+t:t<n?t:n;0<=--r;)e.push(r);return e}),gt:X(function(e,t,n){for(var r=n<0?n+t:n;++r<t;)e.push(r);return e})}}).pseudos.nth=b.pseudos.eq,{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})b.pseudos[e]=B(e);for(e in{submit:!0,reset:!0})b.pseudos[e]=_(e);function G(){}function Y(e,t){var n,r,i,o,a,s,u,l=c[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=y.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=m.exec(a))&&(n=r.shift(),i.push({value:n,type:r[0].replace(ve," ")}),a=a.slice(n.length)),b.filter)!(r=D[o].exec(a))||u[o]&&!(r=u[o](r))||(n=r.shift(),i.push({value:n,type:o,matches:r}),a=a.slice(n.length));if(!n)break}return t?a.length:a?I.error(e):c(e,s).slice(0)}function Q(e){for(var t=0,n=e.length,r="";t<n;t++)r+=e[t].value;return r}function J(a,e,t){var s=e.dir,u=e.next,l=u||s,c=t&&"parentNode"===l,f=n++;return e.first?function(e,t,n){while(e=e[s])if(1===e.nodeType||c)return a(e,t,n);return!1}:function(e,t,n){var r,i,o=[E,f];if(n){while(e=e[s])if((1===e.nodeType||c)&&a(e,t,n))return!0}else while(e=e[s])if(1===e.nodeType||c)if(i=e[S]||(e[S]={}),u&&fe(e,u))e=e[s]||e;else{if((r=i[l])&&r[0]===E&&r[1]===f)return o[2]=r[2];if((i[l]=o)[2]=a(e,t,n))return!0}return!1}}function K(i){return 1<i.length?function(e,t,n){var r=i.length;while(r--)if(!i[r](e,t,n))return!1;return!0}:i[0]}function Z(e,t,n,r,i){for(var o,a=[],s=0,u=e.length,l=null!=t;s<u;s++)(o=e[s])&&(n&&!n(o,r,i)||(a.push(o),l&&t.push(s)));return a}function ee(d,h,g,v,y,e){return v&&!v[S]&&(v=ee(v)),y&&!y[S]&&(y=ee(y,e)),F(function(e,t,n,r){var i,o,a,s,u=[],l=[],c=t.length,f=e||function(e,t,n){for(var r=0,i=t.length;r<i;r++)I(e,t[r],n);return n}(h||"*",n.nodeType?[n]:n,[]),p=!d||!e&&h?f:Z(f,u,d,n,r);if(g?g(p,s=y||(e?d:c||v)?[]:t,n,r):s=p,v){i=Z(s,l),v(i,[],n,r),o=i.length;while(o--)(a=i[o])&&(s[l[o]]=!(p[l[o]]=a))}if(e){if(y||d){if(y){i=[],o=s.length;while(o--)(a=s[o])&&i.push(p[o]=a);y(null,s=[],i,r)}o=s.length;while(o--)(a=s[o])&&-1<(i=y?se.call(e,a):u[o])&&(e[i]=!(t[i]=a))}}else s=Z(s===t?s.splice(c,s.length):s),y?y(null,t,s,r):k.apply(t,s)})}function te(e){for(var i,t,n,r=e.length,o=b.relative[e[0].type],a=o||b.relative[" "],s=o?1:0,u=J(function(e){return e===i},a,!0),l=J(function(e){return-1<se.call(i,e)},a,!0),c=[function(e,t,n){var r=!o&&(n||t!=w)||((i=t).nodeType?u(e,t,n):l(e,t,n));return i=null,r}];s<r;s++)if(t=b.relative[e[s].type])c=[J(K(c),t)];else{if((t=b.filter[e[s].type].apply(null,e[s].matches))[S]){for(n=++s;n<r;n++)if(b.relative[e[n].type])break;return ee(1<s&&K(c),1<s&&Q(e.slice(0,s-1).concat({value:" "===e[s-2].type?"*":""})).replace(ve,"$1"),t,s<n&&te(e.slice(s,n)),n<r&&te(e=e.slice(n)),n<r&&Q(e))}c.push(t)}return K(c)}function ne(e,t){var n,v,y,m,x,r,i=[],o=[],a=u[e+" "];if(!a){t||(t=Y(e)),n=t.length;while(n--)(a=te(t[n]))[S]?i.push(a):o.push(a);(a=u(e,(v=o,m=0<(y=i).length,x=0<v.length,r=function(e,t,n,r,i){var o,a,s,u=0,l="0",c=e&&[],f=[],p=w,d=e||x&&b.find.TAG("*",i),h=E+=null==p?1:Math.random()||.1,g=d.length;for(i&&(w=t==T||t||i);l!==g&&null!=(o=d[l]);l++){if(x&&o){a=0,t||o.ownerDocument==T||(V(o),n=!C);while(s=v[a++])if(s(o,t||T,n)){k.call(r,o);break}i&&(E=h)}m&&((o=!s&&o)&&u--,e&&c.push(o))}if(u+=l,m&&l!==u){a=0;while(s=y[a++])s(c,f,t,n);if(e){if(0<u)while(l--)c[l]||f[l]||(f[l]=pe.call(r));f=Z(f)}k.apply(r,f),i&&!e&&0<f.length&&1<u+y.length&&ce.uniqueSort(r)}return i&&(E=h,w=p),c},m?F(r):r))).selector=e}return a}function re(e,t,n,r){var i,o,a,s,u,l="function"==typeof e&&e,c=!r&&Y(e=l.selector||e);if(n=n||[],1===c.length){if(2<(o=c[0]=c[0].slice(0)).length&&"ID"===(a=o[0]).type&&9===t.nodeType&&C&&b.relative[o[1].type]){if(!(t=(b.find.ID(a.matches[0].replace(O,P),t)||[])[0]))return n;l&&(t=t.parentNode),e=e.slice(o.shift().value.length)}i=D.needsContext.test(e)?0:o.length;while(i--){if(a=o[i],b.relative[s=a.type])break;if((u=b.find[s])&&(r=u(a.matches[0].replace(O,P),H.test(o[0].type)&&U(t.parentNode)||t))){if(o.splice(i,1),!(e=r.length&&Q(o)))return k.apply(n,r),n;break}}}return(l||ne(e,c))(r,t,!C,n,!t||H.test(e)&&U(t.parentNode)||t),n}G.prototype=b.filters=b.pseudos,b.setFilters=new G,le.sortStable=S.split("").sort(l).join("")===S,V(),le.sortDetached=$(function(e){return 1&e.compareDocumentPosition(T.createElement("fieldset"))}),ce.find=I,ce.expr[":"]=ce.expr.pseudos,ce.unique=ce.uniqueSort,I.compile=ne,I.select=re,I.setDocument=V,I.tokenize=Y,I.escape=ce.escapeSelector,I.getText=ce.text,I.isXML=ce.isXMLDoc,I.selectors=ce.expr,I.support=ce.support,I.uniqueSort=ce.uniqueSort}();var d=function(e,t,n){var r=[],i=void 0!==n;while((e=e[t])&&9!==e.nodeType)if(1===e.nodeType){if(i&&ce(e).is(n))break;r.push(e)}return r},h=function(e,t){for(var n=[];e;e=e.nextSibling)1===e.nodeType&&e!==t&&n.push(e);return n},b=ce.expr.match.needsContext,w=/^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i;function T(e,n,r){return v(n)?ce.grep(e,function(e,t){return!!n.call(e,t,e)!==r}):n.nodeType?ce.grep(e,function(e){return e===n!==r}):"string"!=typeof n?ce.grep(e,function(e){return-1<se.call(n,e)!==r}):ce.filter(n,e,r)}ce.filter=function(e,t,n){var r=t[0];return n&&(e=":not("+e+")"),1===t.length&&1===r.nodeType?ce.find.matchesSelector(r,e)?[r]:[]:ce.find.matches(e,ce.grep(t,function(e){return 1===e.nodeType}))},ce.fn.extend({find:function(e){var t,n,r=this.length,i=this;if("string"!=typeof e)return this.pushStack(ce(e).filter(function(){for(t=0;t<r;t++)if(ce.contains(i[t],this))return!0}));for(n=this.pushStack([]),t=0;t<r;t++)ce.find(e,i[t],n);return 1<r?ce.uniqueSort(n):n},filter:function(e){return this.pushStack(T(this,e||[],!1))},not:function(e){return this.pushStack(T(this,e||[],!0))},is:function(e){return!!T(this,"string"==typeof e&&b.test(e)?ce(e):e||[],!1).length}});var k,S=/^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/;(ce.fn.init=function(e,t,n){var r,i;if(!e)return this;if(n=n||k,"string"==typeof e){if(!(r="<"===e[0]&&">"===e[e.length-1]&&3<=e.length?[null,e,null]:S.exec(e))||!r[1]&&t)return!t||t.jquery?(t||n).find(e):this.constructor(t).find(e);if(r[1]){if(t=t instanceof ce?t[0]:t,ce.merge(this,ce.parseHTML(r[1],t&&t.nodeType?t.ownerDocument||t:C,!0)),w.test(r[1])&&ce.isPlainObject(t))for(r in t)v(this[r])?this[r](t[r]):this.attr(r,t[r]);return this}return(i=C.getElementById(r[2]))&&(this[0]=i,this.length=1),this}return e.nodeType?(this[0]=e,this.length=1,this):v(e)?void 0!==n.ready?n.ready(e):e(ce):ce.makeArray(e,this)}).prototype=ce.fn,k=ce(C);var E=/^(?:parents|prev(?:Until|All))/,j={children:!0,contents:!0,next:!0,prev:!0};function A(e,t){while((e=e[t])&&1!==e.nodeType);return e}ce.fn.extend({has:function(e){var t=ce(e,this),n=t.length;return this.filter(function(){for(var e=0;e<n;e++)if(ce.contains(this,t[e]))return!0})},closest:function(e,t){var n,r=0,i=this.length,o=[],a="string"!=typeof e&&ce(e);if(!b.test(e))for(;r<i;r++)for(n=this[r];n&&n!==t;n=n.parentNode)if(n.nodeType<11&&(a?-1<a.index(n):1===n.nodeType&&ce.find.matchesSelector(n,e))){o.push(n);break}return this.pushStack(1<o.length?ce.uniqueSort(o):o)},index:function(e){return e?"string"==typeof e?se.call(ce(e),this[0]):se.call(this,e.jquery?e[0]:e):this[0]&&this[0].parentNode?this.first().prevAll().length:-1},add:function(e,t){return this.pushStack(ce.uniqueSort(ce.merge(this.get(),ce(e,t))))},addBack:function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}}),ce.each({parent:function(e){var t=e.parentNode;return t&&11!==t.nodeType?t:null},parents:function(e){return d(e,"parentNode")},parentsUntil:function(e,t,n){return d(e,"parentNode",n)},next:function(e){return A(e,"nextSibling")},prev:function(e){return A(e,"previousSibling")},nextAll:function(e){return d(e,"nextSibling")},prevAll:function(e){return d(e,"previousSibling")},nextUntil:function(e,t,n){return d(e,"nextSibling",n)},prevUntil:function(e,t,n){return d(e,"previousSibling",n)},siblings:function(e){return h((e.parentNode||{}).firstChild,e)},children:function(e){return h(e.firstChild)},contents:function(e){return null!=e.contentDocument&&r(e.contentDocument)?e.contentDocument:(fe(e,"template")&&(e=e.content||e),ce.merge([],e.childNodes))}},function(r,i){ce.fn[r]=function(e,t){var n=ce.map(this,i,e);return"Until"!==r.slice(-5)&&(t=e),t&&"string"==typeof t&&(n=ce.filter(t,n)),1<this.length&&(j[r]||ce.uniqueSort(n),E.test(r)&&n.reverse()),this.pushStack(n)}});var D=/[^\x20\t\r\n\f]+/g;function N(e){return e}function q(e){throw e}function L(e,t,n,r){var i;try{e&&v(i=e.promise)?i.call(e).done(t).fail(n):e&&v(i=e.then)?i.call(e,t,n):t.apply(void 0,[e].slice(r))}catch(e){n.apply(void 0,[e])}}ce.Callbacks=function(r){var e,n;r="string"==typeof r?(e=r,n={},ce.each(e.match(D)||[],function(e,t){n[t]=!0}),n):ce.extend({},r);var i,t,o,a,s=[],u=[],l=-1,c=function(){for(a=a||r.once,o=i=!0;u.length;l=-1){t=u.shift();while(++l<s.length)!1===s[l].apply(t[0],t[1])&&r.stopOnFalse&&(l=s.length,t=!1)}r.memory||(t=!1),i=!1,a&&(s=t?[]:"")},f={add:function(){return s&&(t&&!i&&(l=s.length-1,u.push(t)),function n(e){ce.each(e,function(e,t){v(t)?r.unique&&f.has(t)||s.push(t):t&&t.length&&"string"!==x(t)&&n(t)})}(arguments),t&&!i&&c()),this},remove:function(){return ce.each(arguments,function(e,t){var n;while(-1<(n=ce.inArray(t,s,n)))s.splice(n,1),n<=l&&l--}),this},has:function(e){return e?-1<ce.inArray(e,s):0<s.length},empty:function(){return s&&(s=[]),this},disable:function(){return a=u=[],s=t="",this},disabled:function(){return!s},lock:function(){return a=u=[],t||i||(s=t=""),this},locked:function(){return!!a},fireWith:function(e,t){return a||(t=[e,(t=t||[]).slice?t.slice():t],u.push(t),i||c()),this},fire:function(){return f.fireWith(this,arguments),this},fired:function(){return!!o}};return f},ce.extend({Deferred:function(e){var o=[["notify","progress",ce.Callbacks("memory"),ce.Callbacks("memory"),2],["resolve","done",ce.Callbacks("once memory"),ce.Callbacks("once memory"),0,"resolved"],["reject","fail",ce.Callbacks("once memory"),ce.Callbacks("once memory"),1,"rejected"]],i="pending",a={state:function(){return i},always:function(){return s.done(arguments).fail(arguments),this},"catch":function(e){return a.then(null,e)},pipe:function(){var i=arguments;return ce.Deferred(function(r){ce.each(o,function(e,t){var n=v(i[t[4]])&&i[t[4]];s[t[1]](function(){var e=n&&n.apply(this,arguments);e&&v(e.promise)?e.promise().progress(r.notify).done(r.resolve).fail(r.reject):r[t[0]+"With"](this,n?[e]:arguments)})}),i=null}).promise()},then:function(t,n,r){var u=0;function l(i,o,a,s){return function(){var n=this,r=arguments,e=function(){var e,t;if(!(i<u)){if((e=a.apply(n,r))===o.promise())throw new TypeError("Thenable self-resolution");t=e&&("object"==typeof e||"function"==typeof e)&&e.then,v(t)?s?t.call(e,l(u,o,N,s),l(u,o,q,s)):(u++,t.call(e,l(u,o,N,s),l(u,o,q,s),l(u,o,N,o.notifyWith))):(a!==N&&(n=void 0,r=[e]),(s||o.resolveWith)(n,r))}},t=s?e:function(){try{e()}catch(e){ce.Deferred.exceptionHook&&ce.Deferred.exceptionHook(e,t.error),u<=i+1&&(a!==q&&(n=void 0,r=[e]),o.rejectWith(n,r))}};i?t():(ce.Deferred.getErrorHook?t.error=ce.Deferred.getErrorHook():ce.Deferred.getStackHook&&(t.error=ce.Deferred.getStackHook()),ie.setTimeout(t))}}return ce.Deferred(function(e){o[0][3].add(l(0,e,v(r)?r:N,e.notifyWith)),o[1][3].add(l(0,e,v(t)?t:N)),o[2][3].add(l(0,e,v(n)?n:q))}).promise()},promise:function(e){return null!=e?ce.extend(e,a):a}},s={};return ce.each(o,function(e,t){var n=t[2],r=t[5];a[t[1]]=n.add,r&&n.add(function(){i=r},o[3-e][2].disable,o[3-e][3].disable,o[0][2].lock,o[0][3].lock),n.add(t[3].fire),s[t[0]]=function(){return s[t[0]+"With"](this===s?void 0:this,arguments),this},s[t[0]+"With"]=n.fireWith}),a.promise(s),e&&e.call(s,s),s},when:function(e){var n=arguments.length,t=n,r=Array(t),i=ae.call(arguments),o=ce.Deferred(),a=function(t){return function(e){r[t]=this,i[t]=1<arguments.length?ae.call(arguments):e,--n||o.resolveWith(r,i)}};if(n<=1&&(L(e,o.done(a(t)).resolve,o.reject,!n),"pending"===o.state()||v(i[t]&&i[t].then)))return o.then();while(t--)L(i[t],a(t),o.reject);return o.promise()}});var H=/^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/;ce.Deferred.exceptionHook=function(e,t){ie.console&&ie.console.warn&&e&&H.test(e.name)&&ie.console.warn("jQuery.Deferred exception: "+e.message,e.stack,t)},ce.readyException=function(e){ie.setTimeout(function(){throw e})};var O=ce.Deferred();function P(){C.removeEventListener("DOMContentLoaded",P),ie.removeEventListener("load",P),ce.ready()}ce.fn.ready=function(e){return O.then(e)["catch"](function(e){ce.readyException(e)}),this},ce.extend({isReady:!1,readyWait:1,ready:function(e){(!0===e?--ce.readyWait:ce.isReady)||(ce.isReady=!0)!==e&&0<--ce.readyWait||O.resolveWith(C,[ce])}}),ce.ready.then=O.then,"complete"===C.readyState||"loading"!==C.readyState&&!C.documentElement.doScroll?ie.setTimeout(ce.ready):(C.addEventListener("DOMContentLoaded",P),ie.addEventListener("load",P));var M=function(e,t,n,r,i,o,a){var s=0,u=e.length,l=null==n;if("object"===x(n))for(s in i=!0,n)M(e,t,s,n[s],!0,o,a);else if(void 0!==r&&(i=!0,v(r)||(a=!0),l&&(a?(t.call(e,r),t=null):(l=t,t=function(e,t,n){return l.call(ce(e),n)})),t))for(;s<u;s++)t(e[s],n,a?r:r.call(e[s],s,t(e[s],n)));return i?e:l?t.call(e):u?t(e[0],n):o},R=/^-ms-/,I=/-([a-z])/g;function W(e,t){return t.toUpperCase()}function F(e){return e.replace(R,"ms-").replace(I,W)}var $=function(e){return 1===e.nodeType||9===e.nodeType||!+e.nodeType};function B(){this.expando=ce.expando+B.uid++}B.uid=1,B.prototype={cache:function(e){var t=e[this.expando];return t||(t={},$(e)&&(e.nodeType?e[this.expando]=t:Object.defineProperty(e,this.expando,{value:t,configurable:!0}))),t},set:function(e,t,n){var r,i=this.cache(e);if("string"==typeof t)i[F(t)]=n;else for(r in t)i[F(r)]=t[r];return i},get:function(e,t){return void 0===t?this.cache(e):e[this.expando]&&e[this.expando][F(t)]},access:function(e,t,n){return void 0===t||t&&"string"==typeof t&&void 0===n?this.get(e,t):(this.set(e,t,n),void 0!==n?n:t)},remove:function(e,t){var n,r=e[this.expando];if(void 0!==r){if(void 0!==t){n=(t=Array.isArray(t)?t.map(F):(t=F(t))in r?[t]:t.match(D)||[]).length;while(n--)delete r[t[n]]}(void 0===t||ce.isEmptyObject(r))&&(e.nodeType?e[this.expando]=void 0:delete e[this.expando])}},hasData:function(e){var t=e[this.expando];return void 0!==t&&!ce.isEmptyObject(t)}};var _=new B,z=new B,X=/^(?:\{[\w\W]*\}|\[[\w\W]*\])$/,U=/[A-Z]/g;function V(e,t,n){var r,i;if(void 0===n&&1===e.nodeType)if(r="data-"+t.replace(U,"-$&").toLowerCase(),"string"==typeof(n=e.getAttribute(r))){try{n="true"===(i=n)||"false"!==i&&("null"===i?null:i===+i+""?+i:X.test(i)?JSON.parse(i):i)}catch(e){}z.set(e,t,n)}else n=void 0;return n}ce.extend({hasData:function(e){return z.hasData(e)||_.hasData(e)},data:function(e,t,n){return z.access(e,t,n)},removeData:function(e,t){z.remove(e,t)},_data:function(e,t,n){return _.access(e,t,n)},_removeData:function(e,t){_.remove(e,t)}}),ce.fn.extend({data:function(n,e){var t,r,i,o=this[0],a=o&&o.attributes;if(void 0===n){if(this.length&&(i=z.get(o),1===o.nodeType&&!_.get(o,"hasDataAttrs"))){t=a.length;while(t--)a[t]&&0===(r=a[t].name).indexOf("data-")&&(r=F(r.slice(5)),V(o,r,i[r]));_.set(o,"hasDataAttrs",!0)}return i}return"object"==typeof n?this.each(function(){z.set(this,n)}):M(this,function(e){var t;if(o&&void 0===e)return void 0!==(t=z.get(o,n))?t:void 0!==(t=V(o,n))?t:void 0;this.each(function(){z.set(this,n,e)})},null,e,1<arguments.length,null,!0)},removeData:function(e){return this.each(function(){z.remove(this,e)})}}),ce.extend({queue:function(e,t,n){var r;if(e)return t=(t||"fx")+"queue",r=_.get(e,t),n&&(!r||Array.isArray(n)?r=_.access(e,t,ce.makeArray(n)):r.push(n)),r||[]},dequeue:function(e,t){t=t||"fx";var n=ce.queue(e,t),r=n.length,i=n.shift(),o=ce._queueHooks(e,t);"inprogress"===i&&(i=n.shift(),r--),i&&("fx"===t&&n.unshift("inprogress"),delete o.stop,i.call(e,function(){ce.dequeue(e,t)},o)),!r&&o&&o.empty.fire()},_queueHooks:function(e,t){var n=t+"queueHooks";return _.get(e,n)||_.access(e,n,{empty:ce.Callbacks("once memory").add(function(){_.remove(e,[t+"queue",n])})})}}),ce.fn.extend({queue:function(t,n){var e=2;return"string"!=typeof t&&(n=t,t="fx",e--),arguments.length<e?ce.queue(this[0],t):void 0===n?this:this.each(function(){var e=ce.queue(this,t,n);ce._queueHooks(this,t),"fx"===t&&"inprogress"!==e[0]&&ce.dequeue(this,t)})},dequeue:function(e){return this.each(function(){ce.dequeue(this,e)})},clearQueue:function(e){return this.queue(e||"fx",[])},promise:function(e,t){var n,r=1,i=ce.Deferred(),o=this,a=this.length,s=function(){--r||i.resolveWith(o,[o])};"string"!=typeof e&&(t=e,e=void 0),e=e||"fx";while(a--)(n=_.get(o[a],e+"queueHooks"))&&n.empty&&(r++,n.empty.add(s));return s(),i.promise(t)}});var G=/[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/.source,Y=new RegExp("^(?:([+-])=|)("+G+")([a-z%]*)$","i"),Q=["Top","Right","Bottom","Left"],J=C.documentElement,K=function(e){return ce.contains(e.ownerDocument,e)},Z={composed:!0};J.getRootNode&&(K=function(e){return ce.contains(e.ownerDocument,e)||e.getRootNode(Z)===e.ownerDocument});var ee=function(e,t){return"none"===(e=t||e).style.display||""===e.style.display&&K(e)&&"none"===ce.css(e,"display")};function te(e,t,n,r){var i,o,a=20,s=r?function(){return r.cur()}:function(){return ce.css(e,t,"")},u=s(),l=n&&n[3]||(ce.cssNumber[t]?"":"px"),c=e.nodeType&&(ce.cssNumber[t]||"px"!==l&&+u)&&Y.exec(ce.css(e,t));if(c&&c[3]!==l){u/=2,l=l||c[3],c=+u||1;while(a--)ce.style(e,t,c+l),(1-o)*(1-(o=s()/u||.5))<=0&&(a=0),c/=o;c*=2,ce.style(e,t,c+l),n=n||[]}return n&&(c=+c||+u||0,i=n[1]?c+(n[1]+1)*n[2]:+n[2],r&&(r.unit=l,r.start=c,r.end=i)),i}var ne={};function re(e,t){for(var n,r,i,o,a,s,u,l=[],c=0,f=e.length;c<f;c++)(r=e[c]).style&&(n=r.style.display,t?("none"===n&&(l[c]=_.get(r,"display")||null,l[c]||(r.style.display="")),""===r.style.display&&ee(r)&&(l[c]=(u=a=o=void 0,a=(i=r).ownerDocument,s=i.nodeName,(u=ne[s])||(o=a.body.appendChild(a.createElement(s)),u=ce.css(o,"display"),o.parentNode.removeChild(o),"none"===u&&(u="block"),ne[s]=u)))):"none"!==n&&(l[c]="none",_.set(r,"display",n)));for(c=0;c<f;c++)null!=l[c]&&(e[c].style.display=l[c]);return e}ce.fn.extend({show:function(){return re(this,!0)},hide:function(){return re(this)},toggle:function(e){return"boolean"==typeof e?e?this.show():this.hide():this.each(function(){ee(this)?ce(this).show():ce(this).hide()})}});var xe,be,we=/^(?:checkbox|radio)$/i,Te=/<([a-z][^\/\0>\x20\t\r\n\f]*)/i,Ce=/^$|^module$|\/(?:java|ecma)script/i;xe=C.createDocumentFragment().appendChild(C.createElement("div")),(be=C.createElement("input")).setAttribute("type","radio"),be.setAttribute("checked","checked"),be.setAttribute("name","t"),xe.appendChild(be),le.checkClone=xe.cloneNode(!0).cloneNode(!0).lastChild.checked,xe.innerHTML="<textarea>x</textarea>",le.noCloneChecked=!!xe.cloneNode(!0).lastChild.defaultValue,xe.innerHTML="<option></option>",le.option=!!xe.lastChild;var ke={thead:[1,"<table>","</table>"],col:[2,"<table><colgroup>","</colgroup></table>"],tr:[2,"<table><tbody>","</tbody></table>"],td:[3,"<table><tbody><tr>","</tr></tbody></table>"],_default:[0,"",""]};function Se(e,t){var n;return n="undefined"!=typeof e.getElementsByTagName?e.getElementsByTagName(t||"*"):"undefined"!=typeof e.querySelectorAll?e.querySelectorAll(t||"*"):[],void 0===t||t&&fe(e,t)?ce.merge([e],n):n}function Ee(e,t){for(var n=0,r=e.length;n<r;n++)_.set(e[n],"globalEval",!t||_.get(t[n],"globalEval"))}ke.tbody=ke.tfoot=ke.colgroup=ke.caption=ke.thead,ke.th=ke.td,le.option||(ke.optgroup=ke.option=[1,"<select multiple='multiple'>","</select>"]);var je=/<|&#?\w+;/;function Ae(e,t,n,r,i){for(var o,a,s,u,l,c,f=t.createDocumentFragment(),p=[],d=0,h=e.length;d<h;d++)if((o=e[d])||0===o)if("object"===x(o))ce.merge(p,o.nodeType?[o]:o);else if(je.test(o)){a=a||f.appendChild(t.createElement("div")),s=(Te.exec(o)||["",""])[1].toLowerCase(),u=ke[s]||ke._default,a.innerHTML=u[1]+ce.htmlPrefilter(o)+u[2],c=u[0];while(c--)a=a.lastChild;ce.merge(p,a.childNodes),(a=f.firstChild).textContent=""}else p.push(t.createTextNode(o));f.textContent="",d=0;while(o=p[d++])if(r&&-1<ce.inArray(o,r))i&&i.push(o);else if(l=K(o),a=Se(f.appendChild(o),"script"),l&&Ee(a),n){c=0;while(o=a[c++])Ce.test(o.type||"")&&n.push(o)}return f}var De=/^([^.]*)(?:\.(.+)|)/;function Ne(){return!0}function qe(){return!1}function Le(e,t,n,r,i,o){var a,s;if("object"==typeof t){for(s in"string"!=typeof n&&(r=r||n,n=void 0),t)Le(e,s,n,r,t[s],o);return e}if(null==r&&null==i?(i=n,r=n=void 0):null==i&&("string"==typeof n?(i=r,r=void 0):(i=r,r=n,n=void 0)),!1===i)i=qe;else if(!i)return e;return 1===o&&(a=i,(i=function(e){return ce().off(e),a.apply(this,arguments)}).guid=a.guid||(a.guid=ce.guid++)),e.each(function(){ce.event.add(this,t,i,r,n)})}function He(e,r,t){t?(_.set(e,r,!1),ce.event.add(e,r,{namespace:!1,handler:function(e){var t,n=_.get(this,r);if(1&e.isTrigger&&this[r]){if(n)(ce.event.special[r]||{}).delegateType&&e.stopPropagation();else if(n=ae.call(arguments),_.set(this,r,n),this[r](),t=_.get(this,r),_.set(this,r,!1),n!==t)return e.stopImmediatePropagation(),e.preventDefault(),t}else n&&(_.set(this,r,ce.event.trigger(n[0],n.slice(1),this)),e.stopPropagation(),e.isImmediatePropagationStopped=Ne)}})):void 0===_.get(e,r)&&ce.event.add(e,r,Ne)}ce.event={global:{},add:function(t,e,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=_.get(t);if($(t)){n.handler&&(n=(o=n).handler,i=o.selector),i&&ce.find.matchesSelector(J,i),n.guid||(n.guid=ce.guid++),(u=v.events)||(u=v.events=Object.create(null)),(a=v.handle)||(a=v.handle=function(e){return"undefined"!=typeof ce&&ce.event.triggered!==e.type?ce.event.dispatch.apply(t,arguments):void 0}),l=(e=(e||"").match(D)||[""]).length;while(l--)d=g=(s=De.exec(e[l])||[])[1],h=(s[2]||"").split(".").sort(),d&&(f=ce.event.special[d]||{},d=(i?f.delegateType:f.bindType)||d,f=ce.event.special[d]||{},c=ce.extend({type:d,origType:g,data:r,handler:n,guid:n.guid,selector:i,needsContext:i&&ce.expr.match.needsContext.test(i),namespace:h.join(".")},o),(p=u[d])||((p=u[d]=[]).delegateCount=0,f.setup&&!1!==f.setup.call(t,r,h,a)||t.addEventListener&&t.addEventListener(d,a)),f.add&&(f.add.call(t,c),c.handler.guid||(c.handler.guid=n.guid)),i?p.splice(p.delegateCount++,0,c):p.push(c),ce.event.global[d]=!0)}},remove:function(e,t,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=_.hasData(e)&&_.get(e);if(v&&(u=v.events)){l=(t=(t||"").match(D)||[""]).length;while(l--)if(d=g=(s=De.exec(t[l])||[])[1],h=(s[2]||"").split(".").sort(),d){f=ce.event.special[d]||{},p=u[d=(r?f.delegateType:f.bindType)||d]||[],s=s[2]&&new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"),a=o=p.length;while(o--)c=p[o],!i&&g!==c.origType||n&&n.guid!==c.guid||s&&!s.test(c.namespace)||r&&r!==c.selector&&("**"!==r||!c.selector)||(p.splice(o,1),c.selector&&p.delegateCount--,f.remove&&f.remove.call(e,c));a&&!p.length&&(f.teardown&&!1!==f.teardown.call(e,h,v.handle)||ce.removeEvent(e,d,v.handle),delete u[d])}else for(d in u)ce.event.remove(e,d+t[l],n,r,!0);ce.isEmptyObject(u)&&_.remove(e,"handle events")}},dispatch:function(e){var t,n,r,i,o,a,s=new Array(arguments.length),u=ce.event.fix(e),l=(_.get(this,"events")||Object.create(null))[u.type]||[],c=ce.event.special[u.type]||{};for(s[0]=u,t=1;t<arguments.length;t++)s[t]=arguments[t];if(u.delegateTarget=this,!c.preDispatch||!1!==c.preDispatch.call(this,u)){a=ce.event.handlers.call(this,u,l),t=0;while((i=a[t++])&&!u.isPropagationStopped()){u.currentTarget=i.elem,n=0;while((o=i.handlers[n++])&&!u.isImmediatePropagationStopped())u.rnamespace&&!1!==o.namespace&&!u.rnamespace.test(o.namespace)||(u.handleObj=o,u.data=o.data,void 0!==(r=((ce.event.special[o.origType]||{}).handle||o.handler).apply(i.elem,s))&&!1===(u.result=r)&&(u.preventDefault(),u.stopPropagation()))}return c.postDispatch&&c.postDispatch.call(this,u),u.result}},handlers:function(e,t){var n,r,i,o,a,s=[],u=t.delegateCount,l=e.target;if(u&&l.nodeType&&!("click"===e.type&&1<=e.button))for(;l!==this;l=l.parentNode||this)if(1===l.nodeType&&("click"!==e.type||!0!==l.disabled)){for(o=[],a={},n=0;n<u;n++)void 0===a[i=(r=t[n]).selector+" "]&&(a[i]=r.needsContext?-1<ce(i,this).index(l):ce.find(i,this,null,[l]).length),a[i]&&o.push(r);o.length&&s.push({elem:l,handlers:o})}return l=this,u<t.length&&s.push({elem:l,handlers:t.slice(u)}),s},addProp:function(t,e){Object.defineProperty(ce.Event.prototype,t,{enumerable:!0,configurable:!0,get:v(e)?function(){if(this.originalEvent)return e(this.originalEvent)}:function(){if(this.originalEvent)return this.originalEvent[t]},set:function(e){Object.defineProperty(this,t,{enumerable:!0,configurable:!0,writable:!0,value:e})}})},fix:function(e){return e[ce.expando]?e:new ce.Event(e)},special:{load:{noBubble:!0},click:{setup:function(e){var t=this||e;return we.test(t.type)&&t.click&&fe(t,"input")&&He(t,"click",!0),!1},trigger:function(e){var t=this||e;return we.test(t.type)&&t.click&&fe(t,"input")&&He(t,"click"),!0},_default:function(e){var t=e.target;return we.test(t.type)&&t.click&&fe(t,"input")&&_.get(t,"click")||fe(t,"a")}},beforeunload:{postDispatch:function(e){void 0!==e.result&&e.originalEvent&&(e.originalEvent.returnValue=e.result)}}}},ce.removeEvent=function(e,t,n){e.removeEventListener&&e.removeEventListener(t,n)},ce.Event=function(e,t){if(!(this instanceof ce.Event))return new ce.Event(e,t);e&&e.type?(this.originalEvent=e,this.type=e.type,this.isDefaultPrevented=e.defaultPrevented||void 0===e.defaultPrevented&&!1===e.returnValue?Ne:qe,this.target=e.target&&3===e.target.nodeType?e.target.parentNode:e.target,this.currentTarget=e.currentTarget,this.relatedTarget=e.relatedTarget):this.type=e,t&&ce.extend(this,t),this.timeStamp=e&&e.timeStamp||Date.now(),this[ce.expando]=!0},ce.Event.prototype={constructor:ce.Event,isDefaultPrevented:qe,isPropagationStopped:qe,isImmediatePropagationStopped:qe,isSimulated:!1,preventDefault:function(){var e=this.originalEvent;this.isDefaultPrevented=Ne,e&&!this.isSimulated&&e.preventDefault()},stopPropagation:function(){var e=this.originalEvent;this.isPropagationStopped=Ne,e&&!this.isSimulated&&e.stopPropagation()},stopImmediatePropagation:function(){var e=this.originalEvent;this.isImmediatePropagationStopped=Ne,e&&!this.isSimulated&&e.stopImmediatePropagation(),this.stopPropagation()}},ce.each({altKey:!0,bubbles:!0,cancelable:!0,changedTouches:!0,ctrlKey:!0,detail:!0,eventPhase:!0,metaKey:!0,pageX:!0,pageY:!0,shiftKey:!0,view:!0,"char":!0,code:!0,charCode:!0,key:!0,keyCode:!0,button:!0,buttons:!0,clientX:!0,clientY:!0,offsetX:!0,offsetY:!0,pointerId:!0,pointerType:!0,screenX:!0,screenY:!0,targetTouches:!0,toElement:!0,touches:!0,which:!0},ce.event.addProp),ce.each({focus:"focusin",blur:"focusout"},function(r,i){function o(e){if(C.documentMode){var t=_.get(this,"handle"),n=ce.event.fix(e);n.type="focusin"===e.type?"focus":"blur",n.isSimulated=!0,t(e),n.target===n.currentTarget&&t(n)}else ce.event.simulate(i,e.target,ce.event.fix(e))}ce.event.special[r]={setup:function(){var e;if(He(this,r,!0),!C.documentMode)return!1;(e=_.get(this,i))||this.addEventListener(i,o),_.set(this,i,(e||0)+1)},trigger:function(){return He(this,r),!0},teardown:function(){var e;if(!C.documentMode)return!1;(e=_.get(this,i)-1)?_.set(this,i,e):(this.removeEventListener(i,o),_.remove(this,i))},_default:function(e){return _.get(e.target,r)},delegateType:i},ce.event.special[i]={setup:function(){var e=this.ownerDocument||this.document||this,t=C.documentMode?this:e,n=_.get(t,i);n||(C.documentMode?this.addEventListener(i,o):e.addEventListener(r,o,!0)),_.set(t,i,(n||0)+1)},teardown:function(){var e=this.ownerDocument||this.document||this,t=C.documentMode?this:e,n=_.get(t,i)-1;n?_.set(t,i,n):(C.documentMode?this.removeEventListener(i,o):e.removeEventListener(r,o,!0),_.remove(t,i))}}}),ce.each({mouseenter:"mouseover",mouseleave:"mouseout",pointerenter:"pointerover",pointerleave:"pointerout"},function(e,i){ce.event.special[e]={delegateType:i,bindType:i,handle:function(e){var t,n=e.relatedTarget,r=e.handleObj;return n&&(n===this||ce.contains(this,n))||(e.type=r.origType,t=r.handler.apply(this,arguments),e.type=i),t}}}),ce.fn.extend({on:function(e,t,n,r){return Le(this,e,t,n,r)},one:function(e,t,n,r){return Le(this,e,t,n,r,1)},off:function(e,t,n){var r,i;if(e&&e.preventDefault&&e.handleObj)return r=e.handleObj,ce(e.delegateTarget).off(r.namespace?r.origType+"."+r.namespace:r.origType,r.selector,r.handler),this;if("object"==typeof e){for(i in e)this.off(i,t,e[i]);return this}return!1!==t&&"function"!=typeof t||(n=t,t=void 0),!1===n&&(n=qe),this.each(function(){ce.event.remove(this,e,n,t)})}});var Oe=/<script|<style|<link/i,Pe=/checked\s*(?:[^=]|=\s*.checked.)/i,Me=/^\s*<!\[CDATA\[|\]\]>\s*$/g;function Re(e,t){return fe(e,"table")&&fe(11!==t.nodeType?t:t.firstChild,"tr")&&ce(e).children("tbody")[0]||e}function Ie(e){return e.type=(null!==e.getAttribute("type"))+"/"+e.type,e}function We(e){return"true/"===(e.type||"").slice(0,5)?e.type=e.type.slice(5):e.removeAttribute("type"),e}function Fe(e,t){var n,r,i,o,a,s;if(1===t.nodeType){if(_.hasData(e)&&(s=_.get(e).events))for(i in _.remove(t,"handle events"),s)for(n=0,r=s[i].length;n<r;n++)ce.event.add(t,i,s[i][n]);z.hasData(e)&&(o=z.access(e),a=ce.extend({},o),z.set(t,a))}}function $e(n,r,i,o){r=g(r);var e,t,a,s,u,l,c=0,f=n.length,p=f-1,d=r[0],h=v(d);if(h||1<f&&"string"==typeof d&&!le.checkClone&&Pe.test(d))return n.each(function(e){var t=n.eq(e);h&&(r[0]=d.call(this,e,t.html())),$e(t,r,i,o)});if(f&&(t=(e=Ae(r,n[0].ownerDocument,!1,n,o)).firstChild,1===e.childNodes.length&&(e=t),t||o)){for(s=(a=ce.map(Se(e,"script"),Ie)).length;c<f;c++)u=e,c!==p&&(u=ce.clone(u,!0,!0),s&&ce.merge(a,Se(u,"script"))),i.call(n[c],u,c);if(s)for(l=a[a.length-1].ownerDocument,ce.map(a,We),c=0;c<s;c++)u=a[c],Ce.test(u.type||"")&&!_.access(u,"globalEval")&&ce.contains(l,u)&&(u.src&&"module"!==(u.type||"").toLowerCase()?ce._evalUrl&&!u.noModule&&ce._evalUrl(u.src,{nonce:u.nonce||u.getAttribute("nonce")},l):m(u.textContent.replace(Me,""),u,l))}return n}function Be(e,t,n){for(var r,i=t?ce.filter(t,e):e,o=0;null!=(r=i[o]);o++)n||1!==r.nodeType||ce.cleanData(Se(r)),r.parentNode&&(n&&K(r)&&Ee(Se(r,"script")),r.parentNode.removeChild(r));return e}ce.extend({htmlPrefilter:function(e){return e},clone:function(e,t,n){var r,i,o,a,s,u,l,c=e.cloneNode(!0),f=K(e);if(!(le.noCloneChecked||1!==e.nodeType&&11!==e.nodeType||ce.isXMLDoc(e)))for(a=Se(c),r=0,i=(o=Se(e)).length;r<i;r++)s=o[r],u=a[r],void 0,"input"===(l=u.nodeName.toLowerCase())&&we.test(s.type)?u.checked=s.checked:"input"!==l&&"textarea"!==l||(u.defaultValue=s.defaultValue);if(t)if(n)for(o=o||Se(e),a=a||Se(c),r=0,i=o.length;r<i;r++)Fe(o[r],a[r]);else Fe(e,c);return 0<(a=Se(c,"script")).length&&Ee(a,!f&&Se(e,"script")),c},cleanData:function(e){for(var t,n,r,i=ce.event.special,o=0;void 0!==(n=e[o]);o++)if($(n)){if(t=n[_.expando]){if(t.events)for(r in t.events)i[r]?ce.event.remove(n,r):ce.removeEvent(n,r,t.handle);n[_.expando]=void 0}n[z.expando]&&(n[z.expando]=void 0)}}}),ce.fn.extend({detach:function(e){return Be(this,e,!0)},remove:function(e){return Be(this,e)},text:function(e){return M(this,function(e){return void 0===e?ce.text(this):this.empty().each(function(){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||(this.textContent=e)})},null,e,arguments.length)},append:function(){return $e(this,arguments,function(e){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||Re(this,e).appendChild(e)})},prepend:function(){return $e(this,arguments,function(e){if(1===this.nodeType||11===this.nodeType||9===this.nodeType){var t=Re(this,e);t.insertBefore(e,t.firstChild)}})},before:function(){return $e(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this)})},after:function(){return $e(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this.nextSibling)})},empty:function(){for(var e,t=0;null!=(e=this[t]);t++)1===e.nodeType&&(ce.cleanData(Se(e,!1)),e.textContent="");return this},clone:function(e,t){return e=null!=e&&e,t=null==t?e:t,this.map(function(){return ce.clone(this,e,t)})},html:function(e){return M(this,function(e){var t=this[0]||{},n=0,r=this.length;if(void 0===e&&1===t.nodeType)return t.innerHTML;if("string"==typeof e&&!Oe.test(e)&&!ke[(Te.exec(e)||["",""])[1].toLowerCase()]){e=ce.htmlPrefilter(e);try{for(;n<r;n++)1===(t=this[n]||{}).nodeType&&(ce.cleanData(Se(t,!1)),t.innerHTML=e);t=0}catch(e){}}t&&this.empty().append(e)},null,e,arguments.length)},replaceWith:function(){var n=[];return $e(this,arguments,function(e){var t=this.parentNode;ce.inArray(this,n)<0&&(ce.cleanData(Se(this)),t&&t.replaceChild(e,this))},n)}}),ce.each({appendTo:"append",prependTo:"prepend",insertBefore:"before",insertAfter:"after",replaceAll:"replaceWith"},function(e,a){ce.fn[e]=function(e){for(var t,n=[],r=ce(e),i=r.length-1,o=0;o<=i;o++)t=o===i?this:this.clone(!0),ce(r[o])[a](t),s.apply(n,t.get());return this.pushStack(n)}});var _e=new RegExp("^("+G+")(?!px)[a-z%]+$","i"),ze=/^--/,Xe=function(e){var t=e.ownerDocument.defaultView;return t&&t.opener||(t=ie),t.getComputedStyle(e)},Ue=function(e,t,n){var r,i,o={};for(i in t)o[i]=e.style[i],e.style[i]=t[i];for(i in r=n.call(e),t)e.style[i]=o[i];return r},Ve=new RegExp(Q.join("|"),"i");function Ge(e,t,n){var r,i,o,a,s=ze.test(t),u=e.style;return(n=n||Xe(e))&&(a=n.getPropertyValue(t)||n[t],s&&a&&(a=a.replace(ve,"$1")||void 0),""!==a||K(e)||(a=ce.style(e,t)),!le.pixelBoxStyles()&&_e.test(a)&&Ve.test(t)&&(r=u.width,i=u.minWidth,o=u.maxWidth,u.minWidth=u.maxWidth=u.width=a,a=n.width,u.width=r,u.minWidth=i,u.maxWidth=o)),void 0!==a?a+"":a}function Ye(e,t){return{get:function(){if(!e())return(this.get=t).apply(this,arguments);delete this.get}}}!function(){function e(){if(l){u.style.cssText="position:absolute;left:-11111px;width:60px;margin-top:1px;padding:0;border:0",l.style.cssText="position:relative;display:block;box-sizing:border-box;overflow:scroll;margin:auto;border:1px;padding:1px;width:60%;top:1%",J.appendChild(u).appendChild(l);var e=ie.getComputedStyle(l);n="1%"!==e.top,s=12===t(e.marginLeft),l.style.right="60%",o=36===t(e.right),r=36===t(e.width),l.style.position="absolute",i=12===t(l.offsetWidth/3),J.removeChild(u),l=null}}function t(e){return Math.round(parseFloat(e))}var n,r,i,o,a,s,u=C.createElement("div"),l=C.createElement("div");l.style&&(l.style.backgroundClip="content-box",l.cloneNode(!0).style.backgroundClip="",le.clearCloneStyle="content-box"===l.style.backgroundClip,ce.extend(le,{boxSizingReliable:function(){return e(),r},pixelBoxStyles:function(){return e(),o},pixelPosition:function(){return e(),n},reliableMarginLeft:function(){return e(),s},scrollboxSize:function(){return e(),i},reliableTrDimensions:function(){var e,t,n,r;return null==a&&(e=C.createElement("table"),t=C.createElement("tr"),n=C.createElement("div"),e.style.cssText="position:absolute;left:-11111px;border-collapse:separate",t.style.cssText="box-sizing:content-box;border:1px solid",t.style.height="1px",n.style.height="9px",n.style.display="block",J.appendChild(e).appendChild(t).appendChild(n),r=ie.getComputedStyle(t),a=parseInt(r.height,10)+parseInt(r.borderTopWidth,10)+parseInt(r.borderBottomWidth,10)===t.offsetHeight,J.removeChild(e)),a}}))}();var Qe=["Webkit","Moz","ms"],Je=C.createElement("div").style,Ke={};function Ze(e){var t=ce.cssProps[e]||Ke[e];return t||(e in Je?e:Ke[e]=function(e){var t=e[0].toUpperCase()+e.slice(1),n=Qe.length;while(n--)if((e=Qe[n]+t)in Je)return e}(e)||e)}var et=/^(none|table(?!-c[ea]).+)/,tt={position:"absolute",visibility:"hidden",display:"block"},nt={letterSpacing:"0",fontWeight:"400"};function rt(e,t,n){var r=Y.exec(t);return r?Math.max(0,r[2]-(n||0))+(r[3]||"px"):t}function it(e,t,n,r,i,o){var a="width"===t?1:0,s=0,u=0,l=0;if(n===(r?"border":"content"))return 0;for(;a<4;a+=2)"margin"===n&&(l+=ce.css(e,n+Q[a],!0,i)),r?("content"===n&&(u-=ce.css(e,"padding"+Q[a],!0,i)),"margin"!==n&&(u-=ce.css(e,"border"+Q[a]+"Width",!0,i))):(u+=ce.css(e,"padding"+Q[a],!0,i),"padding"!==n?u+=ce.css(e,"border"+Q[a]+"Width",!0,i):s+=ce.css(e,"border"+Q[a]+"Width",!0,i));return!r&&0<=o&&(u+=Math.max(0,Math.ceil(e["offset"+t[0].toUpperCase()+t.slice(1)]-o-u-s-.5))||0),u+l}function ot(e,t,n){var r=Xe(e),i=(!le.boxSizingReliable()||n)&&"border-box"===ce.css(e,"boxSizing",!1,r),o=i,a=Ge(e,t,r),s="offset"+t[0].toUpperCase()+t.slice(1);if(_e.test(a)){if(!n)return a;a="auto"}return(!le.boxSizingReliable()&&i||!le.reliableTrDimensions()&&fe(e,"tr")||"auto"===a||!parseFloat(a)&&"inline"===ce.css(e,"display",!1,r))&&e.getClientRects().length&&(i="border-box"===ce.css(e,"boxSizing",!1,r),(o=s in e)&&(a=e[s])),(a=parseFloat(a)||0)+it(e,t,n||(i?"border":"content"),o,r,a)+"px"}function at(e,t,n,r,i){return new at.prototype.init(e,t,n,r,i)}ce.extend({cssHooks:{opacity:{get:function(e,t){if(t){var n=Ge(e,"opacity");return""===n?"1":n}}}},cssNumber:{animationIterationCount:!0,aspectRatio:!0,borderImageSlice:!0,columnCount:!0,flexGrow:!0,flexShrink:!0,fontWeight:!0,gridArea:!0,gridColumn:!0,gridColumnEnd:!0,gridColumnStart:!0,gridRow:!0,gridRowEnd:!0,gridRowStart:!0,lineHeight:!0,opacity:!0,order:!0,orphans:!0,scale:!0,widows:!0,zIndex:!0,zoom:!0,fillOpacity:!0,floodOpacity:!0,stopOpacity:!0,strokeMiterlimit:!0,strokeOpacity:!0},cssProps:{},style:function(e,t,n,r){if(e&&3!==e.nodeType&&8!==e.nodeType&&e.style){var i,o,a,s=F(t),u=ze.test(t),l=e.style;if(u||(t=Ze(s)),a=ce.cssHooks[t]||ce.cssHooks[s],void 0===n)return a&&"get"in a&&void 0!==(i=a.get(e,!1,r))?i:l[t];"string"===(o=typeof n)&&(i=Y.exec(n))&&i[1]&&(n=te(e,t,i),o="number"),null!=n&&n==n&&("number"!==o||u||(n+=i&&i[3]||(ce.cssNumber[s]?"":"px")),le.clearCloneStyle||""!==n||0!==t.indexOf("background")||(l[t]="inherit"),a&&"set"in a&&void 0===(n=a.set(e,n,r))||(u?l.setProperty(t,n):l[t]=n))}},css:function(e,t,n,r){var i,o,a,s=F(t);return ze.test(t)||(t=Ze(s)),(a=ce.cssHooks[t]||ce.cssHooks[s])&&"get"in a&&(i=a.get(e,!0,n)),void 0===i&&(i=Ge(e,t,r)),"normal"===i&&t in nt&&(i=nt[t]),""===n||n?(o=parseFloat(i),!0===n||isFinite(o)?o||0:i):i}}),ce.each(["height","width"],function(e,u){ce.cssHooks[u]={get:function(e,t,n){if(t)return!et.test(ce.css(e,"display"))||e.getClientRects().length&&e.getBoundingClientRect().width?ot(e,u,n):Ue(e,tt,function(){return ot(e,u,n)})},set:function(e,t,n){var r,i=Xe(e),o=!le.scrollboxSize()&&"absolute"===i.position,a=(o||n)&&"border-box"===ce.css(e,"boxSizing",!1,i),s=n?it(e,u,n,a,i):0;return a&&o&&(s-=Math.ceil(e["offset"+u[0].toUpperCase()+u.slice(1)]-parseFloat(i[u])-it(e,u,"border",!1,i)-.5)),s&&(r=Y.exec(t))&&"px"!==(r[3]||"px")&&(e.style[u]=t,t=ce.css(e,u)),rt(0,t,s)}}}),ce.cssHooks.marginLeft=Ye(le.reliableMarginLeft,function(e,t){if(t)return(parseFloat(Ge(e,"marginLeft"))||e.getBoundingClientRect().left-Ue(e,{marginLeft:0},function(){return e.getBoundingClientRect().left}))+"px"}),ce.each({margin:"",padding:"",border:"Width"},function(i,o){ce.cssHooks[i+o]={expand:function(e){for(var t=0,n={},r="string"==typeof e?e.split(" "):[e];t<4;t++)n[i+Q[t]+o]=r[t]||r[t-2]||r[0];return n}},"margin"!==i&&(ce.cssHooks[i+o].set=rt)}),ce.fn.extend({css:function(e,t){return M(this,function(e,t,n){var r,i,o={},a=0;if(Array.isArray(t)){for(r=Xe(e),i=t.length;a<i;a++)o[t[a]]=ce.css(e,t[a],!1,r);return o}return void 0!==n?ce.style(e,t,n):ce.css(e,t)},e,t,1<arguments.length)}}),((ce.Tween=at).prototype={constructor:at,init:function(e,t,n,r,i,o){this.elem=e,this.prop=n,this.easing=i||ce.easing._default,this.options=t,this.start=this.now=this.cur(),this.end=r,this.unit=o||(ce.cssNumber[n]?"":"px")},cur:function(){var e=at.propHooks[this.prop];return e&&e.get?e.get(this):at.propHooks._default.get(this)},run:function(e){var t,n=at.propHooks[this.prop];return this.options.duration?this.pos=t=ce.easing[this.easing](e,this.options.duration*e,0,1,this.options.duration):this.pos=t=e,this.now=(this.end-this.start)*t+this.start,this.options.step&&this.options.step.call(this.elem,this.now,this),n&&n.set?n.set(this):at.propHooks._default.set(this),this}}).init.prototype=at.prototype,(at.propHooks={_default:{get:function(e){var t;return 1!==e.elem.nodeType||null!=e.elem[e.prop]&&null==e.elem.style[e.prop]?e.elem[e.prop]:(t=ce.css(e.elem,e.prop,""))&&"auto"!==t?t:0},set:function(e){ce.fx.step[e.prop]?ce.fx.step[e.prop](e):1!==e.elem.nodeType||!ce.cssHooks[e.prop]&&null==e.elem.style[Ze(e.prop)]?e.elem[e.prop]=e.now:ce.style(e.elem,e.prop,e.now+e.unit)}}}).scrollTop=at.propHooks.scrollLeft={set:function(e){e.elem.nodeType&&e.elem.parentNode&&(e.elem[e.prop]=e.now)}},ce.easing={linear:function(e){return e},swing:function(e){return.5-Math.cos(e*Math.PI)/2},_default:"swing"},ce.fx=at.prototype.init,ce.fx.step={};var st,ut,lt,ct,ft=/^(?:toggle|show|hide)$/,pt=/queueHooks$/;function dt(){ut&&(!1===C.hidden&&ie.requestAnimationFrame?ie.requestAnimationFrame(dt):ie.setTimeout(dt,ce.fx.interval),ce.fx.tick())}function ht(){return ie.setTimeout(function(){st=void 0}),st=Date.now()}function gt(e,t){var n,r=0,i={height:e};for(t=t?1:0;r<4;r+=2-t)i["margin"+(n=Q[r])]=i["padding"+n]=e;return t&&(i.opacity=i.width=e),i}function vt(e,t,n){for(var r,i=(yt.tweeners[t]||[]).concat(yt.tweeners["*"]),o=0,a=i.length;o<a;o++)if(r=i[o].call(n,t,e))return r}function yt(o,e,t){var n,a,r=0,i=yt.prefilters.length,s=ce.Deferred().always(function(){delete u.elem}),u=function(){if(a)return!1;for(var e=st||ht(),t=Math.max(0,l.startTime+l.duration-e),n=1-(t/l.duration||0),r=0,i=l.tweens.length;r<i;r++)l.tweens[r].run(n);return s.notifyWith(o,[l,n,t]),n<1&&i?t:(i||s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l]),!1)},l=s.promise({elem:o,props:ce.extend({},e),opts:ce.extend(!0,{specialEasing:{},easing:ce.easing._default},t),originalProperties:e,originalOptions:t,startTime:st||ht(),duration:t.duration,tweens:[],createTween:function(e,t){var n=ce.Tween(o,l.opts,e,t,l.opts.specialEasing[e]||l.opts.easing);return l.tweens.push(n),n},stop:function(e){var t=0,n=e?l.tweens.length:0;if(a)return this;for(a=!0;t<n;t++)l.tweens[t].run(1);return e?(s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l,e])):s.rejectWith(o,[l,e]),this}}),c=l.props;for(!function(e,t){var n,r,i,o,a;for(n in e)if(i=t[r=F(n)],o=e[n],Array.isArray(o)&&(i=o[1],o=e[n]=o[0]),n!==r&&(e[r]=o,delete e[n]),(a=ce.cssHooks[r])&&"expand"in a)for(n in o=a.expand(o),delete e[r],o)n in e||(e[n]=o[n],t[n]=i);else t[r]=i}(c,l.opts.specialEasing);r<i;r++)if(n=yt.prefilters[r].call(l,o,c,l.opts))return v(n.stop)&&(ce._queueHooks(l.elem,l.opts.queue).stop=n.stop.bind(n)),n;return ce.map(c,vt,l),v(l.opts.start)&&l.opts.start.call(o,l),l.progress(l.opts.progress).done(l.opts.done,l.opts.complete).fail(l.opts.fail).always(l.opts.always),ce.fx.timer(ce.extend(u,{elem:o,anim:l,queue:l.opts.queue})),l}ce.Animation=ce.extend(yt,{tweeners:{"*":[function(e,t){var n=this.createTween(e,t);return te(n.elem,e,Y.exec(t),n),n}]},tweener:function(e,t){v(e)?(t=e,e=["*"]):e=e.match(D);for(var n,r=0,i=e.length;r<i;r++)n=e[r],yt.tweeners[n]=yt.tweeners[n]||[],yt.tweeners[n].unshift(t)},prefilters:[function(e,t,n){var r,i,o,a,s,u,l,c,f="width"in t||"height"in t,p=this,d={},h=e.style,g=e.nodeType&&ee(e),v=_.get(e,"fxshow");for(r in n.queue||(null==(a=ce._queueHooks(e,"fx")).unqueued&&(a.unqueued=0,s=a.empty.fire,a.empty.fire=function(){a.unqueued||s()}),a.unqueued++,p.always(function(){p.always(function(){a.unqueued--,ce.queue(e,"fx").length||a.empty.fire()})})),t)if(i=t[r],ft.test(i)){if(delete t[r],o=o||"toggle"===i,i===(g?"hide":"show")){if("show"!==i||!v||void 0===v[r])continue;g=!0}d[r]=v&&v[r]||ce.style(e,r)}if((u=!ce.isEmptyObject(t))||!ce.isEmptyObject(d))for(r in f&&1===e.nodeType&&(n.overflow=[h.overflow,h.overflowX,h.overflowY],null==(l=v&&v.display)&&(l=_.get(e,"display")),"none"===(c=ce.css(e,"display"))&&(l?c=l:(re([e],!0),l=e.style.display||l,c=ce.css(e,"display"),re([e]))),("inline"===c||"inline-block"===c&&null!=l)&&"none"===ce.css(e,"float")&&(u||(p.done(function(){h.display=l}),null==l&&(c=h.display,l="none"===c?"":c)),h.display="inline-block")),n.overflow&&(h.overflow="hidden",p.always(function(){h.overflow=n.overflow[0],h.overflowX=n.overflow[1],h.overflowY=n.overflow[2]})),u=!1,d)u||(v?"hidden"in v&&(g=v.hidden):v=_.access(e,"fxshow",{display:l}),o&&(v.hidden=!g),g&&re([e],!0),p.done(function(){for(r in g||re([e]),_.remove(e,"fxshow"),d)ce.style(e,r,d[r])})),u=vt(g?v[r]:0,r,p),r in v||(v[r]=u.start,g&&(u.end=u.start,u.start=0))}],prefilter:function(e,t){t?yt.prefilters.unshift(e):yt.prefilters.push(e)}}),ce.speed=function(e,t,n){var r=e&&"object"==typeof e?ce.extend({},e):{complete:n||!n&&t||v(e)&&e,duration:e,easing:n&&t||t&&!v(t)&&t};return ce.fx.off?r.duration=0:"number"!=typeof r.duration&&(r.duration in ce.fx.speeds?r.duration=ce.fx.speeds[r.duration]:r.duration=ce.fx.speeds._default),null!=r.queue&&!0!==r.queue||(r.queue="fx"),r.old=r.complete,r.complete=function(){v(r.old)&&r.old.call(this),r.queue&&ce.dequeue(this,r.queue)},r},ce.fn.extend({fadeTo:function(e,t,n,r){return this.filter(ee).css("opacity",0).show().end().animate({opacity:t},e,n,r)},animate:function(t,e,n,r){var i=ce.isEmptyObject(t),o=ce.speed(e,n,r),a=function(){var e=yt(this,ce.extend({},t),o);(i||_.get(this,"finish"))&&e.stop(!0)};return a.finish=a,i||!1===o.queue?this.each(a):this.queue(o.queue,a)},stop:function(i,e,o){var a=function(e){var t=e.stop;delete e.stop,t(o)};return"string"!=typeof i&&(o=e,e=i,i=void 0),e&&this.queue(i||"fx",[]),this.each(function(){var e=!0,t=null!=i&&i+"queueHooks",n=ce.timers,r=_.get(this);if(t)r[t]&&r[t].stop&&a(r[t]);else for(t in r)r[t]&&r[t].stop&&pt.test(t)&&a(r[t]);for(t=n.length;t--;)n[t].elem!==this||null!=i&&n[t].queue!==i||(n[t].anim.stop(o),e=!1,n.splice(t,1));!e&&o||ce.dequeue(this,i)})},finish:function(a){return!1!==a&&(a=a||"fx"),this.each(function(){var e,t=_.get(this),n=t[a+"queue"],r=t[a+"queueHooks"],i=ce.timers,o=n?n.length:0;for(t.finish=!0,ce.queue(this,a,[]),r&&r.stop&&r.stop.call(this,!0),e=i.length;e--;)i[e].elem===this&&i[e].queue===a&&(i[e].anim.stop(!0),i.splice(e,1));for(e=0;e<o;e++)n[e]&&n[e].finish&&n[e].finish.call(this);delete t.finish})}}),ce.each(["toggle","show","hide"],function(e,r){var i=ce.fn[r];ce.fn[r]=function(e,t,n){return null==e||"boolean"==typeof e?i.apply(this,arguments):this.animate(gt(r,!0),e,t,n)}}),ce.each({slideDown:gt("show"),slideUp:gt("hide"),slideToggle:gt("toggle"),fadeIn:{opacity:"show"},fadeOut:{opacity:"hide"},fadeToggle:{opacity:"toggle"}},function(e,r){ce.fn[e]=function(e,t,n){return this.animate(r,e,t,n)}}),ce.timers=[],ce.fx.tick=function(){var e,t=0,n=ce.timers;for(st=Date.now();t<n.length;t++)(e=n[t])()||n[t]!==e||n.splice(t--,1);n.length||ce.fx.stop(),st=void 0},ce.fx.timer=function(e){ce.timers.push(e),ce.fx.start()},ce.fx.interval=13,ce.fx.start=function(){ut||(ut=!0,dt())},ce.fx.stop=function(){ut=null},ce.fx.speeds={slow:600,fast:200,_default:400},ce.fn.delay=function(r,e){return r=ce.fx&&ce.fx.speeds[r]||r,e=e||"fx",this.queue(e,function(e,t){var n=ie.setTimeout(e,r);t.stop=function(){ie.clearTimeout(n)}})},lt=C.createElement("input"),ct=C.createElement("select").appendChild(C.createElement("option")),lt.type="checkbox",le.checkOn=""!==lt.value,le.optSelected=ct.selected,(lt=C.createElement("input")).value="t",lt.type="radio",le.radioValue="t"===lt.value;var mt,xt=ce.expr.attrHandle;ce.fn.extend({attr:function(e,t){return M(this,ce.attr,e,t,1<arguments.length)},removeAttr:function(e){return this.each(function(){ce.removeAttr(this,e)})}}),ce.extend({attr:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return"undefined"==typeof e.getAttribute?ce.prop(e,t,n):(1===o&&ce.isXMLDoc(e)||(i=ce.attrHooks[t.toLowerCase()]||(ce.expr.match.bool.test(t)?mt:void 0)),void 0!==n?null===n?void ce.removeAttr(e,t):i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:(e.setAttribute(t,n+""),n):i&&"get"in i&&null!==(r=i.get(e,t))?r:null==(r=ce.find.attr(e,t))?void 0:r)},attrHooks:{type:{set:function(e,t){if(!le.radioValue&&"radio"===t&&fe(e,"input")){var n=e.value;return e.setAttribute("type",t),n&&(e.value=n),t}}}},removeAttr:function(e,t){var n,r=0,i=t&&t.match(D);if(i&&1===e.nodeType)while(n=i[r++])e.removeAttribute(n)}}),mt={set:function(e,t,n){return!1===t?ce.removeAttr(e,n):e.setAttribute(n,n),n}},ce.each(ce.expr.match.bool.source.match(/\w+/g),function(e,t){var a=xt[t]||ce.find.attr;xt[t]=function(e,t,n){var r,i,o=t.toLowerCase();return n||(i=xt[o],xt[o]=r,r=null!=a(e,t,n)?o:null,xt[o]=i),r}});var bt=/^(?:input|select|textarea|button)$/i,wt=/^(?:a|area)$/i;function Tt(e){return(e.match(D)||[]).join(" ")}function Ct(e){return e.getAttribute&&e.getAttribute("class")||""}function kt(e){return Array.isArray(e)?e:"string"==typeof e&&e.match(D)||[]}ce.fn.extend({prop:function(e,t){return M(this,ce.prop,e,t,1<arguments.length)},removeProp:function(e){return this.each(function(){delete this[ce.propFix[e]||e]})}}),ce.extend({prop:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return 1===o&&ce.isXMLDoc(e)||(t=ce.propFix[t]||t,i=ce.propHooks[t]),void 0!==n?i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:e[t]=n:i&&"get"in i&&null!==(r=i.get(e,t))?r:e[t]},propHooks:{tabIndex:{get:function(e){var t=ce.find.attr(e,"tabindex");return t?parseInt(t,10):bt.test(e.nodeName)||wt.test(e.nodeName)&&e.href?0:-1}}},propFix:{"for":"htmlFor","class":"className"}}),le.optSelected||(ce.propHooks.selected={get:function(e){var t=e.parentNode;return t&&t.parentNode&&t.parentNode.selectedIndex,null},set:function(e){var t=e.parentNode;t&&(t.selectedIndex,t.parentNode&&t.parentNode.selectedIndex)}}),ce.each(["tabIndex","readOnly","maxLength","cellSpacing","cellPadding","rowSpan","colSpan","useMap","frameBorder","contentEditable"],function(){ce.propFix[this.toLowerCase()]=this}),ce.fn.extend({addClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).addClass(t.call(this,e,Ct(this)))}):(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++)i=e[o],n.indexOf(" "+i+" ")<0&&(n+=i+" ");a=Tt(n),r!==a&&this.setAttribute("class",a)}}):this},removeClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).removeClass(t.call(this,e,Ct(this)))}):arguments.length?(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++){i=e[o];while(-1<n.indexOf(" "+i+" "))n=n.replace(" "+i+" "," ")}a=Tt(n),r!==a&&this.setAttribute("class",a)}}):this:this.attr("class","")},toggleClass:function(t,n){var e,r,i,o,a=typeof t,s="string"===a||Array.isArray(t);return v(t)?this.each(function(e){ce(this).toggleClass(t.call(this,e,Ct(this),n),n)}):"boolean"==typeof n&&s?n?this.addClass(t):this.removeClass(t):(e=kt(t),this.each(function(){if(s)for(o=ce(this),i=0;i<e.length;i++)r=e[i],o.hasClass(r)?o.removeClass(r):o.addClass(r);else void 0!==t&&"boolean"!==a||((r=Ct(this))&&_.set(this,"__className__",r),this.setAttribute&&this.setAttribute("class",r||!1===t?"":_.get(this,"__className__")||""))}))},hasClass:function(e){var t,n,r=0;t=" "+e+" ";while(n=this[r++])if(1===n.nodeType&&-1<(" "+Tt(Ct(n))+" ").indexOf(t))return!0;return!1}});var St=/\r/g;ce.fn.extend({val:function(n){var r,e,i,t=this[0];return arguments.length?(i=v(n),this.each(function(e){var t;1===this.nodeType&&(null==(t=i?n.call(this,e,ce(this).val()):n)?t="":"number"==typeof t?t+="":Array.isArray(t)&&(t=ce.map(t,function(e){return null==e?"":e+""})),(r=ce.valHooks[this.type]||ce.valHooks[this.nodeName.toLowerCase()])&&"set"in r&&void 0!==r.set(this,t,"value")||(this.value=t))})):t?(r=ce.valHooks[t.type]||ce.valHooks[t.nodeName.toLowerCase()])&&"get"in r&&void 0!==(e=r.get(t,"value"))?e:"string"==typeof(e=t.value)?e.replace(St,""):null==e?"":e:void 0}}),ce.extend({valHooks:{option:{get:function(e){var t=ce.find.attr(e,"value");return null!=t?t:Tt(ce.text(e))}},select:{get:function(e){var t,n,r,i=e.options,o=e.selectedIndex,a="select-one"===e.type,s=a?null:[],u=a?o+1:i.length;for(r=o<0?u:a?o:0;r<u;r++)if(((n=i[r]).selected||r===o)&&!n.disabled&&(!n.parentNode.disabled||!fe(n.parentNode,"optgroup"))){if(t=ce(n).val(),a)return t;s.push(t)}return s},set:function(e,t){var n,r,i=e.options,o=ce.makeArray(t),a=i.length;while(a--)((r=i[a]).selected=-1<ce.inArray(ce.valHooks.option.get(r),o))&&(n=!0);return n||(e.selectedIndex=-1),o}}}}),ce.each(["radio","checkbox"],function(){ce.valHooks[this]={set:function(e,t){if(Array.isArray(t))return e.checked=-1<ce.inArray(ce(e).val(),t)}},le.checkOn||(ce.valHooks[this].get=function(e){return null===e.getAttribute("value")?"on":e.value})});var Et=ie.location,jt={guid:Date.now()},At=/\?/;ce.parseXML=function(e){var t,n;if(!e||"string"!=typeof e)return null;try{t=(new ie.DOMParser).parseFromString(e,"text/xml")}catch(e){}return n=t&&t.getElementsByTagName("parsererror")[0],t&&!n||ce.error("Invalid XML: "+(n?ce.map(n.childNodes,function(e){return e.textContent}).join("\n"):e)),t};var Dt=/^(?:focusinfocus|focusoutblur)$/,Nt=function(e){e.stopPropagation()};ce.extend(ce.event,{trigger:function(e,t,n,r){var i,o,a,s,u,l,c,f,p=[n||C],d=ue.call(e,"type")?e.type:e,h=ue.call(e,"namespace")?e.namespace.split("."):[];if(o=f=a=n=n||C,3!==n.nodeType&&8!==n.nodeType&&!Dt.test(d+ce.event.triggered)&&(-1<d.indexOf(".")&&(d=(h=d.split(".")).shift(),h.sort()),u=d.indexOf(":")<0&&"on"+d,(e=e[ce.expando]?e:new ce.Event(d,"object"==typeof e&&e)).isTrigger=r?2:3,e.namespace=h.join("."),e.rnamespace=e.namespace?new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"):null,e.result=void 0,e.target||(e.target=n),t=null==t?[e]:ce.makeArray(t,[e]),c=ce.event.special[d]||{},r||!c.trigger||!1!==c.trigger.apply(n,t))){if(!r&&!c.noBubble&&!y(n)){for(s=c.delegateType||d,Dt.test(s+d)||(o=o.parentNode);o;o=o.parentNode)p.push(o),a=o;a===(n.ownerDocument||C)&&p.push(a.defaultView||a.parentWindow||ie)}i=0;while((o=p[i++])&&!e.isPropagationStopped())f=o,e.type=1<i?s:c.bindType||d,(l=(_.get(o,"events")||Object.create(null))[e.type]&&_.get(o,"handle"))&&l.apply(o,t),(l=u&&o[u])&&l.apply&&$(o)&&(e.result=l.apply(o,t),!1===e.result&&e.preventDefault());return e.type=d,r||e.isDefaultPrevented()||c._default&&!1!==c._default.apply(p.pop(),t)||!$(n)||u&&v(n[d])&&!y(n)&&((a=n[u])&&(n[u]=null),ce.event.triggered=d,e.isPropagationStopped()&&f.addEventListener(d,Nt),n[d](),e.isPropagationStopped()&&f.removeEventListener(d,Nt),ce.event.triggered=void 0,a&&(n[u]=a)),e.result}},simulate:function(e,t,n){var r=ce.extend(new ce.Event,n,{type:e,isSimulated:!0});ce.event.trigger(r,null,t)}}),ce.fn.extend({trigger:function(e,t){return this.each(function(){ce.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return ce.event.trigger(e,t,n,!0)}});var qt=/\[\]$/,Lt=/\r?\n/g,Ht=/^(?:submit|button|image|reset|file)$/i,Ot=/^(?:input|select|textarea|keygen)/i;function Pt(n,e,r,i){var t;if(Array.isArray(e))ce.each(e,function(e,t){r||qt.test(n)?i(n,t):Pt(n+"["+("object"==typeof t&&null!=t?e:"")+"]",t,r,i)});else if(r||"object"!==x(e))i(n,e);else for(t in e)Pt(n+"["+t+"]",e[t],r,i)}ce.param=function(e,t){var n,r=[],i=function(e,t){var n=v(t)?t():t;r[r.length]=encodeURIComponent(e)+"="+encodeURIComponent(null==n?"":n)};if(null==e)return"";if(Array.isArray(e)||e.jquery&&!ce.isPlainObject(e))ce.each(e,function(){i(this.name,this.value)});else for(n in e)Pt(n,e[n],t,i);return r.join("&")},ce.fn.extend({serialize:function(){return ce.param(this.serializeArray())},serializeArray:function(){return this.map(function(){var e=ce.prop(this,"elements");return e?ce.makeArray(e):this}).filter(function(){var e=this.type;return this.name&&!ce(this).is(":disabled")&&Ot.test(this.nodeName)&&!Ht.test(e)&&(this.checked||!we.test(e))}).map(function(e,t){var n=ce(this).val();return null==n?null:Array.isArray(n)?ce.map(n,function(e){return{name:t.name,value:e.replace(Lt,"\r\n")}}):{name:t.name,value:n.replace(Lt,"\r\n")}}).get()}});var Mt=/%20/g,Rt=/#.*$/,It=/([?&])_=[^&]*/,Wt=/^(.*?):[ \t]*([^\r\n]*)$/gm,Ft=/^(?:GET|HEAD)$/,$t=/^\/\//,Bt={},_t={},zt="*/".concat("*"),Xt=C.createElement("a");function Ut(o){return function(e,t){"string"!=typeof e&&(t=e,e="*");var n,r=0,i=e.toLowerCase().match(D)||[];if(v(t))while(n=i[r++])"+"===n[0]?(n=n.slice(1)||"*",(o[n]=o[n]||[]).unshift(t)):(o[n]=o[n]||[]).push(t)}}function Vt(t,i,o,a){var s={},u=t===_t;function l(e){var r;return s[e]=!0,ce.each(t[e]||[],function(e,t){var n=t(i,o,a);return"string"!=typeof n||u||s[n]?u?!(r=n):void 0:(i.dataTypes.unshift(n),l(n),!1)}),r}return l(i.dataTypes[0])||!s["*"]&&l("*")}function Gt(e,t){var n,r,i=ce.ajaxSettings.flatOptions||{};for(n in t)void 0!==t[n]&&((i[n]?e:r||(r={}))[n]=t[n]);return r&&ce.extend(!0,e,r),e}Xt.href=Et.href,ce.extend({active:0,lastModified:{},etag:{},ajaxSettings:{url:Et.href,type:"GET",isLocal:/^(?:about|app|app-storage|.+-extension|file|res|widget):$/.test(Et.protocol),global:!0,processData:!0,async:!0,contentType:"application/x-www-form-urlencoded; charset=UTF-8",accepts:{"*":zt,text:"text/plain",html:"text/html",xml:"application/xml, text/xml",json:"application/json, text/javascript"},contents:{xml:/\bxml\b/,html:/\bhtml/,json:/\bjson\b/},responseFields:{xml:"responseXML",text:"responseText",json:"responseJSON"},converters:{"* text":String,"text html":!0,"text json":JSON.parse,"text xml":ce.parseXML},flatOptions:{url:!0,context:!0}},ajaxSetup:function(e,t){return t?Gt(Gt(e,ce.ajaxSettings),t):Gt(ce.ajaxSettings,e)},ajaxPrefilter:Ut(Bt),ajaxTransport:Ut(_t),ajax:function(e,t){"object"==typeof e&&(t=e,e=void 0),t=t||{};var c,f,p,n,d,r,h,g,i,o,v=ce.ajaxSetup({},t),y=v.context||v,m=v.context&&(y.nodeType||y.jquery)?ce(y):ce.event,x=ce.Deferred(),b=ce.Callbacks("once memory"),w=v.statusCode||{},a={},s={},u="canceled",T={readyState:0,getResponseHeader:function(e){var t;if(h){if(!n){n={};while(t=Wt.exec(p))n[t[1].toLowerCase()+" "]=(n[t[1].toLowerCase()+" "]||[]).concat(t[2])}t=n[e.toLowerCase()+" "]}return null==t?null:t.join(", ")},getAllResponseHeaders:function(){return h?p:null},setRequestHeader:function(e,t){return null==h&&(e=s[e.toLowerCase()]=s[e.toLowerCase()]||e,a[e]=t),this},overrideMimeType:function(e){return null==h&&(v.mimeType=e),this},statusCode:function(e){var t;if(e)if(h)T.always(e[T.status]);else for(t in e)w[t]=[w[t],e[t]];return this},abort:function(e){var t=e||u;return c&&c.abort(t),l(0,t),this}};if(x.promise(T),v.url=((e||v.url||Et.href)+"").replace($t,Et.protocol+"//"),v.type=t.method||t.type||v.method||v.type,v.dataTypes=(v.dataType||"*").toLowerCase().match(D)||[""],null==v.crossDomain){r=C.createElement("a");try{r.href=v.url,r.href=r.href,v.crossDomain=Xt.protocol+"//"+Xt.host!=r.protocol+"//"+r.host}catch(e){v.crossDomain=!0}}if(v.data&&v.processData&&"string"!=typeof v.data&&(v.data=ce.param(v.data,v.traditional)),Vt(Bt,v,t,T),h)return T;for(i in(g=ce.event&&v.global)&&0==ce.active++&&ce.event.trigger("ajaxStart"),v.type=v.type.toUpperCase(),v.hasContent=!Ft.test(v.type),f=v.url.replace(Rt,""),v.hasContent?v.data&&v.processData&&0===(v.contentType||"").indexOf("application/x-www-form-urlencoded")&&(v.data=v.data.replace(Mt,"+")):(o=v.url.slice(f.length),v.data&&(v.processData||"string"==typeof v.data)&&(f+=(At.test(f)?"&":"?")+v.data,delete v.data),!1===v.cache&&(f=f.replace(It,"$1"),o=(At.test(f)?"&":"?")+"_="+jt.guid+++o),v.url=f+o),v.ifModified&&(ce.lastModified[f]&&T.setRequestHeader("If-Modified-Since",ce.lastModified[f]),ce.etag[f]&&T.setRequestHeader("If-None-Match",ce.etag[f])),(v.data&&v.hasContent&&!1!==v.contentType||t.contentType)&&T.setRequestHeader("Content-Type",v.contentType),T.setRequestHeader("Accept",v.dataTypes[0]&&v.accepts[v.dataTypes[0]]?v.accepts[v.dataTypes[0]]+("*"!==v.dataTypes[0]?", "+zt+"; q=0.01":""):v.accepts["*"]),v.headers)T.setRequestHeader(i,v.headers[i]);if(v.beforeSend&&(!1===v.beforeSend.call(y,T,v)||h))return T.abort();if(u="abort",b.add(v.complete),T.done(v.success),T.fail(v.error),c=Vt(_t,v,t,T)){if(T.readyState=1,g&&m.trigger("ajaxSend",[T,v]),h)return T;v.async&&0<v.timeout&&(d=ie.setTimeout(function(){T.abort("timeout")},v.timeout));try{h=!1,c.send(a,l)}catch(e){if(h)throw e;l(-1,e)}}else l(-1,"No Transport");function l(e,t,n,r){var i,o,a,s,u,l=t;h||(h=!0,d&&ie.clearTimeout(d),c=void 0,p=r||"",T.readyState=0<e?4:0,i=200<=e&&e<300||304===e,n&&(s=function(e,t,n){var r,i,o,a,s=e.contents,u=e.dataTypes;while("*"===u[0])u.shift(),void 0===r&&(r=e.mimeType||t.getResponseHeader("Content-Type"));if(r)for(i in s)if(s[i]&&s[i].test(r)){u.unshift(i);break}if(u[0]in n)o=u[0];else{for(i in n){if(!u[0]||e.converters[i+" "+u[0]]){o=i;break}a||(a=i)}o=o||a}if(o)return o!==u[0]&&u.unshift(o),n[o]}(v,T,n)),!i&&-1<ce.inArray("script",v.dataTypes)&&ce.inArray("json",v.dataTypes)<0&&(v.converters["text script"]=function(){}),s=function(e,t,n,r){var i,o,a,s,u,l={},c=e.dataTypes.slice();if(c[1])for(a in e.converters)l[a.toLowerCase()]=e.converters[a];o=c.shift();while(o)if(e.responseFields[o]&&(n[e.responseFields[o]]=t),!u&&r&&e.dataFilter&&(t=e.dataFilter(t,e.dataType)),u=o,o=c.shift())if("*"===o)o=u;else if("*"!==u&&u!==o){if(!(a=l[u+" "+o]||l["* "+o]))for(i in l)if((s=i.split(" "))[1]===o&&(a=l[u+" "+s[0]]||l["* "+s[0]])){!0===a?a=l[i]:!0!==l[i]&&(o=s[0],c.unshift(s[1]));break}if(!0!==a)if(a&&e["throws"])t=a(t);else try{t=a(t)}catch(e){return{state:"parsererror",error:a?e:"No conversion from "+u+" to "+o}}}return{state:"success",data:t}}(v,s,T,i),i?(v.ifModified&&((u=T.getResponseHeader("Last-Modified"))&&(ce.lastModified[f]=u),(u=T.getResponseHeader("etag"))&&(ce.etag[f]=u)),204===e||"HEAD"===v.type?l="nocontent":304===e?l="notmodified":(l=s.state,o=s.data,i=!(a=s.error))):(a=l,!e&&l||(l="error",e<0&&(e=0))),T.status=e,T.statusText=(t||l)+"",i?x.resolveWith(y,[o,l,T]):x.rejectWith(y,[T,l,a]),T.statusCode(w),w=void 0,g&&m.trigger(i?"ajaxSuccess":"ajaxError",[T,v,i?o:a]),b.fireWith(y,[T,l]),g&&(m.trigger("ajaxComplete",[T,v]),--ce.active||ce.event.trigger("ajaxStop")))}return T},getJSON:function(e,t,n){return ce.get(e,t,n,"json")},getScript:function(e,t){return ce.get(e,void 0,t,"script")}}),ce.each(["get","post"],function(e,i){ce[i]=function(e,t,n,r){return v(t)&&(r=r||n,n=t,t=void 0),ce.ajax(ce.extend({url:e,type:i,dataType:r,data:t,success:n},ce.isPlainObject(e)&&e))}}),ce.ajaxPrefilter(function(e){var t;for(t in e.headers)"content-type"===t.toLowerCase()&&(e.contentType=e.headers[t]||"")}),ce._evalUrl=function(e,t,n){return ce.ajax({url:e,type:"GET",dataType:"script",cache:!0,async:!1,global:!1,converters:{"text script":function(){}},dataFilter:function(e){ce.globalEval(e,t,n)}})},ce.fn.extend({wrapAll:function(e){var t;return this[0]&&(v(e)&&(e=e.call(this[0])),t=ce(e,this[0].ownerDocument).eq(0).clone(!0),this[0].parentNode&&t.insertBefore(this[0]),t.map(function(){var e=this;while(e.firstElementChild)e=e.firstElementChild;return e}).append(this)),this},wrapInner:function(n){return v(n)?this.each(function(e){ce(this).wrapInner(n.call(this,e))}):this.each(function(){var e=ce(this),t=e.contents();t.length?t.wrapAll(n):e.append(n)})},wrap:function(t){var n=v(t);return this.each(function(e){ce(this).wrapAll(n?t.call(this,e):t)})},unwrap:function(e){return this.parent(e).not("body").each(function(){ce(this).replaceWith(this.childNodes)}),this}}),ce.expr.pseudos.hidden=function(e){return!ce.expr.pseudos.visible(e)},ce.expr.pseudos.visible=function(e){return!!(e.offsetWidth||e.offsetHeight||e.getClientRects().length)},ce.ajaxSettings.xhr=function(){try{return new ie.XMLHttpRequest}catch(e){}};var Yt={0:200,1223:204},Qt=ce.ajaxSettings.xhr();le.cors=!!Qt&&"withCredentials"in Qt,le.ajax=Qt=!!Qt,ce.ajaxTransport(function(i){var o,a;if(le.cors||Qt&&!i.crossDomain)return{send:function(e,t){var n,r=i.xhr();if(r.open(i.type,i.url,i.async,i.username,i.password),i.xhrFields)for(n in i.xhrFields)r[n]=i.xhrFields[n];for(n in i.mimeType&&r.overrideMimeType&&r.overrideMimeType(i.mimeType),i.crossDomain||e["X-Requested-With"]||(e["X-Requested-With"]="XMLHttpRequest"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(Yt[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onreadystatechange=function(){4===r.readyState&&ie.setTimeout(function(){o&&a()})},o=o("abort");try{r.send(i.hasContent&&i.data||null)}catch(e){if(o)throw e}},abort:function(){o&&o()}}}),ce.ajaxPrefilter(function(e){e.crossDomain&&(e.contents.script=!1)}),ce.ajaxSetup({accepts:{script:"text/javascript, application/javascript, application/ecmascript, application/x-ecmascript"},contents:{script:/\b(?:java|ecma)script\b/},converters:{"text script":function(e){return ce.globalEval(e),e}}}),ce.ajaxPrefilter("script",function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type="GET")}),ce.ajaxTransport("script",function(n){var r,i;if(n.crossDomain||n.scriptAttrs)return{send:function(e,t){r=ce("<script>").attr(n.scriptAttrs||{}).prop({charset:n.scriptCharset,src:n.url}).on("load error",i=function(e){r.remove(),i=null,e&&t("error"===e.type?404:200,e.type)}),C.head.appendChild(r[0])},abort:function(){i&&i()}}});var Jt,Kt=[],Zt=/(=)\?(?=&|$)|\?\?/;ce.ajaxSetup({jsonp:"callback",jsonpCallback:function(){var e=Kt.pop()||ce.expando+"_"+jt.guid++;return this[e]=!0,e}}),ce.ajaxPrefilter("json jsonp",function(e,t,n){var r,i,o,a=!1!==e.jsonp&&(Zt.test(e.url)?"url":"string"==typeof e.data&&0===(e.contentType||"").indexOf("application/x-www-form-urlencoded")&&Zt.test(e.data)&&"data");if(a||"jsonp"===e.dataTypes[0])return r=e.jsonpCallback=v(e.jsonpCallback)?e.jsonpCallback():e.jsonpCallback,a?e[a]=e[a].replace(Zt,"$1"+r):!1!==e.jsonp&&(e.url+=(At.test(e.url)?"&":"?")+e.jsonp+"="+r),e.converters["script json"]=function(){return o||ce.error(r+" was not called"),o[0]},e.dataTypes[0]="json",i=ie[r],ie[r]=function(){o=arguments},n.always(function(){void 0===i?ce(ie).removeProp(r):ie[r]=i,e[r]&&(e.jsonpCallback=t.jsonpCallback,Kt.push(r)),o&&v(i)&&i(o[0]),o=i=void 0}),"script"}),le.createHTMLDocument=((Jt=C.implementation.createHTMLDocument("").body).innerHTML="<form></form><form></form>",2===Jt.childNodes.length),ce.parseHTML=function(e,t,n){return"string"!=typeof e?[]:("boolean"==typeof t&&(n=t,t=!1),t||(le.createHTMLDocument?((r=(t=C.implementation.createHTMLDocument("")).createElement("base")).href=C.location.href,t.head.appendChild(r)):t=C),o=!n&&[],(i=w.exec(e))?[t.createElement(i[1])]:(i=Ae([e],t,o),o&&o.length&&ce(o).remove(),ce.merge([],i.childNodes)));var r,i,o},ce.fn.load=function(e,t,n){var r,i,o,a=this,s=e.indexOf(" ");return-1<s&&(r=Tt(e.slice(s)),e=e.slice(0,s)),v(t)?(n=t,t=void 0):t&&"object"==typeof t&&(i="POST"),0<a.length&&ce.ajax({url:e,type:i||"GET",dataType:"html",data:t}).done(function(e){o=arguments,a.html(r?ce("<div>").append(ce.parseHTML(e)).find(r):e)}).always(n&&function(e,t){a.each(function(){n.apply(this,o||[e.responseText,t,e])})}),this},ce.expr.pseudos.animated=function(t){return ce.grep(ce.timers,function(e){return t===e.elem}).length},ce.offset={setOffset:function(e,t,n){var r,i,o,a,s,u,l=ce.css(e,"position"),c=ce(e),f={};"static"===l&&(e.style.position="relative"),s=c.offset(),o=ce.css(e,"top"),u=ce.css(e,"left"),("absolute"===l||"fixed"===l)&&-1<(o+u).indexOf("auto")?(a=(r=c.position()).top,i=r.left):(a=parseFloat(o)||0,i=parseFloat(u)||0),v(t)&&(t=t.call(e,n,ce.extend({},s))),null!=t.top&&(f.top=t.top-s.top+a),null!=t.left&&(f.left=t.left-s.left+i),"using"in t?t.using.call(e,f):c.css(f)}},ce.fn.extend({offset:function(t){if(arguments.length)return void 0===t?this:this.each(function(e){ce.offset.setOffset(this,t,e)});var e,n,r=this[0];return r?r.getClientRects().length?(e=r.getBoundingClientRect(),n=r.ownerDocument.defaultView,{top:e.top+n.pageYOffset,left:e.left+n.pageXOffset}):{top:0,left:0}:void 0},position:function(){if(this[0]){var e,t,n,r=this[0],i={top:0,left:0};if("fixed"===ce.css(r,"position"))t=r.getBoundingClientRect();else{t=this.offset(),n=r.ownerDocument,e=r.offsetParent||n.documentElement;while(e&&(e===n.body||e===n.documentElement)&&"static"===ce.css(e,"position"))e=e.parentNode;e&&e!==r&&1===e.nodeType&&((i=ce(e).offset()).top+=ce.css(e,"borderTopWidth",!0),i.left+=ce.css(e,"borderLeftWidth",!0))}return{top:t.top-i.top-ce.css(r,"marginTop",!0),left:t.left-i.left-ce.css(r,"marginLeft",!0)}}},offsetParent:function(){return this.map(function(){var e=this.offsetParent;while(e&&"static"===ce.css(e,"position"))e=e.offsetParent;return e||J})}}),ce.each({scrollLeft:"pageXOffset",scrollTop:"pageYOffset"},function(t,i){var o="pageYOffset"===i;ce.fn[t]=function(e){return M(this,function(e,t,n){var r;if(y(e)?r=e:9===e.nodeType&&(r=e.defaultView),void 0===n)return r?r[i]:e[t];r?r.scrollTo(o?r.pageXOffset:n,o?n:r.pageYOffset):e[t]=n},t,e,arguments.length)}}),ce.each(["top","left"],function(e,n){ce.cssHooks[n]=Ye(le.pixelPosition,function(e,t){if(t)return t=Ge(e,n),_e.test(t)?ce(e).position()[n]+"px":t})}),ce.each({Height:"height",Width:"width"},function(a,s){ce.each({padding:"inner"+a,content:s,"":"outer"+a},function(r,o){ce.fn[o]=function(e,t){var n=arguments.length&&(r||"boolean"!=typeof e),i=r||(!0===e||!0===t?"margin":"border");return M(this,function(e,t,n){var r;return y(e)?0===o.indexOf("outer")?e["inner"+a]:e.document.documentElement["client"+a]:9===e.nodeType?(r=e.documentElement,Math.max(e.body["scroll"+a],r["scroll"+a],e.body["offset"+a],r["offset"+a],r["client"+a])):void 0===n?ce.css(e,t,i):ce.style(e,t,n,i)},s,n?e:void 0,n)}})}),ce.each(["ajaxStart","ajaxStop","ajaxComplete","ajaxError","ajaxSuccess","ajaxSend"],function(e,t){ce.fn[t]=function(e){return this.on(t,e)}}),ce.fn.extend({bind:function(e,t,n){return this.on(e,null,t,n)},unbind:function(e,t){return this.off(e,null,t)},delegate:function(e,t,n,r){return this.on(t,e,n,r)},undelegate:function(e,t,n){return 1===arguments.length?this.off(e,"**"):this.off(t,e||"**",n)},hover:function(e,t){return this.on("mouseenter",e).on("mouseleave",t||e)}}),ce.each("blur focus focusin focusout resize scroll click dblclick mousedown mouseup mousemove mouseover mouseout mouseenter mouseleave change select submit keydown keypress keyup contextmenu".split(" "),function(e,n){ce.fn[n]=function(e,t){return 0<arguments.length?this.on(n,null,e,t):this.trigger(n)}});var en=/^[\s\uFEFF\xA0]+|([^\s\uFEFF\xA0])[\s\uFEFF\xA0]+$/g;ce.proxy=function(e,t){var n,r,i;if("string"==typeof t&&(n=e[t],t=e,e=n),v(e))return r=ae.call(arguments,2),(i=function(){return e.apply(t||this,r.concat(ae.call(arguments)))}).guid=e.guid=e.guid||ce.guid++,i},ce.holdReady=function(e){e?ce.readyWait++:ce.ready(!0)},ce.isArray=Array.isArray,ce.parseJSON=JSON.parse,ce.nodeName=fe,ce.isFunction=v,ce.isWindow=y,ce.camelCase=F,ce.type=x,ce.now=Date.now,ce.isNumeric=function(e){var t=ce.type(e);return("number"===t||"string"===t)&&!isNaN(e-parseFloat(e))},ce.trim=function(e){return null==e?"":(e+"").replace(en,"$1")},"function"==typeof define&&define.amd&&define("jquery",[],function(){return ce});var tn=ie.jQuery,nn=ie.$;return ce.noConflict=function(e){return ie.$===ce&&(ie.$=nn),e&&ie.jQuery===ce&&(ie.jQuery=tn),ce},"undefined"==typeof e&&(ie.jQuery=ie.$=ce),ce});
+</script>
+<script>!function(){function n(n){return n&&(n.ownerDocument||n.document||n).documentElement}function t(n){return n&&(n.ownerDocument&&n.ownerDocument.defaultView||n.document&&n||n.defaultView)}function e(n,t){return t>n?-1:n>t?1:n>=t?0:0/0}function r(n){return null===n?0/0:+n}function u(n){return!isNaN(n)}function i(n){return{left:function(t,e,r,u){for(arguments.length<3&&(r=0),arguments.length<4&&(u=t.length);u>r;){var i=r+u>>>1;n(t[i],e)<0?r=i+1:u=i}return r},right:function(t,e,r,u){for(arguments.length<3&&(r=0),arguments.length<4&&(u=t.length);u>r;){var i=r+u>>>1;n(t[i],e)>0?u=i:r=i+1}return r}}}function o(n){return n.length}function a(n){for(var t=1;n*t%1;)t*=10;return t}function c(n,t){for(var e in t)Object.defineProperty(n.prototype,e,{value:t[e],enumerable:!1})}function l(){this._=Object.create(null)}function s(n){return(n+="")===pa||n[0]===va?va+n:n}function f(n){return(n+="")[0]===va?n.slice(1):n}function h(n){return s(n)in this._}function g(n){return(n=s(n))in this._&&delete this._[n]}function p(){var n=[];for(var t in this._)n.push(f(t));return n}function v(){var n=0;for(var t in this._)++n;return n}function d(){for(var n in this._)return!1;return!0}function m(){this._=Object.create(null)}function y(n){return n}function M(n,t,e){return function(){var r=e.apply(t,arguments);return r===t?n:r}}function x(n,t){if(t in n)return t;t=t.charAt(0).toUpperCase()+t.slice(1);for(var e=0,r=da.length;r>e;++e){var u=da[e]+t;if(u in n)return u}}function b(){}function _(){}function w(n){function t(){for(var t,r=e,u=-1,i=r.length;++u<i;)(t=r[u].on)&&t.apply(this,arguments);return n}var e=[],r=new l;return t.on=function(t,u){var i,o=r.get(t);return arguments.length<2?o&&o.on:(o&&(o.on=null,e=e.slice(0,i=e.indexOf(o)).concat(e.slice(i+1)),r.remove(t)),u&&e.push(r.set(t,{on:u})),n)},t}function S(){ta.event.preventDefault()}function k(){for(var n,t=ta.event;n=t.sourceEvent;)t=n;return t}function E(n){for(var t=new _,e=0,r=arguments.length;++e<r;)t[arguments[e]]=w(t);return t.of=function(e,r){return function(u){try{var i=u.sourceEvent=ta.event;u.target=n,ta.event=u,t[u.type].apply(e,r)}finally{ta.event=i}}},t}function A(n){return ya(n,_a),n}function N(n){return"function"==typeof n?n:function(){return Ma(n,this)}}function C(n){return"function"==typeof n?n:function(){return xa(n,this)}}function z(n,t){function e(){this.removeAttribute(n)}function r(){this.removeAttributeNS(n.space,n.local)}function u(){this.setAttribute(n,t)}function i(){this.setAttributeNS(n.space,n.local,t)}function o(){var e=t.apply(this,arguments);null==e?this.removeAttribute(n):this.setAttribute(n,e)}function a(){var e=t.apply(this,arguments);null==e?this.removeAttributeNS(n.space,n.local):this.setAttributeNS(n.space,n.local,e)}return n=ta.ns.qualify(n),null==t?n.local?r:e:"function"==typeof t?n.local?a:o:n.local?i:u}function q(n){return n.trim().replace(/\s+/g," ")}function L(n){return new RegExp("(?:^|\\s+)"+ta.requote(n)+"(?:\\s+|$)","g")}function T(n){return(n+"").trim().split(/^|\s+/)}function R(n,t){function e(){for(var e=-1;++e<u;)n[e](this,t)}function r(){for(var e=-1,r=t.apply(this,arguments);++e<u;)n[e](this,r)}n=T(n).map(D);var u=n.length;return"function"==typeof t?r:e}function D(n){var t=L(n);return function(e,r){if(u=e.classList)return r?u.add(n):u.remove(n);var u=e.getAttribute("class")||"";r?(t.lastIndex=0,t.test(u)||e.setAttribute("class",q(u+" "+n))):e.setAttribute("class",q(u.replace(t," ")))}}function P(n,t,e){function r(){this.style.removeProperty(n)}function u(){this.style.setProperty(n,t,e)}function i(){var r=t.apply(this,arguments);null==r?this.style.removeProperty(n):this.style.setProperty(n,r,e)}return null==t?r:"function"==typeof t?i:u}function U(n,t){function e(){delete this[n]}function r(){this[n]=t}function u(){var e=t.apply(this,arguments);null==e?delete this[n]:this[n]=e}return null==t?e:"function"==typeof t?u:r}function j(n){function t(){var t=this.ownerDocument,e=this.namespaceURI;return e?t.createElementNS(e,n):t.createElement(n)}function e(){return this.ownerDocument.createElementNS(n.space,n.local)}return"function"==typeof n?n:(n=ta.ns.qualify(n)).local?e:t}function F(){var n=this.parentNode;n&&n.removeChild(this)}function H(n){return{__data__:n}}function O(n){return function(){return ba(this,n)}}function I(n){return arguments.length||(n=e),function(t,e){return t&&e?n(t.__data__,e.__data__):!t-!e}}function Y(n,t){for(var e=0,r=n.length;r>e;e++)for(var u,i=n[e],o=0,a=i.length;a>o;o++)(u=i[o])&&t(u,o,e);return n}function Z(n){return ya(n,Sa),n}function V(n){var t,e;return function(r,u,i){var o,a=n[i].update,c=a.length;for(i!=e&&(e=i,t=0),u>=t&&(t=u+1);!(o=a[t])&&++t<c;);return o}}function X(n,t,e){function r(){var t=this[o];t&&(this.removeEventListener(n,t,t.$),delete this[o])}function u(){var u=c(t,ra(arguments));r.call(this),this.addEventListener(n,this[o]=u,u.$=e),u._=t}function i(){var t,e=new RegExp("^__on([^.]+)"+ta.requote(n)+"$");for(var r in this)if(t=r.match(e)){var u=this[r];this.removeEventListener(t[1],u,u.$),delete this[r]}}var o="__on"+n,a=n.indexOf("."),c=$;a>0&&(n=n.slice(0,a));var l=ka.get(n);return l&&(n=l,c=B),a?t?u:r:t?b:i}function $(n,t){return function(e){var r=ta.event;ta.event=e,t[0]=this.__data__;try{n.apply(this,t)}finally{ta.event=r}}}function B(n,t){var e=$(n,t);return function(n){var t=this,r=n.relatedTarget;r&&(r===t||8&r.compareDocumentPosition(t))||e.call(t,n)}}function W(e){var r=".dragsuppress-"+ ++Aa,u="click"+r,i=ta.select(t(e)).on("touchmove"+r,S).on("dragstart"+r,S).on("selectstart"+r,S);if(null==Ea&&(Ea="onselectstart"in e?!1:x(e.style,"userSelect")),Ea){var o=n(e).style,a=o[Ea];o[Ea]="none"}return function(n){if(i.on(r,null),Ea&&(o[Ea]=a),n){var t=function(){i.on(u,null)};i.on(u,function(){S(),t()},!0),setTimeout(t,0)}}}function J(n,e){e.changedTouches&&(e=e.changedTouches[0]);var r=n.ownerSVGElement||n;if(r.createSVGPoint){var u=r.createSVGPoint();if(0>Na){var i=t(n);if(i.scrollX||i.scrollY){r=ta.select("body").append("svg").style({position:"absolute",top:0,left:0,margin:0,padding:0,border:"none"},"important");var o=r[0][0].getScreenCTM();Na=!(o.f||o.e),r.remove()}}return Na?(u.x=e.pageX,u.y=e.pageY):(u.x=e.clientX,u.y=e.clientY),u=u.matrixTransform(n.getScreenCTM().inverse()),[u.x,u.y]}var a=n.getBoundingClientRect();return[e.clientX-a.left-n.clientLeft,e.clientY-a.top-n.clientTop]}function G(){return ta.event.changedTouches[0].identifier}function K(n){return n>0?1:0>n?-1:0}function Q(n,t,e){return(t[0]-n[0])*(e[1]-n[1])-(t[1]-n[1])*(e[0]-n[0])}function nt(n){return n>1?0:-1>n?qa:Math.acos(n)}function tt(n){return n>1?Ra:-1>n?-Ra:Math.asin(n)}function et(n){return((n=Math.exp(n))-1/n)/2}function rt(n){return((n=Math.exp(n))+1/n)/2}function ut(n){return((n=Math.exp(2*n))-1)/(n+1)}function it(n){return(n=Math.sin(n/2))*n}function ot(){}function at(n,t,e){return this instanceof at?(this.h=+n,this.s=+t,void(this.l=+e)):arguments.length<2?n instanceof at?new at(n.h,n.s,n.l):bt(""+n,_t,at):new at(n,t,e)}function ct(n,t,e){function r(n){return n>360?n-=360:0>n&&(n+=360),60>n?i+(o-i)*n/60:180>n?o:240>n?i+(o-i)*(240-n)/60:i}function u(n){return Math.round(255*r(n))}var i,o;return n=isNaN(n)?0:(n%=360)<0?n+360:n,t=isNaN(t)?0:0>t?0:t>1?1:t,e=0>e?0:e>1?1:e,o=.5>=e?e*(1+t):e+t-e*t,i=2*e-o,new mt(u(n+120),u(n),u(n-120))}function lt(n,t,e){return this instanceof lt?(this.h=+n,this.c=+t,void(this.l=+e)):arguments.length<2?n instanceof lt?new lt(n.h,n.c,n.l):n instanceof ft?gt(n.l,n.a,n.b):gt((n=wt((n=ta.rgb(n)).r,n.g,n.b)).l,n.a,n.b):new lt(n,t,e)}function st(n,t,e){return isNaN(n)&&(n=0),isNaN(t)&&(t=0),new ft(e,Math.cos(n*=Da)*t,Math.sin(n)*t)}function ft(n,t,e){return this instanceof ft?(this.l=+n,this.a=+t,void(this.b=+e)):arguments.length<2?n instanceof ft?new ft(n.l,n.a,n.b):n instanceof lt?st(n.h,n.c,n.l):wt((n=mt(n)).r,n.g,n.b):new ft(n,t,e)}function ht(n,t,e){var r=(n+16)/116,u=r+t/500,i=r-e/200;return u=pt(u)*Xa,r=pt(r)*$a,i=pt(i)*Ba,new mt(dt(3.2404542*u-1.5371385*r-.4985314*i),dt(-.969266*u+1.8760108*r+.041556*i),dt(.0556434*u-.2040259*r+1.0572252*i))}function gt(n,t,e){return n>0?new lt(Math.atan2(e,t)*Pa,Math.sqrt(t*t+e*e),n):new lt(0/0,0/0,n)}function pt(n){return n>.206893034?n*n*n:(n-4/29)/7.787037}function vt(n){return n>.008856?Math.pow(n,1/3):7.787037*n+4/29}function dt(n){return Math.round(255*(.00304>=n?12.92*n:1.055*Math.pow(n,1/2.4)-.055))}function mt(n,t,e){return this instanceof mt?(this.r=~~n,this.g=~~t,void(this.b=~~e)):arguments.length<2?n instanceof mt?new mt(n.r,n.g,n.b):bt(""+n,mt,ct):new mt(n,t,e)}function yt(n){return new mt(n>>16,n>>8&255,255&n)}function Mt(n){return yt(n)+""}function xt(n){return 16>n?"0"+Math.max(0,n).toString(16):Math.min(255,n).toString(16)}function bt(n,t,e){var r,u,i,o=0,a=0,c=0;if(r=/([a-z]+)\((.*)\)/.exec(n=n.toLowerCase()))switch(u=r[2].split(","),r[1]){case"hsl":return e(parseFloat(u[0]),parseFloat(u[1])/100,parseFloat(u[2])/100);case"rgb":return t(kt(u[0]),kt(u[1]),kt(u[2]))}return(i=Ga.get(n))?t(i.r,i.g,i.b):(null==n||"#"!==n.charAt(0)||isNaN(i=parseInt(n.slice(1),16))||(4===n.length?(o=(3840&i)>>4,o=o>>4|o,a=240&i,a=a>>4|a,c=15&i,c=c<<4|c):7===n.length&&(o=(16711680&i)>>16,a=(65280&i)>>8,c=255&i)),t(o,a,c))}function _t(n,t,e){var r,u,i=Math.min(n/=255,t/=255,e/=255),o=Math.max(n,t,e),a=o-i,c=(o+i)/2;return a?(u=.5>c?a/(o+i):a/(2-o-i),r=n==o?(t-e)/a+(e>t?6:0):t==o?(e-n)/a+2:(n-t)/a+4,r*=60):(r=0/0,u=c>0&&1>c?0:r),new at(r,u,c)}function wt(n,t,e){n=St(n),t=St(t),e=St(e);var r=vt((.4124564*n+.3575761*t+.1804375*e)/Xa),u=vt((.2126729*n+.7151522*t+.072175*e)/$a),i=vt((.0193339*n+.119192*t+.9503041*e)/Ba);return ft(116*u-16,500*(r-u),200*(u-i))}function St(n){return(n/=255)<=.04045?n/12.92:Math.pow((n+.055)/1.055,2.4)}function kt(n){var t=parseFloat(n);return"%"===n.charAt(n.length-1)?Math.round(2.55*t):t}function Et(n){return"function"==typeof n?n:function(){return n}}function At(n){return function(t,e,r){return 2===arguments.length&&"function"==typeof e&&(r=e,e=null),Nt(t,e,n,r)}}function Nt(n,t,e,r){function u(){var n,t=c.status;if(!t&&zt(c)||t>=200&&300>t||304===t){try{n=e.call(i,c)}catch(r){return void o.error.call(i,r)}o.load.call(i,n)}else o.error.call(i,c)}var i={},o=ta.dispatch("beforesend","progress","load","error"),a={},c=new XMLHttpRequest,l=null;return!this.XDomainRequest||"withCredentials"in c||!/^(http(s)?:)?\/\//.test(n)||(c=new XDomainRequest),"onload"in c?c.onload=c.onerror=u:c.onreadystatechange=function(){c.readyState>3&&u()},c.onprogress=function(n){var t=ta.event;ta.event=n;try{o.progress.call(i,c)}finally{ta.event=t}},i.header=function(n,t){return n=(n+"").toLowerCase(),arguments.length<2?a[n]:(null==t?delete a[n]:a[n]=t+"",i)},i.mimeType=function(n){return arguments.length?(t=null==n?null:n+"",i):t},i.responseType=function(n){return arguments.length?(l=n,i):l},i.response=function(n){return e=n,i},["get","post"].forEach(function(n){i[n]=function(){return i.send.apply(i,[n].concat(ra(arguments)))}}),i.send=function(e,r,u){if(2===arguments.length&&"function"==typeof r&&(u=r,r=null),c.open(e,n,!0),null==t||"accept"in a||(a.accept=t+",*/*"),c.setRequestHeader)for(var s in a)c.setRequestHeader(s,a[s]);return null!=t&&c.overrideMimeType&&c.overrideMimeType(t),null!=l&&(c.responseType=l),null!=u&&i.on("error",u).on("load",function(n){u(null,n)}),o.beforesend.call(i,c),c.send(null==r?null:r),i},i.abort=function(){return c.abort(),i},ta.rebind(i,o,"on"),null==r?i:i.get(Ct(r))}function Ct(n){return 1===n.length?function(t,e){n(null==t?e:null)}:n}function zt(n){var t=n.responseType;return t&&"text"!==t?n.response:n.responseText}function qt(){var n=Lt(),t=Tt()-n;t>24?(isFinite(t)&&(clearTimeout(tc),tc=setTimeout(qt,t)),nc=0):(nc=1,rc(qt))}function Lt(){var n=Date.now();for(ec=Ka;ec;)n>=ec.t&&(ec.f=ec.c(n-ec.t)),ec=ec.n;return n}function Tt(){for(var n,t=Ka,e=1/0;t;)t.f?t=n?n.n=t.n:Ka=t.n:(t.t<e&&(e=t.t),t=(n=t).n);return Qa=n,e}function Rt(n,t){return t-(n?Math.ceil(Math.log(n)/Math.LN10):1)}function Dt(n,t){var e=Math.pow(10,3*ga(8-t));return{scale:t>8?function(n){return n/e}:function(n){return n*e},symbol:n}}function Pt(n){var t=n.decimal,e=n.thousands,r=n.grouping,u=n.currency,i=r&&e?function(n,t){for(var u=n.length,i=[],o=0,a=r[0],c=0;u>0&&a>0&&(c+a+1>t&&(a=Math.max(1,t-c)),i.push(n.substring(u-=a,u+a)),!((c+=a+1)>t));)a=r[o=(o+1)%r.length];return i.reverse().join(e)}:y;return function(n){var e=ic.exec(n),r=e[1]||" ",o=e[2]||">",a=e[3]||"-",c=e[4]||"",l=e[5],s=+e[6],f=e[7],h=e[8],g=e[9],p=1,v="",d="",m=!1,y=!0;switch(h&&(h=+h.substring(1)),(l||"0"===r&&"="===o)&&(l=r="0",o="="),g){case"n":f=!0,g="g";break;case"%":p=100,d="%",g="f";break;case"p":p=100,d="%",g="r";break;case"b":case"o":case"x":case"X":"#"===c&&(v="0"+g.toLowerCase());case"c":y=!1;case"d":m=!0,h=0;break;case"s":p=-1,g="r"}"$"===c&&(v=u[0],d=u[1]),"r"!=g||h||(g="g"),null!=h&&("g"==g?h=Math.max(1,Math.min(21,h)):("e"==g||"f"==g)&&(h=Math.max(0,Math.min(20,h)))),g=oc.get(g)||Ut;var M=l&&f;return function(n){var e=d;if(m&&n%1)return"";var u=0>n||0===n&&0>1/n?(n=-n,"-"):"-"===a?"":a;if(0>p){var c=ta.formatPrefix(n,h);n=c.scale(n),e=c.symbol+d}else n*=p;n=g(n,h);var x,b,_=n.lastIndexOf(".");if(0>_){var w=y?n.lastIndexOf("e"):-1;0>w?(x=n,b=""):(x=n.substring(0,w),b=n.substring(w))}else x=n.substring(0,_),b=t+n.substring(_+1);!l&&f&&(x=i(x,1/0));var S=v.length+x.length+b.length+(M?0:u.length),k=s>S?new Array(S=s-S+1).join(r):"";return M&&(x=i(k+x,k.length?s-b.length:1/0)),u+=v,n=x+b,("<"===o?u+n+k:">"===o?k+u+n:"^"===o?k.substring(0,S>>=1)+u+n+k.substring(S):u+(M?n:k+n))+e}}}function Ut(n){return n+""}function jt(){this._=new Date(arguments.length>1?Date.UTC.apply(this,arguments):arguments[0])}function Ft(n,t,e){function r(t){var e=n(t),r=i(e,1);return r-t>t-e?e:r}function u(e){return t(e=n(new cc(e-1)),1),e}function i(n,e){return t(n=new cc(+n),e),n}function o(n,r,i){var o=u(n),a=[];if(i>1)for(;r>o;)e(o)%i||a.push(new Date(+o)),t(o,1);else for(;r>o;)a.push(new Date(+o)),t(o,1);return a}function a(n,t,e){try{cc=jt;var r=new jt;return r._=n,o(r,t,e)}finally{cc=Date}}n.floor=n,n.round=r,n.ceil=u,n.offset=i,n.range=o;var c=n.utc=Ht(n);return c.floor=c,c.round=Ht(r),c.ceil=Ht(u),c.offset=Ht(i),c.range=a,n}function Ht(n){return function(t,e){try{cc=jt;var r=new jt;return r._=t,n(r,e)._}finally{cc=Date}}}function Ot(n){function t(n){function t(t){for(var e,u,i,o=[],a=-1,c=0;++a<r;)37===n.charCodeAt(a)&&(o.push(n.slice(c,a)),null!=(u=sc[e=n.charAt(++a)])&&(e=n.charAt(++a)),(i=N[e])&&(e=i(t,null==u?"e"===e?" ":"0":u)),o.push(e),c=a+1);return o.push(n.slice(c,a)),o.join("")}var r=n.length;return t.parse=function(t){var r={y:1900,m:0,d:1,H:0,M:0,S:0,L:0,Z:null},u=e(r,n,t,0);if(u!=t.length)return null;"p"in r&&(r.H=r.H%12+12*r.p);var i=null!=r.Z&&cc!==jt,o=new(i?jt:cc);return"j"in r?o.setFullYear(r.y,0,r.j):"w"in r&&("W"in r||"U"in r)?(o.setFullYear(r.y,0,1),o.setFullYear(r.y,0,"W"in r?(r.w+6)%7+7*r.W-(o.getDay()+5)%7:r.w+7*r.U-(o.getDay()+6)%7)):o.setFullYear(r.y,r.m,r.d),o.setHours(r.H+(r.Z/100|0),r.M+r.Z%100,r.S,r.L),i?o._:o},t.toString=function(){return n},t}function e(n,t,e,r){for(var u,i,o,a=0,c=t.length,l=e.length;c>a;){if(r>=l)return-1;if(u=t.charCodeAt(a++),37===u){if(o=t.charAt(a++),i=C[o in sc?t.charAt(a++):o],!i||(r=i(n,e,r))<0)return-1}else if(u!=e.charCodeAt(r++))return-1}return r}function r(n,t,e){_.lastIndex=0;var r=_.exec(t.slice(e));return r?(n.w=w.get(r[0].toLowerCase()),e+r[0].length):-1}function u(n,t,e){x.lastIndex=0;var r=x.exec(t.slice(e));return r?(n.w=b.get(r[0].toLowerCase()),e+r[0].length):-1}function i(n,t,e){E.lastIndex=0;var r=E.exec(t.slice(e));return r?(n.m=A.get(r[0].toLowerCase()),e+r[0].length):-1}function o(n,t,e){S.lastIndex=0;var r=S.exec(t.slice(e));return r?(n.m=k.get(r[0].toLowerCase()),e+r[0].length):-1}function a(n,t,r){return e(n,N.c.toString(),t,r)}function c(n,t,r){return e(n,N.x.toString(),t,r)}function l(n,t,r){return e(n,N.X.toString(),t,r)}function s(n,t,e){var r=M.get(t.slice(e,e+=2).toLowerCase());return null==r?-1:(n.p=r,e)}var f=n.dateTime,h=n.date,g=n.time,p=n.periods,v=n.days,d=n.shortDays,m=n.months,y=n.shortMonths;t.utc=function(n){function e(n){try{cc=jt;var t=new cc;return t._=n,r(t)}finally{cc=Date}}var r=t(n);return e.parse=function(n){try{cc=jt;var t=r.parse(n);return t&&t._}finally{cc=Date}},e.toString=r.toString,e},t.multi=t.utc.multi=ae;var M=ta.map(),x=Yt(v),b=Zt(v),_=Yt(d),w=Zt(d),S=Yt(m),k=Zt(m),E=Yt(y),A=Zt(y);p.forEach(function(n,t){M.set(n.toLowerCase(),t)});var N={a:function(n){return d[n.getDay()]},A:function(n){return v[n.getDay()]},b:function(n){return y[n.getMonth()]},B:function(n){return m[n.getMonth()]},c:t(f),d:function(n,t){return It(n.getDate(),t,2)},e:function(n,t){return It(n.getDate(),t,2)},H:function(n,t){return It(n.getHours(),t,2)},I:function(n,t){return It(n.getHours()%12||12,t,2)},j:function(n,t){return It(1+ac.dayOfYear(n),t,3)},L:function(n,t){return It(n.getMilliseconds(),t,3)},m:function(n,t){return It(n.getMonth()+1,t,2)},M:function(n,t){return It(n.getMinutes(),t,2)},p:function(n){return p[+(n.getHours()>=12)]},S:function(n,t){return It(n.getSeconds(),t,2)},U:function(n,t){return It(ac.sundayOfYear(n),t,2)},w:function(n){return n.getDay()},W:function(n,t){return It(ac.mondayOfYear(n),t,2)},x:t(h),X:t(g),y:function(n,t){return It(n.getFullYear()%100,t,2)},Y:function(n,t){return It(n.getFullYear()%1e4,t,4)},Z:ie,"%":function(){return"%"}},C={a:r,A:u,b:i,B:o,c:a,d:Qt,e:Qt,H:te,I:te,j:ne,L:ue,m:Kt,M:ee,p:s,S:re,U:Xt,w:Vt,W:$t,x:c,X:l,y:Wt,Y:Bt,Z:Jt,"%":oe};return t}function It(n,t,e){var r=0>n?"-":"",u=(r?-n:n)+"",i=u.length;return r+(e>i?new Array(e-i+1).join(t)+u:u)}function Yt(n){return new RegExp("^(?:"+n.map(ta.requote).join("|")+")","i")}function Zt(n){for(var t=new l,e=-1,r=n.length;++e<r;)t.set(n[e].toLowerCase(),e);return t}function Vt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+1));return r?(n.w=+r[0],e+r[0].length):-1}function Xt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e));return r?(n.U=+r[0],e+r[0].length):-1}function $t(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e));return r?(n.W=+r[0],e+r[0].length):-1}function Bt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+4));return r?(n.y=+r[0],e+r[0].length):-1}function Wt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.y=Gt(+r[0]),e+r[0].length):-1}function Jt(n,t,e){return/^[+-]\d{4}$/.test(t=t.slice(e,e+5))?(n.Z=-t,e+5):-1}function Gt(n){return n+(n>68?1900:2e3)}function Kt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.m=r[0]-1,e+r[0].length):-1}function Qt(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.d=+r[0],e+r[0].length):-1}function ne(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+3));return r?(n.j=+r[0],e+r[0].length):-1}function te(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.H=+r[0],e+r[0].length):-1}function ee(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.M=+r[0],e+r[0].length):-1}function re(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+2));return r?(n.S=+r[0],e+r[0].length):-1}function ue(n,t,e){fc.lastIndex=0;var r=fc.exec(t.slice(e,e+3));return r?(n.L=+r[0],e+r[0].length):-1}function ie(n){var t=n.getTimezoneOffset(),e=t>0?"-":"+",r=ga(t)/60|0,u=ga(t)%60;return e+It(r,"0",2)+It(u,"0",2)}function oe(n,t,e){hc.lastIndex=0;var r=hc.exec(t.slice(e,e+1));return r?e+r[0].length:-1}function ae(n){for(var t=n.length,e=-1;++e<t;)n[e][0]=this(n[e][0]);return function(t){for(var e=0,r=n[e];!r[1](t);)r=n[++e];return r[0](t)}}function ce(){}function le(n,t,e){var r=e.s=n+t,u=r-n,i=r-u;e.t=n-i+(t-u)}function se(n,t){n&&dc.hasOwnProperty(n.type)&&dc[n.type](n,t)}function fe(n,t,e){var r,u=-1,i=n.length-e;for(t.lineStart();++u<i;)r=n[u],t.point(r[0],r[1],r[2]);t.lineEnd()}function he(n,t){var e=-1,r=n.length;for(t.polygonStart();++e<r;)fe(n[e],t,1);t.polygonEnd()}function ge(){function n(n,t){n*=Da,t=t*Da/2+qa/4;var e=n-r,o=e>=0?1:-1,a=o*e,c=Math.cos(t),l=Math.sin(t),s=i*l,f=u*c+s*Math.cos(a),h=s*o*Math.sin(a);yc.add(Math.atan2(h,f)),r=n,u=c,i=l}var t,e,r,u,i;Mc.point=function(o,a){Mc.point=n,r=(t=o)*Da,u=Math.cos(a=(e=a)*Da/2+qa/4),i=Math.sin(a)},Mc.lineEnd=function(){n(t,e)}}function pe(n){var t=n[0],e=n[1],r=Math.cos(e);return[r*Math.cos(t),r*Math.sin(t),Math.sin(e)]}function ve(n,t){return n[0]*t[0]+n[1]*t[1]+n[2]*t[2]}function de(n,t){return[n[1]*t[2]-n[2]*t[1],n[2]*t[0]-n[0]*t[2],n[0]*t[1]-n[1]*t[0]]}function me(n,t){n[0]+=t[0],n[1]+=t[1],n[2]+=t[2]}function ye(n,t){return[n[0]*t,n[1]*t,n[2]*t]}function Me(n){var t=Math.sqrt(n[0]*n[0]+n[1]*n[1]+n[2]*n[2]);n[0]/=t,n[1]/=t,n[2]/=t}function xe(n){return[Math.atan2(n[1],n[0]),tt(n[2])]}function be(n,t){return ga(n[0]-t[0])<Ca&&ga(n[1]-t[1])<Ca}function _e(n,t){n*=Da;var e=Math.cos(t*=Da);we(e*Math.cos(n),e*Math.sin(n),Math.sin(t))}function we(n,t,e){++xc,_c+=(n-_c)/xc,wc+=(t-wc)/xc,Sc+=(e-Sc)/xc}function Se(){function n(n,u){n*=Da;var i=Math.cos(u*=Da),o=i*Math.cos(n),a=i*Math.sin(n),c=Math.sin(u),l=Math.atan2(Math.sqrt((l=e*c-r*a)*l+(l=r*o-t*c)*l+(l=t*a-e*o)*l),t*o+e*a+r*c);bc+=l,kc+=l*(t+(t=o)),Ec+=l*(e+(e=a)),Ac+=l*(r+(r=c)),we(t,e,r)}var t,e,r;qc.point=function(u,i){u*=Da;var o=Math.cos(i*=Da);t=o*Math.cos(u),e=o*Math.sin(u),r=Math.sin(i),qc.point=n,we(t,e,r)}}function ke(){qc.point=_e}function Ee(){function n(n,t){n*=Da;var e=Math.cos(t*=Da),o=e*Math.cos(n),a=e*Math.sin(n),c=Math.sin(t),l=u*c-i*a,s=i*o-r*c,f=r*a-u*o,h=Math.sqrt(l*l+s*s+f*f),g=r*o+u*a+i*c,p=h&&-nt(g)/h,v=Math.atan2(h,g);Nc+=p*l,Cc+=p*s,zc+=p*f,bc+=v,kc+=v*(r+(r=o)),Ec+=v*(u+(u=a)),Ac+=v*(i+(i=c)),we(r,u,i)}var t,e,r,u,i;qc.point=function(o,a){t=o,e=a,qc.point=n,o*=Da;var c=Math.cos(a*=Da);r=c*Math.cos(o),u=c*Math.sin(o),i=Math.sin(a),we(r,u,i)},qc.lineEnd=function(){n(t,e),qc.lineEnd=ke,qc.point=_e}}function Ae(n,t){function e(e,r){return e=n(e,r),t(e[0],e[1])}return n.invert&&t.invert&&(e.invert=function(e,r){return e=t.invert(e,r),e&&n.invert(e[0],e[1])}),e}function Ne(){return!0}function Ce(n,t,e,r,u){var i=[],o=[];if(n.forEach(function(n){if(!((t=n.length-1)<=0)){var t,e=n[0],r=n[t];if(be(e,r)){u.lineStart();for(var a=0;t>a;++a)u.point((e=n[a])[0],e[1]);return void u.lineEnd()}var c=new qe(e,n,null,!0),l=new qe(e,null,c,!1);c.o=l,i.push(c),o.push(l),c=new qe(r,n,null,!1),l=new qe(r,null,c,!0),c.o=l,i.push(c),o.push(l)}}),o.sort(t),ze(i),ze(o),i.length){for(var a=0,c=e,l=o.length;l>a;++a)o[a].e=c=!c;for(var s,f,h=i[0];;){for(var g=h,p=!0;g.v;)if((g=g.n)===h)return;s=g.z,u.lineStart();do{if(g.v=g.o.v=!0,g.e){if(p)for(var a=0,l=s.length;l>a;++a)u.point((f=s[a])[0],f[1]);else r(g.x,g.n.x,1,u);g=g.n}else{if(p){s=g.p.z;for(var a=s.length-1;a>=0;--a)u.point((f=s[a])[0],f[1])}else r(g.x,g.p.x,-1,u);g=g.p}g=g.o,s=g.z,p=!p}while(!g.v);u.lineEnd()}}}function ze(n){if(t=n.length){for(var t,e,r=0,u=n[0];++r<t;)u.n=e=n[r],e.p=u,u=e;u.n=e=n[0],e.p=u}}function qe(n,t,e,r){this.x=n,this.z=t,this.o=e,this.e=r,this.v=!1,this.n=this.p=null}function Le(n,t,e,r){return function(u,i){function o(t,e){var r=u(t,e);n(t=r[0],e=r[1])&&i.point(t,e)}function a(n,t){var e=u(n,t);d.point(e[0],e[1])}function c(){y.point=a,d.lineStart()}function l(){y.point=o,d.lineEnd()}function s(n,t){v.push([n,t]);var e=u(n,t);x.point(e[0],e[1])}function f(){x.lineStart(),v=[]}function h(){s(v[0][0],v[0][1]),x.lineEnd();var n,t=x.clean(),e=M.buffer(),r=e.length;if(v.pop(),p.push(v),v=null,r)if(1&t){n=e[0];var u,r=n.length-1,o=-1;if(r>0){for(b||(i.polygonStart(),b=!0),i.lineStart();++o<r;)i.point((u=n[o])[0],u[1]);i.lineEnd()}}else r>1&&2&t&&e.push(e.pop().concat(e.shift())),g.push(e.filter(Te))}var g,p,v,d=t(i),m=u.invert(r[0],r[1]),y={point:o,lineStart:c,lineEnd:l,polygonStart:function(){y.point=s,y.lineStart=f,y.lineEnd=h,g=[],p=[]},polygonEnd:function(){y.point=o,y.lineStart=c,y.lineEnd=l,g=ta.merge(g);var n=Fe(m,p);g.length?(b||(i.polygonStart(),b=!0),Ce(g,De,n,e,i)):n&&(b||(i.polygonStart(),b=!0),i.lineStart(),e(null,null,1,i),i.lineEnd()),b&&(i.polygonEnd(),b=!1),g=p=null},sphere:function(){i.polygonStart(),i.lineStart(),e(null,null,1,i),i.lineEnd(),i.polygonEnd()}},M=Re(),x=t(M),b=!1;return y}}function Te(n){return n.length>1}function Re(){var n,t=[];return{lineStart:function(){t.push(n=[])},point:function(t,e){n.push([t,e])},lineEnd:b,buffer:function(){var e=t;return t=[],n=null,e},rejoin:function(){t.length>1&&t.push(t.pop().concat(t.shift()))}}}function De(n,t){return((n=n.x)[0]<0?n[1]-Ra-Ca:Ra-n[1])-((t=t.x)[0]<0?t[1]-Ra-Ca:Ra-t[1])}function Pe(n){var t,e=0/0,r=0/0,u=0/0;return{lineStart:function(){n.lineStart(),t=1},point:function(i,o){var a=i>0?qa:-qa,c=ga(i-e);ga(c-qa)<Ca?(n.point(e,r=(r+o)/2>0?Ra:-Ra),n.point(u,r),n.lineEnd(),n.lineStart(),n.point(a,r),n.point(i,r),t=0):u!==a&&c>=qa&&(ga(e-u)<Ca&&(e-=u*Ca),ga(i-a)<Ca&&(i-=a*Ca),r=Ue(e,r,i,o),n.point(u,r),n.lineEnd(),n.lineStart(),n.point(a,r),t=0),n.point(e=i,r=o),u=a},lineEnd:function(){n.lineEnd(),e=r=0/0},clean:function(){return 2-t}}}function Ue(n,t,e,r){var u,i,o=Math.sin(n-e);return ga(o)>Ca?Math.atan((Math.sin(t)*(i=Math.cos(r))*Math.sin(e)-Math.sin(r)*(u=Math.cos(t))*Math.sin(n))/(u*i*o)):(t+r)/2}function je(n,t,e,r){var u;if(null==n)u=e*Ra,r.point(-qa,u),r.point(0,u),r.point(qa,u),r.point(qa,0),r.point(qa,-u),r.point(0,-u),r.point(-qa,-u),r.point(-qa,0),r.point(-qa,u);else if(ga(n[0]-t[0])>Ca){var i=n[0]<t[0]?qa:-qa;u=e*i/2,r.point(-i,u),r.point(0,u),r.point(i,u)}else r.point(t[0],t[1])}function Fe(n,t){var e=n[0],r=n[1],u=[Math.sin(e),-Math.cos(e),0],i=0,o=0;yc.reset();for(var a=0,c=t.length;c>a;++a){var l=t[a],s=l.length;if(s)for(var f=l[0],h=f[0],g=f[1]/2+qa/4,p=Math.sin(g),v=Math.cos(g),d=1;;){d===s&&(d=0),n=l[d];var m=n[0],y=n[1]/2+qa/4,M=Math.sin(y),x=Math.cos(y),b=m-h,_=b>=0?1:-1,w=_*b,S=w>qa,k=p*M;if(yc.add(Math.atan2(k*_*Math.sin(w),v*x+k*Math.cos(w))),i+=S?b+_*La:b,S^h>=e^m>=e){var E=de(pe(f),pe(n));Me(E);var A=de(u,E);Me(A);var N=(S^b>=0?-1:1)*tt(A[2]);(r>N||r===N&&(E[0]||E[1]))&&(o+=S^b>=0?1:-1)}if(!d++)break;h=m,p=M,v=x,f=n}}return(-Ca>i||Ca>i&&0>yc)^1&o}function He(n){function t(n,t){return Math.cos(n)*Math.cos(t)>i}function e(n){var e,i,c,l,s;return{lineStart:function(){l=c=!1,s=1},point:function(f,h){var g,p=[f,h],v=t(f,h),d=o?v?0:u(f,h):v?u(f+(0>f?qa:-qa),h):0;if(!e&&(l=c=v)&&n.lineStart(),v!==c&&(g=r(e,p),(be(e,g)||be(p,g))&&(p[0]+=Ca,p[1]+=Ca,v=t(p[0],p[1]))),v!==c)s=0,v?(n.lineStart(),g=r(p,e),n.point(g[0],g[1])):(g=r(e,p),n.point(g[0],g[1]),n.lineEnd()),e=g;else if(a&&e&&o^v){var m;d&i||!(m=r(p,e,!0))||(s=0,o?(n.lineStart(),n.point(m[0][0],m[0][1]),n.point(m[1][0],m[1][1]),n.lineEnd()):(n.point(m[1][0],m[1][1]),n.lineEnd(),n.lineStart(),n.point(m[0][0],m[0][1])))}!v||e&&be(e,p)||n.point(p[0],p[1]),e=p,c=v,i=d},lineEnd:function(){c&&n.lineEnd(),e=null},clean:function(){return s|(l&&c)<<1}}}function r(n,t,e){var r=pe(n),u=pe(t),o=[1,0,0],a=de(r,u),c=ve(a,a),l=a[0],s=c-l*l;if(!s)return!e&&n;var f=i*c/s,h=-i*l/s,g=de(o,a),p=ye(o,f),v=ye(a,h);me(p,v);var d=g,m=ve(p,d),y=ve(d,d),M=m*m-y*(ve(p,p)-1);if(!(0>M)){var x=Math.sqrt(M),b=ye(d,(-m-x)/y);if(me(b,p),b=xe(b),!e)return b;var _,w=n[0],S=t[0],k=n[1],E=t[1];w>S&&(_=w,w=S,S=_);var A=S-w,N=ga(A-qa)<Ca,C=N||Ca>A;if(!N&&k>E&&(_=k,k=E,E=_),C?N?k+E>0^b[1]<(ga(b[0]-w)<Ca?k:E):k<=b[1]&&b[1]<=E:A>qa^(w<=b[0]&&b[0]<=S)){var z=ye(d,(-m+x)/y);return me(z,p),[b,xe(z)]}}}function u(t,e){var r=o?n:qa-n,u=0;return-r>t?u|=1:t>r&&(u|=2),-r>e?u|=4:e>r&&(u|=8),u}var i=Math.cos(n),o=i>0,a=ga(i)>Ca,c=gr(n,6*Da);return Le(t,e,c,o?[0,-n]:[-qa,n-qa])}function Oe(n,t,e,r){return function(u){var i,o=u.a,a=u.b,c=o.x,l=o.y,s=a.x,f=a.y,h=0,g=1,p=s-c,v=f-l;if(i=n-c,p||!(i>0)){if(i/=p,0>p){if(h>i)return;g>i&&(g=i)}else if(p>0){if(i>g)return;i>h&&(h=i)}if(i=e-c,p||!(0>i)){if(i/=p,0>p){if(i>g)return;i>h&&(h=i)}else if(p>0){if(h>i)return;g>i&&(g=i)}if(i=t-l,v||!(i>0)){if(i/=v,0>v){if(h>i)return;g>i&&(g=i)}else if(v>0){if(i>g)return;i>h&&(h=i)}if(i=r-l,v||!(0>i)){if(i/=v,0>v){if(i>g)return;i>h&&(h=i)}else if(v>0){if(h>i)return;g>i&&(g=i)}return h>0&&(u.a={x:c+h*p,y:l+h*v}),1>g&&(u.b={x:c+g*p,y:l+g*v}),u}}}}}}function Ie(n,t,e,r){function u(r,u){return ga(r[0]-n)<Ca?u>0?0:3:ga(r[0]-e)<Ca?u>0?2:1:ga(r[1]-t)<Ca?u>0?1:0:u>0?3:2}function i(n,t){return o(n.x,t.x)}function o(n,t){var e=u(n,1),r=u(t,1);return e!==r?e-r:0===e?t[1]-n[1]:1===e?n[0]-t[0]:2===e?n[1]-t[1]:t[0]-n[0]}return function(a){function c(n){for(var t=0,e=d.length,r=n[1],u=0;e>u;++u)for(var i,o=1,a=d[u],c=a.length,l=a[0];c>o;++o)i=a[o],l[1]<=r?i[1]>r&&Q(l,i,n)>0&&++t:i[1]<=r&&Q(l,i,n)<0&&--t,l=i;return 0!==t}function l(i,a,c,l){var s=0,f=0;if(null==i||(s=u(i,c))!==(f=u(a,c))||o(i,a)<0^c>0){do l.point(0===s||3===s?n:e,s>1?r:t);while((s=(s+c+4)%4)!==f)}else l.point(a[0],a[1])}function s(u,i){return u>=n&&e>=u&&i>=t&&r>=i}function f(n,t){s(n,t)&&a.point(n,t)}function h(){C.point=p,d&&d.push(m=[]),S=!0,w=!1,b=_=0/0}function g(){v&&(p(y,M),x&&w&&A.rejoin(),v.push(A.buffer())),C.point=f,w&&a.lineEnd()}function p(n,t){n=Math.max(-Tc,Math.min(Tc,n)),t=Math.max(-Tc,Math.min(Tc,t));var e=s(n,t);if(d&&m.push([n,t]),S)y=n,M=t,x=e,S=!1,e&&(a.lineStart(),a.point(n,t));else if(e&&w)a.point(n,t);else{var r={a:{x:b,y:_},b:{x:n,y:t}};N(r)?(w||(a.lineStart(),a.point(r.a.x,r.a.y)),a.point(r.b.x,r.b.y),e||a.lineEnd(),k=!1):e&&(a.lineStart(),a.point(n,t),k=!1)}b=n,_=t,w=e}var v,d,m,y,M,x,b,_,w,S,k,E=a,A=Re(),N=Oe(n,t,e,r),C={point:f,lineStart:h,lineEnd:g,polygonStart:function(){a=A,v=[],d=[],k=!0},polygonEnd:function(){a=E,v=ta.merge(v);var t=c([n,r]),e=k&&t,u=v.length;(e||u)&&(a.polygonStart(),e&&(a.lineStart(),l(null,null,1,a),a.lineEnd()),u&&Ce(v,i,t,l,a),a.polygonEnd()),v=d=m=null}};return C}}function Ye(n){var t=0,e=qa/3,r=ir(n),u=r(t,e);return u.parallels=function(n){return arguments.length?r(t=n[0]*qa/180,e=n[1]*qa/180):[t/qa*180,e/qa*180]},u}function Ze(n,t){function e(n,t){var e=Math.sqrt(i-2*u*Math.sin(t))/u;return[e*Math.sin(n*=u),o-e*Math.cos(n)]}var r=Math.sin(n),u=(r+Math.sin(t))/2,i=1+r*(2*u-r),o=Math.sqrt(i)/u;return e.invert=function(n,t){var e=o-t;return[Math.atan2(n,e)/u,tt((i-(n*n+e*e)*u*u)/(2*u))]},e}function Ve(){function n(n,t){Dc+=u*n-r*t,r=n,u=t}var t,e,r,u;Hc.point=function(i,o){Hc.point=n,t=r=i,e=u=o},Hc.lineEnd=function(){n(t,e)}}function Xe(n,t){Pc>n&&(Pc=n),n>jc&&(jc=n),Uc>t&&(Uc=t),t>Fc&&(Fc=t)}function $e(){function n(n,t){o.push("M",n,",",t,i)}function t(n,t){o.push("M",n,",",t),a.point=e}function e(n,t){o.push("L",n,",",t)}function r(){a.point=n}function u(){o.push("Z")}var i=Be(4.5),o=[],a={point:n,lineStart:function(){a.point=t},lineEnd:r,polygonStart:function(){a.lineEnd=u},polygonEnd:function(){a.lineEnd=r,a.point=n},pointRadius:function(n){return i=Be(n),a},result:function(){if(o.length){var n=o.join("");return o=[],n}}};return a}function Be(n){return"m0,"+n+"a"+n+","+n+" 0 1,1 0,"+-2*n+"a"+n+","+n+" 0 1,1 0,"+2*n+"z"}function We(n,t){_c+=n,wc+=t,++Sc}function Je(){function n(n,r){var u=n-t,i=r-e,o=Math.sqrt(u*u+i*i);kc+=o*(t+n)/2,Ec+=o*(e+r)/2,Ac+=o,We(t=n,e=r)}var t,e;Ic.point=function(r,u){Ic.point=n,We(t=r,e=u)}}function Ge(){Ic.point=We}function Ke(){function n(n,t){var e=n-r,i=t-u,o=Math.sqrt(e*e+i*i);kc+=o*(r+n)/2,Ec+=o*(u+t)/2,Ac+=o,o=u*n-r*t,Nc+=o*(r+n),Cc+=o*(u+t),zc+=3*o,We(r=n,u=t)}var t,e,r,u;Ic.point=function(i,o){Ic.point=n,We(t=r=i,e=u=o)},Ic.lineEnd=function(){n(t,e)}}function Qe(n){function t(t,e){n.moveTo(t+o,e),n.arc(t,e,o,0,La)}function e(t,e){n.moveTo(t,e),a.point=r}function r(t,e){n.lineTo(t,e)}function u(){a.point=t}function i(){n.closePath()}var o=4.5,a={point:t,lineStart:function(){a.point=e},lineEnd:u,polygonStart:function(){a.lineEnd=i},polygonEnd:function(){a.lineEnd=u,a.point=t},pointRadius:function(n){return o=n,a},result:b};return a}function nr(n){function t(n){return(a?r:e)(n)}function e(t){return rr(t,function(e,r){e=n(e,r),t.point(e[0],e[1])})}function r(t){function e(e,r){e=n(e,r),t.point(e[0],e[1])}function r(){M=0/0,S.point=i,t.lineStart()}function i(e,r){var i=pe([e,r]),o=n(e,r);u(M,x,y,b,_,w,M=o[0],x=o[1],y=e,b=i[0],_=i[1],w=i[2],a,t),t.point(M,x)}function o(){S.point=e,t.lineEnd()}function c(){r(),S.point=l,S.lineEnd=s}function l(n,t){i(f=n,h=t),g=M,p=x,v=b,d=_,m=w,S.point=i}function s(){u(M,x,y,b,_,w,g,p,f,v,d,m,a,t),S.lineEnd=o,o()}var f,h,g,p,v,d,m,y,M,x,b,_,w,S={point:e,lineStart:r,lineEnd:o,polygonStart:function(){t.polygonStart(),S.lineStart=c
+},polygonEnd:function(){t.polygonEnd(),S.lineStart=r}};return S}function u(t,e,r,a,c,l,s,f,h,g,p,v,d,m){var y=s-t,M=f-e,x=y*y+M*M;if(x>4*i&&d--){var b=a+g,_=c+p,w=l+v,S=Math.sqrt(b*b+_*_+w*w),k=Math.asin(w/=S),E=ga(ga(w)-1)<Ca||ga(r-h)<Ca?(r+h)/2:Math.atan2(_,b),A=n(E,k),N=A[0],C=A[1],z=N-t,q=C-e,L=M*z-y*q;(L*L/x>i||ga((y*z+M*q)/x-.5)>.3||o>a*g+c*p+l*v)&&(u(t,e,r,a,c,l,N,C,E,b/=S,_/=S,w,d,m),m.point(N,C),u(N,C,E,b,_,w,s,f,h,g,p,v,d,m))}}var i=.5,o=Math.cos(30*Da),a=16;return t.precision=function(n){return arguments.length?(a=(i=n*n)>0&&16,t):Math.sqrt(i)},t}function tr(n){var t=nr(function(t,e){return n([t*Pa,e*Pa])});return function(n){return or(t(n))}}function er(n){this.stream=n}function rr(n,t){return{point:t,sphere:function(){n.sphere()},lineStart:function(){n.lineStart()},lineEnd:function(){n.lineEnd()},polygonStart:function(){n.polygonStart()},polygonEnd:function(){n.polygonEnd()}}}function ur(n){return ir(function(){return n})()}function ir(n){function t(n){return n=a(n[0]*Da,n[1]*Da),[n[0]*h+c,l-n[1]*h]}function e(n){return n=a.invert((n[0]-c)/h,(l-n[1])/h),n&&[n[0]*Pa,n[1]*Pa]}function r(){a=Ae(o=lr(m,M,x),i);var n=i(v,d);return c=g-n[0]*h,l=p+n[1]*h,u()}function u(){return s&&(s.valid=!1,s=null),t}var i,o,a,c,l,s,f=nr(function(n,t){return n=i(n,t),[n[0]*h+c,l-n[1]*h]}),h=150,g=480,p=250,v=0,d=0,m=0,M=0,x=0,b=Lc,_=y,w=null,S=null;return t.stream=function(n){return s&&(s.valid=!1),s=or(b(o,f(_(n)))),s.valid=!0,s},t.clipAngle=function(n){return arguments.length?(b=null==n?(w=n,Lc):He((w=+n)*Da),u()):w},t.clipExtent=function(n){return arguments.length?(S=n,_=n?Ie(n[0][0],n[0][1],n[1][0],n[1][1]):y,u()):S},t.scale=function(n){return arguments.length?(h=+n,r()):h},t.translate=function(n){return arguments.length?(g=+n[0],p=+n[1],r()):[g,p]},t.center=function(n){return arguments.length?(v=n[0]%360*Da,d=n[1]%360*Da,r()):[v*Pa,d*Pa]},t.rotate=function(n){return arguments.length?(m=n[0]%360*Da,M=n[1]%360*Da,x=n.length>2?n[2]%360*Da:0,r()):[m*Pa,M*Pa,x*Pa]},ta.rebind(t,f,"precision"),function(){return i=n.apply(this,arguments),t.invert=i.invert&&e,r()}}function or(n){return rr(n,function(t,e){n.point(t*Da,e*Da)})}function ar(n,t){return[n,t]}function cr(n,t){return[n>qa?n-La:-qa>n?n+La:n,t]}function lr(n,t,e){return n?t||e?Ae(fr(n),hr(t,e)):fr(n):t||e?hr(t,e):cr}function sr(n){return function(t,e){return t+=n,[t>qa?t-La:-qa>t?t+La:t,e]}}function fr(n){var t=sr(n);return t.invert=sr(-n),t}function hr(n,t){function e(n,t){var e=Math.cos(t),a=Math.cos(n)*e,c=Math.sin(n)*e,l=Math.sin(t),s=l*r+a*u;return[Math.atan2(c*i-s*o,a*r-l*u),tt(s*i+c*o)]}var r=Math.cos(n),u=Math.sin(n),i=Math.cos(t),o=Math.sin(t);return e.invert=function(n,t){var e=Math.cos(t),a=Math.cos(n)*e,c=Math.sin(n)*e,l=Math.sin(t),s=l*i-c*o;return[Math.atan2(c*i+l*o,a*r+s*u),tt(s*r-a*u)]},e}function gr(n,t){var e=Math.cos(n),r=Math.sin(n);return function(u,i,o,a){var c=o*t;null!=u?(u=pr(e,u),i=pr(e,i),(o>0?i>u:u>i)&&(u+=o*La)):(u=n+o*La,i=n-.5*c);for(var l,s=u;o>0?s>i:i>s;s-=c)a.point((l=xe([e,-r*Math.cos(s),-r*Math.sin(s)]))[0],l[1])}}function pr(n,t){var e=pe(t);e[0]-=n,Me(e);var r=nt(-e[1]);return((-e[2]<0?-r:r)+2*Math.PI-Ca)%(2*Math.PI)}function vr(n,t,e){var r=ta.range(n,t-Ca,e).concat(t);return function(n){return r.map(function(t){return[n,t]})}}function dr(n,t,e){var r=ta.range(n,t-Ca,e).concat(t);return function(n){return r.map(function(t){return[t,n]})}}function mr(n){return n.source}function yr(n){return n.target}function Mr(n,t,e,r){var u=Math.cos(t),i=Math.sin(t),o=Math.cos(r),a=Math.sin(r),c=u*Math.cos(n),l=u*Math.sin(n),s=o*Math.cos(e),f=o*Math.sin(e),h=2*Math.asin(Math.sqrt(it(r-t)+u*o*it(e-n))),g=1/Math.sin(h),p=h?function(n){var t=Math.sin(n*=h)*g,e=Math.sin(h-n)*g,r=e*c+t*s,u=e*l+t*f,o=e*i+t*a;return[Math.atan2(u,r)*Pa,Math.atan2(o,Math.sqrt(r*r+u*u))*Pa]}:function(){return[n*Pa,t*Pa]};return p.distance=h,p}function xr(){function n(n,u){var i=Math.sin(u*=Da),o=Math.cos(u),a=ga((n*=Da)-t),c=Math.cos(a);Yc+=Math.atan2(Math.sqrt((a=o*Math.sin(a))*a+(a=r*i-e*o*c)*a),e*i+r*o*c),t=n,e=i,r=o}var t,e,r;Zc.point=function(u,i){t=u*Da,e=Math.sin(i*=Da),r=Math.cos(i),Zc.point=n},Zc.lineEnd=function(){Zc.point=Zc.lineEnd=b}}function br(n,t){function e(t,e){var r=Math.cos(t),u=Math.cos(e),i=n(r*u);return[i*u*Math.sin(t),i*Math.sin(e)]}return e.invert=function(n,e){var r=Math.sqrt(n*n+e*e),u=t(r),i=Math.sin(u),o=Math.cos(u);return[Math.atan2(n*i,r*o),Math.asin(r&&e*i/r)]},e}function _r(n,t){function e(n,t){o>0?-Ra+Ca>t&&(t=-Ra+Ca):t>Ra-Ca&&(t=Ra-Ca);var e=o/Math.pow(u(t),i);return[e*Math.sin(i*n),o-e*Math.cos(i*n)]}var r=Math.cos(n),u=function(n){return Math.tan(qa/4+n/2)},i=n===t?Math.sin(n):Math.log(r/Math.cos(t))/Math.log(u(t)/u(n)),o=r*Math.pow(u(n),i)/i;return i?(e.invert=function(n,t){var e=o-t,r=K(i)*Math.sqrt(n*n+e*e);return[Math.atan2(n,e)/i,2*Math.atan(Math.pow(o/r,1/i))-Ra]},e):Sr}function wr(n,t){function e(n,t){var e=i-t;return[e*Math.sin(u*n),i-e*Math.cos(u*n)]}var r=Math.cos(n),u=n===t?Math.sin(n):(r-Math.cos(t))/(t-n),i=r/u+n;return ga(u)<Ca?ar:(e.invert=function(n,t){var e=i-t;return[Math.atan2(n,e)/u,i-K(u)*Math.sqrt(n*n+e*e)]},e)}function Sr(n,t){return[n,Math.log(Math.tan(qa/4+t/2))]}function kr(n){var t,e=ur(n),r=e.scale,u=e.translate,i=e.clipExtent;return e.scale=function(){var n=r.apply(e,arguments);return n===e?t?e.clipExtent(null):e:n},e.translate=function(){var n=u.apply(e,arguments);return n===e?t?e.clipExtent(null):e:n},e.clipExtent=function(n){var o=i.apply(e,arguments);if(o===e){if(t=null==n){var a=qa*r(),c=u();i([[c[0]-a,c[1]-a],[c[0]+a,c[1]+a]])}}else t&&(o=null);return o},e.clipExtent(null)}function Er(n,t){return[Math.log(Math.tan(qa/4+t/2)),-n]}function Ar(n){return n[0]}function Nr(n){return n[1]}function Cr(n){for(var t=n.length,e=[0,1],r=2,u=2;t>u;u++){for(;r>1&&Q(n[e[r-2]],n[e[r-1]],n[u])<=0;)--r;e[r++]=u}return e.slice(0,r)}function zr(n,t){return n[0]-t[0]||n[1]-t[1]}function qr(n,t,e){return(e[0]-t[0])*(n[1]-t[1])<(e[1]-t[1])*(n[0]-t[0])}function Lr(n,t,e,r){var u=n[0],i=e[0],o=t[0]-u,a=r[0]-i,c=n[1],l=e[1],s=t[1]-c,f=r[1]-l,h=(a*(c-l)-f*(u-i))/(f*o-a*s);return[u+h*o,c+h*s]}function Tr(n){var t=n[0],e=n[n.length-1];return!(t[0]-e[0]||t[1]-e[1])}function Rr(){tu(this),this.edge=this.site=this.circle=null}function Dr(n){var t=el.pop()||new Rr;return t.site=n,t}function Pr(n){Xr(n),Qc.remove(n),el.push(n),tu(n)}function Ur(n){var t=n.circle,e=t.x,r=t.cy,u={x:e,y:r},i=n.P,o=n.N,a=[n];Pr(n);for(var c=i;c.circle&&ga(e-c.circle.x)<Ca&&ga(r-c.circle.cy)<Ca;)i=c.P,a.unshift(c),Pr(c),c=i;a.unshift(c),Xr(c);for(var l=o;l.circle&&ga(e-l.circle.x)<Ca&&ga(r-l.circle.cy)<Ca;)o=l.N,a.push(l),Pr(l),l=o;a.push(l),Xr(l);var s,f=a.length;for(s=1;f>s;++s)l=a[s],c=a[s-1],Kr(l.edge,c.site,l.site,u);c=a[0],l=a[f-1],l.edge=Jr(c.site,l.site,null,u),Vr(c),Vr(l)}function jr(n){for(var t,e,r,u,i=n.x,o=n.y,a=Qc._;a;)if(r=Fr(a,o)-i,r>Ca)a=a.L;else{if(u=i-Hr(a,o),!(u>Ca)){r>-Ca?(t=a.P,e=a):u>-Ca?(t=a,e=a.N):t=e=a;break}if(!a.R){t=a;break}a=a.R}var c=Dr(n);if(Qc.insert(t,c),t||e){if(t===e)return Xr(t),e=Dr(t.site),Qc.insert(c,e),c.edge=e.edge=Jr(t.site,c.site),Vr(t),void Vr(e);if(!e)return void(c.edge=Jr(t.site,c.site));Xr(t),Xr(e);var l=t.site,s=l.x,f=l.y,h=n.x-s,g=n.y-f,p=e.site,v=p.x-s,d=p.y-f,m=2*(h*d-g*v),y=h*h+g*g,M=v*v+d*d,x={x:(d*y-g*M)/m+s,y:(h*M-v*y)/m+f};Kr(e.edge,l,p,x),c.edge=Jr(l,n,null,x),e.edge=Jr(n,p,null,x),Vr(t),Vr(e)}}function Fr(n,t){var e=n.site,r=e.x,u=e.y,i=u-t;if(!i)return r;var o=n.P;if(!o)return-1/0;e=o.site;var a=e.x,c=e.y,l=c-t;if(!l)return a;var s=a-r,f=1/i-1/l,h=s/l;return f?(-h+Math.sqrt(h*h-2*f*(s*s/(-2*l)-c+l/2+u-i/2)))/f+r:(r+a)/2}function Hr(n,t){var e=n.N;if(e)return Fr(e,t);var r=n.site;return r.y===t?r.x:1/0}function Or(n){this.site=n,this.edges=[]}function Ir(n){for(var t,e,r,u,i,o,a,c,l,s,f=n[0][0],h=n[1][0],g=n[0][1],p=n[1][1],v=Kc,d=v.length;d--;)if(i=v[d],i&&i.prepare())for(a=i.edges,c=a.length,o=0;c>o;)s=a[o].end(),r=s.x,u=s.y,l=a[++o%c].start(),t=l.x,e=l.y,(ga(r-t)>Ca||ga(u-e)>Ca)&&(a.splice(o,0,new Qr(Gr(i.site,s,ga(r-f)<Ca&&p-u>Ca?{x:f,y:ga(t-f)<Ca?e:p}:ga(u-p)<Ca&&h-r>Ca?{x:ga(e-p)<Ca?t:h,y:p}:ga(r-h)<Ca&&u-g>Ca?{x:h,y:ga(t-h)<Ca?e:g}:ga(u-g)<Ca&&r-f>Ca?{x:ga(e-g)<Ca?t:f,y:g}:null),i.site,null)),++c)}function Yr(n,t){return t.angle-n.angle}function Zr(){tu(this),this.x=this.y=this.arc=this.site=this.cy=null}function Vr(n){var t=n.P,e=n.N;if(t&&e){var r=t.site,u=n.site,i=e.site;if(r!==i){var o=u.x,a=u.y,c=r.x-o,l=r.y-a,s=i.x-o,f=i.y-a,h=2*(c*f-l*s);if(!(h>=-za)){var g=c*c+l*l,p=s*s+f*f,v=(f*g-l*p)/h,d=(c*p-s*g)/h,f=d+a,m=rl.pop()||new Zr;m.arc=n,m.site=u,m.x=v+o,m.y=f+Math.sqrt(v*v+d*d),m.cy=f,n.circle=m;for(var y=null,M=tl._;M;)if(m.y<M.y||m.y===M.y&&m.x<=M.x){if(!M.L){y=M.P;break}M=M.L}else{if(!M.R){y=M;break}M=M.R}tl.insert(y,m),y||(nl=m)}}}}function Xr(n){var t=n.circle;t&&(t.P||(nl=t.N),tl.remove(t),rl.push(t),tu(t),n.circle=null)}function $r(n){for(var t,e=Gc,r=Oe(n[0][0],n[0][1],n[1][0],n[1][1]),u=e.length;u--;)t=e[u],(!Br(t,n)||!r(t)||ga(t.a.x-t.b.x)<Ca&&ga(t.a.y-t.b.y)<Ca)&&(t.a=t.b=null,e.splice(u,1))}function Br(n,t){var e=n.b;if(e)return!0;var r,u,i=n.a,o=t[0][0],a=t[1][0],c=t[0][1],l=t[1][1],s=n.l,f=n.r,h=s.x,g=s.y,p=f.x,v=f.y,d=(h+p)/2,m=(g+v)/2;if(v===g){if(o>d||d>=a)return;if(h>p){if(i){if(i.y>=l)return}else i={x:d,y:c};e={x:d,y:l}}else{if(i){if(i.y<c)return}else i={x:d,y:l};e={x:d,y:c}}}else if(r=(h-p)/(v-g),u=m-r*d,-1>r||r>1)if(h>p){if(i){if(i.y>=l)return}else i={x:(c-u)/r,y:c};e={x:(l-u)/r,y:l}}else{if(i){if(i.y<c)return}else i={x:(l-u)/r,y:l};e={x:(c-u)/r,y:c}}else if(v>g){if(i){if(i.x>=a)return}else i={x:o,y:r*o+u};e={x:a,y:r*a+u}}else{if(i){if(i.x<o)return}else i={x:a,y:r*a+u};e={x:o,y:r*o+u}}return n.a=i,n.b=e,!0}function Wr(n,t){this.l=n,this.r=t,this.a=this.b=null}function Jr(n,t,e,r){var u=new Wr(n,t);return Gc.push(u),e&&Kr(u,n,t,e),r&&Kr(u,t,n,r),Kc[n.i].edges.push(new Qr(u,n,t)),Kc[t.i].edges.push(new Qr(u,t,n)),u}function Gr(n,t,e){var r=new Wr(n,null);return r.a=t,r.b=e,Gc.push(r),r}function Kr(n,t,e,r){n.a||n.b?n.l===e?n.b=r:n.a=r:(n.a=r,n.l=t,n.r=e)}function Qr(n,t,e){var r=n.a,u=n.b;this.edge=n,this.site=t,this.angle=e?Math.atan2(e.y-t.y,e.x-t.x):n.l===t?Math.atan2(u.x-r.x,r.y-u.y):Math.atan2(r.x-u.x,u.y-r.y)}function nu(){this._=null}function tu(n){n.U=n.C=n.L=n.R=n.P=n.N=null}function eu(n,t){var e=t,r=t.R,u=e.U;u?u.L===e?u.L=r:u.R=r:n._=r,r.U=u,e.U=r,e.R=r.L,e.R&&(e.R.U=e),r.L=e}function ru(n,t){var e=t,r=t.L,u=e.U;u?u.L===e?u.L=r:u.R=r:n._=r,r.U=u,e.U=r,e.L=r.R,e.L&&(e.L.U=e),r.R=e}function uu(n){for(;n.L;)n=n.L;return n}function iu(n,t){var e,r,u,i=n.sort(ou).pop();for(Gc=[],Kc=new Array(n.length),Qc=new nu,tl=new nu;;)if(u=nl,i&&(!u||i.y<u.y||i.y===u.y&&i.x<u.x))(i.x!==e||i.y!==r)&&(Kc[i.i]=new Or(i),jr(i),e=i.x,r=i.y),i=n.pop();else{if(!u)break;Ur(u.arc)}t&&($r(t),Ir(t));var o={cells:Kc,edges:Gc};return Qc=tl=Gc=Kc=null,o}function ou(n,t){return t.y-n.y||t.x-n.x}function au(n,t,e){return(n.x-e.x)*(t.y-n.y)-(n.x-t.x)*(e.y-n.y)}function cu(n){return n.x}function lu(n){return n.y}function su(){return{leaf:!0,nodes:[],point:null,x:null,y:null}}function fu(n,t,e,r,u,i){if(!n(t,e,r,u,i)){var o=.5*(e+u),a=.5*(r+i),c=t.nodes;c[0]&&fu(n,c[0],e,r,o,a),c[1]&&fu(n,c[1],o,r,u,a),c[2]&&fu(n,c[2],e,a,o,i),c[3]&&fu(n,c[3],o,a,u,i)}}function hu(n,t,e,r,u,i,o){var a,c=1/0;return function l(n,s,f,h,g){if(!(s>i||f>o||r>h||u>g)){if(p=n.point){var p,v=t-n.x,d=e-n.y,m=v*v+d*d;if(c>m){var y=Math.sqrt(c=m);r=t-y,u=e-y,i=t+y,o=e+y,a=p}}for(var M=n.nodes,x=.5*(s+h),b=.5*(f+g),_=t>=x,w=e>=b,S=w<<1|_,k=S+4;k>S;++S)if(n=M[3&S])switch(3&S){case 0:l(n,s,f,x,b);break;case 1:l(n,x,f,h,b);break;case 2:l(n,s,b,x,g);break;case 3:l(n,x,b,h,g)}}}(n,r,u,i,o),a}function gu(n,t){n=ta.rgb(n),t=ta.rgb(t);var e=n.r,r=n.g,u=n.b,i=t.r-e,o=t.g-r,a=t.b-u;return function(n){return"#"+xt(Math.round(e+i*n))+xt(Math.round(r+o*n))+xt(Math.round(u+a*n))}}function pu(n,t){var e,r={},u={};for(e in n)e in t?r[e]=mu(n[e],t[e]):u[e]=n[e];for(e in t)e in n||(u[e]=t[e]);return function(n){for(e in r)u[e]=r[e](n);return u}}function vu(n,t){return n=+n,t=+t,function(e){return n*(1-e)+t*e}}function du(n,t){var e,r,u,i=il.lastIndex=ol.lastIndex=0,o=-1,a=[],c=[];for(n+="",t+="";(e=il.exec(n))&&(r=ol.exec(t));)(u=r.index)>i&&(u=t.slice(i,u),a[o]?a[o]+=u:a[++o]=u),(e=e[0])===(r=r[0])?a[o]?a[o]+=r:a[++o]=r:(a[++o]=null,c.push({i:o,x:vu(e,r)})),i=ol.lastIndex;return i<t.length&&(u=t.slice(i),a[o]?a[o]+=u:a[++o]=u),a.length<2?c[0]?(t=c[0].x,function(n){return t(n)+""}):function(){return t}:(t=c.length,function(n){for(var e,r=0;t>r;++r)a[(e=c[r]).i]=e.x(n);return a.join("")})}function mu(n,t){for(var e,r=ta.interpolators.length;--r>=0&&!(e=ta.interpolators[r](n,t)););return e}function yu(n,t){var e,r=[],u=[],i=n.length,o=t.length,a=Math.min(n.length,t.length);for(e=0;a>e;++e)r.push(mu(n[e],t[e]));for(;i>e;++e)u[e]=n[e];for(;o>e;++e)u[e]=t[e];return function(n){for(e=0;a>e;++e)u[e]=r[e](n);return u}}function Mu(n){return function(t){return 0>=t?0:t>=1?1:n(t)}}function xu(n){return function(t){return 1-n(1-t)}}function bu(n){return function(t){return.5*(.5>t?n(2*t):2-n(2-2*t))}}function _u(n){return n*n}function wu(n){return n*n*n}function Su(n){if(0>=n)return 0;if(n>=1)return 1;var t=n*n,e=t*n;return 4*(.5>n?e:3*(n-t)+e-.75)}function ku(n){return function(t){return Math.pow(t,n)}}function Eu(n){return 1-Math.cos(n*Ra)}function Au(n){return Math.pow(2,10*(n-1))}function Nu(n){return 1-Math.sqrt(1-n*n)}function Cu(n,t){var e;return arguments.length<2&&(t=.45),arguments.length?e=t/La*Math.asin(1/n):(n=1,e=t/4),function(r){return 1+n*Math.pow(2,-10*r)*Math.sin((r-e)*La/t)}}function zu(n){return n||(n=1.70158),function(t){return t*t*((n+1)*t-n)}}function qu(n){return 1/2.75>n?7.5625*n*n:2/2.75>n?7.5625*(n-=1.5/2.75)*n+.75:2.5/2.75>n?7.5625*(n-=2.25/2.75)*n+.9375:7.5625*(n-=2.625/2.75)*n+.984375}function Lu(n,t){n=ta.hcl(n),t=ta.hcl(t);var e=n.h,r=n.c,u=n.l,i=t.h-e,o=t.c-r,a=t.l-u;return isNaN(o)&&(o=0,r=isNaN(r)?t.c:r),isNaN(i)?(i=0,e=isNaN(e)?t.h:e):i>180?i-=360:-180>i&&(i+=360),function(n){return st(e+i*n,r+o*n,u+a*n)+""}}function Tu(n,t){n=ta.hsl(n),t=ta.hsl(t);var e=n.h,r=n.s,u=n.l,i=t.h-e,o=t.s-r,a=t.l-u;return isNaN(o)&&(o=0,r=isNaN(r)?t.s:r),isNaN(i)?(i=0,e=isNaN(e)?t.h:e):i>180?i-=360:-180>i&&(i+=360),function(n){return ct(e+i*n,r+o*n,u+a*n)+""}}function Ru(n,t){n=ta.lab(n),t=ta.lab(t);var e=n.l,r=n.a,u=n.b,i=t.l-e,o=t.a-r,a=t.b-u;return function(n){return ht(e+i*n,r+o*n,u+a*n)+""}}function Du(n,t){return t-=n,function(e){return Math.round(n+t*e)}}function Pu(n){var t=[n.a,n.b],e=[n.c,n.d],r=ju(t),u=Uu(t,e),i=ju(Fu(e,t,-u))||0;t[0]*e[1]<e[0]*t[1]&&(t[0]*=-1,t[1]*=-1,r*=-1,u*=-1),this.rotate=(r?Math.atan2(t[1],t[0]):Math.atan2(-e[0],e[1]))*Pa,this.translate=[n.e,n.f],this.scale=[r,i],this.skew=i?Math.atan2(u,i)*Pa:0}function Uu(n,t){return n[0]*t[0]+n[1]*t[1]}function ju(n){var t=Math.sqrt(Uu(n,n));return t&&(n[0]/=t,n[1]/=t),t}function Fu(n,t,e){return n[0]+=e*t[0],n[1]+=e*t[1],n}function Hu(n,t){var e,r=[],u=[],i=ta.transform(n),o=ta.transform(t),a=i.translate,c=o.translate,l=i.rotate,s=o.rotate,f=i.skew,h=o.skew,g=i.scale,p=o.scale;return a[0]!=c[0]||a[1]!=c[1]?(r.push("translate(",null,",",null,")"),u.push({i:1,x:vu(a[0],c[0])},{i:3,x:vu(a[1],c[1])})):r.push(c[0]||c[1]?"translate("+c+")":""),l!=s?(l-s>180?s+=360:s-l>180&&(l+=360),u.push({i:r.push(r.pop()+"rotate(",null,")")-2,x:vu(l,s)})):s&&r.push(r.pop()+"rotate("+s+")"),f!=h?u.push({i:r.push(r.pop()+"skewX(",null,")")-2,x:vu(f,h)}):h&&r.push(r.pop()+"skewX("+h+")"),g[0]!=p[0]||g[1]!=p[1]?(e=r.push(r.pop()+"scale(",null,",",null,")"),u.push({i:e-4,x:vu(g[0],p[0])},{i:e-2,x:vu(g[1],p[1])})):(1!=p[0]||1!=p[1])&&r.push(r.pop()+"scale("+p+")"),e=u.length,function(n){for(var t,i=-1;++i<e;)r[(t=u[i]).i]=t.x(n);return r.join("")}}function Ou(n,t){return t=(t-=n=+n)||1/t,function(e){return(e-n)/t}}function Iu(n,t){return t=(t-=n=+n)||1/t,function(e){return Math.max(0,Math.min(1,(e-n)/t))}}function Yu(n){for(var t=n.source,e=n.target,r=Vu(t,e),u=[t];t!==r;)t=t.parent,u.push(t);for(var i=u.length;e!==r;)u.splice(i,0,e),e=e.parent;return u}function Zu(n){for(var t=[],e=n.parent;null!=e;)t.push(n),n=e,e=e.parent;return t.push(n),t}function Vu(n,t){if(n===t)return n;for(var e=Zu(n),r=Zu(t),u=e.pop(),i=r.pop(),o=null;u===i;)o=u,u=e.pop(),i=r.pop();return o}function Xu(n){n.fixed|=2}function $u(n){n.fixed&=-7}function Bu(n){n.fixed|=4,n.px=n.x,n.py=n.y}function Wu(n){n.fixed&=-5}function Ju(n,t,e){var r=0,u=0;if(n.charge=0,!n.leaf)for(var i,o=n.nodes,a=o.length,c=-1;++c<a;)i=o[c],null!=i&&(Ju(i,t,e),n.charge+=i.charge,r+=i.charge*i.cx,u+=i.charge*i.cy);if(n.point){n.leaf||(n.point.x+=Math.random()-.5,n.point.y+=Math.random()-.5);var l=t*e[n.point.index];n.charge+=n.pointCharge=l,r+=l*n.point.x,u+=l*n.point.y}n.cx=r/n.charge,n.cy=u/n.charge}function Gu(n,t){return ta.rebind(n,t,"sort","children","value"),n.nodes=n,n.links=ri,n}function Ku(n,t){for(var e=[n];null!=(n=e.pop());)if(t(n),(u=n.children)&&(r=u.length))for(var r,u;--r>=0;)e.push(u[r])}function Qu(n,t){for(var e=[n],r=[];null!=(n=e.pop());)if(r.push(n),(i=n.children)&&(u=i.length))for(var u,i,o=-1;++o<u;)e.push(i[o]);for(;null!=(n=r.pop());)t(n)}function ni(n){return n.children}function ti(n){return n.value}function ei(n,t){return t.value-n.value}function ri(n){return ta.merge(n.map(function(n){return(n.children||[]).map(function(t){return{source:n,target:t}})}))}function ui(n){return n.x}function ii(n){return n.y}function oi(n,t,e){n.y0=t,n.y=e}function ai(n){return ta.range(n.length)}function ci(n){for(var t=-1,e=n[0].length,r=[];++t<e;)r[t]=0;return r}function li(n){for(var t,e=1,r=0,u=n[0][1],i=n.length;i>e;++e)(t=n[e][1])>u&&(r=e,u=t);return r}function si(n){return n.reduce(fi,0)}function fi(n,t){return n+t[1]}function hi(n,t){return gi(n,Math.ceil(Math.log(t.length)/Math.LN2+1))}function gi(n,t){for(var e=-1,r=+n[0],u=(n[1]-r)/t,i=[];++e<=t;)i[e]=u*e+r;return i}function pi(n){return[ta.min(n),ta.max(n)]}function vi(n,t){return n.value-t.value}function di(n,t){var e=n._pack_next;n._pack_next=t,t._pack_prev=n,t._pack_next=e,e._pack_prev=t}function mi(n,t){n._pack_next=t,t._pack_prev=n}function yi(n,t){var e=t.x-n.x,r=t.y-n.y,u=n.r+t.r;return.999*u*u>e*e+r*r}function Mi(n){function t(n){s=Math.min(n.x-n.r,s),f=Math.max(n.x+n.r,f),h=Math.min(n.y-n.r,h),g=Math.max(n.y+n.r,g)}if((e=n.children)&&(l=e.length)){var e,r,u,i,o,a,c,l,s=1/0,f=-1/0,h=1/0,g=-1/0;if(e.forEach(xi),r=e[0],r.x=-r.r,r.y=0,t(r),l>1&&(u=e[1],u.x=u.r,u.y=0,t(u),l>2))for(i=e[2],wi(r,u,i),t(i),di(r,i),r._pack_prev=i,di(i,u),u=r._pack_next,o=3;l>o;o++){wi(r,u,i=e[o]);var p=0,v=1,d=1;for(a=u._pack_next;a!==u;a=a._pack_next,v++)if(yi(a,i)){p=1;break}if(1==p)for(c=r._pack_prev;c!==a._pack_prev&&!yi(c,i);c=c._pack_prev,d++);p?(d>v||v==d&&u.r<r.r?mi(r,u=a):mi(r=c,u),o--):(di(r,i),u=i,t(i))}var m=(s+f)/2,y=(h+g)/2,M=0;for(o=0;l>o;o++)i=e[o],i.x-=m,i.y-=y,M=Math.max(M,i.r+Math.sqrt(i.x*i.x+i.y*i.y));n.r=M,e.forEach(bi)}}function xi(n){n._pack_next=n._pack_prev=n}function bi(n){delete n._pack_next,delete n._pack_prev}function _i(n,t,e,r){var u=n.children;if(n.x=t+=r*n.x,n.y=e+=r*n.y,n.r*=r,u)for(var i=-1,o=u.length;++i<o;)_i(u[i],t,e,r)}function wi(n,t,e){var r=n.r+e.r,u=t.x-n.x,i=t.y-n.y;if(r&&(u||i)){var o=t.r+e.r,a=u*u+i*i;o*=o,r*=r;var c=.5+(r-o)/(2*a),l=Math.sqrt(Math.max(0,2*o*(r+a)-(r-=a)*r-o*o))/(2*a);e.x=n.x+c*u+l*i,e.y=n.y+c*i-l*u}else e.x=n.x+r,e.y=n.y}function Si(n,t){return n.parent==t.parent?1:2}function ki(n){var t=n.children;return t.length?t[0]:n.t}function Ei(n){var t,e=n.children;return(t=e.length)?e[t-1]:n.t}function Ai(n,t,e){var r=e/(t.i-n.i);t.c-=r,t.s+=e,n.c+=r,t.z+=e,t.m+=e}function Ni(n){for(var t,e=0,r=0,u=n.children,i=u.length;--i>=0;)t=u[i],t.z+=e,t.m+=e,e+=t.s+(r+=t.c)}function Ci(n,t,e){return n.a.parent===t.parent?n.a:e}function zi(n){return 1+ta.max(n,function(n){return n.y})}function qi(n){return n.reduce(function(n,t){return n+t.x},0)/n.length}function Li(n){var t=n.children;return t&&t.length?Li(t[0]):n}function Ti(n){var t,e=n.children;return e&&(t=e.length)?Ti(e[t-1]):n}function Ri(n){return{x:n.x,y:n.y,dx:n.dx,dy:n.dy}}function Di(n,t){var e=n.x+t[3],r=n.y+t[0],u=n.dx-t[1]-t[3],i=n.dy-t[0]-t[2];return 0>u&&(e+=u/2,u=0),0>i&&(r+=i/2,i=0),{x:e,y:r,dx:u,dy:i}}function Pi(n){var t=n[0],e=n[n.length-1];return e>t?[t,e]:[e,t]}function Ui(n){return n.rangeExtent?n.rangeExtent():Pi(n.range())}function ji(n,t,e,r){var u=e(n[0],n[1]),i=r(t[0],t[1]);return function(n){return i(u(n))}}function Fi(n,t){var e,r=0,u=n.length-1,i=n[r],o=n[u];return i>o&&(e=r,r=u,u=e,e=i,i=o,o=e),n[r]=t.floor(i),n[u]=t.ceil(o),n}function Hi(n){return n?{floor:function(t){return Math.floor(t/n)*n},ceil:function(t){return Math.ceil(t/n)*n}}:ml}function Oi(n,t,e,r){var u=[],i=[],o=0,a=Math.min(n.length,t.length)-1;for(n[a]<n[0]&&(n=n.slice().reverse(),t=t.slice().reverse());++o<=a;)u.push(e(n[o-1],n[o])),i.push(r(t[o-1],t[o]));return function(t){var e=ta.bisect(n,t,1,a)-1;return i[e](u[e](t))}}function Ii(n,t,e,r){function u(){var u=Math.min(n.length,t.length)>2?Oi:ji,c=r?Iu:Ou;return o=u(n,t,c,e),a=u(t,n,c,mu),i}function i(n){return o(n)}var o,a;return i.invert=function(n){return a(n)},i.domain=function(t){return arguments.length?(n=t.map(Number),u()):n},i.range=function(n){return arguments.length?(t=n,u()):t},i.rangeRound=function(n){return i.range(n).interpolate(Du)},i.clamp=function(n){return arguments.length?(r=n,u()):r},i.interpolate=function(n){return arguments.length?(e=n,u()):e},i.ticks=function(t){return Xi(n,t)},i.tickFormat=function(t,e){return $i(n,t,e)},i.nice=function(t){return Zi(n,t),u()},i.copy=function(){return Ii(n,t,e,r)},u()}function Yi(n,t){return ta.rebind(n,t,"range","rangeRound","interpolate","clamp")}function Zi(n,t){return Fi(n,Hi(Vi(n,t)[2]))}function Vi(n,t){null==t&&(t=10);var e=Pi(n),r=e[1]-e[0],u=Math.pow(10,Math.floor(Math.log(r/t)/Math.LN10)),i=t/r*u;return.15>=i?u*=10:.35>=i?u*=5:.75>=i&&(u*=2),e[0]=Math.ceil(e[0]/u)*u,e[1]=Math.floor(e[1]/u)*u+.5*u,e[2]=u,e}function Xi(n,t){return ta.range.apply(ta,Vi(n,t))}function $i(n,t,e){var r=Vi(n,t);if(e){var u=ic.exec(e);if(u.shift(),"s"===u[8]){var i=ta.formatPrefix(Math.max(ga(r[0]),ga(r[1])));return u[7]||(u[7]="."+Bi(i.scale(r[2]))),u[8]="f",e=ta.format(u.join("")),function(n){return e(i.scale(n))+i.symbol}}u[7]||(u[7]="."+Wi(u[8],r)),e=u.join("")}else e=",."+Bi(r[2])+"f";return ta.format(e)}function Bi(n){return-Math.floor(Math.log(n)/Math.LN10+.01)}function Wi(n,t){var e=Bi(t[2]);return n in yl?Math.abs(e-Bi(Math.max(ga(t[0]),ga(t[1]))))+ +("e"!==n):e-2*("%"===n)}function Ji(n,t,e,r){function u(n){return(e?Math.log(0>n?0:n):-Math.log(n>0?0:-n))/Math.log(t)}function i(n){return e?Math.pow(t,n):-Math.pow(t,-n)}function o(t){return n(u(t))}return o.invert=function(t){return i(n.invert(t))},o.domain=function(t){return arguments.length?(e=t[0]>=0,n.domain((r=t.map(Number)).map(u)),o):r},o.base=function(e){return arguments.length?(t=+e,n.domain(r.map(u)),o):t},o.nice=function(){var t=Fi(r.map(u),e?Math:xl);return n.domain(t),r=t.map(i),o},o.ticks=function(){var n=Pi(r),o=[],a=n[0],c=n[1],l=Math.floor(u(a)),s=Math.ceil(u(c)),f=t%1?2:t;if(isFinite(s-l)){if(e){for(;s>l;l++)for(var h=1;f>h;h++)o.push(i(l)*h);o.push(i(l))}else for(o.push(i(l));l++<s;)for(var h=f-1;h>0;h--)o.push(i(l)*h);for(l=0;o[l]<a;l++);for(s=o.length;o[s-1]>c;s--);o=o.slice(l,s)}return o},o.tickFormat=function(n,t){if(!arguments.length)return Ml;arguments.length<2?t=Ml:"function"!=typeof t&&(t=ta.format(t));var r,a=Math.max(.1,n/o.ticks().length),c=e?(r=1e-12,Math.ceil):(r=-1e-12,Math.floor);return function(n){return n/i(c(u(n)+r))<=a?t(n):""}},o.copy=function(){return Ji(n.copy(),t,e,r)},Yi(o,n)}function Gi(n,t,e){function r(t){return n(u(t))}var u=Ki(t),i=Ki(1/t);return r.invert=function(t){return i(n.invert(t))},r.domain=function(t){return arguments.length?(n.domain((e=t.map(Number)).map(u)),r):e},r.ticks=function(n){return Xi(e,n)},r.tickFormat=function(n,t){return $i(e,n,t)},r.nice=function(n){return r.domain(Zi(e,n))},r.exponent=function(o){return arguments.length?(u=Ki(t=o),i=Ki(1/t),n.domain(e.map(u)),r):t},r.copy=function(){return Gi(n.copy(),t,e)},Yi(r,n)}function Ki(n){return function(t){return 0>t?-Math.pow(-t,n):Math.pow(t,n)}}function Qi(n,t){function e(e){return i[((u.get(e)||("range"===t.t?u.set(e,n.push(e)):0/0))-1)%i.length]}function r(t,e){return ta.range(n.length).map(function(n){return t+e*n})}var u,i,o;return e.domain=function(r){if(!arguments.length)return n;n=[],u=new l;for(var i,o=-1,a=r.length;++o<a;)u.has(i=r[o])||u.set(i,n.push(i));return e[t.t].apply(e,t.a)},e.range=function(n){return arguments.length?(i=n,o=0,t={t:"range",a:arguments},e):i},e.rangePoints=function(u,a){arguments.length<2&&(a=0);var c=u[0],l=u[1],s=n.length<2?(c=(c+l)/2,0):(l-c)/(n.length-1+a);return i=r(c+s*a/2,s),o=0,t={t:"rangePoints",a:arguments},e},e.rangeRoundPoints=function(u,a){arguments.length<2&&(a=0);var c=u[0],l=u[1],s=n.length<2?(c=l=Math.round((c+l)/2),0):(l-c)/(n.length-1+a)|0;return i=r(c+Math.round(s*a/2+(l-c-(n.length-1+a)*s)/2),s),o=0,t={t:"rangeRoundPoints",a:arguments},e},e.rangeBands=function(u,a,c){arguments.length<2&&(a=0),arguments.length<3&&(c=a);var l=u[1]<u[0],s=u[l-0],f=u[1-l],h=(f-s)/(n.length-a+2*c);return i=r(s+h*c,h),l&&i.reverse(),o=h*(1-a),t={t:"rangeBands",a:arguments},e},e.rangeRoundBands=function(u,a,c){arguments.length<2&&(a=0),arguments.length<3&&(c=a);var l=u[1]<u[0],s=u[l-0],f=u[1-l],h=Math.floor((f-s)/(n.length-a+2*c));return i=r(s+Math.round((f-s-(n.length-a)*h)/2),h),l&&i.reverse(),o=Math.round(h*(1-a)),t={t:"rangeRoundBands",a:arguments},e},e.rangeBand=function(){return o},e.rangeExtent=function(){return Pi(t.a[0])},e.copy=function(){return Qi(n,t)},e.domain(n)}function no(n,t){function i(){var e=0,r=t.length;for(a=[];++e<r;)a[e-1]=ta.quantile(n,e/r);return o}function o(n){return isNaN(n=+n)?void 0:t[ta.bisect(a,n)]}var a;return o.domain=function(t){return arguments.length?(n=t.map(r).filter(u).sort(e),i()):n},o.range=function(n){return arguments.length?(t=n,i()):t},o.quantiles=function(){return a},o.invertExtent=function(e){return e=t.indexOf(e),0>e?[0/0,0/0]:[e>0?a[e-1]:n[0],e<a.length?a[e]:n[n.length-1]]},o.copy=function(){return no(n,t)},i()}function to(n,t,e){function r(t){return e[Math.max(0,Math.min(o,Math.floor(i*(t-n))))]}function u(){return i=e.length/(t-n),o=e.length-1,r}var i,o;return r.domain=function(e){return arguments.length?(n=+e[0],t=+e[e.length-1],u()):[n,t]},r.range=function(n){return arguments.length?(e=n,u()):e},r.invertExtent=function(t){return t=e.indexOf(t),t=0>t?0/0:t/i+n,[t,t+1/i]},r.copy=function(){return to(n,t,e)},u()}function eo(n,t){function e(e){return e>=e?t[ta.bisect(n,e)]:void 0}return e.domain=function(t){return arguments.length?(n=t,e):n},e.range=function(n){return arguments.length?(t=n,e):t},e.invertExtent=function(e){return e=t.indexOf(e),[n[e-1],n[e]]},e.copy=function(){return eo(n,t)},e}function ro(n){function t(n){return+n}return t.invert=t,t.domain=t.range=function(e){return arguments.length?(n=e.map(t),t):n},t.ticks=function(t){return Xi(n,t)},t.tickFormat=function(t,e){return $i(n,t,e)},t.copy=function(){return ro(n)},t}function uo(){return 0}function io(n){return n.innerRadius}function oo(n){return n.outerRadius}function ao(n){return n.startAngle}function co(n){return n.endAngle}function lo(n){return n&&n.padAngle}function so(n,t,e,r){return(n-e)*t-(t-r)*n>0?0:1}function fo(n,t,e,r,u){var i=n[0]-t[0],o=n[1]-t[1],a=(u?r:-r)/Math.sqrt(i*i+o*o),c=a*o,l=-a*i,s=n[0]+c,f=n[1]+l,h=t[0]+c,g=t[1]+l,p=(s+h)/2,v=(f+g)/2,d=h-s,m=g-f,y=d*d+m*m,M=e-r,x=s*g-h*f,b=(0>m?-1:1)*Math.sqrt(M*M*y-x*x),_=(x*m-d*b)/y,w=(-x*d-m*b)/y,S=(x*m+d*b)/y,k=(-x*d+m*b)/y,E=_-p,A=w-v,N=S-p,C=k-v;return E*E+A*A>N*N+C*C&&(_=S,w=k),[[_-c,w-l],[_*e/M,w*e/M]]}function ho(n){function t(t){function o(){l.push("M",i(n(s),a))}for(var c,l=[],s=[],f=-1,h=t.length,g=Et(e),p=Et(r);++f<h;)u.call(this,c=t[f],f)?s.push([+g.call(this,c,f),+p.call(this,c,f)]):s.length&&(o(),s=[]);return s.length&&o(),l.length?l.join(""):null}var e=Ar,r=Nr,u=Ne,i=go,o=i.key,a=.7;return t.x=function(n){return arguments.length?(e=n,t):e},t.y=function(n){return arguments.length?(r=n,t):r},t.defined=function(n){return arguments.length?(u=n,t):u},t.interpolate=function(n){return arguments.length?(o="function"==typeof n?i=n:(i=El.get(n)||go).key,t):o},t.tension=function(n){return arguments.length?(a=n,t):a},t}function go(n){return n.join("L")}function po(n){return go(n)+"Z"}function vo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("H",(r[0]+(r=n[t])[0])/2,"V",r[1]);return e>1&&u.push("H",r[0]),u.join("")}function mo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("V",(r=n[t])[1],"H",r[0]);return u.join("")}function yo(n){for(var t=0,e=n.length,r=n[0],u=[r[0],",",r[1]];++t<e;)u.push("H",(r=n[t])[0],"V",r[1]);return u.join("")}function Mo(n,t){return n.length<4?go(n):n[1]+_o(n.slice(1,-1),wo(n,t))}function xo(n,t){return n.length<3?go(n):n[0]+_o((n.push(n[0]),n),wo([n[n.length-2]].concat(n,[n[1]]),t))}function bo(n,t){return n.length<3?go(n):n[0]+_o(n,wo(n,t))}function _o(n,t){if(t.length<1||n.length!=t.length&&n.length!=t.length+2)return go(n);var e=n.length!=t.length,r="",u=n[0],i=n[1],o=t[0],a=o,c=1;if(e&&(r+="Q"+(i[0]-2*o[0]/3)+","+(i[1]-2*o[1]/3)+","+i[0]+","+i[1],u=n[1],c=2),t.length>1){a=t[1],i=n[c],c++,r+="C"+(u[0]+o[0])+","+(u[1]+o[1])+","+(i[0]-a[0])+","+(i[1]-a[1])+","+i[0]+","+i[1];for(var l=2;l<t.length;l++,c++)i=n[c],a=t[l],r+="S"+(i[0]-a[0])+","+(i[1]-a[1])+","+i[0]+","+i[1]}if(e){var s=n[c];r+="Q"+(i[0]+2*a[0]/3)+","+(i[1]+2*a[1]/3)+","+s[0]+","+s[1]}return r}function wo(n,t){for(var e,r=[],u=(1-t)/2,i=n[0],o=n[1],a=1,c=n.length;++a<c;)e=i,i=o,o=n[a],r.push([u*(o[0]-e[0]),u*(o[1]-e[1])]);return r}function So(n){if(n.length<3)return go(n);var t=1,e=n.length,r=n[0],u=r[0],i=r[1],o=[u,u,u,(r=n[1])[0]],a=[i,i,i,r[1]],c=[u,",",i,"L",No(Cl,o),",",No(Cl,a)];for(n.push(n[e-1]);++t<=e;)r=n[t],o.shift(),o.push(r[0]),a.shift(),a.push(r[1]),Co(c,o,a);return n.pop(),c.push("L",r),c.join("")}function ko(n){if(n.length<4)return go(n);for(var t,e=[],r=-1,u=n.length,i=[0],o=[0];++r<3;)t=n[r],i.push(t[0]),o.push(t[1]);for(e.push(No(Cl,i)+","+No(Cl,o)),--r;++r<u;)t=n[r],i.shift(),i.push(t[0]),o.shift(),o.push(t[1]),Co(e,i,o);return e.join("")}function Eo(n){for(var t,e,r=-1,u=n.length,i=u+4,o=[],a=[];++r<4;)e=n[r%u],o.push(e[0]),a.push(e[1]);for(t=[No(Cl,o),",",No(Cl,a)],--r;++r<i;)e=n[r%u],o.shift(),o.push(e[0]),a.shift(),a.push(e[1]),Co(t,o,a);return t.join("")}function Ao(n,t){var e=n.length-1;if(e)for(var r,u,i=n[0][0],o=n[0][1],a=n[e][0]-i,c=n[e][1]-o,l=-1;++l<=e;)r=n[l],u=l/e,r[0]=t*r[0]+(1-t)*(i+u*a),r[1]=t*r[1]+(1-t)*(o+u*c);return So(n)}function No(n,t){return n[0]*t[0]+n[1]*t[1]+n[2]*t[2]+n[3]*t[3]}function Co(n,t,e){n.push("C",No(Al,t),",",No(Al,e),",",No(Nl,t),",",No(Nl,e),",",No(Cl,t),",",No(Cl,e))}function zo(n,t){return(t[1]-n[1])/(t[0]-n[0])}function qo(n){for(var t=0,e=n.length-1,r=[],u=n[0],i=n[1],o=r[0]=zo(u,i);++t<e;)r[t]=(o+(o=zo(u=i,i=n[t+1])))/2;return r[t]=o,r}function Lo(n){for(var t,e,r,u,i=[],o=qo(n),a=-1,c=n.length-1;++a<c;)t=zo(n[a],n[a+1]),ga(t)<Ca?o[a]=o[a+1]=0:(e=o[a]/t,r=o[a+1]/t,u=e*e+r*r,u>9&&(u=3*t/Math.sqrt(u),o[a]=u*e,o[a+1]=u*r));for(a=-1;++a<=c;)u=(n[Math.min(c,a+1)][0]-n[Math.max(0,a-1)][0])/(6*(1+o[a]*o[a])),i.push([u||0,o[a]*u||0]);return i}function To(n){return n.length<3?go(n):n[0]+_o(n,Lo(n))}function Ro(n){for(var t,e,r,u=-1,i=n.length;++u<i;)t=n[u],e=t[0],r=t[1]-Ra,t[0]=e*Math.cos(r),t[1]=e*Math.sin(r);return n}function Do(n){function t(t){function c(){v.push("M",a(n(m),f),s,l(n(d.reverse()),f),"Z")}for(var h,g,p,v=[],d=[],m=[],y=-1,M=t.length,x=Et(e),b=Et(u),_=e===r?function(){return g}:Et(r),w=u===i?function(){return p}:Et(i);++y<M;)o.call(this,h=t[y],y)?(d.push([g=+x.call(this,h,y),p=+b.call(this,h,y)]),m.push([+_.call(this,h,y),+w.call(this,h,y)])):d.length&&(c(),d=[],m=[]);return d.length&&c(),v.length?v.join(""):null}var e=Ar,r=Ar,u=0,i=Nr,o=Ne,a=go,c=a.key,l=a,s="L",f=.7;return t.x=function(n){return arguments.length?(e=r=n,t):r},t.x0=function(n){return arguments.length?(e=n,t):e},t.x1=function(n){return arguments.length?(r=n,t):r
+},t.y=function(n){return arguments.length?(u=i=n,t):i},t.y0=function(n){return arguments.length?(u=n,t):u},t.y1=function(n){return arguments.length?(i=n,t):i},t.defined=function(n){return arguments.length?(o=n,t):o},t.interpolate=function(n){return arguments.length?(c="function"==typeof n?a=n:(a=El.get(n)||go).key,l=a.reverse||a,s=a.closed?"M":"L",t):c},t.tension=function(n){return arguments.length?(f=n,t):f},t}function Po(n){return n.radius}function Uo(n){return[n.x,n.y]}function jo(n){return function(){var t=n.apply(this,arguments),e=t[0],r=t[1]-Ra;return[e*Math.cos(r),e*Math.sin(r)]}}function Fo(){return 64}function Ho(){return"circle"}function Oo(n){var t=Math.sqrt(n/qa);return"M0,"+t+"A"+t+","+t+" 0 1,1 0,"+-t+"A"+t+","+t+" 0 1,1 0,"+t+"Z"}function Io(n){return function(){var t,e;(t=this[n])&&(e=t[t.active])&&(--t.count?delete t[t.active]:delete this[n],t.active+=.5,e.event&&e.event.interrupt.call(this,this.__data__,e.index))}}function Yo(n,t,e){return ya(n,Pl),n.namespace=t,n.id=e,n}function Zo(n,t,e,r){var u=n.id,i=n.namespace;return Y(n,"function"==typeof e?function(n,o,a){n[i][u].tween.set(t,r(e.call(n,n.__data__,o,a)))}:(e=r(e),function(n){n[i][u].tween.set(t,e)}))}function Vo(n){return null==n&&(n=""),function(){this.textContent=n}}function Xo(n){return null==n?"__transition__":"__transition_"+n+"__"}function $o(n,t,e,r,u){var i=n[e]||(n[e]={active:0,count:0}),o=i[r];if(!o){var a=u.time;o=i[r]={tween:new l,time:a,delay:u.delay,duration:u.duration,ease:u.ease,index:t},u=null,++i.count,ta.timer(function(u){function c(e){if(i.active>r)return s();var u=i[i.active];u&&(--i.count,delete i[i.active],u.event&&u.event.interrupt.call(n,n.__data__,u.index)),i.active=r,o.event&&o.event.start.call(n,n.__data__,t),o.tween.forEach(function(e,r){(r=r.call(n,n.__data__,t))&&v.push(r)}),h=o.ease,f=o.duration,ta.timer(function(){return p.c=l(e||1)?Ne:l,1},0,a)}function l(e){if(i.active!==r)return 1;for(var u=e/f,a=h(u),c=v.length;c>0;)v[--c].call(n,a);return u>=1?(o.event&&o.event.end.call(n,n.__data__,t),s()):void 0}function s(){return--i.count?delete i[r]:delete n[e],1}var f,h,g=o.delay,p=ec,v=[];return p.t=g+a,u>=g?c(u-g):void(p.c=c)},0,a)}}function Bo(n,t,e){n.attr("transform",function(n){var r=t(n);return"translate("+(isFinite(r)?r:e(n))+",0)"})}function Wo(n,t,e){n.attr("transform",function(n){var r=t(n);return"translate(0,"+(isFinite(r)?r:e(n))+")"})}function Jo(n){return n.toISOString()}function Go(n,t,e){function r(t){return n(t)}function u(n,e){var r=n[1]-n[0],u=r/e,i=ta.bisect(Vl,u);return i==Vl.length?[t.year,Vi(n.map(function(n){return n/31536e6}),e)[2]]:i?t[u/Vl[i-1]<Vl[i]/u?i-1:i]:[Bl,Vi(n,e)[2]]}return r.invert=function(t){return Ko(n.invert(t))},r.domain=function(t){return arguments.length?(n.domain(t),r):n.domain().map(Ko)},r.nice=function(n,t){function e(e){return!isNaN(e)&&!n.range(e,Ko(+e+1),t).length}var i=r.domain(),o=Pi(i),a=null==n?u(o,10):"number"==typeof n&&u(o,n);return a&&(n=a[0],t=a[1]),r.domain(Fi(i,t>1?{floor:function(t){for(;e(t=n.floor(t));)t=Ko(t-1);return t},ceil:function(t){for(;e(t=n.ceil(t));)t=Ko(+t+1);return t}}:n))},r.ticks=function(n,t){var e=Pi(r.domain()),i=null==n?u(e,10):"number"==typeof n?u(e,n):!n.range&&[{range:n},t];return i&&(n=i[0],t=i[1]),n.range(e[0],Ko(+e[1]+1),1>t?1:t)},r.tickFormat=function(){return e},r.copy=function(){return Go(n.copy(),t,e)},Yi(r,n)}function Ko(n){return new Date(n)}function Qo(n){return JSON.parse(n.responseText)}function na(n){var t=ua.createRange();return t.selectNode(ua.body),t.createContextualFragment(n.responseText)}var ta={version:"3.5.6"},ea=[].slice,ra=function(n){return ea.call(n)},ua=this.document;if(ua)try{ra(ua.documentElement.childNodes)[0].nodeType}catch(ia){ra=function(n){for(var t=n.length,e=new Array(t);t--;)e[t]=n[t];return e}}if(Date.now||(Date.now=function(){return+new Date}),ua)try{ua.createElement("DIV").style.setProperty("opacity",0,"")}catch(oa){var aa=this.Element.prototype,ca=aa.setAttribute,la=aa.setAttributeNS,sa=this.CSSStyleDeclaration.prototype,fa=sa.setProperty;aa.setAttribute=function(n,t){ca.call(this,n,t+"")},aa.setAttributeNS=function(n,t,e){la.call(this,n,t,e+"")},sa.setProperty=function(n,t,e){fa.call(this,n,t+"",e)}}ta.ascending=e,ta.descending=function(n,t){return n>t?-1:t>n?1:t>=n?0:0/0},ta.min=function(n,t){var e,r,u=-1,i=n.length;if(1===arguments.length){for(;++u<i;)if(null!=(r=n[u])&&r>=r){e=r;break}for(;++u<i;)null!=(r=n[u])&&e>r&&(e=r)}else{for(;++u<i;)if(null!=(r=t.call(n,n[u],u))&&r>=r){e=r;break}for(;++u<i;)null!=(r=t.call(n,n[u],u))&&e>r&&(e=r)}return e},ta.max=function(n,t){var e,r,u=-1,i=n.length;if(1===arguments.length){for(;++u<i;)if(null!=(r=n[u])&&r>=r){e=r;break}for(;++u<i;)null!=(r=n[u])&&r>e&&(e=r)}else{for(;++u<i;)if(null!=(r=t.call(n,n[u],u))&&r>=r){e=r;break}for(;++u<i;)null!=(r=t.call(n,n[u],u))&&r>e&&(e=r)}return e},ta.extent=function(n,t){var e,r,u,i=-1,o=n.length;if(1===arguments.length){for(;++i<o;)if(null!=(r=n[i])&&r>=r){e=u=r;break}for(;++i<o;)null!=(r=n[i])&&(e>r&&(e=r),r>u&&(u=r))}else{for(;++i<o;)if(null!=(r=t.call(n,n[i],i))&&r>=r){e=u=r;break}for(;++i<o;)null!=(r=t.call(n,n[i],i))&&(e>r&&(e=r),r>u&&(u=r))}return[e,u]},ta.sum=function(n,t){var e,r=0,i=n.length,o=-1;if(1===arguments.length)for(;++o<i;)u(e=+n[o])&&(r+=e);else for(;++o<i;)u(e=+t.call(n,n[o],o))&&(r+=e);return r},ta.mean=function(n,t){var e,i=0,o=n.length,a=-1,c=o;if(1===arguments.length)for(;++a<o;)u(e=r(n[a]))?i+=e:--c;else for(;++a<o;)u(e=r(t.call(n,n[a],a)))?i+=e:--c;return c?i/c:void 0},ta.quantile=function(n,t){var e=(n.length-1)*t+1,r=Math.floor(e),u=+n[r-1],i=e-r;return i?u+i*(n[r]-u):u},ta.median=function(n,t){var i,o=[],a=n.length,c=-1;if(1===arguments.length)for(;++c<a;)u(i=r(n[c]))&&o.push(i);else for(;++c<a;)u(i=r(t.call(n,n[c],c)))&&o.push(i);return o.length?ta.quantile(o.sort(e),.5):void 0},ta.variance=function(n,t){var e,i,o=n.length,a=0,c=0,l=-1,s=0;if(1===arguments.length)for(;++l<o;)u(e=r(n[l]))&&(i=e-a,a+=i/++s,c+=i*(e-a));else for(;++l<o;)u(e=r(t.call(n,n[l],l)))&&(i=e-a,a+=i/++s,c+=i*(e-a));return s>1?c/(s-1):void 0},ta.deviation=function(){var n=ta.variance.apply(this,arguments);return n?Math.sqrt(n):n};var ha=i(e);ta.bisectLeft=ha.left,ta.bisect=ta.bisectRight=ha.right,ta.bisector=function(n){return i(1===n.length?function(t,r){return e(n(t),r)}:n)},ta.shuffle=function(n,t,e){(i=arguments.length)<3&&(e=n.length,2>i&&(t=0));for(var r,u,i=e-t;i;)u=Math.random()*i--|0,r=n[i+t],n[i+t]=n[u+t],n[u+t]=r;return n},ta.permute=function(n,t){for(var e=t.length,r=new Array(e);e--;)r[e]=n[t[e]];return r},ta.pairs=function(n){for(var t,e=0,r=n.length-1,u=n[0],i=new Array(0>r?0:r);r>e;)i[e]=[t=u,u=n[++e]];return i},ta.zip=function(){if(!(r=arguments.length))return[];for(var n=-1,t=ta.min(arguments,o),e=new Array(t);++n<t;)for(var r,u=-1,i=e[n]=new Array(r);++u<r;)i[u]=arguments[u][n];return e},ta.transpose=function(n){return ta.zip.apply(ta,n)},ta.keys=function(n){var t=[];for(var e in n)t.push(e);return t},ta.values=function(n){var t=[];for(var e in n)t.push(n[e]);return t},ta.entries=function(n){var t=[];for(var e in n)t.push({key:e,value:n[e]});return t},ta.merge=function(n){for(var t,e,r,u=n.length,i=-1,o=0;++i<u;)o+=n[i].length;for(e=new Array(o);--u>=0;)for(r=n[u],t=r.length;--t>=0;)e[--o]=r[t];return e};var ga=Math.abs;ta.range=function(n,t,e){if(arguments.length<3&&(e=1,arguments.length<2&&(t=n,n=0)),(t-n)/e===1/0)throw new Error("infinite range");var r,u=[],i=a(ga(e)),o=-1;if(n*=i,t*=i,e*=i,0>e)for(;(r=n+e*++o)>t;)u.push(r/i);else for(;(r=n+e*++o)<t;)u.push(r/i);return u},ta.map=function(n,t){var e=new l;if(n instanceof l)n.forEach(function(n,t){e.set(n,t)});else if(Array.isArray(n)){var r,u=-1,i=n.length;if(1===arguments.length)for(;++u<i;)e.set(u,n[u]);else for(;++u<i;)e.set(t.call(n,r=n[u],u),r)}else for(var o in n)e.set(o,n[o]);return e};var pa="__proto__",va="\x00";c(l,{has:h,get:function(n){return this._[s(n)]},set:function(n,t){return this._[s(n)]=t},remove:g,keys:p,values:function(){var n=[];for(var t in this._)n.push(this._[t]);return n},entries:function(){var n=[];for(var t in this._)n.push({key:f(t),value:this._[t]});return n},size:v,empty:d,forEach:function(n){for(var t in this._)n.call(this,f(t),this._[t])}}),ta.nest=function(){function n(t,o,a){if(a>=i.length)return r?r.call(u,o):e?o.sort(e):o;for(var c,s,f,h,g=-1,p=o.length,v=i[a++],d=new l;++g<p;)(h=d.get(c=v(s=o[g])))?h.push(s):d.set(c,[s]);return t?(s=t(),f=function(e,r){s.set(e,n(t,r,a))}):(s={},f=function(e,r){s[e]=n(t,r,a)}),d.forEach(f),s}function t(n,e){if(e>=i.length)return n;var r=[],u=o[e++];return n.forEach(function(n,u){r.push({key:n,values:t(u,e)})}),u?r.sort(function(n,t){return u(n.key,t.key)}):r}var e,r,u={},i=[],o=[];return u.map=function(t,e){return n(e,t,0)},u.entries=function(e){return t(n(ta.map,e,0),0)},u.key=function(n){return i.push(n),u},u.sortKeys=function(n){return o[i.length-1]=n,u},u.sortValues=function(n){return e=n,u},u.rollup=function(n){return r=n,u},u},ta.set=function(n){var t=new m;if(n)for(var e=0,r=n.length;r>e;++e)t.add(n[e]);return t},c(m,{has:h,add:function(n){return this._[s(n+="")]=!0,n},remove:g,values:p,size:v,empty:d,forEach:function(n){for(var t in this._)n.call(this,f(t))}}),ta.behavior={},ta.rebind=function(n,t){for(var e,r=1,u=arguments.length;++r<u;)n[e=arguments[r]]=M(n,t,t[e]);return n};var da=["webkit","ms","moz","Moz","o","O"];ta.dispatch=function(){for(var n=new _,t=-1,e=arguments.length;++t<e;)n[arguments[t]]=w(n);return n},_.prototype.on=function(n,t){var e=n.indexOf("."),r="";if(e>=0&&(r=n.slice(e+1),n=n.slice(0,e)),n)return arguments.length<2?this[n].on(r):this[n].on(r,t);if(2===arguments.length){if(null==t)for(n in this)this.hasOwnProperty(n)&&this[n].on(r,null);return this}},ta.event=null,ta.requote=function(n){return n.replace(ma,"\\$&")};var ma=/[\\\^\$\*\+\?\|\[\]\(\)\.\{\}]/g,ya={}.__proto__?function(n,t){n.__proto__=t}:function(n,t){for(var e in t)n[e]=t[e]},Ma=function(n,t){return t.querySelector(n)},xa=function(n,t){return t.querySelectorAll(n)},ba=function(n,t){var e=n.matches||n[x(n,"matchesSelector")];return(ba=function(n,t){return e.call(n,t)})(n,t)};"function"==typeof Sizzle&&(Ma=function(n,t){return Sizzle(n,t)[0]||null},xa=Sizzle,ba=Sizzle.matchesSelector),ta.selection=function(){return ta.select(ua.documentElement)};var _a=ta.selection.prototype=[];_a.select=function(n){var t,e,r,u,i=[];n=N(n);for(var o=-1,a=this.length;++o<a;){i.push(t=[]),t.parentNode=(r=this[o]).parentNode;for(var c=-1,l=r.length;++c<l;)(u=r[c])?(t.push(e=n.call(u,u.__data__,c,o)),e&&"__data__"in u&&(e.__data__=u.__data__)):t.push(null)}return A(i)},_a.selectAll=function(n){var t,e,r=[];n=C(n);for(var u=-1,i=this.length;++u<i;)for(var o=this[u],a=-1,c=o.length;++a<c;)(e=o[a])&&(r.push(t=ra(n.call(e,e.__data__,a,u))),t.parentNode=e);return A(r)};var wa={svg:"http://www.w3.org/2000/svg",xhtml:"http://www.w3.org/1999/xhtml",xlink:"http://www.w3.org/1999/xlink",xml:"http://www.w3.org/XML/1998/namespace",xmlns:"http://www.w3.org/2000/xmlns/"};ta.ns={prefix:wa,qualify:function(n){var t=n.indexOf(":"),e=n;return t>=0&&(e=n.slice(0,t),n=n.slice(t+1)),wa.hasOwnProperty(e)?{space:wa[e],local:n}:n}},_a.attr=function(n,t){if(arguments.length<2){if("string"==typeof n){var e=this.node();return n=ta.ns.qualify(n),n.local?e.getAttributeNS(n.space,n.local):e.getAttribute(n)}for(t in n)this.each(z(t,n[t]));return this}return this.each(z(n,t))},_a.classed=function(n,t){if(arguments.length<2){if("string"==typeof n){var e=this.node(),r=(n=T(n)).length,u=-1;if(t=e.classList){for(;++u<r;)if(!t.contains(n[u]))return!1}else for(t=e.getAttribute("class");++u<r;)if(!L(n[u]).test(t))return!1;return!0}for(t in n)this.each(R(t,n[t]));return this}return this.each(R(n,t))},_a.style=function(n,e,r){var u=arguments.length;if(3>u){if("string"!=typeof n){2>u&&(e="");for(r in n)this.each(P(r,n[r],e));return this}if(2>u){var i=this.node();return t(i).getComputedStyle(i,null).getPropertyValue(n)}r=""}return this.each(P(n,e,r))},_a.property=function(n,t){if(arguments.length<2){if("string"==typeof n)return this.node()[n];for(t in n)this.each(U(t,n[t]));return this}return this.each(U(n,t))},_a.text=function(n){return arguments.length?this.each("function"==typeof n?function(){var t=n.apply(this,arguments);this.textContent=null==t?"":t}:null==n?function(){this.textContent=""}:function(){this.textContent=n}):this.node().textContent},_a.html=function(n){return arguments.length?this.each("function"==typeof n?function(){var t=n.apply(this,arguments);this.innerHTML=null==t?"":t}:null==n?function(){this.innerHTML=""}:function(){this.innerHTML=n}):this.node().innerHTML},_a.append=function(n){return n=j(n),this.select(function(){return this.appendChild(n.apply(this,arguments))})},_a.insert=function(n,t){return n=j(n),t=N(t),this.select(function(){return this.insertBefore(n.apply(this,arguments),t.apply(this,arguments)||null)})},_a.remove=function(){return this.each(F)},_a.data=function(n,t){function e(n,e){var r,u,i,o=n.length,f=e.length,h=Math.min(o,f),g=new Array(f),p=new Array(f),v=new Array(o);if(t){var d,m=new l,y=new Array(o);for(r=-1;++r<o;)m.has(d=t.call(u=n[r],u.__data__,r))?v[r]=u:m.set(d,u),y[r]=d;for(r=-1;++r<f;)(u=m.get(d=t.call(e,i=e[r],r)))?u!==!0&&(g[r]=u,u.__data__=i):p[r]=H(i),m.set(d,!0);for(r=-1;++r<o;)m.get(y[r])!==!0&&(v[r]=n[r])}else{for(r=-1;++r<h;)u=n[r],i=e[r],u?(u.__data__=i,g[r]=u):p[r]=H(i);for(;f>r;++r)p[r]=H(e[r]);for(;o>r;++r)v[r]=n[r]}p.update=g,p.parentNode=g.parentNode=v.parentNode=n.parentNode,a.push(p),c.push(g),s.push(v)}var r,u,i=-1,o=this.length;if(!arguments.length){for(n=new Array(o=(r=this[0]).length);++i<o;)(u=r[i])&&(n[i]=u.__data__);return n}var a=Z([]),c=A([]),s=A([]);if("function"==typeof n)for(;++i<o;)e(r=this[i],n.call(r,r.parentNode.__data__,i));else for(;++i<o;)e(r=this[i],n);return c.enter=function(){return a},c.exit=function(){return s},c},_a.datum=function(n){return arguments.length?this.property("__data__",n):this.property("__data__")},_a.filter=function(n){var t,e,r,u=[];"function"!=typeof n&&(n=O(n));for(var i=0,o=this.length;o>i;i++){u.push(t=[]),t.parentNode=(e=this[i]).parentNode;for(var a=0,c=e.length;c>a;a++)(r=e[a])&&n.call(r,r.__data__,a,i)&&t.push(r)}return A(u)},_a.order=function(){for(var n=-1,t=this.length;++n<t;)for(var e,r=this[n],u=r.length-1,i=r[u];--u>=0;)(e=r[u])&&(i&&i!==e.nextSibling&&i.parentNode.insertBefore(e,i),i=e);return this},_a.sort=function(n){n=I.apply(this,arguments);for(var t=-1,e=this.length;++t<e;)this[t].sort(n);return this.order()},_a.each=function(n){return Y(this,function(t,e,r){n.call(t,t.__data__,e,r)})},_a.call=function(n){var t=ra(arguments);return n.apply(t[0]=this,t),this},_a.empty=function(){return!this.node()},_a.node=function(){for(var n=0,t=this.length;t>n;n++)for(var e=this[n],r=0,u=e.length;u>r;r++){var i=e[r];if(i)return i}return null},_a.size=function(){var n=0;return Y(this,function(){++n}),n};var Sa=[];ta.selection.enter=Z,ta.selection.enter.prototype=Sa,Sa.append=_a.append,Sa.empty=_a.empty,Sa.node=_a.node,Sa.call=_a.call,Sa.size=_a.size,Sa.select=function(n){for(var t,e,r,u,i,o=[],a=-1,c=this.length;++a<c;){r=(u=this[a]).update,o.push(t=[]),t.parentNode=u.parentNode;for(var l=-1,s=u.length;++l<s;)(i=u[l])?(t.push(r[l]=e=n.call(u.parentNode,i.__data__,l,a)),e.__data__=i.__data__):t.push(null)}return A(o)},Sa.insert=function(n,t){return arguments.length<2&&(t=V(this)),_a.insert.call(this,n,t)},ta.select=function(t){var e;return"string"==typeof t?(e=[Ma(t,ua)],e.parentNode=ua.documentElement):(e=[t],e.parentNode=n(t)),A([e])},ta.selectAll=function(n){var t;return"string"==typeof n?(t=ra(xa(n,ua)),t.parentNode=ua.documentElement):(t=n,t.parentNode=null),A([t])},_a.on=function(n,t,e){var r=arguments.length;if(3>r){if("string"!=typeof n){2>r&&(t=!1);for(e in n)this.each(X(e,n[e],t));return this}if(2>r)return(r=this.node()["__on"+n])&&r._;e=!1}return this.each(X(n,t,e))};var ka=ta.map({mouseenter:"mouseover",mouseleave:"mouseout"});ua&&ka.forEach(function(n){"on"+n in ua&&ka.remove(n)});var Ea,Aa=0;ta.mouse=function(n){return J(n,k())};var Na=this.navigator&&/WebKit/.test(this.navigator.userAgent)?-1:0;ta.touch=function(n,t,e){if(arguments.length<3&&(e=t,t=k().changedTouches),t)for(var r,u=0,i=t.length;i>u;++u)if((r=t[u]).identifier===e)return J(n,r)},ta.behavior.drag=function(){function n(){this.on("mousedown.drag",i).on("touchstart.drag",o)}function e(n,t,e,i,o){return function(){function a(){var n,e,r=t(h,v);r&&(n=r[0]-M[0],e=r[1]-M[1],p|=n|e,M=r,g({type:"drag",x:r[0]+l[0],y:r[1]+l[1],dx:n,dy:e}))}function c(){t(h,v)&&(m.on(i+d,null).on(o+d,null),y(p&&ta.event.target===f),g({type:"dragend"}))}var l,s=this,f=ta.event.target,h=s.parentNode,g=r.of(s,arguments),p=0,v=n(),d=".drag"+(null==v?"":"-"+v),m=ta.select(e(f)).on(i+d,a).on(o+d,c),y=W(f),M=t(h,v);u?(l=u.apply(s,arguments),l=[l.x-M[0],l.y-M[1]]):l=[0,0],g({type:"dragstart"})}}var r=E(n,"drag","dragstart","dragend"),u=null,i=e(b,ta.mouse,t,"mousemove","mouseup"),o=e(G,ta.touch,y,"touchmove","touchend");return n.origin=function(t){return arguments.length?(u=t,n):u},ta.rebind(n,r,"on")},ta.touches=function(n,t){return arguments.length<2&&(t=k().touches),t?ra(t).map(function(t){var e=J(n,t);return e.identifier=t.identifier,e}):[]};var Ca=1e-6,za=Ca*Ca,qa=Math.PI,La=2*qa,Ta=La-Ca,Ra=qa/2,Da=qa/180,Pa=180/qa,Ua=Math.SQRT2,ja=2,Fa=4;ta.interpolateZoom=function(n,t){function e(n){var t=n*y;if(m){var e=rt(v),o=i/(ja*h)*(e*ut(Ua*t+v)-et(v));return[r+o*l,u+o*s,i*e/rt(Ua*t+v)]}return[r+n*l,u+n*s,i*Math.exp(Ua*t)]}var r=n[0],u=n[1],i=n[2],o=t[0],a=t[1],c=t[2],l=o-r,s=a-u,f=l*l+s*s,h=Math.sqrt(f),g=(c*c-i*i+Fa*f)/(2*i*ja*h),p=(c*c-i*i-Fa*f)/(2*c*ja*h),v=Math.log(Math.sqrt(g*g+1)-g),d=Math.log(Math.sqrt(p*p+1)-p),m=d-v,y=(m||Math.log(c/i))/Ua;return e.duration=1e3*y,e},ta.behavior.zoom=function(){function n(n){n.on(q,f).on(Oa+".zoom",g).on("dblclick.zoom",p).on(R,h)}function e(n){return[(n[0]-k.x)/k.k,(n[1]-k.y)/k.k]}function r(n){return[n[0]*k.k+k.x,n[1]*k.k+k.y]}function u(n){k.k=Math.max(N[0],Math.min(N[1],n))}function i(n,t){t=r(t),k.x+=n[0]-t[0],k.y+=n[1]-t[1]}function o(t,e,r,o){t.__chart__={x:k.x,y:k.y,k:k.k},u(Math.pow(2,o)),i(d=e,r),t=ta.select(t),C>0&&(t=t.transition().duration(C)),t.call(n.event)}function a(){b&&b.domain(x.range().map(function(n){return(n-k.x)/k.k}).map(x.invert)),w&&w.domain(_.range().map(function(n){return(n-k.y)/k.k}).map(_.invert))}function c(n){z++||n({type:"zoomstart"})}function l(n){a(),n({type:"zoom",scale:k.k,translate:[k.x,k.y]})}function s(n){--z||(n({type:"zoomend"}),d=null)}function f(){function n(){f=1,i(ta.mouse(u),g),l(a)}function r(){h.on(L,null).on(T,null),p(f&&ta.event.target===o),s(a)}var u=this,o=ta.event.target,a=D.of(u,arguments),f=0,h=ta.select(t(u)).on(L,n).on(T,r),g=e(ta.mouse(u)),p=W(u);Dl.call(u),c(a)}function h(){function n(){var n=ta.touches(p);return g=k.k,n.forEach(function(n){n.identifier in d&&(d[n.identifier]=e(n))}),n}function t(){var t=ta.event.target;ta.select(t).on(x,r).on(b,a),_.push(t);for(var e=ta.event.changedTouches,u=0,i=e.length;i>u;++u)d[e[u].identifier]=null;var c=n(),l=Date.now();if(1===c.length){if(500>l-M){var s=c[0];o(p,s,d[s.identifier],Math.floor(Math.log(k.k)/Math.LN2)+1),S()}M=l}else if(c.length>1){var s=c[0],f=c[1],h=s[0]-f[0],g=s[1]-f[1];m=h*h+g*g}}function r(){var n,t,e,r,o=ta.touches(p);Dl.call(p);for(var a=0,c=o.length;c>a;++a,r=null)if(e=o[a],r=d[e.identifier]){if(t)break;n=e,t=r}if(r){var s=(s=e[0]-n[0])*s+(s=e[1]-n[1])*s,f=m&&Math.sqrt(s/m);n=[(n[0]+e[0])/2,(n[1]+e[1])/2],t=[(t[0]+r[0])/2,(t[1]+r[1])/2],u(f*g)}M=null,i(n,t),l(v)}function a(){if(ta.event.touches.length){for(var t=ta.event.changedTouches,e=0,r=t.length;r>e;++e)delete d[t[e].identifier];for(var u in d)return void n()}ta.selectAll(_).on(y,null),w.on(q,f).on(R,h),E(),s(v)}var g,p=this,v=D.of(p,arguments),d={},m=0,y=".zoom-"+ta.event.changedTouches[0].identifier,x="touchmove"+y,b="touchend"+y,_=[],w=ta.select(p),E=W(p);t(),c(v),w.on(q,null).on(R,t)}function g(){var n=D.of(this,arguments);y?clearTimeout(y):(Dl.call(this),v=e(d=m||ta.mouse(this)),c(n)),y=setTimeout(function(){y=null,s(n)},50),S(),u(Math.pow(2,.002*Ha())*k.k),i(d,v),l(n)}function p(){var n=ta.mouse(this),t=Math.log(k.k)/Math.LN2;o(this,n,e(n),ta.event.shiftKey?Math.ceil(t)-1:Math.floor(t)+1)}var v,d,m,y,M,x,b,_,w,k={x:0,y:0,k:1},A=[960,500],N=Ia,C=250,z=0,q="mousedown.zoom",L="mousemove.zoom",T="mouseup.zoom",R="touchstart.zoom",D=E(n,"zoomstart","zoom","zoomend");return Oa||(Oa="onwheel"in ua?(Ha=function(){return-ta.event.deltaY*(ta.event.deltaMode?120:1)},"wheel"):"onmousewheel"in ua?(Ha=function(){return ta.event.wheelDelta},"mousewheel"):(Ha=function(){return-ta.event.detail},"MozMousePixelScroll")),n.event=function(n){n.each(function(){var n=D.of(this,arguments),t=k;Tl?ta.select(this).transition().each("start.zoom",function(){k=this.__chart__||{x:0,y:0,k:1},c(n)}).tween("zoom:zoom",function(){var e=A[0],r=A[1],u=d?d[0]:e/2,i=d?d[1]:r/2,o=ta.interpolateZoom([(u-k.x)/k.k,(i-k.y)/k.k,e/k.k],[(u-t.x)/t.k,(i-t.y)/t.k,e/t.k]);return function(t){var r=o(t),a=e/r[2];this.__chart__=k={x:u-r[0]*a,y:i-r[1]*a,k:a},l(n)}}).each("interrupt.zoom",function(){s(n)}).each("end.zoom",function(){s(n)}):(this.__chart__=k,c(n),l(n),s(n))})},n.translate=function(t){return arguments.length?(k={x:+t[0],y:+t[1],k:k.k},a(),n):[k.x,k.y]},n.scale=function(t){return arguments.length?(k={x:k.x,y:k.y,k:+t},a(),n):k.k},n.scaleExtent=function(t){return arguments.length?(N=null==t?Ia:[+t[0],+t[1]],n):N},n.center=function(t){return arguments.length?(m=t&&[+t[0],+t[1]],n):m},n.size=function(t){return arguments.length?(A=t&&[+t[0],+t[1]],n):A},n.duration=function(t){return arguments.length?(C=+t,n):C},n.x=function(t){return arguments.length?(b=t,x=t.copy(),k={x:0,y:0,k:1},n):b},n.y=function(t){return arguments.length?(w=t,_=t.copy(),k={x:0,y:0,k:1},n):w},ta.rebind(n,D,"on")};var Ha,Oa,Ia=[0,1/0];ta.color=ot,ot.prototype.toString=function(){return this.rgb()+""},ta.hsl=at;var Ya=at.prototype=new ot;Ya.brighter=function(n){return n=Math.pow(.7,arguments.length?n:1),new at(this.h,this.s,this.l/n)},Ya.darker=function(n){return n=Math.pow(.7,arguments.length?n:1),new at(this.h,this.s,n*this.l)},Ya.rgb=function(){return ct(this.h,this.s,this.l)},ta.hcl=lt;var Za=lt.prototype=new ot;Za.brighter=function(n){return new lt(this.h,this.c,Math.min(100,this.l+Va*(arguments.length?n:1)))},Za.darker=function(n){return new lt(this.h,this.c,Math.max(0,this.l-Va*(arguments.length?n:1)))},Za.rgb=function(){return st(this.h,this.c,this.l).rgb()},ta.lab=ft;var Va=18,Xa=.95047,$a=1,Ba=1.08883,Wa=ft.prototype=new ot;Wa.brighter=function(n){return new ft(Math.min(100,this.l+Va*(arguments.length?n:1)),this.a,this.b)},Wa.darker=function(n){return new ft(Math.max(0,this.l-Va*(arguments.length?n:1)),this.a,this.b)},Wa.rgb=function(){return ht(this.l,this.a,this.b)},ta.rgb=mt;var Ja=mt.prototype=new ot;Ja.brighter=function(n){n=Math.pow(.7,arguments.length?n:1);var t=this.r,e=this.g,r=this.b,u=30;return t||e||r?(t&&u>t&&(t=u),e&&u>e&&(e=u),r&&u>r&&(r=u),new mt(Math.min(255,t/n),Math.min(255,e/n),Math.min(255,r/n))):new mt(u,u,u)},Ja.darker=function(n){return n=Math.pow(.7,arguments.length?n:1),new mt(n*this.r,n*this.g,n*this.b)},Ja.hsl=function(){return _t(this.r,this.g,this.b)},Ja.toString=function(){return"#"+xt(this.r)+xt(this.g)+xt(this.b)};var Ga=ta.map({aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074});Ga.forEach(function(n,t){Ga.set(n,yt(t))}),ta.functor=Et,ta.xhr=At(y),ta.dsv=function(n,t){function e(n,e,i){arguments.length<3&&(i=e,e=null);var o=Nt(n,t,null==e?r:u(e),i);return o.row=function(n){return arguments.length?o.response(null==(e=n)?r:u(n)):e},o}function r(n){return e.parse(n.responseText)}function u(n){return function(t){return e.parse(t.responseText,n)}}function i(t){return t.map(o).join(n)}function o(n){return a.test(n)?'"'+n.replace(/\"/g,'""')+'"':n}var a=new RegExp('["'+n+"\n]"),c=n.charCodeAt(0);return e.parse=function(n,t){var r;return e.parseRows(n,function(n,e){if(r)return r(n,e-1);var u=new Function("d","return {"+n.map(function(n,t){return JSON.stringify(n)+": d["+t+"]"}).join(",")+"}");r=t?function(n,e){return t(u(n),e)}:u})},e.parseRows=function(n,t){function e(){if(s>=l)return o;if(u)return u=!1,i;var t=s;if(34===n.charCodeAt(t)){for(var e=t;e++<l;)if(34===n.charCodeAt(e)){if(34!==n.charCodeAt(e+1))break;++e}s=e+2;var r=n.charCodeAt(e+1);return 13===r?(u=!0,10===n.charCodeAt(e+2)&&++s):10===r&&(u=!0),n.slice(t+1,e).replace(/""/g,'"')}for(;l>s;){var r=n.charCodeAt(s++),a=1;if(10===r)u=!0;else if(13===r)u=!0,10===n.charCodeAt(s)&&(++s,++a);else if(r!==c)continue;return n.slice(t,s-a)}return n.slice(t)}for(var r,u,i={},o={},a=[],l=n.length,s=0,f=0;(r=e())!==o;){for(var h=[];r!==i&&r!==o;)h.push(r),r=e();t&&null==(h=t(h,f++))||a.push(h)}return a},e.format=function(t){if(Array.isArray(t[0]))return e.formatRows(t);var r=new m,u=[];return t.forEach(function(n){for(var t in n)r.has(t)||u.push(r.add(t))}),[u.map(o).join(n)].concat(t.map(function(t){return u.map(function(n){return o(t[n])}).join(n)})).join("\n")},e.formatRows=function(n){return n.map(i).join("\n")},e},ta.csv=ta.dsv(",","text/csv"),ta.tsv=ta.dsv("	","text/tab-separated-values");var Ka,Qa,nc,tc,ec,rc=this[x(this,"requestAnimationFrame")]||function(n){setTimeout(n,17)};ta.timer=function(n,t,e){var r=arguments.length;2>r&&(t=0),3>r&&(e=Date.now());var u=e+t,i={c:n,t:u,f:!1,n:null};Qa?Qa.n=i:Ka=i,Qa=i,nc||(tc=clearTimeout(tc),nc=1,rc(qt))},ta.timer.flush=function(){Lt(),Tt()},ta.round=function(n,t){return t?Math.round(n*(t=Math.pow(10,t)))/t:Math.round(n)};var uc=["y","z","a","f","p","n","\xb5","m","","k","M","G","T","P","E","Z","Y"].map(Dt);ta.formatPrefix=function(n,t){var e=0;return n&&(0>n&&(n*=-1),t&&(n=ta.round(n,Rt(n,t))),e=1+Math.floor(1e-12+Math.log(n)/Math.LN10),e=Math.max(-24,Math.min(24,3*Math.floor((e-1)/3)))),uc[8+e/3]};var ic=/(?:([^{])?([<>=^]))?([+\- ])?([$#])?(0)?(\d+)?(,)?(\.-?\d+)?([a-z%])?/i,oc=ta.map({b:function(n){return n.toString(2)},c:function(n){return String.fromCharCode(n)},o:function(n){return n.toString(8)},x:function(n){return n.toString(16)},X:function(n){return n.toString(16).toUpperCase()},g:function(n,t){return n.toPrecision(t)},e:function(n,t){return n.toExponential(t)},f:function(n,t){return n.toFixed(t)},r:function(n,t){return(n=ta.round(n,Rt(n,t))).toFixed(Math.max(0,Math.min(20,Rt(n*(1+1e-15),t))))}}),ac=ta.time={},cc=Date;jt.prototype={getDate:function(){return this._.getUTCDate()},getDay:function(){return this._.getUTCDay()},getFullYear:function(){return this._.getUTCFullYear()},getHours:function(){return this._.getUTCHours()},getMilliseconds:function(){return this._.getUTCMilliseconds()},getMinutes:function(){return this._.getUTCMinutes()},getMonth:function(){return this._.getUTCMonth()},getSeconds:function(){return this._.getUTCSeconds()},getTime:function(){return this._.getTime()},getTimezoneOffset:function(){return 0},valueOf:function(){return this._.valueOf()},setDate:function(){lc.setUTCDate.apply(this._,arguments)},setDay:function(){lc.setUTCDay.apply(this._,arguments)},setFullYear:function(){lc.setUTCFullYear.apply(this._,arguments)},setHours:function(){lc.setUTCHours.apply(this._,arguments)},setMilliseconds:function(){lc.setUTCMilliseconds.apply(this._,arguments)},setMinutes:function(){lc.setUTCMinutes.apply(this._,arguments)},setMonth:function(){lc.setUTCMonth.apply(this._,arguments)},setSeconds:function(){lc.setUTCSeconds.apply(this._,arguments)},setTime:function(){lc.setTime.apply(this._,arguments)}};var lc=Date.prototype;ac.year=Ft(function(n){return n=ac.day(n),n.setMonth(0,1),n},function(n,t){n.setFullYear(n.getFullYear()+t)},function(n){return n.getFullYear()}),ac.years=ac.year.range,ac.years.utc=ac.year.utc.range,ac.day=Ft(function(n){var t=new cc(2e3,0);return t.setFullYear(n.getFullYear(),n.getMonth(),n.getDate()),t},function(n,t){n.setDate(n.getDate()+t)},function(n){return n.getDate()-1}),ac.days=ac.day.range,ac.days.utc=ac.day.utc.range,ac.dayOfYear=function(n){var t=ac.year(n);return Math.floor((n-t-6e4*(n.getTimezoneOffset()-t.getTimezoneOffset()))/864e5)},["sunday","monday","tuesday","wednesday","thursday","friday","saturday"].forEach(function(n,t){t=7-t;var e=ac[n]=Ft(function(n){return(n=ac.day(n)).setDate(n.getDate()-(n.getDay()+t)%7),n},function(n,t){n.setDate(n.getDate()+7*Math.floor(t))},function(n){var e=ac.year(n).getDay();return Math.floor((ac.dayOfYear(n)+(e+t)%7)/7)-(e!==t)});ac[n+"s"]=e.range,ac[n+"s"].utc=e.utc.range,ac[n+"OfYear"]=function(n){var e=ac.year(n).getDay();return Math.floor((ac.dayOfYear(n)+(e+t)%7)/7)}}),ac.week=ac.sunday,ac.weeks=ac.sunday.range,ac.weeks.utc=ac.sunday.utc.range,ac.weekOfYear=ac.sundayOfYear;var sc={"-":"",_:" ",0:"0"},fc=/^\s*\d+/,hc=/^%/;ta.locale=function(n){return{numberFormat:Pt(n),timeFormat:Ot(n)}};var gc=ta.locale({decimal:".",thousands:",",grouping:[3],currency:["$",""],dateTime:"%a %b %e %X %Y",date:"%m/%d/%Y",time:"%H:%M:%S",periods:["AM","PM"],days:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],shortDays:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],months:["January","February","March","April","May","June","July","August","September","October","November","December"],shortMonths:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]});ta.format=gc.numberFormat,ta.geo={},ce.prototype={s:0,t:0,add:function(n){le(n,this.t,pc),le(pc.s,this.s,this),this.s?this.t+=pc.t:this.s=pc.t
+},reset:function(){this.s=this.t=0},valueOf:function(){return this.s}};var pc=new ce;ta.geo.stream=function(n,t){n&&vc.hasOwnProperty(n.type)?vc[n.type](n,t):se(n,t)};var vc={Feature:function(n,t){se(n.geometry,t)},FeatureCollection:function(n,t){for(var e=n.features,r=-1,u=e.length;++r<u;)se(e[r].geometry,t)}},dc={Sphere:function(n,t){t.sphere()},Point:function(n,t){n=n.coordinates,t.point(n[0],n[1],n[2])},MultiPoint:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)n=e[r],t.point(n[0],n[1],n[2])},LineString:function(n,t){fe(n.coordinates,t,0)},MultiLineString:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)fe(e[r],t,0)},Polygon:function(n,t){he(n.coordinates,t)},MultiPolygon:function(n,t){for(var e=n.coordinates,r=-1,u=e.length;++r<u;)he(e[r],t)},GeometryCollection:function(n,t){for(var e=n.geometries,r=-1,u=e.length;++r<u;)se(e[r],t)}};ta.geo.area=function(n){return mc=0,ta.geo.stream(n,Mc),mc};var mc,yc=new ce,Mc={sphere:function(){mc+=4*qa},point:b,lineStart:b,lineEnd:b,polygonStart:function(){yc.reset(),Mc.lineStart=ge},polygonEnd:function(){var n=2*yc;mc+=0>n?4*qa+n:n,Mc.lineStart=Mc.lineEnd=Mc.point=b}};ta.geo.bounds=function(){function n(n,t){M.push(x=[s=n,h=n]),f>t&&(f=t),t>g&&(g=t)}function t(t,e){var r=pe([t*Da,e*Da]);if(m){var u=de(m,r),i=[u[1],-u[0],0],o=de(i,u);Me(o),o=xe(o);var c=t-p,l=c>0?1:-1,v=o[0]*Pa*l,d=ga(c)>180;if(d^(v>l*p&&l*t>v)){var y=o[1]*Pa;y>g&&(g=y)}else if(v=(v+360)%360-180,d^(v>l*p&&l*t>v)){var y=-o[1]*Pa;f>y&&(f=y)}else f>e&&(f=e),e>g&&(g=e);d?p>t?a(s,t)>a(s,h)&&(h=t):a(t,h)>a(s,h)&&(s=t):h>=s?(s>t&&(s=t),t>h&&(h=t)):t>p?a(s,t)>a(s,h)&&(h=t):a(t,h)>a(s,h)&&(s=t)}else n(t,e);m=r,p=t}function e(){b.point=t}function r(){x[0]=s,x[1]=h,b.point=n,m=null}function u(n,e){if(m){var r=n-p;y+=ga(r)>180?r+(r>0?360:-360):r}else v=n,d=e;Mc.point(n,e),t(n,e)}function i(){Mc.lineStart()}function o(){u(v,d),Mc.lineEnd(),ga(y)>Ca&&(s=-(h=180)),x[0]=s,x[1]=h,m=null}function a(n,t){return(t-=n)<0?t+360:t}function c(n,t){return n[0]-t[0]}function l(n,t){return t[0]<=t[1]?t[0]<=n&&n<=t[1]:n<t[0]||t[1]<n}var s,f,h,g,p,v,d,m,y,M,x,b={point:n,lineStart:e,lineEnd:r,polygonStart:function(){b.point=u,b.lineStart=i,b.lineEnd=o,y=0,Mc.polygonStart()},polygonEnd:function(){Mc.polygonEnd(),b.point=n,b.lineStart=e,b.lineEnd=r,0>yc?(s=-(h=180),f=-(g=90)):y>Ca?g=90:-Ca>y&&(f=-90),x[0]=s,x[1]=h}};return function(n){g=h=-(s=f=1/0),M=[],ta.geo.stream(n,b);var t=M.length;if(t){M.sort(c);for(var e,r=1,u=M[0],i=[u];t>r;++r)e=M[r],l(e[0],u)||l(e[1],u)?(a(u[0],e[1])>a(u[0],u[1])&&(u[1]=e[1]),a(e[0],u[1])>a(u[0],u[1])&&(u[0]=e[0])):i.push(u=e);for(var o,e,p=-1/0,t=i.length-1,r=0,u=i[t];t>=r;u=e,++r)e=i[r],(o=a(u[1],e[0]))>p&&(p=o,s=e[0],h=u[1])}return M=x=null,1/0===s||1/0===f?[[0/0,0/0],[0/0,0/0]]:[[s,f],[h,g]]}}(),ta.geo.centroid=function(n){xc=bc=_c=wc=Sc=kc=Ec=Ac=Nc=Cc=zc=0,ta.geo.stream(n,qc);var t=Nc,e=Cc,r=zc,u=t*t+e*e+r*r;return za>u&&(t=kc,e=Ec,r=Ac,Ca>bc&&(t=_c,e=wc,r=Sc),u=t*t+e*e+r*r,za>u)?[0/0,0/0]:[Math.atan2(e,t)*Pa,tt(r/Math.sqrt(u))*Pa]};var xc,bc,_c,wc,Sc,kc,Ec,Ac,Nc,Cc,zc,qc={sphere:b,point:_e,lineStart:Se,lineEnd:ke,polygonStart:function(){qc.lineStart=Ee},polygonEnd:function(){qc.lineStart=Se}},Lc=Le(Ne,Pe,je,[-qa,-qa/2]),Tc=1e9;ta.geo.clipExtent=function(){var n,t,e,r,u,i,o={stream:function(n){return u&&(u.valid=!1),u=i(n),u.valid=!0,u},extent:function(a){return arguments.length?(i=Ie(n=+a[0][0],t=+a[0][1],e=+a[1][0],r=+a[1][1]),u&&(u.valid=!1,u=null),o):[[n,t],[e,r]]}};return o.extent([[0,0],[960,500]])},(ta.geo.conicEqualArea=function(){return Ye(Ze)}).raw=Ze,ta.geo.albers=function(){return ta.geo.conicEqualArea().rotate([96,0]).center([-.6,38.7]).parallels([29.5,45.5]).scale(1070)},ta.geo.albersUsa=function(){function n(n){var i=n[0],o=n[1];return t=null,e(i,o),t||(r(i,o),t)||u(i,o),t}var t,e,r,u,i=ta.geo.albers(),o=ta.geo.conicEqualArea().rotate([154,0]).center([-2,58.5]).parallels([55,65]),a=ta.geo.conicEqualArea().rotate([157,0]).center([-3,19.9]).parallels([8,18]),c={point:function(n,e){t=[n,e]}};return n.invert=function(n){var t=i.scale(),e=i.translate(),r=(n[0]-e[0])/t,u=(n[1]-e[1])/t;return(u>=.12&&.234>u&&r>=-.425&&-.214>r?o:u>=.166&&.234>u&&r>=-.214&&-.115>r?a:i).invert(n)},n.stream=function(n){var t=i.stream(n),e=o.stream(n),r=a.stream(n);return{point:function(n,u){t.point(n,u),e.point(n,u),r.point(n,u)},sphere:function(){t.sphere(),e.sphere(),r.sphere()},lineStart:function(){t.lineStart(),e.lineStart(),r.lineStart()},lineEnd:function(){t.lineEnd(),e.lineEnd(),r.lineEnd()},polygonStart:function(){t.polygonStart(),e.polygonStart(),r.polygonStart()},polygonEnd:function(){t.polygonEnd(),e.polygonEnd(),r.polygonEnd()}}},n.precision=function(t){return arguments.length?(i.precision(t),o.precision(t),a.precision(t),n):i.precision()},n.scale=function(t){return arguments.length?(i.scale(t),o.scale(.35*t),a.scale(t),n.translate(i.translate())):i.scale()},n.translate=function(t){if(!arguments.length)return i.translate();var l=i.scale(),s=+t[0],f=+t[1];return e=i.translate(t).clipExtent([[s-.455*l,f-.238*l],[s+.455*l,f+.238*l]]).stream(c).point,r=o.translate([s-.307*l,f+.201*l]).clipExtent([[s-.425*l+Ca,f+.12*l+Ca],[s-.214*l-Ca,f+.234*l-Ca]]).stream(c).point,u=a.translate([s-.205*l,f+.212*l]).clipExtent([[s-.214*l+Ca,f+.166*l+Ca],[s-.115*l-Ca,f+.234*l-Ca]]).stream(c).point,n},n.scale(1070)};var Rc,Dc,Pc,Uc,jc,Fc,Hc={point:b,lineStart:b,lineEnd:b,polygonStart:function(){Dc=0,Hc.lineStart=Ve},polygonEnd:function(){Hc.lineStart=Hc.lineEnd=Hc.point=b,Rc+=ga(Dc/2)}},Oc={point:Xe,lineStart:b,lineEnd:b,polygonStart:b,polygonEnd:b},Ic={point:We,lineStart:Je,lineEnd:Ge,polygonStart:function(){Ic.lineStart=Ke},polygonEnd:function(){Ic.point=We,Ic.lineStart=Je,Ic.lineEnd=Ge}};ta.geo.path=function(){function n(n){return n&&("function"==typeof a&&i.pointRadius(+a.apply(this,arguments)),o&&o.valid||(o=u(i)),ta.geo.stream(n,o)),i.result()}function t(){return o=null,n}var e,r,u,i,o,a=4.5;return n.area=function(n){return Rc=0,ta.geo.stream(n,u(Hc)),Rc},n.centroid=function(n){return _c=wc=Sc=kc=Ec=Ac=Nc=Cc=zc=0,ta.geo.stream(n,u(Ic)),zc?[Nc/zc,Cc/zc]:Ac?[kc/Ac,Ec/Ac]:Sc?[_c/Sc,wc/Sc]:[0/0,0/0]},n.bounds=function(n){return jc=Fc=-(Pc=Uc=1/0),ta.geo.stream(n,u(Oc)),[[Pc,Uc],[jc,Fc]]},n.projection=function(n){return arguments.length?(u=(e=n)?n.stream||tr(n):y,t()):e},n.context=function(n){return arguments.length?(i=null==(r=n)?new $e:new Qe(n),"function"!=typeof a&&i.pointRadius(a),t()):r},n.pointRadius=function(t){return arguments.length?(a="function"==typeof t?t:(i.pointRadius(+t),+t),n):a},n.projection(ta.geo.albersUsa()).context(null)},ta.geo.transform=function(n){return{stream:function(t){var e=new er(t);for(var r in n)e[r]=n[r];return e}}},er.prototype={point:function(n,t){this.stream.point(n,t)},sphere:function(){this.stream.sphere()},lineStart:function(){this.stream.lineStart()},lineEnd:function(){this.stream.lineEnd()},polygonStart:function(){this.stream.polygonStart()},polygonEnd:function(){this.stream.polygonEnd()}},ta.geo.projection=ur,ta.geo.projectionMutator=ir,(ta.geo.equirectangular=function(){return ur(ar)}).raw=ar.invert=ar,ta.geo.rotation=function(n){function t(t){return t=n(t[0]*Da,t[1]*Da),t[0]*=Pa,t[1]*=Pa,t}return n=lr(n[0]%360*Da,n[1]*Da,n.length>2?n[2]*Da:0),t.invert=function(t){return t=n.invert(t[0]*Da,t[1]*Da),t[0]*=Pa,t[1]*=Pa,t},t},cr.invert=ar,ta.geo.circle=function(){function n(){var n="function"==typeof r?r.apply(this,arguments):r,t=lr(-n[0]*Da,-n[1]*Da,0).invert,u=[];return e(null,null,1,{point:function(n,e){u.push(n=t(n,e)),n[0]*=Pa,n[1]*=Pa}}),{type:"Polygon",coordinates:[u]}}var t,e,r=[0,0],u=6;return n.origin=function(t){return arguments.length?(r=t,n):r},n.angle=function(r){return arguments.length?(e=gr((t=+r)*Da,u*Da),n):t},n.precision=function(r){return arguments.length?(e=gr(t*Da,(u=+r)*Da),n):u},n.angle(90)},ta.geo.distance=function(n,t){var e,r=(t[0]-n[0])*Da,u=n[1]*Da,i=t[1]*Da,o=Math.sin(r),a=Math.cos(r),c=Math.sin(u),l=Math.cos(u),s=Math.sin(i),f=Math.cos(i);return Math.atan2(Math.sqrt((e=f*o)*e+(e=l*s-c*f*a)*e),c*s+l*f*a)},ta.geo.graticule=function(){function n(){return{type:"MultiLineString",coordinates:t()}}function t(){return ta.range(Math.ceil(i/d)*d,u,d).map(h).concat(ta.range(Math.ceil(l/m)*m,c,m).map(g)).concat(ta.range(Math.ceil(r/p)*p,e,p).filter(function(n){return ga(n%d)>Ca}).map(s)).concat(ta.range(Math.ceil(a/v)*v,o,v).filter(function(n){return ga(n%m)>Ca}).map(f))}var e,r,u,i,o,a,c,l,s,f,h,g,p=10,v=p,d=90,m=360,y=2.5;return n.lines=function(){return t().map(function(n){return{type:"LineString",coordinates:n}})},n.outline=function(){return{type:"Polygon",coordinates:[h(i).concat(g(c).slice(1),h(u).reverse().slice(1),g(l).reverse().slice(1))]}},n.extent=function(t){return arguments.length?n.majorExtent(t).minorExtent(t):n.minorExtent()},n.majorExtent=function(t){return arguments.length?(i=+t[0][0],u=+t[1][0],l=+t[0][1],c=+t[1][1],i>u&&(t=i,i=u,u=t),l>c&&(t=l,l=c,c=t),n.precision(y)):[[i,l],[u,c]]},n.minorExtent=function(t){return arguments.length?(r=+t[0][0],e=+t[1][0],a=+t[0][1],o=+t[1][1],r>e&&(t=r,r=e,e=t),a>o&&(t=a,a=o,o=t),n.precision(y)):[[r,a],[e,o]]},n.step=function(t){return arguments.length?n.majorStep(t).minorStep(t):n.minorStep()},n.majorStep=function(t){return arguments.length?(d=+t[0],m=+t[1],n):[d,m]},n.minorStep=function(t){return arguments.length?(p=+t[0],v=+t[1],n):[p,v]},n.precision=function(t){return arguments.length?(y=+t,s=vr(a,o,90),f=dr(r,e,y),h=vr(l,c,90),g=dr(i,u,y),n):y},n.majorExtent([[-180,-90+Ca],[180,90-Ca]]).minorExtent([[-180,-80-Ca],[180,80+Ca]])},ta.geo.greatArc=function(){function n(){return{type:"LineString",coordinates:[t||r.apply(this,arguments),e||u.apply(this,arguments)]}}var t,e,r=mr,u=yr;return n.distance=function(){return ta.geo.distance(t||r.apply(this,arguments),e||u.apply(this,arguments))},n.source=function(e){return arguments.length?(r=e,t="function"==typeof e?null:e,n):r},n.target=function(t){return arguments.length?(u=t,e="function"==typeof t?null:t,n):u},n.precision=function(){return arguments.length?n:0},n},ta.geo.interpolate=function(n,t){return Mr(n[0]*Da,n[1]*Da,t[0]*Da,t[1]*Da)},ta.geo.length=function(n){return Yc=0,ta.geo.stream(n,Zc),Yc};var Yc,Zc={sphere:b,point:b,lineStart:xr,lineEnd:b,polygonStart:b,polygonEnd:b},Vc=br(function(n){return Math.sqrt(2/(1+n))},function(n){return 2*Math.asin(n/2)});(ta.geo.azimuthalEqualArea=function(){return ur(Vc)}).raw=Vc;var Xc=br(function(n){var t=Math.acos(n);return t&&t/Math.sin(t)},y);(ta.geo.azimuthalEquidistant=function(){return ur(Xc)}).raw=Xc,(ta.geo.conicConformal=function(){return Ye(_r)}).raw=_r,(ta.geo.conicEquidistant=function(){return Ye(wr)}).raw=wr;var $c=br(function(n){return 1/n},Math.atan);(ta.geo.gnomonic=function(){return ur($c)}).raw=$c,Sr.invert=function(n,t){return[n,2*Math.atan(Math.exp(t))-Ra]},(ta.geo.mercator=function(){return kr(Sr)}).raw=Sr;var Bc=br(function(){return 1},Math.asin);(ta.geo.orthographic=function(){return ur(Bc)}).raw=Bc;var Wc=br(function(n){return 1/(1+n)},function(n){return 2*Math.atan(n)});(ta.geo.stereographic=function(){return ur(Wc)}).raw=Wc,Er.invert=function(n,t){return[-t,2*Math.atan(Math.exp(n))-Ra]},(ta.geo.transverseMercator=function(){var n=kr(Er),t=n.center,e=n.rotate;return n.center=function(n){return n?t([-n[1],n[0]]):(n=t(),[n[1],-n[0]])},n.rotate=function(n){return n?e([n[0],n[1],n.length>2?n[2]+90:90]):(n=e(),[n[0],n[1],n[2]-90])},e([0,0,90])}).raw=Er,ta.geom={},ta.geom.hull=function(n){function t(n){if(n.length<3)return[];var t,u=Et(e),i=Et(r),o=n.length,a=[],c=[];for(t=0;o>t;t++)a.push([+u.call(this,n[t],t),+i.call(this,n[t],t),t]);for(a.sort(zr),t=0;o>t;t++)c.push([a[t][0],-a[t][1]]);var l=Cr(a),s=Cr(c),f=s[0]===l[0],h=s[s.length-1]===l[l.length-1],g=[];for(t=l.length-1;t>=0;--t)g.push(n[a[l[t]][2]]);for(t=+f;t<s.length-h;++t)g.push(n[a[s[t]][2]]);return g}var e=Ar,r=Nr;return arguments.length?t(n):(t.x=function(n){return arguments.length?(e=n,t):e},t.y=function(n){return arguments.length?(r=n,t):r},t)},ta.geom.polygon=function(n){return ya(n,Jc),n};var Jc=ta.geom.polygon.prototype=[];Jc.area=function(){for(var n,t=-1,e=this.length,r=this[e-1],u=0;++t<e;)n=r,r=this[t],u+=n[1]*r[0]-n[0]*r[1];return.5*u},Jc.centroid=function(n){var t,e,r=-1,u=this.length,i=0,o=0,a=this[u-1];for(arguments.length||(n=-1/(6*this.area()));++r<u;)t=a,a=this[r],e=t[0]*a[1]-a[0]*t[1],i+=(t[0]+a[0])*e,o+=(t[1]+a[1])*e;return[i*n,o*n]},Jc.clip=function(n){for(var t,e,r,u,i,o,a=Tr(n),c=-1,l=this.length-Tr(this),s=this[l-1];++c<l;){for(t=n.slice(),n.length=0,u=this[c],i=t[(r=t.length-a)-1],e=-1;++e<r;)o=t[e],qr(o,s,u)?(qr(i,s,u)||n.push(Lr(i,o,s,u)),n.push(o)):qr(i,s,u)&&n.push(Lr(i,o,s,u)),i=o;a&&n.push(n[0]),s=u}return n};var Gc,Kc,Qc,nl,tl,el=[],rl=[];Or.prototype.prepare=function(){for(var n,t=this.edges,e=t.length;e--;)n=t[e].edge,n.b&&n.a||t.splice(e,1);return t.sort(Yr),t.length},Qr.prototype={start:function(){return this.edge.l===this.site?this.edge.a:this.edge.b},end:function(){return this.edge.l===this.site?this.edge.b:this.edge.a}},nu.prototype={insert:function(n,t){var e,r,u;if(n){if(t.P=n,t.N=n.N,n.N&&(n.N.P=t),n.N=t,n.R){for(n=n.R;n.L;)n=n.L;n.L=t}else n.R=t;e=n}else this._?(n=uu(this._),t.P=null,t.N=n,n.P=n.L=t,e=n):(t.P=t.N=null,this._=t,e=null);for(t.L=t.R=null,t.U=e,t.C=!0,n=t;e&&e.C;)r=e.U,e===r.L?(u=r.R,u&&u.C?(e.C=u.C=!1,r.C=!0,n=r):(n===e.R&&(eu(this,e),n=e,e=n.U),e.C=!1,r.C=!0,ru(this,r))):(u=r.L,u&&u.C?(e.C=u.C=!1,r.C=!0,n=r):(n===e.L&&(ru(this,e),n=e,e=n.U),e.C=!1,r.C=!0,eu(this,r))),e=n.U;this._.C=!1},remove:function(n){n.N&&(n.N.P=n.P),n.P&&(n.P.N=n.N),n.N=n.P=null;var t,e,r,u=n.U,i=n.L,o=n.R;if(e=i?o?uu(o):i:o,u?u.L===n?u.L=e:u.R=e:this._=e,i&&o?(r=e.C,e.C=n.C,e.L=i,i.U=e,e!==o?(u=e.U,e.U=n.U,n=e.R,u.L=n,e.R=o,o.U=e):(e.U=u,u=e,n=e.R)):(r=n.C,n=e),n&&(n.U=u),!r){if(n&&n.C)return void(n.C=!1);do{if(n===this._)break;if(n===u.L){if(t=u.R,t.C&&(t.C=!1,u.C=!0,eu(this,u),t=u.R),t.L&&t.L.C||t.R&&t.R.C){t.R&&t.R.C||(t.L.C=!1,t.C=!0,ru(this,t),t=u.R),t.C=u.C,u.C=t.R.C=!1,eu(this,u),n=this._;break}}else if(t=u.L,t.C&&(t.C=!1,u.C=!0,ru(this,u),t=u.L),t.L&&t.L.C||t.R&&t.R.C){t.L&&t.L.C||(t.R.C=!1,t.C=!0,eu(this,t),t=u.L),t.C=u.C,u.C=t.L.C=!1,ru(this,u),n=this._;break}t.C=!0,n=u,u=u.U}while(!n.C);n&&(n.C=!1)}}},ta.geom.voronoi=function(n){function t(n){var t=new Array(n.length),r=a[0][0],u=a[0][1],i=a[1][0],o=a[1][1];return iu(e(n),a).cells.forEach(function(e,a){var c=e.edges,l=e.site,s=t[a]=c.length?c.map(function(n){var t=n.start();return[t.x,t.y]}):l.x>=r&&l.x<=i&&l.y>=u&&l.y<=o?[[r,o],[i,o],[i,u],[r,u]]:[];s.point=n[a]}),t}function e(n){return n.map(function(n,t){return{x:Math.round(i(n,t)/Ca)*Ca,y:Math.round(o(n,t)/Ca)*Ca,i:t}})}var r=Ar,u=Nr,i=r,o=u,a=ul;return n?t(n):(t.links=function(n){return iu(e(n)).edges.filter(function(n){return n.l&&n.r}).map(function(t){return{source:n[t.l.i],target:n[t.r.i]}})},t.triangles=function(n){var t=[];return iu(e(n)).cells.forEach(function(e,r){for(var u,i,o=e.site,a=e.edges.sort(Yr),c=-1,l=a.length,s=a[l-1].edge,f=s.l===o?s.r:s.l;++c<l;)u=s,i=f,s=a[c].edge,f=s.l===o?s.r:s.l,r<i.i&&r<f.i&&au(o,i,f)<0&&t.push([n[r],n[i.i],n[f.i]])}),t},t.x=function(n){return arguments.length?(i=Et(r=n),t):r},t.y=function(n){return arguments.length?(o=Et(u=n),t):u},t.clipExtent=function(n){return arguments.length?(a=null==n?ul:n,t):a===ul?null:a},t.size=function(n){return arguments.length?t.clipExtent(n&&[[0,0],n]):a===ul?null:a&&a[1]},t)};var ul=[[-1e6,-1e6],[1e6,1e6]];ta.geom.delaunay=function(n){return ta.geom.voronoi().triangles(n)},ta.geom.quadtree=function(n,t,e,r,u){function i(n){function i(n,t,e,r,u,i,o,a){if(!isNaN(e)&&!isNaN(r))if(n.leaf){var c=n.x,s=n.y;if(null!=c)if(ga(c-e)+ga(s-r)<.01)l(n,t,e,r,u,i,o,a);else{var f=n.point;n.x=n.y=n.point=null,l(n,f,c,s,u,i,o,a),l(n,t,e,r,u,i,o,a)}else n.x=e,n.y=r,n.point=t}else l(n,t,e,r,u,i,o,a)}function l(n,t,e,r,u,o,a,c){var l=.5*(u+a),s=.5*(o+c),f=e>=l,h=r>=s,g=h<<1|f;n.leaf=!1,n=n.nodes[g]||(n.nodes[g]=su()),f?u=l:a=l,h?o=s:c=s,i(n,t,e,r,u,o,a,c)}var s,f,h,g,p,v,d,m,y,M=Et(a),x=Et(c);if(null!=t)v=t,d=e,m=r,y=u;else if(m=y=-(v=d=1/0),f=[],h=[],p=n.length,o)for(g=0;p>g;++g)s=n[g],s.x<v&&(v=s.x),s.y<d&&(d=s.y),s.x>m&&(m=s.x),s.y>y&&(y=s.y),f.push(s.x),h.push(s.y);else for(g=0;p>g;++g){var b=+M(s=n[g],g),_=+x(s,g);v>b&&(v=b),d>_&&(d=_),b>m&&(m=b),_>y&&(y=_),f.push(b),h.push(_)}var w=m-v,S=y-d;w>S?y=d+w:m=v+S;var k=su();if(k.add=function(n){i(k,n,+M(n,++g),+x(n,g),v,d,m,y)},k.visit=function(n){fu(n,k,v,d,m,y)},k.find=function(n){return hu(k,n[0],n[1],v,d,m,y)},g=-1,null==t){for(;++g<p;)i(k,n[g],f[g],h[g],v,d,m,y);--g}else n.forEach(k.add);return f=h=n=s=null,k}var o,a=Ar,c=Nr;return(o=arguments.length)?(a=cu,c=lu,3===o&&(u=e,r=t,e=t=0),i(n)):(i.x=function(n){return arguments.length?(a=n,i):a},i.y=function(n){return arguments.length?(c=n,i):c},i.extent=function(n){return arguments.length?(null==n?t=e=r=u=null:(t=+n[0][0],e=+n[0][1],r=+n[1][0],u=+n[1][1]),i):null==t?null:[[t,e],[r,u]]},i.size=function(n){return arguments.length?(null==n?t=e=r=u=null:(t=e=0,r=+n[0],u=+n[1]),i):null==t?null:[r-t,u-e]},i)},ta.interpolateRgb=gu,ta.interpolateObject=pu,ta.interpolateNumber=vu,ta.interpolateString=du;var il=/[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g,ol=new RegExp(il.source,"g");ta.interpolate=mu,ta.interpolators=[function(n,t){var e=typeof t;return("string"===e?Ga.has(t.toLowerCase())||/^(#|rgb\(|hsl\()/i.test(t)?gu:du:t instanceof ot?gu:Array.isArray(t)?yu:"object"===e&&isNaN(t)?pu:vu)(n,t)}],ta.interpolateArray=yu;var al=function(){return y},cl=ta.map({linear:al,poly:ku,quad:function(){return _u},cubic:function(){return wu},sin:function(){return Eu},exp:function(){return Au},circle:function(){return Nu},elastic:Cu,back:zu,bounce:function(){return qu}}),ll=ta.map({"in":y,out:xu,"in-out":bu,"out-in":function(n){return bu(xu(n))}});ta.ease=function(n){var t=n.indexOf("-"),e=t>=0?n.slice(0,t):n,r=t>=0?n.slice(t+1):"in";return e=cl.get(e)||al,r=ll.get(r)||y,Mu(r(e.apply(null,ea.call(arguments,1))))},ta.interpolateHcl=Lu,ta.interpolateHsl=Tu,ta.interpolateLab=Ru,ta.interpolateRound=Du,ta.transform=function(n){var t=ua.createElementNS(ta.ns.prefix.svg,"g");return(ta.transform=function(n){if(null!=n){t.setAttribute("transform",n);var e=t.transform.baseVal.consolidate()}return new Pu(e?e.matrix:sl)})(n)},Pu.prototype.toString=function(){return"translate("+this.translate+")rotate("+this.rotate+")skewX("+this.skew+")scale("+this.scale+")"};var sl={a:1,b:0,c:0,d:1,e:0,f:0};ta.interpolateTransform=Hu,ta.layout={},ta.layout.bundle=function(){return function(n){for(var t=[],e=-1,r=n.length;++e<r;)t.push(Yu(n[e]));return t}},ta.layout.chord=function(){function n(){var n,l,f,h,g,p={},v=[],d=ta.range(i),m=[];for(e=[],r=[],n=0,h=-1;++h<i;){for(l=0,g=-1;++g<i;)l+=u[h][g];v.push(l),m.push(ta.range(i)),n+=l}for(o&&d.sort(function(n,t){return o(v[n],v[t])}),a&&m.forEach(function(n,t){n.sort(function(n,e){return a(u[t][n],u[t][e])})}),n=(La-s*i)/n,l=0,h=-1;++h<i;){for(f=l,g=-1;++g<i;){var y=d[h],M=m[y][g],x=u[y][M],b=l,_=l+=x*n;p[y+"-"+M]={index:y,subindex:M,startAngle:b,endAngle:_,value:x}}r[y]={index:y,startAngle:f,endAngle:l,value:(l-f)/n},l+=s}for(h=-1;++h<i;)for(g=h-1;++g<i;){var w=p[h+"-"+g],S=p[g+"-"+h];(w.value||S.value)&&e.push(w.value<S.value?{source:S,target:w}:{source:w,target:S})}c&&t()}function t(){e.sort(function(n,t){return c((n.source.value+n.target.value)/2,(t.source.value+t.target.value)/2)})}var e,r,u,i,o,a,c,l={},s=0;return l.matrix=function(n){return arguments.length?(i=(u=n)&&u.length,e=r=null,l):u},l.padding=function(n){return arguments.length?(s=n,e=r=null,l):s},l.sortGroups=function(n){return arguments.length?(o=n,e=r=null,l):o},l.sortSubgroups=function(n){return arguments.length?(a=n,e=null,l):a},l.sortChords=function(n){return arguments.length?(c=n,e&&t(),l):c},l.chords=function(){return e||n(),e},l.groups=function(){return r||n(),r},l},ta.layout.force=function(){function n(n){return function(t,e,r,u){if(t.point!==n){var i=t.cx-n.x,o=t.cy-n.y,a=u-e,c=i*i+o*o;if(c>a*a/d){if(p>c){var l=t.charge/c;n.px-=i*l,n.py-=o*l}return!0}if(t.point&&c&&p>c){var l=t.pointCharge/c;n.px-=i*l,n.py-=o*l}}return!t.charge}}function t(n){n.px=ta.event.x,n.py=ta.event.y,a.resume()}var e,r,u,i,o,a={},c=ta.dispatch("start","tick","end"),l=[1,1],s=.9,f=fl,h=hl,g=-30,p=gl,v=.1,d=.64,m=[],M=[];return a.tick=function(){if((r*=.99)<.005)return c.end({type:"end",alpha:r=0}),!0;var t,e,a,f,h,p,d,y,x,b=m.length,_=M.length;for(e=0;_>e;++e)a=M[e],f=a.source,h=a.target,y=h.x-f.x,x=h.y-f.y,(p=y*y+x*x)&&(p=r*i[e]*((p=Math.sqrt(p))-u[e])/p,y*=p,x*=p,h.x-=y*(d=f.weight/(h.weight+f.weight)),h.y-=x*d,f.x+=y*(d=1-d),f.y+=x*d);if((d=r*v)&&(y=l[0]/2,x=l[1]/2,e=-1,d))for(;++e<b;)a=m[e],a.x+=(y-a.x)*d,a.y+=(x-a.y)*d;if(g)for(Ju(t=ta.geom.quadtree(m),r,o),e=-1;++e<b;)(a=m[e]).fixed||t.visit(n(a));for(e=-1;++e<b;)a=m[e],a.fixed?(a.x=a.px,a.y=a.py):(a.x-=(a.px-(a.px=a.x))*s,a.y-=(a.py-(a.py=a.y))*s);c.tick({type:"tick",alpha:r})},a.nodes=function(n){return arguments.length?(m=n,a):m},a.links=function(n){return arguments.length?(M=n,a):M},a.size=function(n){return arguments.length?(l=n,a):l},a.linkDistance=function(n){return arguments.length?(f="function"==typeof n?n:+n,a):f},a.distance=a.linkDistance,a.linkStrength=function(n){return arguments.length?(h="function"==typeof n?n:+n,a):h},a.friction=function(n){return arguments.length?(s=+n,a):s},a.charge=function(n){return arguments.length?(g="function"==typeof n?n:+n,a):g},a.chargeDistance=function(n){return arguments.length?(p=n*n,a):Math.sqrt(p)},a.gravity=function(n){return arguments.length?(v=+n,a):v},a.theta=function(n){return arguments.length?(d=n*n,a):Math.sqrt(d)},a.alpha=function(n){return arguments.length?(n=+n,r?r=n>0?n:0:n>0&&(c.start({type:"start",alpha:r=n}),ta.timer(a.tick)),a):r},a.start=function(){function n(n,r){if(!e){for(e=new Array(c),a=0;c>a;++a)e[a]=[];for(a=0;s>a;++a){var u=M[a];e[u.source.index].push(u.target),e[u.target.index].push(u.source)}}for(var i,o=e[t],a=-1,l=o.length;++a<l;)if(!isNaN(i=o[a][n]))return i;return Math.random()*r}var t,e,r,c=m.length,s=M.length,p=l[0],v=l[1];for(t=0;c>t;++t)(r=m[t]).index=t,r.weight=0;for(t=0;s>t;++t)r=M[t],"number"==typeof r.source&&(r.source=m[r.source]),"number"==typeof r.target&&(r.target=m[r.target]),++r.source.weight,++r.target.weight;for(t=0;c>t;++t)r=m[t],isNaN(r.x)&&(r.x=n("x",p)),isNaN(r.y)&&(r.y=n("y",v)),isNaN(r.px)&&(r.px=r.x),isNaN(r.py)&&(r.py=r.y);if(u=[],"function"==typeof f)for(t=0;s>t;++t)u[t]=+f.call(this,M[t],t);else for(t=0;s>t;++t)u[t]=f;if(i=[],"function"==typeof h)for(t=0;s>t;++t)i[t]=+h.call(this,M[t],t);else for(t=0;s>t;++t)i[t]=h;if(o=[],"function"==typeof g)for(t=0;c>t;++t)o[t]=+g.call(this,m[t],t);else for(t=0;c>t;++t)o[t]=g;return a.resume()},a.resume=function(){return a.alpha(.1)},a.stop=function(){return a.alpha(0)},a.drag=function(){return e||(e=ta.behavior.drag().origin(y).on("dragstart.force",Xu).on("drag.force",t).on("dragend.force",$u)),arguments.length?void this.on("mouseover.force",Bu).on("mouseout.force",Wu).call(e):e},ta.rebind(a,c,"on")};var fl=20,hl=1,gl=1/0;ta.layout.hierarchy=function(){function n(u){var i,o=[u],a=[];for(u.depth=0;null!=(i=o.pop());)if(a.push(i),(l=e.call(n,i,i.depth))&&(c=l.length)){for(var c,l,s;--c>=0;)o.push(s=l[c]),s.parent=i,s.depth=i.depth+1;r&&(i.value=0),i.children=l}else r&&(i.value=+r.call(n,i,i.depth)||0),delete i.children;return Qu(u,function(n){var e,u;t&&(e=n.children)&&e.sort(t),r&&(u=n.parent)&&(u.value+=n.value)}),a}var t=ei,e=ni,r=ti;return n.sort=function(e){return arguments.length?(t=e,n):t},n.children=function(t){return arguments.length?(e=t,n):e},n.value=function(t){return arguments.length?(r=t,n):r},n.revalue=function(t){return r&&(Ku(t,function(n){n.children&&(n.value=0)}),Qu(t,function(t){var e;t.children||(t.value=+r.call(n,t,t.depth)||0),(e=t.parent)&&(e.value+=t.value)})),t},n},ta.layout.partition=function(){function n(t,e,r,u){var i=t.children;if(t.x=e,t.y=t.depth*u,t.dx=r,t.dy=u,i&&(o=i.length)){var o,a,c,l=-1;for(r=t.value?r/t.value:0;++l<o;)n(a=i[l],e,c=a.value*r,u),e+=c}}function t(n){var e=n.children,r=0;if(e&&(u=e.length))for(var u,i=-1;++i<u;)r=Math.max(r,t(e[i]));return 1+r}function e(e,i){var o=r.call(this,e,i);return n(o[0],0,u[0],u[1]/t(o[0])),o}var r=ta.layout.hierarchy(),u=[1,1];return e.size=function(n){return arguments.length?(u=n,e):u},Gu(e,r)},ta.layout.pie=function(){function n(o){var a,c=o.length,l=o.map(function(e,r){return+t.call(n,e,r)}),s=+("function"==typeof r?r.apply(this,arguments):r),f=("function"==typeof u?u.apply(this,arguments):u)-s,h=Math.min(Math.abs(f)/c,+("function"==typeof i?i.apply(this,arguments):i)),g=h*(0>f?-1:1),p=(f-c*g)/ta.sum(l),v=ta.range(c),d=[];return null!=e&&v.sort(e===pl?function(n,t){return l[t]-l[n]}:function(n,t){return e(o[n],o[t])}),v.forEach(function(n){d[n]={data:o[n],value:a=l[n],startAngle:s,endAngle:s+=a*p+g,padAngle:h}}),d}var t=Number,e=pl,r=0,u=La,i=0;return n.value=function(e){return arguments.length?(t=e,n):t},n.sort=function(t){return arguments.length?(e=t,n):e},n.startAngle=function(t){return arguments.length?(r=t,n):r},n.endAngle=function(t){return arguments.length?(u=t,n):u},n.padAngle=function(t){return arguments.length?(i=t,n):i},n};var pl={};ta.layout.stack=function(){function n(a,c){if(!(h=a.length))return a;var l=a.map(function(e,r){return t.call(n,e,r)}),s=l.map(function(t){return t.map(function(t,e){return[i.call(n,t,e),o.call(n,t,e)]})}),f=e.call(n,s,c);l=ta.permute(l,f),s=ta.permute(s,f);var h,g,p,v,d=r.call(n,s,c),m=l[0].length;for(p=0;m>p;++p)for(u.call(n,l[0][p],v=d[p],s[0][p][1]),g=1;h>g;++g)u.call(n,l[g][p],v+=s[g-1][p][1],s[g][p][1]);return a}var t=y,e=ai,r=ci,u=oi,i=ui,o=ii;return n.values=function(e){return arguments.length?(t=e,n):t},n.order=function(t){return arguments.length?(e="function"==typeof t?t:vl.get(t)||ai,n):e},n.offset=function(t){return arguments.length?(r="function"==typeof t?t:dl.get(t)||ci,n):r},n.x=function(t){return arguments.length?(i=t,n):i},n.y=function(t){return arguments.length?(o=t,n):o},n.out=function(t){return arguments.length?(u=t,n):u},n};var vl=ta.map({"inside-out":function(n){var t,e,r=n.length,u=n.map(li),i=n.map(si),o=ta.range(r).sort(function(n,t){return u[n]-u[t]}),a=0,c=0,l=[],s=[];for(t=0;r>t;++t)e=o[t],c>a?(a+=i[e],l.push(e)):(c+=i[e],s.push(e));return s.reverse().concat(l)},reverse:function(n){return ta.range(n.length).reverse()},"default":ai}),dl=ta.map({silhouette:function(n){var t,e,r,u=n.length,i=n[0].length,o=[],a=0,c=[];for(e=0;i>e;++e){for(t=0,r=0;u>t;t++)r+=n[t][e][1];r>a&&(a=r),o.push(r)}for(e=0;i>e;++e)c[e]=(a-o[e])/2;return c},wiggle:function(n){var t,e,r,u,i,o,a,c,l,s=n.length,f=n[0],h=f.length,g=[];for(g[0]=c=l=0,e=1;h>e;++e){for(t=0,u=0;s>t;++t)u+=n[t][e][1];for(t=0,i=0,a=f[e][0]-f[e-1][0];s>t;++t){for(r=0,o=(n[t][e][1]-n[t][e-1][1])/(2*a);t>r;++r)o+=(n[r][e][1]-n[r][e-1][1])/a;i+=o*n[t][e][1]}g[e]=c-=u?i/u*a:0,l>c&&(l=c)}for(e=0;h>e;++e)g[e]-=l;return g},expand:function(n){var t,e,r,u=n.length,i=n[0].length,o=1/u,a=[];for(e=0;i>e;++e){for(t=0,r=0;u>t;t++)r+=n[t][e][1];if(r)for(t=0;u>t;t++)n[t][e][1]/=r;else for(t=0;u>t;t++)n[t][e][1]=o}for(e=0;i>e;++e)a[e]=0;return a},zero:ci});ta.layout.histogram=function(){function n(n,i){for(var o,a,c=[],l=n.map(e,this),s=r.call(this,l,i),f=u.call(this,s,l,i),i=-1,h=l.length,g=f.length-1,p=t?1:1/h;++i<g;)o=c[i]=[],o.dx=f[i+1]-(o.x=f[i]),o.y=0;if(g>0)for(i=-1;++i<h;)a=l[i],a>=s[0]&&a<=s[1]&&(o=c[ta.bisect(f,a,1,g)-1],o.y+=p,o.push(n[i]));return c}var t=!0,e=Number,r=pi,u=hi;return n.value=function(t){return arguments.length?(e=t,n):e},n.range=function(t){return arguments.length?(r=Et(t),n):r},n.bins=function(t){return arguments.length?(u="number"==typeof t?function(n){return gi(n,t)}:Et(t),n):u},n.frequency=function(e){return arguments.length?(t=!!e,n):t},n},ta.layout.pack=function(){function n(n,i){var o=e.call(this,n,i),a=o[0],c=u[0],l=u[1],s=null==t?Math.sqrt:"function"==typeof t?t:function(){return t};if(a.x=a.y=0,Qu(a,function(n){n.r=+s(n.value)}),Qu(a,Mi),r){var f=r*(t?1:Math.max(2*a.r/c,2*a.r/l))/2;Qu(a,function(n){n.r+=f}),Qu(a,Mi),Qu(a,function(n){n.r-=f})}return _i(a,c/2,l/2,t?1:1/Math.max(2*a.r/c,2*a.r/l)),o}var t,e=ta.layout.hierarchy().sort(vi),r=0,u=[1,1];return n.size=function(t){return arguments.length?(u=t,n):u},n.radius=function(e){return arguments.length?(t=null==e||"function"==typeof e?e:+e,n):t},n.padding=function(t){return arguments.length?(r=+t,n):r},Gu(n,e)},ta.layout.tree=function(){function n(n,u){var s=o.call(this,n,u),f=s[0],h=t(f);if(Qu(h,e),h.parent.m=-h.z,Ku(h,r),l)Ku(f,i);else{var g=f,p=f,v=f;Ku(f,function(n){n.x<g.x&&(g=n),n.x>p.x&&(p=n),n.depth>v.depth&&(v=n)});var d=a(g,p)/2-g.x,m=c[0]/(p.x+a(p,g)/2+d),y=c[1]/(v.depth||1);Ku(f,function(n){n.x=(n.x+d)*m,n.y=n.depth*y})}return s}function t(n){for(var t,e={A:null,children:[n]},r=[e];null!=(t=r.pop());)for(var u,i=t.children,o=0,a=i.length;a>o;++o)r.push((i[o]=u={_:i[o],parent:t,children:(u=i[o].children)&&u.slice()||[],A:null,a:null,z:0,m:0,c:0,s:0,t:null,i:o}).a=u);return e.children[0]}function e(n){var t=n.children,e=n.parent.children,r=n.i?e[n.i-1]:null;if(t.length){Ni(n);var i=(t[0].z+t[t.length-1].z)/2;r?(n.z=r.z+a(n._,r._),n.m=n.z-i):n.z=i}else r&&(n.z=r.z+a(n._,r._));n.parent.A=u(n,r,n.parent.A||e[0])}function r(n){n._.x=n.z+n.parent.m,n.m+=n.parent.m}function u(n,t,e){if(t){for(var r,u=n,i=n,o=t,c=u.parent.children[0],l=u.m,s=i.m,f=o.m,h=c.m;o=Ei(o),u=ki(u),o&&u;)c=ki(c),i=Ei(i),i.a=n,r=o.z+f-u.z-l+a(o._,u._),r>0&&(Ai(Ci(o,n,e),n,r),l+=r,s+=r),f+=o.m,l+=u.m,h+=c.m,s+=i.m;o&&!Ei(i)&&(i.t=o,i.m+=f-s),u&&!ki(c)&&(c.t=u,c.m+=l-h,e=n)}return e}function i(n){n.x*=c[0],n.y=n.depth*c[1]}var o=ta.layout.hierarchy().sort(null).value(null),a=Si,c=[1,1],l=null;return n.separation=function(t){return arguments.length?(a=t,n):a},n.size=function(t){return arguments.length?(l=null==(c=t)?i:null,n):l?null:c},n.nodeSize=function(t){return arguments.length?(l=null==(c=t)?null:i,n):l?c:null},Gu(n,o)},ta.layout.cluster=function(){function n(n,i){var o,a=t.call(this,n,i),c=a[0],l=0;Qu(c,function(n){var t=n.children;t&&t.length?(n.x=qi(t),n.y=zi(t)):(n.x=o?l+=e(n,o):0,n.y=0,o=n)});var s=Li(c),f=Ti(c),h=s.x-e(s,f)/2,g=f.x+e(f,s)/2;return Qu(c,u?function(n){n.x=(n.x-c.x)*r[0],n.y=(c.y-n.y)*r[1]}:function(n){n.x=(n.x-h)/(g-h)*r[0],n.y=(1-(c.y?n.y/c.y:1))*r[1]}),a}var t=ta.layout.hierarchy().sort(null).value(null),e=Si,r=[1,1],u=!1;return n.separation=function(t){return arguments.length?(e=t,n):e},n.size=function(t){return arguments.length?(u=null==(r=t),n):u?null:r},n.nodeSize=function(t){return arguments.length?(u=null!=(r=t),n):u?r:null},Gu(n,t)},ta.layout.treemap=function(){function n(n,t){for(var e,r,u=-1,i=n.length;++u<i;)r=(e=n[u]).value*(0>t?0:t),e.area=isNaN(r)||0>=r?0:r}function t(e){var i=e.children;if(i&&i.length){var o,a,c,l=f(e),s=[],h=i.slice(),p=1/0,v="slice"===g?l.dx:"dice"===g?l.dy:"slice-dice"===g?1&e.depth?l.dy:l.dx:Math.min(l.dx,l.dy);for(n(h,l.dx*l.dy/e.value),s.area=0;(c=h.length)>0;)s.push(o=h[c-1]),s.area+=o.area,"squarify"!==g||(a=r(s,v))<=p?(h.pop(),p=a):(s.area-=s.pop().area,u(s,v,l,!1),v=Math.min(l.dx,l.dy),s.length=s.area=0,p=1/0);s.length&&(u(s,v,l,!0),s.length=s.area=0),i.forEach(t)}}function e(t){var r=t.children;if(r&&r.length){var i,o=f(t),a=r.slice(),c=[];for(n(a,o.dx*o.dy/t.value),c.area=0;i=a.pop();)c.push(i),c.area+=i.area,null!=i.z&&(u(c,i.z?o.dx:o.dy,o,!a.length),c.length=c.area=0);r.forEach(e)}}function r(n,t){for(var e,r=n.area,u=0,i=1/0,o=-1,a=n.length;++o<a;)(e=n[o].area)&&(i>e&&(i=e),e>u&&(u=e));return r*=r,t*=t,r?Math.max(t*u*p/r,r/(t*i*p)):1/0}function u(n,t,e,r){var u,i=-1,o=n.length,a=e.x,l=e.y,s=t?c(n.area/t):0;if(t==e.dx){for((r||s>e.dy)&&(s=e.dy);++i<o;)u=n[i],u.x=a,u.y=l,u.dy=s,a+=u.dx=Math.min(e.x+e.dx-a,s?c(u.area/s):0);u.z=!0,u.dx+=e.x+e.dx-a,e.y+=s,e.dy-=s}else{for((r||s>e.dx)&&(s=e.dx);++i<o;)u=n[i],u.x=a,u.y=l,u.dx=s,l+=u.dy=Math.min(e.y+e.dy-l,s?c(u.area/s):0);u.z=!1,u.dy+=e.y+e.dy-l,e.x+=s,e.dx-=s}}function i(r){var u=o||a(r),i=u[0];return i.x=0,i.y=0,i.dx=l[0],i.dy=l[1],o&&a.revalue(i),n([i],i.dx*i.dy/i.value),(o?e:t)(i),h&&(o=u),u}var o,a=ta.layout.hierarchy(),c=Math.round,l=[1,1],s=null,f=Ri,h=!1,g="squarify",p=.5*(1+Math.sqrt(5));
+return i.size=function(n){return arguments.length?(l=n,i):l},i.padding=function(n){function t(t){var e=n.call(i,t,t.depth);return null==e?Ri(t):Di(t,"number"==typeof e?[e,e,e,e]:e)}function e(t){return Di(t,n)}if(!arguments.length)return s;var r;return f=null==(s=n)?Ri:"function"==(r=typeof n)?t:"number"===r?(n=[n,n,n,n],e):e,i},i.round=function(n){return arguments.length?(c=n?Math.round:Number,i):c!=Number},i.sticky=function(n){return arguments.length?(h=n,o=null,i):h},i.ratio=function(n){return arguments.length?(p=n,i):p},i.mode=function(n){return arguments.length?(g=n+"",i):g},Gu(i,a)},ta.random={normal:function(n,t){var e=arguments.length;return 2>e&&(t=1),1>e&&(n=0),function(){var e,r,u;do e=2*Math.random()-1,r=2*Math.random()-1,u=e*e+r*r;while(!u||u>1);return n+t*e*Math.sqrt(-2*Math.log(u)/u)}},logNormal:function(){var n=ta.random.normal.apply(ta,arguments);return function(){return Math.exp(n())}},bates:function(n){var t=ta.random.irwinHall(n);return function(){return t()/n}},irwinHall:function(n){return function(){for(var t=0,e=0;n>e;e++)t+=Math.random();return t}}},ta.scale={};var ml={floor:y,ceil:y};ta.scale.linear=function(){return Ii([0,1],[0,1],mu,!1)};var yl={s:1,g:1,p:1,r:1,e:1};ta.scale.log=function(){return Ji(ta.scale.linear().domain([0,1]),10,!0,[1,10])};var Ml=ta.format(".0e"),xl={floor:function(n){return-Math.ceil(-n)},ceil:function(n){return-Math.floor(-n)}};ta.scale.pow=function(){return Gi(ta.scale.linear(),1,[0,1])},ta.scale.sqrt=function(){return ta.scale.pow().exponent(.5)},ta.scale.ordinal=function(){return Qi([],{t:"range",a:[[]]})},ta.scale.category10=function(){return ta.scale.ordinal().range(bl)},ta.scale.category20=function(){return ta.scale.ordinal().range(_l)},ta.scale.category20b=function(){return ta.scale.ordinal().range(wl)},ta.scale.category20c=function(){return ta.scale.ordinal().range(Sl)};var bl=[2062260,16744206,2924588,14034728,9725885,9197131,14907330,8355711,12369186,1556175].map(Mt),_l=[2062260,11454440,16744206,16759672,2924588,10018698,14034728,16750742,9725885,12955861,9197131,12885140,14907330,16234194,8355711,13092807,12369186,14408589,1556175,10410725].map(Mt),wl=[3750777,5395619,7040719,10264286,6519097,9216594,11915115,13556636,9202993,12426809,15186514,15190932,8666169,11356490,14049643,15177372,8077683,10834324,13528509,14589654].map(Mt),Sl=[3244733,7057110,10406625,13032431,15095053,16616764,16625259,16634018,3253076,7652470,10607003,13101504,7695281,10394312,12369372,14342891,6513507,9868950,12434877,14277081].map(Mt);ta.scale.quantile=function(){return no([],[])},ta.scale.quantize=function(){return to(0,1,[0,1])},ta.scale.threshold=function(){return eo([.5],[0,1])},ta.scale.identity=function(){return ro([0,1])},ta.svg={},ta.svg.arc=function(){function n(){var n=Math.max(0,+e.apply(this,arguments)),l=Math.max(0,+r.apply(this,arguments)),s=o.apply(this,arguments)-Ra,f=a.apply(this,arguments)-Ra,h=Math.abs(f-s),g=s>f?0:1;if(n>l&&(p=l,l=n,n=p),h>=Ta)return t(l,g)+(n?t(n,1-g):"")+"Z";var p,v,d,m,y,M,x,b,_,w,S,k,E=0,A=0,N=[];if((m=(+c.apply(this,arguments)||0)/2)&&(d=i===kl?Math.sqrt(n*n+l*l):+i.apply(this,arguments),g||(A*=-1),l&&(A=tt(d/l*Math.sin(m))),n&&(E=tt(d/n*Math.sin(m)))),l){y=l*Math.cos(s+A),M=l*Math.sin(s+A),x=l*Math.cos(f-A),b=l*Math.sin(f-A);var C=Math.abs(f-s-2*A)<=qa?0:1;if(A&&so(y,M,x,b)===g^C){var z=(s+f)/2;y=l*Math.cos(z),M=l*Math.sin(z),x=b=null}}else y=M=0;if(n){_=n*Math.cos(f-E),w=n*Math.sin(f-E),S=n*Math.cos(s+E),k=n*Math.sin(s+E);var q=Math.abs(s-f+2*E)<=qa?0:1;if(E&&so(_,w,S,k)===1-g^q){var L=(s+f)/2;_=n*Math.cos(L),w=n*Math.sin(L),S=k=null}}else _=w=0;if((p=Math.min(Math.abs(l-n)/2,+u.apply(this,arguments)))>.001){v=l>n^g?0:1;var T=null==S?[_,w]:null==x?[y,M]:Lr([y,M],[S,k],[x,b],[_,w]),R=y-T[0],D=M-T[1],P=x-T[0],U=b-T[1],j=1/Math.sin(Math.acos((R*P+D*U)/(Math.sqrt(R*R+D*D)*Math.sqrt(P*P+U*U)))/2),F=Math.sqrt(T[0]*T[0]+T[1]*T[1]);if(null!=x){var H=Math.min(p,(l-F)/(j+1)),O=fo(null==S?[_,w]:[S,k],[y,M],l,H,g),I=fo([x,b],[_,w],l,H,g);p===H?N.push("M",O[0],"A",H,",",H," 0 0,",v," ",O[1],"A",l,",",l," 0 ",1-g^so(O[1][0],O[1][1],I[1][0],I[1][1]),",",g," ",I[1],"A",H,",",H," 0 0,",v," ",I[0]):N.push("M",O[0],"A",H,",",H," 0 1,",v," ",I[0])}else N.push("M",y,",",M);if(null!=S){var Y=Math.min(p,(n-F)/(j-1)),Z=fo([y,M],[S,k],n,-Y,g),V=fo([_,w],null==x?[y,M]:[x,b],n,-Y,g);p===Y?N.push("L",V[0],"A",Y,",",Y," 0 0,",v," ",V[1],"A",n,",",n," 0 ",g^so(V[1][0],V[1][1],Z[1][0],Z[1][1]),",",1-g," ",Z[1],"A",Y,",",Y," 0 0,",v," ",Z[0]):N.push("L",V[0],"A",Y,",",Y," 0 0,",v," ",Z[0])}else N.push("L",_,",",w)}else N.push("M",y,",",M),null!=x&&N.push("A",l,",",l," 0 ",C,",",g," ",x,",",b),N.push("L",_,",",w),null!=S&&N.push("A",n,",",n," 0 ",q,",",1-g," ",S,",",k);return N.push("Z"),N.join("")}function t(n,t){return"M0,"+n+"A"+n+","+n+" 0 1,"+t+" 0,"+-n+"A"+n+","+n+" 0 1,"+t+" 0,"+n}var e=io,r=oo,u=uo,i=kl,o=ao,a=co,c=lo;return n.innerRadius=function(t){return arguments.length?(e=Et(t),n):e},n.outerRadius=function(t){return arguments.length?(r=Et(t),n):r},n.cornerRadius=function(t){return arguments.length?(u=Et(t),n):u},n.padRadius=function(t){return arguments.length?(i=t==kl?kl:Et(t),n):i},n.startAngle=function(t){return arguments.length?(o=Et(t),n):o},n.endAngle=function(t){return arguments.length?(a=Et(t),n):a},n.padAngle=function(t){return arguments.length?(c=Et(t),n):c},n.centroid=function(){var n=(+e.apply(this,arguments)+ +r.apply(this,arguments))/2,t=(+o.apply(this,arguments)+ +a.apply(this,arguments))/2-Ra;return[Math.cos(t)*n,Math.sin(t)*n]},n};var kl="auto";ta.svg.line=function(){return ho(y)};var El=ta.map({linear:go,"linear-closed":po,step:vo,"step-before":mo,"step-after":yo,basis:So,"basis-open":ko,"basis-closed":Eo,bundle:Ao,cardinal:bo,"cardinal-open":Mo,"cardinal-closed":xo,monotone:To});El.forEach(function(n,t){t.key=n,t.closed=/-closed$/.test(n)});var Al=[0,2/3,1/3,0],Nl=[0,1/3,2/3,0],Cl=[0,1/6,2/3,1/6];ta.svg.line.radial=function(){var n=ho(Ro);return n.radius=n.x,delete n.x,n.angle=n.y,delete n.y,n},mo.reverse=yo,yo.reverse=mo,ta.svg.area=function(){return Do(y)},ta.svg.area.radial=function(){var n=Do(Ro);return n.radius=n.x,delete n.x,n.innerRadius=n.x0,delete n.x0,n.outerRadius=n.x1,delete n.x1,n.angle=n.y,delete n.y,n.startAngle=n.y0,delete n.y0,n.endAngle=n.y1,delete n.y1,n},ta.svg.chord=function(){function n(n,a){var c=t(this,i,n,a),l=t(this,o,n,a);return"M"+c.p0+r(c.r,c.p1,c.a1-c.a0)+(e(c,l)?u(c.r,c.p1,c.r,c.p0):u(c.r,c.p1,l.r,l.p0)+r(l.r,l.p1,l.a1-l.a0)+u(l.r,l.p1,c.r,c.p0))+"Z"}function t(n,t,e,r){var u=t.call(n,e,r),i=a.call(n,u,r),o=c.call(n,u,r)-Ra,s=l.call(n,u,r)-Ra;return{r:i,a0:o,a1:s,p0:[i*Math.cos(o),i*Math.sin(o)],p1:[i*Math.cos(s),i*Math.sin(s)]}}function e(n,t){return n.a0==t.a0&&n.a1==t.a1}function r(n,t,e){return"A"+n+","+n+" 0 "+ +(e>qa)+",1 "+t}function u(n,t,e,r){return"Q 0,0 "+r}var i=mr,o=yr,a=Po,c=ao,l=co;return n.radius=function(t){return arguments.length?(a=Et(t),n):a},n.source=function(t){return arguments.length?(i=Et(t),n):i},n.target=function(t){return arguments.length?(o=Et(t),n):o},n.startAngle=function(t){return arguments.length?(c=Et(t),n):c},n.endAngle=function(t){return arguments.length?(l=Et(t),n):l},n},ta.svg.diagonal=function(){function n(n,u){var i=t.call(this,n,u),o=e.call(this,n,u),a=(i.y+o.y)/2,c=[i,{x:i.x,y:a},{x:o.x,y:a},o];return c=c.map(r),"M"+c[0]+"C"+c[1]+" "+c[2]+" "+c[3]}var t=mr,e=yr,r=Uo;return n.source=function(e){return arguments.length?(t=Et(e),n):t},n.target=function(t){return arguments.length?(e=Et(t),n):e},n.projection=function(t){return arguments.length?(r=t,n):r},n},ta.svg.diagonal.radial=function(){var n=ta.svg.diagonal(),t=Uo,e=n.projection;return n.projection=function(n){return arguments.length?e(jo(t=n)):t},n},ta.svg.symbol=function(){function n(n,r){return(zl.get(t.call(this,n,r))||Oo)(e.call(this,n,r))}var t=Ho,e=Fo;return n.type=function(e){return arguments.length?(t=Et(e),n):t},n.size=function(t){return arguments.length?(e=Et(t),n):e},n};var zl=ta.map({circle:Oo,cross:function(n){var t=Math.sqrt(n/5)/2;return"M"+-3*t+","+-t+"H"+-t+"V"+-3*t+"H"+t+"V"+-t+"H"+3*t+"V"+t+"H"+t+"V"+3*t+"H"+-t+"V"+t+"H"+-3*t+"Z"},diamond:function(n){var t=Math.sqrt(n/(2*Ll)),e=t*Ll;return"M0,"+-t+"L"+e+",0 0,"+t+" "+-e+",0Z"},square:function(n){var t=Math.sqrt(n)/2;return"M"+-t+","+-t+"L"+t+","+-t+" "+t+","+t+" "+-t+","+t+"Z"},"triangle-down":function(n){var t=Math.sqrt(n/ql),e=t*ql/2;return"M0,"+e+"L"+t+","+-e+" "+-t+","+-e+"Z"},"triangle-up":function(n){var t=Math.sqrt(n/ql),e=t*ql/2;return"M0,"+-e+"L"+t+","+e+" "+-t+","+e+"Z"}});ta.svg.symbolTypes=zl.keys();var ql=Math.sqrt(3),Ll=Math.tan(30*Da);_a.transition=function(n){for(var t,e,r=Tl||++Ul,u=Xo(n),i=[],o=Rl||{time:Date.now(),ease:Su,delay:0,duration:250},a=-1,c=this.length;++a<c;){i.push(t=[]);for(var l=this[a],s=-1,f=l.length;++s<f;)(e=l[s])&&$o(e,s,u,r,o),t.push(e)}return Yo(i,u,r)},_a.interrupt=function(n){return this.each(null==n?Dl:Io(Xo(n)))};var Tl,Rl,Dl=Io(Xo()),Pl=[],Ul=0;Pl.call=_a.call,Pl.empty=_a.empty,Pl.node=_a.node,Pl.size=_a.size,ta.transition=function(n,t){return n&&n.transition?Tl?n.transition(t):n:ta.selection().transition(n)},ta.transition.prototype=Pl,Pl.select=function(n){var t,e,r,u=this.id,i=this.namespace,o=[];n=N(n);for(var a=-1,c=this.length;++a<c;){o.push(t=[]);for(var l=this[a],s=-1,f=l.length;++s<f;)(r=l[s])&&(e=n.call(r,r.__data__,s,a))?("__data__"in r&&(e.__data__=r.__data__),$o(e,s,i,u,r[i][u]),t.push(e)):t.push(null)}return Yo(o,i,u)},Pl.selectAll=function(n){var t,e,r,u,i,o=this.id,a=this.namespace,c=[];n=C(n);for(var l=-1,s=this.length;++l<s;)for(var f=this[l],h=-1,g=f.length;++h<g;)if(r=f[h]){i=r[a][o],e=n.call(r,r.__data__,h,l),c.push(t=[]);for(var p=-1,v=e.length;++p<v;)(u=e[p])&&$o(u,p,a,o,i),t.push(u)}return Yo(c,a,o)},Pl.filter=function(n){var t,e,r,u=[];"function"!=typeof n&&(n=O(n));for(var i=0,o=this.length;o>i;i++){u.push(t=[]);for(var e=this[i],a=0,c=e.length;c>a;a++)(r=e[a])&&n.call(r,r.__data__,a,i)&&t.push(r)}return Yo(u,this.namespace,this.id)},Pl.tween=function(n,t){var e=this.id,r=this.namespace;return arguments.length<2?this.node()[r][e].tween.get(n):Y(this,null==t?function(t){t[r][e].tween.remove(n)}:function(u){u[r][e].tween.set(n,t)})},Pl.attr=function(n,t){function e(){this.removeAttribute(a)}function r(){this.removeAttributeNS(a.space,a.local)}function u(n){return null==n?e:(n+="",function(){var t,e=this.getAttribute(a);return e!==n&&(t=o(e,n),function(n){this.setAttribute(a,t(n))})})}function i(n){return null==n?r:(n+="",function(){var t,e=this.getAttributeNS(a.space,a.local);return e!==n&&(t=o(e,n),function(n){this.setAttributeNS(a.space,a.local,t(n))})})}if(arguments.length<2){for(t in n)this.attr(t,n[t]);return this}var o="transform"==n?Hu:mu,a=ta.ns.qualify(n);return Zo(this,"attr."+n,t,a.local?i:u)},Pl.attrTween=function(n,t){function e(n,e){var r=t.call(this,n,e,this.getAttribute(u));return r&&function(n){this.setAttribute(u,r(n))}}function r(n,e){var r=t.call(this,n,e,this.getAttributeNS(u.space,u.local));return r&&function(n){this.setAttributeNS(u.space,u.local,r(n))}}var u=ta.ns.qualify(n);return this.tween("attr."+n,u.local?r:e)},Pl.style=function(n,e,r){function u(){this.style.removeProperty(n)}function i(e){return null==e?u:(e+="",function(){var u,i=t(this).getComputedStyle(this,null).getPropertyValue(n);return i!==e&&(u=mu(i,e),function(t){this.style.setProperty(n,u(t),r)})})}var o=arguments.length;if(3>o){if("string"!=typeof n){2>o&&(e="");for(r in n)this.style(r,n[r],e);return this}r=""}return Zo(this,"style."+n,e,i)},Pl.styleTween=function(n,e,r){function u(u,i){var o=e.call(this,u,i,t(this).getComputedStyle(this,null).getPropertyValue(n));return o&&function(t){this.style.setProperty(n,o(t),r)}}return arguments.length<3&&(r=""),this.tween("style."+n,u)},Pl.text=function(n){return Zo(this,"text",n,Vo)},Pl.remove=function(){var n=this.namespace;return this.each("end.transition",function(){var t;this[n].count<2&&(t=this.parentNode)&&t.removeChild(this)})},Pl.ease=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].ease:("function"!=typeof n&&(n=ta.ease.apply(ta,arguments)),Y(this,function(r){r[e][t].ease=n}))},Pl.delay=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].delay:Y(this,"function"==typeof n?function(r,u,i){r[e][t].delay=+n.call(r,r.__data__,u,i)}:(n=+n,function(r){r[e][t].delay=n}))},Pl.duration=function(n){var t=this.id,e=this.namespace;return arguments.length<1?this.node()[e][t].duration:Y(this,"function"==typeof n?function(r,u,i){r[e][t].duration=Math.max(1,n.call(r,r.__data__,u,i))}:(n=Math.max(1,n),function(r){r[e][t].duration=n}))},Pl.each=function(n,t){var e=this.id,r=this.namespace;if(arguments.length<2){var u=Rl,i=Tl;try{Tl=e,Y(this,function(t,u,i){Rl=t[r][e],n.call(t,t.__data__,u,i)})}finally{Rl=u,Tl=i}}else Y(this,function(u){var i=u[r][e];(i.event||(i.event=ta.dispatch("start","end","interrupt"))).on(n,t)});return this},Pl.transition=function(){for(var n,t,e,r,u=this.id,i=++Ul,o=this.namespace,a=[],c=0,l=this.length;l>c;c++){a.push(n=[]);for(var t=this[c],s=0,f=t.length;f>s;s++)(e=t[s])&&(r=e[o][u],$o(e,s,o,i,{time:r.time,ease:r.ease,delay:r.delay+r.duration,duration:r.duration})),n.push(e)}return Yo(a,o,i)},ta.svg.axis=function(){function n(n){n.each(function(){var n,l=ta.select(this),s=this.__chart__||e,f=this.__chart__=e.copy(),h=null==c?f.ticks?f.ticks.apply(f,a):f.domain():c,g=null==t?f.tickFormat?f.tickFormat.apply(f,a):y:t,p=l.selectAll(".tick").data(h,f),v=p.enter().insert("g",".domain").attr("class","tick").style("opacity",Ca),d=ta.transition(p.exit()).style("opacity",Ca).remove(),m=ta.transition(p.order()).style("opacity",1),M=Math.max(u,0)+o,x=Ui(f),b=l.selectAll(".domain").data([0]),_=(b.enter().append("path").attr("class","domain"),ta.transition(b));v.append("line"),v.append("text");var w,S,k,E,A=v.select("line"),N=m.select("line"),C=p.select("text").text(g),z=v.select("text"),q=m.select("text"),L="top"===r||"left"===r?-1:1;if("bottom"===r||"top"===r?(n=Bo,w="x",k="y",S="x2",E="y2",C.attr("dy",0>L?"0em":".71em").style("text-anchor","middle"),_.attr("d","M"+x[0]+","+L*i+"V0H"+x[1]+"V"+L*i)):(n=Wo,w="y",k="x",S="y2",E="x2",C.attr("dy",".32em").style("text-anchor",0>L?"end":"start"),_.attr("d","M"+L*i+","+x[0]+"H0V"+x[1]+"H"+L*i)),A.attr(E,L*u),z.attr(k,L*M),N.attr(S,0).attr(E,L*u),q.attr(w,0).attr(k,L*M),f.rangeBand){var T=f,R=T.rangeBand()/2;s=f=function(n){return T(n)+R}}else s.rangeBand?s=f:d.call(n,f,s);v.call(n,s,f),m.call(n,f,f)})}var t,e=ta.scale.linear(),r=jl,u=6,i=6,o=3,a=[10],c=null;return n.scale=function(t){return arguments.length?(e=t,n):e},n.orient=function(t){return arguments.length?(r=t in Fl?t+"":jl,n):r},n.ticks=function(){return arguments.length?(a=arguments,n):a},n.tickValues=function(t){return arguments.length?(c=t,n):c},n.tickFormat=function(e){return arguments.length?(t=e,n):t},n.tickSize=function(t){var e=arguments.length;return e?(u=+t,i=+arguments[e-1],n):u},n.innerTickSize=function(t){return arguments.length?(u=+t,n):u},n.outerTickSize=function(t){return arguments.length?(i=+t,n):i},n.tickPadding=function(t){return arguments.length?(o=+t,n):o},n.tickSubdivide=function(){return arguments.length&&n},n};var jl="bottom",Fl={top:1,right:1,bottom:1,left:1};ta.svg.brush=function(){function n(t){t.each(function(){var t=ta.select(this).style("pointer-events","all").style("-webkit-tap-highlight-color","rgba(0,0,0,0)").on("mousedown.brush",i).on("touchstart.brush",i),o=t.selectAll(".background").data([0]);o.enter().append("rect").attr("class","background").style("visibility","hidden").style("cursor","crosshair"),t.selectAll(".extent").data([0]).enter().append("rect").attr("class","extent").style("cursor","move");var a=t.selectAll(".resize").data(v,y);a.exit().remove(),a.enter().append("g").attr("class",function(n){return"resize "+n}).style("cursor",function(n){return Hl[n]}).append("rect").attr("x",function(n){return/[ew]$/.test(n)?-3:null}).attr("y",function(n){return/^[ns]/.test(n)?-3:null}).attr("width",6).attr("height",6).style("visibility","hidden"),a.style("display",n.empty()?"none":null);var c,f=ta.transition(t),h=ta.transition(o);l&&(c=Ui(l),h.attr("x",c[0]).attr("width",c[1]-c[0]),r(f)),s&&(c=Ui(s),h.attr("y",c[0]).attr("height",c[1]-c[0]),u(f)),e(f)})}function e(n){n.selectAll(".resize").attr("transform",function(n){return"translate("+f[+/e$/.test(n)]+","+h[+/^s/.test(n)]+")"})}function r(n){n.select(".extent").attr("x",f[0]),n.selectAll(".extent,.n>rect,.s>rect").attr("width",f[1]-f[0])}function u(n){n.select(".extent").attr("y",h[0]),n.selectAll(".extent,.e>rect,.w>rect").attr("height",h[1]-h[0])}function i(){function i(){32==ta.event.keyCode&&(C||(M=null,q[0]-=f[1],q[1]-=h[1],C=2),S())}function v(){32==ta.event.keyCode&&2==C&&(q[0]+=f[1],q[1]+=h[1],C=0,S())}function d(){var n=ta.mouse(b),t=!1;x&&(n[0]+=x[0],n[1]+=x[1]),C||(ta.event.altKey?(M||(M=[(f[0]+f[1])/2,(h[0]+h[1])/2]),q[0]=f[+(n[0]<M[0])],q[1]=h[+(n[1]<M[1])]):M=null),A&&m(n,l,0)&&(r(k),t=!0),N&&m(n,s,1)&&(u(k),t=!0),t&&(e(k),w({type:"brush",mode:C?"move":"resize"}))}function m(n,t,e){var r,u,i=Ui(t),c=i[0],l=i[1],s=q[e],v=e?h:f,d=v[1]-v[0];return C&&(c-=s,l-=d+s),r=(e?p:g)?Math.max(c,Math.min(l,n[e])):n[e],C?u=(r+=s)+d:(M&&(s=Math.max(c,Math.min(l,2*M[e]-r))),r>s?(u=r,r=s):u=s),v[0]!=r||v[1]!=u?(e?a=null:o=null,v[0]=r,v[1]=u,!0):void 0}function y(){d(),k.style("pointer-events","all").selectAll(".resize").style("display",n.empty()?"none":null),ta.select("body").style("cursor",null),L.on("mousemove.brush",null).on("mouseup.brush",null).on("touchmove.brush",null).on("touchend.brush",null).on("keydown.brush",null).on("keyup.brush",null),z(),w({type:"brushend"})}var M,x,b=this,_=ta.select(ta.event.target),w=c.of(b,arguments),k=ta.select(b),E=_.datum(),A=!/^(n|s)$/.test(E)&&l,N=!/^(e|w)$/.test(E)&&s,C=_.classed("extent"),z=W(b),q=ta.mouse(b),L=ta.select(t(b)).on("keydown.brush",i).on("keyup.brush",v);if(ta.event.changedTouches?L.on("touchmove.brush",d).on("touchend.brush",y):L.on("mousemove.brush",d).on("mouseup.brush",y),k.interrupt().selectAll("*").interrupt(),C)q[0]=f[0]-q[0],q[1]=h[0]-q[1];else if(E){var T=+/w$/.test(E),R=+/^n/.test(E);x=[f[1-T]-q[0],h[1-R]-q[1]],q[0]=f[T],q[1]=h[R]}else ta.event.altKey&&(M=q.slice());k.style("pointer-events","none").selectAll(".resize").style("display",null),ta.select("body").style("cursor",_.style("cursor")),w({type:"brushstart"}),d()}var o,a,c=E(n,"brushstart","brush","brushend"),l=null,s=null,f=[0,0],h=[0,0],g=!0,p=!0,v=Ol[0];return n.event=function(n){n.each(function(){var n=c.of(this,arguments),t={x:f,y:h,i:o,j:a},e=this.__chart__||t;this.__chart__=t,Tl?ta.select(this).transition().each("start.brush",function(){o=e.i,a=e.j,f=e.x,h=e.y,n({type:"brushstart"})}).tween("brush:brush",function(){var e=yu(f,t.x),r=yu(h,t.y);return o=a=null,function(u){f=t.x=e(u),h=t.y=r(u),n({type:"brush",mode:"resize"})}}).each("end.brush",function(){o=t.i,a=t.j,n({type:"brush",mode:"resize"}),n({type:"brushend"})}):(n({type:"brushstart"}),n({type:"brush",mode:"resize"}),n({type:"brushend"}))})},n.x=function(t){return arguments.length?(l=t,v=Ol[!l<<1|!s],n):l},n.y=function(t){return arguments.length?(s=t,v=Ol[!l<<1|!s],n):s},n.clamp=function(t){return arguments.length?(l&&s?(g=!!t[0],p=!!t[1]):l?g=!!t:s&&(p=!!t),n):l&&s?[g,p]:l?g:s?p:null},n.extent=function(t){var e,r,u,i,c;return arguments.length?(l&&(e=t[0],r=t[1],s&&(e=e[0],r=r[0]),o=[e,r],l.invert&&(e=l(e),r=l(r)),e>r&&(c=e,e=r,r=c),(e!=f[0]||r!=f[1])&&(f=[e,r])),s&&(u=t[0],i=t[1],l&&(u=u[1],i=i[1]),a=[u,i],s.invert&&(u=s(u),i=s(i)),u>i&&(c=u,u=i,i=c),(u!=h[0]||i!=h[1])&&(h=[u,i])),n):(l&&(o?(e=o[0],r=o[1]):(e=f[0],r=f[1],l.invert&&(e=l.invert(e),r=l.invert(r)),e>r&&(c=e,e=r,r=c))),s&&(a?(u=a[0],i=a[1]):(u=h[0],i=h[1],s.invert&&(u=s.invert(u),i=s.invert(i)),u>i&&(c=u,u=i,i=c))),l&&s?[[e,u],[r,i]]:l?[e,r]:s&&[u,i])},n.clear=function(){return n.empty()||(f=[0,0],h=[0,0],o=a=null),n},n.empty=function(){return!!l&&f[0]==f[1]||!!s&&h[0]==h[1]},ta.rebind(n,c,"on")};var Hl={n:"ns-resize",e:"ew-resize",s:"ns-resize",w:"ew-resize",nw:"nwse-resize",ne:"nesw-resize",se:"nwse-resize",sw:"nesw-resize"},Ol=[["n","e","s","w","nw","ne","se","sw"],["e","w"],["n","s"],[]],Il=ac.format=gc.timeFormat,Yl=Il.utc,Zl=Yl("%Y-%m-%dT%H:%M:%S.%LZ");Il.iso=Date.prototype.toISOString&&+new Date("2000-01-01T00:00:00.000Z")?Jo:Zl,Jo.parse=function(n){var t=new Date(n);return isNaN(t)?null:t},Jo.toString=Zl.toString,ac.second=Ft(function(n){return new cc(1e3*Math.floor(n/1e3))},function(n,t){n.setTime(n.getTime()+1e3*Math.floor(t))},function(n){return n.getSeconds()}),ac.seconds=ac.second.range,ac.seconds.utc=ac.second.utc.range,ac.minute=Ft(function(n){return new cc(6e4*Math.floor(n/6e4))},function(n,t){n.setTime(n.getTime()+6e4*Math.floor(t))},function(n){return n.getMinutes()}),ac.minutes=ac.minute.range,ac.minutes.utc=ac.minute.utc.range,ac.hour=Ft(function(n){var t=n.getTimezoneOffset()/60;return new cc(36e5*(Math.floor(n/36e5-t)+t))},function(n,t){n.setTime(n.getTime()+36e5*Math.floor(t))},function(n){return n.getHours()}),ac.hours=ac.hour.range,ac.hours.utc=ac.hour.utc.range,ac.month=Ft(function(n){return n=ac.day(n),n.setDate(1),n},function(n,t){n.setMonth(n.getMonth()+t)},function(n){return n.getMonth()}),ac.months=ac.month.range,ac.months.utc=ac.month.utc.range;var Vl=[1e3,5e3,15e3,3e4,6e4,3e5,9e5,18e5,36e5,108e5,216e5,432e5,864e5,1728e5,6048e5,2592e6,7776e6,31536e6],Xl=[[ac.second,1],[ac.second,5],[ac.second,15],[ac.second,30],[ac.minute,1],[ac.minute,5],[ac.minute,15],[ac.minute,30],[ac.hour,1],[ac.hour,3],[ac.hour,6],[ac.hour,12],[ac.day,1],[ac.day,2],[ac.week,1],[ac.month,1],[ac.month,3],[ac.year,1]],$l=Il.multi([[".%L",function(n){return n.getMilliseconds()}],[":%S",function(n){return n.getSeconds()}],["%I:%M",function(n){return n.getMinutes()}],["%I %p",function(n){return n.getHours()}],["%a %d",function(n){return n.getDay()&&1!=n.getDate()}],["%b %d",function(n){return 1!=n.getDate()}],["%B",function(n){return n.getMonth()}],["%Y",Ne]]),Bl={range:function(n,t,e){return ta.range(Math.ceil(n/e)*e,+t,e).map(Ko)},floor:y,ceil:y};Xl.year=ac.year,ac.scale=function(){return Go(ta.scale.linear(),Xl,$l)};var Wl=Xl.map(function(n){return[n[0].utc,n[1]]}),Jl=Yl.multi([[".%L",function(n){return n.getUTCMilliseconds()}],[":%S",function(n){return n.getUTCSeconds()}],["%I:%M",function(n){return n.getUTCMinutes()}],["%I %p",function(n){return n.getUTCHours()}],["%a %d",function(n){return n.getUTCDay()&&1!=n.getUTCDate()}],["%b %d",function(n){return 1!=n.getUTCDate()}],["%B",function(n){return n.getUTCMonth()}],["%Y",Ne]]);Wl.year=ac.year.utc,ac.scale.utc=function(){return Go(ta.scale.linear(),Wl,Jl)},ta.text=At(function(n){return n.responseText}),ta.json=function(n,t){return Nt(n,"application/json",Qo,t)},ta.html=function(n,t){return Nt(n,"text/html",na,t)},ta.xml=At(function(n){return n.responseXML}),"function"==typeof define&&define.amd?define(ta):"object"==typeof module&&module.exports&&(module.exports=ta),this.d3=ta}();</script>
+<style type="text/css">.profvis {
+position: relative;
+}
+.profvis * {
+
+-webkit-box-sizing: content-box;
+-moz-box-sizing: content-box;
+box-sizing: content-box;
+}
+.profvis-footer .info-label {
+cursor: default;
+}
+.profvis-panel1 {
+left: 0px;
+top: 23px;
+position: absolute;
+}
+.profvis-panel1-vertical {
+bottom: 0px;
+width: 500px;
+margin-bottom: 20px;
+}
+.profvis-panel1-horizontal {
+height: 378px;
+right: 0px;
+}
+.profvis-panel2 {
+position: absolute;
+right: 0px;
+bottom: 0px;
+}
+.profvis-panel2-vertical {
+top: 23px;
+left: 508px;
+margin-bottom: 20px;
+}
+.profvis-panel2-horizontal {
+left: 0px;
+top: 408px;
+margin-bottom: 20px;
+}
+.profvis-splitbar {
+position: absolute;
+background-color: rgb(224, 224, 224);
+border-color: #ddd;
+border-style: solid;
+background-repeat: no-repeat;
+background-position: center;
+}
+.profvis-splitbar-vertical {
+cursor: col-resize;
+left: 500px;
+width: 8px;
+top: 23px;
+bottom: 0px;
+border-width: 0 1px;
+background-image: url('data:image/png;base64,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');
+}
+.profvis-splitbar-horizontal {
+cursor: row-resize;
+top: 400px;
+height: 8px;
+left: 0px;
+right: 0px;
+border-width: 0px 0;
+background-image: url('data:image/png;base64,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');
+}
+.profvis-status-bar {
+position: absolute;
+padding: 0px 0px;
+top: 0;
+left: 0;
+right: 0;
+height: 22px;
+line-height: 18px;
+border-bottom: 1px solid rgb(196, 201, 204);
+background-color: rgb(248, 249, 248);
+color: #444;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-footer {
+position: absolute;
+padding: 0px 0px;
+bottom: 0px;
+left: 0;
+right: 0;
+height: 19px;
+line-height: 18px;
+border-top: 1px solid rgb(196, 201, 204);
+background-color: rgb(248, 249, 248);
+color: #444;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-status-bar .info-block {
+display: inline-block;
+vertical-align: top;
+width: 140px;
+padding: 2px 11px 2px 11px;
+}
+.profvis-footer .info-block {
+display: inline-block;
+vertical-align: top;
+padding: 1px 11px 1px 11px;
+}
+.profvis-footer .info-block-right {
+display: inline-block;
+vertical-align: top;
+padding: 1px 11px 1px 11px;
+float: right;
+}
+.profvis-status-bar .result-block {
+width: auto;
+cursor: pointer;
+}
+.profvis-status-bar .result-block-active {
+width: auto;
+background: rgb(227, 229, 230);
+}
+.profvis-status-bar .spacing-block {
+display: inline-block;
+width: 25px;
+}
+.profvis-status-bar .separator-block {
+display: inline-block;
+width: 1px;
+text-align: center;
+}
+.profvis-status-bar .separator-block .separator-image {
+width: 2px;
+height: 26px;
+margin-top: -2px;
+}
+.profvis-status-bar .options-button {
+float: right;
+color: #444;
+text-decoration: none;
+cursor: pointer;
+padding: 2px 11px 2px 11px;
+}
+.profvis-options-panel {
+float: left;
+position: absolute;
+right: 0;
+top: 21px;
+padding: 3px 6px;
+border: 1px solid #999;
+background-color: #fff;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+line-height: 170%;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+cursor: pointer;
+}
+.profvis-code {
+position: absolute;
+top: 0px;
+left: 0;
+bottom: 0;
+right: 0;
+overflow-y: auto;
+border: 0px solid #ddd;
+}
+.profvis-flamegraph {
+position: absolute;
+right: 0;
+top: 0;
+bottom: 0;
+left: 0;
+overflow: hidden;
+border: 0px solid #ddd;
+background: rgb(249, 249, 250);
+}
+table.profvis-table {
+border-collapse: collapse;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+width: 100%;
+text-align: left;
+cursor: default;
+}
+table.profvis-table th {
+background-color: rgb(249, 249, 250);
+width: 14%;
+}
+table.profvis-table th.spacing {
+width: 20px;
+}
+table.profvis-table th.filename {
+font-family: monospace;
+padding-left: 10px;
+width: auto;
+}
+table.profvis-table th.percent {
+text-align: center;
+}
+table.profvis-table tr {
+border-top: 1px solid transparent;
+border-bottom: 1px solid transparent;
+vertical-align: top;
+}
+
+table.profvis-table tr.locked > td {
+border-top: 1px solid #444;
+border-bottom: 1px solid #444;
+}
+table.profvis-table tr > td {
+padding-top: 0;
+padding-bottom: 0;
+}
+table.profvis-table tr.active {
+background-color: #fdb;
+}
+table.profvis-table .linenum {
+color: #aaa;
+padding: 0 15px;
+font-family: monospace;
+width: 25px;
+}
+
+table.profvis-table [data-pseudo-content]::before {
+content: attr(data-pseudo-content);
+}
+table.profvis-table .code {
+white-space: pre-wrap;
+margin: 0;
+min-height: 1.25em;
+line-height: 1.25;
+width: auto;
+font-family: monospace;
+background: transparent;
+}
+table.profvis-table .time, table.profvis-table .percent {
+padding: 0 5px;
+text-align: right;
+min-width: 2em;
+max-width: 2em;
+overflow: hidden;
+padding-right: 10px;
+}
+table.profvis-table .memory {
+padding-right: 5px;
+}
+table.profvis-table th.time {
+text-align: center;
+}
+table.profvis-table .memory {
+padding: 0 5px;
+text-align: right;
+min-width: 2em;
+max-width: 4em;
+overflow: hidden;
+padding-right: 10px;
+}
+table.profvis-table .memory-right {
+text-align: left;
+}
+table.profvis-table th.memory {
+text-align: center;
+}
+table.profvis-table .timebar-cell {
+padding-left: 0;
+border-left: 1px solid #444;
+min-width: 3em;
+width: 3em;
+}
+table.profvis-table .timebar-cell > .timebar {
+background-color: #5A5A5A;
+border-radius: 0px 2px 2px 0px;
+line-height: 15px;
+}
+table.profvis-table .membar-left-cell {
+padding-left: 0;
+padding-right: 0;
+border-left: 0px solid black;
+min-width: 0.5em;
+width: 0.5em;
+}
+table.profvis-table .membar-left-cell > .membar {
+background-color: #A7A7A7;
+float: right;
+border-radius: 2px 0px 0px 2px;
+line-height: 15px;
+}
+table.profvis-table .membar-right-cell {
+padding-left: 0;
+border-left: 1px solid black;
+min-width: 1em;
+width: 1em;
+}
+table.profvis-table .membar-right-cell > .membar {
+background-color: #5A5A5A;
+border-radius: 0px 2px 2px 0px;
+line-height: 15px;
+}
+.profvis-flamegraph .background {
+fill: rgb(249, 249, 250);
+}
+.profvis-flamegraph .cell .rect {
+stroke: #000;
+stroke-width: 0.25px;
+fill: #fff;
+}
+.profvis-flamegraph .cell.active .rect {
+stroke-width: 0.75px;
+fill: #ddd;
+}
+.profvis-flamegraph .cell.highlighted .rect {
+fill: #ffc;
+}
+.profvis-flamegraph .cell.highlighted.active .rect {
+fill: #fdb;
+}
+.profvis-flamegraph .cell.output .rect {
+fill: #eef;
+}
+.profvis-flamegraph .cell.gc .rect {
+fill: #ccc;
+}
+.profvis-flamegraph .cell.stacktrace .rect {
+fill: #eee;
+}
+.profvis-flamegraph .cell.stacktrace .profvis-label {
+fill: #666;
+}
+.profvis-flamegraph .cell.locked {
+font-weight: bold;
+}
+.profvis-flamegraph .cell.locked .rect {
+stroke-width: 2px;
+}
+.profvis-flamegraph .cell .profvis-label {
+font-family: monospace;
+font-size: 11px;
+cursor: default;
+}
+.profvis-flamegraph .axis text {
+font: 10px sans-serif;
+}
+.profvis-flamegraph .axis path,
+.profvis-flamegraph .axis line {
+fill: none;
+stroke: #000;
+shape-rendering: crispEdges;
+}
+.profvis-flamegraph .profvis-tooltip rect {
+fill: rgb(249, 249, 250);
+stroke: #000;
+opacity: 0.75;
+stroke-opacity: 0.75;
+stroke-width: 0.5;
+}
+.profvis-flamegraph .profvis-tooltip text {
+text-anchor: middle;
+font-family: monospace;
+font-size: 11px;
+}
+.profvis-infobox {
+position: absolute;
+left: 8px;
+top: 8px;
+opacity: 0.8;
+border-radius: 3px;
+color: #f8f8f8;
+background-color: #333;
+padding: 5px 10px;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+line-height: 100%;
+pointer-events: none;
+min-width: 280px;
+}
+.profvis-infobox table {
+border-collapse: separate;
+border-spacing: 2px;
+}
+.profvis-infobox table td {
+padding: 1px;
+}
+.profvis-infobox .infobox-title {
+font-weight: bold;
+}
+.profvis-message {
+width: 100%;
+height: 100%;
+display: -ms-flexbox;
+display: -webkit-flex;
+display: flex;
+-ms-flex-pack: center;
+-webkit-justify-content: center;
+justify-content: center;
+-ms-flex-align: center;
+-webkit-align-items: center;
+align-items: center;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+}
+.profvis-message div {
+color: #444;
+height: 25%;
+}
+.profvis-treetable {
+top: 0px;
+bottom: 0px;
+left: 0px;
+right: 0px;
+position: absolute;
+margin-top: 23px;
+margin-bottom: 21px;
+margin-right: 0px;
+overflow: hidden;
+font: 10px sans-serif;
+color: #161616;
+font-family: "Lucida Sans", "DejaVu Sans", "Lucida Grande", "Segoe UI", Verdana, Helvetica, sans-serif;
+font-size: 11px;
+overflow-y: auto;
+}
+.profvis-treetable .results {
+width: 100%;
+table-layout: fixed;
+}
+.profvis-treetable th {
+font-weight: normal;
+height: 18px;
+background-color: #F8F9F8;
+border-bottom: solid 1px #E4E4E4;
+border-right: solid 1px #E4E4E4;
+padding-left: 3px;
+padding-right: 3px;
+}
+.profvis-treetable td {
+height: 18px;
+border-bottom: solid 1px #E4E4E4;
+border-right: solid 1px #E4E4E4;
+padding-left: 3px;
+padding-right: 3px;
+overflow: hidden;
+text-overflow: ellipsis;
+}
+.profvis-treetable .action {
+width: 18px;
+}
+.profvis-treetable .memory {
+width: 100px;
+text-align: right;
+}
+.profvis-treetable th {
+cursor: default;
+-webkit-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+overflow: hidden;
+}
+.profvis-treetable th.memory {
+text-align: center;
+}
+.profvis-treetable .time {
+width: 100px;
+text-align: right;
+}
+.profvis-treetable th.time {
+text-align: center;
+}
+.profvis-treetable .count {
+text-align: right;
+}
+.profvis-treetable th.count {
+text-align: center;
+}
+.profvis-treetable th.code-label {
+text-align: left;
+padding-left: 5px;
+}
+.profvis-treetable td.label-pointer {
+cursor: pointer;
+}
+.profvis-treetable .label-text {
+display: inline-block;
+-webkit-user-select: none;
+-khtml-user-select: none;
+-moz-user-select: none;
+-ms-user-select: none;
+user-select: none;
+}
+.profvis-treetable .path {
+text-align: left;
+}
+.profvis-treetable .treetable-expand > div {
+display: inline-block;
+width: 15px;
+}
+.profvis-treetable .treetable-expand > div > div{
+width: 0px;
+height: 0px;
+margin-left: 3px;
+margin-right: 6px;
+border-top: 4px solid transparent;
+border-left: 6px solid #161616;
+border-bottom: 4px solid transparent;
+}
+.profvis-treetable .treetable-collapse > div {
+display: inline-block;
+width: 15px;
+}
+.profvis-treetable .treetable-collapse > div > div {
+width: 0px;
+height: 0px;
+margin-left: 3px;
+margin-right: 6px;
+border-right: 4px solid transparent;
+border-top: 6px solid #161616;
+border-left: 4px solid transparent;
+display: inline-block;
+}
+.profvis-treetable .time-info {
+padding: 0px;
+padding-right: 2px;
+text-align: right;
+}
+.profvis-treetable .timebar {
+width: 0px;
+height: 14px;
+background-color: #5A5A5A;
+float: left;
+border-radius: 2px 2px 2px 2px;
+padding-top: 0px;
+margin-top: 1px;
+}
+.profvis-treetable .timecell {
+padding-top: 2px;
+padding-right: 3px;
+}
+.profvis-treetable .memory-info {
+padding-left: 0px;
+padding-right: 2px;
+text-align: right;
+}
+.profvis-treetable .memory-info-right {
+padding-left: 2px;
+padding-right: 0px;
+text-align: left;
+}
+.profvis-treetable .memory-leftbar-wrapper {
+float: left;
+height: 14px;
+width: 5px;
+}
+.profvis-treetable .memory-leftbar {
+width: 2px;
+height: 14px;
+background-color: #A7A7A7;
+float: right;
+border-radius: 1px 0px 0px 1px;
+}
+.profvis-treetable .memory-rightbar {
+width: 2px;
+float: left;
+height: 14px;
+background-color: #5A5A5A;
+border-radius: 0px 1px 1px 0px;
+}
+.profvis-treetable .memory-cell {
+}
+.profvis-treetable .memory-bar-container {
+margin-right: 3px;
+}
+.profvis-treetable .time-bar-container {
+margin-right: 3px;
+}
+</style>
+<script>/*jshint
+  undef:true,
+  browser:true,
+  devel: true,
+  jquery:true,
+  strict:false,
+  curly:false,
+  indent:2
+*/
+/*global profvis:true, d3, hljs */
+
+profvis = (function() {
+  var profvis = {};
+
+  profvis.render = function(el, message) {
+
+    function generateStatusBarButton(id, caption, active) {
+      var spacerImage = 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAIAAAAUCAYAAACnOeyiAAAAXklEQVR42mNgAIL///8zMYSGhjIDGYIMIiIMvECGMwMDN4M4kFEDUqIIZKwDMdSBjAsghj6Q8QPEMAAy/lOBoQekv4AYKkDGfgZeXl4RICOLQUtLiw3IUAJJMQIZ7AC2tU2tXJxOYgAAAABJRU5ErkJggg==';
+
+      var buttonHtml =
+        '<div id="' + id  + '" class="info-block ' +
+        (active ? 'result-block-active' : 'result-block') +
+        '"><span class="info-label">' + caption + '</span></div>' +
+        '<div class="separator-block"><img class="separator-image" src="' + spacerImage + '"></div>';
+
+      return buttonHtml;
+    }
+
+    function generateStatusBar(el, onToogle) {
+      var $el = $(el);
+
+      el.innerHTML =
+        generateStatusBarButton('flameGraphButton', 'Flame Graph', true) +
+        generateStatusBarButton('treetableButton', 'Data', false) +
+        '<span role="button" class="options-button">Options &#x25BE;</span>';
+
+      $el.find("span.options-button").on("click", function(e) {
+        e.preventDefault();
+        e.stopPropagation();
+
+        vis.optionsPanel.toggleVisibility();
+      });
+
+      var setStatusBarButtons = function(e) {
+        $(".info-block").removeClass("result-block-active");
+        $(".info-block").addClass("result-block");
+        e.addClass("result-block-active");
+      };
+
+      $el.find("#flameGraphButton").on("click", function() {
+        setStatusBarButtons($(this));
+        onToogle("flamegraph");
+      });
+
+      $el.find("#treetableButton").on("click", function() {
+        setStatusBarButtons($(this));
+        onToogle("treetable");
+      });
+
+      return {
+        el: el
+      };
+    }
+
+    function generateFooter(el, onToogle) {
+      var $el = $(el);
+
+      el.innerHTML =
+        '<div class="info-block"><span class="info-label">Sample Interval: ' +
+          vis.interval + 'ms</span></div>' +
+        '<div class="info-block-right">' +
+        // '<span class="info-label" title="Peak memory allocation">' + (Math.round(vis.totalMem * 100) / 100) + 'MB</span>' +
+        // ' / ' +
+        '<span class="info-label" title="Total time">' + vis.totalTime + 'ms</span>' +
+        '</div>';
+
+      return {
+        el: el
+      };
+    }
+
+    function generateOptionsPanel(el, onOptionsChange) {
+      var $el = $(el);
+
+      el.innerHTML =
+        '<div role="button" class="split-horizontal">' +
+          '<span class="options-checkbox" data-checked="1">' +
+          (vis.splitDir === "h" ? '&#x2612;' : '&#x2610;') +
+          '</span> Split horizontally' +
+        '</div>' +
+        '<div role="button" class="hide-internal">' +
+          '<span class="options-checkbox" data-checked="1">&#x2612;</span> Hide internal function calls' +
+        '</div>' +
+        '<div role="button" class="hide-zero-row">' +
+          '<span class="options-checkbox" data-checked="0">&#x2610;</span> Hide lines of code with zero time' +
+        '</div>' +
+        '<div role="button" class="hide-memory">' +
+          '<span class="options-checkbox" data-checked="0">&#x2610;</span> Hide memory results' +
+        '</div>';
+
+      // Toggle the appearance of a checkbox and return the new checked state.
+      function toggleCheckbox($checkbox) {
+        // Use attr() instead of data(), because the latter tries to coerce to
+        // numbers, which complicates our comparisons.
+        var checked = $checkbox.attr("data-checked");
+
+        if (checked === "0") {
+          $checkbox.attr("data-checked", "1");
+          $checkbox.html("&#x2612;");
+          return true;
+
+        } else {
+          $checkbox.attr("data-checked", "0");
+          $checkbox.html("&#x2610;");
+          return false;
+        }
+      }
+
+      $el.find(".split-horizontal")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("split", checked);
+        });
+
+      $el.find(".hide-internal")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("internals", checked);
+        });
+
+      $el.find(".hide-memory")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+          onOptionsChange("memory", checked);
+        });
+
+      // Make the "hide internal" option available or unavailable to users
+      function enableHideInternal() {
+        $el.find(".hide-internal").css("display", "");
+      }
+      function disableHideInternal() {
+        $el.find(".hide-internal").css("display", "none");
+      }
+      // By default, start with it unavailable; it's only relevant for Shiny
+      // apps.
+      disableHideInternal();
+
+
+      $el.find(".hide-zero-row")
+        .on("click", function() {
+          var checked = toggleCheckbox($(this).find(".options-checkbox"));
+
+          if (checked) {
+            vis.codeTable.hideZeroTimeRows();
+          } else {
+            vis.codeTable.showZeroTimeRows();
+          }
+        });
+
+      el.style.visibility = "hidden";
+      function toggleVisibility(offset) {
+        if (el.style.visibility === "visible") {
+          el.style.visibility = "hidden";
+        } else {
+          el.style.visibility = "visible";
+          $(document).on("click", hideOnClickOutside);
+        }
+      }
+
+      // Hide the panel when a click happens outside. This handler also removes
+      // itself after it fires.
+      function hideOnClickOutside(e) {
+        var $el = $(el);
+        if (!$el.is(e.target) && $el.has(e.target).length === 0) {
+          el.style.visibility = "hidden";
+          // Unregister this event listener
+          $(document).off("click", hideOnClickOutside);
+        }
+      }
+
+      return {
+        el: el,
+        toggleVisibility: toggleVisibility,
+        enableHideInternal: enableHideInternal,
+        disableHideInternal: disableHideInternal
+      };
+    }
+
+    function notifySourceFileMessage(d, details) {
+      if (window.parent.postMessage) {
+        window.parent.postMessage({
+          source: "profvis",
+          message: "sourcefile",
+          file: d.filename,
+          normpath: d.normpath ? d.normpath : getNormPath(vis.files, d.filename),
+          line: d.linenum,
+          details: details
+        }, window.location.origin);
+      }
+    }
+
+    function roundOneDecimalNum(number, decimals) {
+      return Math.round(number * 10) / 10;
+    }
+
+    function roundOneDecimal(number, decimals) {
+      if (!number) return 0;
+      return roundOneDecimalNum(number).toFixed(1);
+    }
+
+    // Generate the code table ----------------------------------------
+    function generateCodeTable(el) {
+      var useMemory = false;
+      var content = d3.select(el);
+
+      if (vis.fileLineStats.length === 0) {
+        content.append("div")
+          .attr("class", "profvis-message")
+          .append("div")
+            .text("(Sources not available)");
+      }
+
+      // One table for each file
+      var tables = content.selectAll("table")
+          .data(vis.fileLineStats)
+        .enter()
+          .append("table")
+          .attr("class", "profvis-table");
+
+      // Table headers
+      var headerRows = tables.append("tr");
+      headerRows.append("th")
+        .attr("colspan", "2")
+        .attr("class", "filename")
+        .text(function(d) { return d.filename; });
+
+      var percentTooltip = "Percentage of tracked execution time";
+      var percentMemTooltip = "Percentage of peak memory deallocation and allocation";
+
+      headerRows.append("th")
+        .attr("class", "table-memory memory")
+        .attr("colspan", "4")
+        .text("Memory");
+
+      headerRows.append("th")
+        .attr("class", "time")
+        .attr("colspan", "2")
+        .text("Time");
+
+      headerRows.append("th")
+        .attr("class", "spacing")
+        .attr("data-pseudo-content", "\u00a0");
+
+      // Insert each line of code
+      var rows = tables.selectAll("tr.code-row")
+          .data(function(d) { return d.lineData; })
+        .enter()
+          .append("tr")
+          .attr("class", "code-row");
+
+      // Use pseudo-content and CSS content rule to make text unselectable and
+      // uncopyable. See https://danoc.me/blog/css-prevent-copy/
+      rows.append("td")
+        .attr("class", "linenum")
+        .attr("data-pseudo-content", function(d) { return d.linenum; });
+
+      rows.append("td")
+        .attr("class", "code r")
+        .text(function(d) { return d.content; })
+        .each(function() { hljs.highlightElement(this); });
+
+      rows.append("td")
+        .attr("class", "table-memory memory")
+        .attr("title", "Memory deallocation (MB)")
+        .attr("data-pseudo-content",
+              function(d) { return roundOneDecimalNum(d.sumMemDealloc) !== 0 ? roundOneDecimal(d.sumMemDealloc) : ""; });
+
+      rows.append("td")
+        .attr("class", "table-memory membar-left-cell")
+        .append("div")
+          .attr("class", "membar")
+          .attr("title", percentMemTooltip)
+          .style("width", function(d) {
+            var p = Math.min(Math.abs(Math.min(Math.round(d.propMemDealloc * 100), 0)), 100);
+
+            // 8% is the minimal size that looks visually appealing while drawing an almost empty bar
+            p = roundOneDecimalNum(d.sumMemDealloc) !== 0 ? Math.max(p, 8) : 0;
+            return p + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "table-memory membar-right-cell")
+        .append("div")
+          .attr("class", "membar")
+          .attr("title", percentMemTooltip)
+          .style("width", function(d) {
+            var p = Math.min(Math.max(Math.round(d.propMemAlloc * 100), 0), 100);
+
+            // 4% is the minimal size that looks visually appealing while drawing an almost empty bar
+            p = roundOneDecimalNum(d.sumMemAlloc) !== 0 ? Math.max(p, 4) : 0;
+            return p + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "table-memory memory memory-right")
+        .attr("title", "Memory allocation (MB)")
+        .attr("data-pseudo-content",
+              function(d) { return roundOneDecimalNum(d.sumMemAlloc) !== 0 ? roundOneDecimal(d.sumMemAlloc) : ""; });
+
+      rows.append("td")
+        .attr("class", "time")
+        .attr("title", "Total time (ms)")
+        .attr("data-pseudo-content",
+              function(d) { return Math.round(d.sumTime * 100) !== 0 ? (Math.round(d.sumTime * 100) / 100) : ""; });
+
+      rows.append("td")
+        .attr("class", "timebar-cell")
+        .append("div")
+          .attr("class", "timebar")
+          .attr("title", percentTooltip)
+          .style("width", function(d) {
+            return Math.round(d.propTime * 100) + "%";
+          })
+          // Add the equivalent of &nbsp; to be added with CSS content
+          .attr("data-pseudo-content", "\u00a0");
+
+      rows.append("td")
+        .attr("class", "spacing")
+        .attr("data-pseudo-content", "\u00a0");
+
+      rows
+        .on("click", function(d) {
+          // Info box is only relevant when mousing over flamegraph
+          vis.infoBox.hide();
+          highlighter.click(d);
+          notifySourceFileMessage(d, "select");
+        })
+        .on("mouseover", function(d) {
+          if (highlighter.isLocked()) return;
+
+          // Info box is only relevant when mousing over flamegraph
+          vis.infoBox.hide();
+          highlighter.hover(d);
+        })
+        .on("mouseout", function(d) {
+          if (highlighter.isLocked()) return;
+
+          highlighter.hover(null);
+        })
+        .on("dblclick", function(d) {
+          notifySourceFileMessage(d, "open");
+        });
+
+      function hideZeroTimeRows() {
+        rows
+          .filter(function(d) { return d.sumTime === 0; })
+          .style("display", "none");
+      }
+
+      function showZeroTimeRows() {
+        rows
+          .filter(function(d) { return d.sumTime === 0; })
+          .style("display", "");
+      }
+
+      function addLockHighlight(d) {
+        var target = d;
+        rows
+          .filter(function(d) { return d === target; } )
+          .classed({ locked: true });
+      }
+
+      function clearLockHighlight() {
+        rows
+          .filter(".locked")
+          .classed({ locked: false });
+      }
+
+      function addActiveHighlight(d) {
+        // If we have filename and linenum, search for cells that match, and
+        // set them as "active".
+        var target = d;
+        if (target.filename && target.linenum) {
+          var tr = rows
+            .filter(function(d) {
+              return d.linenum === target.linenum &&
+                     d.filename === target.filename;
+            })
+            .classed({ active: true });
+
+          tr.node().scrollIntoViewIfNeeded();
+        }
+      }
+
+      function clearActiveHighlight() {
+        rows
+          .filter(".active")
+          .classed({ active: false });
+      }
+
+      function enableScroll() {
+        // TODO: implement this
+      }
+
+      function disableScroll() {
+      }
+
+      function useMemoryResults() {
+        d3.selectAll(".table-memory").style("display", vis.hideMemory ? "none" : "");
+      }
+
+      return {
+        el: el,
+        hideZeroTimeRows: hideZeroTimeRows,
+        showZeroTimeRows: showZeroTimeRows,
+        addLockHighlight: addLockHighlight,
+        clearLockHighlight: clearLockHighlight,
+        addActiveHighlight: addActiveHighlight,
+        clearActiveHighlight: clearActiveHighlight,
+        enableScroll: enableScroll,
+        disableScroll: disableScroll,
+        useMemoryResults: useMemoryResults
+      };
+    }
+
+
+    var highlighter = (function() {
+      // D3 data objects for the currently locked and active items
+      var lockItem = null;
+      var activeItem = null;
+
+      function isLocked() {
+        return lockItem !== null;
+      }
+
+      function currentLock() {
+        return lockItem;
+      }
+
+      function currentActive() {
+        return activeItem;
+      }
+
+
+      // This is called when a flamegraph cell or a line of code is clicked on.
+      // Clicks also should trigger hover events.
+      function click(d) {
+        // If d is null (background is clicked), or if locked and this click
+        // is on the currently locked selection, just unlock and return.
+        if (d === null || (lockItem && d === lockItem)) {
+          lockItem = null;
+          vis.flameGraph.clearLockHighlight();
+          vis.codeTable.clearLockHighlight();
+          return;
+        }
+
+        // If nothing currently locked, or if locked and this click is on
+        // something other than the currently locked selection, then lock the
+        // current selection.
+        lockItem = d;
+
+        vis.flameGraph.clearLockHighlight();
+        vis.codeTable.clearLockHighlight();
+        hover(null);
+
+        vis.flameGraph.addLockHighlight(d);
+        vis.codeTable.addLockHighlight(d);
+        hover(d);
+      }
+
+
+      function hover(d) {
+        activeItem = d;
+
+        if (activeItem) {
+          vis.flameGraph.addActiveHighlight(activeItem);
+          vis.codeTable.addActiveHighlight(activeItem);
+          return;
+        }
+
+        vis.flameGraph.clearActiveHighlight();
+        vis.codeTable.clearActiveHighlight();
+      }
+
+      return {
+        isLocked: isLocked,
+        currentLock: currentLock,
+        currentActive: currentActive,
+
+        click: click,
+        hover: hover
+      };
+    })();
+
+
+    // Generate the flame graph -----------------------------------------------
+    function generateFlameGraph(el) {
+      el.innerHTML = "";
+
+      var stackHeight = 15;   // Height of each layer on the stack, in pixels
+      var zoomMargin = 0.02;  // Extra margin on sides when zooming to fit
+
+      // Dimensions -----------------------------------------------------------
+
+      // Margin inside the svg where the plotting occurs
+      var dims = {
+        margin: { top: 0, right: 0, left: 0, bottom: 30 }
+      };
+      dims.width = el.clientWidth - dims.margin.left - dims.margin.right;
+      dims.height = el.clientHeight - dims.margin.top - dims.margin.bottom;
+
+      var domains = {
+        x: [
+          d3.min(vis.prof, function(d) { return d.startTime; }),
+          d3.max(vis.prof, function(d) { return d.endTime; })
+        ],
+        y: [
+          d3.min(vis.prof, function(d) { return d.depth; }) - 1,
+          d3.max(vis.prof, function(d) { return d.depth; })
+        ]
+      };
+      // Slightly expand x domain
+      domains.x = expandRange(domains.x, zoomMargin);
+
+      // Scales ---------------------------------------------------------------
+      var scales = {
+        x: d3.scale.linear()
+            .domain(domains.x)
+            .range([0, dims.width]),
+
+        y: d3.scale.linear()
+            .domain(domains.y)
+            .range([dims.height, dims.height - (domains.y[1] - domains.y[0]) * stackHeight]),
+
+        // This will be a function that, given a data point, returns the depth.
+        // This function can change; sometimes it returns the original depth,
+        // and sometimes it returns the collapsed depth. This isn't exactly a
+        // scale function, but it's close enough for our purposes.
+        getDepth: null
+      };
+
+      function useCollapsedDepth() {
+        scales.getDepth = function(d) { return d.depthCollapsed; };
+      }
+      function useUncollapsedDepth() {
+        scales.getDepth = function(d) { return d.depth; };
+      }
+
+      useCollapsedDepth();
+
+      // SVG container objects ------------------------------------------------
+      var svg = d3.select(el).append('svg');
+
+      var clipRect = svg.append("clipPath")
+          .attr("id", "clip-" + vis.el.id)
+        .append("rect");
+
+      var container = svg.append('g')
+        .attr("transform", "translate(" + dims.margin.left + "," + dims.margin.top + ")")
+        .attr("clip-path", "url(" + urlNoHash() + "#clip-" + vis.el.id + ")");
+
+      // Add a background rect so we have something to grab for zooming/panning
+      var backgroundRect = container.append("rect")
+        .attr("class", "background");
+
+      // Axes ------------------------------------------------------------
+      var xAxis = d3.svg.axis()
+        .scale(scales.x)
+        .orient("bottom");
+
+      svg.append("g")
+        .attr("class", "x axis")
+        .call(xAxis);
+
+      // Container sizing -----------------------------------------------------
+      // Update dimensions of various container elements, based on the overall
+      // dimensions of the containing div.
+      function updateContainerSize() {
+        dims.width = el.clientWidth - dims.margin.left - dims.margin.right;
+        dims.height = el.clientHeight - dims.margin.top - dims.margin.bottom;
+
+        svg
+          .attr('width', dims.width + dims.margin.left + dims.margin.right)
+          .attr('height', dims.height + dims.margin.top + dims.margin.bottom);
+
+        clipRect
+          .attr("x", dims.margin.left)
+          .attr("y", dims.margin.top)
+          .attr("width", dims.width)
+          .attr("height", dims.height);
+
+        backgroundRect
+          .attr("width", dims.width)
+          .attr("height", dims.height);
+
+        svg.select(".x.axis")
+          .attr("transform", "translate(" + dims.margin.left + "," + dims.height + ")");
+      }
+
+
+      // Redrawing ------------------------------------------------------------
+
+      // Redrawing is a little complicated. For performance reasons, the
+      // flamegraph cells that are offscreen aren't rendered; they're removed
+      // from the D3 selection of cells. However, when transitions are
+      // involved, it may be necssary to add objects in their correct
+      // off-screen starting locations before the transition, and then do the
+      // transition. Similarly, it may be necssary to transition objects to
+      // their correct off-screen ending positions.
+      //
+      // In order to handle this, whenever there's a transition, we need to
+      // have the scales for before the transition, and after. When a function
+      // invokes a transition, it will generally do the following: (1) save the
+      // previous scales, (2) modify the current scales, (3) call a redraw
+      // function. The redraw functions are customized for different types of
+      // transitions, and they will use the saved previous scales to position
+      // objects correctly for the transition. When there's no transition, the
+      // previous scales aren't needed, and the redrawImmediate() function
+      // should be used.
+
+      // Cache cells for faster access (avoid a d3.select())
+      var cells;
+
+      // For a data element, return identifying key
+      function dataKey(d) {
+        return d.depth + "-" + d.startTime + "-" + d.endTime;
+      }
+
+      // For transitions with animation, we need to have a copy of the previous
+      // scales in addition to the current ones.
+      var prevScales = {};
+      function savePrevScales() {
+        prevScales = {
+          x:        scales.x.copy(),
+          y:        scales.y.copy(),
+          getDepth: scales.getDepth
+        };
+      }
+      savePrevScales();
+
+
+      // Returns a D3 selection of the cells that are within the plotting
+      // region, using a set of scales.
+      function selectActiveCells(scales) {
+        var xScale = scales.x;
+        var yScale = scales.y;
+        var depth = scales.getDepth;
+        var width = dims.width;
+        var height = dims.height;
+
+        var data = vis.prof.filter(function(d) {
+          var depthVal = depth(d);
+          return !(xScale(d.endTime)    < 0      ||
+                   xScale(d.startTime)  > width  ||
+                   depthVal           === null   ||
+                   yScale(depthVal - 1) < 0      ||
+                   yScale(depthVal)     > height);
+        });
+
+        cells = container.selectAll("g.cell").data(data, dataKey);
+
+        return cells;
+      }
+
+      // Given an enter selection, add the rect and text objects, but don't
+      // position them. Returns a selection of the new <g> elements.
+      // This should usually be called with addItems(sel.enter()) instead
+      // of sel.enter().call(addItems), because the latter returns the original
+      // enter selection, not the selection of <g> elements, and can't be
+      // used for chaining more function calls on the <g> selection.
+      function addItems(enterSelection) {
+        var cells = enterSelection.append("g")
+          .attr("class", "cell")
+          .classed("highlighted", function(d) { return d.filename !== null; })
+          .call(addMouseEventHandlers);
+
+        // Add CSS classes for highlighting cells with labels that match particular
+        // regex patterns.
+        var highlightPatterns = d3.entries(message.highlight);
+        highlightPatterns.map(function(item) {
+          var cssClass = item.key;
+          var regexp = new RegExp(item.value);
+
+          cells.classed(cssClass, function(d) {
+            return d.label.search(regexp) !== -1;
+          });
+        });
+
+        cells.append("rect")
+          .attr("class", "rect");
+
+        cells.append("text")
+          .attr("class", "profvis-label")
+          .text(function(d) { return d.label; });
+
+        return cells;
+      }
+
+      // Given a selection, position the rects and labels, using a set of
+      // scales.
+      function positionItems(cells, scales) {
+        var xScale = scales.x;
+        var yScale = scales.y;
+        var depth = scales.getDepth;
+
+        cells.select("rect")
+          .attr("width", function(d) {
+            return xScale(d.endTime) - xScale(d.startTime);
+          })
+          .attr("height", yScale(0) - yScale(1))
+          .attr("x", function(d) { return xScale(d.startTime); })
+          .attr("y", function(d) { return yScale(depth(d)); });
+
+        cells.select("text")
+          .attr("x", function(d) {
+            // To place the labels, check if there's enough space to fit the
+            // label plus padding in the rect. (We already know the label fits
+            // without padding if we got here.)
+            // * If there's not enough space, simply center the label in the
+            //   rect.
+            // * If there is enough space, keep the label within the rect, with
+            //   padding. Try to left-align, keeping the label within the
+            //   viewing area if possible.
+
+            // Padding on left and right
+            var pad = 2;
+
+            var textWidth = getLabelWidth(this, d.label.length);
+            var rectWidth = xScale(d.endTime) - xScale(d.startTime);
+
+            if (textWidth + pad*2 > rectWidth) {
+              return xScale(d.startTime) + (rectWidth - textWidth) / 2;
+            } else {
+              return Math.min(
+                Math.max(0, xScale(d.startTime)) + pad,
+                xScale(d.endTime) - textWidth - pad
+              );
+            }
+          })
+          .attr("y", function(d) { return yScale(depth(d) - 0.8); });
+
+        return cells;
+      }
+
+
+      // Redraw without a transition (regular panning and zooming)
+      function redrawImmediate() {
+        cells = selectActiveCells(scales);
+
+        cells.exit().remove();
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive());
+        cells.call(positionItems, scales);
+        cells.select('text')
+          .call(updateLabelVisibility);
+        svg.select(".x.axis").call(xAxis);
+      }
+
+      // Redraw for double-click zooming, where there's a transition
+      function redrawZoom(duration) {
+        // Figure out if we're zooming in or out. This will determine when we
+        // recalculate the label visibility: before or after the transition.
+        var prevExtent = prevScales.x.domain()[1] - prevScales.x.domain()[0];
+        var curExtent = scales.x.domain()[1] - scales.x.domain()[0];
+        var zoomIn = curExtent < prevExtent;
+
+        cells = selectActiveCells(scales);
+
+        // Phase 1
+        // Add the enter items, highlight them, and position them using the
+        // previous scales
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        // If zooming out, update label visibility. This will hide some labels
+        // now, before the transition, ensuring that they will never be larger
+        // than the box.
+        if (!zoomIn) {
+          cells.select('text')
+            .call(updateLabelVisibility);
+        }
+
+        // Phase 2
+        // Position the update (and enter) items using the new scales
+        cells
+          .transition().duration(duration)
+            .call(positionItems, scales);
+
+        // Position the exit items using the new scales
+        cells.exit()
+          .transition().duration(duration)
+            .call(positionItems, scales);
+
+        // Update x axis
+        svg.select(".x.axis")
+          .transition().duration(duration)
+            .call(xAxis);
+
+        // Phase 3
+        // If zooming in, update label visibility. This will hide some labels
+        // now, after the transition, ensuring that they will never be larger
+        // than the box.
+        if (zoomIn) {
+          cells.select('text')
+            .transition().delay(duration)
+            .call(updateLabelVisibility);
+        }
+
+        // Remove the exit items
+        cells.exit()
+          .transition().delay(duration)
+            .remove();
+      }
+
+      // Redraw when internal functions are hidden
+      function redrawCollapse(exitDuration, updateDuration) {
+        cells = selectActiveCells(scales);
+
+        // There are two subsets of the exit items:
+        //   1. Those that exit because depth is null. These should fade out.
+        //   2. Those that exit because they move off screen. These should wait
+        //      for subset 1 to fade out, then move with a transition.
+        var fadeOutCells = cells.exit()
+          .filter(function(d) { return scales.getDepth(d) === null; });
+        var moveOutCells = cells.exit()
+          .filter(function(d) { return scales.getDepth(d) !== null; });
+
+        // Phase 1
+        // Add the enter items, highlight them, and position them using the
+        // previous scales
+        addItems(cells.enter())
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        cells.select('text')
+          .call(updateLabelVisibility);
+
+        // Phase 2
+        // Fade out the items that have a null depth
+        fadeOutCells
+          .transition().duration(exitDuration)
+            .style("opacity", 0);
+
+        // Phase 3
+        // Position the update (and enter) items using the new scales
+        cells
+          .transition().delay(exitDuration).duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Position the exit items that move out, using the new scales
+        moveOutCells
+          .transition().delay(exitDuration).duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Phase 4
+        // Remove all the exit items
+        cells.exit()
+          .transition().delay(exitDuration + updateDuration)
+          .remove();
+      }
+
+      // Redraw when internal functions are un-hidden
+      function redrawUncollapse(updateDuration, enterDuration) {
+        cells = selectActiveCells(scales);
+
+        var enterCells = addItems(cells.enter());
+        // There are two subsets of the enter items:
+        //   1. Those that enter because they move on screen (but the previous
+        //      depth was not null). These should move with a transition.
+        //   2. Those that enter because the previous depth was null. These
+        //      should wait for subset 1 to move, then fade in.
+        var moveInCells = enterCells
+          .filter(function(d) { return prevScales.getDepth(d) !== null; });
+        var fadeInCells = enterCells
+          .filter(function(d) { return prevScales.getDepth(d) === null; });
+
+        // Phase 1
+        // Highlight and position the move-in items with the old scales
+        moveInCells
+          .call(addLockHighlightSelection, highlighter.currentLock())
+          .call(addActiveHighlightSelection, highlighter.currentActive())
+          .call(positionItems, prevScales);
+
+        cells.select('text')
+          .call(updateLabelVisibility);
+
+        // Phase 2
+        // Position the move-in, update, and exit items with a transition
+        moveInCells
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+        cells
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+        cells.exit()
+          .transition().duration(updateDuration)
+            .call(positionItems, scales);
+
+        // Phase 3
+        // Highlight and position the fade-in items, then fade in
+        fadeInCells
+            .call(addLockHighlightSelection, highlighter.currentLock())
+            .call(addActiveHighlightSelection, highlighter.currentActive())
+            .call(positionItems, scales)
+            .style("opacity", 0)
+          .transition().delay(updateDuration).duration(enterDuration)
+            .style("opacity", 1);
+
+        // Phase 4
+        // Remove the exit items
+        cells.exit()
+          .transition().delay(updateDuration + enterDuration)
+            .remove();
+      }
+
+
+      // Calculate whether to display label in each cell ----------------------
+
+      // Finding the dimensions of SVG elements is expensive. We'll reduce the
+      // calls getBoundingClientRect() by caching the dimensions.
+
+      // Cache the width of labels. This is a lookup table which, given the
+      // number of characters, gives the number of pixels. The label width
+      // never changes, so we can keep it outside of updateLabelVisibility().
+      var labelWidthTable = {};
+      function getLabelWidth(el, nchar) {
+        // Add entry if it doesn't already exist
+        if (labelWidthTable[nchar] === undefined) {
+          // If the text isn't displayed, then we can't get its width. Make
+          // sure it's visible, get the width, and then restore original
+          // display state.
+          var oldDisplay = el.style.display;
+          el.style.display = "inline";
+          labelWidthTable[nchar] = el.getBoundingClientRect().width;
+          el.style.display = oldDisplay;
+        }
+        return labelWidthTable[nchar];
+      }
+
+      // Show labels that fit in the corresponding rectangle, and hide others.
+      function updateLabelVisibility(labels) {
+        // Cache the width of rects. This is a lookup table which, given the
+        // timespan (width in data), gives the number of pixels. The width of
+        // rects changes with the x scale, so we have to rebuild the table each
+        // time the scale changes.
+        var rectWidthTable = {};
+        var x0 = scales.x(0);
+        function getRectWidth(time) {
+          // Add entry if it doesn't already exist
+          if (rectWidthTable[time] === undefined) {
+            rectWidthTable[time] = scales.x(time) - x0;
+          }
+          return rectWidthTable[time];
+        }
+
+        // Now calculate text and rect width for each cell.
+        labels.style("display", function(d) {
+          var labelWidth = getLabelWidth(this, d.label.length);
+          var boxWidth = getRectWidth(d.endTime - d.startTime);
+
+          return (labelWidth <= boxWidth) ? "" : "none";
+        });
+
+        return labels;
+      }
+
+
+      function onResize() {
+        updateContainerSize();
+
+        scales.x.range([0, dims.width]);
+        zoom.x(scales.x);
+
+        // Preserve distance from bottom, instead of from top (which is the
+        // default behavior).
+        scales.y.range([
+          dims.height,
+          dims.height - (domains.y[1] - domains.y[0]) * stackHeight
+        ]);
+        redrawImmediate();
+      }
+
+      // Attach mouse event handlers ------------------------------------
+      var dragging = false;
+
+      function addMouseEventHandlers(cells) {
+        cells
+          .on("mouseup", function(d) {
+            if (dragging) return;
+
+            // If it wasn't a drag, treat it as a click
+            vis.infoBox.show(d);
+            highlighter.click(d);
+            notifySourceFileMessage(d, "select");
+          })
+          .on("mouseover", function(d) {
+            if (dragging) return;
+
+            // If no label currently shown, display a tooltip
+            var label = this.querySelector(".profvis-label");
+            if (label.style.display === "none") {
+              var box = this.getBBox();
+              showTooltip(
+                d.label,
+                box.x + box.width / 2,
+                box.y - box.height
+              );
+            }
+
+            if (!highlighter.isLocked()) {
+              vis.infoBox.show(d);
+              highlighter.hover(d);
+            }
+          })
+          .on("mouseout", function(d) {
+            if (dragging) return;
+
+            hideTooltip();
+
+            if (!highlighter.isLocked()) {
+              vis.infoBox.hide();
+              highlighter.hover(null);
+            }
+          })
+          .on("dblclick.zoomcell", function(d) {
+            // When a cell is double-clicked, zoom x to that cell's width.
+            savePrevScales();
+
+            scales.x.domain(expandRange([d.startTime, d.endTime], zoomMargin));
+            zoom.x(scales.x);
+
+            redrawZoom(250);
+
+            notifySourceFileMessage(d, "open");
+          });
+
+        return cells;
+      }
+
+      // Tooltip --------------------------------------------------------
+      function showTooltip(label, x, y) {
+        var tooltip = container.append("g").attr("class", "profvis-tooltip");
+        var tooltipRect = tooltip.append("rect");
+        var tooltipLabel = tooltip.append("text")
+          .text(label)
+          .attr("x", x)
+          .attr("y", y + stackHeight * 0.2); // Shift down slightly for baseline
+
+        // Add box around label
+        var labelBox = tooltipLabel.node().getBBox();
+        var rectWidth = labelBox.width + 10;
+        var rectHeight = labelBox.height + 4;
+        tooltipRect
+          .attr("width", rectWidth)
+          .attr("height", rectHeight)
+          .attr("x", x - rectWidth / 2)
+          .attr("y", y - rectHeight / 2)
+          .attr("rx", 4)    // Rounded corners -- can't set this in CSS
+          .attr("ry", 4);
+      }
+
+      function hideTooltip() {
+        container.select("g.profvis-tooltip").remove();
+      }
+
+
+      // Highlighting ---------------------------------------------------------
+
+      function addLockHighlight(d) {
+        addLockHighlightSelection(cells, d);
+      }
+
+      function clearLockHighlight() {
+        cells
+          .filter(".locked")
+          .classed({ locked: false });
+      }
+
+
+      function addActiveHighlight(d) {
+        if (!d) return;
+        addActiveHighlightSelection(cells, d);
+      }
+
+      function clearActiveHighlight() {
+        cells
+          .filter(".active")
+          .classed({ active: false });
+      }
+
+      // These are versions of addLockHighlight and addActiveHighlight which
+      // are only internally visible. It must be passed a selection of cells to
+      // perform the highlighting on. This can be more efficient because it can
+      // operate on just an enter selection instead of all cells.
+      function addLockHighlightSelection(selection, d) {
+        if (!d) return;
+
+        var target = d;
+        selection
+          .filter(function(d) { return d === target; } )
+          .classed({ locked: true })
+          .call(moveToFront);
+      }
+
+      function addActiveHighlightSelection(selection, d) {
+        if (!d) return;
+
+        var target = d;
+        if (target.filename && target.linenum) {
+          selection
+            .filter(function(d) {
+              // Check for filename and linenum match, and if provided, a label match.
+              var match = d.filename === target.filename &&
+                          d.linenum === target.linenum;
+              if (!!target.label) {
+                match = match && (d.label === target.label);
+              }
+              return match;
+            })
+            .classed({ active: true });
+
+        } else if (target.label) {
+          // Don't highlight blocks for these labels
+          var exclusions = ["<Anonymous>", "FUN"];
+          if (exclusions.some(function(x) { return target.label === x; })) {
+            return;
+          }
+
+          // If we only have the label, search for cells that match, but make sure
+          // to not select ones that have a filename and linenum.
+          selection
+            .filter(function(d) {
+              return d.label === target.label &&
+                     d.filename === null &&
+                     d.linenum === null;
+            })
+            .classed({ active: true });
+        }
+      }
+
+      // Move a D3 selection to front. If this is called on a selection, that
+      // selection should have been created with a data indexing function (e.g.
+      // data(data, function(d) { return ... })). Otherwise, the wrong object
+      // may be moved to the front.
+      function moveToFront(selection) {
+        return selection.each(function() {
+          this.parentNode.appendChild(this);
+        });
+      }
+
+
+      // Panning and zooming --------------------------------------------
+      // For panning and zooming x, d3.behavior.zoom does most of what we want
+      // automatically. For panning y, we can't use d3.behavior.zoom becuase it
+      // will also automatically add zooming, which we don't want. Instead, we
+      // need to use d3.behavior.drag and set the y domain appropriately.
+      var drag = d3.behavior.drag()
+        .on("drag", function() {
+          dragging = true;
+          var y = scales.y;
+          var ydom = y.domain();
+          var ydiff = y.invert(d3.event.dy) - y.invert(0);
+          y.domain([ydom[0] - ydiff, ydom[1] - ydiff]);
+        });
+
+
+      // For mousewheel zooming, we need to limit zoom amount. This is needed
+      // because in Firefox, zoom increments are too big. To do this, we limit
+      // scaleExtent before the first zoom event, and after each subsequent
+      // one.
+      //
+      // When zooming out, there's an additional limit: never zoom out past
+      // the original zoom span. The reason it's necessary to calculate this
+      // each time, instead of simply setting the scaleExtent() so that the
+      // lower bound is 1, is because other zoom events (like
+      // dblclick.zoomcell) are able to change the domain of scales.x, without
+      // changing the value of zoom.scale(). This means that the relationship
+      // between the zoom.scale() does not have a fixed linear relationship to
+      // the span of scales.x, and we have to recalculate it.
+      var maxZoomPerStep = 1.1;
+
+      function zoomOutLimit() {
+        var span = scales.x.domain()[1] - scales.x.domain()[0];
+        var startSpan = domains.x[1] - domains.x[0];
+        return Math.min(maxZoomPerStep, startSpan/span);
+      }
+
+      var zoom = d3.behavior.zoom()
+        .x(scales.x)
+        .on("zoomstart", function() {
+          zoom.scaleExtent([zoom.scale() / zoomOutLimit(), zoom.scale() * maxZoomPerStep]);
+        })
+        .on("zoom", function(e) {
+          redrawImmediate();
+          zoom.scaleExtent([zoom.scale() / zoomOutLimit(), zoom.scale() * maxZoomPerStep]);
+        });
+
+      // Register drag before zooming, because we need the drag to set the y
+      // scale before the zoom triggers a redraw.
+      svg
+        .on("mouseup", function(d) {
+          dragging = false;
+        })
+        .call(drag);
+
+      // Unlock selection when background is clicked, and zoom out when
+      // background is double-clicked.
+      backgroundRect
+        .on("mouseup", function(d) {
+          if (dragging) return;
+
+          // If it wasn't a drag, hide info box and unlock.
+          vis.infoBox.hide();
+          highlighter.click(null);
+        })
+        .on("dblclick.zoombackground", function() {
+          savePrevScales();
+
+          scales.x.domain(domains.x);
+          zoom.x(scales.x);
+
+          redrawZoom(250);
+        });
+
+
+      var zoomEnabled = false;
+      function disableZoom() {
+        if (zoomEnabled) {
+          svg.on(".zoom", null);
+          zoomEnabled = false;
+        }
+      }
+      function enableZoom() {
+        if (!zoomEnabled) {
+          svg
+            .call(zoom)
+            .on("dblclick.zoom", null); // Disable zoom's built-in double-click behavior
+          zoomEnabled = true;
+        }
+      }
+      enableZoom();
+
+      onResize();
+
+      return {
+        el: el,
+        onResize: onResize,
+        onUpdateInternals: onResize,
+        redrawImmediate: redrawImmediate,
+        redrawZoom: redrawZoom,
+        redrawCollapse: redrawCollapse,
+        redrawUncollapse: redrawUncollapse,
+        savePrevScales: savePrevScales,
+        useCollapsedDepth: useCollapsedDepth,
+        useUncollapsedDepth: useUncollapsedDepth,
+        addLockHighlight: addLockHighlight,
+        clearLockHighlight: clearLockHighlight,
+        addActiveHighlight: addActiveHighlight,
+        clearActiveHighlight: clearActiveHighlight,
+        disableZoom: disableZoom,
+        enableZoom: enableZoom
+      };
+    } // generateFlameGraph
+
+
+    function initInfoBox(el) {
+
+      function show(d) {
+        var label = d.label ? d.label : "";
+        var ref = (d.filename && d.linenum) ?
+          (d.filename + "#" + d.linenum) :
+          "(source unavailable)";
+
+        el.style.visibility = "";
+
+        el.innerHTML =
+          "<table>" +
+          "<tr><td class='infobox-title'>Label</td><td>" + escapeHTML(label) + "</td></tr>" +
+          "<tr><td class='infobox-title'>Called from</td><td>" + escapeHTML(ref) + "</td></tr>" +
+          "<tr><td class='infobox-title'>Total time</td><td>" + (d.endTime - d.startTime) + "ms</td></tr>" +
+          "<tr><td class='infobox-title'>Memory</td><td>" +
+            roundOneDecimal(d.sumMemDealloc) + " / " + roundOneDecimal(d.sumMemAlloc) +
+            " MB</td></tr>" +
+          "<tr><td class='infobox-title'>Agg. total time</td><td>" + vis.aggLabelTimes[label] + "ms</td></tr>" +
+          "<tr><td class='infobox-title'>Call stack depth</td><td>" + d.depth + "</td></tr>" +
+          "</table>";
+      }
+
+      function hide() {
+        el.style.visibility = "hidden";
+      }
+
+      hide();
+
+      return {
+        el: el,
+        show: show,
+        hide: hide
+      };
+    }
+
+    // Generate the tree table ----------------------------------------
+    function generateTreetable(el) {
+      var content = d3.select(el);
+
+      var table = content.append("table")
+          .attr("class", "results")
+          .attr("cellspacing", "0")
+          .attr("cellpadding", "0");
+
+      table.append("col");
+      table.append("col")
+        .style("width", "120px");
+      table.append("col")
+        .style("width", "50px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "26px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "50px")
+        .attr("class", "treetable-memory");
+      table.append("col")
+        .style("width", "50px");
+      table.append("col")
+        .style("width", "40px");
+
+      var tableBody = table.append("tbody");
+
+      var headerRows = tableBody.append("tr");
+
+      headerRows.append("th")
+        .attr("class", "code-label")
+        .text("Code");
+
+      headerRows.append("th")
+        .attr("class", "path")
+        .text("File");
+
+      headerRows.append("th")
+        .attr("class", "treetable-memory memory")
+        .attr("colspan", "3")
+        .text("Memory (MB)");
+
+      headerRows.append("th")
+        .attr("class", "time")
+        .attr("colspan", "2")
+        .text("Time (ms)");
+
+      // Retrieve all nodes (n), recursevely, where check(n) == true.
+      function allTopNodes(nodes, check) {
+        var included = [];
+        nodes = nodes.slice();
+
+        while (nodes.length > 0) {
+          var node = nodes.shift();
+
+          if (check(node))
+            included.push(node);
+          else {
+            node.sumChildren.forEach(function(c1) {
+              nodes.unshift(c1);
+            });
+          }
+        }
+        return included;
+      }
+
+      // Is there one node (n), including root, where check(n) == true?
+      function oneNode(root, check) {
+        var nodes = [root];
+
+        while (nodes.length > 0) {
+          var n = nodes.shift();
+          if (check(n))
+            return true;
+
+          n.sumChildren.forEach(function(x) {
+            nodes.unshift(x);
+          });
+        }
+
+        return false;
+      }
+
+      function updateRowsDisplay(d) {
+        if (vis.hideInternals && d.isInternal)
+          return "none";
+        else if (!vis.hideInternals && d.isDescendant)
+          return "none";
+
+        var collapsed = false;
+        while (d.parent) {
+          d = d.parent;
+          if (d.collapsed) {
+            collapsed = true;
+            break;
+          }
+        }
+        return collapsed ? "none" : "";
+      }
+
+      function toggleTreeNode(d) {
+        if (!d.canExpand)
+          return;
+
+        var collapsed = d.collapsed;
+        if (collapsed === undefined) {
+          // Create a copy since we might insert the same node twice: once
+          // for the normal leaf the other one for a collapsed node.
+          var sumChildren = d.sumChildren.map(function(x) {
+            return jQuery.extend({}, x);
+          });
+
+          var childNodes = sumChildren.filter(function(x) {
+            return x.depthCollapsed !== null;
+          });
+
+          childNodes.forEach(function(x) {
+            x.isInternal = d.isInternal ? d.isInternal : false;
+            x.isDescendant = d.isDescendant ? d.isDescendant : false;
+          });
+
+          var internalChildNodes = sumChildren.filter(function(x) {
+            return x.depthCollapsed === null;
+          });
+
+          internalChildNodes.forEach(function(x) {
+            x.isInternal = true;
+            x.isDescendant = false;
+          });
+
+          var notInternalDescendantNodes = [];
+          if (!d.isInternal) {
+            notInternalDescendantNodes = allTopNodes(internalChildNodes, function(x) {
+              return x.depthCollapsed !== null && d.depth < x.depth;
+            });
+          }
+
+          notInternalDescendantNodes.forEach(function(x) {
+            x.isInternal = false;
+            x.isDescendant = true;
+          });
+
+          childNodes = childNodes.concat(internalChildNodes);
+          childNodes = childNodes.concat(notInternalDescendantNodes);
+
+          childNodes.forEach(function(n) {
+            n.visualDepth = d.visualDepth + 1;
+            n.parent = d;
+          });
+
+          vis.profTable = vis.profTable.concat(childNodes);
+          d.collapsed = false;
+
+          updateRows();
+
+          // Nodes are sorted "heaviest first"
+          if (childNodes.length == 1) toggleTreeNode(childNodes[0]);
+        }
+        else {
+          d.collapsed = !collapsed;
+          updateRows();
+        }
+      }
+
+      function updateLabelCells(labelCell) {
+        labelCell
+          .attr("nowrap", "true")
+          .style("padding-left", function(d) {
+            return (8 + 15 * (d.visualDepth - 1)) + "px";
+          })
+          .on("click", toggleTreeNode)
+          .attr("class", function(d) {
+            d.canExpand = false;
+            if (d.sumChildren) {
+              d.sumChildren.forEach(function(c) {
+                if (c.sumChildren.length > 0) {
+                  if (!vis.hideInternals || oneNode(c, function(c1) { return c1.depthCollapsed !== null; }))
+                    d.canExpand = true;
+                }
+              });
+            }
+
+            var collapsedClass = "";
+            if (d.canExpand)
+              collapsedClass = d.collapsed === undefined ? "treetable-expand" : d.collapsed ? "treetable-expand" : "treetable-collapse";
+
+            return "code-label " + (d.canExpand ? "label-pointer " + collapsedClass : "");
+          });
+      }
+
+      function updateRows() {
+        var rows = tableBody.selectAll("tr.treetable-row")
+          .data(vis.profTable, function(d) {
+            return d.id;
+          });
+
+        rows.exit()
+          .remove();
+
+        var updatedRows = rows
+          .style("display", updateRowsDisplay);
+
+        var updatedLabelCells = updatedRows.selectAll("td.code-label");
+        updateLabelCells(updatedLabelCells);
+
+        var newRows = rows.enter()
+          .append("tr")
+          .filter(function(d) {
+            if (vis.hideInternals && d.depthCollapsed === null)
+              return false;
+
+            return true;
+          })
+          .on("click", function(d) {
+            table.selectAll("tr")
+              .style("background-color", null);
+
+            this.style.backgroundColor = "rgb(241, 241, 241)";
+            notifySourceFileMessage(d, "select");
+          })
+          .style("display", updateRowsDisplay);
+
+        newRows
+          .attr("class", "treetable-row");
+
+        var labelCell = newRows.append("td");
+        updateLabelCells(labelCell);
+
+        var cellWrapper = labelCell.append("div");
+        cellWrapper.append("div");
+
+        labelCell.append("div")
+          .attr("class", "label-text")
+          .text(function(d) { return d.label; });
+
+        newRows.append("td")
+          .attr("class", "path")
+          .text(function(d) {
+            var lastSlash = d.filename ? d.filename.lastIndexOf("/") : -1;
+            if (lastSlash >= 0)
+              return d.filename.substr(lastSlash + 1);
+
+            return d.filename;
+          });
+
+        newRows.append("td")
+          .attr("class", "treetable-memory memory-info")
+          .text(function(d) {
+            return roundOneDecimal(d.sumMemDealloc);
+          });
+
+        var memoryBarContainer = newRows.append("td")
+          .attr("class", "treetable-memory memory-bar-container");
+
+        var memoryLeftCell = memoryBarContainer.append("div")
+          .attr("class", "memory-leftbar-wrapper");
+
+        memoryLeftCell.append("div")
+          .attr("class", "memory-leftbar")
+          .style("width", function(d) {
+            return  1 + Math.min(Math.abs(Math.min(Math.round(d.propMemDealloc * 5), 0)), 5) + "px";
+          });
+
+        memoryBarContainer.append("div")
+          .attr("class", "memory-rightbar")
+          .style("width", function(d) {
+            return 1 + Math.min(Math.max(Math.round(d.propMemAlloc * 13), 0), 13) + "px";
+          });
+
+        newRows.append("td")
+          .attr("class", "treetable-memory memory-info-right")
+          .text(function(d) {
+            return roundOneDecimal(d.sumMemAlloc);
+          });
+
+        newRows.append("td")
+          .attr("class", "time-info")
+          .text(function(d) {
+            return d.sumTime;
+          });
+
+        var timeCell = newRows.append("td")
+          .attr("class", "time-bar-container");
+
+        timeCell.append("div")
+          .attr("class", "timebar")
+          .style("width", function(d) {
+            return Math.round(d.propTime * 20) + "px";
+          });
+
+        var unorderedRows = d3.selectAll("tr.treetable-row")
+          .data(vis.profTable, function(d) {
+            return d.id;
+          });
+
+        unorderedRows.sort(function(a,b) {
+          return (a.id < b.id) ? -1 : (a.id == b.id ? 0 : 1);
+        });
+
+        useMemoryResults();
+      }
+
+      var buildProfTable = function (profTree) {
+        var head = jQuery.extend({}, profTree);
+        var nodes = [head];
+
+        var aggregateChildren = function(node) {
+          var nameMap = {};
+          node.children.forEach(function(c) {
+            var nameMapEntry = nameMap[c.label];
+            if (!nameMapEntry) {
+              nameMapEntry = jQuery.extend({}, c);
+              nameMapEntry.sumTime     = c.endTime - c.startTime;
+              nameMapEntry.sumChildren = [];
+              nameMapEntry.children    = [];
+              nameMapEntry.parent      = node;
+              nameMapEntry.sumCount    = 1;
+            }
+            else {
+              nameMapEntry.sumMem        = nameMapEntry.sumMem        + c.sumMem;
+              nameMapEntry.sumMemDealloc = nameMapEntry.sumMemDealloc + c.sumMemDealloc;
+              nameMapEntry.sumMemAlloc   = nameMapEntry.sumMemAlloc   + c.sumMemAlloc;
+              nameMapEntry.sumTime       = nameMapEntry.sumTime       + (c.endTime - c.startTime);
+              nameMapEntry.sumCount      = nameMapEntry.sumCount      + 1;
+            }
+
+            nameMapEntry.propMem        = nameMapEntry.sumMem        / vis.totalMem;
+            nameMapEntry.propMemDealloc = nameMapEntry.sumMemDealloc / vis.totalMem;
+            nameMapEntry.propMemAlloc   = nameMapEntry.sumMemAlloc   / vis.totalMem;
+            nameMapEntry.propTime       = nameMapEntry.sumTime       / vis.totalTime;
+
+            c.children.forEach(function(e) {
+              nameMapEntry.children.push(e);
+            });
+
+            nameMap[c.label] = nameMapEntry;
+          });
+
+          var childrenSum = [];
+          for (var label in nameMap) {
+            childrenSum.push(nameMap[label]);
+          }
+
+          // Sort by time descending
+          childrenSum.sort(function(a, b) { return b.sumTime - a.sumTime });
+          return childrenSum;
+        };
+
+        function addToNodesAt(c, i) {
+          nodes.splice(i, 0, c);
+        }
+
+        var id = 0;
+        while (nodes.length > 0) {
+          var node = nodes.shift();
+
+          node.id = id;
+          id = id + 1;
+
+          node.sumChildren = aggregateChildren(node);
+
+          // Processing in order is important to preserve order of IDs!
+          node.sumChildren.forEach(addToNodesAt);
+        }
+
+        return head.sumChildren;
+      };
+
+      function useMemoryResults() {
+        d3.selectAll(".treetable-memory").style("display", vis.hideMemory ? "none" : "");
+      }
+
+      vis.profTable = buildProfTable(vis.profTree);
+      vis.profTable.forEach(function(e) {
+        e.visualDepth = 1;
+      });
+
+      updateRows();
+
+      return {
+        el: el,
+        onResize: updateRows,
+        onOptionsChange: updateRows,
+        onUpdateInternals: function() {
+
+        },
+        useMemoryResults: useMemoryResults
+      };
+    }
+
+    function enableScroll() {
+      vis.codeTable.enableScroll();
+      vis.flameGraph.enableZoom();
+    }
+
+    function disableScroll() {
+      vis.codeTable.disableScroll();
+      vis.flameGraph.disableZoom();
+    }
+
+
+    // Set up resizing --------------------------------------------------------
+
+    // This is used as a jQuery event namespace so that we can remove the window
+    // resize handler on subsequent calls to initResizing(). Not elegant, but it
+    // gets the job done.
+    var resizeCallbackNamespace = randomString(10);
+
+    // Resize panel1 and panel2 to 50% of available space and add callback
+    // for window resizing.
+    function initResizing() {
+      var $el = $(vis.el);
+      var $panel1 = $el.children(".profvis-panel1");
+      var $panel2 = $el.children(".profvis-panel2");
+      var $splitBar = $el.children(".profvis-splitbar");
+      var $statusBar = $el.children(".profvis-status-bar");
+
+      // Clear any existing positioning that may have happened from previous
+      // calls to this function and the callbacks that it sets up.
+      $panel1.removeAttr("style");
+      $panel2.removeAttr("style");
+      $splitBar.removeAttr("style");
+      $statusBar.removeAttr("style");
+
+      // CSS class suffix for split direction
+      var splitClass = (vis.splitDir === "h") ? "horizontal" : "vertical";
+
+      // Remove existing horizontal/vertical class and add the correct class back.
+      $panel1.removeClass("profvis-panel1-horizontal profvis-panel1-vertical");
+      $panel2.removeClass("profvis-panel2-horizontal profvis-panel2-vertical");
+      $splitBar.removeClass("profvis-splitbar-horizontal profvis-splitbar-vertical");
+      $panel1.addClass("profvis-panel1-" + splitClass);
+      $panel2.addClass("profvis-panel2-" + splitClass);
+      $splitBar.addClass("profvis-splitbar-" + splitClass);
+
+
+      var splitBarGap;
+      var margin;
+      // Record the proportions from the previous call to resizePanels. This is
+      // needed when we resize the window to preserve the same proportions.
+      var lastSplitProportion;
+
+      if (vis.splitDir === "v") {
+        // Record the gap between the split bar and the objects to left and right
+        splitBarGap = {
+          left: $splitBar.offset().left - offsetRight($panel1),
+          right: $panel2.offset().left - offsetRight($splitBar)
+        };
+
+        // Capture the initial distance from the left and right of container element
+        margin = {
+          left: $panel1.position().left,
+          right: $el.innerWidth() - positionRight($panel2)
+        };
+
+      } else if (vis.splitDir === "h") {
+        splitBarGap = {
+          top: $splitBar.offset().top - offsetBottom($panel1),
+          bottom: $panel2.offset().top - offsetBottom($splitBar)
+        };
+
+        margin = {
+          top: $panel1.position().top,
+          bottom: $el.innerWidth() - positionBottom($panel2)
+        };
+      }
+
+      // Resize the panels. splitProportion is a number from 0-1 representing the
+      // horizontal position of the split bar.
+      function resizePanels(splitProportion) {
+        if (!splitProportion)
+          splitProportion = lastSplitProportion;
+
+        if (vis.splitDir === "v") {
+          var innerWidth = offsetRight($panel2) - $panel1.offset().left;
+
+          $splitBar.offset({
+            left: $panel1.offset().left + innerWidth * splitProportion -
+                  $splitBar.outerWidth()/2
+          });
+
+          // Size and position the panels
+          $panel1.outerWidth($splitBar.position().left - splitBarGap.left -
+                             margin.left);
+          $panel2.offset({ left: offsetRight($splitBar) + splitBarGap.right });
+
+        } else if (vis.splitDir === "h") {
+          var innerHeight = offsetBottom($panel2) - $panel1.offset().top;
+
+          $splitBar.offset({
+            top: $panel1.offset().top + innerHeight * splitProportion -
+                 $splitBar.outerHeight()/2
+          });
+
+          // Size and position the panels
+          $panel1.outerHeight($splitBar.position().top - splitBarGap.top -
+                             margin.top);
+          $panel2.offset({ top: offsetBottom($splitBar) + splitBarGap.bottom });
+        }
+
+        lastSplitProportion = splitProportion;
+      }
+
+      // Initially, set widths to 50/50
+      // For the first sizing, we don't need to call vis.flameGraph.onResize()
+      // because this happens before the flame graph is generated.
+      resizePanels(0.5);
+
+      var resizePanelsDebounced = debounce(function() {
+        resizePanels(lastSplitProportion);
+        vis.activeViews.forEach(function(e) {
+          if (e.onResize) e.onResize();
+        });
+      }, 250);
+
+      // Clear old resize handler and add new one. We use a namespace for this
+      // visualization to make sure not to delete handlers for other profvis
+      // visualizations on the same page (this can happen with Rmd documents).
+      $(window).off("resize.profvis." + resizeCallbackNamespace);
+      $(window).on("resize.profvis." + resizeCallbackNamespace, resizePanelsDebounced);
+
+      // Get current proportional position of split bar
+      function splitProportion() {
+        var splitCenter;
+
+        if (vis.splitDir === "v") {
+          splitCenter = $splitBar.offset().left - $panel1.offset().left +
+                            $splitBar.outerWidth()/2;
+          var innerWidth = offsetRight($panel2) - $panel1.offset().left;
+          return splitCenter / innerWidth;
+
+        } else if (vis.splitDir === "h") {
+          splitCenter = $splitBar.offset().top - $panel1.offset().top +
+                            $splitBar.outerHeight()/2;
+          var innerHeight = offsetBottom($panel2) - $panel1.offset().top;
+          return splitCenter / innerHeight;
+        }
+      }
+
+      function positionRight($el) {
+        return $el.position().left + $el.outerWidth();
+      }
+      function offsetRight($el) {
+        return $el.offset().left + $el.outerWidth();
+      }
+      function positionBottom($el) {
+        return $el.position().top + $el.outerHeight();
+      }
+      function offsetBottom($el) {
+        return $el.offset().top + $el.outerHeight();
+      }
+
+      // Enable dragging of the split bar ---------------------------------------
+      (function() {
+        var dragging = false;
+        // For vertical split (left-right dragging)
+        var startDragX;
+        var startOffsetLeft;
+        // For horizontal split (up-down dragging)
+        var startDragY;
+        var startOffsetTop;
+
+        var stopDrag = function(e) {
+          if (!dragging) return;
+          dragging = false;
+
+          document.removeEventListener("mousemove", drag);
+          document.removeEventListener("mouseup", stopDrag);
+
+          $splitBar.css("opacity", "");
+
+          if ((vis.splitDir === "v" && e.pageX - startDragX === 0) ||
+              (vis.splitDir === "h" && e.pageY - startDragY === 0)) {
+            return;
+          }
+
+          resizePanels(splitProportion());
+          vis.flameGraph.onResize();
+        };
+
+        var startDrag = function(e) {
+          // Don't start another drag if we're already in one.
+          if (dragging) return;
+          dragging = true;
+          pauseEvent(e);
+
+          $splitBar.css("opacity", 0.75);
+
+          if (vis.splitDir === "v") {
+            startDragX = e.pageX;
+            startOffsetLeft = $splitBar.offset().left;
+          } else {
+            startDragY = e.pageY;
+            startOffsetTop = $splitBar.offset().top;
+          }
+
+          document.addEventListener("mousemove", drag);
+          document.addEventListener("mouseup", stopDrag);
+        };
+
+        var drag = function(e) {
+          if (!dragging) return;
+          pauseEvent(e);
+
+          if (vis.splitDir === "v") {
+            var dx = e.pageX - startDragX;
+            if (dx === 0)
+              return;
+
+            // Move the split bar
+            $splitBar.offset({ left: startOffsetLeft + dx });
+
+          } else if (vis.splitDir === "h") {
+            var dy = e.pageY - startDragY;
+            if (dy === 0)
+              return;
+
+            // Move the split bar
+            $splitBar.offset({ top: startOffsetTop + dy });
+          }
+        };
+
+        // Stop propogation so that we don't select text while dragging
+        function pauseEvent(e){
+          if(e.stopPropagation) e.stopPropagation();
+          if(e.preventDefault) e.preventDefault();
+          e.cancelBubble = true;
+          e.returnValue = false;
+          return false;
+        }
+
+        // Remove existing event listener from previous calls to initResizing().
+        $splitBar.off("mousedown.profvis");
+        $splitBar.on("mousedown.profvis", startDrag);
+      })();
+
+
+      return {
+        resizePanels: resizePanels
+      };
+    }
+
+
+    var prof = prepareProfData(message.prof, message.interval);
+
+    var vis = {
+      el: el,
+      prof: prof,
+      profTree: getProfTree(prof),
+      interval: message.interval,
+      totalTime: getTotalTime(prof),
+      totalMem: getTotalMemory(prof),
+      files: message.files,
+      aggLabelTimes: getAggregatedLabelTimes(prof),
+      fileLineStats: getFileLineStats(prof, message.files),
+      profTable: [],
+
+      // Objects representing each component
+      statusBar: null,
+      optionsPanel: null,
+      codeTable: null,
+      flameGraph: null,
+      infoBox: null,
+      treetable: null,
+      activeViews: [],
+
+      // Functions to enable/disable responding to scrollwheel events
+      enableScroll: enableScroll,
+      disableScroll: disableScroll,
+
+      splitDir: message.split,
+      hideInternals: true,
+      hideMemory: false,
+
+      resizePanels: null
+    };
+
+
+    // Render the objects ---------------------------------------------
+
+    var statusBarEl = document.createElement("div");
+    statusBarEl.className = "profvis-status-bar";
+    vis.el.appendChild(statusBarEl);
+
+    // Container panels - top/bottom or left/right
+    var panel1 = document.createElement("div");
+    panel1.className = "profvis-panel1";
+    vis.el.appendChild(panel1);
+
+    var panel2 = document.createElement("div");
+    panel2.className = "profvis-panel2";
+    vis.el.appendChild(panel2);
+
+    var splitBarEl = document.createElement("div");
+    splitBarEl.className = "profvis-splitbar";
+    vis.el.appendChild(splitBarEl);
+
+    var footerEl = document.createElement("div");
+    footerEl.className = "profvis-footer";
+    vis.el.appendChild(footerEl);
+
+    // Items in the panels
+    var codeTableEl = document.createElement("div");
+    codeTableEl.className = "profvis-code";
+    panel1.appendChild(codeTableEl);
+
+    var flameGraphEl = document.createElement("div");
+    flameGraphEl.className = "profvis-flamegraph";
+    panel2.appendChild(flameGraphEl);
+
+    var infoBoxEl = document.createElement("div");
+    infoBoxEl.className = "profvis-infobox";
+    panel2.appendChild(infoBoxEl);
+
+    var treetableEl = document.createElement("div");
+    treetableEl.className = "profvis-treetable";
+    treetableEl.style.display = "none";
+    vis.el.appendChild(treetableEl);
+
+    var optionsPanelEl = document.createElement("div");
+    optionsPanelEl.className = "profvis-options-panel";
+    vis.el.appendChild(optionsPanelEl);
+
+    // Efficient to properly size panels before the code + flamegraph are
+    // rendered, so that we don't have to re-render.
+    var resize = initResizing();
+    vis.resizePanels = resize.resizePanels;
+
+    var hideViews = function() {
+      splitBarEl.style.display = "none";
+      panel1.style.display = "none";
+      panel2.style.display = "none";
+      treetableEl.style.display = "none";
+    };
+
+    var toggleViews = function(view) {
+      hideViews();
+
+      switch (view) {
+        case "flamegraph":
+          splitBarEl.style.display = "block";
+          panel1.style.display = "block";
+          panel2.style.display = "block";
+
+          vis.activeViews = [vis.flameGraph, vis.codeTable];
+          vis.resizePanels();
+          break;
+        case "treetable":
+          if (!vis.treetable) {
+            vis.treetable = generateTreetable(treetableEl);
+          }
+
+          treetableEl.style.display = "block";
+
+          vis.activeViews = [vis.treetable];
+          break;
+      }
+
+      vis.activeViews.forEach(function(e) {
+        if (e.onResize) e.onResize();
+      });
+    };
+
+    var onOptionsChange = function(option, checked) {
+      switch (option)
+      {
+        case "split": {
+          vis.splitDir = checked ? "h" : "v";
+          // Check that flame graph is visible
+          if ($.inArray(vis.flameGraph, vis.activeViews) !== -1) {
+            initResizing();
+            vis.flameGraph.onResize();
+          }
+          break;
+        }
+        case "internals": {
+          vis.flameGraph.savePrevScales();
+
+          vis.hideInternals = checked;
+          if (checked) {
+            vis.flameGraph.useCollapsedDepth();
+            vis.flameGraph.redrawCollapse(400, 400);
+          } else {
+            vis.flameGraph.useUncollapsedDepth();
+            vis.flameGraph.redrawUncollapse(400, 250);
+          }
+
+          vis.activeViews.forEach(function(e) {
+            if (e.onOptionsChange) e.onOptionsChange();
+          });
+
+          break;
+        }
+        case "memory": {
+          vis.hideMemory = checked;
+          vis.activeViews.forEach(function(e) {
+            if (e.useMemoryResults) e.useMemoryResults();
+          });
+          break;
+        }
+      }
+    };
+
+    // Create the UI components
+    vis.statusBar = generateStatusBar(statusBarEl, toggleViews);
+    vis.footer = generateFooter(footerEl);
+    vis.optionsPanel = generateOptionsPanel(optionsPanelEl, onOptionsChange);
+    vis.codeTable = generateCodeTable(codeTableEl);
+    vis.flameGraph = generateFlameGraph(flameGraphEl);
+    vis.infoBox = initInfoBox(infoBoxEl);
+    vis.treetable = null;
+    vis.activeViews = [vis.flameGraph, vis.codeTable];
+
+    // If any depth collapsing occured, enable the "hide internal" checkbox.
+    if (prof.some(function(d) { return d.depth !== d.depthCollapsed; })) {
+      vis.optionsPanel.enableHideInternal();
+    }
+
+    // Start with scrolling disabled because of mousewheel scrolling issue
+    disableScroll();
+
+    // Make the vis object accessible via the DOM element
+    $(el).data("profvis", vis);
+
+    return vis;
+  };  // profvis.render()
+
+  // Calculate amount of time spent on each line of code. Returns nested objects
+  // grouped by file, and then by line number.
+  function getFileLineStats(prof, files) {
+    // Drop entries with null or "" filename
+    prof = prof.filter(function(row) {
+      return row.filename !== null && row.filename !== "";
+    });
+
+    // Gather line-by-line file contents
+    var fileLineStats = files.map(function(file) {
+      // Create array of objects with info for each line of code.
+      var lines = file.content.split("\n");
+      var lineData = [];
+      var filename = file.filename;
+      var normpath = file.normpath;
+      for (var i=0; i<lines.length; i++) {
+        lineData[i] = {
+          filename: filename,
+          normpath: normpath,
+          linenum: i + 1,
+          content: lines[i],
+          sumTime: 0,
+          sumMem: 0,
+          sumMemAlloc: 0,
+          sumMemDealloc: 0
+        };
+      }
+
+      return {
+        filename: filename,
+        lineData: lineData
+      };
+    });
+
+    // Get timing data for each line
+    var statsData = d3.nest()
+      .key(function(d) { return d.filename; })
+      .key(function(d) { return d.linenum; })
+      .rollup(function(leaves) {
+        var sumTime = leaves.reduce(function(sum, d) {
+          // Add this node's time only if no ancestor node has the same
+          // filename and linenum. This is to avoid double-counting times for
+          // a line.
+          var incTime = 0;
+          if (!ancestorHasFilenameLinenum(d.filename, d.linenum, d.parent)) {
+            incTime = d.endTime - d.startTime;
+          }
+          return sum + incTime;
+        }, 0);
+
+        var sumMem = leaves.reduce(function(sum, d) {
+          return sum + d.sumMem;
+        }, 0);
+
+        var sumMemDealloc = leaves.reduce(function(sum, d) {
+          return sum + d.sumMemDealloc;
+        }, 0);
+
+        var sumMemAlloc = leaves.reduce(function(sum, d) {
+          return sum + d.sumMemAlloc;
+        }, 0);
+
+        return {
+          filename: leaves[0].filename,
+          linenum: leaves[0].linenum,
+          sumTime: sumTime,
+          sumMem: sumMem,
+          sumMemAlloc: sumMemAlloc,
+          sumMemDealloc: sumMemDealloc
+        };
+      })
+      .entries(prof);
+
+    // Insert the sumTimes into line content data
+    statsData.forEach(function(fileInfo) {
+      // Find item in fileTimes that matches the file of this fileInfo object
+      var fileLineData = fileLineStats.filter(function(d) {
+        return d.filename === fileInfo.key;
+      })[0].lineData;
+
+      fileInfo.values.forEach(function(lineInfo) {
+        lineInfo = lineInfo.values;
+        fileLineData[lineInfo.linenum - 1].sumTime = lineInfo.sumTime;
+        fileLineData[lineInfo.linenum - 1].sumMem = lineInfo.sumMem;
+        fileLineData[lineInfo.linenum - 1].sumMemDealloc = lineInfo.sumMemDealloc;
+        fileLineData[lineInfo.linenum - 1].sumMemAlloc = lineInfo.sumMemAlloc;
+      });
+    });
+
+    // Calculate proportional times, relative to the longest time in the data
+    // set. Modifies data in place.
+    var fileMaxTimes = fileLineStats.map(function(lines) {
+      var lineTimes = lines.lineData.map(function(x) { return x.sumTime; });
+      return d3.max(lineTimes);
+    });
+
+    var maxTime = d3.max(fileMaxTimes);
+
+    fileLineStats.map(function(lines) {
+      lines.lineData.map(function(line) {
+        line.propTime = line.sumTime / maxTime;
+      });
+    });
+
+    var totalMem = getTotalMemory(prof);
+
+    fileLineStats.map(function(lines) {
+      lines.lineData.map(function(line) {
+        line.propMem = line.sumMem / totalMem;
+        line.propMemDealloc = line.sumMemDealloc / totalMem;
+        line.propMemAlloc = line.sumMemAlloc / totalMem;
+      });
+    });
+
+    return fileLineStats;
+
+    // Returns true if the given node or one of its ancestors has the given
+    // filename and linenum; false otherwise.
+    function ancestorHasFilenameLinenum(filename, linenum, node) {
+      if (!node) {
+        return false;
+      }
+      if (node.filename === filename && node.linenum === linenum) {
+        return true;
+      }
+      return ancestorHasFilenameLinenum(filename, linenum, node.parent);
+    }
+  }
+
+  function prepareProfData(prof, interval) {
+    // Convert object-with-arrays format prof data to array-of-objects format
+    var data = colToRows(prof);
+    data = addParentChildLinks(data);
+    data = consolidateRuns(data);
+    data = applyInterval(data, interval);
+    data = findCollapsedDepths(data);
+
+    return data;
+  }
+
+  // Given the raw profiling data, convert `time` and `lastTime` fields to
+  // `startTime` and `endTime`, and use the supplied interval. Modifies data
+  // in place.
+  function applyInterval(prof, interval) {
+    prof.forEach(function(d) {
+      d.startTime = interval * (d.time - 1);
+      d.endTime = interval * (d.lastTime);
+      delete d.time;
+      delete d.lastTime;
+    });
+
+    return prof;
+  }
+
+  // Find the total time spanned in the data
+  function getTotalTime(prof) {
+    return d3.max(prof, function(d) { return d.endTime; }) -
+           d3.min(prof, function(d) { return d.startTime; });
+  }
+
+  // Find the total memory spanned in the data
+  function getTotalMemory(prof) {
+    return d3.max(prof, function(d) { return d.memalloc; });
+  }
+
+  // Calculate the total amount of time spent in each function label
+  function getAggregatedLabelTimes(prof) {
+    var labelTimes = {};
+    var tree = getProfTree(prof);
+    calcLabelTimes(tree);
+
+    return labelTimes;
+
+    // Traverse the tree with the following strategy:
+    // * Check if current label is used in an ancestor.
+    //   * If yes, don't add to times for that label.
+    //   * If no, do add to times for that label.
+    // * Recurse into children.
+    function calcLabelTimes(node) {
+      var label = node.label;
+      if (!ancestorHasLabel(label, node.parent)) {
+        if (labelTimes[label] === undefined)
+          labelTimes[label] = 0;
+
+        labelTimes[label] += node.endTime - node.startTime;
+      }
+
+      node.children.forEach(calcLabelTimes);
+    }
+
+    // Returns true if the given node or one of its ancestors has the given
+    // label; false otherwise.
+    function ancestorHasLabel(label, node) {
+      if (node) {
+        if (node.label === label) {
+          return true;
+        }
+        return ancestorHasLabel(label, node.parent);
+      } else {
+        return false;
+      }
+    }
+  }
+
+
+  // Given profiling data, add parent and child links to indicate stack
+  // relationships.
+  function addParentChildLinks(prof) {
+    var data = d3.nest()
+      .key(function(d) { return d.time; })
+      .rollup(function(leaves) {
+        leaves = leaves.sort(function(a, b) { return a.depth - b.depth; });
+
+        leaves[0].parent = null;
+        leaves[0].children = [];
+
+        for (var i=1; i<leaves.length; i++) {
+          leaves[i-1].children.push(leaves[i]);
+          leaves[i].parent = leaves[i-1];
+          leaves[i].children = [];
+        }
+
+        return leaves;
+      })
+      .map(prof);
+
+    // Convert data from object of arrays to array of arrays
+    data = d3.map(data).values();
+    // Flatten data
+    return d3.merge(data);
+  }
+
+
+  // Given profiling data, consolidate consecutive blocks for a flamegraph.
+  // This function also assigns correct parent-child relationships to form a
+  // tree of data objects, with a hidden root node at depth 0.
+  function consolidateRuns(prof) {
+    // Create a special top-level leaf whose only purpose is to point to its
+    // children, the items at depth 1.
+    var topLeaf = {
+      depth: 0,
+      parent: null,
+      children: prof.filter(function(d) { return d.depth === 1; })
+    };
+
+    var tree = consolidateTree(topLeaf);
+    var data = treeToArray(tree);
+    // Remove the root node from the flattened data
+    data = data.filter(function(d) { return d.depth !== 0; });
+    return data;
+
+    function consolidateTree(tree) {
+      var leaves = tree.children;
+      leaves = leaves.sort(function(a, b) { return a.time - b.time; });
+
+      // Collapse consecutive leaves, with some conditions
+      var startLeaf = null;  // leaf starting this run
+      var lastLeaf = null;   // The last leaf we've looked at
+      var newLeaves = [];
+      var collectedChildren = [];
+      var sumMem = 0;
+      var sumMemDealloc = 0;
+      var sumMemAlloc = 0;
+
+      // This takes the start leaf, end leaf, and the set of children for the
+      // new leaf, and creates a new leaf which copies all its properties from
+      // the startLeaf, except lastTime and children.
+      function addNewLeaf(startLeaf, endLeaf, newLeafChildren, sumMem, sumMemDealloc, sumMemAlloc) {
+        var newLeaf = $.extend({}, startLeaf);
+        newLeaf.lastTime = endLeaf.time;
+        newLeaf.parent = tree;
+        newLeaf.children = newLeafChildren;
+
+        // Recurse into children
+        newLeaf = consolidateTree(newLeaf);
+
+        // Aggregate memory from this consolidation batch and their children
+        aggregateMemory(newLeaf, sumMem, sumMemDealloc, sumMemAlloc);
+
+        newLeaves.push(newLeaf);
+      }
+
+      function aggregateMemory(leaf, sumMem, sumMemDealloc, sumMemAlloc) {
+        leaf.sumMem = sumMem;
+        leaf.sumMemDealloc = sumMemDealloc;
+        leaf.sumMemAlloc = sumMemAlloc;
+        if (leaf.children) {
+          leaf.children.forEach(function(child) {
+            leaf.sumMem += child.sumMem ? child.sumMem : 0;
+            leaf.sumMemDealloc += child.sumMemDealloc ? child.sumMemDealloc : 0;
+            leaf.sumMemAlloc += child.sumMemAlloc ? child.sumMemAlloc : 0;
+          });
+        }
+      }
+
+      for (var i=0; i<leaves.length; i++) {
+        var leaf = leaves[i];
+
+        if (i === 0) {
+          startLeaf = leaf;
+          sumMem = sumMemAlloc = sumMemDealloc = 0;
+        } else if (leaf.label !== startLeaf.label ||
+                   leaf.filename !== startLeaf.filename ||
+                   leaf.linenum !== startLeaf.linenum ||
+                   leaf.depth !== startLeaf.depth)
+        {
+          addNewLeaf(startLeaf, lastLeaf, collectedChildren, sumMem, sumMemDealloc, sumMemAlloc);
+
+          collectedChildren = [];
+          startLeaf = leaf;
+          sumMem = sumMemAlloc = sumMemDealloc = 0;
+        }
+
+        sumMem += leaf.meminc;
+        sumMemDealloc += Math.min(leaf.meminc, 0);
+        sumMemAlloc += Math.max(leaf.meminc, 0);
+        collectedChildren = collectedChildren.concat(leaf.children);
+        lastLeaf = leaf;
+      }
+
+      // Add the last one, if there were any at all
+      if (i !== 0) {
+        addNewLeaf(startLeaf, lastLeaf, collectedChildren, sumMem, sumMemDealloc, sumMemAlloc);
+      }
+
+      tree.children = newLeaves;
+      return tree;
+    }
+
+    // Given a tree, pull out all the leaves and put them in a flat array
+    function treeToArray(tree) {
+      var allLeaves = [];
+
+      function pushLeaves(leaf) {
+        allLeaves.push(leaf);
+        leaf.children.forEach(pushLeaves);
+      }
+
+      pushLeaves(tree);
+      return allLeaves;
+    }
+  }
+
+
+  // Given profiling data with parent-child information, get the root node.
+  function getProfTree(prof) {
+    if (prof.length === 0)
+      return null;
+
+    // Climb up to the top of the tree
+    var node = prof[0];
+    while (node.parent) {
+      node = node.parent;
+    }
+    return node;
+  }
+
+
+  // Given profiling data, find depth of items after hiding items between
+  // items with labels "..stacktraceoff.." and "..stacktraceon..". Modifies
+  // data in place.
+  function findCollapsedDepths(data) {
+    var tree = getProfTree(data);
+    calculateDepths(tree, tree.depth, 0);
+    return data;
+
+    function calculateDepths(node, curCollapsedDepth, stacktraceOffCount) {
+      if (node.label === "..stacktraceoff..") {
+        stacktraceOffCount++;
+      }
+
+      if (stacktraceOffCount > 0) {
+        node.depthCollapsed = null;
+      } else {
+        node.depthCollapsed = curCollapsedDepth;
+        curCollapsedDepth++;
+      }
+
+      if (node.label === "..stacktraceon..") {
+        stacktraceOffCount--;
+      }
+
+      // Recurse
+      node.children.forEach(function(x) {
+        calculateDepths(x, curCollapsedDepth, stacktraceOffCount);
+      });
+    }
+  }
+
+
+  // Transform column-oriented data (an object with arrays) to row-oriented data
+  // (an array of objects).
+  function colToRows(x) {
+    var colnames = d3.keys(x);
+    if (colnames.length === 0)
+      return [];
+
+    var newdata = [];
+    for (var i=0; i < x[colnames[0]].length; i++) {
+      var row = {};
+      for (var j=0; j < colnames.length; j++) {
+        var colname = colnames[j];
+        row[colname] = x[colname][i];
+      }
+      newdata[i] = row;
+    }
+
+    return newdata;
+  }
+
+  // Given an array with two values (a min and max), return an array with the
+  // range expanded by `amount`.
+  function expandRange(range, amount) {
+    var adjust = amount * (range[1] - range[0]);
+    return [
+      range[0] - adjust,
+      range[1] + adjust
+    ];
+  }
+
+
+  // Escape an HTML string.
+  function escapeHTML(text) {
+    return text
+      .replace(/&/g, "&amp;")
+      .replace(/</g, "&lt;")
+      .replace(/>/g, "&gt;")
+      .replace(/"/g, "&quot;")
+      .replace(/'/g, "&#039;");
+  }
+
+  // This returns the current page URL without any trailing hash. Should be
+  // used in url() references in SVGs to avoid problems when there's a <base>
+  // tag in the document.
+  function urlNoHash() {
+    return window.location.href.split("#")[0];
+  }
+
+  function debounce(f, delay) {
+    var timer = null;
+    return function() {
+      var context = this;
+      var args = arguments;
+      clearTimeout(timer);
+      timer = setTimeout(function () {
+        f.apply(context, args);
+      }, delay);
+    };
+  }
+
+  function randomString(length) {
+    var chars = 'abcdefghijklmnopqrstuvwxyz';
+    var result = '';
+    for (var i = length; i > 0; --i)
+      result += chars[Math.floor(Math.random() * chars.length)];
+    return result;
+  }
+
+  var getNormPath = function(files, filename) {
+    var normpath = null;
+    files.forEach(function(e) {
+      if (e.filename == filename) {
+        normpath = e.normpath;
+      }
+    });
+    return normpath;
+  };
+
+
+  (function() {
+    // Prevent unwanted scroll capturing. Based on the corresponding code in
+    // https://github.com/rstudio/leaflet
+
+    // The rough idea is that we disable scroll wheel zooming inside each
+    // profvis object, until the user moves the mouse cursor or clicks on the
+    // visualization. This is trickier than just listening for mousemove,
+    // because mousemove is fired when the page is scrolled, even if the user
+    // did not physically move the mouse. We handle this by examining the
+    // mousemove event's screenX and screenY properties; if they change, we know
+    // it's a "true" move.
+    //
+    // There's a complication to this: when the mouse wheel is scrolled quickly,
+    // on the step where the profvis DOM object overlaps the cursor, sometimes
+    // the mousemove event happens before the mousewheel event, and sometimes
+    // it's the reverse (at least on Chrome 46 on Linux). This means that we
+    // can't rely on the mousemove handler disabling the profvis object's zoom
+    // before a scroll event is triggered on the profvis object (cauzing
+    // zooming). In order to deal with this, we start each profvis object with
+    // zooming disabled, and also disable zooming when the cursor leaves the
+    // profvis div. That way, even if a mousewheel event gets triggered on the
+    // object before the mousemove, it won't cause zooming.
+
+    // lastScreen can never be null, but its x and y can.
+    var lastScreen = { x: null, y: null };
+
+    $(document)
+      .on("mousewheel DOMMouseScroll", function(e) {
+        // Any mousemove events at this screen position will be ignored.
+        lastScreen = { x: e.originalEvent.screenX, y: e.originalEvent.screenY };
+      })
+      .on("mousemove", ".profvis", function(e) {
+        // Did the mouse really move?
+        if (lastScreen.x !== null && e.screenX !== lastScreen.x || e.screenY !== lastScreen.y) {
+          $(this).data("profvis").flameGraph.enableZoom();
+          lastScreen = { x: null, y: null };
+        }
+      })
+      .on("mousedown", ".profvis", function(e) {
+        // Clicking always enables zooming.
+        $(this).data("profvis").flameGraph.enableZoom();
+        lastScreen = { x: null, y: null };
+      })
+      .on("mouseleave", ".profvis", function(e) {
+        $(this).data("profvis").flameGraph.disableZoom();
+      });
+  })();
+
+  return profvis;
+})();
+</script>
+<script>(function() {
+
+  // Polyfill for scrollIntoViewIfNeeded()
+  // From https://gist.github.com/jocki84/6ffafd003387179a988e
+  // License: ISC
+  if (!Element.prototype.scrollIntoViewIfNeeded) {
+    Element.prototype.scrollIntoViewIfNeeded = function (centerIfNeeded) {
+      "use strict";
+
+      function makeRange(start, length) {
+        return {"start": start, "length": length, "end": start + length};
+      }
+
+      function coverRange(inner, outer) {
+        if (
+          false === centerIfNeeded ||
+          (outer.start < inner.end && inner.start < outer.end)
+        ) {
+          return Math.max(
+              inner.end - outer.length,
+              Math.min(outer.start, inner.start)
+          );
+        }
+        return (inner.start + inner.end - outer.length) / 2;
+      }
+
+      function makePoint(x, y) {
+        return {
+          "x": x,
+          "y": y,
+          "translate": function translate(dX, dY) {
+            return makePoint(x + dX, y + dY);
+          }
+        };
+      }
+
+      function absolute(elem, pt) {
+        while (elem) {
+          pt = pt.translate(elem.offsetLeft, elem.offsetTop);
+          elem = elem.offsetParent;
+        }
+        return pt;
+      }
+
+      var target = absolute(this, makePoint(0, 0)),
+          extent = makePoint(this.offsetWidth, this.offsetHeight),
+          elem = this.parentNode,
+          origin;
+
+      while (elem instanceof HTMLElement) {
+        // Apply desired scroll amount.
+        origin = absolute(elem, makePoint(elem.clientLeft, elem.clientTop));
+        elem.scrollLeft = coverRange(
+          makeRange(target.x - origin.x, extent.x),
+          makeRange(elem.scrollLeft, elem.clientWidth)
+        );
+        elem.scrollTop = coverRange(
+          makeRange(target.y - origin.y, extent.y),
+          makeRange(elem.scrollTop, elem.clientHeight)
+        );
+
+        // Determine actual scroll amount by reading back scroll properties.
+        target = target.translate(-elem.scrollLeft, -elem.scrollTop);
+        elem = elem.parentNode;
+      }
+    };
+  }
+
+})()</script>
+<style type="text/css">.profvis-code span.hljs-operator,
+.profvis-code span.hljs-paren {
+color: rgb(104, 118, 135)
+}
+.profvis-code span.hljs-literal {
+color: rgb(88, 72, 246)
+}
+.profvis-code span.hljs-number {
+color: rgb(0, 0, 205);
+}
+.profvis-code span.hljs-comment {
+color: rgb(76, 136, 107);
+}
+.profvis-code span.hljs-keyword {
+color: rgb(0, 0, 255);
+}
+.profvis-code span.hljs-identifier {
+color: rgb(0, 0, 0);
+}
+.profvis-code span.hljs-string {
+color: rgb(3, 106, 7);
+}
+</style>
+<script>/*!
+  Highlight.js v11.10.0 (git: 366a8bd012)
+  (c) 2006-2024 Josh Goebel <hello@joshgoebel.com> and other contributors
+  License: BSD-3-Clause
+ */
+var hljs=function(){"use strict";function e(t){
+return t instanceof Map?t.clear=t.delete=t.set=()=>{
+throw Error("map is read-only")}:t instanceof Set&&(t.add=t.clear=t.delete=()=>{
+throw Error("set is read-only")
+}),Object.freeze(t),Object.getOwnPropertyNames(t).forEach((n=>{
+const i=t[n],s=typeof i;"object"!==s&&"function"!==s||Object.isFrozen(i)||e(i)
+})),t}class t{constructor(e){
+void 0===e.data&&(e.data={}),this.data=e.data,this.isMatchIgnored=!1}
+ignoreMatch(){this.isMatchIgnored=!0}}function n(e){
+return e.replace(/&/g,"&amp;").replace(/</g,"&lt;").replace(/>/g,"&gt;").replace(/"/g,"&quot;").replace(/'/g,"&#x27;")
+}function i(e,...t){const n=Object.create(null);for(const t in e)n[t]=e[t]
+;return t.forEach((e=>{for(const t in e)n[t]=e[t]})),n}const s=e=>!!e.scope
+;class o{constructor(e,t){
+this.buffer="",this.classPrefix=t.classPrefix,e.walk(this)}addText(e){
+this.buffer+=n(e)}openNode(e){if(!s(e))return;const t=((e,{prefix:t})=>{
+if(e.startsWith("language:"))return e.replace("language:","language-")
+;if(e.includes(".")){const n=e.split(".")
+;return[`${t}${n.shift()}`,...n.map(((e,t)=>`${e}${"_".repeat(t+1)}`))].join(" ")
+}return`${t}${e}`})(e.scope,{prefix:this.classPrefix});this.span(t)}
+closeNode(e){s(e)&&(this.buffer+="</span>")}value(){return this.buffer}span(e){
+this.buffer+=`<span class="${e}">`}}const r=(e={})=>{const t={children:[]}
+;return Object.assign(t,e),t};class a{constructor(){
+this.rootNode=r(),this.stack=[this.rootNode]}get top(){
+return this.stack[this.stack.length-1]}get root(){return this.rootNode}add(e){
+this.top.children.push(e)}openNode(e){const t=r({scope:e})
+;this.add(t),this.stack.push(t)}closeNode(){
+if(this.stack.length>1)return this.stack.pop()}closeAllNodes(){
+for(;this.closeNode(););}toJSON(){return JSON.stringify(this.rootNode,null,4)}
+walk(e){return this.constructor._walk(e,this.rootNode)}static _walk(e,t){
+return"string"==typeof t?e.addText(t):t.children&&(e.openNode(t),
+t.children.forEach((t=>this._walk(e,t))),e.closeNode(t)),e}static _collapse(e){
+"string"!=typeof e&&e.children&&(e.children.every((e=>"string"==typeof e))?e.children=[e.children.join("")]:e.children.forEach((e=>{
+a._collapse(e)})))}}class c extends a{constructor(e){super(),this.options=e}
+addText(e){""!==e&&this.add(e)}startScope(e){this.openNode(e)}endScope(){
+this.closeNode()}__addSublanguage(e,t){const n=e.root
+;t&&(n.scope="language:"+t),this.add(n)}toHTML(){
+return new o(this,this.options).value()}finalize(){
+return this.closeAllNodes(),!0}}function l(e){
+return e?"string"==typeof e?e:e.source:null}function g(e){return h("(?=",e,")")}
+function u(e){return h("(?:",e,")*")}function d(e){return h("(?:",e,")?")}
+function h(...e){return e.map((e=>l(e))).join("")}function f(...e){const t=(e=>{
+const t=e[e.length-1]
+;return"object"==typeof t&&t.constructor===Object?(e.splice(e.length-1,1),t):{}
+})(e);return"("+(t.capture?"":"?:")+e.map((e=>l(e))).join("|")+")"}
+function p(e){return RegExp(e.toString()+"|").exec("").length-1}
+const b=/\[(?:[^\\\]]|\\.)*\]|\(\??|\\([1-9][0-9]*)|\\./
+;function m(e,{joinWith:t}){let n=0;return e.map((e=>{n+=1;const t=n
+;let i=l(e),s="";for(;i.length>0;){const e=b.exec(i);if(!e){s+=i;break}
+s+=i.substring(0,e.index),
+i=i.substring(e.index+e[0].length),"\\"===e[0][0]&&e[1]?s+="\\"+(Number(e[1])+t):(s+=e[0],
+"("===e[0]&&n++)}return s})).map((e=>`(${e})`)).join(t)}
+const E="[a-zA-Z]\\w*",x="[a-zA-Z_]\\w*",w="\\b\\d+(\\.\\d+)?",y="(-?)(\\b0[xX][a-fA-F0-9]+|(\\b\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)",_="\\b(0b[01]+)",O={
+begin:"\\\\[\\s\\S]",relevance:0},v={scope:"string",begin:"'",end:"'",
+illegal:"\\n",contains:[O]},k={scope:"string",begin:'"',end:'"',illegal:"\\n",
+contains:[O]},N=(e,t,n={})=>{const s=i({scope:"comment",begin:e,end:t,
+contains:[]},n);s.contains.push({scope:"doctag",
+begin:"[ ]*(?=(TODO|FIXME|NOTE|BUG|OPTIMIZE|HACK|XXX):)",
+end:/(TODO|FIXME|NOTE|BUG|OPTIMIZE|HACK|XXX):/,excludeBegin:!0,relevance:0})
+;const o=f("I","a","is","so","us","to","at","if","in","it","on",/[A-Za-z]+['](d|ve|re|ll|t|s|n)/,/[A-Za-z]+[-][a-z]+/,/[A-Za-z][a-z]{2,}/)
+;return s.contains.push({begin:h(/[ ]+/,"(",o,/[.]?[:]?([.][ ]|[ ])/,"){3}")}),s
+},S=N("//","$"),M=N("/\\*","\\*/"),R=N("#","$");var j=Object.freeze({
+__proto__:null,APOS_STRING_MODE:v,BACKSLASH_ESCAPE:O,BINARY_NUMBER_MODE:{
+scope:"number",begin:_,relevance:0},BINARY_NUMBER_RE:_,COMMENT:N,
+C_BLOCK_COMMENT_MODE:M,C_LINE_COMMENT_MODE:S,C_NUMBER_MODE:{scope:"number",
+begin:y,relevance:0},C_NUMBER_RE:y,END_SAME_AS_BEGIN:e=>Object.assign(e,{
+"on:begin":(e,t)=>{t.data._beginMatch=e[1]},"on:end":(e,t)=>{
+t.data._beginMatch!==e[1]&&t.ignoreMatch()}}),HASH_COMMENT_MODE:R,IDENT_RE:E,
+MATCH_NOTHING_RE:/\b\B/,METHOD_GUARD:{begin:"\\.\\s*"+x,relevance:0},
+NUMBER_MODE:{scope:"number",begin:w,relevance:0},NUMBER_RE:w,
+PHRASAL_WORDS_MODE:{
+begin:/\b(a|an|the|are|I'm|isn't|don't|doesn't|won't|but|just|should|pretty|simply|enough|gonna|going|wtf|so|such|will|you|your|they|like|more)\b/
+},QUOTE_STRING_MODE:k,REGEXP_MODE:{scope:"regexp",begin:/\/(?=[^/\n]*\/)/,
+end:/\/[gimuy]*/,contains:[O,{begin:/\[/,end:/\]/,relevance:0,contains:[O]}]},
+RE_STARTERS_RE:"!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|-|-=|/=|/|:|;|<<|<<=|<=|<|===|==|=|>>>=|>>=|>=|>>>|>>|>|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~",
+SHEBANG:(e={})=>{const t=/^#![ ]*\//
+;return e.binary&&(e.begin=h(t,/.*\b/,e.binary,/\b.*/)),i({scope:"meta",begin:t,
+end:/$/,relevance:0,"on:begin":(e,t)=>{0!==e.index&&t.ignoreMatch()}},e)},
+TITLE_MODE:{scope:"title",begin:E,relevance:0},UNDERSCORE_IDENT_RE:x,
+UNDERSCORE_TITLE_MODE:{scope:"title",begin:x,relevance:0}});function A(e,t){
+"."===e.input[e.index-1]&&t.ignoreMatch()}function I(e,t){
+void 0!==e.className&&(e.scope=e.className,delete e.className)}function T(e,t){
+t&&e.beginKeywords&&(e.begin="\\b("+e.beginKeywords.split(" ").join("|")+")(?!\\.)(?=\\b|\\s)",
+e.__beforeBegin=A,e.keywords=e.keywords||e.beginKeywords,delete e.beginKeywords,
+void 0===e.relevance&&(e.relevance=0))}function L(e,t){
+Array.isArray(e.illegal)&&(e.illegal=f(...e.illegal))}function B(e,t){
+if(e.match){
+if(e.begin||e.end)throw Error("begin & end are not supported with match")
+;e.begin=e.match,delete e.match}}function P(e,t){
+void 0===e.relevance&&(e.relevance=1)}const D=(e,t)=>{if(!e.beforeMatch)return
+;if(e.starts)throw Error("beforeMatch cannot be used with starts")
+;const n=Object.assign({},e);Object.keys(e).forEach((t=>{delete e[t]
+})),e.keywords=n.keywords,e.begin=h(n.beforeMatch,g(n.begin)),e.starts={
+relevance:0,contains:[Object.assign(n,{endsParent:!0})]
+},e.relevance=0,delete n.beforeMatch
+},H=["of","and","for","in","not","or","if","then","parent","list","value"],C="keyword"
+;function $(e,t,n=C){const i=Object.create(null)
+;return"string"==typeof e?s(n,e.split(" ")):Array.isArray(e)?s(n,e):Object.keys(e).forEach((n=>{
+Object.assign(i,$(e[n],t,n))})),i;function s(e,n){
+t&&(n=n.map((e=>e.toLowerCase()))),n.forEach((t=>{const n=t.split("|")
+;i[n[0]]=[e,U(n[0],n[1])]}))}}function U(e,t){
+return t?Number(t):(e=>H.includes(e.toLowerCase()))(e)?0:1}const z={},W=e=>{
+console.error(e)},X=(e,...t)=>{console.log("WARN: "+e,...t)},G=(e,t)=>{
+z[`${e}/${t}`]||(console.log(`Deprecated as of ${e}. ${t}`),z[`${e}/${t}`]=!0)
+},K=Error();function F(e,t,{key:n}){let i=0;const s=e[n],o={},r={}
+;for(let e=1;e<=t.length;e++)r[e+i]=s[e],o[e+i]=!0,i+=p(t[e-1])
+;e[n]=r,e[n]._emit=o,e[n]._multi=!0}function Z(e){(e=>{
+e.scope&&"object"==typeof e.scope&&null!==e.scope&&(e.beginScope=e.scope,
+delete e.scope)})(e),"string"==typeof e.beginScope&&(e.beginScope={
+_wrap:e.beginScope}),"string"==typeof e.endScope&&(e.endScope={_wrap:e.endScope
+}),(e=>{if(Array.isArray(e.begin)){
+if(e.skip||e.excludeBegin||e.returnBegin)throw W("skip, excludeBegin, returnBegin not compatible with beginScope: {}"),
+K
+;if("object"!=typeof e.beginScope||null===e.beginScope)throw W("beginScope must be object"),
+K;F(e,e.begin,{key:"beginScope"}),e.begin=m(e.begin,{joinWith:""})}})(e),(e=>{
+if(Array.isArray(e.end)){
+if(e.skip||e.excludeEnd||e.returnEnd)throw W("skip, excludeEnd, returnEnd not compatible with endScope: {}"),
+K
+;if("object"!=typeof e.endScope||null===e.endScope)throw W("endScope must be object"),
+K;F(e,e.end,{key:"endScope"}),e.end=m(e.end,{joinWith:""})}})(e)}function V(e){
+function t(t,n){
+return RegExp(l(t),"m"+(e.case_insensitive?"i":"")+(e.unicodeRegex?"u":"")+(n?"g":""))
+}class n{constructor(){
+this.matchIndexes={},this.regexes=[],this.matchAt=1,this.position=0}
+addRule(e,t){
+t.position=this.position++,this.matchIndexes[this.matchAt]=t,this.regexes.push([t,e]),
+this.matchAt+=p(e)+1}compile(){0===this.regexes.length&&(this.exec=()=>null)
+;const e=this.regexes.map((e=>e[1]));this.matcherRe=t(m(e,{joinWith:"|"
+}),!0),this.lastIndex=0}exec(e){this.matcherRe.lastIndex=this.lastIndex
+;const t=this.matcherRe.exec(e);if(!t)return null
+;const n=t.findIndex(((e,t)=>t>0&&void 0!==e)),i=this.matchIndexes[n]
+;return t.splice(0,n),Object.assign(t,i)}}class s{constructor(){
+this.rules=[],this.multiRegexes=[],
+this.count=0,this.lastIndex=0,this.regexIndex=0}getMatcher(e){
+if(this.multiRegexes[e])return this.multiRegexes[e];const t=new n
+;return this.rules.slice(e).forEach((([e,n])=>t.addRule(e,n))),
+t.compile(),this.multiRegexes[e]=t,t}resumingScanAtSamePosition(){
+return 0!==this.regexIndex}considerAll(){this.regexIndex=0}addRule(e,t){
+this.rules.push([e,t]),"begin"===t.type&&this.count++}exec(e){
+const t=this.getMatcher(this.regexIndex);t.lastIndex=this.lastIndex
+;let n=t.exec(e)
+;if(this.resumingScanAtSamePosition())if(n&&n.index===this.lastIndex);else{
+const t=this.getMatcher(0);t.lastIndex=this.lastIndex+1,n=t.exec(e)}
+return n&&(this.regexIndex+=n.position+1,
+this.regexIndex===this.count&&this.considerAll()),n}}
+if(e.compilerExtensions||(e.compilerExtensions=[]),
+e.contains&&e.contains.includes("self"))throw Error("ERR: contains `self` is not supported at the top-level of a language.  See documentation.")
+;return e.classNameAliases=i(e.classNameAliases||{}),function n(o,r){const a=o
+;if(o.isCompiled)return a
+;[I,B,Z,D].forEach((e=>e(o,r))),e.compilerExtensions.forEach((e=>e(o,r))),
+o.__beforeBegin=null,[T,L,P].forEach((e=>e(o,r))),o.isCompiled=!0;let c=null
+;return"object"==typeof o.keywords&&o.keywords.$pattern&&(o.keywords=Object.assign({},o.keywords),
+c=o.keywords.$pattern,
+delete o.keywords.$pattern),c=c||/\w+/,o.keywords&&(o.keywords=$(o.keywords,e.case_insensitive)),
+a.keywordPatternRe=t(c,!0),
+r&&(o.begin||(o.begin=/\B|\b/),a.beginRe=t(a.begin),o.end||o.endsWithParent||(o.end=/\B|\b/),
+o.end&&(a.endRe=t(a.end)),
+a.terminatorEnd=l(a.end)||"",o.endsWithParent&&r.terminatorEnd&&(a.terminatorEnd+=(o.end?"|":"")+r.terminatorEnd)),
+o.illegal&&(a.illegalRe=t(o.illegal)),
+o.contains||(o.contains=[]),o.contains=[].concat(...o.contains.map((e=>(e=>(e.variants&&!e.cachedVariants&&(e.cachedVariants=e.variants.map((t=>i(e,{
+variants:null},t)))),e.cachedVariants?e.cachedVariants:q(e)?i(e,{
+starts:e.starts?i(e.starts):null
+}):Object.isFrozen(e)?i(e):e))("self"===e?o:e)))),o.contains.forEach((e=>{n(e,a)
+})),o.starts&&n(o.starts,r),a.matcher=(e=>{const t=new s
+;return e.contains.forEach((e=>t.addRule(e.begin,{rule:e,type:"begin"
+}))),e.terminatorEnd&&t.addRule(e.terminatorEnd,{type:"end"
+}),e.illegal&&t.addRule(e.illegal,{type:"illegal"}),t})(a),a}(e)}function q(e){
+return!!e&&(e.endsWithParent||q(e.starts))}class J extends Error{
+constructor(e,t){super(e),this.name="HTMLInjectionError",this.html=t}}
+const Y=n,Q=i,ee=Symbol("nomatch"),te=n=>{
+const i=Object.create(null),s=Object.create(null),o=[];let r=!0
+;const a="Could not find the language '{}', did you forget to load/include a language module?",l={
+disableAutodetect:!0,name:"Plain text",contains:[]};let p={
+ignoreUnescapedHTML:!1,throwUnescapedHTML:!1,noHighlightRe:/^(no-?highlight)$/i,
+languageDetectRe:/\blang(?:uage)?-([\w-]+)\b/i,classPrefix:"hljs-",
+cssSelector:"pre code",languages:null,__emitter:c};function b(e){
+return p.noHighlightRe.test(e)}function m(e,t,n){let i="",s=""
+;"object"==typeof t?(i=e,
+n=t.ignoreIllegals,s=t.language):(G("10.7.0","highlight(lang, code, ...args) has been deprecated."),
+G("10.7.0","Please use highlight(code, options) instead.\nhttps://github.com/highlightjs/highlight.js/issues/2277"),
+s=e,i=t),void 0===n&&(n=!0);const o={code:i,language:s};N("before:highlight",o)
+;const r=o.result?o.result:E(o.language,o.code,n)
+;return r.code=o.code,N("after:highlight",r),r}function E(e,n,s,o){
+const c=Object.create(null);function l(){if(!N.keywords)return void M.addText(R)
+;let e=0;N.keywordPatternRe.lastIndex=0;let t=N.keywordPatternRe.exec(R),n=""
+;for(;t;){n+=R.substring(e,t.index)
+;const s=_.case_insensitive?t[0].toLowerCase():t[0],o=(i=s,N.keywords[i]);if(o){
+const[e,i]=o
+;if(M.addText(n),n="",c[s]=(c[s]||0)+1,c[s]<=7&&(j+=i),e.startsWith("_"))n+=t[0];else{
+const n=_.classNameAliases[e]||e;u(t[0],n)}}else n+=t[0]
+;e=N.keywordPatternRe.lastIndex,t=N.keywordPatternRe.exec(R)}var i
+;n+=R.substring(e),M.addText(n)}function g(){null!=N.subLanguage?(()=>{
+if(""===R)return;let e=null;if("string"==typeof N.subLanguage){
+if(!i[N.subLanguage])return void M.addText(R)
+;e=E(N.subLanguage,R,!0,S[N.subLanguage]),S[N.subLanguage]=e._top
+}else e=x(R,N.subLanguage.length?N.subLanguage:null)
+;N.relevance>0&&(j+=e.relevance),M.__addSublanguage(e._emitter,e.language)
+})():l(),R=""}function u(e,t){
+""!==e&&(M.startScope(t),M.addText(e),M.endScope())}function d(e,t){let n=1
+;const i=t.length-1;for(;n<=i;){if(!e._emit[n]){n++;continue}
+const i=_.classNameAliases[e[n]]||e[n],s=t[n];i?u(s,i):(R=s,l(),R=""),n++}}
+function h(e,t){
+return e.scope&&"string"==typeof e.scope&&M.openNode(_.classNameAliases[e.scope]||e.scope),
+e.beginScope&&(e.beginScope._wrap?(u(R,_.classNameAliases[e.beginScope._wrap]||e.beginScope._wrap),
+R=""):e.beginScope._multi&&(d(e.beginScope,t),R="")),N=Object.create(e,{parent:{
+value:N}}),N}function f(e,n,i){let s=((e,t)=>{const n=e&&e.exec(t)
+;return n&&0===n.index})(e.endRe,i);if(s){if(e["on:end"]){const i=new t(e)
+;e["on:end"](n,i),i.isMatchIgnored&&(s=!1)}if(s){
+for(;e.endsParent&&e.parent;)e=e.parent;return e}}
+if(e.endsWithParent)return f(e.parent,n,i)}function b(e){
+return 0===N.matcher.regexIndex?(R+=e[0],1):(T=!0,0)}function m(e){
+const t=e[0],i=n.substring(e.index),s=f(N,e,i);if(!s)return ee;const o=N
+;N.endScope&&N.endScope._wrap?(g(),
+u(t,N.endScope._wrap)):N.endScope&&N.endScope._multi?(g(),
+d(N.endScope,e)):o.skip?R+=t:(o.returnEnd||o.excludeEnd||(R+=t),
+g(),o.excludeEnd&&(R=t));do{
+N.scope&&M.closeNode(),N.skip||N.subLanguage||(j+=N.relevance),N=N.parent
+}while(N!==s.parent);return s.starts&&h(s.starts,e),o.returnEnd?0:t.length}
+let w={};function y(i,o){const a=o&&o[0];if(R+=i,null==a)return g(),0
+;if("begin"===w.type&&"end"===o.type&&w.index===o.index&&""===a){
+if(R+=n.slice(o.index,o.index+1),!r){const t=Error(`0 width match regex (${e})`)
+;throw t.languageName=e,t.badRule=w.rule,t}return 1}
+if(w=o,"begin"===o.type)return(e=>{
+const n=e[0],i=e.rule,s=new t(i),o=[i.__beforeBegin,i["on:begin"]]
+;for(const t of o)if(t&&(t(e,s),s.isMatchIgnored))return b(n)
+;return i.skip?R+=n:(i.excludeBegin&&(R+=n),
+g(),i.returnBegin||i.excludeBegin||(R=n)),h(i,e),i.returnBegin?0:n.length})(o)
+;if("illegal"===o.type&&!s){
+const e=Error('Illegal lexeme "'+a+'" for mode "'+(N.scope||"<unnamed>")+'"')
+;throw e.mode=N,e}if("end"===o.type){const e=m(o);if(e!==ee)return e}
+if("illegal"===o.type&&""===a)return 1
+;if(I>1e5&&I>3*o.index)throw Error("potential infinite loop, way more iterations than matches")
+;return R+=a,a.length}const _=O(e)
+;if(!_)throw W(a.replace("{}",e)),Error('Unknown language: "'+e+'"')
+;const v=V(_);let k="",N=o||v;const S={},M=new p.__emitter(p);(()=>{const e=[]
+;for(let t=N;t!==_;t=t.parent)t.scope&&e.unshift(t.scope)
+;e.forEach((e=>M.openNode(e)))})();let R="",j=0,A=0,I=0,T=!1;try{
+if(_.__emitTokens)_.__emitTokens(n,M);else{for(N.matcher.considerAll();;){
+I++,T?T=!1:N.matcher.considerAll(),N.matcher.lastIndex=A
+;const e=N.matcher.exec(n);if(!e)break;const t=y(n.substring(A,e.index),e)
+;A=e.index+t}y(n.substring(A))}return M.finalize(),k=M.toHTML(),{language:e,
+value:k,relevance:j,illegal:!1,_emitter:M,_top:N}}catch(t){
+if(t.message&&t.message.includes("Illegal"))return{language:e,value:Y(n),
+illegal:!0,relevance:0,_illegalBy:{message:t.message,index:A,
+context:n.slice(A-100,A+100),mode:t.mode,resultSoFar:k},_emitter:M};if(r)return{
+language:e,value:Y(n),illegal:!1,relevance:0,errorRaised:t,_emitter:M,_top:N}
+;throw t}}function x(e,t){t=t||p.languages||Object.keys(i);const n=(e=>{
+const t={value:Y(e),illegal:!1,relevance:0,_top:l,_emitter:new p.__emitter(p)}
+;return t._emitter.addText(e),t})(e),s=t.filter(O).filter(k).map((t=>E(t,e,!1)))
+;s.unshift(n);const o=s.sort(((e,t)=>{
+if(e.relevance!==t.relevance)return t.relevance-e.relevance
+;if(e.language&&t.language){if(O(e.language).supersetOf===t.language)return 1
+;if(O(t.language).supersetOf===e.language)return-1}return 0})),[r,a]=o,c=r
+;return c.secondBest=a,c}function w(e){let t=null;const n=(e=>{
+let t=e.className+" ";t+=e.parentNode?e.parentNode.className:""
+;const n=p.languageDetectRe.exec(t);if(n){const t=O(n[1])
+;return t||(X(a.replace("{}",n[1])),
+X("Falling back to no-highlight mode for this block.",e)),t?n[1]:"no-highlight"}
+return t.split(/\s+/).find((e=>b(e)||O(e)))})(e);if(b(n))return
+;if(N("before:highlightElement",{el:e,language:n
+}),e.dataset.highlighted)return void console.log("Element previously highlighted. To highlight again, first unset `dataset.highlighted`.",e)
+;if(e.children.length>0&&(p.ignoreUnescapedHTML||(console.warn("One of your code blocks includes unescaped HTML. This is a potentially serious security risk."),
+console.warn("https://github.com/highlightjs/highlight.js/wiki/security"),
+console.warn("The element with unescaped HTML:"),
+console.warn(e)),p.throwUnescapedHTML))throw new J("One of your code blocks includes unescaped HTML.",e.innerHTML)
+;t=e;const i=t.textContent,o=n?m(i,{language:n,ignoreIllegals:!0}):x(i)
+;e.innerHTML=o.value,e.dataset.highlighted="yes",((e,t,n)=>{const i=t&&s[t]||n
+;e.classList.add("hljs"),e.classList.add("language-"+i)
+})(e,n,o.language),e.result={language:o.language,re:o.relevance,
+relevance:o.relevance},o.secondBest&&(e.secondBest={
+language:o.secondBest.language,relevance:o.secondBest.relevance
+}),N("after:highlightElement",{el:e,result:o,text:i})}let y=!1;function _(){
+"loading"!==document.readyState?document.querySelectorAll(p.cssSelector).forEach(w):y=!0
+}function O(e){return e=(e||"").toLowerCase(),i[e]||i[s[e]]}
+function v(e,{languageName:t}){"string"==typeof e&&(e=[e]),e.forEach((e=>{
+s[e.toLowerCase()]=t}))}function k(e){const t=O(e)
+;return t&&!t.disableAutodetect}function N(e,t){const n=e;o.forEach((e=>{
+e[n]&&e[n](t)}))}
+"undefined"!=typeof window&&window.addEventListener&&window.addEventListener("DOMContentLoaded",(()=>{
+y&&_()}),!1),Object.assign(n,{highlight:m,highlightAuto:x,highlightAll:_,
+highlightElement:w,
+highlightBlock:e=>(G("10.7.0","highlightBlock will be removed entirely in v12.0"),
+G("10.7.0","Please use highlightElement now."),w(e)),configure:e=>{p=Q(p,e)},
+initHighlighting:()=>{
+_(),G("10.6.0","initHighlighting() deprecated.  Use highlightAll() now.")},
+initHighlightingOnLoad:()=>{
+_(),G("10.6.0","initHighlightingOnLoad() deprecated.  Use highlightAll() now.")
+},registerLanguage:(e,t)=>{let s=null;try{s=t(n)}catch(t){
+if(W("Language definition for '{}' could not be registered.".replace("{}",e)),
+!r)throw t;W(t),s=l}
+s.name||(s.name=e),i[e]=s,s.rawDefinition=t.bind(null,n),s.aliases&&v(s.aliases,{
+languageName:e})},unregisterLanguage:e=>{delete i[e]
+;for(const t of Object.keys(s))s[t]===e&&delete s[t]},
+listLanguages:()=>Object.keys(i),getLanguage:O,registerAliases:v,
+autoDetection:k,inherit:Q,addPlugin:e=>{(e=>{
+e["before:highlightBlock"]&&!e["before:highlightElement"]&&(e["before:highlightElement"]=t=>{
+e["before:highlightBlock"](Object.assign({block:t.el},t))
+}),e["after:highlightBlock"]&&!e["after:highlightElement"]&&(e["after:highlightElement"]=t=>{
+e["after:highlightBlock"](Object.assign({block:t.el},t))})})(e),o.push(e)},
+removePlugin:e=>{const t=o.indexOf(e);-1!==t&&o.splice(t,1)}}),n.debugMode=()=>{
+r=!1},n.safeMode=()=>{r=!0},n.versionString="11.10.0",n.regex={concat:h,
+lookahead:g,either:f,optional:d,anyNumberOfTimes:u}
+;for(const t in j)"object"==typeof j[t]&&e(j[t]);return Object.assign(n,j),n
+},ne=te({});return ne.newInstance=()=>te({}),ne}()
+;"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=hljs);/*! `r` grammar compiled for Highlight.js 11.10.0 */
+(()=>{var e=(()=>{"use strict";return e=>{
+const a=e.regex,n=/(?:(?:[a-zA-Z]|\.[._a-zA-Z])[._a-zA-Z0-9]*)|\.(?!\d)/,i=a.either(/0[xX][0-9a-fA-F]+\.[0-9a-fA-F]*[pP][+-]?\d+i?/,/0[xX][0-9a-fA-F]+(?:[pP][+-]?\d+)?[Li]?/,/(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][+-]?\d+)?[Li]?/),s=/[=!<>:]=|\|\||&&|:::?|<-|<<-|->>|->|\|>|[-+*\/?!$&|:<=>@^~]|\*\*/,t=a.either(/[()]/,/[{}]/,/\[\[/,/[[\]]/,/\\/,/,/)
+;return{name:"R",keywords:{$pattern:n,
+keyword:"function if in break next repeat else for while",
+literal:"NULL NA TRUE FALSE Inf NaN NA_integer_|10 NA_real_|10 NA_character_|10 NA_complex_|10",
+built_in:"LETTERS letters month.abb month.name pi T F abs acos acosh all any anyNA Arg as.call as.character as.complex as.double as.environment as.integer as.logical as.null.default as.numeric as.raw asin asinh atan atanh attr attributes baseenv browser c call ceiling class Conj cos cosh cospi cummax cummin cumprod cumsum digamma dim dimnames emptyenv exp expression floor forceAndCall gamma gc.time globalenv Im interactive invisible is.array is.atomic is.call is.character is.complex is.double is.environment is.expression is.finite is.function is.infinite is.integer is.language is.list is.logical is.matrix is.na is.name is.nan is.null is.numeric is.object is.pairlist is.raw is.recursive is.single is.symbol lazyLoadDBfetch length lgamma list log max min missing Mod names nargs nzchar oldClass on.exit pos.to.env proc.time prod quote range Re rep retracemem return round seq_along seq_len seq.int sign signif sin sinh sinpi sqrt standardGeneric substitute sum switch tan tanh tanpi tracemem trigamma trunc unclass untracemem UseMethod xtfrm"
+},contains:[e.COMMENT(/#'/,/$/,{contains:[{scope:"doctag",match:/@examples/,
+starts:{end:a.lookahead(a.either(/\n^#'\s*(?=@[a-zA-Z]+)/,/\n^(?!#')/)),
+endsParent:!0}},{scope:"doctag",begin:"@param",end:/$/,contains:[{
+scope:"variable",variants:[{match:n},{match:/`(?:\\.|[^`\\])+`/}],endsParent:!0
+}]},{scope:"doctag",match:/@[a-zA-Z]+/},{scope:"keyword",match:/\\[a-zA-Z]+/}]
+}),e.HASH_COMMENT_MODE,{scope:"string",contains:[e.BACKSLASH_ESCAPE],
+variants:[e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\(/,end:/\)(-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\{/,end:/\}(-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]"(-*)\[/,end:/\](-*)"/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\(/,end:/\)(-*)'/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\{/,end:/\}(-*)'/
+}),e.END_SAME_AS_BEGIN({begin:/[rR]'(-*)\[/,end:/\](-*)'/}),{begin:'"',end:'"',
+relevance:0},{begin:"'",end:"'",relevance:0}]},{relevance:0,variants:[{scope:{
+1:"operator",2:"number"},match:[s,i]},{scope:{1:"operator",2:"number"},
+match:[/%[^%]*%/,i]},{scope:{1:"punctuation",2:"number"},match:[t,i]},{scope:{
+2:"number"},match:[/[^a-zA-Z0-9._]|^/,i]}]},{scope:{3:"operator"},
+match:[n,/\s+/,/<-/,/\s+/]},{scope:"operator",relevance:0,variants:[{match:s},{
+match:/%[^%]*%/}]},{scope:"punctuation",relevance:0,match:t},{begin:"`",end:"`",
+contains:[{begin:/\\./}]}]}}})();hljs.registerLanguage("r",e)})();</script>
+<script>HTMLWidgets.widget({
+
+  name: 'profvis',
+
+  type: 'output',
+
+  initialize: function(el, width, height) {
+
+    return {
+      // TODO: add instance fields as required
+    };
+
+  },
+
+  renderValue: function(el, x, instance) {
+    profvis.render(el, x.message);
+  },
+
+  resize: function(el, width, height, instance) {
+
+  }
+
+});
+</script>
+
+</head>
+<body style="background-color: white;">
+<div id="htmlwidget_container">
+  <div class="profvis html-widget html-fill-item" id="htmlwidget-fe773d8b3d0235254c42" style="width:960px;height:500px;"></div>
+</div>
+<script type="application/json" data-for="htmlwidget-fe773d8b3d0235254c42">{"x":{"message":{"prof":{"time":[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,12,12,12,13,13,13,13,13,13,14,14,15,15,15,15,15,15,15,15,15,15,15,15,15,16,16,16,16,17,17,17,17,17,17,17,17,17,17,17,17,17,18,18,19,19,20,20,20,20,20,20,20,20,20,20,20,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,29,29,30,30,31,31,32,32,32,32,32,32,33,33,34,34,35,35,36,36,37,37,38,38,39,39,40,40,41,41,42,42,43,43,44,44,45,45,46,46,47,47,47,47,47,47,47,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,50,50,51,51,51,52,53,53,53,53,53,53,53,53,53,53,53,54,54,54,54,54,54,54,54,54,55,55,55,55,55,55,55,55,55,55,55,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,56,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,57,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,58,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,59,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,60,61,61,61,61,61,61,61,61,61,61,61,61,61,61,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,62,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,63,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,64,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,65,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,66,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,68,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,69,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,70,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,71,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,72,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,73,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,74,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,75,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,76,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,77,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,79,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,80,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,81,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,82,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,83,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,84,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,85,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,86,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,87,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,88,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,89,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,91,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,92,93,93,93,93,93,93,94,94,95,95,95,96,96,97,97,97,97,97,97,97,98,98,98,98,98,98,98,99,99,99,99,99,99,100,101,101,101,101,101,101,101,101,101,102,102,102,102,102,102,102,102,102,103,103,103,104,104,105,105,106,106,107,107,107,107,107,107,108,108,109,109,110,110,111,111,112,112,112,112,112,112,112,112,112,113,113,113,114,114,114,114,114,114,114,114,114,114,115,115,115,115,115,115,115,115,116,116,116,116,116,116,116,117,117,117,117,117,117,117,118,118,118,118,118,118,118,119,119,119,119,119,119,119,120,120,120,120,120,120,120,121,121,122,122,122,123,123,124,124,124,124,124,124,124,125,125,126,126,127,127,128,128,129,129,130,130,131,131,132,132,132,133,133,134,134,135,135,136,136,137,137,138,138,139,139,140,140,141,141,141,142,142,143,143,144,144,145,145,146,146,146,146,146,146,146,147,147,148,148,149,149,149,149,150,150,151,151,152,152,153,153,154,154,154,154,154,154,154,154,155,155,156,156,157,157,158,158,159,159,160,160,161,161,162,162,163,163,164,164,165,165,165,166,166,166,166,166,166,166,166,167,167,167,167,167,168,168,168,168,168,168,168,169,169,169,169,169,169,169,170,170,170,170,170,170,170,171,171,171,171,171,171,171,171,171,171,171,171,172,172,172,172,172,172,172,173,173,174,174,174,174,174,174,174,174,174,174,174,174,174,174,175,175,175,175,175,175,175,175,175,175,176,176,176,176,176,176,176,176,177,177,178,178,178,178,178,178,178,178,178,178,179,179,180,180,181,181,181,181,181,181,181,182,182,182,183,183,183,183,183,183,183,183,183,184,184,184,184,184,184,185,185,185,185,185,185,185,185,186,186,186,186,186,186,186,186,186,186,186,186,186,187,187,187,187,187,187,187,188,188,188,188,188,188,188,188,189,189,189,189,189,190,190,191,191,192,192,193,193,193,193,193,193,193,193,194,194,194,194,195,195,196,196,197,197,198,198,198,198,198,198,198,199,199,200,200,201,201,202,202,202,202,202,203,203,204,204,205,205,206,206,207,207,208,208,209,209,210,210,210,210,210,210,210,210,211,211,212,212,213,213,214,214,214,214,214,214,214,214,215,215,215,215,215,215,215,215,215,215,215,215,215,215,215,215,215,216,216,216,216,216,216,216,216,216,216,216,216,216,216,216,216,216,216,216,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,217,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,218,219,219,219,220,220,220,220,220,221,221,221,221,221,221,221,221,221,221,221,221,221,221,221,222,222,222,222,222,222,223,223,224,224,224,224,224,224,225,225,225,225,225,225,225,225,225,225,226,226,226,226,226,227,227,228,228,229,229,230,230,231,231,232,232,233,233,234,234,235,235,236,236,237,237,238,238,239,239,240,240,241,241,242,242,243,243,244,244,244,244,244,244,244,244,244,244,245,245,245,245,245,245,245,245,245,245,245,245,245,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,246,247,247,247,247,247,247,247,247,247,247,247,247,247,247,247,247,247,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,248,249,249,249,249,249,249,250,250,250,250,250,251,251,252,252,253,253,254,254,254,254,254,254,254,254,255,255,255,255,255,255,255,255,255,255,256,256,256,256,256,256,256,256,257,257,257,257,257,257,257,257,258,258,258,258,258,259,259,260,260,261,261,261,261,261,261,261,261,261,261,261,262,263,263,264,265,265,265,266,266,266,267,267,267,268,268,268,269,269,269,270,270,270,271,271,271,272,272,272,273,273,273,274,274,274,275,275,275,276,276,276,277,277,277,278,278,278,279,279,279,280,280,280,280,280,280,280,281,281,281,281,281,281,281,282,282,283,283,283,283,283,283,283,284,284,285,285,285,285,285,285,285,285,285,285,285,285,285,286,286,286,286,286,286,286,286,286,286,286,286,287,287,288,288,289,289,290,290,290,290,290,290,290,290,291,291,291,291,291,291,291,292,292,292,292,292,292,292,292,292,293,293,293,294,294,294,294,294,294,294,294,294,295,295,295,295,295,295,295,295,295,295,295,295,295,296,296,297,297,298,298,299,299,300,300,301,301,302,302,303,303,304,304,305,305,306,306,307,307,308,308,308,308,308,308,308,308,309,309,310,310,311,311,312,312,313,313,314,314,315,315,316,316,317,317,318,318,319,319,320,320,321,321,322,322,322,322,322,322,323,323,324,324,325,325,326,326,327,327,328,328,329,329,330,330,331,331,332,332,333,333,334,334,335,335,336,336,337,337,338,338,339,339,340,340,341,341,341,341,341,341,342,342,342,342,342,342,343,343,343,343,343,343,343,343,343,344,344,344,344,344,344,345,345,345,345,345,345,345,345,345,346,346,346,346,346,347,347,347,347,347,347,347,347,348,348,349,349,349,349,349,349,349,349,350,350,351,351,351,351,351,351,351,352,352,353,353,353,353,353,353,353,353,353,353,353,353,353,354,354,354,354,354,354,354,354,354,354,354,354,354,354,355,355,355,355,356,356,357,357,357,357,357,357,358,358,359,359,360,360,360,360,360,360,361,361,361,361,361,361,361,361,362,362,363,363,363,363,363,363,363,363,363,364,364,365,365,365,365,366,366,367,367,367,367,367,367,368,368,368,368,368,368,369,369,369,369,370,370,371,371,372,372,372,372,373,373,374,374,375,375,376,376,377,377,378,378,379,379,379,379,379,379,379,380,380,381,381,382,382,382,382,383,383,384,384,385,385,385,385,385,385,385,385,386,386,387,387,388,388,389,389,389,390,390,390,390,390,391,391,391,392,392,392,393,393,393,393,393,393,393,393,393,394,394,395,395,395,395,395,395,396,396,396,396,396,396,396,396,396,396,396,396,396,397,397,397,397,397,397,397,398,398,398,398,398,398,398,398,399,399,399,399,399,399,399,400,400,400,400,400,400,400,400,401,401,401,401,401,401,401,402,402,402,402,402,402,403,403,404,404,405,405,405,405,405,405,406,406,406,406,406,406,406,406,407,407,407,407,407,407,407,407,408,408,408,408,408,408,409,409,409,409,409,409,409,410,410,411,411,411,411,411,412,412,412,412,412,413,413,413,413,413,413,413,413,414,414,414,414,414,414,414,414,414,414,414,414,414,415,415,415,415,415,415,416,416,416,416,416,416,416,416,416,417,417,417,417,417,417,417,417,418,418,418,418,418,418,418,418,418,418,418,418,418,419,419,420,420,421,421,421,422,422,422,422,422,422,422,422,422,422,423,423,423,423,423,423,423,424,424,425,425,426,426,427,427,428,428,429,429,430,430,431,431,432,432,432,432,432,432,433,433,434,434,435,435,436,436,437,437,438,438,439,439,440,440,441,441,442,442,443,443,444,444,445,445,446,446,447,447,447,447,447,448,448,448,448,448,449,449,450,450,451,451,452,452,453,453,454,454,455,455,456,456,457,457,458,458,459,459,460,460,461,461,461,461,461,462,462,462,462,462,463,463,463,463,463,464,464,465,465,466,466,467,467,467,467,467,467,467,468,468,468,468,468,468,468,469,469,469,469,469,469,470,470,470,471,471,471,471,471,471,471,471,471,472,472,472,472,472,472,473,473,474,474,474,474,474,474,474,474,474,474,474,474,474,475,475,476,476,476,476,476,476,476,477,477,478,478,479,479,479,479,479,479,479,480,480,481,481,481,481,481,481,481,482,482,482,482,482,482,482,483,483,483,483,483,483,483,483,484,484,484,484,484,484,484,484,485,485,485,485,486,486,486,486,486,486,486,486,487,487,487,487,488,488,488,488,488,488,488,489,489,489,489,490,490,490,490,490,490,490,490,490,491,491,491,491,491,491,492,492,493,493,493,493,493,493,493,493,493,493,493,493,493,493,493,494,494,495,495,495,495,495,495,495,495,495,495,496,496,496,496,496,496,496,497,497,497,497,497,497,497,497,497,497,497,497,497,498,498,499,499,500,500,500,500,500,500,500,500,500,501,501,502,502,503,503,504,504,505,505,506,506,507,507,507,507,507,507,507,507,508,508,509,509,510,510,511,511,511,511,512,512,513,513,514,514,515,515,515,516,516,517,517,518,518,519,519,520,520,520,520,520,520,521,521,522,522,522,522,522,522,523,523,523,523,523,523,523,524,524,524,524,524,524,524,524,524,524,524,525,525,525,525,525,525,525,525,525,526,526,526,526,526,526,526,526,527,527,527,527,527,527,528,528,528,528,528,529,529,529,529,529,529,529,529,529,530,530,530,530,530,530,530,531,531,531,531,531,531,531,531,532,532,532,532,532,532,532,532,533,533,533,533,533,533,534,534,534,534,534,534,534,535,535,535,535,535,535,535,535,536,536,536,536,536,536,536,536,536,536,536,536,536,536,537,537,537,537,537,537,537,537,537,537,538,538,538,539,539,539,540,540,540,540,540,540,541,541,541,541,541,541,541,541,541,542,542,542,542,542,542,542,542,542,542,542,542,542,543,543,544,544,544,544,544,544,544,545,545,545,545,545,545,545,546,546,547,547,547,547,547,547,547,548,548,549,549,549,549,549,549,550,550,550,550,550,550,550,550,551,551,551,551,551,551,551,551,551,552,552,552,552,552,552,553,553,554,554,555,555,556,556,557,557,558,558,559,559,560,560,561,561,562,562,563,563,564,564,565,565,565,565,565,565,565,566,566,567,567,568,568,569,569,570,570,571,571,571,572,572,573,573,574,574,575,575,576,576,576,576,576,576,576,576,576,577,577,578,578,579,579,580,580,581,581,582,582,583,583,584,584,585,585,586,586,586,586,586,586,586,586,586,587,587,587,587,587,587,587,588,588,588,589,589,590,590,590,590,590,590,590,591,591,591,591,591,591,591,591,592,592,592,592,592,592,592,592,592,593,593,594,594,594,594,594,594,595,595,595,595,595,595,595,595,595,595,595,595,595,596,596,596,596,596,596,596,596,597,597,597,598,598,599,599,599,599,599,599,599,599,600,600,600,601,601,601,601,601,601,601,602,602,603,603,603,603,603,603,604,604,605,605,605,605,605,605,606,606,607,607,608,608,608,608,608,608,608,608,609,609,609,609,609,610,610,610,610,610,610,610,611,611,612,612,612,612,612,612,612,612,613,613,613,613,613,613,613,613,614,614,615,615,616,616,617,617,618,618,619,619,620,620,621,621,622,622,623,623,624,624,625,625,626,626,627,627,628,628,629,629,630,630,631,631,632,632,632,633,633,634,634,635,635,636,636,636,637,637,637,637,637,637,637,638,638,638,639,639,640,640,640,640,640,640,640,641,641,641,641,641,641,641,641,641,641,642,642,643,643,644,644,644,644,644,644,644,645,645,645,646,646,647,647,647,647,647,647,648,648,648,648,648,648,648,649,649,650,650,650,650,650,650,650,651,651,651,651,651,651,652,652,652,652,652,652,653,653,653,653,653,653,653,653,653,653,654,654,655,655,655,655,656,656,656,656,656,656,656,657,657,657,657,657,657,657,657,658,658,658,658,658,658,658,659,659,659,659,659,659,659,659,660,660,660,660,660,660,661,661,661,661,661,661,661,661,661,661,662,662,662,662,662,662,662,662,662,662,662,662,662,662,663,663,663,663,663,663,663,664,664,664,664,664,664,664,665,665,666,667,667,667,668,668,668,668,668,668,668,668,669,669,669,669,669,669,670,670,671,671,671,671,671,671,671,671,672,672,673,673,674,674,675,675,676,676,677,677,678,678,679,679,680,680,680,680,680,681,681,682,682,683,683,684,684,685,685,686,686,686,686,686,686,686,686,687,687,688,688,689,689,689,690,690,691,691,692,692,693,693,694,694,695,695,696,696,697,697,697,698,698,699,699,700,700,701,701,702,702,703,703,704,704,705,705,706,706,707,707,708,708,709,709,710,710,711,711,712,712,713,713,713,714,714,715,715,715,715,715,715,715,716,716,716,716,716,716,716,716,717,717,718,718,718,718,718,718,718,718,719,719,719,719,719,719,719,719,719,720,720,720,720,720,720,720,721,721,721,721,721,721,722,722,723,723,724,724,725,725,725,725,725,725,725,726,726,726,726,726,726,726,726,726,727,727,727,727,727,727,728,728,728,728,728,728,728,729,729,729,729,729,729,729,730,730,730,730,730,731,731,732,732,732,732,732,732,732,732,733,733,734,734,734,734,734,735,735,736,736,737,737,737,737,737,737,738,739,739,740,740,740,740,741,741,742,742,743,743,744,744,744,744,744,744,744,744,744,745,745,745,745,745,745,745,745,745,746,746,746,746,746,746,746,746,747,747,747,747,747,747,747,747,748,748,748,748,748,748,749,749,749,749,749,749,749,750,750,751,751,752,752,752,753,753,754,754,755,755,756,756,757,757,758,758,759,759,760,760,760,761,761,761,761,762,762,763,763,764,764,765,765,766,766,767,767,768,768,768,768,768,768,768,769,769,769,769,769,769,769,770,770,770,770,771,771,771,772,772,772,772,772,772,773,773,773,773,773,773,774,774,774,774,774,774,775,775,775,775,775,775,775,776,776,776,777,777,777,778,778,779,779,780,780,780,780,780,780,780,781,781,782,782,782,783,783,783,783,783,783,783,784,784,784,784,784,784,784,784,785,785,785,786,786,786,786,786,787,787,787,787,787,787,787,787,788,788,789,789,790,790,790,790,790,790,790,790,790,790,790,790,791,791,791,791,791,791,792,792,792,792,792,792,792,793,793,793,793,793,793,793,794,794,794,794,794,794,794,794,795,795,795,795,795,795,795,796,796,796,796,796,796,796,796,796,796,797,797,797,797,797,798,798,798,798,798,798,798,799,799,800,800,800,800,800,801,801,802,802,802,802,802,802,802,803,803,803,803,803,803,803,803,803,803,803,804,804,804,805,805,806,806,806,806,806,806,806,807,807,807,807,808,808,809,809,810,810,811,811,812,812,813,813,814,814,815,815,815,816,816,817,817,818,818,819,819,820,820,821,821,822,822,823,823,823,823,823,823,823,823,824,824,825,825,826,826,827,827,828,828,829,829,830,830,831,831,832,832,833,833,834,834,835,835,836,836,837,837,838,838,839,839,839,839,839,839,839,839,840,840,841,841,842,842,843,843,844,844,845,845,846,846,847,847,848,848,848,848,848,848,848,848,849,849,850,850,850,850,850,850,850,851,851,852,852,852,852,852,853,853,853,853,853,854,854,854,854,854,854,854,854,854,854,855,855,855,855,855,855,855,855,855,855,856,856,856,856,856,856,856,856,856,856,857,857,857,857,857,857,857,857,858,858,858,858,858,858,858,858,859,859,859,859,859,859,859,859,860,860,861,861,861,861,861,861,862,862,862,862,862,862,862,862,863,863,864,864,865,865,865,866,866,867,867,867,867,868,868,868,868,869,869,869,869,869,869,869,870,870,870,870,870,870,870,870,871,871,871,871,871,871,871,872,872,873,873,873,873,873,873,873,874,874,874,874,874,874,874,874,875,875,875,875,875,875,876,876,876,876,876,876,876,876,876,876,876,876,876,877,877,877,877,877,877,877,878,878,878,878,878,879,879,879,879,879,879,880,880,880,880,880,880,880,880,881,881,881,881,882,882,883,883,884,884,885,885,885,886,886,887,887,888,888,889,889,889,890,890,891,891,892,892,893,893,893,894,894,895,895,896,896,897,897,898,898,899,899,900,900,900,900,900,900,901,901,902,902,902,903,903,903,904,904,904,904,904,905,905,906,906,907,907,908,908,909,909,910,910,911,911,912,912,913,913,914,914,915,915,916,916,917,917,918,918,919,919,919,919,919,919,919,920,920,921,921,922,922,923,923,924,924,925,925,926,926,927,927,927,927,927,928,928,928,928,929,929,929,929,929,930,930,930,930,930,930,930,930,930,931,931,931,931,931,931,931,931,931,931,931,932,932,932,932,932,933,933,933,933,933,933,933,933,933,934,934,934,934,934,934,934,934,935,935,935,935,935,935,935,935,935,935,936,936,937,937,937,937,937,937,938,938,938,938,938,939,939,939,939,939,939,939,940,940,940,940,940,940,940,940,941,941,941,941,941,941,941,942,942,942,942,942,942,943,943,943,943,943,943,943,944,944,945,945,945,945,946,946,946,946,946,946,946,946,947,947,947,947,947,947,948,948,949,949,949,949,950,950,950,950,950,950,950,950,951,951,951,951,951,951,951,951,952,952,952,952,952,952,952,953,953,954,954,955,955,955,955,955,955,955,955,955,956,956,956,956,956,956,956,957,957,957,957,957,957,957,957,957,957,958,958,959,959,959,959,959,959,959,959,960,960,960,960,960,960,960,960,960,960,961,961,962,962,963,963,964,964,965,965,966,966,966,966,966,966,966,966,966,967,967,968,968,969,969,970,970,971,971,972,972,973,973,974,974,974,974,974,974,974,974,975,975,976,976,977,977,978,978,979,979,980,980,981,981,982,982,983,983,984,984,985,985,985,985,986,986,987,987,988,988,988,988,988,988,988,988,989,989,990,990,991,991,992,992,992,992,992,992,992,992,993,993,994,994,995,995,995,995,995,996,996,997,997,997,997,997,997,997,998,998,998,999,999,999,999,999,999,999,999,1000,1000,1000,1000,1000,1000,1000,1000,1001,1001,1002,1002,1002,1002,1002,1002,1003,1003,1003,1003,1003,1003,1003,1004,1004,1005,1005,1005,1005,1005,1006,1006,1006,1006,1006,1006,1006,1007,1007,1007,1007,1007,1007,1007,1007,1007,1007,1007,1007,1007,1008,1008,1008,1008,1008,1008,1008,1008,1008,1008,1009,1009,1009,1009,1009,1009,1009,1009,1010,1010,1011,1011,1011,1011,1011,1011,1011,1011,1012,1012,1012,1012,1012,1012,1012,1013,1013,1013,1014,1014,1015,1015,1016,1016,1017,1017,1017,1017,1017,1017,1018,1018,1019,1019,1019,1019,1019,1019,1019,1019,1019,1020,1020,1020,1020,1020,1020,1020,1021,1021,1021,1021,1021,1022,1022,1023,1023,1023,1023,1023,1023,1023,1024,1024,1024,1024,1024,1024,1024,1025,1025,1025,1025,1025,1025,1025,1025,1025,1026,1026,1026,1026,1026,1026,1026,1027,1027,1028,1028,1029,1029,1030,1030,1030,1031,1031,1032,1032,1033,1033,1034,1034,1035,1035,1036,1036,1037,1037,1037,1037,1037,1038,1038,1038,1038,1038,1038,1039,1039,1040,1040,1041,1041,1042,1042,1042,1042,1043,1043,1044,1044,1045,1045,1046,1046,1046,1046,1046,1046,1046,1047,1047,1047,1047,1047,1047,1048,1048,1049,1049,1049,1049,1050,1050,1051,1051,1052,1052,1053,1053,1054,1054,1055,1055,1056,1056,1057,1057,1058,1058,1059,1059,1060,1060,1061,1061,1062,1062,1063,1063,1064,1064,1065,1065,1066,1066,1067,1067,1068,1068,1069,1069,1070,1070,1070,1070,1070,1070,1071,1071,1071,1071,1071,1072,1073,1073,1074,1074,1075,1075,1076,1076,1076,1076,1077,1077,1077,1077,1077,1077,1077,1078,1078,1078,1078,1078,1078,1078,1078,1079,1079,1079,1079,1080,1080,1080,1080,1080,1080,1080,1081,1081,1081,1081,1081,1081,1081,1082,1082,1082,1083,1083,1083,1083,1083,1083,1083,1083,1084,1084,1084,1084,1084,1084,1084,1084,1085,1085,1085,1085,1085,1085,1085,1086,1086,1086,1086,1086,1086,1086,1086,1087,1087,1087,1087,1087,1087,1088,1088,1088,1088,1088,1088,1088,1088,1088,1088,1088,1088,1088,1088,1089,1089,1089,1089,1089,1089,1090,1090,1091,1091,1092,1092,1092,1092,1092,1092,1092,1092,1092,1092,1092,1092,1093,1093,1093,1093,1093,1093,1093,1093,1093,1094,1094,1095,1095,1095,1095,1095,1095,1095,1095,1095,1095,1096,1096,1096,1096,1096,1097,1097,1098,1098,1098,1098,1098,1098,1098,1098,1099,1100,1100,1101,1101,1102,1102,1103,1103,1104,1104,1105,1105,1106,1106,1107,1107,1107,1108,1108,1109,1109,1110,1110,1111,1111,1112,1112,1113,1113,1114,1114,1114,1114,1114,1115,1115,1116,1116,1117,1117,1118,1118,1119,1119,1120,1120,1121,1121,1121,1122,1122,1123,1123,1124,1124,1125,1125,1126,1126,1127,1127,1128,1128,1128,1128,1128,1128,1129,1129,1130,1130,1131,1131,1132,1132,1133,1133,1134,1134,1134,1135,1135,1135,1135,1135,1136,1136,1137,1137,1137,1138,1138,1138,1138,1138,1138,1138,1139,1139,1139,1140,1140,1140,1140,1140,1140,1140,1140,1140,1141,1141,1142,1142,1142,1142,1142,1142,1143,1143,1143,1143,1143,1143,1143,1143,1144,1144,1145,1145,1146,1146,1146,1146,1147,1147,1147,1147,1147,1147,1147,1147,1148,1148,1148,1148,1148,1148,1149,1149,1149,1149,1149,1149,1149,1149,1150,1150,1150,1150,1150,1150,1150,1150,1150,1151,1151,1151,1152,1152,1153,1153,1153,1153,1154,1154,1155,1155,1156,1156,1156,1156,1156,1156,1156,1157,1157,1157,1157,1157,1157,1157,1157,1157,1158,1158,1158,1158,1158,1159,1159,1159,1159,1159,1159,1159,1159,1160,1160,1161,1161,1161,1161,1162,1162,1162,1163,1163,1164,1164,1165,1165,1166,1166,1167,1167,1168,1168,1169,1169,1170,1170,1170,1170,1171,1171,1172,1172,1173,1173,1174,1174,1174,1174,1174,1174,1174,1175,1175,1176,1176,1177,1177,1178,1178,1178,1179,1179,1180,1180,1181,1181,1182,1182,1182,1182,1182,1182,1182,1183,1183,1184,1184,1184,1184,1185,1185,1185,1185,1185,1185,1185,1186,1186,1186,1186,1186,1186,1186,1187,1187,1187,1187,1187,1187,1188,1188,1189,1189,1189,1189,1189,1189,1189,1190,1190,1190,1190,1190,1190,1190,1190,1191,1191,1191,1191,1191,1191,1191,1191,1192,1192,1192,1192,1192,1192,1192,1193,1193,1194,1194,1194,1194,1194,1194,1195,1195,1195,1195,1195,1195,1196,1196,1196,1196,1196,1196,1196,1196,1197,1197,1197,1197,1197,1197,1198,1198,1198,1198,1198,1198,1198,1198,1198,1198,1199,1199,1200,1200,1200,1200,1200,1200,1201,1201,1201,1201,1201,1201,1201,1201,1201,1201,1201,1202,1202,1202,1202,1202,1202,1202,1202,1202,1203,1203,1203,1203,1203,1203,1203,1203,1203,1203,1203,1203,1203,1204,1204,1204,1204,1204,1204,1204,1204,1205,1205,1205,1205,1205,1205,1205,1206,1206,1207,1207,1208,1208,1209,1209,1209,1209,1209,1209,1209,1209,1210,1210,1211,1211,1212,1212,1212,1213,1213,1213,1213,1213,1213,1213,1214,1214,1214,1214,1214,1214,1214,1214,1214,1214,1215,1215,1216,1216,1216,1216,1216,1216,1216,1217,1217,1217,1217,1217,1217,1217,1218,1218,1218,1218,1218,1218,1218,1219,1219,1219,1219,1219,1219,1219,1219,1219,1219,1219,1219,1220,1220,1221,1221,1222,1222,1223,1223,1224,1224,1225,1225,1225,1226,1226,1226,1226,1226,1227,1227,1228,1228,1229,1229,1230,1230,1231,1231,1232,1232,1232,1232,1232,1232,1232,1233,1233,1234,1234,1235,1235,1236,1236,1237,1237,1238,1238,1238,1239,1239,1240,1240,1241,1241,1242,1242,1243,1243,1244,1244,1245,1245,1245,1246,1246,1246,1246,1247,1247,1248,1248,1249,1249,1250,1250,1251,1251,1252,1252,1252,1253,1253,1253,1253,1253,1253,1253,1253,1253,1253,1253,1253,1253,1253,1254,1254,1254,1254,1254,1254,1254,1254,1255,1255,1255,1255,1255,1255,1255,1256,1256,1256,1256,1256,1256,1256,1256,1257,1257,1257,1257,1257,1257,1257,1257,1257,1257,1257,1257,1257,1258,1258,1258,1258,1258,1258,1258,1259,1259,1259,1260,1260,1260,1260,1260,1260,1260,1261,1261,1261,1261,1261,1261,1261,1262,1262,1262,1262,1262,1262,1262,1262,1263,1263,1264,1264,1264,1264,1264,1264,1264,1264,1264,1264,1265,1265,1265,1265,1265,1265,1265,1265,1265,1265,1266,1266,1267,1267,1268,1268,1268,1268,1268,1268,1268,1269,1269,1269,1269,1269,1269,1269,1269,1270,1270,1271,1271,1271,1271,1271,1271,1271,1271,1272,1272,1272,1272,1272,1272,1272,1273,1273,1273,1273,1273,1274,1274,1274,1274,1274,1274,1275,1275,1276,1276,1277,1277,1277,1277,1277,1277,1277,1277,1277,1278,1278,1278,1278,1278,1279,1279,1279,1279,1279,1279,1279,1279,1279,1279,1279,1279,1279,1280,1280,1280,1280,1280,1280,1280,1280,1281,1281,1281,1281,1281,1281,1281,1282,1282,1282,1282,1282,1282,1282,1282,1283,1283,1283,1283,1283,1284,1284,1285,1286,1286,1286,1286,1286,1286,1286,1287,1287,1288,1288,1289,1289,1290,1290,1291,1291,1291,1291,1292,1292,1293,1293,1294,1294,1295,1295,1296,1296,1296,1296,1296,1297,1297,1298,1298,1299,1299,1300,1300,1301,1301,1301,1301,1301,1302,1302,1303,1303,1304,1304,1305,1305,1306,1306,1306,1306,1306,1306,1306,1307,1307,1308,1308,1309,1309,1310,1310,1310,1310,1310,1311,1311,1311,1311,1311,1311,1311,1312,1312,1312,1312,1312,1312,1312,1312,1312,1313,1313,1314,1314,1314,1314,1314,1314,1315,1315,1315,1315,1315,1315,1316,1316,1316,1316,1317,1317,1317,1317,1317,1317,1317,1317,1317,1317,1318,1318,1318,1318,1318,1318,1319,1319,1319,1319,1320,1320,1320,1320,1320,1321,1321,1321,1321,1321,1321,1322,1322,1322,1322,1322,1322,1322,1322,1323,1323,1323,1323,1323,1323,1323,1323,1323,1324,1324,1324,1324,1324,1325,1325,1325,1325,1325,1325,1325,1325,1325,1326,1326,1326,1326,1326,1326,1326,1326,1326,1326,1326,1326,1327,1327,1327,1327,1327,1328,1328,1329,1329,1329,1329,1329,1329,1329,1329,1329,1329,1329,1329,1330,1330,1330,1330,1330,1330,1330,1330,1330,1330,1330,1330,1331,1331,1331,1331,1331,1331,1331,1331,1332,1332,1332,1332,1332,1332,1332,1332,1333,1333,1333,1333,1333,1333,1333,1333,1334,1334,1334,1334,1334,1334,1334,1334,1334,1334,1335,1335,1335,1335,1335,1335,1336,1336,1337,1337,1337,1337,1337,1337,1337,1337,1337,1337,1338,1338,1338,1338,1338,1338,1338,1339,1339,1339,1339,1339,1340,1340,1340,1341,1341,1342,1342,1343,1343,1344,1344,1345,1345,1346,1346,1346,1346,1346,1346,1346,1346,1346,1346,1347,1347,1348,1348,1349,1349,1350,1350,1351,1351,1352,1352,1353,1353,1354,1354,1355,1355,1356,1356,1356,1356,1356,1357,1357,1358,1358,1359,1359,1360,1360,1361,1361,1362,1362,1363,1363,1364,1364,1364,1365,1365,1366,1366,1367,1367,1368,1368,1368,1368,1368,1368,1368,1368,1369,1369,1370,1370,1371,1371,1371,1372,1372,1372,1372,1372,1372,1372,1373,1373,1374,1374,1375,1375,1375,1375,1375,1375,1375,1376,1376,1376,1376,1376,1376,1376,1376,1377,1377,1377,1377,1377,1377,1377,1378,1378,1378,1378,1378,1378,1379,1379,1380,1380,1380,1380,1380,1380,1380,1381,1381,1382,1382,1382,1382,1382,1382,1383,1383,1383,1383,1383,1383,1383,1384,1384,1384,1384,1384,1385,1385,1385,1385,1385,1385,1385,1385,1385,1385,1385,1385,1385,1385,1386,1386,1386,1386,1386,1386,1386,1386,1386,1387,1387,1387,1387,1387,1387,1387,1387,1387,1387,1388,1388,1389,1389,1389,1389,1389,1389,1389,1390,1390,1390,1390,1390,1391,1391,1391,1391,1391,1391,1391,1392,1392,1393,1393,1394,1394,1395,1395,1395,1396,1396,1396,1396,1396,1396,1396,1396,1397,1397,1397,1397,1397,1397,1397,1397,1397,1397,1398,1398,1399,1399,1400,1400,1400,1400,1400,1400,1400,1400,1400,1401,1401,1401,1401,1401,1401,1401,1401,1401,1401,1402,1402,1403,1403,1404,1404,1405,1405,1406,1406,1406,1406,1406,1406,1406,1406,1407,1407,1407,1407,1407,1408,1408,1409,1409,1410,1410,1411,1411,1412,1412,1412,1412,1412,1412,1412,1413,1413,1414,1414,1415,1415,1416,1416,1417,1417,1418,1418,1418,1418,1418,1419,1419,1420,1420,1421,1421,1421,1422,1422,1423,1423,1424,1424,1425,1425,1426,1426,1426,1426,1426,1426,1426,1426,1427,1427,1427,1427,1428,1428,1428,1428,1428,1428,1428,1429,1429,1429,1429,1429,1429,1429,1429,1429,1430,1430,1430,1430,1430,1430,1430,1431,1431,1431,1431,1431,1431,1431,1432,1432,1433,1433,1433,1433,1433,1433,1433,1434,1434,1434,1434,1434,1434,1435,1435,1436,1436,1436,1436,1437,1437,1437,1437,1437,1437,1437,1437,1438,1438,1438,1438,1438,1438,1438,1439,1439,1439,1439,1439,1439,1439,1439,1439,1439,1439,1439,1439,1440,1440,1441,1441,1441,1442,1442,1442,1442,1442,1442,1442,1442,1443,1443,1443,1443,1443,1443,1443,1444,1444,1444,1445,1445,1446,1446,1447,1447,1447,1447,1447,1447,1447,1447,1448,1448,1448,1448,1448,1448,1448,1448,1448,1448,1449,1449,1449,1449,1449,1449,1449,1449,1450,1450,1450,1450,1451,1451,1451,1451,1451,1451,1451,1451,1451,1451,1451,1451,1451,1451,1452,1452,1452,1452,1452,1452,1452,1452,1452,1452,1453,1453,1454,1454,1454,1454,1454,1454,1454,1454,1454,1454,1454,1454,1454,1455,1455,1455,1455,1455,1455,1455,1455,1455,1455,1455,1456,1456,1456,1457,1457,1457,1457,1457,1457,1457,1457,1458,1458,1458,1458,1458,1458,1458,1458,1459,1459,1459,1459,1459,1459,1460,1460,1460,1460,1461,1461,1462,1462,1463,1463,1464,1464,1465,1465,1465,1465,1465,1465,1465,1465,1465,1465,1466,1466,1467,1467,1468,1468,1469,1469,1470,1470,1471,1471,1472,1472,1473,1473,1474,1474,1475,1475,1476,1476,1477,1477,1478,1478,1479,1479,1480,1480,1480,1480,1480,1481,1481,1482,1482,1483,1483,1484,1484,1485,1485,1486,1486,1487,1487,1488,1488,1489,1489,1490,1490,1491,1491,1491,1491,1491,1491,1491,1491,1492,1492,1493,1493,1494,1494,1495,1495,1496,1496,1497,1497,1498,1498,1499,1499,1499,1499,1499,1500,1500,1500,1500,1500,1500,1500,1501,1501,1501,1501,1501,1501,1501,1502,1502,1502,1502,1502,1502,1502,1503,1503,1503,1503,1503,1503,1503,1503,1503,1504,1504,1504,1504,1504,1504,1505,1505,1505,1505,1505,1506,1506,1506,1506,1506,1507,1508,1508,1508,1508,1508,1508,1509,1509,1509,1509,1509,1509,1509,1509,1510,1510,1510,1510,1510,1510,1511,1511,1511,1511,1511,1511,1511,1512,1512,1512,1512,1512,1512,1512,1513,1513,1513,1513,1513,1513,1514,1514,1515,1515,1515,1515,1515,1515,1515,1516,1516,1517,1517,1517,1517,1517,1517,1517,1517,1517,1517,1517,1517,1517,1518,1518,1518,1518,1518,1518,1518,1519,1519,1519,1519,1520,1520,1520,1520,1520,1520,1520,1521,1521,1521,1521,1521,1521,1521,1521,1522,1522,1523,1523,1524,1524,1524,1524,1524,1525,1525,1525,1525,1525,1525,1525,1526,1526,1526,1526,1526,1526,1526,1527,1527,1528,1528,1528,1528,1528,1528,1528,1528,1528,1528,1528,1529,1529,1530,1530,1530,1530,1530,1530,1531,1531,1532,1532,1533,1533,1534,1534,1534,1534,1534,1534,1534,1534,1535,1535,1536,1536,1537,1537,1538,1538,1539,1539,1539,1539,1539,1539,1539,1540,1540,1541,1541,1541,1541,1541,1541,1541,1541,1541,1542,1542,1543,1543,1544,1544,1544,1544,1545,1545,1546,1546,1547,1547,1548,1548,1548,1549,1549,1550,1550,1551,1551,1552,1552,1552,1552,1552,1552,1552,1552,1552,1553,1553,1553,1554,1554,1554,1554,1555,1555,1556,1556,1556,1557,1557,1557,1557,1558,1558,1558,1558,1558,1558,1558,1558,1558,1559,1559,1560,1560,1561,1561,1562,1562,1562,1562,1562,1562,1563,1563,1563,1563,1563,1564,1564,1564,1564,1565,1565,1565,1565,1565,1565,1565,1565,1566,1566,1566,1566,1566,1566,1566,1567,1567,1567,1567,1567,1567,1567,1568,1568,1569,1569,1569,1569,1569,1569,1569,1570,1570,1570,1570,1570,1570,1570,1571,1571,1572,1572,1572,1572,1572,1572,1572,1572,1572,1572,1572,1572,1572,1572,1573,1573,1573,1573,1573,1574,1574,1574,1574,1574,1574,1574,1574,1575,1575,1576,1576,1576,1576,1576,1576,1576,1577,1577,1577,1577,1577,1577,1577,1577,1578,1578,1578,1578,1578,1578,1578,1578,1579,1579,1579,1579,1579,1579,1579,1579,1580,1580,1581,1581,1581,1581,1581,1581,1581,1582,1582,1583,1583,1583,1583,1583,1583,1584,1584,1584,1584,1584,1584,1584,1584,1585,1585,1586,1586,1586,1586,1586,1586,1587,1587,1587,1587,1587,1587,1587,1587,1588,1588,1588,1588,1588,1589,1589,1590,1590,1590,1590,1591,1591,1592,1592,1593,1593,1594,1594,1595,1595,1596,1596,1597,1597,1598,1598,1599,1599,1600,1600,1601,1601,1601,1602,1602,1603,1603,1604,1604,1605,1605,1606,1606,1606,1607,1607,1608,1608,1609,1609,1610,1610,1611,1611,1612,1612,1612,1612,1612,1612,1613,1613,1614,1614,1615,1615,1616,1616,1617,1617,1618,1618,1619,1619,1619,1619,1619,1619,1619,1620,1620,1620,1620,1620,1620,1620,1620,1620,1621,1621,1621,1621,1621,1621,1621,1621,1621,1621,1621,1621,1621,1621,1622,1622,1622,1622,1622,1622,1622,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1623,1624,1624,1624,1624,1624,1624,1624,1624,1625,1625,1625,1625,1625,1625,1626,1626,1626,1626,1626,1626,1627,1627,1627,1627,1627,1627,1627,1627,1628,1628,1628,1628,1628,1629,1629,1629,1629,1629,1629,1629,1630,1630,1631,1631,1632,1632,1632,1632,1632,1632,1632,1632,1632,1633,1633,1633,1634,1634,1634,1634,1634,1634,1634,1635,1635,1636,1636,1636,1636,1636,1636,1636,1637,1637,1637,1637,1637,1637,1637,1637,1638,1638,1638,1638,1638,1638,1638,1638,1639,1639,1639,1639,1639,1639,1639,1639,1640,1640,1640,1640,1640,1640,1640,1640,1641,1641,1641,1641,1641,1641,1641,1641,1642,1642,1642,1642,1642,1642,1642,1642,1643,1643,1643,1643,1643,1643,1643,1643,1644,1644,1644,1644,1644,1644,1644,1644,1645,1645,1645,1645,1645,1645,1645,1645,1646,1646,1646,1646,1646,1646,1646,1646,1647,1647,1647,1647,1647,1647,1647,1647,1648,1648,1648,1648,1648,1648,1648,1648,1649,1649,1649,1649,1649,1649,1649,1649,1650,1650,1650,1650,1650,1650,1650,1650,1651,1651,1651,1651,1651,1651,1651,1651,1651,1651,1652,1652,1652,1652,1652,1652,1652,1652,1653,1653,1653,1653,1653,1653,1653,1653,1654,1654,1654,1654,1655,1655,1655,1655,1655,1655,1655,1655,1655,1656,1656,1656,1656,1656,1657,1657,1657,1657,1657,1657,1657,1658,1658,1658,1658,1658,1658,1659,1659,1660,1660,1661,1661,1661,1661,1661,1661,1661,1662,1662,1662,1662,1662,1662,1662,1663,1663,1664,1664,1665,1665,1666,1666,1667,1667,1668,1668,1669,1669,1669,1669,1669,1669,1669,1669,1670,1670,1671,1671,1672,1672,1673,1673,1674,1674,1674,1674,1674,1674,1674,1675,1675,1676,1676,1677,1677,1678,1678,1679,1679,1679,1679,1679,1679,1679,1679,1680,1680,1681,1681,1682,1682,1683,1683,1684,1684,1684,1684,1684,1685,1685,1686,1686,1687,1687,1688,1688,1689,1689,1690,1690,1690,1690,1690,1690,1690,1690,1690,1690,1691,1691,1691,1691,1691,1691],"depth":[32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,3,2,1,1,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,72,71,70,69,68,67,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,98,97,96,95,94,93,92,91,90,89,88,87,86,85,84,83,82,81,80,79,78,77,76,75,74,73,72,71,70,69,68,67,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,77,76,75,74,73,72,71,70,69,68,67,66,65,64,63,62,61,60,59,58,57,56,55,54,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,53,52,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,51,50,49,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,48,47,46,45,44,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,43,42,41,40,39,38,37,36,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,3,2,1,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,35,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,1,2,1,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,4,3,2,1,2,1,6,5,4,3,2,1,6,5,4,3,2,1,4,3,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,5,4,3,2,1,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,3,2,1,3,2,1,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,2,1,8,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,3,2,1,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,1,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,2,1,6,5,4,3,2,1,1,2,1,4,3,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,3,2,1,6,5,4,3,2,1,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,3,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,3,2,1,2,1,7,6,5,4,3,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,2,1,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,3,2,1,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,5,4,3,2,1,1,2,1,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,5,4,3,2,1,2,1,3,2,1,7,6,5,4,3,2,1,3,2,1,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,3,2,1,2,1,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,6,5,4,3,2,1,4,3,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,4,3,2,1,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,12,11,10,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,3,2,1,7,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,2,1,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,3,2,1,2,1,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,11,10,9,8,7,6,5,4,3,2,1,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,4,3,2,1,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1,5,4,3,2,1,5,4,3,2,1,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,4,3,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,2,1,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,11,10,9,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,4,3,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,3,2,1,4,3,2,1,2,1,3,2,1,4,3,2,1,9,8,7,6,5,4,3,2,1,2,1,2,1,2,1,6,5,4,3,2,1,5,4,3,2,1,4,3,2,1,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,2,1,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,3,2,1,2,1,2,1,2,1,2,1,2,1,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,9,8,7,6,5,4,3,2,1,14,13,12,11,10,9,8,7,6,5,4,3,2,1,7,6,5,4,3,2,1,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,6,5,4,3,2,1,6,5,4,3,2,1,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,9,8,7,6,5,4,3,2,1,3,2,1,7,6,5,4,3,2,1,2,1,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,10,9,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,8,7,6,5,4,3,2,1,4,3,2,1,9,8,7,6,5,4,3,2,1,5,4,3,2,1,7,6,5,4,3,2,1,6,5,4,3,2,1,2,1,2,1,7,6,5,4,3,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,8,7,6,5,4,3,2,1,2,1,2,1,2,1,2,1,5,4,3,2,1,2,1,2,1,2,1,2,1,2,1,10,9,8,7,6,5,4,3,2,1,6,5,4,3,2,1],"label":["findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","isBaseVar","FUN","lapply","Filter","findLocalsList","funEnv","make.functionContext","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findLocVar","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","findVar","cmpSym","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","make.promiseContext","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","tryCatch","checkCall","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$patchlabels","codeBufCode","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","findLocVar","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","get","getFoldFun","constantFoldCall","constantFold","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","getInlineInfo","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","gam.control","mgcv::gam","pboot","chol.default","mroot","mini.roots","estimate.gam","mgcv::gam","pboot",".C","profvis","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot","gam.side","gam.setup","mgcv::gam","pboot","conditionCall","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot",".C","profvis","as.double","profvis","%in%","findLocals1","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","cmpfun","compiler:::tryCmpfun","profvis","%in%","constantFoldCall","constantFold","constantFoldCall","constantFold","constantFoldCall","constantFold","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","$","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallExprFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpRepeatBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis",".Call","profvis",".Call","profvis",".Call","profvis","return (sum((Imat - Fhat)^2)/length(Fhat)^2)","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot","$","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","F_X_t0_R0[i1, ] <- F_X_t0_R0[-i1, ][i1.closest, ]","pboot","<GC>","apply","pboot","topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1, coef_g.fit=boot_b_temp$coef_g.fit, ","FUN","lapply","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","cmpfun","compiler:::tryCmpfun","profvis","FUN","lapply","findLocalsList1","findLocalsList","funEnv","make.functionContext","cmpfun","compiler:::tryCmpfun","profvis","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","cmpfun","compiler:::tryCmpfun","profvis","tryInline","cmpCall","cmp","cmpBuiltinArgs","cmpBuiltin","cmpDotInternalCall","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findFunDef","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallExprFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","extractSrcref","getExprSrcref","cb$setcurexpr","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","%in%","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpBuiltinArgs","cmpDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","grep","is.ddsym","cmpSym","cmp","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallExprFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpTag","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","%in%","getInlineInfo","isBaseVar","isLoopTopFun","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","checkSkipLoopCntxtList","checkSkipLoopCntxt","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","make.callContext","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSym","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim1","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","getInlineInfo","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findFunDef","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSym","cmp","cmpIndices","cmpSubassignDispatch","h","trySetterInline","cmpSetterCall","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpComplexAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","cmpForBody","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpConstArg","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","exists","findCenvVar","getInlineInfo","isBaseVar","getFoldFun","constantFoldCall","constantFold","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$putconst","cmpSym","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$patchlabels","codeBufCode","genCode","cmpfun","compiler:::tryCmpfun","profvis","any","profvis","<GC>","length","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","[[<-.data.frame","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","profvis","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","standardGeneric","profvis","standardGeneric","profvis",".C","profvis","sum","profvis","set_names","mask$forget","mutate_cols","mutate.data.frame","est_psi","fit_one","==","profvis","is.na","profvis",".C","profvis",".C","profvis","%in%",".deparseOpts","deparse","FUN","vapply","model.matrix.default","predict.gam","est_psi","fit_one","<GC>",".C","profvis","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","nrow","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>",".C","profvis",".C","profvis","match.arg","order","order","factor","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pnorm","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","if_R0_temp <- c(M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","rowSums","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","<GC>","X_in_fold_adjust_scale <- X_adjust_scale[fold_list[[k]], ]","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","splineDesign","ns","profvis","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","NextMethod","[.factor","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis","as.character","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","eval","eval","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mutate_col","mutate_cols","mutate.data.frame","est_psi","fit_one",".C","profvis",".C","profvis","%*%","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","delete.response","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","var","FUN","apply","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","simplify2array","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","array","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","cmpfun","compiler:::tryCmpfun","profvis","cb$putcode","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findVar","cmpSym","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallExprFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findLocVar","cmpCall","cmp","cmpIndices","cmpSubsetDispatch","h","tryInline","cmpCall","cmp","cmpBuiltinArgs","h","tryInline","cmpCall","cmp","cmpPrim2","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","<GC>","[.data.frame","pboot_model","newton","gam.outer","estimate.gam","mgcv::gam","pboot_model","deparse","mode","deparse","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot_model","structure","makeRestart","makeRestartList","withRestarts",".signalSimpleWarning","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","pboot_model","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot_model","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","pboot_model",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","mayCallBrowserList","mayCallBrowser","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","getInlineInfo","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","putconst","cb$putcode","cmpSym","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","findCenvVar","findLocVar","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$setcurexpr","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","h","tryInline","cmpCall","cmp","genCode","cmpCallArgs","cmpCallSymFun","cmpCall","cmp","cmpSymbolAssign","h","tryInline","cmpCall","cmp","h","tryInline","cmpCall","cmp","genCode","cmpfun","compiler:::tryCmpfun","profvis","cb$patchlabels","codeBufCode","genCode","cmpfun","compiler:::tryCmpfun","profvis","unlist","simplify2array","sapply","NW_new","pboot_sim","crossprod","profvis",".Fortran","profvis","standardGeneric","profvis","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","factor","unique.default","model.frame.default","est_psi","fit_one",".C","profvis","dim","profvis","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","profvis",".C","profvis","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","<GC>",".C","profvis","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Fortran","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","conditionMessage","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%*%","profvis",".C","profvis",".Call","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","tryCatchOne","tryCatchList","tryCatch","try","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","structure","simpleError","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","unlist","simplify2array","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","sum","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","stopifnot","srcfilecopy","parse","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","estimate.gam","mgcv::gam","est_psi","fit_one","match.fun","vapply","pmin","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","is.numeric","profvis","mean","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","predict.gam","est_psi","fit_one","...elt","profvis","%in%","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one",".C","profvis","is.function","profvis","levels.default","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.setup","mgcv::gam","est_psi","fit_one","...elt","profvis","eigen","totalPenaltySpace","estimate.gam","mgcv::gam","est_psi","fit_one","qr.qty","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","standardGeneric","profvis","[[","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mu_Yexp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+","est_psi","fit_one","FUN","lapply","sapply","NW_new","pboot_sim","<GC>","apply","pboot_sim","$","predict.gam","pboot_sim","isTRUE","mean.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".External2","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one","stopifnot","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","<Anonymous>","[[.data.frame","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","paste","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","factor","unique.default","factor","predict.gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","...length","profvis","qr.qty","PredictMat","predict.gam","est_psi","fit_one","$<-","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","structure","simpleError","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","%*%","profvis",".C","profvis","<GC>",".C","profvis","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mean.default","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","M3d2list","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","M3d2list","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","M3d2list","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one","t","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","fix.family.link.family","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","conditionMessage","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","anyNA","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","%in%","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$<-","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.control","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","diag","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","mode","data.class","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","names","profvis","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.list","profvis",".C","profvis","<Anonymous>","[[.data.frame","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","array","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis","getwd","srcfilecopy","parse","get.var","predict.gam","pboot_sim","FUN","profvis","dots_split","env","vars_select_eval","eval_select_impl","tidyselect::eval_select","select.data.frame","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","withCallingHandlers","suppressWarnings","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","qr.default","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","model.frame.default","predict.gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unique","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","$","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","data.class","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","as.double","profvis","<GC>","as.double","profvis","qr.qty","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one","simpleError","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","length","profvis","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unlist","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","rm","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","W <- K(D/exp(log_bandwidth)) * Id_neq","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","sort.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","aperm.default","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmatch",".deparseOpts","deparse","FUN","vapply","model.frame.default","model.matrix.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","model.frame.default","est_psi","fit_one","%*%","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","list","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","match.arg","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","predict.gam","est_psi","fit_one",".C","profvis","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","vapply","order","factor","predict.gam","est_psi","fit_one",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","lapply","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","+","profvis","%in%",".deparseOpts","deparse","FUN","vapply","model.frame.default","est_psi","fit_one","variance","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","any","profvis","seq.int","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","is.nan","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","if (eq(max(abs(if_R1_temp)),z=if_R1_temp)>0) {","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","var_temp_trunc[k, g] <- sum((if_temp_trunc - mean(if_temp_trunc))^2)/(nk_in_fold-1)","est_psi","fit_one","dnorm","K","FUN","lapply","sapply","NW_new","pboot_sim","aperm.default","apply","pboot_sim",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","is.finite","profvis","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","FUN","vapply","model.frame.default","predict.gam","est_psi","fit_one","<GC>","pmatch",".deparseOpts","deparse","mode","formula.default","reformulate","mgcv::s","est_psi","fit_one","as.double","profvis","deparse","mgcv::s","est_psi","fit_one","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","structure","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ctrfn","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","structure","simpleError","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","profvis","<GC>","standardGeneric","profvis","storage.mode","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","mode","formula.default","reformulate","mgcv::s","est_psi","fit_one",".C","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","truncate","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","IF_R1_trunc_diff[[g]] <- c(IF_R1_trunc_diff[[g]], if_R1_temp_trunc_diff)","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","c","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","deparse","mode","formula.default","reformulate","mgcv::gam","est_psi","fit_one",".C","profvis","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.character.factor","factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","standardGeneric","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","dplyr_new_data_frame","dplyr_reconstruct","dplyr_col_modify.data.frame","mutate.data.frame","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attributes","profvis","parse","get.var","predict.gam","est_psi","fit_one",".C","profvis","-","profvis","qr.qty","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","profvis",".subset2","profvis","[","predict.gam","est_psi","fit_one",".C","profvis","standardGeneric","profvis","%*%","profvis","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","lapply","sapply","model.frame.default","predict.gam","est_psi","fit_one","formals","match.arg","sort.int","sort.default","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","if_R0_temp  <- c(M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","is.na","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one","base::setdiff","setdiff.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","length","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one","dnorm","K","FUN","lapply","sapply","NW_new","pboot_sim","ecdf <- runif(1,0,1)","FUN","apply","pboot_sim","factor","predict.gam","pboot_sim","family$dev.resids","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","smooth.info","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","[[","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".Call","profvis","<GC>",".Call","profvis","is.matrix","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","mgcv::gam","est_psi","fit_one","isTRUE","contrasts","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".Fortran","profvis","sys.call","[[<-.data.frame","predict.gam","est_psi","fit_one","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","array","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","cbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","FUN","vapply","model.frame.default","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.array","profvis","dimnames.data.frame","rownames","predict.gam","est_psi","fit_one","%*%","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","data.class","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unique.default","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","if_R0_temp <- c(M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis","unlist","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","length","profvis","factor","variable.summary","mgcv::gam","est_psi","fit_one","t","PredictMat","predict.gam","est_psi","fit_one","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","<GC>","%*%","profvis","length","profvis","[[","predict.gam","est_psi","fit_one","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".deparseOpts","deparse","FUN","vapply","model.matrix.default","predict.gam","est_psi","fit_one","colMeans","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.setup","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","model.matrix.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","if_R0_temp  <- c(M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","f","<Anonymous>","uniroot","est_psi","fit_one",".C","profvis","<GC>","is.finite","profvis","[","model.frame.default","pboot","gam.fit3.post.proc","gam.outer","estimate.gam","mgcv::gam","pboot","oldClass","profvis",".C","profvis",".C","profvis",".C","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","pboot",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","unlist","simplify2array","sapply","NW_new","pboot","lapply","sapply","NW_new","pboot","[[.data.frame","na.exclude.data.frame","model.frame.default","predict.gam","pboot","eval","match.arg","order","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","deparse","FUN","vapply","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","conditionCall","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one",".External2","profvis","[.data.frame","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","%in%","[[.data.frame","model.frame.default","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one","pmatch",".deparseOpts","deparse","mgcv::s","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".External","profvis","all.equal","mgcv::s","est_psi","fit_one","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","cbind2","gam.setup","mgcv::gam","est_psi","fit_one","is.na","profvis","$","predict.gam","est_psi","fit_one","getwd","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","as.matrix","qr.default","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".External","profvis","<GC>","as.vector","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","mini.roots","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","structure","simpleError","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","max","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","%*%","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","<GC>","Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","order","sort.int","sort.default","ns","profvis",".C","profvis","deparse","mode","formula.default","reformulate","mgcv::s","est_psi","fit_one","<GC>",".C","profvis","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","levels","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","formula","reformulate","mgcv::gam","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","t.default","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","nargs","profvis","standardGeneric","profvis",".C","profvis","unique.default","factor","unique.default","model.frame.default","est_psi","fit_one",".C","profvis","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","length","NROW","[[<-.data.frame","model.frame.default","predict.gam","est_psi","fit_one","<GC>","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","terms","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.character.factor","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis",".Call","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","isTRUE","mean.default","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","return (sum((Imat - Fhat)^2)/length(Fhat)^2)","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","pboot_model",".C","profvis","formula","reformulate","mgcv::gam","pboot_model","is.matrix","profvis",".C","profvis","sum","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".C","profvis","<GC>","array","simplify2array","sapply","NW_new","pboot_sim","isTRUE","which","FUN","apply","pboot_sim","profvis","-","profvis",".C","profvis","c","profvis","model.frame.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.data.frame","est_psi","fit_one","as.matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t.default","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","lockBinding","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one","stopifnot","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply",".getXlevels","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","match.fun","vapply","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one",".C","profvis","t","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","structure","eigen","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","uniroot","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","mgcv::s","est_psi","fit_one","formula.character","as.formula","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one","expr","context_local","local_mask","initialize","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one",".C","profvis","$","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","colSums","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".External","profvis","gam.setup","mgcv::gam","est_psi","fit_one","pmax","formatC","format_perc","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","ncol","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","<GC>","names","profvis",".C","profvis","all_vars1","mgcv::gam","est_psi","fit_one",".Fortran","profvis",".C","profvis","as.list","vapply","rm","PredictMat","predict.gam","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","makepredictcall","model.frame.default","est_psi","fit_one","mgcv::gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","sys.call","[[.data.frame","[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","pboot_sim","apply","pboot_sim","<GC>","PredictMat","predict.gam","pboot_sim","if (is.numeric(data[,i]) | is.integer(data[, i])){ paste(\"s\", \"(\",names(data)[i], \", k=5)\", sep=\"\")}","FUN","lapply","sapply","gam.variables","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.list","vapply",".getXlevels","gam.setup","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","as.vector","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","paste","FUN","vapply","model.frame.default","predict.gam","est_psi","fit_one","sum","profvis","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one","sys.call","[[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sys.call","[[.data.frame","gam.setup","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".C","profvis","environment","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","stopifnot","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ncol","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".C","profvis",".C","profvis",">","profvis","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","names","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","%*%","profvis","pmin","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","match.fun","vapply","pmin","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","uniroot","est_psi","fit_one","<GC>","if_temp <- c(M_in_fold_t_R0*eta_t_R0_weight*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","est_psi","fit_one","attr.all.equal","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","paste","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>",".C","profvis","rev","eigen","totalPenaltySpace","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","^","profvis","suppressWarnings","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","eval","match.arg","order","order","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","sys.call","[[.data.frame","[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","[.terms","parametricPenalty","gam.setup","mgcv::gam","est_psi","fit_one",".Call","profvis",".C","profvis","t.default","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is.na","na.omit.data.frame","model.frame.default","est_psi","fit_one","all.equal.numeric","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Diag","ctrfn","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","dev.resids","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","profvis","paste","FUN","vapply","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mean.default","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","truncate","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","eq","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","eq","est_psi","fit_one","dnorm","K","FUN","lapply","sapply","NW_new","pboot_sim","<GC>","Kxb <- sapply(xb, function(x, Xb) K(Xb-x, h), Xb=Xb)","dnorm","K","FUN","lapply","sapply","NW_new","pboot_sim","apply","pboot_sim","t","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","qr.qty","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","unique.default","model.frame.default","est_psi","fit_one","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","model.frame.default","predict.gam","est_psi","fit_one","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","$<-","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","deparse","FUN","vapply",".getXlevels","gam.setup","mgcv::gam","est_psi","fit_one","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","%in%","[[.data.frame","predict.gam","est_psi","fit_one","match.fun","lapply","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","na.omit.data.frame","model.frame.default","est_psi","fit_one","%*%","profvis","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","stopifnot","srcfilecopy","parse","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","ifelse","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","ctrfn","contrasts","model.matrix.default","predict.gam","est_psi","fit_one","standardGeneric","profvis","srcfilecopy","parse","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","levels","contrasts","model.matrix.default","gam.setup","mgcv::gam","est_psi","fit_one","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","mgcv::gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".External2","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmatch","match.arg","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","y_t_R1 = sort(unique(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))    ","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","if_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), ","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","factor","[.factor","model.frame.default","predict.gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","<GC>","gam.side","gam.setup","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.factor","model.frame.default","predict.gam","est_psi","fit_one","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","na.exclude.data.frame","model.frame.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sum","profvis",".C","profvis","standardGeneric","profvis","<GC>","c","profvis","sys.parent","match.arg","order","order","factor","predict.gam","est_psi","fit_one","chol.default","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","sum","profvis",".C","profvis","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","structure","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mean.default","f","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","eval","eval","see_if","assertthat::assert_that","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","as.matrix","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","mu_Yexp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","parse","get.var","predict.gam","pboot_sim","dnorm","K","FUN","lapply","sapply","NW_new","pboot_sim","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","pboot_sim","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","nrow","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one",".C","profvis","matrix","predict.gam","est_psi","fit_one","unlist","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","vapply","order","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","predict.gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","smooth.construct.tp.smooth.spec","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","mgcv::s","est_psi","fit_one",".C","profvis",".C","profvis","<GC>","matrix","Predict.matrix.tprs.smooth","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.setup","mgcv::gam","est_psi","fit_one","conditionMessage","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","strsplit","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","standardGeneric","profvis","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","array","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","deparse","FUN","vapply","model.frame.default","est_psi","fit_one","[[","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","FUN","vapply","order","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","outer","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","%*%","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","mostattributes<-","pmin","eq","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[","[.data.frame","na.omit.data.frame","model.frame.default","est_psi","fit_one","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","srcfilecopy","parse","mgcv::gam","est_psi","fit_one","profvis","paste","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[","dplyr_col_select","mutate_keep","mutate.data.frame","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","[.data.frame","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","as.double","profvis","[","model.matrix.default","predict.gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","vapply","order","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","[.data.frame","na.omit.data.frame","model.frame.default","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","aperm.default","sweep","scale.default","MAVE::mave.compute","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis","fit_t_R0_h  <- fit_SensIAT_single_index_norm1coef_model(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],","which","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis","mean","est_psi","fit_one",".Call","profvis","c","profvis",".Call","profvis","logical","order","sweep","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","model.frame.default","predict.gam","pboot_sim","y_t_R0[min(which(ecdf<=x))]","FUN","apply","pboot_sim","apply","pboot_sim","splineDesign","ns","profvis","all.equal.numeric","mgcv::s","est_psi","fit_one","dbinom","aic","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","any","profvis","is.finite","profvis","sum","profvis","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one","eval","model.frame.default","predict.gam","est_psi","fit_one","do.call","mgcv::gam","est_psi","fit_one","unlist","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","initialize","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one",".C","profvis","structure","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","FUN","lapply","assign_func_envs","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","standardGeneric","profvis","stdin","parse","get.var","predict.gam","est_psi","fit_one","rbind","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","initial.sp","initial.spg","estimate.gam","mgcv::gam","est_psi","fit_one","validmu","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","sum","profvis","[.data.frame","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","if_temp_trunc <- if_R1_temp_trunc*prop.R1+if_R0_temp_trunc*(1-prop.R1)","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","c","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","c","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","matrix","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all.equal.character","attr.all.equal","all.equal.list","attr.all.equal","all.equal.numeric","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","mode","deparse","value[[3]]","tryCatchOne","tryCatchList","tryCatch","try","get.var","ExtractData","smooth.construct3","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","parse","get.var","ExtractData","Predict.matrix3","PredictMat","predict.gam","est_psi","fit_one","$<-","smoothCon","gam.setup","mgcv::gam","est_psi","fit_one","paste","interpret.gam0","interpret.gam","mgcv::gam","est_psi","fit_one","<GC>","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","gam.side","gam.setup","mgcv::gam","est_psi","fit_one","diag","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".C","profvis","is.expression","profvis","eval","eval","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","length","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","all","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","t","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","is_character","chr_unserialise_unicode","initialize","DataMask$new","mutate_cols","mutate.data.frame","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","<GC>","eval","eval","get.null.coef","estimate.gam","mgcv::gam","est_psi","fit_one","chol","mroot","gam.reparam","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","$","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","unique","model.frame.default","est_psi","fit_one","as.vector","outer","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","quantile.default","variable.summary","mgcv::gam","est_psi","fit_one","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one",".Call","profvis","any","profvis","gam.fit3","newton","gam.outer","estimate.gam","mgcv::gam","est_psi","fit_one","getwd","srcfilecopy","parse","get.var","predict.gam","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","vapply","pmin","f","<Anonymous>","uniroot","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","dnorm","K","FUN","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","lapply","sapply","NW_new","est_psi","fit_one",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis",".Call","profvis","<GC>","W <- K(D/exp(log_bandwidth)) * Id_neq","dnorm","K","fn","<Anonymous>","optim","fit_SensIAT_single_index_norm1coef_model","est_psi","fit_one","mean","f","<Anonymous>","uniroot","est_psi","fit_one"],"filenum":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,2,1,null,2,1,1,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,null,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,null,1,null,null,null,6,2,1,6,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,3,4,2,1,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,4,2,1,null,null,6,2,1,null,2,1,null,null,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,3,4,2,1,null,3,4,2,1,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,null,null,3,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,null,null,null,null,null,null,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,6,6,null,null,6,2,1,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,null,4,2,1,6,6,null,null,6,2,1,2,null,2,1,null,null,1,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,6,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,6,6,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,6,2,1,null,6,2,1,null,null,null,null,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,4,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,3,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,null,6,null,null,6,4,2,1,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,null,null,null,null,null,null,6,4,2,1,2,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,6,2,1,null,2,null,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,4,2,1,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,1,2,1,null,null,null,1,2,null,null,2,4,2,1,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,null,2,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,2,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,2,4,2,1,null,null,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,null,null,null,2,4,2,1,6,6,null,null,6,2,1,null,6,6,6,null,null,6,2,1,2,1,null,null,null,4,2,1,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,2,1,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,4,2,1,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,1,6,6,null,null,6,2,1,null,null,null,null,null,null,null,null,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,2,1,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,null,null,4,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,null,null,3,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,4,2,1,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,null,6,6,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,4,2,1,null,null,3,3,3,null,null,3,4,2,1,null,null,null,null,4,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,3,null,null,3,4,2,1,null,null,1,2,null,2,1,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,2,1,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,4,null,null,null,null,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,null,null,null,4,2,1,null,null,2,1,null,null,null,null,null,null,4,2,1,null,null,4,2,1,null,null,null,null,4,2,1,null,null,null,4,2,1,null,null,null,null,null,null,null,null,4,2,1,null,null,null,null,null,2,1,null,null,null,null,null,null,null,null,null,null,null,null,3,3,null,null,3,4,2,1,null,null,null,null,null,null,null,null,null,2,null,null,4,2,1,null,null,null,null,null,null,null,null,6,6,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,6,4,2,1,null,null,null,null,null,null,null,null,null,null,null,3,3,3,null,null,3,4,2,1,2,null,null,4,2,1],"linenum":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,204,null,null,232,12,null,null,null,null,232,12,null,null,null,null,null,null,null,null,null,null,null,null,null,233,12,null,null,234,12,null,null,null,null,null,null,null,null,null,null,null,235,12,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,238,null,null,null,null,null,null,null,63,null,null,94,238,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,277,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,323,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,323,null,346,12,null,364,12,15,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,null,null,null,null,null,622,null,null,null,null,null,null,null,null,null,null,null,null,132,622,15,null,null,null,null,134,622,15,null,null,null,134,622,15,null,null,null,null,null,null,null,128,622,15,null,null,null,null,null,null,128,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,15,null,null,null,null,null,null,null,null,null,null,128,622,15,null,null,null,null,null,130,622,15,null,null,null,null,132,622,15,null,null,null,null,134,622,15,null,null,null,null,null,622,15,null,null,null,null,128,622,15,null,null,null,null,130,622,15,null,null,null,null,null,null,null,null,null,null,null,null,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,396,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,422,622,15,null,null,null,null,null,null,null,null,60,null,null,94,295,622,15,null,null,null,null,null,233,622,15,null,null,null,null,null,null,null,null,28,59,null,null,94,295,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,130,622,18,null,null,null,622,18,null,null,null,null,132,622,18,null,null,null,null,132,622,18,null,null,null,null,134,622,18,null,null,null,null,null,null,null,null,null,null,622,18,null,null,null,null,128,622,18,null,null,null,null,null,null,null,null,null,null,null,null,null,132,622,18,null,null,null,null,null,null,null,132,622,18,null,null,null,null,null,132,622,18,null,null,null,null,null,null,null,null,null,null,622,18,null,null,null,null,null,null,null,null,132,622,18,134,622,18,null,null,null,null,null,null,null,622,18,null,null,null,128,622,18,null,null,null,null,null,128,622,18,null,null,null,null,null,null,null,null,null,null,130,622,18,null,null,null,null,132,622,18,null,null,null,null,null,134,622,18,null,null,null,622,18,null,null,null,null,null,null,null,null,null,null,null,134,622,18,null,null,622,18,null,null,null,null,null,null,null,null,null,38,330,622,18,null,null,null,null,null,null,null,389,346,622,18,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,330,622,18,null,null,null,null,null,null,28,59,null,null,94,330,622,18,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,23,null,null,427,23,null,null,null,431,23,null,null,null,null,null,null,null,null,null,null,null,null,null,432,23,null,null,null,null,null,null,null,null,null,null,null,null,434,23,null,null,null,null,null,null,null,null,435,23,null,null,null,435,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,32,null,null,null,null,null,null,null,null,null,null,null,null,32,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,32,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,32,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,32,null,null,null,null,null,32,null,null,null,389,554,32,395,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,132,622,39,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,128,622,39,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,null,128,622,39,132,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,295,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,355,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,63,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,94,330,622,39,null,null,null,128,622,42,null,null,null,null,null,null,128,622,42,null,null,null,128,622,42,null,null,null,null,null,null,130,622,42,null,null,132,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,622,42,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,132,622,42,null,null,null,134,622,42,null,null,null,null,null,128,622,42,null,null,null,130,622,42,null,132,622,42,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,514,622,42,null,null,null,null,48,330,622,42,null,null,null,null,28,59,null,null,94,330,622,42,null,null,null,null,null,null,396,622,42,null,null,389,557,32,null,572,32,null,null,32,null,null,null,null,null,null,128,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,132,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,130,622,39,null,null,null,132,622,39,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,null,622,39,null,null,128,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,null,null,132,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,498,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,53,330,622,39,null,null,514,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,38,295,622,39,null,38,295,622,39,null,38,295,622,39,null,null,null,null,null,null,null,16,null,null,514,622,39,null,null,null,null,128,622,42,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,134,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,128,622,42,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,132,622,42,null,132,622,42,null,null,null,null,null,134,622,42,null,128,622,42,null,null,null,null,128,622,42,null,130,622,42,null,null,null,null,null,null,130,622,42,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,null,null,128,622,42,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,330,622,42,null,null,null,null,null,null,38,330,622,42,null,null,null,null,null,null,462,622,42,null,null,null,null,null,null,468,null,null,null,null,null,null,32,null,null,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,622,39,null,null,null,null,null,null,128,622,39,null,null,null,null,130,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,132,622,39,null,null,null,null,134,622,39,null,null,null,null,null,null,128,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,59,null,null,94,330,622,39,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,61,null,null,94,295,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,128,622,42,null,622,42,null,null,null,null,null,null,134,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,622,42,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,134,622,42,null,622,42,null,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,622,42,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,62,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,487,622,42,null,null,null,null,null,null,537,622,42,382,389,null,null,389,554,32,null,592,32,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,128,622,39,null,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,null,622,39,null,null,null,null,622,39,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,null,134,622,39,null,null,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,506,622,39,null,null,null,null,null,null,null,null,null,null,null,59,null,null,94,295,622,39,null,null,null,null,501,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,531,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,466,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,134,622,42,null,null,null,null,134,622,42,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,134,622,42,null,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,130,622,42,null,null,132,622,42,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,622,42,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,134,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,134,622,42,null,null,null,null,622,42,null,null,null,null,330,622,42,null,null,null,null,440,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,536,622,42,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,null,498,622,42,382,389,null,null,389,551,32,585,null,584,32,null,null,32,null,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,622,39,null,null,null,null,132,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,128,622,39,null,null,null,null,null,128,622,39,null,null,null,null,128,622,39,null,null,null,null,null,null,null,130,622,39,null,null,null,622,39,null,null,null,null,132,622,39,null,null,null,null,null,622,39,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,130,622,39,132,622,39,null,null,null,null,null,null,134,622,39,null,295,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,422,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,391,null,null,391,349,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,382,389,null,null,389,346,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,520,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,134,622,42,null,null,null,622,42,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,null,null,null,622,42,null,128,622,42,null,null,null,null,128,622,42,null,null,null,null,null,130,622,42,null,null,null,null,130,622,42,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,622,42,null,null,null,128,622,42,null,null,null,null,null,null,null,null,null,null,128,622,42,null,null,null,null,130,622,42,null,null,132,622,42,null,null,null,132,622,42,null,null,null,null,null,134,622,42,null,null,622,42,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,440,622,42,null,null,null,null,null,null,535,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,506,622,42,null,null,null,null,null,null,null,12,null,null,null,233,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,251,12,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,391,323,12,null,389,332,12,null,null,null,null,12,null,null,null,null,null,null,128,622,15,null,null,null,null,null,null,null,null,130,622,15,null,null,132,622,15,null,null,null,null,null,null,132,622,15,null,null,null,null,null,134,622,15,null,null,null,null,null,null,null,null,622,15,null,null,null,null,null,130,622,15,null,null,null,622,15,null,null,null,null,132,622,15,null,null,null,null,null,134,622,15,null,null,null,null,null,622,15,null,null,null,null,622,15,null,null,null,null,128,622,15,null,null,null,null,622,15,null,null,null,null,null,132,622,15,null,null,null,134,622,15,null,null,null,null,622,15,null,null,null,null,null,130,622,15,null,null,null,null,null,132,622,15,null,null,null,null,134,622,15,null,null,null,null,null,null,null,null,null,null,128,622,15,null,null,null,null,130,622,15,null,null,null,null,null,null,null,132,622,15,null,null,null,null,null,null,null,134,622,15,null,null,null,null,null,null,null,null,622,15,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,330,622,15,512,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,330,622,15,null,null,null,null,null,null,null,null,null,null,61,null,null,null,null,null,null,null,null,null,53,295,622,15,null,null,null,null,null,391,null,null,391,349,622,15,null,null,null,null,null,null,28,59,null,null,94,295,622,15,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,18,null,null,null,null,null,null,null,null,132,622,18,null,null,null,null,null,132,622,18,null,null,null,null,null,null,622,18,null,null,null,null,128,622,18,null,null,null,null,130,622,18,null,null,null,null,132,622,18,null,null,null,null,null,null,null,null,null,null,134,622,18,null,null,null,null,null,null,null,null,622,18,null,null,null,null,null,128,622,18,null,null,null,null,null,null,null,132,622,18,null,null,null,null,132,622,18,134,622,18,null,null,null,null,null,null,null,null,null,null,622,18,null,null,null,null,null,null,null,null,134,622,18,null,null,null,null,null,622,18,null,null,128,622,18,null,null,null,null,null,null,132,622,18,null,null,null,null,132,622,18,null,null,null,null,null,null,134,622,18,null,null,null,null,null,622,18,null,null,null,null,null,null,474,622,18,null,null,null,null,null,null,468,null,null,null,null,null,null,389,355,622,18,16,null,null,506,622,18,null,null,null,null,null,null,null,null,622,18,null,null,null,null,null,null,63,null,null,94,330,622,18,null,null,null,null,431,23,null,null,null,null,432,23,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,389,557,32,null,590,null,588,32,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,128,622,39,null,null,null,null,null,128,622,39,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,134,622,39,98,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,128,622,39,null,null,130,622,39,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,450,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,490,622,39,null,null,null,null,null,null,null,null,null,null,null,null,492,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,16,null,498,622,39,null,null,null,null,null,null,null,null,null,null,498,622,39,null,null,128,622,42,null,null,null,622,42,null,null,null,null,132,622,42,132,622,42,null,null,null,null,null,null,null,622,42,null,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,130,622,42,null,null,null,132,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,128,622,42,null,null,130,622,42,null,null,null,null,null,130,622,42,null,null,null,null,622,42,134,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,495,622,42,null,null,null,null,null,null,null,16,null,null,490,622,42,null,null,null,null,null,null,450,622,42,null,null,null,null,null,null,null,null,null,null,null,null,32,564,32,null,null,null,32,3,null,null,2,16,622,39,null,null,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,130,622,39,null,null,null,null,622,39,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,622,39,null,null,null,null,128,622,39,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,132,622,39,null,null,null,null,132,622,39,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,400,null,16,null,498,622,39,null,null,null,null,null,null,null,null,null,null,null,null,16,null,514,622,39,null,null,null,null,null,null,null,null,null,null,479,622,39,null,null,null,null,null,null,null,null,null,null,null,null,498,622,39,null,413,622,39,null,null,null,null,null,null,null,null,null,null,516,622,39,null,null,null,null,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,130,622,42,null,null,null,null,132,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,null,null,null,130,622,42,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,622,42,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,622,42,null,null,null,null,null,128,622,42,null,null,130,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,495,622,42,null,null,null,null,null,null,null,null,null,null,498,622,42,null,null,null,null,null,null,null,null,null,16,503,622,42,null,null,null,null,null,null,null,null,null,16,null,null,490,622,42,null,null,null,null,null,null,null,16,511,622,42,382,389,null,null,389,551,32,null,389,382,389,null,null,389,560,32,592,32,null,null,null,128,622,39,null,null,null,130,622,39,null,null,622,39,null,null,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,622,39,null,null,128,622,39,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,null,134,622,39,null,null,null,622,39,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,134,622,39,null,null,null,null,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,132,622,39,null,null,134,622,39,134,622,39,null,null,null,null,null,null,null,null,null,null,null,59,28,59,null,null,94,330,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,55,295,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,353,622,39,null,null,null,null,null,null,28,59,null,null,94,295,622,39,null,null,null,null,455,622,39,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,134,622,42,null,null,null,null,134,622,42,null,null,null,null,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,134,622,42,null,null,null,null,134,622,42,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,134,622,42,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,59,null,null,94,330,622,42,null,null,490,622,42,null,null,null,null,null,null,null,null,null,null,null,37,295,622,42,null,null,null,null,null,null,null,null,null,null,null,38,330,622,42,null,null,null,null,396,622,42,null,null,null,null,null,null,null,null,28,59,null,null,94,330,622,42,null,null,null,32,382,389,null,null,389,560,32,null,null,null,null,null,null,null,null,32,null,null,null,null,128,622,39,null,null,null,null,128,622,39,null,null,null,null,null,null,132,622,39,null,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,130,622,39,null,622,39,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,130,622,39,null,null,null,null,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,null,132,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,128,622,39,null,null,null,null,null,null,null,null,130,622,39,null,null,null,null,null,132,622,39,null,null,null,null,622,39,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,61,null,null,94,295,622,39,null,null,null,null,469,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,53,295,622,39,null,null,null,null,61,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,330,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,16,503,622,39,null,null,null,null,128,622,42,null,null,null,null,130,622,42,null,null,null,null,130,622,42,null,null,null,null,null,null,132,622,42,null,null,null,null,622,42,null,null,134,622,42,null,null,128,622,42,null,null,null,null,132,622,42,null,null,null,null,null,132,622,42,null,null,null,132,622,42,null,null,null,null,134,622,42,null,null,null,null,134,622,42,null,null,null,null,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,null,134,622,42,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,622,42,null,null,null,null,128,622,42,null,null,null,null,128,622,42,null,null,null,null,null,null,null,null,null,null,132,622,42,null,null,null,null,null,null,622,42,null,null,null,null,null,null,382,389,null,null,389,355,622,42,null,null,null,null,null,null,null,null,null,null,null,38,295,622,42,null,null,59,28,59,null,null,94,295,622,42,null,null,null,null,295,295,622,42,null,null,null,null,null,null,480,622,42,null,null,null,null,null,null,null,null,61,null,null,94,330,622,42,null,null,32,582,null,580,32,588,32,null,null,null,null,null,622,39,null,null,null,null,null,null,130,622,39,null,null,null,null,null,null,null,null,null,134,622,39,null,null,null,622,39,null,128,622,39,null,null,null,null,null,128,622,39,null,null,null,null,130,622,39,null,null,null,null,132,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,130,622,39,null,null,132,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,130,622,39,null,null,null,null,null,null,134,622,39,null,null,null,null,null,null,622,39,null,null,null,null,null,128,622,39,null,null,null,null,null,132,622,39,null,null,null,null,null,132,622,39,null,null,134,622,39,null,null,null,null,622,39,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,519,622,39,null,null,null,null,null,null,null,null,null,501,null,null,null,null,null,null,null,null,null,null,null,16,null,null,514,622,39,null,null,null,null,null,null,null,null,null,null,517,null,null,null,null,null,128,622,42,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,null,null,null,null,null,130,622,42,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,null,622,42,null,null,null,128,622,42,null,null,null,130,622,42,null,null,null,null,null,130,622,42,null,null,132,622,42,null,null,null,null,132,622,42,null,null,null,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,130,622,42,null,null,null,null,null,null,132,622,42,null,null,null,null,null,134,622,42,null,null,null,null,null,null,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,128,622,42,null,null,null,null,null,null,null,128,622,42,null,null,null,null,null,130,622,42,null,null,null,null,null,132,622,42,null,null,622,42,null,null,null,null,null,null,134,622,42,null,null,128,622,42,null,null,null,null,128,622,42,null,null,null,130,622,42,null,null,null,null,null,null,null,null,134,622,42,null,null,null,null,null,622,42,null,null,null,null,null,null,null,null,null,null,null,null,28,59,null,null,94,295,622,42,null,null,null,null,null,null,null,null,null,16,null,null,514,622,42,null,null,null,null,null,null,null,null,382,389,null,null,389,349,622,42,null,null,null,null,null,null,null,null,null,389,355,622,42,null,null,null,null,null,null,null,null,null,null,null,59,28,59,null,null,94,330,622,42,16,null,null,490,622,42],"memalloc":[62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.47512054443359,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,62.87318420410156,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.0804443359375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,64.751708984375,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.37564849853516,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,65.98256683349609,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,66.53610229492188,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.05980682373047,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,67.56636810302734,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.12989807128906,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,68.67479705810547,62.95221710205078,62.95221710205078,62.95221710205078,63.95455169677734,63.95455169677734,63.95455169677734,63.95455169677734,63.95455169677734,63.95455169677734,68.69016265869141,68.69016265869141,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,76.33140563964844,82.86410522460938,82.86410522460938,82.86410522460938,82.86410522460938,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,90.06938934326172,98.73429107666016,98.73429107666016,104.6601181030273,104.6601181030273,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,112.5605545043945,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,62.61360931396484,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.19052124023438,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.69471740722656,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,63.77207183837891,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.23841094970703,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,64.73870086669922,65.16874694824219,65.16874694824219,65.16874694824219,65.16874694824219,65.16874694824219,65.16874694824219,69.38417816162109,69.38417816162109,69.38417816162109,69.38417816162109,69.38417816162109,69.38417816162109,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,69.53177642822266,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,79.68756103515625,87.21620178222656,87.21620178222656,88.43888854980469,88.43888854980469,88.43888854980469,88.43888854980469,88.43888854980469,88.43888854980469,88.43888854980469,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.25154876708984,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,91.76728057861328,105.7802734375,105.7802734375,112.8182525634766,112.8182525634766,112.8182525634766,67.19660186767578,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,68.51705932617188,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,70.25302886962891,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,71.85582733154297,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,72.78675079345703,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,73.5498046875,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,74.36936950683594,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.12071990966797,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,75.7728271484375,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,76.51209259033203,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,77.31436157226562,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,65.48619079589844,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.1201171875,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,66.81338500976562,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,67.52891540527344,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.23873901367188,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,68.95530700683594,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,69.57704162597656,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,70.14495086669922,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.09068298339844,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,71.70052337646484,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.27008819580078,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,72.97084808349609,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,73.63725280761719,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,65.45866394042969,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.13980865478516,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,66.74063110351562,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.33651733398438,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,67.90463256835938,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,68.47795104980469,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.03497314453125,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,69.55534362792969,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.05642700195312,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,70.62123107910156,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.15347290039062,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,71.64865112304688,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.15571594238281,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.62770080566406,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,72.968994140625,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.64951324462891,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,73.92686462402344,74.13105773925781,74.13105773925781,74.13105773925781,74.13105773925781,74.13105773925781,74.13105773925781,77.02796936035156,77.02796936035156,81.77199554443359,81.77199554443359,81.77199554443359,70.93641662597656,70.93641662597656,77.35507965087891,77.35507965087891,77.35507965087891,77.35507965087891,77.35507965087891,77.35507965087891,77.35507965087891,85.49382781982422,85.49382781982422,85.49382781982422,85.49382781982422,85.49382781982422,85.49382781982422,85.49382781982422,92.37362670898438,92.37362670898438,92.37362670898438,92.37362670898438,92.37362670898438,92.37362670898438,93.39666748046875,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,100.2410659790039,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,107.7482147216797,112.8099060058594,112.8099060058594,112.8099060058594,67.68470001220703,67.68470001220703,76.498291015625,76.498291015625,82.22711181640625,82.22711181640625,86.16366577148438,86.16366577148438,86.16366577148438,86.16366577148438,86.16366577148438,86.16366577148438,89.92430877685547,89.92430877685547,95.77970886230469,95.77970886230469,100.819709777832,100.819709777832,106.1367568969727,106.1367568969727,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,108.6281280517578,112.8176116943359,112.8176116943359,112.8176116943359,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,69.61050415039062,75.60325622558594,75.60325622558594,75.60325622558594,75.60325622558594,75.60325622558594,75.60325622558594,75.60325622558594,75.60325622558594,82.25908660888672,82.25908660888672,82.25908660888672,82.25908660888672,82.25908660888672,82.25908660888672,82.25908660888672,88.36461639404297,88.36461639404297,88.36461639404297,88.36461639404297,88.36461639404297,88.36461639404297,88.36461639404297,94.25795745849609,94.25795745849609,94.25795745849609,94.25795745849609,94.25795745849609,94.25795745849609,94.25795745849609,96.30492401123047,96.30492401123047,96.30492401123047,96.30492401123047,96.30492401123047,96.30492401123047,96.30492401123047,102.8170547485352,102.8170547485352,102.8170547485352,102.8170547485352,102.8170547485352,102.8170547485352,102.8170547485352,108.9559173583984,108.9559173583984,112.6734008789062,112.6734008789062,112.6734008789062,71.40987396240234,71.40987396240234,77.61505889892578,77.61505889892578,77.61505889892578,77.61505889892578,77.61505889892578,77.61505889892578,77.61505889892578,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,78.45403289794922,83.37060546875,83.37060546875,83.37060546875,83.37060546875,87.80991363525391,87.80991363525391,87.80991363525391,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,89.60446166992188,94.86585235595703,94.86585235595703,94.86585235595703,94.86585235595703,94.86585235595703,94.86585235595703,101.3806076049805,101.3806076049805,101.3806076049805,102.0409622192383,102.0409622192383,102.0409622192383,102.0409622192383,102.0409622192383,102.0409622192383,102.0409622192383,102.0409622192383,103.9098587036133,103.9098587036133,103.9098587036133,103.9098587036133,103.9098587036133,103.9098587036133,103.9098587036133,107.2212829589844,107.2212829589844,107.2212829589844,107.2212829589844,112.8157043457031,112.8157043457031,112.8157043457031,112.8157043457031,68.69428253173828,68.69428253173828,68.69428253173828,68.69428253173828,68.69428253173828,68.69428253173828,68.69428253173828,68.69428253173828,73.20620727539062,73.20620727539062,73.20620727539062,73.20620727539062,73.20620727539062,73.20620727539062,73.20620727539062,73.20620727539062,73.78733062744141,73.78733062744141,73.78733062744141,73.78733062744141,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,80.03031158447266,85.57605743408203,85.57605743408203,85.57605743408203,85.57605743408203,85.57605743408203,85.57605743408203,92.58669281005859,92.58669281005859,92.58669281005859,98.45333862304688,98.45333862304688,98.45333862304688,98.45333862304688,98.45333862304688,98.45333862304688,98.45333862304688,98.45333862304688,104.7678833007812,104.7678833007812,104.7678833007812,104.7678833007812,104.7678833007812,112.7599792480469,112.7599792480469,112.7599792480469,112.7599792480469,112.7599792480469,112.7599792480469,112.7599792480469,72.75398254394531,72.75398254394531,72.75398254394531,72.75398254394531,72.75398254394531,72.75398254394531,72.75398254394531,78.55625915527344,78.55625915527344,78.55625915527344,78.55625915527344,78.55625915527344,78.55625915527344,78.55625915527344,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,80.54567718505859,86.79759216308594,86.79759216308594,86.79759216308594,86.79759216308594,86.79759216308594,86.79759216308594,86.79759216308594,92.43520355224609,92.43520355224609,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,99.64199829101562,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,107.9468231201172,105.7588577270508,105.7588577270508,105.7588577270508,105.7588577270508,105.7588577270508,105.7588577270508,105.7588577270508,105.7588577270508,74.76364898681641,74.76364898681641,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,80.75523376464844,82.28276062011719,82.28276062011719,87.66133880615234,87.66133880615234,93.71495056152344,93.71495056152344,93.71495056152344,93.71495056152344,93.71495056152344,93.71495056152344,93.71495056152344,100.1560440063477,100.1560440063477,100.1560440063477,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,106.8296432495117,107.7733383178711,107.7733383178711,107.7733383178711,107.7733383178711,107.7733383178711,107.7733383178711,112.8179931640625,112.8179931640625,112.8179931640625,112.8179931640625,112.8179931640625,112.8179931640625,112.8179931640625,112.8179931640625,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,73.55783081054688,79.58182525634766,79.58182525634766,79.58182525634766,79.58182525634766,79.58182525634766,79.58182525634766,79.58182525634766,85.73560333251953,85.73560333251953,85.73560333251953,85.73560333251953,85.73560333251953,85.73560333251953,85.73560333251953,85.73560333251953,91.48429107666016,91.48429107666016,91.48429107666016,91.48429107666016,91.48429107666016,93.93346405029297,93.93346405029297,100.0935440063477,100.0935440063477,106.468132019043,106.468132019043,112.17529296875,112.17529296875,112.17529296875,112.17529296875,112.17529296875,112.17529296875,112.17529296875,112.17529296875,72.98323059082031,72.98323059082031,72.98323059082031,72.98323059082031,73.8685302734375,73.8685302734375,74.73727416992188,74.73727416992188,74.73727416992188,74.73727416992188,74.7481689453125,74.7481689453125,74.7481689453125,74.7481689453125,74.7481689453125,74.7481689453125,74.7481689453125,80.55888366699219,80.55888366699219,81.49650573730469,81.49650573730469,81.49650573730469,81.49650573730469,84.46713256835938,84.46713256835938,84.46713256835938,84.46713256835938,84.46713256835938,87.64918518066406,87.64918518066406,88.42594909667969,88.42594909667969,88.42594909667969,88.42594909667969,88.42594909667969,88.42594909667969,94.6800537109375,94.6800537109375,95.61768341064453,95.61768341064453,95.61768341064453,95.61768341064453,96.75391387939453,96.75391387939453,96.75391387939453,96.75391387939453,96.75391387939453,96.75391387939453,96.75391387939453,96.75391387939453,102.5632781982422,102.5632781982422,103.588249206543,103.588249206543,103.588249206543,103.588249206543,104.9225387573242,104.9225387573242,104.9225387573242,104.9225387573242,104.9225387573242,104.9225387573242,104.9225387573242,104.9225387573242,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,109.7429809570312,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.3016738891602,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,110.8718109130859,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,111.4019546508789,112.8166580200195,112.8166580200195,112.8166580200195,76.29837799072266,76.29837799072266,76.29837799072266,76.29837799072266,76.29837799072266,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,86.46575927734375,93.54018402099609,93.54018402099609,93.54018402099609,93.54018402099609,93.54018402099609,93.54018402099609,100.2248611450195,100.2248611450195,110.9437103271484,110.9437103271484,110.9437103271484,110.9437103271484,110.9437103271484,110.9437103271484,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,73.51922607421875,80.72840118408203,80.72840118408203,80.72840118408203,80.72840118408203,80.72840118408203,81.02721405029297,81.02721405029297,81.02721405029297,81.02721405029297,81.02721405029297,81.02721405029297,81.02721405029297,81.02721405029297,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,85.32218170166016,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,93.06019592285156,97.57847595214844,97.57847595214844,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,99.40212249755859,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.0589218139648,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,100.650146484375,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.2250061035156,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,101.7701263427734,102.3222122192383,102.3222122192383,102.3222122192383,102.3222122192383,102.3222122192383,102.3222122192383,109.9055709838867,109.9055709838867,109.9055709838867,109.9055709838867,109.9055709838867,76.24022674560547,76.24022674560547,83.87957763671875,83.87957763671875,86.61851501464844,86.61851501464844,95.26475524902344,95.26475524902344,95.26475524902344,95.26475524902344,95.26475524902344,95.26475524902344,95.26475524902344,95.26475524902344,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,100.7698516845703,106.3387603759766,106.3387603759766,106.3387603759766,106.3387603759766,106.3387603759766,106.3387603759766,106.3387603759766,106.3387603759766,112.8183746337891,112.8183746337891,112.8183746337891,112.8183746337891,112.8183746337891,112.8183746337891,112.8183746337891,112.8183746337891,79.52999877929688,79.52999877929688,79.52999877929688,79.52999877929688,79.52999877929688,85.79605102539062,85.79605102539062,87.23228454589844,87.23228454589844,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,90.24880981445312,96.42730712890625,101.9602813720703,101.9602813720703,108.3644409179688,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.1375350952148,112.1375350952148,112.1375350952148,62.55233001708984,62.55233001708984,62.55233001708984,62.55233001708984,62.55233001708984,62.55233001708984,65.22597503662109,65.22597503662109,65.22597503662109,65.22597503662109,65.22597503662109,65.22597503662109,65.22597503662109,67.12358856201172,67.12358856201172,67.12358856201172,67.12358856201172,67.12358856201172,67.12358856201172,67.12358856201172,72.44972229003906,72.44972229003906,78.29830169677734,78.29830169677734,78.29830169677734,78.29830169677734,78.29830169677734,78.29830169677734,78.29830169677734,83.85131072998047,83.85131072998047,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,86.95011138916016,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,91.39569854736328,97.64762115478516,97.64762115478516,103.5835418701172,103.5835418701172,109.288818359375,109.288818359375,90.47119903564453,90.47119903564453,90.47119903564453,90.47119903564453,90.47119903564453,90.47119903564453,90.47119903564453,90.47119903564453,65.87513732910156,65.87513732910156,65.87513732910156,65.87513732910156,65.87513732910156,65.87513732910156,65.87513732910156,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,69.39014434814453,75.31881713867188,75.31881713867188,75.31881713867188,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,81.4561767578125,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,85.99703216552734,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,86.79575347900391,91.15110778808594,91.15110778808594,91.15110778808594,91.15110778808594,91.15110778808594,91.15110778808594,96.67031097412109,96.67031097412109,96.67031097412109,96.67031097412109,96.67031097412109,96.67031097412109,96.67031097412109,96.67031097412109,98.82059478759766,98.82059478759766,98.82059478759766,98.82059478759766,98.82059478759766,98.82059478759766,98.82059478759766,98.82059478759766,101.0979232788086,101.0979232788086,101.0979232788086,101.0979232788086,101.0979232788086,101.0979232788086,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,107.1056594848633,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,111.9292755126953,67.79218292236328,67.79218292236328,67.79218292236328,67.79218292236328,67.79218292236328,67.79218292236328,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,70.41859436035156,75.87321472167969,75.87321472167969,75.87321472167969,75.87321472167969,75.87321472167969,75.87321472167969,77.94615173339844,77.94615173339844,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,83.58055877685547,88.44989776611328,88.44989776611328,88.44989776611328,88.44989776611328,88.44989776611328,88.44989776611328,90.52909851074219,90.52909851074219,90.52909851074219,90.52909851074219,90.52909851074219,90.52909851074219,96.612060546875,96.612060546875,96.612060546875,96.612060546875,96.612060546875,96.612060546875,103.553108215332,103.553108215332,103.553108215332,103.553108215332,103.553108215332,103.553108215332,103.553108215332,103.553108215332,103.553108215332,111.2260665893555,111.2260665893555,111.2260665893555,111.2260665893555,111.2260665893555,111.2260665893555,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,76.49091339111328,71.35022735595703,71.35022735595703,71.35022735595703,71.35022735595703,71.35022735595703,78.46059417724609,78.46059417724609,78.46059417724609,78.46059417724609,78.46059417724609,78.46059417724609,78.46059417724609,78.46059417724609,85.11630249023438,85.11630249023438,86.08730316162109,86.08730316162109,86.08730316162109,86.08730316162109,86.08730316162109,86.08730316162109,86.08730316162109,86.08730316162109,93.05805969238281,93.05805969238281,98.94189453125,98.94189453125,98.94189453125,98.94189453125,98.94189453125,98.94189453125,98.94189453125,105.3152542114258,105.3152542114258,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,110.9853363037109,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,66.85453796386719,69.95185852050781,69.95185852050781,69.95185852050781,69.95185852050781,74.75266265869141,74.75266265869141,81.16951751708984,81.16951751708984,81.16951751708984,81.16951751708984,81.16951751708984,81.16951751708984,88.48111724853516,88.48111724853516,94.92811584472656,94.92811584472656,97.48151397705078,97.48151397705078,97.48151397705078,97.48151397705078,97.48151397705078,97.48151397705078,102.9459533691406,102.9459533691406,102.9459533691406,102.9459533691406,102.9459533691406,102.9459533691406,102.9459533691406,102.9459533691406,109.0029296875,109.0029296875,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,112.8052215576172,72.52692413330078,72.52692413330078,78.58536529541016,78.58536529541016,78.58536529541016,78.58536529541016,85.26360321044922,85.26360321044922,86.49529266357422,86.49529266357422,86.49529266357422,86.49529266357422,86.49529266357422,86.49529266357422,92.55906677246094,92.55906677246094,92.55906677246094,92.55906677246094,92.55906677246094,92.55906677246094,98.74115753173828,98.74115753173828,98.74115753173828,98.74115753173828,106.8351974487305,106.8351974487305,112.7206726074219,112.7206726074219,69.11289215087891,69.11289215087891,69.11289215087891,69.11289215087891,69.989501953125,69.989501953125,70.62022399902344,70.62022399902344,70.62022399902344,70.62022399902344,74.83405303955078,74.83405303955078,75.43492889404297,75.43492889404297,75.43492889404297,75.43492889404297,79.98158264160156,79.98158264160156,79.98158264160156,79.98158264160156,79.98158264160156,79.98158264160156,79.98158264160156,81.27313232421875,81.27313232421875,81.27313232421875,81.27313232421875,81.29568481445312,81.29568481445312,81.29568481445312,81.29568481445312,87.03978729248047,87.03978729248047,87.73949432373047,87.73949432373047,88.62113189697266,88.62113189697266,88.62113189697266,88.62113189697266,88.62113189697266,88.62113189697266,88.62113189697266,88.62113189697266,92.69275665283203,92.69275665283203,93.27150726318359,93.27150726318359,93.27150726318359,93.27150726318359,98.62702941894531,98.62702941894531,98.62702941894531,107.3648529052734,107.3648529052734,107.3648529052734,107.3648529052734,107.3648529052734,81.64437866210938,81.64437866210938,81.64437866210938,75.78977203369141,75.78977203369141,75.78977203369141,80.869873046875,80.869873046875,80.869873046875,80.869873046875,80.869873046875,80.869873046875,80.869873046875,80.869873046875,80.869873046875,89.05557250976562,89.05557250976562,93.42632293701172,93.42632293701172,93.42632293701172,93.42632293701172,93.42632293701172,93.42632293701172,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,100.4697799682617,110.2234802246094,110.2234802246094,110.2234802246094,110.2234802246094,110.2234802246094,110.2234802246094,110.2234802246094,108.8550720214844,108.8550720214844,108.8550720214844,108.8550720214844,108.8550720214844,108.8550720214844,108.8550720214844,108.8550720214844,76.23725891113281,76.23725891113281,76.23725891113281,76.23725891113281,76.23725891113281,76.23725891113281,76.23725891113281,77.47123718261719,77.47123718261719,77.47123718261719,77.47123718261719,77.47123718261719,77.47123718261719,77.47123718261719,77.47123718261719,85.18082427978516,85.18082427978516,85.18082427978516,85.18082427978516,85.18082427978516,85.18082427978516,85.18082427978516,92.65468597412109,92.65468597412109,92.65468597412109,92.65468597412109,92.65468597412109,92.65468597412109,99.75093078613281,99.75093078613281,106.0592193603516,106.0592193603516,108.8432769775391,108.8432769775391,108.8432769775391,108.8432769775391,108.8432769775391,108.8432769775391,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,112.810546875,76.413818359375,76.413818359375,76.413818359375,76.413818359375,76.413818359375,76.413818359375,76.413818359375,76.413818359375,83.715087890625,83.715087890625,83.715087890625,83.715087890625,83.715087890625,83.715087890625,89.88248443603516,89.88248443603516,89.88248443603516,89.88248443603516,89.88248443603516,89.88248443603516,89.88248443603516,96.97103881835938,96.97103881835938,103.360481262207,103.360481262207,103.360481262207,103.360481262207,103.360481262207,104.5844650268555,104.5844650268555,104.5844650268555,104.5844650268555,104.5844650268555,112.8182907104492,112.8182907104492,112.8182907104492,112.8182907104492,112.8182907104492,112.8182907104492,112.8182907104492,112.8182907104492,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,74.16596221923828,80.13795471191406,80.13795471191406,80.13795471191406,80.13795471191406,80.13795471191406,80.13795471191406,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,86.51529693603516,92.57978057861328,92.57978057861328,92.57978057861328,92.57978057861328,92.57978057861328,92.57978057861328,92.57978057861328,92.57978057861328,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,97.15686798095703,100.5298233032227,100.5298233032227,107.1123962402344,107.1123962402344,112.805534362793,112.805534362793,112.805534362793,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,74.33216857910156,80.42555236816406,80.42555236816406,80.42555236816406,80.42555236816406,80.42555236816406,80.42555236816406,80.42555236816406,87.26454925537109,87.26454925537109,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,88.07608032226562,92.62357330322266,92.62357330322266,92.62357330322266,92.62357330322266,96.27919769287109,96.27919769287109,96.27919769287109,96.27919769287109,96.27919769287109,96.27919769287109,98.32488250732422,98.32488250732422,98.32488250732422,98.32488250732422,98.32488250732422,98.32488250732422,98.32488250732422,98.32488250732422,102.5651702880859,102.5651702880859,102.5651702880859,102.5651702880859,102.5651702880859,102.5651702880859,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,107.8734436035156,112.3620452880859,112.3620452880859,112.3620452880859,112.3620452880859,112.7802200317383,112.7802200317383,112.7802200317383,112.7802200317383,112.7802200317383,77.79512023925781,77.79512023925781,77.79512023925781,77.79512023925781,77.79512023925781,78.59761047363281,78.59761047363281,78.59761047363281,78.59761047363281,78.59761047363281,78.59761047363281,78.59761047363281,78.59761047363281,82.96122741699219,82.96122741699219,82.96122741699219,82.96122741699219,82.96122741699219,82.96122741699219,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97168731689453,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.97742462158203,88.98165130615234,88.98165130615234,88.98165130615234,88.98165130615234,88.98165130615234,93.67520141601562,93.67520141601562,93.67520141601562,93.67520141601562,93.67520141601562,93.67520141601562,98.46530151367188,98.46530151367188,98.46530151367188,98.46530151367188,98.46530151367188,98.46530151367188,98.46530151367188,102.3111953735352,102.3111953735352,102.3111953735352,102.3111953735352,102.3111953735352,102.3111953735352,102.3111953735352,109.5183868408203,109.5183868408203,109.5183868408203,109.5183868408203,109.5183868408203,109.5183868408203,106.0846633911133,106.0846633911133,106.0846633911133,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,79.16600036621094,85.24014282226562,85.24014282226562,85.24014282226562,85.24014282226562,85.24014282226562,85.24014282226562,90.07920074462891,90.07920074462891,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,91.79183197021484,97.79359436035156,97.79359436035156,103.3591918945312,103.3591918945312,103.3591918945312,103.3591918945312,103.3591918945312,103.3591918945312,103.3591918945312,109.8290863037109,109.8290863037109,75.52701568603516,75.52701568603516,82.57573699951172,82.57573699951172,82.57573699951172,82.57573699951172,82.57573699951172,82.57573699951172,82.57573699951172,84.60549163818359,84.60549163818359,91.46688842773438,91.46688842773438,91.46688842773438,91.46688842773438,91.46688842773438,91.46688842773438,91.46688842773438,99.50908660888672,99.50908660888672,99.50908660888672,99.50908660888672,99.50908660888672,99.50908660888672,99.50908660888672,105.896354675293,105.896354675293,105.896354675293,105.896354675293,105.896354675293,105.896354675293,105.896354675293,105.896354675293,112.7297515869141,112.7297515869141,112.7297515869141,112.7297515869141,112.7297515869141,112.7297515869141,112.7297515869141,112.7297515869141,78.26038360595703,78.26038360595703,78.26038360595703,78.26038360595703,84.38402557373047,84.38402557373047,84.38402557373047,84.38402557373047,84.38402557373047,84.38402557373047,84.38402557373047,84.38402557373047,86.03653717041016,86.03653717041016,86.03653717041016,86.03653717041016,93.22880554199219,93.22880554199219,93.22880554199219,93.22880554199219,93.22880554199219,93.22880554199219,93.22880554199219,99.79833984375,99.79833984375,99.79833984375,99.79833984375,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,103.9399032592773,110.4966049194336,110.4966049194336,110.4966049194336,110.4966049194336,110.4966049194336,110.4966049194336,76.62937927246094,76.62937927246094,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,82.42713928222656,85.3646240234375,85.3646240234375,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,90.97731018066406,97.32096862792969,97.32096862792969,97.32096862792969,97.32096862792969,97.32096862792969,97.32096862792969,97.32096862792969,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,103.6709899902344,110.3122482299805,110.3122482299805,77.07161712646484,77.07161712646484,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,80.37339782714844,81.30683135986328,81.30683135986328,81.30683135986328,81.30683135986328,81.30683135986328,81.30683135986328,86.70448303222656,86.70448303222656,87.24338531494141,87.24338531494141,87.24338531494141,87.24338531494141,88.79182434082031,88.79182434082031,88.79182434082031,88.79182434082031,88.79182434082031,88.79182434082031,88.79182434082031,88.79182434082031,93.19905090332031,93.19905090332031,93.84284973144531,93.84284973144531,93.84284973144531,93.84284973144531,93.8470458984375,93.8470458984375,93.8470458984375,93.8470458984375,99.53086090087891,99.53086090087891,100.118766784668,100.118766784668,100.118766784668,100.118766784668,104.2489776611328,104.2489776611328,104.2489776611328,106.1388626098633,106.1388626098633,106.1388626098633,106.1388626098633,106.1388626098633,106.1388626098633,111.6541519165039,111.6541519165039,78.98600006103516,78.98600006103516,78.98600006103516,78.98600006103516,78.98600006103516,78.98600006103516,91.81226348876953,91.81226348876953,97.84810638427734,97.84810638427734,97.84810638427734,97.84810638427734,97.84810638427734,97.84810638427734,102.9169006347656,102.9169006347656,102.9169006347656,102.9169006347656,102.9169006347656,102.9169006347656,102.9169006347656,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,109.2818298339844,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,91.53170776367188,84.96477508544922,84.96477508544922,84.96477508544922,84.96477508544922,84.96477508544922,84.96477508544922,84.96477508544922,84.96477508544922,91.23292541503906,91.23292541503906,91.23292541503906,91.23292541503906,91.23292541503906,91.23292541503906,97.77568054199219,97.77568054199219,97.77568054199219,97.77568054199219,97.77568054199219,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,99.16823577880859,105.6138229370117,105.6138229370117,105.6138229370117,105.6138229370117,105.6138229370117,105.6138229370117,105.6138229370117,112.8047866821289,112.8047866821289,112.8047866821289,112.8047866821289,112.8047866821289,112.8047866821289,112.8047866821289,112.8047866821289,82.05007171630859,82.05007171630859,82.05007171630859,82.05007171630859,82.05007171630859,82.05007171630859,82.05007171630859,82.05007171630859,89.30735778808594,89.30735778808594,89.30735778808594,89.30735778808594,89.30735778808594,89.30735778808594,95.80911254882812,95.80911254882812,95.80911254882812,95.80911254882812,95.80911254882812,95.80911254882812,95.80911254882812,97.04470062255859,97.04470062255859,97.04470062255859,97.04470062255859,97.04470062255859,97.04470062255859,97.04470062255859,97.04470062255859,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,102.277458190918,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,109.8673248291016,112.8183670043945,112.8183670043945,112.8183670043945,64.34342956542969,64.34342956542969,64.34342956542969,67.66341400146484,67.66341400146484,67.66341400146484,67.66341400146484,67.66341400146484,67.66341400146484,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,75.69258880615234,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,76.72496795654297,82.33180236816406,82.33180236816406,88.99930572509766,88.99930572509766,88.99930572509766,88.99930572509766,88.99930572509766,88.99930572509766,88.99930572509766,95.98712921142578,95.98712921142578,95.98712921142578,95.98712921142578,95.98712921142578,95.98712921142578,95.98712921142578,101.2687911987305,101.2687911987305,104.1760864257812,104.1760864257812,104.1760864257812,104.1760864257812,104.1760864257812,104.1760864257812,104.1760864257812,109.9990768432617,109.9990768432617,80.12258148193359,80.12258148193359,80.12258148193359,80.12258148193359,80.12258148193359,80.12258148193359,70.27883911132812,70.27883911132812,70.27883911132812,70.27883911132812,70.27883911132812,70.27883911132812,70.27883911132812,70.27883911132812,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,76.15819549560547,80.83575439453125,80.83575439453125,80.83575439453125,80.83575439453125,80.83575439453125,80.83575439453125,81.44366455078125,81.44366455078125,81.44366455078125,81.44366455078125,81.44366455078125,81.44366455078125,81.44366455078125,81.44366455078125,85.57789611816406,85.57789611816406,85.57789611816406,85.57789611816406,85.57789611816406,85.57789611816406,91.157470703125,91.157470703125,91.157470703125,91.157470703125,91.157470703125,91.157470703125,94.83940124511719,94.83940124511719,94.83940124511719,94.83940124511719,95.43121337890625,95.43121337890625,95.43121337890625,95.43121337890625,95.43121337890625,95.43121337890625,95.43121337890625,100.7863006591797,100.7863006591797,100.7863006591797,100.7863006591797,100.7863006591797,100.7863006591797,104.3404312133789,104.3404312133789,104.3404312133789,104.3404312133789,106.7884063720703,106.7884063720703,106.7884063720703,109.8160400390625,109.8160400390625,109.8160400390625,109.8160400390625,109.8160400390625,109.8160400390625,109.8160400390625,109.8160400390625,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,112.7747497558594,67.49986267089844,67.49986267089844,67.49986267089844,67.49986267089844,67.49986267089844,67.49986267089844,73.52864837646484,73.52864837646484,73.52864837646484,73.52864837646484,73.52864837646484,73.52864837646484,77.24596405029297,77.24596405029297,77.24596405029297,77.24596405029297,77.24596405029297,77.24596405029297,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,83.44700622558594,89.36058044433594,89.36058044433594,89.36058044433594,89.36058044433594,89.36058044433594,89.36058044433594,89.36058044433594,94.76292419433594,94.76292419433594,94.76292419433594,102.7158126831055,102.7158126831055,109.4596633911133,109.4596633911133,109.4596633911133,109.4596633911133,109.4596633911133,109.4596633911133,109.4596633911133,70.59420776367188,70.59420776367188,70.59420776367188,70.59420776367188,70.59420776367188,70.59420776367188,70.59420776367188,70.59420776367188,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,71.97697448730469,75.41238403320312,75.41238403320312,81.29190063476562,81.29190063476562,81.29190063476562,81.29190063476562,81.29190063476562,81.29190063476562,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,87.87718963623047,94.14199066162109,94.14199066162109,94.14199066162109,94.14199066162109,94.14199066162109,94.14199066162109,94.14199066162109,94.14199066162109,99.30694580078125,99.30694580078125,99.30694580078125,102.1559524536133,102.1559524536133,108.6430358886719,108.6430358886719,108.6430358886719,108.6430358886719,108.6430358886719,108.6430358886719,108.6430358886719,108.6430358886719,112.8065032958984,112.8065032958984,112.8065032958984,72.64980316162109,72.64980316162109,72.64980316162109,72.64980316162109,72.64980316162109,72.64980316162109,72.64980316162109,78.49119567871094,78.49119567871094,82.40441131591797,82.40441131591797,82.40441131591797,82.40441131591797,82.40441131591797,82.40441131591797,86.5626220703125,86.5626220703125,93.52156066894531,93.52156066894531,93.52156066894531,93.52156066894531,93.52156066894531,93.52156066894531,99.47438812255859,99.47438812255859,106.6229095458984,106.6229095458984,112.8179168701172,112.8179168701172,112.8179168701172,112.8179168701172,112.8179168701172,112.8179168701172,112.8179168701172,112.8179168701172,71.51910400390625,71.51910400390625,71.51910400390625,71.51910400390625,71.51910400390625,73.1441650390625,73.1441650390625,73.1441650390625,73.1441650390625,73.1441650390625,73.1441650390625,73.1441650390625,78.96097564697266,78.96097564697266,86.99161529541016,86.99161529541016,86.99161529541016,86.99161529541016,86.99161529541016,86.99161529541016,86.99161529541016,86.99161529541016,94.07564544677734,94.07564544677734,94.07564544677734,94.07564544677734,94.07564544677734,94.07564544677734,94.07564544677734,94.07564544677734,100.2338027954102,100.2338027954102,104.3117523193359,104.3117523193359,104.8597106933594,104.8597106933594,105.7220687866211,105.7220687866211,105.7220687866211,105.7220687866211,105.7220687866211,105.7220687866211,111.4931182861328,111.4931182861328,112.5421524047852,112.5421524047852,112.5421524047852,112.5421524047852,112.5421524047852,112.5421524047852,70.29764556884766,70.29764556884766,74.68467712402344,74.68467712402344,75.57815551757812,75.57815551757812,75.57815551757812,75.57815551757812,75.57815551757812,75.57815551757812,81.46855926513672,81.46855926513672,82.22608947753906,82.22608947753906,82.22608947753906,82.22608947753906,85.72755432128906,85.72755432128906,85.72755432128906,87.74592590332031,87.74592590332031,88.52569580078125,88.52569580078125,88.52569580078125,88.52569580078125,93.17603302001953,93.17603302001953,93.17603302001953,100.523078918457,100.523078918457,100.523078918457,100.523078918457,100.523078918457,100.523078918457,100.523078918457,112.4020004272461,112.4020004272461,112.4020004272461,73.16633605957031,73.16633605957031,77.17730712890625,77.17730712890625,77.17730712890625,77.17730712890625,77.17730712890625,77.17730712890625,77.17730712890625,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,82.90756225585938,91.80873107910156,91.80873107910156,98.07766723632812,98.07766723632812,104.2110977172852,104.2110977172852,104.2110977172852,104.2110977172852,104.2110977172852,104.2110977172852,104.2110977172852,112.8006134033203,112.8006134033203,112.8006134033203,77.02290344238281,77.02290344238281,82.24469757080078,82.24469757080078,82.24469757080078,82.24469757080078,82.24469757080078,82.24469757080078,85.50989532470703,85.50989532470703,85.50989532470703,85.50989532470703,85.50989532470703,85.50989532470703,85.50989532470703,91.50119018554688,91.50119018554688,97.49723815917969,97.49723815917969,97.49723815917969,97.49723815917969,97.49723815917969,97.49723815917969,97.49723815917969,104.1599273681641,104.1599273681641,104.1599273681641,104.1599273681641,104.1599273681641,104.1599273681641,111.9416809082031,111.9416809082031,111.9416809082031,111.9416809082031,111.9416809082031,111.9416809082031,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,112.8184127807617,74.73407745361328,74.73407745361328,83.10076904296875,83.10076904296875,83.10076904296875,83.10076904296875,89.91281890869141,89.91281890869141,89.91281890869141,89.91281890869141,89.91281890869141,89.91281890869141,89.91281890869141,95.77434539794922,95.77434539794922,95.77434539794922,95.77434539794922,95.77434539794922,95.77434539794922,95.77434539794922,95.77434539794922,102.3407592773438,102.3407592773438,102.3407592773438,102.3407592773438,102.3407592773438,102.3407592773438,102.3407592773438,112.2099761962891,112.2099761962891,112.2099761962891,112.2099761962891,112.2099761962891,112.2099761962891,112.2099761962891,112.2099761962891,74.37863922119141,74.37863922119141,74.37863922119141,74.37863922119141,74.37863922119141,74.37863922119141,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,75.48439025878906,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,81.77474212646484,87.78479766845703,87.78479766845703,87.78479766845703,87.78479766845703,87.78479766845703,87.78479766845703,87.78479766845703,94.56147766113281,94.56147766113281,94.56147766113281,94.56147766113281,94.56147766113281,94.56147766113281,94.56147766113281,104.8445739746094,104.8445739746094,109.7099533081055,112.8124694824219,112.8124694824219,112.8124694824219,76.50727844238281,76.50727844238281,76.50727844238281,76.50727844238281,76.50727844238281,76.50727844238281,76.50727844238281,76.50727844238281,83.72420501708984,83.72420501708984,83.72420501708984,83.72420501708984,83.72420501708984,83.72420501708984,90.49797058105469,90.49797058105469,96.94016265869141,96.94016265869141,96.94016265869141,96.94016265869141,96.94016265869141,96.94016265869141,96.94016265869141,96.94016265869141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,98.68332672119141,103.3943099975586,103.3943099975586,103.3943099975586,103.3943099975586,103.3943099975586,103.3943099975586,108.8718185424805,108.8718185424805,108.8718185424805,108.8718185424805,108.8718185424805,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,109.6315460205078,92.79304504394531,92.79304504394531,92.79304504394531,92.79304504394531,92.79304504394531,92.79304504394531,92.79304504394531,92.79304504394531,76.82299041748047,76.82299041748047,76.82299041748047,76.82299041748047,81.21092224121094,81.21092224121094,81.21092224121094,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,82.49089050292969,87.20195007324219,87.20195007324219,87.20195007324219,87.20195007324219,91.15234375,91.15234375,91.15234375,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,92.96302795410156,97.63251495361328,97.63251495361328,97.63251495361328,97.63251495361328,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,102.8495330810547,107.5207672119141,107.5207672119141,107.5207672119141,107.5207672119141,107.5207672119141,107.5207672119141,112.8159332275391,112.8159332275391,112.8159332275391,78.37857055664062,78.37857055664062,86.85087585449219,86.85087585449219,86.85087585449219,86.85087585449219,86.85087585449219,86.85087585449219,86.85087585449219,95.31211853027344,95.31211853027344,95.31211853027344,95.31211853027344,95.31211853027344,95.31211853027344,95.31211853027344,95.31211853027344,101.774772644043,101.774772644043,107.7771911621094,107.7771911621094,107.7771911621094,107.7771911621094,107.7771911621094,107.7771911621094,107.7771911621094,107.7771911621094,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,112.8180999755859,80.76272583007812,80.76272583007812,80.76272583007812,80.76272583007812,80.76272583007812,80.76272583007812,80.76272583007812,84.28781890869141,84.28781890869141,84.28781890869141,84.28781890869141,84.28781890869141,84.28781890869141,88.43739318847656,88.43739318847656,94.22776031494141,94.22776031494141,100.2792663574219,100.2792663574219,106.0040283203125,106.0040283203125,106.0040283203125,106.0040283203125,106.0040283203125,106.0040283203125,106.0040283203125,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,112.8010559082031,80.10012054443359,80.10012054443359,80.10012054443359,80.10012054443359,80.10012054443359,80.10012054443359,82.66998291015625,82.66998291015625,82.66998291015625,82.66998291015625,82.66998291015625,82.66998291015625,82.66998291015625,88.40792083740234,88.40792083740234,88.40792083740234,88.40792083740234,88.40792083740234,88.40792083740234,88.40792083740234,94.87950897216797,94.87950897216797,94.87950897216797,94.87950897216797,94.87950897216797,104.0494689941406,104.0494689941406,110.3504409790039,110.3504409790039,110.3504409790039,110.3504409790039,110.3504409790039,110.3504409790039,110.3504409790039,110.3504409790039,78.73454284667969,78.73454284667969,82.81043243408203,82.81043243408203,82.81043243408203,82.81043243408203,82.81043243408203,86.63426208496094,86.63426208496094,92.62471771240234,92.62471771240234,100.0039825439453,100.0039825439453,100.0039825439453,100.0039825439453,100.0039825439453,100.0039825439453,106.4279632568359,112.8017730712891,112.8017730712891,78.55253601074219,78.55253601074219,78.55253601074219,78.55253601074219,82.55614471435547,82.55614471435547,88.57367706298828,88.57367706298828,94.70122528076172,94.70122528076172,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,101.1305847167969,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,110.5252990722656,80.05677795410156,80.05677795410156,80.05677795410156,80.05677795410156,80.05677795410156,80.05677795410156,80.05677795410156,80.05677795410156,89.29501342773438,89.29501342773438,89.29501342773438,89.29501342773438,89.29501342773438,89.29501342773438,89.29501342773438,89.29501342773438,94.95876312255859,94.95876312255859,94.95876312255859,94.95876312255859,94.95876312255859,94.95876312255859,96.06443786621094,96.06443786621094,96.06443786621094,96.06443786621094,96.06443786621094,96.06443786621094,96.06443786621094,96.11608123779297,96.11608123779297,96.11608123779297,96.11608123779297,100.4863891601562,100.4863891601562,100.4863891601562,102.5072250366211,102.5072250366211,102.5072250366211,102.5072250366211,102.5072250366211,102.5072250366211,107.123779296875,107.123779296875,108.3333129882812,108.3333129882812,108.3333129882812,108.3333129882812,108.3333129882812,108.3333129882812,112.7840194702148,112.7840194702148,112.7840194702148,81.09490203857422,81.09490203857422,81.09490203857422,81.09490203857422,81.77368927001953,81.77368927001953,81.77368927001953,81.77368927001953,81.77368927001953,81.77368927001953,87.51495361328125,87.51495361328125,88.68988037109375,88.68988037109375,88.68988037109375,88.68988037109375,92.23683929443359,92.23683929443359,92.23683929443359,92.23683929443359,92.23683929443359,92.23683929443359,92.23683929443359,97.70090484619141,97.70090484619141,97.70090484619141,97.70090484619141,97.70090484619141,97.70090484619141,97.70090484619141,111.0893478393555,111.0893478393555,111.0893478393555,111.0893478393555,82.34097290039062,82.34097290039062,82.34097290039062,85.80885314941406,85.80885314941406,85.80885314941406,85.80885314941406,85.80885314941406,85.80885314941406,94.27040863037109,94.27040863037109,94.27040863037109,94.27040863037109,94.27040863037109,94.27040863037109,99.78555297851562,99.78555297851562,99.78555297851562,99.78555297851562,99.78555297851562,99.78555297851562,106.9340896606445,106.9340896606445,106.9340896606445,106.9340896606445,106.9340896606445,106.9340896606445,106.9340896606445,112.8182678222656,112.8182678222656,112.8182678222656,69.62832641601562,69.62832641601562,69.62832641601562,68.75385284423828,68.75385284423828,72.99260711669922,72.99260711669922,82.11331939697266,82.11331939697266,82.11331939697266,82.11331939697266,82.11331939697266,82.11331939697266,82.11331939697266,90.83293914794922,90.83293914794922,97.74954223632812,97.74954223632812,97.74954223632812,104.9363555908203,104.9363555908203,104.9363555908203,104.9363555908203,104.9363555908203,104.9363555908203,104.9363555908203,111.8877029418945,111.8877029418945,111.8877029418945,111.8877029418945,111.8877029418945,111.8877029418945,111.8877029418945,111.8877029418945,73.46743774414062,73.46743774414062,73.46743774414062,73.90602874755859,73.90602874755859,73.90602874755859,73.90602874755859,73.90602874755859,74.92533874511719,74.92533874511719,74.92533874511719,74.92533874511719,74.92533874511719,74.92533874511719,74.92533874511719,74.92533874511719,83.23949432373047,83.23949432373047,89.68976593017578,89.68976593017578,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,95.78074645996094,102.3913879394531,102.3913879394531,102.3913879394531,102.3913879394531,102.3913879394531,102.3913879394531,108.2126541137695,108.2126541137695,108.2126541137695,108.2126541137695,108.2126541137695,108.2126541137695,108.2126541137695,110.3538284301758,110.3538284301758,110.3538284301758,110.3538284301758,110.3538284301758,110.3538284301758,110.3538284301758,67.15912628173828,67.15912628173828,67.15912628173828,67.15912628173828,67.15912628173828,67.15912628173828,67.15912628173828,67.15912628173828,75.51826477050781,75.51826477050781,75.51826477050781,75.51826477050781,75.51826477050781,75.51826477050781,75.51826477050781,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,81.83986663818359,89.13425445556641,89.13425445556641,89.13425445556641,89.13425445556641,89.13425445556641,96.64615631103516,96.64615631103516,96.64615631103516,96.64615631103516,96.64615631103516,96.64615631103516,96.64615631103516,102.6177444458008,102.6177444458008,105.6257171630859,105.6257171630859,105.6257171630859,105.6257171630859,105.6257171630859,111.0773620605469,111.0773620605469,68.37586975097656,68.37586975097656,68.37586975097656,68.37586975097656,68.37586975097656,68.37586975097656,68.37586975097656,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,73.37442779541016,79.51807403564453,79.51807403564453,79.51807403564453,87.43818664550781,87.43818664550781,93.57398223876953,93.57398223876953,93.57398223876953,93.57398223876953,93.57398223876953,93.57398223876953,93.57398223876953,95.41545104980469,95.41545104980469,95.41545104980469,95.41545104980469,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,95.485595703125,100.5472869873047,100.5472869873047,100.5472869873047,100.5472869873047,104.4782180786133,104.4782180786133,104.4782180786133,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,105.605354309082,110.2690277099609,110.2690277099609,110.2690277099609,110.2690277099609,108.0753555297852,108.0753555297852,108.0753555297852,108.0753555297852,108.0753555297852,108.0753555297852,108.0753555297852,108.0753555297852,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,70.82600402832031,76.09681701660156,76.09681701660156,76.09681701660156,76.09681701660156,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,80.72225189208984,85.60964202880859,85.60964202880859,87.41930389404297,87.41930389404297,87.41930389404297,87.41930389404297,87.41930389404297,87.41930389404297,87.41930389404297,87.41930389404297,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,91.15561676025391,95.69436645507812,95.69436645507812,95.69436645507812,95.69436645507812,99.9683837890625,99.9683837890625,104.8063430786133,104.8063430786133,104.8063430786133,104.8063430786133,104.8063430786133,104.8063430786133,104.8063430786133,104.8063430786133,110.8245849609375,110.8245849609375,70.98479461669922,70.98479461669922,70.98479461669922,70.98479461669922,70.98479461669922,70.98479461669922,70.98479461669922,77.21683502197266,77.21683502197266,84.30068969726562,84.30068969726562,84.30068969726562,84.30068969726562,84.30068969726562,90.24990844726562,90.24990844726562,90.24990844726562,90.24990844726562,90.24990844726562,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,91.45541381835938,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,100.7866744995117,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,107.1272277832031,112.817741394043,112.817741394043,112.817741394043,112.817741394043,112.817741394043,112.817741394043,112.817741394043,112.817741394043,73.92191314697266,73.92191314697266,73.92191314697266,73.92191314697266,73.92191314697266,73.92191314697266,73.92191314697266,73.92191314697266,79.33908843994141,79.33908843994141,79.33908843994141,79.33908843994141,79.33908843994141,79.33908843994141,79.33908843994141,79.33908843994141,83.52650451660156,83.52650451660156,87.4053955078125,87.4053955078125,87.4053955078125,87.4053955078125,87.4053955078125,87.4053955078125,96.84033203125,96.84033203125,96.84033203125,96.84033203125,96.84033203125,96.84033203125,96.84033203125,96.84033203125,103.1598815917969,103.1598815917969,109.2406997680664,109.2406997680664,85.27764129638672,85.27764129638672,85.27764129638672,75.24018859863281,75.24018859863281,81.09516143798828,81.09516143798828,81.09516143798828,81.09516143798828,82.31759643554688,82.31759643554688,82.31759643554688,82.31759643554688,91.02587890625,91.02587890625,91.02587890625,91.02587890625,91.02587890625,91.02587890625,91.02587890625,98.15450286865234,98.15450286865234,98.15450286865234,98.15450286865234,98.15450286865234,98.15450286865234,98.15450286865234,98.15450286865234,105.2973098754883,105.2973098754883,105.2973098754883,105.2973098754883,105.2973098754883,105.2973098754883,105.2973098754883,111.5360412597656,111.5360412597656,72.32140350341797,72.32140350341797,72.32140350341797,72.32140350341797,72.32140350341797,72.32140350341797,72.32140350341797,76.80360412597656,76.80360412597656,76.80360412597656,76.80360412597656,76.80360412597656,76.80360412597656,76.80360412597656,76.80360412597656,77.84627532958984,77.84627532958984,77.84627532958984,77.84627532958984,77.84627532958984,77.84627532958984,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,86.28052520751953,92.51776123046875,92.51776123046875,92.51776123046875,92.51776123046875,92.51776123046875,92.51776123046875,92.51776123046875,99.705078125,99.705078125,99.705078125,99.705078125,99.705078125,107.9389038085938,107.9389038085938,107.9389038085938,107.9389038085938,107.9389038085938,107.9389038085938,112.8183898925781,112.8183898925781,112.8183898925781,112.8183898925781,112.8183898925781,112.8183898925781,112.8183898925781,112.8183898925781,74.63983917236328,74.63983917236328,74.63983917236328,74.63983917236328,75.49947357177734,75.49947357177734,75.99723815917969,75.99723815917969,75.99723815917969,75.99723815917969,79.53453063964844,79.53453063964844,79.53453063964844,81.57006072998047,81.57006072998047,82.22093200683594,82.22093200683594,82.22093200683594,82.22093200683594,86.42958068847656,86.42958068847656,86.42958068847656,88.55023193359375,88.55023193359375,89.19959259033203,89.19959259033203,89.19959259033203,89.19959259033203,94.31060028076172,94.31060028076172,94.31060028076172,95.36058044433594,95.36058044433594,95.36058044433594,95.36058044433594,95.36058044433594,95.36058044433594,100.4660568237305,100.4660568237305,101.0164337158203,101.0164337158203,101.0164337158203,101.0164337158203,104.5646820068359,104.5646820068359,104.5646820068359,104.5646820068359,104.5646820068359,104.5646820068359,108.7505340576172,108.7505340576172,112.8174896240234,112.8174896240234,112.8174896240234,81.574462890625,81.574462890625,81.574462890625,88.10649108886719,88.10649108886719,88.10649108886719,88.10649108886719,88.10649108886719,94.90067291259766,94.90067291259766,102.1812438964844,102.1812438964844,110.0977630615234,110.0977630615234,74.53380584716797,74.53380584716797,79.90190124511719,79.90190124511719,79.90190124511719,79.90190124511719,79.90190124511719,79.90190124511719,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,84.26246643066406,87.45936584472656,87.45936584472656,87.45936584472656,87.45936584472656,87.45936584472656,87.45936584472656,87.45936584472656,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,94.41825103759766,101.946891784668,101.946891784668,101.946891784668,101.946891784668,108.7322387695312,108.7322387695312,108.7322387695312,108.7322387695312,108.7322387695312,77.67225646972656,77.67225646972656,77.67225646972656,77.67225646972656,90.26923370361328,90.26923370361328,90.26923370361328,90.26923370361328,90.26923370361328,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,93.60649871826172,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,98.95557403564453,105.3174133300781,105.3174133300781,105.3174133300781,105.3174133300781,105.3174133300781,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,112.8178405761719,79.39209747314453,79.39209747314453,79.39209747314453,79.39209747314453,79.39209747314453,79.39209747314453,79.39209747314453,79.39209747314453,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,85.91462707519531,86.89108276367188,86.89108276367188,92.53639221191406,92.53639221191406,92.53639221191406,92.53639221191406,92.53639221191406,92.53639221191406,98.75776672363281,98.75776672363281,98.75776672363281,98.75776672363281,98.75776672363281,106.6465225219727,106.6465225219727,106.6465225219727,106.6465225219727,106.6465225219727,106.6465225219727,106.6465225219727,112.5697631835938,112.5697631835938,112.5697631835938,112.5697631835938,112.5697631835938,112.5697631835938,112.5697631835938,112.5697631835938,81.04605865478516,81.04605865478516,81.04605865478516,81.04605865478516,81.04605865478516,81.04605865478516,81.04605865478516,81.92137145996094,81.92137145996094,81.92137145996094,81.92137145996094,81.92137145996094,81.92137145996094,88.833251953125,88.833251953125,88.833251953125,88.833251953125,88.833251953125,88.833251953125,88.833251953125,96.94670867919922,96.94670867919922,103.1524047851562,103.1524047851562,103.1524047851562,103.1524047851562,109.8619613647461,109.8619613647461,109.8619613647461,109.8619613647461,109.8619613647461,109.8619613647461,109.8619613647461,109.8619613647461,112.812141418457,112.812141418457,112.812141418457,112.812141418457,112.812141418457,112.812141418457,84.0748291015625,84.0748291015625,85.95912170410156,85.95912170410156,85.95912170410156,85.95912170410156,91.45121002197266,91.45121002197266,91.45121002197266,91.45121002197266,91.45121002197266,91.45121002197266,91.45121002197266,91.45121002197266,96.48371887207031,96.48371887207031,96.48371887207031,96.48371887207031,96.48371887207031,96.48371887207031,96.48371887207031,96.48371887207031,102.4228286743164,102.4228286743164,102.4228286743164,102.4228286743164,102.4228286743164,102.4228286743164,102.4228286743164,110.0043106079102,110.0043106079102,111.3965377807617,111.3965377807617,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,88.63383483886719,83.86215972900391,83.86215972900391,83.86215972900391,83.86215972900391,83.86215972900391,83.86215972900391,83.86215972900391,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,89.36141204833984,97.538330078125,97.538330078125,103.2566986083984,103.2566986083984,103.2566986083984,103.2566986083984,103.2566986083984,103.2566986083984,103.2566986083984,103.2566986083984,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,105.7517242431641,106.2068176269531,106.2068176269531,106.2068176269531,106.2068176269531,106.2068176269531,106.2068176269531,110.2576065063477,110.2576065063477,110.2576065063477,110.2576065063477,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,112.7694473266602,83.12187194824219,83.12187194824219,83.3814697265625,83.3814697265625,83.3814697265625,83.3814697265625,83.3814697265625,83.3814697265625,83.3814697265625,83.3814697265625,88.05908203125,88.05908203125,88.05908203125,88.05908203125,89.50987243652344,89.50987243652344,89.50987243652344,89.50987243652344,89.50987243652344,89.50987243652344,89.50987243652344,89.50987243652344,94.15428161621094,94.15428161621094,94.15428161621094,94.15428161621094,94.15428161621094,94.15428161621094,98.17311859130859,98.17311859130859,98.17311859130859,98.17311859130859,98.85511016845703,98.85511016845703,105.0631332397461,105.0631332397461,105.0631332397461,105.0631332397461,105.0631332397461,105.0631332397461,105.0631332397461,105.0631332397461,105.7445220947266,105.7445220947266,105.7445220947266,105.7445220947266,109.5756988525391,109.5756988525391,109.5756988525391,109.5756988525391,90.95691680908203,90.95691680908203,90.95691680908203,90.95691680908203,90.95691680908203,90.95691680908203,90.95691680908203,90.95691680908203,84.16173553466797,84.16173553466797,84.16173553466797,84.16173553466797,84.16173553466797,84.16173553466797,85.62564086914062,85.62564086914062,85.62564086914062,85.62564086914062,85.62564086914062,85.62564086914062,85.62564086914062,85.62564086914062,88.52352142333984,88.52352142333984,88.52352142333984,88.52352142333984,94.74563598632812,94.74563598632812,94.74563598632812,94.74563598632812,94.74563598632812,100.9142990112305,100.9142990112305,108.500846862793,108.500846862793,108.500846862793,108.500846862793,108.500846862793,108.500846862793,108.500846862793,112.8171615600586,112.8171615600586,112.8171615600586,84.44535064697266,84.44535064697266,84.44535064697266,84.44535064697266,84.44535064697266,84.44535064697266,84.44535064697266,84.44535064697266,93.03012084960938,93.03012084960938,93.03012084960938,93.03012084960938,93.03012084960938,93.03012084960938,93.03012084960938,93.03012084960938,98.69734954833984,98.69734954833984,101.879150390625,101.879150390625,101.879150390625,101.879150390625,101.879150390625,101.879150390625,106.1399383544922,106.1399383544922,106.1399383544922,106.1399383544922,106.1399383544922,106.1399383544922,106.1399383544922,112.362434387207,112.362434387207,85.35870361328125,85.35870361328125,85.35870361328125,85.35870361328125,85.35870361328125,91.58939361572266,91.58939361572266,91.58939361572266,91.58939361572266,91.58939361572266,91.58939361572266,91.58939361572266,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,97.47273254394531,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,103.4018173217773,105.2187271118164,105.2187271118164,105.2187271118164,105.2187271118164,105.2187271118164,105.2187271118164,105.2187271118164,105.2187271118164,110.8876495361328,110.8876495361328,112.8184051513672,112.8184051513672,112.8184051513672,112.8184051513672,112.8184051513672,112.8184051513672,112.8184051513672,112.8184051513672,69.91353607177734,69.91353607177734,69.91353607177734,69.91353607177734,69.91353607177734,69.91353607177734,69.91353607177734,74.55718231201172,74.55718231201172,74.55718231201172,80.52078247070312,80.52078247070312,81.90225219726562,81.90225219726562,88.28810882568359,88.28810882568359,95.88779449462891,95.88779449462891,95.88779449462891,95.88779449462891,95.88779449462891,95.88779449462891,103.3806076049805,103.3806076049805,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,109.5497665405273,112.1115036010742,112.1115036010742,112.1115036010742,112.1115036010742,112.1115036010742,112.1115036010742,112.1115036010742,73.45710754394531,73.45710754394531,73.45710754394531,73.45710754394531,73.45710754394531,71.14768218994141,71.14768218994141,77.46552276611328,77.46552276611328,77.46552276611328,77.46552276611328,77.46552276611328,77.46552276611328,77.46552276611328,85.10400390625,85.10400390625,85.10400390625,85.10400390625,85.10400390625,85.10400390625,85.10400390625,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,91.58965301513672,94.20162963867188,94.20162963867188,94.20162963867188,94.20162963867188,94.20162963867188,94.20162963867188,94.20162963867188,94.54081726074219,94.54081726074219,96.0892333984375,96.0892333984375,96.0892333984375,96.0892333984375,100.7186737060547,100.7186737060547,100.7186737060547,101.8561630249023,101.8561630249023,103.3294982910156,103.3294982910156,103.3294982910156,103.3294982910156,108.3332290649414,108.3332290649414,108.6789245605469,108.6789245605469,110.239372253418,110.239372253418,112.5413208007812,112.5413208007812,112.5413208007812,112.5413208007812,112.5413208007812,68.48240661621094,68.48240661621094,68.48240661621094,68.48240661621094,68.48240661621094,68.48240661621094,69.78422546386719,69.78422546386719,71.02992248535156,71.02992248535156,71.02992248535156,71.02992248535156,75.2132568359375,75.2132568359375,75.2132568359375,75.2132568359375,77.58818054199219,77.58818054199219,78.95815277099609,78.95815277099609,78.95815277099609,78.95815277099609,81.89415740966797,81.89415740966797,81.89415740966797,81.89415740966797,81.89415740966797,81.89415740966797,81.89415740966797,86.87855529785156,86.87855529785156,86.87855529785156,86.87855529785156,86.87855529785156,86.87855529785156,98.12825775146484,98.12825775146484,104.9264831542969,104.9264831542969,104.9264831542969,104.9264831542969,111.2971878051758,111.2971878051758,69.44472503662109,69.44472503662109,78.14797973632812,78.14797973632812,84.88140869140625,84.88140869140625,86.92007446289062,86.92007446289062,86.92007446289062,86.92007446289062,86.92007446289062,86.92007446289062,86.92007446289062,86.92007446289062,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,91.18059539794922,97.57903289794922,97.57903289794922,97.57903289794922,97.57903289794922,97.57903289794922,97.57903289794922,101.515983581543,101.515983581543,101.515983581543,101.515983581543,105.7701110839844,105.7701110839844,104.1015777587891,104.1015777587891,104.1015777587891,104.1015777587891,104.1015777587891,104.1015777587891,78.70377349853516,78.70377349853516,78.70377349853516,78.70377349853516,78.70377349853516,82.88968658447266,89.27001190185547,89.27001190185547,94.20920562744141,94.20920562744141,100.5576629638672,100.5576629638672,104.1600723266602,104.1600723266602,104.1600723266602,104.1600723266602,108.8206329345703,108.8206329345703,108.8206329345703,108.8206329345703,108.8206329345703,108.8206329345703,108.8206329345703,96.63756561279297,96.63756561279297,96.63756561279297,96.63756561279297,96.63756561279297,96.63756561279297,96.63756561279297,96.63756561279297,75.92754364013672,75.92754364013672,75.92754364013672,75.92754364013672,81.43869018554688,81.43869018554688,81.43869018554688,81.43869018554688,81.43869018554688,81.43869018554688,81.43869018554688,87.53445434570312,87.53445434570312,87.53445434570312,87.53445434570312,87.53445434570312,87.53445434570312,87.53445434570312,89.54161071777344,89.54161071777344,89.54161071777344,95.29325103759766,95.29325103759766,95.29325103759766,95.29325103759766,95.29325103759766,95.29325103759766,95.29325103759766,95.29325103759766,101.5186004638672,101.5186004638672,101.5186004638672,101.5186004638672,101.5186004638672,101.5186004638672,101.5186004638672,101.5186004638672,107.9399185180664,107.9399185180664,107.9399185180664,107.9399185180664,107.9399185180664,107.9399185180664,107.9399185180664,112.8100357055664,112.8100357055664,112.8100357055664,112.8100357055664,112.8100357055664,112.8100357055664,112.8100357055664,112.8100357055664,73.83968353271484,73.83968353271484,73.83968353271484,73.83968353271484,73.83968353271484,73.83968353271484,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,75.11734008789062,81.91232299804688,81.91232299804688,81.91232299804688,81.91232299804688,81.91232299804688,81.91232299804688,89.42776489257812,89.42776489257812,95.99669647216797,95.99669647216797,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,101.9799728393555,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,105.2095642089844,110.6764526367188,110.6764526367188,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,74.30081939697266,78.81362915039062,78.81362915039062,78.81362915039062,78.81362915039062,78.81362915039062,84.67107391357422,84.67107391357422,92.29514312744141,92.29514312744141,92.29514312744141,92.29514312744141,92.29514312744141,92.29514312744141,92.29514312744141,92.29514312744141,97.29112243652344,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,98.21383666992188,102.4777374267578,102.4777374267578,102.4777374267578,102.4777374267578,106.6007614135742,106.6007614135742,106.6007614135742,108.2781143188477,108.2781143188477,108.2781143188477,108.2781143188477,108.2781143188477,108.2781143188477,111.8515930175781,111.8515930175781,111.8515930175781,111.8515930175781,111.8515930175781,111.8515930175781,77.30686950683594,77.30686950683594,77.30686950683594,77.30686950683594,77.30686950683594,79.66632843017578,79.66632843017578,79.66632843017578,79.66632843017578,79.66632843017578,79.66632843017578,83.18733978271484,83.18733978271484,83.18733978271484,83.18733978271484,83.18733978271484,83.18733978271484,87.81935882568359,87.81935882568359,87.81935882568359,89.89450836181641,89.89450836181641,89.89450836181641,89.89450836181641,89.89450836181641,89.89450836181641,93.82749176025391,93.82749176025391,93.82749176025391,93.82749176025391,93.82749176025391,93.82749176025391,99.09468841552734,99.09468841552734,99.09468841552734,99.09468841552734,99.09468841552734,99.09468841552734,100.4399795532227,100.4399795532227,100.4399795532227,100.4399795532227,100.4399795532227,100.4399795532227,104.2535247802734,104.2535247802734,104.2535247802734,104.2535247802734,108.0522994995117,108.0522994995117,108.0522994995117,112.1922378540039,112.1922378540039,112.1922378540039,112.1922378540039,112.1922378540039,77.33255004882812,77.33255004882812,84.55030059814453,84.55030059814453,84.55030059814453,90.15042877197266,90.15042877197266,90.15042877197266,90.15042877197266,90.15042877197266,90.15042877197266,90.15042877197266,96.24662780761719,96.24662780761719,96.24662780761719,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,100.1090621948242,102.3869094848633,102.3869094848633,109.3684997558594,109.3684997558594,109.3684997558594,109.3684997558594,109.3684997558594,109.3684997558594,112.8035354614258,112.8035354614258,112.8035354614258,112.8035354614258,112.8035354614258,112.8035354614258,112.8035354614258,112.8035354614258,81.36692810058594,81.36692810058594,86.51626586914062,86.51626586914062,87.51285552978516,87.51285552978516,87.51285552978516,87.51285552978516,93.41812896728516,93.41812896728516,93.41812896728516,93.41812896728516,93.41812896728516,93.41812896728516,93.41812896728516,93.41812896728516,98.81159210205078,98.81159210205078,98.81159210205078,98.81159210205078,98.81159210205078,98.81159210205078,106.4354705810547,106.4354705810547,106.4354705810547,106.4354705810547,106.4354705810547,106.4354705810547,106.4354705810547,106.4354705810547,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.3016510009766,112.8184204101562,112.8184204101562,112.8184204101562,78.5999755859375,78.5999755859375,85.83119964599609,85.83119964599609,85.83119964599609,85.83119964599609,90.56712341308594,90.56712341308594,98.58564758300781,98.58564758300781,102.7887115478516,102.7887115478516,102.7887115478516,102.7887115478516,102.7887115478516,102.7887115478516,102.7887115478516,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,104.7658996582031,110.9792556762695,110.9792556762695,110.9792556762695,110.9792556762695,110.9792556762695,77.30928802490234,77.30928802490234,77.30928802490234,77.30928802490234,77.30928802490234,77.30928802490234,77.30928802490234,77.30928802490234,82.11418151855469,82.11418151855469,89.09838104248047,89.09838104248047,89.09838104248047,89.09838104248047,95.97550201416016,95.97550201416016,95.97550201416016,96.88668060302734,96.88668060302734,96.88668060302734,96.88668060302734,98.29360961914062,98.29360961914062,98.29360961914062,98.29360961914062,102.4718704223633,102.4718704223633,103.5776748657227,103.5776748657227,103.5776748657227,103.5776748657227,108.1815338134766,108.1815338134766,108.1815338134766,108.1815338134766,108.7400436401367,108.7400436401367,110.0929336547852,110.0929336547852,110.0929336547852,110.0929336547852,77.91120147705078,77.91120147705078,77.91120147705078,77.91120147705078,77.91120147705078,77.91120147705078,77.91120147705078,80.49985504150391,80.49985504150391,81.70565032958984,81.70565032958984,81.70565032958984,81.70565032958984,85.50941467285156,85.50941467285156,85.50941467285156,87.02001953125,87.02001953125,88.09524536132812,88.09524536132812,88.09524536132812,88.09524536132812,94.63242340087891,94.63242340087891,94.63242340087891,94.63242340087891,94.63242340087891,94.63242340087891,94.63242340087891,105.8454360961914,105.8454360961914,112.8106460571289,112.8106460571289,112.8106460571289,112.8106460571289,81.33309936523438,81.33309936523438,81.33309936523438,81.33309936523438,81.33309936523438,81.33309936523438,81.33309936523438,86.63139343261719,86.63139343261719,86.63139343261719,86.63139343261719,86.63139343261719,86.63139343261719,86.63139343261719,92.73050689697266,92.73050689697266,92.73050689697266,92.73050689697266,92.73050689697266,92.73050689697266,99.21194458007812,99.21194458007812,107.0653839111328,107.0653839111328,107.0653839111328,107.0653839111328,107.0653839111328,107.0653839111328,107.0653839111328,112.8152084350586,112.8152084350586,112.8152084350586,112.8152084350586,112.8152084350586,112.8152084350586,112.8152084350586,112.8152084350586,85.50003814697266,85.50003814697266,85.50003814697266,85.50003814697266,85.50003814697266,85.50003814697266,85.50003814697266,85.50003814697266,88.36164855957031,88.36164855957031,88.36164855957031,88.36164855957031,88.36164855957031,88.36164855957031,88.36164855957031,92.50962829589844,92.50962829589844,98.35184478759766,98.35184478759766,98.35184478759766,98.35184478759766,98.35184478759766,98.35184478759766,106.1491088867188,106.1491088867188,106.1491088867188,106.1491088867188,106.1491088867188,106.1491088867188,112.8161087036133,112.8161087036133,112.8161087036133,112.8161087036133,112.8161087036133,112.8161087036133,112.8161087036133,112.8161087036133,82.77880859375,82.77880859375,82.77880859375,82.77880859375,82.77880859375,82.77880859375,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,88.80577087402344,89.94584655761719,89.94584655761719,97.31776428222656,97.31776428222656,97.31776428222656,97.31776428222656,97.31776428222656,97.31776428222656,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,102.7802886962891,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,111.3570785522461,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,83.15093994140625,88.09500122070312,88.09500122070312,88.09500122070312,88.09500122070312,88.09500122070312,88.09500122070312,88.09500122070312,88.09500122070312,92.34520721435547,92.34520721435547,92.34520721435547,92.34520721435547,92.34520721435547,92.34520721435547,92.34520721435547,95.63866424560547,95.63866424560547,102.1891708374023,102.1891708374023,108.5184020996094,108.5184020996094,94.20027923583984,94.20027923583984,94.20027923583984,94.20027923583984,94.20027923583984,94.20027923583984,94.20027923583984,94.20027923583984,89.44412231445312,89.44412231445312,95.35492706298828,95.35492706298828,98.90231323242188,98.90231323242188,98.90231323242188,103.4389190673828,103.4389190673828,103.4389190673828,103.4389190673828,103.4389190673828,103.4389190673828,103.4389190673828,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,109.6031341552734,82.83403015136719,82.83403015136719,87.60075378417969,87.60075378417969,87.60075378417969,87.60075378417969,87.60075378417969,87.60075378417969,87.60075378417969,96.86988830566406,96.86988830566406,96.86988830566406,96.86988830566406,96.86988830566406,96.86988830566406,96.86988830566406,102.9005813598633,102.9005813598633,102.9005813598633,102.9005813598633,102.9005813598633,102.9005813598633,102.9005813598633,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,104.9358444213867,105.2599334716797,105.2599334716797,105.2599334716797,105.2599334716797,105.2599334716797,105.2599334716797,108.9792709350586,108.9792709350586,108.9792709350586,108.9792709350586,112.8183975219727,112.8183975219727,112.8183975219727,84.19667053222656,84.19667053222656,84.19667053222656,84.19667053222656,84.19667053222656,85.03585052490234,85.03585052490234,85.03585052490234,85.03585052490234,85.03585052490234,85.03585052490234,88.43357849121094,88.43357849121094,88.43357849121094,88.43357849121094,92.73553466796875,92.73553466796875,92.73553466796875,92.73553466796875,92.73553466796875,92.73553466796875,92.73553466796875,94.12741851806641,94.12741851806641,94.12741851806641,94.12741851806641,94.12741851806641,94.12741851806641,97.94579315185547,97.94579315185547,97.94579315185547,97.94579315185547,101.5640716552734,101.5640716552734,101.5640716552734,103.4728546142578,103.4728546142578,103.4728546142578,103.4728546142578,103.4728546142578,103.4728546142578,103.4728546142578,103.4728546142578,107.4661407470703,107.4661407470703,107.4661407470703,107.4661407470703,111.0902633666992,111.0902633666992,111.0902633666992,112.8181533813477,112.8181533813477,112.8181533813477,112.8181533813477,70.22664642333984,70.22664642333984,70.22664642333984,70.22664642333984,70.22664642333984,70.22664642333984,73.25310516357422,73.25310516357422,73.25310516357422,73.25310516357422,77.2625732421875,77.2625732421875,77.2625732421875,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,81.15727996826172,88.35025787353516,88.35025787353516,88.35025787353516,88.35025787353516,88.35025787353516,88.35025787353516,88.35025787353516,88.35025787353516,94.07241821289062,94.07241821289062,94.07241821289062,94.07241821289062,94.07241821289062,94.07241821289062,94.07241821289062,100.2650833129883,100.2650833129883,100.2650833129883,100.2650833129883,100.2650833129883,100.2650833129883,100.2650833129883,100.2650833129883,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,104.8836669921875,108.1782073974609,108.1782073974609,108.1782073974609,108.1782073974609,108.1782073974609,108.1782073974609,108.1782073974609,92.82217407226562,92.82217407226562,92.82217407226562,74.43180084228516,74.43180084228516,74.43180084228516,74.43180084228516,74.43180084228516,74.43180084228516,74.43180084228516,81.83270263671875,81.83270263671875,81.83270263671875,81.83270263671875,81.83270263671875,81.83270263671875,81.83270263671875,88.33702850341797,88.33702850341797,88.33702850341797,88.33702850341797,88.33702850341797,88.33702850341797,88.33702850341797,88.33702850341797,97.17028045654297,97.17028045654297,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,103.0280609130859,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,105.5026016235352,111.4512405395508,111.4512405395508,72.17999267578125,72.17999267578125,77.43911743164062,77.43911743164062,77.43911743164062,77.43911743164062,77.43911743164062,77.43911743164062,77.43911743164062,83.34293365478516,83.34293365478516,83.34293365478516,83.34293365478516,83.34293365478516,83.34293365478516,83.34293365478516,83.34293365478516,89.68869781494141,89.68869781494141,94.91149139404297,94.91149139404297,94.91149139404297,94.91149139404297,94.91149139404297,94.91149139404297,94.91149139404297,94.91149139404297,98.05307769775391,98.05307769775391,98.05307769775391,98.05307769775391,98.05307769775391,98.05307769775391,98.05307769775391,106.0918121337891,106.0918121337891,106.0918121337891,106.0918121337891,106.0918121337891,112.18701171875,112.18701171875,112.18701171875,112.18701171875,112.18701171875,112.18701171875,73.02760314941406,73.02760314941406,81.19808197021484,81.19808197021484,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,89.60435485839844,97.96223449707031,97.96223449707031,97.96223449707031,97.96223449707031,97.96223449707031,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,105.9059295654297,112.8079299926758,112.8079299926758,112.8079299926758,112.8079299926758,112.8079299926758,112.8079299926758,112.8079299926758,112.8079299926758,72.69937896728516,72.69937896728516,72.69937896728516,72.69937896728516,72.69937896728516,72.69937896728516,72.69937896728516,74.77680969238281,74.77680969238281,74.77680969238281,74.77680969238281,74.77680969238281,74.77680969238281,74.77680969238281,74.77680969238281,82.69902038574219,82.69902038574219,82.69902038574219,82.69902038574219,82.69902038574219,90.79608154296875,90.79608154296875,97.82044982910156,104.4677200317383,104.4677200317383,104.4677200317383,104.4677200317383,104.4677200317383,104.4677200317383,104.4677200317383,105.3846664428711,105.3846664428711,105.3846664428711,105.3846664428711,106.7699890136719,106.7699890136719,106.7699890136719,106.7699890136719,111.7466430664062,111.7466430664062,111.7466430664062,111.7466430664062,112.0548934936523,112.0548934936523,73.45749664306641,73.45749664306641,73.45749664306641,73.45749664306641,73.45749664306641,73.45749664306641,78.24961853027344,78.24961853027344,78.24961853027344,78.24961853027344,78.24961853027344,79.50495147705078,79.50495147705078,81.24678039550781,81.24678039550781,81.24678039550781,81.24678039550781,81.24678039550781,81.24678039550781,85.20845031738281,85.20845031738281,85.20845031738281,85.20845031738281,85.20845031738281,88.03337097167969,88.03337097167969,88.03337097167969,88.03337097167969,89.78394317626953,89.78394317626953,89.78394317626953,89.78394317626953,94.20602416992188,94.20602416992188,94.20602416992188,94.20602416992188,94.20602416992188,94.20602416992188,94.20602416992188,95.65856170654297,95.65856170654297,97.19998931884766,97.19998931884766,97.19998931884766,97.19998931884766,100.9186172485352,100.9186172485352,100.9186172485352,100.9186172485352,100.9186172485352,106.5158081054688,106.5158081054688,106.5158081054688,106.5158081054688,106.5158081054688,106.5158081054688,106.5158081054688,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,84.11843109130859,83.29559326171875,83.29559326171875,86.58309936523438,86.58309936523438,86.58309936523438,86.58309936523438,86.58309936523438,86.58309936523438,92.34016418457031,92.34016418457031,92.34016418457031,92.34016418457031,92.34016418457031,92.34016418457031,98.88999176025391,98.88999176025391,98.88999176025391,98.88999176025391,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,106.0126266479492,112.4244079589844,112.4244079589844,112.4244079589844,112.4244079589844,112.4244079589844,112.4244079589844,77.87295532226562,77.87295532226562,77.87295532226562,77.87295532226562,78.699951171875,78.699951171875,78.699951171875,78.699951171875,78.699951171875,83.59562683105469,83.59562683105469,83.59562683105469,83.59562683105469,83.59562683105469,83.59562683105469,90.21518707275391,90.21518707275391,90.21518707275391,90.21518707275391,90.21518707275391,90.21518707275391,90.21518707275391,90.21518707275391,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,95.49825286865234,100.9950561523438,100.9950561523438,100.9950561523438,100.9950561523438,100.9950561523438,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,103.8657073974609,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,109.8019409179688,82.82235717773438,82.82235717773438,82.82235717773438,82.82235717773438,82.82235717773438,83.03572845458984,83.03572845458984,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,88.25416564941406,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,91.26839447021484,95.69354248046875,95.69354248046875,95.69354248046875,95.69354248046875,95.69354248046875,95.69354248046875,95.69354248046875,95.69354248046875,101.6630477905273,101.6630477905273,101.6630477905273,101.6630477905273,101.6630477905273,101.6630477905273,101.6630477905273,101.6630477905273,107.7216796875,107.7216796875,107.7216796875,107.7216796875,107.7216796875,107.7216796875,107.7216796875,107.7216796875,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,112.817626953125,79.87379455566406,79.87379455566406,79.87379455566406,79.87379455566406,79.87379455566406,79.87379455566406,80.81813049316406,80.81813049316406,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,86.54112243652344,92.69356536865234,92.69356536865234,92.69356536865234,92.69356536865234,92.69356536865234,92.69356536865234,92.69356536865234,98.84898376464844,98.84898376464844,98.84898376464844,98.84898376464844,98.84898376464844,107.0971832275391,107.0971832275391,107.0971832275391,108.0813827514648,108.0813827514648,108.0813827514648,108.0813827514648,108.0813827514648,108.0813827514648,108.0813827514648,108.0813827514648,111.7805633544922,111.7805633544922,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,112.7984313964844,81.49356079101562,81.49356079101562,82.58441925048828,82.58441925048828,82.58441925048828,82.58441925048828,82.58441925048828,82.58441925048828,86.17354583740234,86.17354583740234,86.17354583740234,86.17354583740234,91.27099609375,91.27099609375,91.27099609375,91.27099609375,91.27099609375,91.27099609375,91.91432952880859,91.91432952880859,91.91432952880859,91.91432952880859,91.91432952880859,94.68997955322266,94.68997955322266,94.68997955322266,94.68997955322266,100.9596328735352,100.9596328735352,100.9596328735352,100.9596328735352,100.9596328735352,100.9596328735352,104.4405899047852,104.4405899047852,104.4405899047852,104.4405899047852,107.1377639770508,107.1377639770508,107.1377639770508,110.6332702636719,110.6332702636719,110.6332702636719,110.6332702636719,110.6332702636719,110.6332702636719,111.5000381469727,111.5000381469727,111.5000381469727,111.5000381469727,111.5000381469727,111.5000381469727,111.5000381469727,111.5000381469727,81.84694671630859,81.84694671630859,81.84694671630859,81.84694671630859,85.77280426025391,85.77280426025391,85.77280426025391,89.54341125488281,89.54341125488281,89.54341125488281,89.54341125488281,89.54341125488281,89.54341125488281,89.54341125488281,95.19788360595703,95.19788360595703,101.4355926513672,101.4355926513672,107.8818283081055,107.8818283081055,107.8818283081055,107.8818283081055,107.8818283081055,107.8818283081055,107.8818283081055,99.43167877197266,99.43167877197266,99.43167877197266,99.43167877197266,99.43167877197266,99.43167877197266,99.43167877197266,99.43167877197266,88.94115447998047,88.94115447998047,88.94115447998047,88.94115447998047,88.94115447998047,88.94115447998047,88.94115447998047,90.18113708496094,90.18113708496094,90.18113708496094,90.18113708496094,90.18113708496094,90.18113708496094,95.90332794189453,95.90332794189453,102.16259765625,102.16259765625,102.16259765625,102.16259765625,102.16259765625,102.16259765625,102.16259765625,108.0147171020508,108.0147171020508,112.8183135986328,112.8183135986328,112.8183135986328,112.8183135986328,112.8183135986328,112.8183135986328,85.97816467285156,85.97816467285156,85.97816467285156,85.97816467285156,85.97816467285156,85.97816467285156,85.97816467285156,88.25366973876953,88.25366973876953,88.25366973876953,88.25366973876953,88.25366973876953,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,92.19153594970703,98.216552734375,98.216552734375,98.216552734375,98.216552734375,98.216552734375,98.216552734375,98.216552734375,98.216552734375,98.216552734375,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,104.2635116577148,110.8602676391602,110.8602676391602,83.30658721923828,83.30658721923828,83.30658721923828,83.30658721923828,83.30658721923828,83.30658721923828,83.30658721923828,84.19631195068359,84.19631195068359,84.19631195068359,84.19631195068359,84.19631195068359,88.58897399902344,88.58897399902344,88.58897399902344,88.58897399902344,88.58897399902344,88.58897399902344,88.58897399902344,94.50413513183594,94.50413513183594,100.6618881225586,100.6618881225586,106.9684295654297,106.9684295654297,112.8184280395508,112.8184280395508,112.8184280395508,83.11920166015625,83.11920166015625,83.11920166015625,83.11920166015625,83.11920166015625,83.11920166015625,83.11920166015625,83.11920166015625,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,86.02956390380859,91.87427520751953,91.87427520751953,97.90476989746094,97.90476989746094,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,104.3716354370117,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,108.4669876098633,109.0052947998047,109.0052947998047,110.3220443725586,110.3220443725586,110.3220443725586,110.3220443725586,110.3220443725586,110.3220443725586,102.6066284179688,102.6066284179688,102.6066284179688,102.6066284179688,102.6066284179688,102.6066284179688,102.6066284179688,102.6066284179688,86.69050598144531,86.69050598144531,86.69050598144531,86.69050598144531,86.69050598144531,87.28630828857422,87.28630828857422,88.73035430908203,88.73035430908203,88.73035430908203,88.73035430908203,88.73035430908203,88.73035430908203,94.76158905029297,94.76158905029297,94.76158905029297,94.76158905029297,94.76158905029297,94.76158905029297,94.76158905029297,94.79486846923828,94.79486846923828,96.12589263916016,96.12589263916016,96.12589263916016,96.12589263916016,96.12589263916016,96.12589263916016,102.4464492797852,102.4464492797852,103.5769195556641,103.5769195556641,103.5769195556641,103.5769195556641,103.5769195556641,103.6214904785156,103.6214904785156,103.6214904785156,103.6214904785156,108.2204513549805,108.2204513549805,108.2204513549805,109.5132141113281,109.5132141113281,110.6440505981445,110.6440505981445,110.6440505981445,110.6440505981445,110.6440505981445,110.6440505981445,85.36579132080078,85.36579132080078,85.36579132080078,85.36579132080078,85.36579132080078,85.36579132080078,85.36579132080078,85.36579132080078,89.84059143066406,89.84059143066406,89.84059143066406,89.84059143066406,99.09729766845703,99.09729766845703,99.09729766845703,99.09729766845703,99.09729766845703,99.09729766845703,99.09729766845703,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,108.1311874389648,112.2548751831055,112.2548751831055,112.2548751831055,112.2548751831055,112.2548751831055,112.2548751831055,112.2548751831055,88.01145935058594,88.01145935058594,88.01145935058594,88.01145935058594,88.01145935058594,88.01145935058594,88.01145935058594,92.76735687255859,92.76735687255859,98.87809753417969,98.87809753417969,98.87809753417969,98.87809753417969,98.87809753417969,98.87809753417969,98.87809753417969,106.5095596313477,106.5095596313477,106.5095596313477,106.5095596313477,106.5095596313477,106.5095596313477,112.7128219604492,112.7128219604492,86.29786682128906,86.29786682128906,86.29786682128906,86.29786682128906,88.99734497070312,88.99734497070312,88.99734497070312,88.99734497070312,88.99734497070312,88.99734497070312,88.99734497070312,88.99734497070312,94.50346374511719,94.50346374511719,94.50346374511719,94.50346374511719,94.50346374511719,94.50346374511719,94.50346374511719,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,100.9103164672852,107.0248031616211,107.0248031616211,109.8396835327148,109.8396835327148,109.8396835327148,112.8178939819336,112.8178939819336,112.8178939819336,112.8178939819336,112.8178939819336,112.8178939819336,112.8178939819336,112.8178939819336,89.8846435546875,89.8846435546875,89.8846435546875,89.8846435546875,89.8846435546875,89.8846435546875,89.8846435546875,95.67179870605469,95.67179870605469,95.67179870605469,102.5411987304688,102.5411987304688,108.8250579833984,108.8250579833984,112.8184280395508,112.8184280395508,112.8184280395508,112.8184280395508,112.8184280395508,112.8184280395508,112.8184280395508,112.8184280395508,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,70.76306915283203,72.00892639160156,72.00892639160156,72.00892639160156,72.00892639160156,72.00892639160156,72.00892639160156,72.00892639160156,72.00892639160156,77.54977416992188,77.54977416992188,77.54977416992188,77.54977416992188,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,83.78355407714844,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,92.35542297363281,99.02996826171875,99.02996826171875,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,105.2730941772461,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,107.2446060180664,112.8122863769531,112.8122863769531,112.8122863769531,73.63709259033203,73.63709259033203,73.63709259033203,73.63709259033203,73.63709259033203,73.63709259033203,73.63709259033203,73.63709259033203,78.73719787597656,78.73719787597656,78.73719787597656,78.73719787597656,78.73719787597656,78.73719787597656,78.73719787597656,78.73719787597656,85.26358032226562,85.26358032226562,85.26358032226562,85.26358032226562,85.26358032226562,85.26358032226562,91.43608856201172,91.43608856201172,91.43608856201172,91.43608856201172,92.38735198974609,92.38735198974609,92.38735198974609,92.38735198974609,92.38735198974609,92.38735198974609,92.38735198974609,92.38735198974609,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,93.54020690917969,96.60729217529297,96.60729217529297,96.60729217529297,96.60729217529297,101.0181198120117,101.0181198120117,102.6519546508789,102.6519546508789,102.6519546508789,102.6519546508789,102.6519546508789,102.6519546508789,102.6519546508789,102.6519546508789,106.7306900024414,106.7306900024414,106.7306900024414,106.7306900024414,106.7306900024414,106.7306900024414,112.4297561645508,112.4297561645508,112.4297561645508,112.4297561645508,112.4297561645508,112.4297561645508,112.4297561645508,112.4297561645508,112.7747116088867,112.7747116088867,112.7747116088867,112.7747116088867,112.7747116088867,75.71253204345703,75.71253204345703,75.71253204345703,75.71253204345703,77.03057861328125,77.03057861328125,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,81.76720428466797,86.25225830078125,86.25225830078125,86.25225830078125,86.25225830078125,88.56061553955078,88.56061553955078,88.56061553955078,88.56061553955078,88.56061553955078,88.56061553955078,88.56061553955078,88.56061553955078,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,92.0906982421875,96.62387084960938,96.62387084960938,96.62387084960938,96.62387084960938,101.2044296264648,101.2044296264648,101.2044296264648,101.2044296264648,101.2044296264648,106.1194839477539,106.1194839477539,106.1194839477539,106.1194839477539,106.1194839477539,106.1194839477539,106.1194839477539,111.8412399291992,111.8412399291992,111.8412399291992,111.8412399291992,111.8412399291992,111.8412399291992,111.8412399291992,75.39870452880859,75.39870452880859,75.39870452880859,75.39870452880859,75.39870452880859,75.39870452880859,75.39870452880859,80.753173828125,80.753173828125,80.753173828125,80.753173828125,80.753173828125,80.753173828125,80.753173828125,80.753173828125,80.753173828125,88.16805267333984,88.16805267333984,88.16805267333984,88.16805267333984,88.16805267333984,88.16805267333984,94.29689025878906,94.29689025878906,94.29689025878906,94.29689025878906,94.29689025878906,95.41623687744141,95.41623687744141,95.41623687744141,95.41623687744141,95.41623687744141,101.4779052734375,107.5065460205078,107.5065460205078,107.5065460205078,107.5065460205078,107.5065460205078,107.5065460205078,112.8175659179688,112.8175659179688,112.8175659179688,112.8175659179688,112.8175659179688,112.8175659179688,112.8175659179688,112.8175659179688,78.17208862304688,78.17208862304688,78.17208862304688,78.17208862304688,78.17208862304688,78.17208862304688,82.93610382080078,82.93610382080078,82.93610382080078,82.93610382080078,82.93610382080078,82.93610382080078,82.93610382080078,91.24457550048828,91.24457550048828,91.24457550048828,91.24457550048828,91.24457550048828,91.24457550048828,91.24457550048828,94.994384765625,94.994384765625,94.994384765625,94.994384765625,94.994384765625,94.994384765625,98.57370758056641,98.57370758056641,104.6194915771484,104.6194915771484,104.6194915771484,104.6194915771484,104.6194915771484,104.6194915771484,104.6194915771484,111.1914825439453,111.1914825439453,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,75.44903564453125,80.25154113769531,80.25154113769531,80.25154113769531,80.25154113769531,80.25154113769531,80.25154113769531,80.25154113769531,83.98307037353516,83.98307037353516,83.98307037353516,83.98307037353516,86.51645660400391,86.51645660400391,86.51645660400391,86.51645660400391,86.51645660400391,86.51645660400391,86.51645660400391,92.19985198974609,92.19985198974609,92.19985198974609,92.19985198974609,92.19985198974609,92.19985198974609,92.19985198974609,92.19985198974609,97.91278076171875,97.91278076171875,104.4687194824219,104.4687194824219,109.1124038696289,109.1124038696289,109.1124038696289,109.1124038696289,109.1124038696289,112.2995147705078,112.2995147705078,112.2995147705078,112.2995147705078,112.2995147705078,112.2995147705078,112.2995147705078,77.12351226806641,77.12351226806641,77.12351226806641,77.12351226806641,77.12351226806641,77.12351226806641,77.12351226806641,81.81660461425781,81.81660461425781,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,86.77631378173828,92.90979766845703,92.90979766845703,97.8670654296875,97.8670654296875,97.8670654296875,97.8670654296875,97.8670654296875,97.8670654296875,98.49078369140625,98.49078369140625,100.1332168579102,100.1332168579102,100.1332168579102,100.1332168579102,102.748649597168,102.748649597168,102.748649597168,102.748649597168,102.748649597168,102.748649597168,102.748649597168,102.748649597168,105.1142349243164,105.1142349243164,106.6451416015625,106.6451416015625,106.6451416015625,106.6451416015625,106.6451416015625,106.6451416015625,112.2949752807617,112.2949752807617,112.2949752807617,112.2949752807617,112.2949752807617,112.2949752807617,112.2949752807617,112.2950057983398,112.2950057983398,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,76.10018920898438,77.24501800537109,77.24501800537109,77.24501800537109,77.24501800537109,82.59227752685547,82.59227752685547,82.59227752685547,82.59227752685547,82.62924194335938,82.62924194335938,84.3184814453125,84.3184814453125,84.3184814453125,84.3184814453125,87.81008148193359,87.81008148193359,87.81008148193359,89.95644378662109,89.95644378662109,89.97281646728516,89.97281646728516,91.69509887695312,91.69509887695312,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,93.17325592041016,98.99788665771484,98.99788665771484,98.99788665771484,112.1051940917969,112.1051940917969,112.1051940917969,112.1051940917969,80.19148254394531,80.19148254394531,83.4207763671875,83.4207763671875,83.4207763671875,88.35502624511719,88.35502624511719,88.35502624511719,88.35502624511719,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,95.50129699707031,101.3600311279297,101.3600311279297,110.6222686767578,110.6222686767578,79.96776580810547,79.96776580810547,84.75897216796875,84.75897216796875,84.75897216796875,84.75897216796875,84.75897216796875,84.75897216796875,91.22783660888672,91.22783660888672,91.22783660888672,91.22783660888672,91.22783660888672,92.18898010253906,92.18898010253906,92.18898010253906,92.18898010253906,98.64667510986328,98.64667510986328,98.64667510986328,98.64667510986328,98.64667510986328,98.64667510986328,98.64667510986328,98.64667510986328,104.8803482055664,104.8803482055664,104.8803482055664,104.8803482055664,104.8803482055664,104.8803482055664,104.8803482055664,111.4061508178711,111.4061508178711,111.4061508178711,111.4061508178711,111.4061508178711,111.4061508178711,111.4061508178711,81.01340484619141,81.01340484619141,85.86018371582031,85.86018371582031,85.86018371582031,85.86018371582031,85.86018371582031,85.86018371582031,85.86018371582031,88.91972351074219,88.91972351074219,88.91972351074219,88.91972351074219,88.91972351074219,88.91972351074219,88.91972351074219,92.30620574951172,92.30620574951172,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,98.28781890869141,105.8975601196289,105.8975601196289,105.8975601196289,105.8975601196289,105.8975601196289,112.8178024291992,112.8178024291992,112.8178024291992,112.8178024291992,112.8178024291992,112.8178024291992,112.8178024291992,112.8178024291992,82.50720977783203,82.50720977783203,87.41419219970703,87.41419219970703,87.41419219970703,87.41419219970703,87.41419219970703,87.41419219970703,87.41419219970703,90.90700531005859,90.90700531005859,90.90700531005859,90.90700531005859,90.90700531005859,90.90700531005859,90.90700531005859,90.90700531005859,94.31304168701172,94.31304168701172,94.31304168701172,94.31304168701172,94.31304168701172,94.31304168701172,94.31304168701172,94.31304168701172,100.2233276367188,100.2233276367188,100.2233276367188,100.2233276367188,100.2233276367188,100.2233276367188,100.2233276367188,100.2233276367188,106.3812942504883,106.3812942504883,112.4350128173828,112.4350128173828,112.4350128173828,112.4350128173828,112.4350128173828,112.4350128173828,112.4350128173828,83.28873443603516,83.28873443603516,85.79639434814453,85.79639434814453,85.79639434814453,85.79639434814453,85.79639434814453,85.79639434814453,88.65487670898438,88.65487670898438,88.65487670898438,88.65487670898438,88.65487670898438,88.65487670898438,88.65487670898438,88.65487670898438,94.46707153320312,94.46707153320312,100.9623260498047,100.9623260498047,100.9623260498047,100.9623260498047,100.9623260498047,100.9623260498047,109.8347015380859,109.8347015380859,109.8347015380859,109.8347015380859,109.8347015380859,109.8347015380859,109.8347015380859,109.8347015380859,81.13920593261719,81.13920593261719,81.13920593261719,81.13920593261719,81.13920593261719,86.43650054931641,86.43650054931641,88.92041015625,88.92041015625,88.92041015625,88.92041015625,89.45523834228516,89.45523834228516,89.45523834228516,89.45523834228516,89.45523834228516,89.45523834228516,93.18838500976562,93.18838500976562,93.18838500976562,93.18838500976562,97.98519134521484,97.98519134521484,97.98519134521484,97.98519134521484,97.98519134521484,97.98519134521484,101.1176605224609,101.1176605224609,101.1176605224609,101.1176605224609,105.6366806030273,105.6366806030273,105.6366806030273,106.2594528198242,106.2594528198242,106.2594528198242,106.2594528198242,109.2190246582031,109.2190246582031,109.2190246582031,109.2190246582031,112.8182144165039,112.8182144165039,112.8182144165039,83.58476257324219,83.58476257324219,83.58476257324219,83.58476257324219,83.58476257324219,83.58476257324219,86.78950500488281,86.78950500488281,86.78950500488281,86.78950500488281,90.53786468505859,90.53786468505859,90.53786468505859,90.53786468505859,90.53786468505859,90.53786468505859,92.78876495361328,92.78876495361328,92.78876495361328,92.78876495361328,92.78876495361328,92.78876495361328,96.04737854003906,96.04737854003906,96.04737854003906,96.04737854003906,100.8854675292969,100.8854675292969,105.4210968017578,105.4210968017578,105.4210968017578,105.4210968017578,105.4210968017578,105.4210968017578,105.4210968017578,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,111.0846176147461,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,85.10167694091797,89.89745330810547,89.89745330810547,89.89745330810547,89.89745330810547,89.89745330810547,89.89745330810547,89.89745330810547,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,95.42134857177734,102.3660659790039,102.3660659790039,102.3660659790039,102.3660659790039,102.3660659790039,102.3660659790039,102.3660659790039,102.3660659790039,103.494499206543,103.494499206543,103.494499206543,103.494499206543,103.494499206543,103.494499206543,110.2644271850586,110.2644271850586,110.2644271850586,110.2644271850586,110.2644271850586,110.2644271850586,95.69182586669922,95.69182586669922,95.69182586669922,95.69182586669922,95.69182586669922,95.69182586669922,95.69182586669922,95.69182586669922,88.20853424072266,88.20853424072266,88.20853424072266,88.20853424072266,88.20853424072266,94.88543701171875,94.88543701171875,94.88543701171875,94.88543701171875,94.88543701171875,94.88543701171875,94.88543701171875,100.4453811645508,100.4453811645508,104.4316940307617,104.4316940307617,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,108.0757904052734,112.8184280395508,112.8184280395508,112.8184280395508,87.67042541503906,87.67042541503906,87.67042541503906,87.67042541503906,87.67042541503906,87.67042541503906,87.67042541503906,93.32602691650391,93.32602691650391,101.0993194580078,101.0993194580078,101.0993194580078,101.0993194580078,101.0993194580078,101.0993194580078,101.0993194580078,107.3288497924805,107.3288497924805,107.3288497924805,107.3288497924805,107.3288497924805,107.3288497924805,107.3288497924805,107.3288497924805,111.7903671264648,111.7903671264648,111.7903671264648,111.7903671264648,111.7903671264648,111.7903671264648,111.7903671264648,111.7903671264648,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,112.818962097168,62.39470672607422,62.39470672607422,62.39470672607422,62.39470672607422,62.39470672607422,62.39470672607422,62.39470672607422,62.39470672607422,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,64.21143341064453,70.26963806152344,70.26963806152344,70.26963806152344,70.26963806152344,70.26963806152344,70.26963806152344,70.26963806152344,70.26963806152344,76.62399291992188,76.62399291992188,76.62399291992188,76.62399291992188,76.62399291992188,76.62399291992188,76.62399291992188,76.62399291992188,84.86608123779297,84.86608123779297,84.86608123779297,84.86608123779297,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,91.77947235107422,92.98699188232422,92.98699188232422,92.98699188232422,92.98699188232422,92.98699188232422,99.50939178466797,99.50939178466797,99.50939178466797,99.50939178466797,99.50939178466797,99.50939178466797,99.50939178466797,105.8819274902344,105.8819274902344,105.8819274902344,105.8819274902344,105.8819274902344,105.8819274902344,112.4922332763672,112.4922332763672,64.61199188232422,64.61199188232422,70.60549163818359,70.60549163818359,70.60549163818359,70.60549163818359,70.60549163818359,70.60549163818359,70.60549163818359,76.46503448486328,76.46503448486328,76.46503448486328,76.46503448486328,76.46503448486328,76.46503448486328,76.46503448486328,77.12468719482422,77.12468719482422,78.54556274414062,78.54556274414062,78.54556274414062,78.54556274414062,78.54556274414062,78.54556274414062,78.54556274414062,78.54556274414062,85.23636627197266,85.23636627197266,85.49190521240234,85.49190521240234,85.49190521240234,85.49190521240234,85.49190521240234,85.49190521240234,85.49190521240234,85.49190521240234,86.38529205322266,86.38529205322266,86.38529205322266,86.38529205322266,86.38529205322266,86.38529205322266,86.38529205322266,86.38529205322266,92.51967620849609,92.51967620849609,92.51967620849609,92.51967620849609,92.51967620849609,92.51967620849609,92.51967620849609,93.36894226074219,93.36894226074219,94.75057983398438,94.75057983398438,94.75057983398438,94.75057983398438,94.75057983398438,94.75057983398438,98.48275756835938,98.48275756835938,98.48275756835938,98.48275756835938,98.48275756835938,98.48275756835938,98.48275756835938,98.48275756835938,100.9736328125,100.9736328125,102.281494140625,102.281494140625,102.281494140625,102.281494140625,102.281494140625,102.281494140625,106.022216796875,106.022216796875,106.022216796875,106.022216796875,106.022216796875,108.6976165771484,108.6976165771484,110.0337448120117,110.0337448120117,110.0337448120117,110.0337448120117,110.0337448120117,110.0337448120117,110.0337448120117,110.0337448120117,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,112.7927932739258,67.45448303222656,67.45448303222656,67.45448303222656,67.45448303222656,67.45448303222656,67.45448303222656],"meminc":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3980636596679688,0,0,0,0,0,0,0,0,0,0,0,1.207260131835938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6712646484375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6239395141601562,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6069183349609375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5535354614257812,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5237045288085938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.506561279296875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5635299682617188,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5448989868164062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-5.722579956054688,0,0,1.002334594726562,0,0,0,0,0,4.735610961914062,0,7.641242980957031,0,0,0,0,0,0,0,0,0,0,0,0,6.532699584960938,0,0,0,7.205284118652344,0,0,0,0,0,0,0,0,0,0,0,0,8.664901733398438,0,5.925827026367188,0,7.900436401367188,0,0,0,0,0,0,0,0,0,0,-49.94694519042969,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5769119262695312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5041961669921875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.07735443115234375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.466339111328125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5002899169921875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.4300460815429688,0,0,0,0,0,4.215431213378906,0,0,0,0,0,0.1475982666015625,0,0,0,0,0,0,0,0,0,0,0,0,0,10.15578460693359,0,0,0,0,0,0,0,0,0,0,0,7.528640747070312,0,1.222686767578125,0,0,0,0,0,0,2.812660217285156,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5157318115234375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.01299285888672,0,7.037979125976562,0,0,-45.62165069580078,1.320457458496094,0,0,0,0,0,0,0,0,0,0,1.735969543457031,0,0,0,0,0,0,0,0,1.602798461914062,0,0,0,0,0,0,0,0,0,0,0.9309234619140625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7630538940429688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.8195648193359375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7513504028320312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6521072387695312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7392654418945312,0,0,0,0,0,0,0,0,0,0,0,0,0,0.8022689819335938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-11.82817077636719,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6339263916015625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.693267822265625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7155303955078125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7098236083984375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7165679931640625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.621734619140625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5679092407226562,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.9457321166992188,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6098403930664062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5695648193359375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.7007598876953125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6664047241210938,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-8.1785888671875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6811447143554688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6008224487304688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.59588623046875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.568115234375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5733184814453125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5570220947265625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5203704833984375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5010833740234375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5648040771484375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5322418212890625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.49517822265625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5070648193359375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.47198486328125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3412933349609375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6805191040039062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.2773513793945312,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.204193115234375,0,0,0,0,0,2.89691162109375,0,4.744026184082031,0,0,-10.83557891845703,0,6.418663024902344,0,0,0,0,0,0,8.138748168945312,0,0,0,0,0,0,6.879798889160156,0,0,0,0,0,1.023040771484375,6.844398498535156,0,0,0,0,0,0,0,0,7.507148742675781,0,0,0,0,0,0,0,0,5.061691284179688,0,0,-45.12520599365234,0,8.813591003417969,0,5.72882080078125,0,3.936553955078125,0,0,0,0,0,3.760643005371094,0,5.855400085449219,0,5.040000915527344,0,5.317047119140625,0,2.491371154785156,0,0,0,0,0,0,0,0,4.189483642578125,0,0,-43.20710754394531,0,0,0,0,0,0,0,0,0,5.992752075195312,0,0,0,0,0,0,0,6.655830383300781,0,0,0,0,0,0,6.10552978515625,0,0,0,0,0,0,5.893341064453125,0,0,0,0,0,0,2.046966552734375,0,0,0,0,0,0,6.512130737304688,0,0,0,0,0,0,6.138862609863281,0,3.717483520507812,0,0,-41.26352691650391,0,6.205184936523438,0,0,0,0,0,0,0.8389739990234375,0,0,0,0,0,0,0,0,0,4.916572570800781,0,0,0,4.439308166503906,0,0,1.794548034667969,0,0,0,0,0,0,0,0,0,5.261390686035156,0,0,0,0,0,6.514755249023438,0,0,0.6603546142578125,0,0,0,0,0,0,0,1.868896484375,0,0,0,0,0,0,3.311424255371094,0,0,0,5.59442138671875,0,0,0,-44.12142181396484,0,0,0,0,0,0,0,4.511924743652344,0,0,0,0,0,0,0,0.5811233520507812,0,0,0,6.24298095703125,0,0,0,0,0,0,0,0,0,5.545745849609375,0,0,0,0,0,7.010635375976562,0,0,5.866645812988281,0,0,0,0,0,0,0,6.314544677734375,0,0,0,0,7.992095947265625,0,0,0,0,0,0,-40.00599670410156,0,0,0,0,0,0,5.802276611328125,0,0,0,0,0,0,1.989418029785156,0,0,0,0,0,0,0,0,0,0,0,6.251914978027344,0,0,0,0,0,0,5.637611389160156,0,7.206794738769531,0,0,0,0,0,0,0,0,0,0,0,0,0,8.304824829101562,0,0,0,0,0,0,0,0,0,-2.187965393066406,0,0,0,0,0,0,0,-30.99520874023438,0,5.991584777832031,0,0,0,0,0,0,0,0,0,1.52752685546875,0,5.378578186035156,0,6.053611755371094,0,0,0,0,0,0,6.441093444824219,0,0,0,0,0,0,0,0,0,0,0,0.943695068359375,0,0,0,0,0,5.044654846191406,0,0,0,0,0,0,0,-39.26016235351562,0,0,0,0,0,0,0,0,0,0,0,0,6.023994445800781,0,0,0,0,0,0,6.153778076171875,0,0,0,0,0,0,0,5.748687744140625,0,0,0,0,2.449172973632812,0,6.160079956054688,0,6.374588012695312,0,5.707160949707031,0,0,0,0,0,0,0,-39.19206237792969,0,0,0,0.8852996826171875,0,0.868743896484375,0,0,0,0.010894775390625,0,0,0,0,0,0,5.810714721679688,0,0.9376220703125,0,0,0,2.970626831054688,0,0,0,0,3.182052612304688,0,0.776763916015625,0,0,0,0,0,6.254104614257812,0,0.9376296997070312,0,0,0,1.13623046875,0,0,0,0,0,0,0,5.809364318847656,0,1.024971008300781,0,0,0,1.33428955078125,0,0,0,0,0,0,0,4.820442199707031,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5586929321289062,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5701370239257812,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5301437377929688,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.414703369140625,0,0,-36.51828002929688,0,0,0,0,10.16738128662109,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.074424743652344,0,0,0,0,0,6.684677124023438,0,10.71884918212891,0,0,0,0,0,-37.42448425292969,0,0,0,0,0,0,0,0,0,7.209175109863281,0,0,0,0,0.2988128662109375,0,0,0,0,0,0,0,4.294967651367188,0,0,0,0,0,0,0,0,0,0,0,0,0,7.738014221191406,0,0,0,0,0,0,0,0,0,4.518280029296875,0,1.823646545410156,0,0,0,0,0,0,0,0,0,0.65679931640625,0,0,0,0,0,0,0,0,0,0,0,0,0.5912246704101562,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.574859619140625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5451202392578125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5520858764648438,0,0,0,0,0,7.583358764648438,0,0,0,0,-33.66534423828125,0,7.639350891113281,0,2.738937377929688,0,8.646240234375,0,0,0,0,0,0,0,5.505096435546875,0,0,0,0,0,0,0,0,0,5.56890869140625,0,0,0,0,0,0,0,6.4796142578125,0,0,0,0,0,0,0,-33.28837585449219,0,0,0,0,6.26605224609375,0,1.436233520507812,0,3.016525268554688,0,0,0,0,0,0,0,0,0,0,6.178497314453125,5.532974243164062,0,6.404159545898438,4.44610595703125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-0.6730117797851562,0,0,-49.585205078125,0,0,0,0,0,2.67364501953125,0,0,0,0,0,0,1.897613525390625,0,0,0,0,0,0,5.326133728027344,0,5.848579406738281,0,0,0,0,0,0,5.553009033203125,0,3.098800659179688,0,0,0,0,0,0,0,0,0,0,0,0,4.445587158203125,0,0,0,0,0,0,0,0,0,0,0,6.251922607421875,0,5.935920715332031,0,5.705276489257812,0,-18.81761932373047,0,0,0,0,0,0,0,-24.59606170654297,0,0,0,0,0,0,3.515007019042969,0,0,0,0,0,0,0,0,5.928672790527344,0,0,6.137359619140625,0,0,0,0,0,0,0,0,4.540855407714844,0,0,0,0,0,0,0,0,0,0,0,0,0.7987213134765625,0,0,0,0,0,0,0,0,0,4.355354309082031,0,0,0,0,0,5.519203186035156,0,0,0,0,0,0,0,2.150283813476562,0,0,0,0,0,0,0,2.277328491210938,0,0,0,0,0,6.007736206054688,0,0,0,0,0,0,0,0,0,4.823616027832031,0,0,0,0,0,0,0,0,0,-44.13709259033203,0,0,0,0,0,2.626411437988281,0,0,0,0,0,0,0,0,0,0,0,5.454620361328125,0,0,0,0,0,2.07293701171875,0,5.634407043457031,0,0,0,0,0,0,0,0,0,4.869338989257812,0,0,0,0,0,2.079200744628906,0,0,0,0,0,6.082962036132812,0,0,0,0,0,6.941047668457031,0,0,0,0,0,0,0,0,7.672958374023438,0,0,0,0,0,-34.73515319824219,0,0,0,0,0,0,0,0,-5.14068603515625,0,0,0,0,7.110366821289062,0,0,0,0,0,0,0,6.655708312988281,0,0.9710006713867188,0,0,0,0,0,0,0,6.970756530761719,0,5.883834838867188,0,0,0,0,0,0,6.373359680175781,0,5.670082092285156,0,0,0,0,0,0,0,0,0,0,0,0,-44.13079833984375,0,0,0,0,0,0,0,0,0,0,0,0,0,3.097320556640625,0,0,0,4.800804138183594,0,6.416854858398438,0,0,0,0,0,7.311599731445312,0,6.446998596191406,0,2.553398132324219,0,0,0,0,0,5.464439392089844,0,0,0,0,0,0,0,6.056976318359375,0,3.802291870117188,0,0,0,0,0,0,0,0,-40.27829742431641,0,6.058441162109375,0,0,0,6.678237915039062,0,1.231689453125,0,0,0,0,0,6.063774108886719,0,0,0,0,0,6.182090759277344,0,0,0,8.094039916992188,0,5.885475158691406,0,-43.60778045654297,0,0,0,0.8766098022460938,0,0.6307220458984375,0,0,0,4.213829040527344,0,0.6008758544921875,0,0,0,4.546653747558594,0,0,0,0,0,0,1.291549682617188,0,0,0,0.022552490234375,0,0,0,5.744102478027344,0,0.69970703125,0,0.8816375732421875,0,0,0,0,0,0,0,4.071624755859375,0,0.5787506103515625,0,0,0,5.355522155761719,0,0,8.737823486328125,0,0,0,0,-25.72047424316406,0,0,-5.854606628417969,0,0,5.080101013183594,0,0,0,0,0,0,0,0,8.185699462890625,0,4.370750427246094,0,0,0,0,0,7.04345703125,0,0,0,0,0,0,0,0,0,0,0,0,9.753700256347656,0,0,0,0,0,0,-1.368408203125,0,0,0,0,0,0,0,-32.61781311035156,0,0,0,0,0,0,1.233978271484375,0,0,0,0,0,0,0,7.709587097167969,0,0,0,0,0,0,7.473861694335938,0,0,0,0,0,7.096244812011719,0,6.30828857421875,0,2.7840576171875,0,0,0,0,0,3.967269897460938,0,0,0,0,0,0,0,-36.396728515625,0,0,0,0,0,0,0,7.30126953125,0,0,0,0,0,6.167396545410156,0,0,0,0,0,0,7.088554382324219,0,6.389442443847656,0,0,0,0,1.223983764648438,0,0,0,0,8.23382568359375,0,0,0,0,0,0,0,-38.65232849121094,0,0,0,0,0,0,0,0,0,0,0,0,5.971992492675781,0,0,0,0,0,6.377342224121094,0,0,0,0,0,0,0,0,6.064483642578125,0,0,0,0,0,0,0,4.57708740234375,0,0,0,0,0,0,0,0,0,0,0,0,3.372955322265625,0,6.582572937011719,0,5.693138122558594,0,0,-38.47336578369141,0,0,0,0,0,0,0,0,0,6.0933837890625,0,0,0,0,0,0,6.838996887207031,0,0.8115310668945312,0,0,0,0,0,0,0,0,0,4.547492980957031,0,0,0,3.655624389648438,0,0,0,0,0,2.045684814453125,0,0,0,0,0,0,0,4.240287780761719,0,0,0,0,0,5.308273315429688,0,0,0,0,0,0,0,0,0,4.488601684570312,0,0,0,0.4181747436523438,0,0,0,0,-34.98509979248047,0,0,0,0,0.802490234375,0,0,0,0,0,0,0,4.363616943359375,0,0,0,0,0,6.010459899902344,0,0,0,0,0,0,0,0,0,0.0057373046875,0,0,0,0,0,0,0,0,0,0.0042266845703125,0,0,0,0,4.693550109863281,0,0,0,0,0,4.79010009765625,0,0,0,0,0,0,3.845893859863281,0,0,0,0,0,0,7.207191467285156,0,0,0,0,0,-3.433723449707031,0,0,-26.91866302490234,0,0,0,0,0,0,0,0,6.074142456054688,0,0,0,0,0,4.839057922363281,0,1.712631225585938,0,0,0,0,0,0,0,0,0,0,0,0,6.001762390136719,0,5.565597534179688,0,0,0,0,0,0,6.469894409179688,0,-34.30207061767578,0,7.048721313476562,0,0,0,0,0,0,2.029754638671875,0,6.861396789550781,0,0,0,0,0,0,8.042198181152344,0,0,0,0,0,0,6.38726806640625,0,0,0,0,0,0,0,6.833396911621094,0,0,0,0,0,0,0,-34.46936798095703,0,0,0,6.123641967773438,0,0,0,0,0,0,0,1.652511596679688,0,0,0,7.192268371582031,0,0,0,0,0,0,6.569534301757812,0,0,0,4.141563415527344,0,0,0,0,0,0,0,0,6.55670166015625,0,0,0,0,0,-33.86722564697266,0,5.797760009765625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.937484741210938,0,5.612686157226562,0,0,0,0,0,0,0,0,0,6.343658447265625,0,0,0,0,0,0,6.350021362304688,0,0,0,0,0,0,0,0,0,0,0,0,6.641258239746094,0,-33.24063110351562,0,3.301780700683594,0,0,0,0,0,0,0,0,0.9334335327148438,0,0,0,0,0,5.397651672363281,0,0.5389022827148438,0,0,0,1.548439025878906,0,0,0,0,0,0,0,4.4072265625,0,0.643798828125,0,0,0,0.0041961669921875,0,0,0,5.683815002441406,0,0.5879058837890625,0,0,0,4.130210876464844,0,0,1.889884948730469,0,0,0,0,0,5.515289306640625,0,-32.66815185546875,0,0,0,0,0,12.82626342773438,0,6.035842895507812,0,0,0,0,0,5.068794250488281,0,0,0,0,0,0,6.36492919921875,0,0,0,0,0,0,0,0,0,0,-17.7501220703125,0,0,0,0,0,0,0,0,-6.566932678222656,0,0,0,0,0,0,0,6.268150329589844,0,0,0,0,0,6.542755126953125,0,0,0,0,1.392555236816406,0,0,0,0,0,0,0,0,6.445587158203125,0,0,0,0,0,0,7.190963745117188,0,0,0,0,0,0,0,-30.75471496582031,0,0,0,0,0,0,0,7.257286071777344,0,0,0,0,0,6.501754760742188,0,0,0,0,0,0,1.235588073730469,0,0,0,0,0,0,0,5.232757568359375,0,0,0,0,0,0,0,0,0,0,0,0,0,7.589866638183594,0,0,0,0,0,0,0,0,0,2.951042175292969,0,0,-48.47493743896484,0,0,3.319984436035156,0,0,0,0,0,8.0291748046875,0,0,0,0,0,0,0,0,1.032379150390625,0,0,0,0,0,0,0,0,0,0,0,0,5.606834411621094,0,6.667503356933594,0,0,0,0,0,0,6.987823486328125,0,0,0,0,0,0,5.281661987304688,0,2.907295227050781,0,0,0,0,0,0,5.822990417480469,0,-29.87649536132812,0,0,0,0,0,-9.843742370605469,0,0,0,0,0,0,0,5.879356384277344,0,0,0,0,0,0,0,0,4.677558898925781,0,0,0,0,0,0.60791015625,0,0,0,0,0,0,0,4.134231567382812,0,0,0,0,0,5.579574584960938,0,0,0,0,0,3.681930541992188,0,0,0,0.5918121337890625,0,0,0,0,0,0,5.355087280273438,0,0,0,0,0,3.554130554199219,0,0,0,2.447975158691406,0,0,3.027633666992188,0,0,0,0,0,0,0,2.958709716796875,0,0,0,0,0,0,0,0,-45.27488708496094,0,0,0,0,0,6.028785705566406,0,0,0,0,0,3.717315673828125,0,0,0,0,0,6.201042175292969,0,0,0,0,0,0,0,0,5.91357421875,0,0,0,0,0,0,5.40234375,0,0,7.952888488769531,0,6.743850708007812,0,0,0,0,0,0,-38.86545562744141,0,0,0,0,0,0,0,1.382766723632812,0,0,0,0,0,0,0,0,3.435409545898438,0,5.8795166015625,0,0,0,0,0,6.585289001464844,0,0,0,0,0,0,0,0,0,0,0,0,6.264801025390625,0,0,0,0,0,0,0,5.164955139160156,0,0,2.849006652832031,0,6.487083435058594,0,0,0,0,0,0,0,4.163467407226562,0,0,-40.15670013427734,0,0,0,0,0,0,5.841392517089844,0,3.913215637207031,0,0,0,0,0,4.158210754394531,0,6.958938598632812,0,0,0,0,0,5.952827453613281,0,7.148521423339844,0,6.19500732421875,0,0,0,0,0,0,0,-41.29881286621094,0,0,0,0,1.62506103515625,0,0,0,0,0,0,5.816810607910156,0,8.0306396484375,0,0,0,0,0,0,0,7.084030151367188,0,0,0,0,0,0,0,6.158157348632812,0,4.077949523925781,0,0.5479583740234375,0,0.8623580932617188,0,0,0,0,0,5.771049499511719,0,1.049034118652344,0,0,0,0,0,-42.2445068359375,0,4.387031555175781,0,0.8934783935546875,0,0,0,0,0,5.890403747558594,0,0.7575302124023438,0,0,0,3.50146484375,0,0,2.01837158203125,0,0.7797698974609375,0,0,0,4.650337219238281,0,0,7.3470458984375,0,0,0,0,0,0,11.87892150878906,0,0,-39.23566436767578,0,4.010971069335938,0,0,0,0,0,0,5.730255126953125,0,0,0,0,0,0,0,0,0,8.901168823242188,0,6.268936157226562,0,6.133430480957031,0,0,0,0,0,0,8.589515686035156,0,0,-35.7777099609375,0,5.221794128417969,0,0,0,0,0,3.26519775390625,0,0,0,0,0,0,5.991294860839844,0,5.996047973632812,0,0,0,0,0,0,6.662689208984375,0,0,0,0,0,7.781753540039062,0,0,0,0,0,0.8767318725585938,0,0,0,0,0,0,0,0,0,-38.08433532714844,0,8.366691589355469,0,0,0,6.812049865722656,0,0,0,0,0,0,5.861526489257812,0,0,0,0,0,0,0,6.566413879394531,0,0,0,0,0,0,9.869216918945312,0,0,0,0,0,0,0,-37.83133697509766,0,0,0,0,0,1.105751037597656,0,0,0,0,0,0,0,0,0,6.290351867675781,0,0,0,0,0,0,0,0,0,0,0,0,0,6.010055541992188,0,0,0,0,0,0,6.776679992675781,0,0,0,0,0,0,10.28309631347656,0,4.865379333496094,3.102516174316406,0,0,-36.30519104003906,0,0,0,0,0,0,0,7.216926574707031,0,0,0,0,0,6.773765563964844,0,6.442192077636719,0,0,0,0,0,0,0,1.7431640625,0,0,0,0,0,0,0,0,0,4.710983276367188,0,0,0,0,0,5.477508544921875,0,0,0,0,0.7597274780273438,0,0,0,0,0,0,0,0,0,-16.8385009765625,0,0,0,0,0,0,0,-15.97005462646484,0,0,0,4.387931823730469,0,0,1.27996826171875,0,0,0,0,0,0,0,0,0,4.7110595703125,0,0,0,3.950393676757812,0,0,1.810684204101562,0,0,0,0,0,0,0,0,0,4.669486999511719,0,0,0,5.217018127441406,0,0,0,0,0,0,0,0,0,4.671234130859375,0,0,0,0,0,5.295166015625,0,0,-34.43736267089844,0,8.472305297851562,0,0,0,0,0,0,8.46124267578125,0,0,0,0,0,0,0,6.462654113769531,0,6.002418518066406,0,0,0,0,0,0,0,5.040908813476562,0,0,0,0,0,0,0,0,-32.05537414550781,0,0,0,0,0,0,3.525093078613281,0,0,0,0,0,4.149574279785156,0,5.790367126464844,0,6.051506042480469,0,5.724761962890625,0,0,0,0,0,0,6.797027587890625,0,0,0,0,0,0,0,0,-32.70093536376953,0,0,0,0,0,2.569862365722656,0,0,0,0,0,0,5.737937927246094,0,0,0,0,0,0,6.471588134765625,0,0,0,0,9.169960021972656,0,6.300971984863281,0,0,0,0,0,0,0,-31.61589813232422,0,4.075889587402344,0,0,0,0,3.823829650878906,0,5.990455627441406,0,7.379264831542969,0,0,0,0,0,6.423980712890625,6.373809814453125,0,-34.24923706054688,0,0,0,4.003608703613281,0,6.017532348632812,0,6.127548217773438,0,6.429359436035156,0,0,0,0,0,0,0,0,9.39471435546875,0,0,0,0,0,0,0,0,-30.46852111816406,0,0,0,0,0,0,0,9.238235473632812,0,0,0,0,0,0,0,5.663749694824219,0,0,0,0,0,1.105674743652344,0,0,0,0,0,0,0.05164337158203125,0,0,0,4.370307922363281,0,0,2.020835876464844,0,0,0,0,0,4.616554260253906,0,1.20953369140625,0,0,0,0,0,4.450706481933594,0,0,-31.68911743164062,0,0,0,0.6787872314453125,0,0,0,0,0,5.741264343261719,0,1.1749267578125,0,0,0,3.546958923339844,0,0,0,0,0,0,5.464065551757812,0,0,0,0,0,0,13.38844299316406,0,0,0,-28.74837493896484,0,0,3.467880249023438,0,0,0,0,0,8.461555480957031,0,0,0,0,0,5.515144348144531,0,0,0,0,0,7.148536682128906,0,0,0,0,0,0,5.884178161621094,0,0,-43.18994140625,0,0,-0.8744735717773438,0,4.238754272460938,0,9.120712280273438,0,0,0,0,0,0,8.719619750976562,0,6.916603088378906,0,0,7.186813354492188,0,0,0,0,0,0,6.951347351074219,0,0,0,0,0,0,0,-38.42026519775391,0,0,0.4385910034179688,0,0,0,0,1.019309997558594,0,0,0,0,0,0,0,8.314155578613281,0,6.450271606445312,0,6.090980529785156,0,0,0,0,0,0,0,0,0,0,0,6.610641479492188,0,0,0,0,0,5.821266174316406,0,0,0,0,0,0,2.14117431640625,0,0,0,0,0,0,-43.1947021484375,0,0,0,0,0,0,0,8.359138488769531,0,0,0,0,0,0,6.321601867675781,0,0,0,0,0,0,0,0,0,7.294387817382812,0,0,0,0,7.51190185546875,0,0,0,0,0,0,5.971588134765625,0,3.007972717285156,0,0,0,0,5.451644897460938,0,-42.70149230957031,0,0,0,0,0,0,4.998558044433594,0,0,0,0,0,0,0,0,0,0,6.143646240234375,0,0,7.920112609863281,0,6.135795593261719,0,0,0,0,0,0,1.841468811035156,0,0,0,0.0701446533203125,0,0,0,0,0,0,0,0,0,5.061691284179688,0,0,0,3.930931091308594,0,0,1.12713623046875,0,0,0,0,0,0,0,0,0,4.663673400878906,0,0,0,-2.193672180175781,0,0,0,0,0,0,0,-37.24935150146484,0,0,0,0,0,0,0,0,0,0,0,5.27081298828125,0,0,0,4.625434875488281,0,0,0,0,0,0,0,0,0,0,0,4.88739013671875,0,1.809661865234375,0,0,0,0,0,0,0,3.736312866210938,0,0,0,0,0,0,0,0,0,4.538749694824219,0,0,0,4.274017333984375,0,4.837959289550781,0,0,0,0,0,0,0,6.018241882324219,0,-39.83979034423828,0,0,0,0,0,0,6.232040405273438,0,7.083854675292969,0,0,0,0,5.94921875,0,0,0,0,1.20550537109375,0,0,0,0,0,0,0,0,0,9.331260681152344,0,0,0,0,0,0,0,0,0,6.340553283691406,0,0,0,0,0,0,0,0,0,5.690513610839844,0,0,0,0,0,0,0,-38.89582824707031,0,0,0,0,0,0,0,5.41717529296875,0,0,0,0,0,0,0,4.187416076660156,0,3.878890991210938,0,0,0,0,0,9.4349365234375,0,0,0,0,0,0,0,6.319549560546875,0,6.080818176269531,0,-23.96305847167969,0,0,-10.03745269775391,0,5.854972839355469,0,0,0,1.222434997558594,0,0,0,8.708282470703125,0,0,0,0,0,0,7.128623962402344,0,0,0,0,0,0,0,7.142807006835938,0,0,0,0,0,0,6.238731384277344,0,-39.21463775634766,0,0,0,0,0,0,4.482200622558594,0,0,0,0,0,0,0,1.042671203613281,0,0,0,0,0,8.434249877929688,0,0,0,0,0,0,0,0,0,0,0,0,6.237236022949219,0,0,0,0,0,0,7.18731689453125,0,0,0,0,8.23382568359375,0,0,0,0,0,4.879486083984375,0,0,0,0,0,0,0,-38.17855072021484,0,0,0,0.8596343994140625,0,0.4977645874023438,0,0,0,3.53729248046875,0,0,2.035530090332031,0,0.6508712768554688,0,0,0,4.208648681640625,0,0,2.120651245117188,0,0.6493606567382812,0,0,0,5.111007690429688,0,0,1.049980163574219,0,0,0,0,0,5.105476379394531,0,0.5503768920898438,0,0,0,3.548248291015625,0,0,0,0,0,4.18585205078125,0,4.06695556640625,0,0,-31.24302673339844,0,0,6.532028198242188,0,0,0,0,6.794181823730469,0,7.280570983886719,0,7.916519165039062,0,-35.56395721435547,0,5.368095397949219,0,0,0,0,0,4.360565185546875,0,0,0,0,0,0,0,0,0,0,0,0,0,3.1968994140625,0,0,0,0,0,0,6.958885192871094,0,0,0,0,0,0,0,0,0,7.528640747070312,0,0,0,6.785346984863281,0,0,0,0,-31.05998229980469,0,0,0,12.59697723388672,0,0,0,0,3.337265014648438,0,0,0,0,0,0,0,0,5.349075317382812,0,0,0,0,0,0,0,0,0,0,6.361839294433594,0,0,0,0,7.50042724609375,0,0,0,0,0,0,0,0,-33.42574310302734,0,0,0,0,0,0,0,6.522529602050781,0,0,0,0,0,0,0,0,0,0.9764556884765625,0,5.645309448242188,0,0,0,0,0,6.22137451171875,0,0,0,0,7.888755798339844,0,0,0,0,0,0,5.923240661621094,0,0,0,0,0,0,0,-31.52370452880859,0,0,0,0,0,0,0.8753128051757812,0,0,0,0,0,6.911880493164062,0,0,0,0,0,0,8.113456726074219,0,6.205696105957031,0,0,0,6.709556579589844,0,0,0,0,0,0,0,2.950180053710938,0,0,0,0,0,-28.73731231689453,0,1.884292602539062,0,0,0,5.492088317871094,0,0,0,0,0,0,0,5.032508850097656,0,0,0,0,0,0,0,5.939109802246094,0,0,0,0,0,0,7.58148193359375,0,1.392227172851562,0,-22.76270294189453,0,0,0,0,0,0,0,0,-4.771675109863281,0,0,0,0,0,0,5.499252319335938,0,0,0,0,0,0,0,0,0,8.176918029785156,0,5.718368530273438,0,0,0,0,0,0,0,2.495025634765625,0,0,0,0,0,0,0,0,0,0.4550933837890625,0,0,0,0,0,4.050788879394531,0,0,0,2.5118408203125,0,0,0,0,0,0,0,0,-29.64757537841797,0,0.2595977783203125,0,0,0,0,0,0,0,4.6776123046875,0,0,0,1.450790405273438,0,0,0,0,0,0,0,4.6444091796875,0,0,0,0,0,4.018836975097656,0,0,0,0.6819915771484375,0,6.208023071289062,0,0,0,0,0,0,0,0.6813888549804688,0,0,0,3.8311767578125,0,0,0,-18.61878204345703,0,0,0,0,0,0,0,-6.795181274414062,0,0,0,0,0,1.463905334472656,0,0,0,0,0,0,0,2.897880554199219,0,0,0,6.222114562988281,0,0,0,0,6.168663024902344,0,7.5865478515625,0,0,0,0,0,0,4.316314697265625,0,0,-28.37181091308594,0,0,0,0,0,0,0,8.584770202636719,0,0,0,0,0,0,0,5.667228698730469,0,3.181800842285156,0,0,0,0,0,4.260787963867188,0,0,0,0,0,0,6.222496032714844,0,-27.00373077392578,0,0,0,0,6.230690002441406,0,0,0,0,0,0,5.883338928222656,0,0,0,0,0,0,0,0,0,0,0,0,5.929084777832031,0,0,0,0,0,0,0,0,0,1.816909790039062,0,0,0,0,0,0,0,5.668922424316406,0,1.930755615234375,0,0,0,0,0,0,0,-42.90486907958984,0,0,0,0,0,0,4.643646240234375,0,0,5.963600158691406,0,1.3814697265625,0,6.385856628417969,0,7.599685668945312,0,0,0,0,0,7.492813110351562,0,6.169158935546875,0,0,0,0,0,0,0,0,2.561737060546875,0,0,0,0,0,0,-38.65439605712891,0,0,0,0,-2.309425354003906,0,6.317840576171875,0,0,0,0,0,0,7.638481140136719,0,0,0,0,0,0,6.485649108886719,0,0,0,0,0,0,0,0,2.611976623535156,0,0,0,0,0,0,0.3391876220703125,0,1.548416137695312,0,0,0,4.629440307617188,0,0,1.137489318847656,0,1.473335266113281,0,0,0,5.003730773925781,0,0.3456954956054688,0,1.560447692871094,0,2.301948547363281,0,0,0,0,-44.05891418457031,0,0,0,0,0,1.30181884765625,0,1.245697021484375,0,0,0,4.183334350585938,0,0,0,2.374923706054688,0,1.369972229003906,0,0,0,2.936004638671875,0,0,0,0,0,0,4.984397888183594,0,0,0,0,0,11.24970245361328,0,6.798225402832031,0,0,0,6.370704650878906,0,-41.85246276855469,0,8.703254699707031,0,6.733428955078125,0,2.038665771484375,0,0,0,0,0,0,0,4.260520935058594,0,0,0,0,0,0,0,0,0,0,0,6.3984375,0,0,0,0,0,3.93695068359375,0,0,0,4.254127502441406,0,-1.668533325195312,0,0,0,0,0,-25.39780426025391,0,0,0,0,4.1859130859375,6.380325317382812,0,4.939193725585938,0,6.348457336425781,0,3.602409362792969,0,0,0,4.660560607910156,0,0,0,0,0,0,-12.18306732177734,0,0,0,0,0,0,0,-20.71002197265625,0,0,0,5.511146545410156,0,0,0,0,0,0,6.09576416015625,0,0,0,0,0,0,2.007156372070312,0,0,5.751640319824219,0,0,0,0,0,0,0,6.225349426269531,0,0,0,0,0,0,0,6.421318054199219,0,0,0,0,0,0,4.8701171875,0,0,0,0,0,0,0,-38.97035217285156,0,0,0,0,0,1.277656555175781,0,0,0,0,0,0,0,0,0,0,0,0,0,6.79498291015625,0,0,0,0,0,7.51544189453125,0,6.568931579589844,0,5.9832763671875,0,0,0,0,0,0,0,0,0,0,0,3.229591369628906,0,0,0,0,0,0,0,0,5.466888427734375,0,-36.37563323974609,0,0,0,0,0,0,0,0,0,4.512809753417969,0,0,0,0,5.857444763183594,0,7.624069213867188,0,0,0,0,0,0,0,4.995979309082031,0.9227142333984375,0,0,0,0,0,0,0,0,0,4.263900756835938,0,0,0,4.123023986816406,0,0,1.677352905273438,0,0,0,0,0,3.573478698730469,0,0,0,0,0,-34.54472351074219,0,0,0,0,2.359458923339844,0,0,0,0,0,3.521011352539062,0,0,0,0,0,4.63201904296875,0,0,2.075149536132812,0,0,0,0,0,3.9329833984375,0,0,0,0,0,5.267196655273438,0,0,0,0,0,1.345291137695312,0,0,0,0,0,3.813545227050781,0,0,0,3.798774719238281,0,0,4.139938354492188,0,0,0,0,-34.85968780517578,0,7.217750549316406,0,0,5.600128173828125,0,0,0,0,0,0,6.096199035644531,0,0,3.862434387207031,0,0,0,0,0,0,0,0,2.277847290039062,0,6.981590270996094,0,0,0,0,0,3.435035705566406,0,0,0,0,0,0,0,-31.43660736083984,0,5.149337768554688,0,0.9965896606445312,0,0,0,5.9052734375,0,0,0,0,0,0,0,5.393463134765625,0,0,0,0,0,7.623878479003906,0,0,0,0,0,0,0,5.866180419921875,0,0,0,0,0,0,0,0,0.5167694091796875,0,0,-34.21844482421875,0,7.231224060058594,0,0,0,4.735923767089844,0,8.018524169921875,0,4.20306396484375,0,0,0,0,0,0,1.977188110351562,0,0,0,0,0,0,0,0,6.213356018066406,0,0,0,0,-33.66996765136719,0,0,0,0,0,0,0,4.804893493652344,0,6.984199523925781,0,0,0,6.877120971679688,0,0,0.9111785888671875,0,0,0,1.406929016113281,0,0,0,4.178260803222656,0,1.105804443359375,0,0,0,4.603858947753906,0,0,0,0.5585098266601562,0,1.352890014648438,0,0,0,-32.18173217773438,0,0,0,0,0,0,2.588653564453125,0,1.205795288085938,0,0,0,3.803764343261719,0,0,1.510604858398438,0,1.075225830078125,0,0,0,6.537178039550781,0,0,0,0,0,0,11.2130126953125,0,6.9652099609375,0,0,0,-31.47754669189453,0,0,0,0,0,0,5.298294067382812,0,0,0,0,0,0,6.099113464355469,0,0,0,0,0,6.481437683105469,0,7.853439331054688,0,0,0,0,0,0,5.749824523925781,0,0,0,0,0,0,0,-27.31517028808594,0,0,0,0,0,0,0,2.861610412597656,0,0,0,0,0,0,4.147979736328125,0,5.842216491699219,0,0,0,0,0,7.797264099121094,0,0,0,0,0,6.666999816894531,0,0,0,0,0,0,0,-30.03730010986328,0,0,0,0,0,6.026962280273438,0,0,0,0,0,0,0,0,0,1.14007568359375,0,7.371917724609375,0,0,0,0,0,5.4625244140625,0,0,0,0,0,0,0,0,0,0,8.576789855957031,0,0,0,0,0,0,0,0,-28.20613861083984,0,0,0,0,0,0,0,0,0,0,0,0,4.944061279296875,0,0,0,0,0,0,0,4.250205993652344,0,0,0,0,0,0,3.29345703125,0,6.550506591796875,0,6.329231262207031,0,-14.31812286376953,0,0,0,0,0,0,0,-4.756156921386719,0,5.910804748535156,0,3.547386169433594,0,0,4.536605834960938,0,0,0,0,0,0,6.164215087890625,0,0,0,0,0,0,0,0,0,-26.76910400390625,0,4.7667236328125,0,0,0,0,0,0,9.269134521484375,0,0,0,0,0,0,6.030693054199219,0,0,0,0,0,0,2.035263061523438,0,0,0,0,0,0,0,0,0,0,0,0.3240890502929688,0,0,0,0,0,3.719337463378906,0,0,0,3.839126586914062,0,0,-28.62172698974609,0,0,0,0,0.8391799926757812,0,0,0,0,0,3.397727966308594,0,0,0,4.301956176757812,0,0,0,0,0,0,1.391883850097656,0,0,0,0,0,3.818374633789062,0,0,0,3.618278503417969,0,0,1.908782958984375,0,0,0,0,0,0,0,3.9932861328125,0,0,0,3.624122619628906,0,0,1.727890014648438,0,0,0,-42.59150695800781,0,0,0,0,0,3.026458740234375,0,0,0,4.009468078613281,0,0,3.894706726074219,0,0,0,0,0,0,0,0,0,0,0,0,0,7.192977905273438,0,0,0,0,0,0,0,5.722160339355469,0,0,0,0,0,0,6.192665100097656,0,0,0,0,0,0,0,4.618583679199219,0,0,0,0,0,0,0,0,0,0,0,0,3.294540405273438,0,0,0,0,0,0,-15.35603332519531,0,0,-18.39037322998047,0,0,0,0,0,0,7.400901794433594,0,0,0,0,0,0,6.504325866699219,0,0,0,0,0,0,0,8.833251953125,0,5.857780456542969,0,0,0,0,0,0,0,0,0,2.474540710449219,0,0,0,0,0,0,0,0,0,5.948638916015625,0,-39.27124786376953,0,5.259124755859375,0,0,0,0,0,0,5.903816223144531,0,0,0,0,0,0,0,6.34576416015625,0,5.222793579101562,0,0,0,0,0,0,0,3.141586303710938,0,0,0,0,0,0,8.038734436035156,0,0,0,0,6.095199584960938,0,0,0,0,0,-39.15940856933594,0,8.170478820800781,0,8.406272888183594,0,0,0,0,0,0,0,0,8.357879638671875,0,0,0,0,7.943695068359375,0,0,0,0,0,0,0,0,0,0,0,0,6.902000427246094,0,0,0,0,0,0,0,-40.10855102539062,0,0,0,0,0,0,2.077430725097656,0,0,0,0,0,0,0,7.922210693359375,0,0,0,0,8.097061157226562,0,7.024368286132812,6.647270202636719,0,0,0,0,0,0,0.9169464111328125,0,0,0,1.385322570800781,0,0,0,4.976654052734375,0,0,0,0.3082504272460938,0,-38.59739685058594,0,0,0,0,0,4.792121887207031,0,0,0,0,1.255332946777344,0,1.741828918457031,0,0,0,0,0,3.961669921875,0,0,0,0,2.824920654296875,0,0,0,1.750572204589844,0,0,0,4.422080993652344,0,0,0,0,0,0,1.452537536621094,0,1.541427612304688,0,0,0,3.7186279296875,0,0,0,0,5.597190856933594,0,0,0,0,0,0,-22.39737701416016,0,0,0,0,0,0,0,0,-0.8228378295898438,0,3.287506103515625,0,0,0,0,0,5.757064819335938,0,0,0,0,0,6.549827575683594,0,0,0,7.122634887695312,0,0,0,0,0,0,0,0,0,6.411781311035156,0,0,0,0,0,-34.55145263671875,0,0,0,0.826995849609375,0,0,0,0,4.895675659179688,0,0,0,0,0,6.619560241699219,0,0,0,0,0,0,0,5.283065795898438,0,0,0,0,0,0,0,0,5.496803283691406,0,0,0,0,2.870651245117188,0,0,0,0,0,0,0,0,5.936233520507812,0,0,0,0,0,0,0,0,0,0,0,-26.97958374023438,0,0,0,0,0.2133712768554688,0,5.218437194824219,0,0,0,0,0,0,0,0,0,0,0,3.014228820800781,0,0,0,0,0,0,0,0,0,0,0,4.425148010253906,0,0,0,0,0,0,0,5.969505310058594,0,0,0,0,0,0,0,6.058631896972656,0,0,0,0,0,0,0,5.095947265625,0,0,0,0,0,0,0,0,0,-32.94383239746094,0,0,0,0,0,0.9443359375,0,5.722991943359375,0,0,0,0,0,0,0,0,0,6.152442932128906,0,0,0,0,0,0,6.155418395996094,0,0,0,0,8.248199462890625,0,0,0.9841995239257812,0,0,0,0,0,0,0,3.699180603027344,0,1.017868041992188,0,0,0,0,0,0,0,0,0,-31.30487060546875,0,1.090858459472656,0,0,0,0,0,3.589126586914062,0,0,0,5.097450256347656,0,0,0,0,0,0.6433334350585938,0,0,0,0,2.775650024414062,0,0,0,6.2696533203125,0,0,0,0,0,3.48095703125,0,0,0,2.697174072265625,0,0,3.495506286621094,0,0,0,0,0,0.8667678833007812,0,0,0,0,0,0,0,-29.65309143066406,0,0,0,3.925857543945312,0,0,3.770606994628906,0,0,0,0,0,0,5.654472351074219,0,6.237709045410156,0,6.446235656738281,0,0,0,0,0,0,-8.450149536132812,0,0,0,0,0,0,0,-10.49052429199219,0,0,0,0,0,0,1.239982604980469,0,0,0,0,0,5.722190856933594,0,6.259269714355469,0,0,0,0,0,0,5.852119445800781,0,4.803596496582031,0,0,0,0,0,-26.84014892578125,0,0,0,0,0,0,2.275505065917969,0,0,0,0,3.9378662109375,0,0,0,0,0,0,0,0,0,0,0,0,0,6.025016784667969,0,0,0,0,0,0,0,0,6.046958923339844,0,0,0,0,0,0,0,0,0,6.596755981445312,0,-27.55368041992188,0,0,0,0,0,0,0.8897247314453125,0,0,0,0,4.392662048339844,0,0,0,0,0,0,5.9151611328125,0,6.157752990722656,0,6.306541442871094,0,5.849998474121094,0,0,-29.69922637939453,0,0,0,0,0,0,0,2.910362243652344,0,0,0,0,0,0,0,0,0,5.844711303710938,0,6.030494689941406,0,6.466865539550781,0,0,0,0,0,0,0,0,4.095352172851562,0,0,0,0,0,0,0,0,0,0.5383071899414062,0,1.316749572753906,0,0,0,0,0,-7.715415954589844,0,0,0,0,0,0,0,-15.91612243652344,0,0,0,0,0.5958023071289062,0,1.444046020507812,0,0,0,0,0,6.031234741210938,0,0,0,0,0,0,0.0332794189453125,0,1.331024169921875,0,0,0,0,0,6.320556640625,0,1.130470275878906,0,0,0,0,0.0445709228515625,0,0,0,4.598960876464844,0,0,1.292762756347656,0,1.130836486816406,0,0,0,0,0,-25.27825927734375,0,0,0,0,0,0,0,4.474800109863281,0,0,0,9.256706237792969,0,0,0,0,0,0,9.033889770507812,0,0,0,0,0,0,0,0,4.123687744140625,0,0,0,0,0,0,-24.24341583251953,0,0,0,0,0,0,4.755897521972656,0,6.110740661621094,0,0,0,0,0,0,7.631462097167969,0,0,0,0,0,6.203262329101562,0,-26.41495513916016,0,0,0,2.699478149414062,0,0,0,0,0,0,0,5.506118774414062,0,0,0,0,0,0,6.406852722167969,0,0,0,0,0,0,0,0,0,0,0,0,6.114486694335938,0,2.81488037109375,0,0,2.97821044921875,0,0,0,0,0,0,0,-22.93325042724609,0,0,0,0,0,0,5.787155151367188,0,0,6.869400024414062,0,6.283859252929688,0,3.993370056152344,0,0,0,0,0,0,0,-42.05535888671875,0,0,0,0,0,0,0,0,0,1.245857238769531,0,0,0,0,0,0,0,5.540847778320312,0,0,0,6.233779907226562,0,0,0,0,0,0,0,0,0,0,0,0,0,8.571868896484375,0,0,0,0,0,0,0,0,0,6.674545288085938,0,6.243125915527344,0,0,0,0,0,0,0,0,0,0,0,0,1.971511840820312,0,0,0,0,0,0,0,0,0,0,5.567680358886719,0,0,-39.17519378662109,0,0,0,0,0,0,0,5.100105285644531,0,0,0,0,0,0,0,6.526382446289062,0,0,0,0,0,6.172508239746094,0,0,0,0.951263427734375,0,0,0,0,0,0,0,1.152854919433594,0,0,0,0,0,0,0,0,0,3.067085266113281,0,0,0,4.41082763671875,0,1.633834838867188,0,0,0,0,0,0,0,4.0787353515625,0,0,0,0,0,5.699066162109375,0,0,0,0,0,0,0,0.3449554443359375,0,0,0,0,-37.06217956542969,0,0,0,1.318046569824219,0,4.736625671386719,0,0,0,0,0,0,0,0,0,4.485054016113281,0,0,0,2.308357238769531,0,0,0,0,0,0,0,3.530082702636719,0,0,0,0,0,0,0,0,0,4.533172607421875,0,0,0,4.580558776855469,0,0,0,0,4.915054321289062,0,0,0,0,0,0,5.721755981445312,0,0,0,0,0,0,-36.44253540039062,0,0,0,0,0,0,5.354469299316406,0,0,0,0,0,0,0,0,7.414878845214844,0,0,0,0,0,6.128837585449219,0,0,0,0,1.119346618652344,0,0,0,0,6.061668395996094,6.028640747070312,0,0,0,0,0,5.311019897460938,0,0,0,0,0,0,0,-34.64547729492188,0,0,0,0,0,4.764015197753906,0,0,0,0,0,0,8.3084716796875,0,0,0,0,0,0,3.749809265136719,0,0,0,0,0,3.579322814941406,0,6.045783996582031,0,0,0,0,0,0,6.571990966796875,0,-35.74244689941406,0,0,0,0,0,0,0,0,0,0,0,0,4.802505493164062,0,0,0,0,0,0,3.731529235839844,0,0,0,2.53338623046875,0,0,0,0,0,0,5.683395385742188,0,0,0,0,0,0,0,5.712928771972656,0,6.555938720703125,0,4.643684387207031,0,0,0,0,3.187110900878906,0,0,0,0,0,0,-35.17600250244141,0,0,0,0,0,0,4.693092346191406,0,4.959709167480469,0,0,0,0,0,0,0,0,0,0,6.13348388671875,0,4.957267761230469,0,0,0,0,0,0.62371826171875,0,1.642433166503906,0,0,0,2.615432739257812,0,0,0,0,0,0,0,2.365585327148438,0,1.530906677246094,0,0,0,0,0,5.649833679199219,0,0,0,0,0,0,3.0517578125e-05,0,-36.19481658935547,0,0,0,0,0,0,0,0,1.144828796386719,0,0,0,5.347259521484375,0,0,0,0.03696441650390625,0,1.689239501953125,0,0,0,3.491600036621094,0,0,2.1463623046875,0,0.0163726806640625,0,1.722282409667969,0,1.478157043457031,0,0,0,0,0,0,0,0,5.824630737304688,0,0,13.10730743408203,0,0,0,-31.91371154785156,0,3.229293823242188,0,0,4.934249877929688,0,0,0,7.146270751953125,0,0,0,0,0,0,0,0,5.858734130859375,0,9.262237548828125,0,-30.65450286865234,0,4.791206359863281,0,0,0,0,0,6.468864440917969,0,0,0,0,0.9611434936523438,0,0,0,6.457695007324219,0,0,0,0,0,0,0,6.233673095703125,0,0,0,0,0,0,6.525802612304688,0,0,0,0,0,0,-30.39274597167969,0,4.846778869628906,0,0,0,0,0,0,3.059539794921875,0,0,0,0,0,0,3.386482238769531,0,5.981613159179688,0,0,0,0,0,0,0,0,0,0,0,0,0,7.6097412109375,0,0,0,0,6.920242309570312,0,0,0,0,0,0,0,-30.31059265136719,0,4.906982421875,0,0,0,0,0,0,3.492813110351562,0,0,0,0,0,0,0,3.406036376953125,0,0,0,0,0,0,0,5.910285949707031,0,0,0,0,0,0,0,6.157966613769531,0,6.053718566894531,0,0,0,0,0,0,-29.14627838134766,0,2.507659912109375,0,0,0,0,0,2.858482360839844,0,0,0,0,0,0,0,5.81219482421875,0,6.495254516601562,0,0,0,0,0,8.87237548828125,0,0,0,0,0,0,0,-28.69549560546875,0,0,0,0,5.297294616699219,0,2.483909606933594,0,0,0,0.5348281860351562,0,0,0,0,0,3.733146667480469,0,0,0,4.796806335449219,0,0,0,0,0,3.132469177246094,0,0,0,4.519020080566406,0,0,0.622772216796875,0,0,0,2.959571838378906,0,0,0,3.599189758300781,0,0,-29.23345184326172,0,0,0,0,0,3.204742431640625,0,0,0,3.748359680175781,0,0,0,0,0,2.250900268554688,0,0,0,0,0,3.258613586425781,0,0,0,4.838088989257812,0,4.535629272460938,0,0,0,0,0,0,5.663520812988281,0,0,0,0,0,0,0,0,-25.98294067382812,0,0,0,0,0,0,0,0,0,0,0,0,0,4.7957763671875,0,0,0,0,0,0,5.523895263671875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.944717407226562,0,0,0,0,0,0,0,1.128433227539062,0,0,0,0,0,6.769927978515625,0,0,0,0,0,-14.57260131835938,0,0,0,0,0,0,0,-7.483291625976562,0,0,0,0,6.676902770996094,0,0,0,0,0,0,5.559944152832031,0,3.986312866210938,0,3.644096374511719,0,0,0,0,0,0,0,0,4.742637634277344,0,0,-25.14800262451172,0,0,0,0,0,0,5.655601501464844,0,7.773292541503906,0,0,0,0,0,0,6.229530334472656,0,0,0,0,0,0,0,4.461517333984375,0,0,0,0,0,0,0,1.028594970703125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-50.42425537109375,0,0,0,0,0,0,0,1.816726684570312,0,0,0,0,0,0,0,0,0,6.058204650878906,0,0,0,0,0,0,0,6.354354858398438,0,0,0,0,0,0,0,8.242088317871094,0,0,0,6.91339111328125,0,0,0,0,0,0,0,0,1.20751953125,0,0,0,0,6.52239990234375,0,0,0,0,0,0,6.372535705566406,0,0,0,0,0,6.610305786132812,0,-47.88024139404297,0,5.993499755859375,0,0,0,0,0,0,5.859542846679688,0,0,0,0,0,0,0.6596527099609375,0,1.420875549316406,0,0,0,0,0,0,0,6.690803527832031,0,0.2555389404296875,0,0,0,0,0,0,0,0.8933868408203125,0,0,0,0,0,0,0,6.134384155273438,0,0,0,0,0,0,0.8492660522460938,0,1.381637573242188,0,0,0,0,0,3.732177734375,0,0,0,0,0,0,0,2.490875244140625,0,1.307861328125,0,0,0,0,0,3.74072265625,0,0,0,0,2.675399780273438,0,1.336128234863281,0,0,0,0,0,0,0,2.759048461914062,0,0,0,0,0,0,0,0,0,-45.33831024169922,0,0,0,0,0],"filename":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,"/HelperFunction.R",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,null,"<expr>",null,null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/singleindexmodelfunctions.R",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,"<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,"<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,null,"<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,null,null,null,"<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"<expr>","/HelperFunction.R","<expr>",null,null,null,"<expr>","/HelperFunction.R",null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,"/HelperFunction.R",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"<expr>","/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"<expr>","/HelperFunction.R",null,"/HelperFunction.R","<expr>","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/HelperFunction.R","<expr>",null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,"/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/singleindexmodelfunctions.R",null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,"/singleindexmodelfunctions.R","/est_s_t_y.R","/HelperFunction.R","<expr>",null,null,null,null,null,null,null,null,null,null,null,"/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R","/SensIAT_sim_outcome_modeler_mave.R",null,null,"/SensIAT_sim_outcome_modeler_mave.R","/est_s_t_y.R","/HelperFunction.R","<expr>","/HelperFunction.R",null,null,"/est_s_t_y.R","/HelperFunction.R","<expr>"]},"interval":10,"files":[{"filename":"<expr>","content":"pv <- profvis({\n\n## empty containers\nBoot.Est <- matrix(NA, nrow=nrow(grid), ncol=264)\n\n## parametric bootstrap\nload(\"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/simData/imputed1/n500/sim1.rds\")\nX_sim = data.frame(dplyr::select(data, c(age, pain_bq, expectationb, ChronicPainb)))\n\nfor(i in 1:nboot_B){\n  \n  boot_b_temp <- pboot(data=data, X_sim=X_sim, sim.size=500, seed=NULL)\n  data.new <- boot_b_temp$data.new\n  X.new <- data.frame(dplyr::select(data.new, c(age, pain_bq, expectationb, ChronicPainb)))\n  topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1, coef_g.fit=boot_b_temp$coef_g.fit, \n                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, \n                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)\n  oral_vals    <- fit_one(data=data.new, X=X.new, trt_val=0, coef_g.fit=boot_b_temp$coef_g.fit, \n                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, \n                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)\n  Boot.Est[which(grid$b==i&grid$c==1), ] <- c(topical_vals, oral_vals)\n  \n  boot_b_fit <- pboot_model(data=data.new, X_sim=X.new)\n  coef_g.fit <- coef(boot_b_fit$g.fit)\n  coef_t_R0.fit <- coef(boot_b_fit$t_R0.fit)\n  coef_t_R1.fit <- coef(boot_b_fit$t_R1.fit)\n  coef_M_R0.fit <- coef(boot_b_fit$M_R0.fit)\n  coef_M_R1.fit <- coef(boot_b_fit$M_R1.fit)\n  \n  for(j in 1:nboot_C){\n    \n    data.new2 <- pboot_sim(data=data.new, X_sim=X.new, sim.size=500, seed=NULL, \n                             fit_t_R0_h=boot_b_fit$fit_t_R0_h, fit_t_R1_h=boot_b_fit$fit_t_R1_h, \n                             fit_t0_R0_h=boot_b_fit$fit_t0_R0_h, fit_t0_R1_h=boot_b_fit$fit_t0_R1_h, \n                             g.fit=boot_b_fit$g.fit, t_R0.fit=boot_b_fit$t_R0.fit, M_R0.fit=boot_b_fit$M_R0.fit, \n                             M_R1.fit=boot_b_fit$M_R1.fit)\n    X.new2 <- data.frame(dplyr::select(data.new2, c(age, pain_bq, expectationb, ChronicPainb)))\n    ## inner estimator\n    temp_topical <- fit_one(data=data.new2, X=X.new2, trt_val=1, coef_g.fit=coef_g.fit, \n                            coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,\n                            coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)\n    temp_oral <- fit_one(data=data.new2, X=X.new2, trt_val=0, coef_g.fit=coef_g.fit, \n                         coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,\n                         coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)\n    Boot.Est[which(grid$b==i&grid$c==j), 133:264] <- c(temp_topical, temp_oral)\n    \n  }\n  \n  print(i)\n  \n}\n\n})\n","normpath":"<expr>"},{"filename":"/HelperFunction.R","content":"gam.variables <- function(data){\n  sapply(1:ncol(data), function(i){\n    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste(\"s\", \"(\",names(data)[i], \", k=5)\", sep=\"\")}\n    else{names(data[i]) }\n  })\n}\n\nsingle.index.variables <- function(data){\n  sapply(1:ncol(data), function(i){\n    if (is.numeric(data[,i]) | is.integer(data[, i])){ paste(\"ns\", \"(\",names(data[i]), \")\", sep=\"\")}\n    else{names(data[i]) }\n  })\n}\n\neq <- function(theta,z) {\n  mean( pmin( (z)^2, theta^2 )/ theta^2) - log(length(z))/length(z)\n}\n\n## Induced estimates\ncounterfactual <- function(Y, Y0, M, R, X, t, trt, gamma, est){\n  \n  result <- vector(length=length(gamma))\n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model and \n  index.var.Y <- single.index.variables(X)\n  X_adjust <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(t==trt & R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(t==trt & R==1), ]\n  X_R0 <- X[which(R==0), ]\n  X_R1 <- X[which(R==1), ]\n  Y_t_R0 <- Y[which(t==trt & R==0)]\n  Y_t_R1 <- Y[which(t==trt & R==1)]\n  M_t_R0 <- M[which(t==trt & R==0)]\n  M_t_R1 <- M[which(t==trt & R==1)]\n  trt.ind_R0 <- trt.ind[which(R==0)]\n  trt.ind_R1 <- trt.ind[which(R==1)]\n  \n  ## fit outcome model\n  requireNamespace('MAVE', quietly = TRUE)\n  SDR_t_R0 <- coef(MAVE::mave.compute(X_adjust_scale_t_R0[which(M_t_R0==1), ], Y_t_R0[which(M_t_R0==1)], max.dim = 1), 1)\n  # SDR_t_R0 <- cumuSIR(X=X_adjust_scale_t_R0[which(M_t_R0==1), ], Y=Y_t_R0[which(M_t_R0==1)])\n  fit_t_R0_h <- SIDRnew_fixed_bandwidth(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                        Y = Y_t_R0[which(M_t_R0==1)],\n                                        initial = SDR_t_R0,\n                                        kernel = \"K2_Biweight\",\n                                        method = \"optim\",\n                                        ids = 1:length(Y_t_R0[which(M_t_R0==1)]))\n  SDR_t_R1 <- coef(MAVE::mave.compute(X_adjust_scale_t_R1[which(M_t_R1==1), ], Y_t_R1[which(M_t_R1==1)], max.dim = 1), 1)\n  # SDR_t_R1 <- cumuSIR(X=X_adjust_scale_t_R1[which(M_t_R1==1), ], Y=Y_t_R1[which(M_t_R1==1)])\n  fit_t_R1_h <- SIDRnew_fixed_bandwidth(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                        Y = Y_t_R1[which(M_t_R1==1)],\n                                        initial = SDR_t_R1,\n                                        kernel = \"K2_Biweight\",\n                                        method = \"optim\",\n                                        ids = 1:length(Y_t_R1[which(M_t_R1==1)]))\n  \n  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)\n  X_beta_t_R0 <- as.vector(X_adjust_scale %*% fit_t_R0_h$coef)\n  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)\n  X_beta_t_R1 <- as.vector(X_adjust_scale %*% fit_t_R1_h$coef)\n  \n  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    \n  ny_t_R0 = length(y_t_R0) \n  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], \n                     xb=X_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                     kernel = \"K2_Biweight\")\n  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    \n  ny_t_R1 = length(y_t_R1) \n  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], \n                     xb=X_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                     kernel = \"K2_Biweight\")\n  \n  i1 = which(apply(F_X_t_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X_beta_t_R0[i1], X_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X_beta_t_R1[i1], X_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]\n  \n  dF_X_t_R0 <- F_X_t_R0-c(0, F_X_t_R0[,-ny_t_R0])\n  dF_X_t_R1 <- F_X_t_R1-c(0, F_X_t_R1[,-ny_t_R1])\n  \n  ## conditional expectation of Y given R=0, T=t and X\n  mu_X_t_R0 <- c(dF_X_t_R0 %*% (y_t_R0+c(0, y_t_R0[-ny_t_R0]))/2)\n  ## conditional expectation of Y given R=1, T=t and X\n  mu_X_t_R1 <- c(dF_X_t_R1 %*% (y_t_R1+c(0, y_t_R1[-ny_t_R1]))/2)\n  \n  ## fit g model\n  g.fit <- mgcv::gam(as.formula(paste(\"R ~\", gam.var)), data=cbind(R, X), family=binomial) \n  g1 <- predict(g.fit, newdata=X, type=\"response\") \n  g0 <- 1-g1\n  \n  ## fit treatment assignment model\n  t_R0.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  t_R1.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R1 ~\", gam.var)), data=X_R1, family=binomial) ## treatment model\n  pi_R0 <- predict(t_R0.fit, newdata=X, type=\"response\") \n  pi_R1 <- predict(t_R1.fit, newdata=X, type=\"response\")\n\n  ## empirical mean\n  prop_t <- sum(trt.ind)/n\n  mean_Y0_t0 <- mean(Y0[which(t!=trt)])\n  mean_Y0_t <- mean(Y0[which(t==trt)])\n  \n  result_t0 <- (est-mean(mu_X_t_R0*pi_R0*g0+mu_X_t_R1*pi_R1*g1))/(1-prop_t)-mean_Y0_t0\n  result_t <- mean(mu_X_t_R0*pi_R0*g0+mu_X_t_R1*pi_R1*g1)/prop_t-mean_Y0_t\n  return(c(result_t0, result_t))\n  \n}\n\n\n## truth: single index or beta regression\ntruth <- function(Y, Y0, M, R, t, X, trt, gamma){\n  \n  truth_t <- c()\n  truth_t_R1 <- c()\n  truth_t_R0 <- c()\n  \n  truth_t_diff <- c()\n  truth_t_R1_diff <- c()\n  truth_t_R0_diff <- c()\n  \n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model and \n  index.var.Y <- single.index.variables(X)\n  \n  X_R0 <- X[which(R==0), ]\n  X_R1 <- X[which(R==1), ]\n  Y_t_R0 <- Y[which(t==trt & R==0)]\n  Y_t_R1 <- Y[which(t==trt & R==1)]\n  M_t_R0 <- M[which(t==trt & R==0)]\n  M_t_R1 <- M[which(t==trt & R==1)]\n  trt.ind_R0 <- trt.ind[which(R==0)]\n  trt.ind_R1 <- trt.ind[which(R==1)]\n  \n  ## fit outcome model\n    # rescale outcome to (0,1)\n    eps <- 1e-6\n    Y01 <- Y/100\n    # nudge any 0/1 slightly inside (only needed if any exact 0 or 100)\n    Y01[Y01 <= 0] <- eps\n    Y01[Y01 >= 1] <- 1 - eps\n    \n    Y_t_R0.fit <- betareg(as.formula(paste(\"Y01 ~\", paste(index.var.Y, collapse = \"+\"))), data=cbind(Y01, X)[which(t==trt & R==0 & M==1), ])\n    Y_t_R1.fit <- betareg(as.formula(paste(\"Y01 ~\", paste(index.var.Y, collapse = \"+\"))), data=cbind(Y01, X)[which(t==trt & R==1 & M==1), ])\n    \n    phi_t_R0 <- Y_t_R0.fit$coefficients$precision\n    phi_t_R1 <- Y_t_R1.fit$coefficients$precision\n    \n    mu_X_t_R0 <- 100*predict(Y_t_R0.fit, newdata=X, type=\"response\")\n    mu_X_t_R1 <- 100*predict(Y_t_R1.fit, newdata=X, type=\"response\")\n  \n  ## fit g model\n  g.fit <- mgcv::gam(as.formula(paste(\"R ~\", gam.var)), data=cbind(R, X), family=binomial) \n  g1 <- predict(g.fit, newdata=X, type=\"response\") \n  g0 <- 1-g1\n  \n  ## fit treatment assignment model\n  t_R0.fit <- mgcv::gam(as.formula(paste(\"trt.ind_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  pi_R0 <- predict(t_R0.fit, newdata=X, type=\"response\") \n\n  for(g in 1:length(gamma)){\n      \n      mu_Yexp_X_t_R0 <- mapply(function(a,b) {\n        integrate(function(y) 100*y * exp(gamma[g]*pnorm((100*y-60)/25)) * dbeta(y, shape1 = a, shape2 = b), lower = 0, upper = 1)$value\n      }, mu_X_t_R0/100*phi_t_R0, (1-mu_X_t_R0/100)*phi_t_R0)\n      \n      mu_exp_X_t_R0 <- mapply(function(a,b) {\n        integrate(function(y) exp(gamma[g]*pnorm((100*y-60)/25)) * dbeta(y, shape1 = a, shape2 = b), lower = 0, upper = 1)$value\n      }, mu_X_t_R0/100*phi_t_R0, (1-mu_X_t_R0/100)*phi_t_R0)\n      \n\n      truth_t <- c(truth_t, mean(g1*mu_X_t_R1+g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0))))\n      truth_t_R0 <- c(truth_t_R0, mean(g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))/mean(g0))\n      truth_t_diff <- c(truth_t_diff, mean(g1*mu_X_t_R1+g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))-mean(Y0))\n      truth_t_R0_diff <- c(truth_t_R0_diff, mean(g0*(mu_X_t_R0*pi_R0+mu_Yexp_X_t_R0/mu_exp_X_t_R0*(1-pi_R0)))/mean(g0)-mean(Y0[which(R==0)]))\n      \n  }\n  \n  truth_t_R1 <- mean(mu_X_t_R1*g1)/mean(g1)\n  truth_t_R1_diff <- mean(mu_X_t_R1*g1)/mean(g1)-mean(Y0[which(R==1)])\n  \n  return(list(t=truth_t, t_R0=truth_t_R0, t_R1=truth_t_R1, \n              t_diff=truth_t_diff, t_R0_diff=truth_t_R0_diff, \n              t_R1_diff=truth_t_R1_diff))\n  \n}\n\n## parametric bootstrap: simulate new data based on models from original data\npboot <- function(data, X_sim, sim.size, seed){\n  \n  ## fit models\n  X_with_t <- cbind(as.factor(data$t), X_sim)\n  colnames(X_with_t)[1] <- \"treatment\"\n  gam.var <- paste(gam.variables(X_sim), collapse = \"+\") ## gam variables for treatment assignment model\n  gam.var.M <- paste(gam.variables(X_with_t), collapse = \"+\") ## gam variables for missing data model\n  index.var.Y <- paste(single.index.variables(X_sim), collapse = \"+\")\n  X_adjust <- model.matrix(as.formula(paste(\"~\", index.var.Y)), data = X_sim)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]\n  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]\n  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]\n  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]\n  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]\n  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]\n  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]\n  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]\n  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]\n  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]\n  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]\n  \n  X_R0 <- X_sim[which(data$R==0), ]\n  t_R0 <- data$t[which(data$R==0)]\n  X_R1 <- X_sim[which(data$R==1), ]\n  t_R1 <- data$t[which(data$R==1)]\n  \n  X_with_t_R0 <- X_with_t[which(data$R==0), ]\n  X_with_t_R1 <- X_with_t[which(data$R==1), ]\n  M_R0 <- data$M[which(data$R==0)]\n  M_R1 <- data$M[which(data$R==1)]\n  \n  g.fit <- mgcv::gam(as.formula(paste(\"data$R ~\", gam.var)), data=X_sim, family=binomial) \n  t_R0.fit <- mgcv::gam(as.formula(paste(\"t_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  t_R1.fit <- mgcv::gam(as.formula(paste(\"t_R1 ~\", gam.var)), data=X_R1, family=binomial) ## treatment model\n  M_R0.fit <- mgcv::gam(as.formula(paste(\"M_R0 ~\", gam.var.M)), data=X_with_t_R0, family=binomial) ## missing data model\n  M_R1.fit <- mgcv::gam(as.formula(paste(\"M_R1 ~\", gam.var.M)), data=X_with_t_R1, family=binomial) ## missing data model\n  \n  fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                              Y = Y_t_R1[which(M_t_R1==1)],\n                                                              ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R1_h, \"try-error\")) {\n    fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                                Y = Y_t_R1[which(M_t_R1==1)],\n                                                                ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                              Y = Y_t_R0[which(M_t_R0==1)],\n                                                              ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R0_h, \"try-error\")) {\n    fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                                Y = Y_t_R0[which(M_t_R0==1)],\n                                                                ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                               Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                               ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R1_h, \"try-error\")) {\n    fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                                 Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                                 ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                               Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                               ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R0_h, \"try-error\")) {\n    fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                                 Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                                 ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)\n  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)\n  X_t0_R0_beta_t0_R0 <- as.vector(X_adjust_scale_t0_R0[which(M_t0_R0==1), ] %*% fit_t0_R0_h$coef)\n  X_t0_R1_beta_t0_R1 <- as.vector(X_adjust_scale_t0_R1[which(M_t0_R1==1), ] %*% fit_t0_R1_h$coef)\n  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    \n  ny_t_R0 = length(y_t_R0) \n  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    \n  ny_t_R1 = length(y_t_R1) \n  y_t0_R0 = sort(unique(Y_t0_R0[which(M_t0_R0==1)]))    \n  ny_t0_R0 = length(y_t0_R0) \n  y_t0_R1 = sort(unique(Y_t0_R1[which(M_t0_R1==1)]))    \n  ny_t0_R1 = length(y_t0_R1) \n  \n  ## simulate data\n  if(!is.null(seed)){set.seed(seed)}\n  boot.indices <- sample(1:sim.size, size=sim.size, replace = T)\n  X.new <- X_sim[boot.indices,]\n  X_adjust_scale.new <- X_adjust_scale[boot.indices, ]\n  ## new R\n  prob.R <- predict(g.fit, newdata=X.new, type=\"response\") \n  R.new <- rbinom(n=sim.size, size=1, prob=prob.R)\n  ## new T\n  T.new_R1 <- rbinom(n=sim.size,size=1,prob=0.5)\n  prob.T_R0 <- predict(t_R0.fit, newdata=X.new, type=\"response\")\n  T.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.T_R0)\n  T.new <- T.new_R1*R.new+T.new_R0*(1-R.new)\n  \n  ## new Y\n  X.new_beta_t_R0 <- as.vector(X_adjust_scale.new %*% fit_t_R0_h$coef)\n  X.new_beta_t_R1 <- as.vector(X_adjust_scale.new %*% fit_t_R1_h$coef)\n  X.new_beta_t0_R0 <- as.vector(X_adjust_scale.new %*% fit_t0_R0_h$coef)\n  X.new_beta_t0_R1 <- as.vector(X_adjust_scale.new %*% fit_t0_R1_h$coef)\n  \n  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], \n                     xb=X.new_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], \n                     xb=X.new_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t0_R0 <- NW_new(Xb=X_t0_R0_beta_t0_R0, Y=Y_t0_R0[which(M_t0_R0==1)], \n                      xb=X.new_beta_t0_R0, y=y_t0_R0, h=fit_t0_R0_h$bandwidth, \n                      kernel = \"dnorm\")\n  F_X_t0_R1 <- NW_new(Xb=X_t0_R1_beta_t0_R1, Y=Y_t0_R1[which(M_t0_R1==1)], \n                      xb=X.new_beta_t0_R1, y=y_t0_R1, h=fit_t0_R1_h$bandwidth, \n                      kernel = \"dnorm\")\n  \n  i1 = which(apply(F_X_t_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R0[i1], X.new_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R1[i1], X.new_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R0[i1], X.new_beta_t0_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R0[i1, ] <- F_X_t0_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R1[i1], X.new_beta_t0_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R1[i1, ] <- F_X_t0_R1[-i1, ][i1.closest, ]\n  \n  Y.new_t_R0 <- apply(F_X_t_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t_R1 <- apply(F_X_t_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R1[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R0 <- apply(F_X_t0_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R1 <- apply(F_X_t0_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R1[min(which(ecdf<=x))]\n  })\n  Y.new <- Y.new_t_R0*T.new*(1-R.new)+Y.new_t_R1*T.new*R.new+\n    Y.new_t0_R0*(1-T.new)*(1-R.new)+Y.new_t0_R1*(1-T.new)*R.new\n  \n  ## new M\n  X_with_t.new <- cbind(T.new, X.new)\n  colnames(X_with_t.new)[1] <- \"treatment\"\n  prob.M_R0 <- predict(M_R0.fit, newdata=X_with_t.new, type=\"response\")\n  prob.M_R1 <- predict(M_R1.fit, newdata=X_with_t.new, type=\"response\")\n  M.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.M_R0)\n  M.new_R1 <- rbinom(n=sim.size,size=1,prob=prob.M_R1)\n  M.new <- M.new_R0*(1-R.new)+M.new_R1*R.new\n  \n  Y.new[M.new==0] <- NA\n  \n  data.new <- data.frame(cbind(Y.new, M.new, R.new, T.new, X.new))\n  colnames(data.new) <- c(\"Y\", \"M\", \"R\", \"t\", colnames(X.new))  \n  \n  coef_g.fit <- coef(g.fit)\n  coef_t_R0.fit <- coef(t_R0.fit)\n  coef_t_R1.fit <- coef(t_R1.fit)\n  coef_M_R0.fit <- coef(M_R0.fit)\n  coef_M_R1.fit <- coef(M_R1.fit)\n  \n  return(list(data.new=data.new, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, \n              coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit))\n  \n}\n\n## 1st step of parametric bootstrap: model fitting using original data\npboot_model <- function(data, X_sim){\n  \n  ## fit models\n  X_with_t <- cbind(as.factor(data$t), X_sim)\n  colnames(X_with_t)[1] <- \"treatment\"\n  gam.var <- paste(gam.variables(X_sim), collapse = \"+\") ## gam variables for treatment assignment model\n  gam.var.M <- paste(gam.variables(X_with_t), collapse = \"+\") ## gam variables for missing data model\n  index.var.Y <- paste(single.index.variables(X_sim), collapse = \"+\")\n  X_adjust <- model.matrix(as.formula(paste(\"~\", index.var.Y)), data = X_sim)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]\n  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]\n  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]\n  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]\n  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]\n  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]\n  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]\n  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]\n  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]\n  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]\n  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]\n  \n  X_R0 <- X_sim[which(data$R==0), ]\n  t_R0 <- data$t[which(data$R==0)]\n  X_R1 <- X_sim[which(data$R==1), ]\n  t_R1 <- data$t[which(data$R==1)]\n  \n  X_with_t_R0 <- X_with_t[which(data$R==0), ]\n  X_with_t_R1 <- X_with_t[which(data$R==1), ]\n  M_R0 <- data$M[which(data$R==0)]\n  M_R1 <- data$M[which(data$R==1)]\n  \n  g.fit <- mgcv::gam(as.formula(paste(\"data$R ~\", gam.var)), data=X_sim, family=binomial) \n  t_R0.fit <- mgcv::gam(as.formula(paste(\"t_R0 ~\", gam.var)), data=X_R0, family=binomial) ## treatment model\n  t_R1.fit <- mgcv::gam(as.formula(paste(\"t_R1 ~\", gam.var)), data=X_R1, family=binomial) ## treatment model\n  M_R0.fit <- mgcv::gam(as.formula(paste(\"M_R0 ~\", gam.var.M)), data=X_with_t_R0, family=binomial) ## missing data model\n  M_R1.fit <- mgcv::gam(as.formula(paste(\"M_R1 ~\", gam.var.M)), data=X_with_t_R1, family=binomial) ## missing data model\n  \n  fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                              Y = Y_t_R1[which(M_t_R1==1)],\n                                                              ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R1_h, \"try-error\")) {\n    fit_t_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R1[which(M_t_R1==1), ],\n                                                                Y = Y_t_R1[which(M_t_R1==1)],\n                                                                ids=1:length(Y_t_R1[which(M_t_R1==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                              Y = Y_t_R0[which(M_t_R0==1)],\n                                                              ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                              kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                              use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t_R0_h, \"try-error\")) {\n    fit_t_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t_R0[which(M_t_R0==1), ],\n                                                                Y = Y_t_R0[which(M_t_R0==1)],\n                                                                ids=1:length(Y_t_R0[which(M_t_R0==1)]), \n                                                                kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                               Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                               ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R1_h, \"try-error\")) {\n    fit_t0_R1_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R1[which(M_t0_R1==1), ],\n                                                                 Y = Y_t0_R1[which(M_t0_R1==1)],\n                                                                 ids=1:length(Y_t0_R1[which(M_t0_R1==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                               Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                               ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                               kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                               use_mave=TRUE), silent = TRUE)\n  if (inherits(fit_t0_R0_h, \"try-error\")) {\n    fit_t0_R0_h  <- try(fit_SensIAT_single_index_norm1coef_model(X = X_adjust_scale_t0_R0[which(M_t0_R0==1), ],\n                                                                 Y = Y_t0_R0[which(M_t0_R0==1)],\n                                                                 ids=1:length(Y_t0_R0[which(M_t0_R0==1)]), \n                                                                 kernel=\"dnorm\", bw.selection=\"ise\", bw.method=\"optim\", \n                                                                 use_mave=FALSE), silent = TRUE)\n  }\n  \n  return(list(fit_t_R0_h=fit_t_R0_h, fit_t_R1_h=fit_t_R1_h, fit_t0_R0_h=fit_t0_R0_h, \n              fit_t0_R1_h=fit_t0_R1_h, g.fit=g.fit, t_R0.fit=t_R0.fit, t_R1.fit=t_R1.fit, \n              M_R0.fit=M_R0.fit, M_R1.fit=M_R1.fit))\n  \n}\n\n## 2nd step of parametric bootstrap: simulate new data\npboot_sim <- function(data, X_sim, sim.size, seed, \n                      fit_t_R0_h, fit_t_R1_h, fit_t0_R0_h, \n                      fit_t0_R1_h, g.fit, t_R0.fit, M_R0.fit, M_R1.fit){\n  \n  ## fit models\n  index.var.Y <- paste(single.index.variables(X_sim), collapse = \"+\")\n  X_adjust <- model.matrix(as.formula(paste(\"~\", index.var.Y)), data = X_sim)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  X_adjust_scale_t_R0 <- X_adjust_scale[which(data$t==1 & data$R==0), ]\n  X_adjust_scale_t_R1 <- X_adjust_scale[which(data$t==1 & data$R==1), ]\n  X_adjust_scale_t0_R0 <- X_adjust_scale[which(data$t==0 & data$R==0), ]\n  X_adjust_scale_t0_R1 <- X_adjust_scale[which(data$t==0 & data$R==1), ]\n  M_t_R0 <- data$M[which(data$t==1 & data$R==0)]\n  M_t_R1 <- data$M[which(data$t==1 & data$R==1)]\n  M_t0_R0 <- data$M[which(data$t==0 & data$R==0)]\n  M_t0_R1 <- data$M[which(data$t==0 & data$R==1)]\n  Y_t_R0 <- data$Y[which(data$t==1 & data$R==0)]\n  Y_t_R1 <- data$Y[which(data$t==1 & data$R==1)]\n  Y_t0_R0 <- data$Y[which(data$t==0 & data$R==0)]\n  Y_t0_R1 <- data$Y[which(data$t==0 & data$R==1)]\n\n  X_t_R0_beta_t_R0 <- as.vector(X_adjust_scale_t_R0[which(M_t_R0==1), ] %*% fit_t_R0_h$coef)\n  X_t_R1_beta_t_R1 <- as.vector(X_adjust_scale_t_R1[which(M_t_R1==1), ] %*% fit_t_R1_h$coef)\n  X_t0_R0_beta_t0_R0 <- as.vector(X_adjust_scale_t0_R0[which(M_t0_R0==1), ] %*% fit_t0_R0_h$coef)\n  X_t0_R1_beta_t0_R1 <- as.vector(X_adjust_scale_t0_R1[which(M_t0_R1==1), ] %*% fit_t0_R1_h$coef)\n  y_t_R0 = sort(unique(Y_t_R0[which(M_t_R0==1)]))    \n  ny_t_R0 = length(y_t_R0) \n  y_t_R1 = sort(unique(Y_t_R1[which(M_t_R1==1)]))    \n  ny_t_R1 = length(y_t_R1) \n  y_t0_R0 = sort(unique(Y_t0_R0[which(M_t0_R0==1)]))    \n  ny_t0_R0 = length(y_t0_R0) \n  y_t0_R1 = sort(unique(Y_t0_R1[which(M_t0_R1==1)]))    \n  ny_t0_R1 = length(y_t0_R1) \n  \n  ## simulate data\n  if(!is.null(seed)){set.seed(seed)}\n  boot.indices <- sample(1:sim.size, size=sim.size, replace = T)\n  X.new <- X_sim[boot.indices,]\n  X_adjust_scale.new <- X_adjust_scale[boot.indices, ]\n  ## new R\n  prob.R <- predict(g.fit, newdata=X.new, type=\"response\") \n  R.new <- rbinom(n=sim.size, size=1, prob=prob.R)\n  ## new T\n  T.new_R1 <- rbinom(n=sim.size,size=1,prob=0.5)\n  prob.T_R0 <- predict(t_R0.fit, newdata=X.new, type=\"response\")\n  T.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.T_R0)\n  T.new <- T.new_R1*R.new+T.new_R0*(1-R.new)\n  \n  ## new Y\n  X.new_beta_t_R0 <- as.vector(X_adjust_scale.new %*% fit_t_R0_h$coef)\n  X.new_beta_t_R1 <- as.vector(X_adjust_scale.new %*% fit_t_R1_h$coef)\n  X.new_beta_t0_R0 <- as.vector(X_adjust_scale.new %*% fit_t0_R0_h$coef)\n  X.new_beta_t0_R1 <- as.vector(X_adjust_scale.new %*% fit_t0_R1_h$coef)\n  \n  F_X_t_R0 <- NW_new(Xb=X_t_R0_beta_t_R0, Y=Y_t_R0[which(M_t_R0==1)], \n                     xb=X.new_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t_R1 <- NW_new(Xb=X_t_R1_beta_t_R1, Y=Y_t_R1[which(M_t_R1==1)], \n                     xb=X.new_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                     kernel = \"dnorm\")\n  F_X_t0_R0 <- NW_new(Xb=X_t0_R0_beta_t0_R0, Y=Y_t0_R0[which(M_t0_R0==1)], \n                      xb=X.new_beta_t0_R0, y=y_t0_R0, h=fit_t0_R0_h$bandwidth, \n                      kernel = \"dnorm\")\n  F_X_t0_R1 <- NW_new(Xb=X_t0_R1_beta_t0_R1, Y=Y_t0_R1[which(M_t0_R1==1)], \n                      xb=X.new_beta_t0_R1, y=y_t0_R1, h=fit_t0_R1_h$bandwidth, \n                      kernel = \"dnorm\")\n  \n  i1 = which(apply(F_X_t_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R0[i1], X.new_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R0[i1, ] <- F_X_t_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t_R1[i1], X.new_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t_R1[i1, ] <- F_X_t_R1[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R0==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R0[i1], X.new_beta_t0_R0[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R0[i1, ] <- F_X_t0_R0[-i1, ][i1.closest, ]\n  \n  i1 = which(apply(F_X_t0_R1==0,1,prod)==1)\n  i1.closest <- apply(abs(outer(X.new_beta_t0_R1[i1], X.new_beta_t0_R1[-i1], FUN = \"-\")), 1, which.min)\n  F_X_t0_R1[i1, ] <- F_X_t0_R1[-i1, ][i1.closest, ]\n  \n  Y.new_t_R0 <- apply(F_X_t_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t_R1 <- apply(F_X_t_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t_R1[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R0 <- apply(F_X_t0_R0, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R0[min(which(ecdf<=x))]\n  })\n  Y.new_t0_R1 <- apply(F_X_t0_R1, 1, function(x){\n    ecdf <- runif(1,0,1)\n    y_t0_R1[min(which(ecdf<=x))]\n  })\n  Y.new <- Y.new_t_R0*T.new*(1-R.new)+Y.new_t_R1*T.new*R.new+\n    Y.new_t0_R0*(1-T.new)*(1-R.new)+Y.new_t0_R1*(1-T.new)*R.new\n  \n  ## new M\n  X_with_t.new <- cbind(T.new, X.new)\n  colnames(X_with_t.new)[1] <- \"treatment\"\n  prob.M_R0 <- predict(M_R0.fit, newdata=X_with_t.new, type=\"response\")\n  prob.M_R1 <- predict(M_R1.fit, newdata=X_with_t.new, type=\"response\")\n  M.new_R0 <- rbinom(n=sim.size,size=1,prob=prob.M_R0)\n  M.new_R1 <- rbinom(n=sim.size,size=1,prob=prob.M_R1)\n  M.new <- M.new_R0*(1-R.new)+M.new_R1*R.new\n  \n  Y.new[M.new==0] <- NA\n  \n  data.new <- data.frame(cbind(Y.new, M.new, R.new, T.new, X.new))\n  colnames(data.new) <- c(\"Y\", \"M\", \"R\", \"t\", colnames(X.new))  \n  \n  return(data.new)\n  \n}\n\n\n## run algorithm\nfit_one <- function(data, X, trt_val, coef_g.fit=NULL, coef_t_R0.fit=NULL, \n                    coef_t_R1.fit=NULL, coef_M_R0.fit=NULL, coef_M_R1.fit=NULL) {\n  # try mave first\n  out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, X=X,\n                     t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,\n                     IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel=\"dnorm\",\n                     method=\"optim\", single_index_method=\"norm1coef\",\n                     use_mave=TRUE, seed=NULL, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, \n                     coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit),\n             silent = TRUE)\n  \n  if (inherits(out, \"try-error\")) {\n    # fallback cumSIR\n    out <- try(est_psi(Y=data$Y, M=data$M, R=data$R, X=X,\n                       t=data$t, trt=trt_val, gamma=seq(-5, 5, by=1), fold=5,\n                       IF_output=FALSE, simple_trunc=FALSE, quant=NULL, kernel=\"dnorm\",\n                       method=\"optim\", single_index_method=\"norm1coef\",\n                       use_mave=FALSE, seed=NULL, coef_g.fit=coef_g.fit, coef_t_R0.fit=coef_t_R0.fit, \n                       coef_t_R1.fit=coef_t_R1.fit, coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit),\n               silent = TRUE)\n  }\n  \n  if (inherits(out, \"try-error\") || is.null(out)) {\n    return(rep(NA_real_, 6*length(seq(-5, 5, by=1))))\n  }else{\n    return(c(out$est_trunc, out$est_trunc_R1, out$est_trunc_R0, \n             out$var_trunc, out$var_trunc_R1, out$var_trunc_R0))\n  }\n}\n\n\n\n\n\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/HelperFunction.R"},{"filename":"/SensIAT_sim_outcome_modeler_mave.R","content":"# Single Index Model using MAVE and Optimizing Bandwidth.\n#\n# Single index model estimation using minimum average variance estimation (MAVE).\n# A direction is estimated using MAVE, and then the bandwidth is selected by\n# minimization of the cross-validated pseudo-integrated squared error.\n# Optionally, the initial coefficients of the outcome model can be re-estimated\n# by optimization on a spherical manifold.  This option requires the\n# [ManifoldOptim][ManifoldOptim::manifold.optim] package.\n\nfit_SensIAT_single_index_norm1coef_model <-\nfunction(X, Y, ids, \n         kernel = \"K2_Biweight\",\n         mave.method = \"meanMAVE\",\n         use_mave,\n         id = ..id..,\n         bw.selection = c('ise', 'mse'),\n         bw.method = c('optim', 'grid', 'optimize'),\n         bw.range = c(0.01, 1.5),\n         reestimate.coef = 0,\n         ...\n){\n    unique_y <- sort(unique(Y))\n\n    if (kernel==\"K2_Biweight\"){\n        K <- function(x) 15/16*(1-(x)^2)^2 * (abs(x) <= 1)\n        K1<- function(x) 3/4*(1-(x)^2) * (abs(x) <= 1)\n    } else if (kernel==\"dnorm\") {\n        K <- function(x) dnorm(x,0,1)\n        K1 <- function(x) -x*dnorm(x, 0, 1)\n    } else if (kernel==\"K4_Biweight\"){\n        K <- function(x) 105/64*(1-3*((x)^2)) * (1-(x)^2)^2 * (abs(x) <= 1)\n    } else{\n        stop(\"Unknown kernel type. Please use either 'K2_Biweight', 'dnorm', or 'K4_Biweight'.\")\n    }\n\n    if(use_mave){\n      assertthat::assert_that(requireNamespace(\"MAVE\", quietly = TRUE))\n      mave_fit <- MAVE::mave.compute(X, Y, max.dim = 1, method = mave.method)\n      beta_hat <- mave_fit$dir[[1]][,1,drop=TRUE]\n    }else{\n      beta_hat <- cumuSIR(X = X, Y = Y)\n    }\n\n    bw_old <- 1\n    delta_beta = NA_real_\n    res <- NULL\n\n    Id_neq <- outer(ids, ids, \\(x,y)as.numeric(x!=y))\n    Imat <- outer(Y, unique_y, `<=`)\n    repeat{\n        Xbeta <- (X %*% beta_hat)[,]\n        sigma <- sd(Xbeta)\n        D <- outer(Xbeta, Xbeta, FUN = `-`)\n\n        bw.selection <- match.arg(bw.selection)\n        if(bw.selection == 'ise'){\n            # Use Integrated Squared Error (ISE) for bandwidth selection\n            err <- function(log_bandwidth){\n                W <- K(D/exp(log_bandwidth)) * Id_neq\n                denom <- rowSums(W)\n                Fhat <- sweep(W %*% Imat, 1, denom, \"/\")\n                Fhat[is.nan(Fhat)] <- 0\n                return (sum((Imat - Fhat)^2)/length(Fhat)^2)\n            }\n        } else if(bw.selection == 'mse'){\n            # Use Mean Squared Error (MSE) for bandwidth selection\n            err <- function(log_bandwidth){\n                W <- K(D/exp(log_bandwidth)) * Id_neq\n                denom <- rowSums(W)\n                mean_Y <- c(W %*% Y) / denom\n                return (mean((Y - mean_Y)^2, na.rm = TRUE))\n            }\n        } else {\n            stop(\"Unknown bw.selection type. Please use either 'ise' or 'mse'.\")\n        }\n\n        bw.method <- match.arg(bw.method)\n        if(bw.method == 'grid'){\n            # Use grid search for bandwidth selection\n            log_bw_seq <- log(seq(min(bw.range), max(bw.range), length.out = 100) * sigma)\n            err_values <- purrr::map_dbl(log_bw_seq, err)\n            bw_opt <- log_bw_seq[which.min(err_values)]\n            bw.details <- list(par = bw_opt,\n                           value = min(err_values),\n                           convergence = 0,\n                           message = \"Grid search completed successfully.\",\n                           bw.method = bw.method,\n                           log_bw_seq = log_bw_seq,\n                           err_values = err_values\n                           )\n        } else if(bw.method == 'optim'){\n            # Use optimization for bandwidth selection\n            initial <- log(sigma * 0.30)\n            bw.details <- optim(initial, err, method = \"L-BFGS-B\", lower = log(sigma * min(bw.range)), upper = log(sigma * max(bw.range)), ...)\n            bw.details$initial = initial\n            bw.details$bw.method = bw.method\n            bw_opt <- bw.details$par\n        } else if(bw.method == 'optimize'){\n            # Use optimize for bandwidth selection\n            result <- stats::optimize(err,\n                               interval = c(log(sigma * min(bw.range)), log(sigma * max(bw.range))),\n                               ...)\n            bw_opt <- result$minimum\n            bw.details <- list(minimum = result$minimum,\n                               value = result$objective,\n                               bw.method  = bw.method,\n                               interval = c(log(sigma * 0.05), log(sigma * 1.5)))\n        } else{\n            stop(\"Unknown bw.method type. Please use either 'optim' or 'grid'.\")\n        }\n\n\n        delta_bw = abs(bw_opt - bw_old)\n\n        if(!is.null(res) && res$fval <= bw.details$value) break\n        last.optimized = 'bandwidth'\n\n        if(reestimate.coef <= 0) break\n        reestimate.coef <- reestimate.coef - 1\n\n\n        bw_old <- bw_opt\n        rlang::check_installed(\"ManifoldOptim\")\n        requireNamespace(\"ManifoldOptim\", quietly = TRUE)\n\n        beta_hat_old <- beta_hat\n        if(bw.selection == \"ise\") {\n            objFun <- function(beta){\n                Xbeta <- (X %*% beta)[,]\n                D <- outer(Xbeta, Xbeta, FUN = `-`)\n                W <- K(D/exp(bw_opt)) * Id_neq\n                denom <- rowSums(W)\n                Fhat <- sweep(W %*% Imat, 1, denom, \"/\")\n                Fhat[is.nan(Fhat)] <- 0\n                return (sum((Imat - Fhat)^2)/length(Fhat)^2)\n            }\n        } else if(bw.selection == \"mse\") {\n            objFun <- function(beta){\n                Xbeta <- (X %*% beta)[,]\n                D <- outer(Xbeta, Xbeta, FUN = `-`)\n                W <- K1(D/exp(bw_opt)) * Id_neq\n                denom <- rowSums(W)\n                mean_Y <- c(W %*% Y) / denom\n                return (mean((Y - mean_Y)^2, na.rm = TRUE))\n            }\n        } else {\n            stop(\"Unknown bw.selection type. Please use either 'ise' or 'mse'.\")\n        }\n        mod <- Rcpp::Module(\"ManifoldOptim_module\", PACKAGE = \"ManifoldOptim\")\n        prob <- new(mod$RProblem, objFun)\n        mani.params <- ManifoldOptim::get.manifold.params(IsCheckParams = FALSE)\n        solver.params <- ManifoldOptim::get.solver.params(IsCheckParams = FALSE)\n        maniDef <- ManifoldOptim::get.sphere.defn(length(beta_hat))\n\n        res <- ManifoldOptim::manifold.optim(prob, maniDef,\n                              mani.params = mani.params,\n                              solver.params = solver.params, x0 = beta_hat)\n        if(res$fval >= bw.details$value) break\n        last.optimized = 'beta'\n\n        beta_hat <- as.vector(res$xopt)\n        delta_beta = abs(beta_hat - beta_hat_old)\n    }\n    return(\n            list(\n                coef = beta_hat,\n                bandwidth = exp(bw_opt),\n                details = list(bw.last = bw.details,\n                               bw.delta = delta_bw,\n                               bw.unscaled = bw_opt/sigma,\n                               beta.delta = delta_beta,\n                               beta.last  = res,\n                               last.optimized = last.optimized\n                               )\n            )\n    )\n}\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/SensIAT_sim_outcome_modeler_mave.R"},{"filename":"/est_s_t_y.R","content":"\nest_psi <- function(Y, M, R, X, t, trt, gamma, fold, seed, IF_output, \n                    simple_trunc, quant, kernel, method, single_index_method, \n                    use_mave=TRUE, coef_g.fit=NULL, coef_t_R0.fit=NULL, coef_t_R1.fit=NULL, \n                    coef_M_R0.fit=NULL, coef_M_R1.fit=NULL){\n  \n  n <- length(t)\n  Y[is.na(Y)] <- 0\n  \n  trt.ind <- as.numeric(t==trt) # create treatment indicator variable\n  \n  ## set up covariates list and design matrix for modeling\n  X_with_T <- cbind(as.factor(t), X)\n  colnames(X_with_T)[1] <- \"treatment\"\n  gam.var <- paste(gam.variables(X), collapse = \"+\") ## gam variables for treatment assignment model\n  gam.var.M <- paste(gam.variables(X_with_T), collapse = \"+\") ## gam variables for missing data model\n  index.var.Y <- single.index.variables(X)\n  X_adjust <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n  X_adjust_scale <- scale(X_adjust)\n  \n  ## empty containers\n  IF <- vector(mode = \"list\", length = length(gamma))\n  IF_R1 <- vector(mode = \"list\", length = length(gamma))\n  IF_R0 <- vector(mode = \"list\", length = length(gamma))\n  est_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R1_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R0_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R1_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R0_temp <- matrix(0, nrow=fold, ncol=length(gamma))\n  IF_diff <- vector(mode = \"list\", length = length(gamma))\n  IF_R1_diff <- vector(mode = \"list\", length = length(gamma))\n  IF_R0_diff <- vector(mode = \"list\", length = length(gamma))\n  est_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R1_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  est_R0_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R1_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  var_R0_temp_diff <- matrix(0, nrow=fold, ncol=length(gamma))  \n  vector_R1 <- vector_R0 <- c()\n  id_list <- c()\n  if(!simple_trunc){\n    IF_trunc <- vector(mode = \"list\", length = length(gamma))\n    IF_R1_trunc <- vector(mode = \"list\", length = length(gamma))\n    IF_R0_trunc <- vector(mode = \"list\", length = length(gamma))\n    est_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R1_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R0_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R1_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R0_temp_trunc <- matrix(0, nrow=fold, ncol=length(gamma))\n    IF_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    IF_R1_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    IF_R0_trunc_diff <- vector(mode = \"list\", length = length(gamma))\n    est_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R1_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    est_R0_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R1_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n    var_R0_temp_trunc_diff <- matrix(0, nrow=fold, ncol=length(gamma))\n  \n  }\n  \n  ## cross fit\n  if(!is.null(seed)){set.seed(seed)}\n  indx <- sample(1:n)\n  fold_list <- split(1:n, indx %% fold)\n  fold_nk_list <- vector(length=fold)\n  \n  ## containers\n  pain_bq_reordered <- c()\n  pain_bq_reordered_R1 <- c()\n  pain_bq_reordered_R0 <- c()\n  pi_R0_l <- c()\n  pi_R1_l <- c()\n  eta_t_R0_l <- c()\n  eta_t0_R0_l <- c()\n  eta_T_R1_l <- c()\n  fold_index_pi_R0_l <- c()\n  fold_index_pi_R1_l <- c()\n  fold_index_eta_t_R0_l <- c()\n  fold_index_eta_t0_R0_l <- c()\n  fold_index_eta_T_R1_l <- c()\n  fold_index_pain <- c()\n  \n  ## compute weights across folds\n  for (k in 1:fold){\n    ## out-of-fold data\n    if(fold>1){\n      out_fold_id_list <- setdiff(1:n, fold_list[[k]])\n    }else{\n      out_fold_id_list <- 1:n\n    }\n    M_out_fold <- M[out_fold_id_list]\n    R_out_fold <- R[out_fold_id_list]\n    t_out_fold <- t[out_fold_id_list]\n    trt.ind_out_fold <- trt.ind[out_fold_id_list]\n    X_out_fold <- X[out_fold_id_list, ]\n    X_with_T_out_fold <- X_with_T[out_fold_id_list, ]\n    \n    t_out_fold_R0 <- t_out_fold[which(R_out_fold==0)]\n    X_out_fold_R0 <- X_out_fold[which(R_out_fold==0), ]\n    t_out_fold_R1 <- t_out_fold[which(R_out_fold==1)]\n    X_out_fold_R1 <- X_out_fold[which(R_out_fold==1), ]\n    \n    M_out_fold_R0 <- M_out_fold[which(R_out_fold==0)]\n    X_with_T_out_fold_R0 <- X_with_T_out_fold[which(R_out_fold==0), ]\n    M_out_fold_R1 <- M_out_fold[which(R_out_fold==1)]\n    X_with_T_out_fold_R1 <- X_with_T_out_fold[which(R_out_fold==1), ]\n    \n    ## in-fold data\n    nk_in_fold <- length(fold_list[[k]])\n    fold_nk_list[k] <- nk_in_fold\n    R_in_fold <- R[fold_list[[k]]]\n    t_in_fold <- t[fold_list[[k]]]\n    X_in_fold <- X[fold_list[[k]], ]\n    X_with_T_in_fold <- X_with_T[fold_list[[k]], ]\n    \n    X_in_fold_t_R0 <- X_in_fold[which(t_in_fold==trt & R_in_fold==0), ]\n    X_in_fold_t0_R0 <- X_in_fold[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_in_fold_R1 <- X_in_fold[which(R_in_fold==1), ]\n    \n    X_with_T_in_fold_t_R0 <- X_with_T_in_fold[which(t_in_fold==trt & R_in_fold==0), ]\n    X_with_T_in_fold_t0_R0 <- X_with_T_in_fold[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_with_T_in_fold_R1 <- X_with_T_in_fold[which(R_in_fold==1), ]\n    \n    ## fit models\n    t_R0.fit <- mgcv::gam(as.formula(paste(\"t_out_fold_R0 ~\", gam.var)), data=X_out_fold_R0, \n                          family=binomial, start=coef_t_R0.fit) ## treatment model\n    t_R1.fit <- mgcv::gam(as.formula(paste(\"t_out_fold_R1 ~\", gam.var)), data=X_out_fold_R1, \n                          family=binomial, start=coef_t_R1.fit) ## treatment model\n    M_R0.fit <- mgcv::gam(as.formula(paste(\"M_out_fold_R0 ~\", gam.var.M)), data=X_with_T_out_fold_R0, \n                          family=binomial, start=coef_M_R0.fit) ## missing data model\n    M_R1.fit <- mgcv::gam(as.formula(paste(\"M_out_fold_R1 ~\", gam.var.M)), data=X_with_T_out_fold_R1, \n                          family=binomial, start=coef_M_R1.fit) ## missing data model\n    \n    prop.R1 <- mean(R_in_fold)\n    \n    ## get predictions for pi\n    if(trt==1){\n      pi_R0 <- predict(t_R0.fit, newdata=X_in_fold_t_R0, type=\"response\") \n      pi_R1 <- predict(t_R1.fit, newdata=X_in_fold_R1, type=\"response\")  \n    }else{\n      pi_R0 <- 1-predict(t_R0.fit, newdata=X_in_fold_t_R0, type=\"response\") \n      pi_R1 <- 1-predict(t_R1.fit, newdata=X_in_fold_R1, type=\"response\")  \n    }\n    pi_R0_l <- c(pi_R0_l, pi_R0)\n    pi_R1_l <- c(pi_R1_l, pi_R1)\n    fold_index_pi_R0_l <- c(fold_index_pi_R0_l, rep(k, length(pi_R0)))\n    fold_index_pi_R1_l <- c(fold_index_pi_R1_l, rep(k, length(pi_R1)))\n    \n    ## get predictions for eta\n    eta_t_R0 <- predict(M_R0.fit, newdata=mutate(X_with_T_in_fold_t_R0, treatment=trt), type=\"response\")\n    eta_t0_R0 <- predict(M_R0.fit, newdata=mutate(X_with_T_in_fold_t0_R0, treatment=1-trt), type=\"response\")\n    eta_T_R1 <- predict(M_R1.fit, newdata=X_with_T_in_fold_R1, type=\"response\")\n    eta_t_R0_l <- c(eta_t_R0_l, eta_t_R0)\n    eta_t0_R0_l <- c(eta_t0_R0_l, eta_t0_R0)\n    eta_T_R1_l <- c(eta_T_R1_l, eta_T_R1)\n    fold_index_eta_t_R0_l <- c(fold_index_eta_t_R0_l, rep(k, length(eta_t_R0)))\n    fold_index_eta_t0_R0_l <- c(fold_index_eta_t0_R0_l, rep(k, length(eta_t0_R0)))\n    fold_index_eta_T_R1_l <- c(fold_index_eta_T_R1_l, rep(k, length(eta_T_R1)))\n    \n    if(trt==1){\n      pain_bq_temp <- c(X_in_fold_t_R0$pain_bq, X_in_fold_t0_R0$pain_bq, X_in_fold_R1$pain_bq)\n      pain_bq_R1_temp <- c(rep(0, length(X_in_fold_t_R0$pain_bq)+length(X_in_fold_t0_R0$pain_bq)), X_in_fold_R1$pain_bq)/prop.R1\n      pain_bq_R0_temp <- c(X_in_fold_t_R0$pain_bq, X_in_fold_t0_R0$pain_bq, rep(0, length(X_in_fold_R1$pain_bq)))/(1-prop.R1)\n    }else{\n      pain_bq_temp <- c(X_in_fold_t0_R0$pain_bq, X_in_fold_t_R0$pain_bq, X_in_fold_R1$pain_bq)\n      pain_bq_R1_temp <- c(rep(0, length(X_in_fold_t0_R0$pain_bq)+length(X_in_fold_t_R0$pain_bq)), X_in_fold_R1$pain_bq)/prop.R1\n      pain_bq_R0_temp <- c(X_in_fold_t0_R0$pain_bq, X_in_fold_t_R0$pain_bq, rep(0, length(X_in_fold_R1$pain_bq)))/(1-prop.R1)\n    }\n    pain_bq_reordered <- c(pain_bq_reordered, pain_bq_temp)\n    pain_bq_reordered_R1 <- c(pain_bq_reordered_R1, pain_bq_R1_temp)\n    pain_bq_reordered_R0 <- c(pain_bq_reordered_R0, pain_bq_R0_temp)\n    fold_index_pain <- c(fold_index_pain, rep(k, length(pain_bq_temp)))\n  }\n  \n  ## weight truncation\n  if(!simple_trunc){\n  pi_R0_l <- pmin(pmax(pi_R0_l,0.01),0.99)\n  pi_R1_l <- pmin(pmax(pi_R1_l,0.01),0.99)\n  eta_t_R0_l <- pmin(pmax(eta_t_R0_l,0.01),0.99)\n  eta_t0_R0_l <- pmin(pmax(eta_t0_R0_l,0.01),0.99)\n  eta_T_R1_l <- pmin(pmax(eta_T_R1_l,0.01),0.99)\n  }\n  pi_R0_weight_l <- 1/pi_R0_l\n  pi_R1_weight_l <- 1/pi_R1_l\n  eta_t_R0_weight_l <- 1/eta_t_R0_l\n  eta_t0_R0_weight_l <- 1/eta_t0_R0_l\n  eta_T_R1_weight_l <- 1/eta_T_R1_l\n  if(simple_trunc){\n  pi_R0_weight_l[which(pi_R0_weight_l >= quantile(pi_R0_weight_l, probs = quant))] <- quantile(pi_R0_weight_l, probs = quant)\n  pi_R1_weight_l[which(pi_R1_weight_l >= quantile(pi_R1_weight_l, probs = quant))] <- quantile(pi_R1_weight_l, probs = quant)\n  quant_eta_T_R0_weight <- quantile(c(eta_t_R0_weight_l, eta_t0_R0_weight_l), probs = quant)\n  eta_t_R0_weight_l[which(eta_t_R0_weight_l>=quant_eta_T_R0_weight)] <- quant_eta_T_R0_weight\n  eta_t0_R0_weight_l[which(eta_t0_R0_weight_l>=quant_eta_T_R0_weight)] <- quant_eta_T_R0_weight\n  eta_T_R1_weight_l[which(eta_T_R1_weight_l >= quantile(eta_T_R1_weight_l, probs = quant))] <- quantile(eta_T_R1_weight_l, probs = quant)\n  }\n  \n  ## compute outcome model and influence function for each fold\n  for (k in 1:fold){\n    \n    ## out-of-fold data\n    if(fold>1){\n      out_fold_id_list <- setdiff(1:n, fold_list[[k]])\n    }else{\n      out_fold_id_list <- 1:n\n    }\n    Y_out_fold <- Y[out_fold_id_list]\n    M_out_fold <- M[out_fold_id_list]\n    R_out_fold <- R[out_fold_id_list]\n    t_out_fold <- t[out_fold_id_list]\n    X_out_fold <- X[out_fold_id_list, ]\n    X_out_fold_adjust_scale <- X_adjust_scale[out_fold_id_list, ]\n\n    Y_out_fold_t_R0 <- Y_out_fold[which(t_out_fold==trt & R_out_fold==0)]\n    Y_out_fold_t_R1 <- Y_out_fold[which(t_out_fold==trt & R_out_fold==1)]\n    X_out_fold_t_R0_adjust_scale <- X_out_fold_adjust_scale[which(t_out_fold==trt & R_out_fold==0), ]\n    X_out_fold_t_R1_adjust_scale <- X_out_fold_adjust_scale[which(t_out_fold==trt & R_out_fold==1), ]\n    M_out_fold_t_R0 <- M_out_fold[which(t_out_fold==trt & R_out_fold==0)]\n    M_out_fold_t_R1 <- M_out_fold[which(t_out_fold==trt & R_out_fold==1)]\n    #X_out_fold_t_R0 <- X_out_fold[which(t_out_fold==trt & R_out_fold==0), ]\n    #X_out_fold_t_R1 <- X_out_fold[which(t_out_fold==trt & R_out_fold==1), ]\n    #X_out_fold_t_R0_adjust_scale <- model.matrix(as.formula(paste(\"~\", paste(index.var.Y, collapse = \"+\"))), data = X)[,-1]\n\n    ## in-fold data\n    nk_in_fold <- length(fold_list[[k]])\n    Y_in_fold <- Y[fold_list[[k]]]\n    M_in_fold <- M[fold_list[[k]]]\n    R_in_fold <- R[fold_list[[k]]]\n    t_in_fold <- t[fold_list[[k]]]\n    trt.ind_in_fold <- trt.ind[fold_list[[k]]]\n    X_in_fold_adjust_scale <- X_adjust_scale[fold_list[[k]], ]\n\n    X_in_fold_t_R0_adjust_scale <- X_in_fold_adjust_scale[which(t_in_fold==trt & R_in_fold==0), ]\n    X_in_fold_t0_R0_adjust_scale <- X_in_fold_adjust_scale[which(t_in_fold!=trt & R_in_fold==0), ]\n    X_in_fold_R1_adjust_scale <- X_in_fold_adjust_scale[which(R_in_fold==1), ]\n    \n    M_in_fold_t_R0 <- M_in_fold[which(t_in_fold==trt & R_in_fold==0)]\n    M_in_fold_t0_R0 <- M_in_fold[which(t_in_fold!=trt & R_in_fold==0)]\n    M_in_fold_R1 <- M_in_fold[which(R_in_fold==1)]\n\n    Y_in_fold_t_R0 <- Y_in_fold[which(t_in_fold==trt & R_in_fold==0)]\n    Y_in_fold_R1 <- Y_in_fold[which(R_in_fold==1)]\n    \n    trt.ind_in_fold_R1 <- trt.ind_in_fold[which(R_in_fold==1)]\n    \n    id_list <- c(id_list, fold_list[[k]])\n    \n    ## get the weights in fold k\n    pi_R0_weight <- pi_R0_weight_l[which(fold_index_pi_R0_l==k)]\n    pi_R1_weight <- pi_R1_weight_l[which(fold_index_pi_R1_l==k)]\n    eta_t_R0_weight <- eta_t_R0_weight_l[which(fold_index_eta_t_R0_l==k)]\n    eta_t0_R0_weight <- eta_t0_R0_weight_l[which(fold_index_eta_t0_R0_l==k)]\n    eta_T_R1_weight <- eta_T_R1_weight_l[which(fold_index_eta_T_R1_l==k)]\n    \n    ## get baseline pain score in fold k\n    pain_bq_temp <- pain_bq_reordered[which(fold_index_pain==k)]\n    pain_bq_R1_temp <- pain_bq_reordered_R1[which(fold_index_pain==k)]\n    pain_bq_R0_temp <- pain_bq_reordered_R0[which(fold_index_pain==k)]\n    \n    ## fit models\n    if(single_index_method==\"fixed_bandwidth\"){\n      if(use_mave){\n        requireNamespace('MAVE', quietly = TRUE)\n        SDR_t_R0 <- coef(MAVE::mave.compute(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                            Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], max.dim = 1), 1)\n      }else{\n        SDR_t_R0 <- cumuSIR(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)])\n      }\n      fit_t_R0_h <- SIDRnew_fixed_bandwidth(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)],\n                                            initial = SDR_t_R0,\n                                            kernel = kernel,\n                                            method = method,\n                                            ids = 1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))\n\n    }else if(single_index_method==\"fixed_coef\"){\n    if(use_mave){\n      requireNamespace('MAVE', quietly = TRUE)\n      SDR_t_R0 <- coef(MAVE::mave.compute(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                          Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], max.dim = 1), 1)\n    }else{\n      SDR_t_R0 <- cumuSIR(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                          Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)])\n    }\n    fit_t_R0_h <- SIDR_Ravinew(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                               Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)],\n                               initial=c(1,as.vector(SDR_t_R0[-1]/SDR_t_R0[1])), \n                               kernel = kernel,\n                               method = method, \n                               index_ID=1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))\n    }else if(single_index_method==\"norm1coef\"){\n    fit_t_R0_h  <- fit_SensIAT_single_index_norm1coef_model(X = X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ],\n                                                            Y = Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                                                            ids=1:length(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]), \n                                                            kernel=kernel, bw.selection=\"ise\", bw.method=\"optim\", use_mave=use_mave)\n    }\n    \n    if(single_index_method==\"fixed_bandwidth\"){\n    if(use_mave){\n    SDR_t_R1 <- coef(MAVE::mave.compute(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                        Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], max.dim = 1), 1)\n    }else{\n    SDR_t_R1 <- cumuSIR(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                        Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)])\n    }\n    fit_t_R1_h <- SIDRnew_fixed_bandwidth(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                          Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                                          initial = SDR_t_R1,\n                                          kernel = kernel,\n                                          method = method,\n                                          ids = 1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))\n    }else if(single_index_method==\"fixed_coef\"){\n      if(use_mave){\n        SDR_t_R1 <- coef(MAVE::mave.compute(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                            Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], max.dim = 1), 1)\n      }else{\n        SDR_t_R1 <- cumuSIR(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                            Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)])\n      }\n    fit_t_R1_h <- SIDR_Ravinew(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                               Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                               initial=c(1,as.vector(SDR_t_R1[-1]/SDR_t_R1[1])), \n                               kernel = kernel,\n                               method = method, \n                               index_ID=1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))\n    }else if(single_index_method==\"norm1coef\"){\n    fit_t_R1_h  <- fit_SensIAT_single_index_norm1coef_model(X = X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ],\n                                                            Y = Y_out_fold_t_R1[which(M_out_fold_t_R1==1)],\n                                                            ids=1:length(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]), \n                                                            kernel=kernel, bw.selection=\"ise\", bw.method=\"optim\", use_mave=use_mave)\n    }\n    \n    ## get prediction for X'beta\n    X_in_fold_t_R0_beta_t_R0 <- as.vector(X_in_fold_t_R0_adjust_scale %*% fit_t_R0_h$coef)\n    X_in_fold_t0_R0_beta_t_R0 <- as.vector(X_in_fold_t0_R0_adjust_scale %*% fit_t_R0_h$coef)\n    X_in_fold_R1_beta_t_R1 <- as.vector(X_in_fold_R1_adjust_scale %*% fit_t_R1_h$coef)\n    X_out_fold_t_R0_beta_t_R0 <- as.vector(X_out_fold_t_R0_adjust_scale[which(M_out_fold_t_R0==1), ] %*% fit_t_R0_h$coef)\n    X_out_fold_t_R1_beta_t_R1 <- as.vector(X_out_fold_t_R1_adjust_scale[which(M_out_fold_t_R1==1), ] %*% fit_t_R1_h$coef)\n    \n    ## compute CDF\n    y_t_R0 = sort(unique(Y_out_fold_t_R0[which(M_out_fold_t_R0==1)]))    \n    ny_t_R0 = length(y_t_R0) \n    F_t_R0_X_t_R0 <- NW_new(Xb=X_out_fold_t_R0_beta_t_R0, Y=Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                            xb=X_in_fold_t_R0_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                            kernel = kernel)\n    F_t_R0_X_t0_R0 <- NW_new(Xb=X_out_fold_t_R0_beta_t_R0, Y=Y_out_fold_t_R0[which(M_out_fold_t_R0==1)], \n                             xb=X_in_fold_t0_R0_beta_t_R0, y=y_t_R0, h=fit_t_R0_h$bandwidth, \n                             kernel = kernel)\n    \n    y_t_R1 = sort(unique(Y_out_fold_t_R1[which(M_out_fold_t_R1==1)]))    \n    ny_t_R1 = length(y_t_R1) \n    F_t_R1_X_R1 <- NW_new(Xb=X_out_fold_t_R1_beta_t_R1, Y=Y_out_fold_t_R1[which(M_out_fold_t_R1==1)], \n                          xb=X_in_fold_R1_beta_t_R1, y=y_t_R1, h=fit_t_R1_h$bandwidth, \n                          kernel = kernel)\n    \n    #fix up cases where CDF is improper by finding closest people with closest X'beta\n    i1 = which(apply(F_t_R0_X_t_R0==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_t_R0_beta_t_R0[i1], X_in_fold_t_R0_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R0_X_t_R0[i1, ] <- F_t_R0_X_t_R0[-i1, ,drop = FALSE][i1.closest, ]\n\n    i1 = which(apply(F_t_R0_X_t0_R0==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_t0_R0_beta_t_R0[i1], X_in_fold_t0_R0_beta_t_R0[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R0_X_t0_R0[i1, ] <- F_t_R0_X_t0_R0[-i1, ,drop = FALSE][i1.closest, ]\n\n    i1 = which(apply(F_t_R1_X_R1==0,1,prod)==1)\n    i1.closest <- apply(abs(outer(X_in_fold_R1_beta_t_R1[i1], X_in_fold_R1_beta_t_R1[-i1], FUN = \"-\")), 1, which.min)\n    F_t_R1_X_R1[i1, ] <- F_t_R1_X_R1[-i1, ,drop = FALSE][i1.closest, ]\n\n    #compute PDF\n    dF_t_R0_X_t_R0 <- F_t_R0_X_t_R0-cbind(rep(0, dim(F_t_R0_X_t_R0)[1]), F_t_R0_X_t_R0[,-ny_t_R0, drop = FALSE])\n    dF_t_R0_X_t0_R0 <- F_t_R0_X_t0_R0-cbind(rep(0, dim(F_t_R0_X_t0_R0)[1]), F_t_R0_X_t0_R0[,-ny_t_R0, drop = FALSE])\n    dF_t_R1_X_R1 <- F_t_R1_X_R1-cbind(rep(0, dim(F_t_R1_X_R1)[1]), F_t_R1_X_R1[,-ny_t_R1, drop = FALSE])\n    \n    ## conditional expectation of Y given R=0, T=t and X, for I(R=0, T=t)\n    mu_Y_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0+c(0, y_t_R0[-ny_t_R0]))/2)\n    \n    ## conditional expectation of Y given R=1, T=t and X, for I(R=1)\n    mu_Y_t_R1_X_R1 <- c(dF_t_R1_X_R1 %*% (y_t_R1+c(0, y_t_R1[-ny_t_R1]))/2)\n    \n    ## P(R=1)\n    prop.R1 <- mean(R_in_fold)\n    \n    ## vector_R1 and vector_R0\n    vector_R1 <- c(vector_R1, c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                rep(1/prop.R1, length(M_in_fold_R1))))\n    vector_R0 <- c(vector_R0, c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                rep(0, length(M_in_fold_R1))))\n    \n    ## Compute influence function for each gamma_t\n    for (g in 1:length(gamma)){\n      \n    ## conditional expectation of Y * exp given R=0, T=t and X, for I(R=0, T=t)\n    mu_Yexp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                     c(0, y_t_R0[-ny_t_R0])*exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n      \n    ## conditional expectation of exp given R=0, T=t and X, for I(R=0, T=t)\n    mu_exp_t_R0_X_t_R0 <- c(dF_t_R0_X_t_R0 %*% (exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                  exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## conditional expectation of Y * exp given R=0, T=t and X, for I(R=0, T=1-t)\n    mu_Yexp_t_R0_X_t0_R0 <- c(dF_t_R0_X_t0_R0 %*% (y_t_R0*exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                     c(0, y_t_R0[-ny_t_R0])*exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## conditional expectation of exp given R=0, T=t and X, for I(R=0, T=1-t)\n    mu_exp_t_R0_X_t0_R0 <- c(dF_t_R0_X_t0_R0 %*% (exp(gamma[g]*pnorm((y_t_R0-60)/25))+\n                                                    exp(gamma[g]*c(0, pnorm((y_t_R0-60)/25)[-ny_t_R0])))/2)\n    \n    ## IF+psi within each fold\n    if(trt==1){\n      if_temp <- c(M_in_fold_t_R0*eta_t_R0_weight*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                              (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                   M_in_fold_t0_R0*eta_t0_R0_weight*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                   M_in_fold_R1*eta_T_R1_weight*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n        c((1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0, \n          (1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0,\n          (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1)\n      if_temp_diff <- if_temp-pain_bq_temp\n      \n      if_R0_temp <- c(M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                                 (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                      M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                      rep(0, length(M_in_fold_R1)))+\n        c((1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0/(1-prop.R1), \n          (1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/(mu_exp_t_R0_X_t0_R0*(1-prop.R1)),\n          rep(0, length(M_in_fold_R1)))\n      if_R0_temp_diff <- if_R0_temp-pain_bq_R0_temp\n    }else{\n      if_temp <- c(M_in_fold_t0_R0*eta_t0_R0_weight*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                   M_in_fold_t_R0*eta_t_R0_weight*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                              (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                   M_in_fold_R1*eta_T_R1_weight*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n        c((1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0,\n          (1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0, \n          (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1)\n      if_temp_diff <- if_temp-pain_bq_temp\n      \n      if_R0_temp  <- c(M_in_fold_t0_R0*eta_t0_R0_weight/(1-prop.R1)*mu_Yexp_t_R0_X_t0_R0/mu_exp_t_R0_X_t0_R0, \n                         M_in_fold_t_R0*eta_t_R0_weight/(1-prop.R1)*(Y_in_fold_t_R0+(pi_R0_weight-1)*exp(gamma[g]*pnorm((Y_in_fold_t_R0-60)/25))/mu_exp_t_R0_X_t_R0*\n                                                    (Y_in_fold_t_R0-mu_Yexp_t_R0_X_t_R0/mu_exp_t_R0_X_t_R0)), \n                         rep(0, length(M_in_fold_R1)))+\n        c((1-M_in_fold_t0_R0*eta_t0_R0_weight)*mu_Yexp_t_R0_X_t0_R0/(mu_exp_t_R0_X_t0_R0*(1-prop.R1)),\n          (1-M_in_fold_t_R0*eta_t_R0_weight)*mu_Y_t_R0_X_t_R0/(1-prop.R1), \n          rep(0, length(M_in_fold_R1)))\n      if_R0_temp_diff <- if_R0_temp-pain_bq_R0_temp\n    }\n    \n    vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                             rep(0, length(M_in_fold_R1)))*mean(if_R0_temp)\n    vector_mean_R0_temp_diff <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                  rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_diff)\n    \n    if_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                    M_in_fold_R1*eta_T_R1_weight/prop.R1*(trt.ind_in_fold_R1*pi_R1_weight*(Y_in_fold_R1-mu_Y_t_R1_X_R1)+mu_Y_t_R1_X_R1))+\n      c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), (1-M_in_fold_R1*eta_T_R1_weight)*mu_Y_t_R1_X_R1/prop.R1)\n    if_R1_temp_diff <- if_R1_temp-pain_bq_R1_temp\n    \n    vector_mean_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                             rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp)\n    vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                  rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_diff)\n    \n    IF[[g]] <- c(IF[[g]], if_temp)\n    IF_R1[[g]] <- c(IF_R1[[g]], if_R1_temp)\n    IF_R0[[g]] <- c(IF_R0[[g]], if_R0_temp)\n    IF_diff[[g]] <- c(IF_diff[[g]], if_temp_diff)\n    IF_R1_diff[[g]] <- c(IF_R1_diff[[g]], if_R1_temp_diff)\n    IF_R0_diff[[g]] <- c(IF_R0_diff[[g]], if_R0_temp_diff)\n    \n    est_temp[k, g] <- mean(if_temp)\n    est_R1_temp[k, g] <- mean(if_R1_temp)\n    est_R0_temp[k, g] <- mean(if_R0_temp)\n    var_temp[k, g] <- sum((if_temp - mean(if_temp))^2)/(nk_in_fold-1)\n    var_R1_temp[k, g] <- sum((if_R1_temp - vector_mean_R1_temp)^2)/(nk_in_fold-1)\n    var_R0_temp[k, g] <- sum((if_R0_temp - vector_mean_R0_temp)^2)/(nk_in_fold-1)\n    est_temp_diff[k, g] <- mean(if_temp_diff)\n    est_R1_temp_diff[k, g] <- mean(if_R1_temp_diff)\n    est_R0_temp_diff[k, g] <- mean(if_R0_temp_diff)\n    var_temp_diff[k, g] <- sum((if_temp_diff - mean(if_temp_diff))^2)/(nk_in_fold-1)\n    var_R1_temp_diff[k, g] <- sum((if_R1_temp_diff - vector_mean_R1_temp_diff)^2)/(nk_in_fold-1)\n    var_R0_temp_diff[k, g] <- sum((if_R0_temp_diff - vector_mean_R0_temp_diff)^2)/(nk_in_fold-1)\n    \n    if(!simple_trunc){\n      \n      if (eq(max(abs(if_R1_temp)),z=if_R1_temp)>0) {\n        trunc <- max(abs(if_R1_temp))\n      } else {\n        trunc <- uniroot(eq, z=if_R1_temp, interval=c(0.01, max(abs(if_R1_temp))))$root\n      }\n      if_R1_temp_trunc <- pmin(abs(if_R1_temp),trunc) *  sign(if_R1_temp)\n      IF_R1_trunc[[g]] <- c(IF_R1_trunc[[g]], if_R1_temp_trunc)\n      \n      if (eq(max(abs(if_R1_temp_diff)),z=if_R1_temp_diff)>0) {\n        trunc <- max(abs(if_R1_temp_diff))\n      } else {\n        trunc <- uniroot(eq, z=if_R1_temp_diff, interval=c(0.01, max(abs(if_R1_temp_diff))))$root\n      }\n      if_R1_temp_trunc_diff <- pmin(abs(if_R1_temp_diff),trunc) * sign(if_R1_temp_diff)\n      IF_R1_trunc_diff[[g]] <- c(IF_R1_trunc_diff[[g]], if_R1_temp_trunc_diff)\n      \n      if (eq(max(abs(if_R0_temp)),z=if_R0_temp)>0) {\n        trunc <- max(abs(if_R0_temp))\n      } else {\n        trunc <- uniroot(eq, z=if_R0_temp, interval=c(0.01, max(abs(if_R0_temp))))$root\n      }\n      if_R0_temp_trunc <- pmin(abs(if_R0_temp),trunc) * sign(if_R0_temp)\n      IF_R0_trunc[[g]] <- c(IF_R0_trunc[[g]], if_R0_temp_trunc)\n      \n      if (eq(max(abs(if_R0_temp_diff)),z=if_R0_temp_diff)>0) {\n        trunc <- max(abs(if_R0_temp_diff))\n      } else {\n        trunc <- uniroot(eq, z=if_R0_temp_diff, interval=c(0.01, max(abs(if_R0_temp_diff))))$root\n      }\n      if_R0_temp_trunc_diff <- pmin(abs(if_R0_temp_diff),trunc) * sign(if_R0_temp_diff)\n      IF_R0_trunc_diff[[g]] <- c(IF_R0_trunc_diff[[g]], if_R0_temp_trunc_diff)\n      \n      if_temp_trunc <- if_R1_temp_trunc*prop.R1+if_R0_temp_trunc*(1-prop.R1)\n      IF_trunc[[g]] <- c(IF_trunc[[g]], if_temp_trunc)\n      if_temp_trunc_diff <- if_R1_temp_trunc_diff*prop.R1+if_R0_temp_trunc_diff*(1-prop.R1)\n      IF_trunc_diff[[g]] <- c(IF_trunc_diff[[g]], if_temp_trunc_diff)\n      \n      vector_mean_R0_temp <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                               rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_trunc)\n      vector_mean_R0_temp_diff <- c(rep(1/(1-prop.R1), length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)), \n                                    rep(0, length(M_in_fold_R1)))*mean(if_R0_temp_trunc_diff)\n      \n      vector_mean_R1_temp <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                               rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_trunc)\n      vector_mean_R1_temp_diff <- c(rep(0, length(M_in_fold_t_R0)+length(M_in_fold_t0_R0)),\n                                    rep(1/prop.R1, length(M_in_fold_R1)))*mean(if_R1_temp_trunc_diff)\n      # \n      est_temp_trunc[k, g] <- mean(if_temp_trunc)\n      est_R1_temp_trunc[k, g] <- mean(if_R1_temp_trunc)\n      est_R0_temp_trunc[k, g] <- mean(if_R0_temp_trunc)\n      var_temp_trunc[k, g] <- sum((if_temp_trunc - mean(if_temp_trunc))^2)/(nk_in_fold-1)\n      var_R1_temp_trunc[k, g] <- sum((if_R1_temp_trunc - vector_mean_R1_temp)^2)/(nk_in_fold-1)\n      var_R0_temp_trunc[k, g] <- sum((if_R0_temp_trunc - vector_mean_R0_temp)^2)/(nk_in_fold-1)\n      \n      est_temp_trunc_diff[k, g] <- mean(if_temp_trunc_diff)\n      est_R1_temp_trunc_diff[k, g] <- mean(if_R1_temp_trunc_diff)\n      est_R0_temp_trunc_diff[k, g] <- mean(if_R0_temp_trunc_diff)\n      var_temp_trunc_diff[k, g] <- sum((if_temp_trunc_diff - mean(if_temp_trunc_diff))^2)/(nk_in_fold-1)\n      var_R1_temp_trunc_diff[k, g] <- sum((if_R1_temp_trunc_diff - vector_mean_R1_temp_diff)^2)/(nk_in_fold-1)\n      var_R0_temp_trunc_diff[k, g] <- sum((if_R0_temp_trunc_diff - vector_mean_R0_temp_diff)^2)/(nk_in_fold-1)\n      \n    }\n    }\n  }\n  \n  ## output containers\n  r_est <- colMeans(est_temp)\n  r_est_R1 <- colMeans(est_R1_temp)\n  r_est_R0 <- colMeans(est_R0_temp)\n  r_var <- colSums(var_temp)/(fold*n)\n  r_var_R1 <- colSums(var_R1_temp)/(fold*n)\n  r_var_R0 <- colSums(var_R0_temp)/(fold*n)\n  r_lowerCI <- r_est-qnorm(0.975)*sqrt(r_var)\n  r_lowerCI_R1 <- r_est_R1-qnorm(0.975)*sqrt(r_var_R1)\n  r_lowerCI_R0 <- r_est_R0-qnorm(0.975)*sqrt(r_var_R0)\n  r_upperCI <- r_est+qnorm(0.975)*sqrt(r_var) \n  r_upperCI_R1 <- r_est_R1+qnorm(0.975)*sqrt(r_var_R1) \n  r_upperCI_R0 <- r_est_R0+qnorm(0.975)*sqrt(r_var_R0) \n  r_est_diff <- colMeans(est_temp_diff)\n  r_est_R1_diff <- colMeans(est_R1_temp_diff)\n  r_est_R0_diff <- colMeans(est_R0_temp_diff)\n  r_var_diff <- colSums(var_temp_diff)/(fold*n)\n  r_var_R1_diff <- colSums(var_R1_temp_diff)/(fold*n)\n  r_var_R0_diff <- colSums(var_R0_temp_diff)/(fold*n)\n  r_lowerCI_diff <- r_est_diff-qnorm(0.975)*sqrt(r_var_diff)\n  r_lowerCI_R1_diff <- r_est_R1_diff-qnorm(0.975)*sqrt(r_var_R1_diff)\n  r_lowerCI_R0_diff <- r_est_R0_diff-qnorm(0.975)*sqrt(r_var_R0_diff)\n  r_upperCI_diff <- r_est_diff+qnorm(0.975)*sqrt(r_var_diff) \n  r_upperCI_R1_diff <- r_est_R1_diff+qnorm(0.975)*sqrt(r_var_R1_diff) \n  r_upperCI_R0_diff <- r_est_R0_diff+qnorm(0.975)*sqrt(r_var_R0_diff)\n  if(!simple_trunc){\n    r_est_trunc <- colMeans(est_temp_trunc)\n    r_est_trunc_R1 <- colMeans(est_R1_temp_trunc)\n    r_est_trunc_R0 <- colMeans(est_R0_temp_trunc)\n    r_var_trunc <- colSums(var_temp_trunc)/(fold*n)\n    r_var_trunc_R1 <- colSums(var_R1_temp_trunc)/(fold*n)\n    r_var_trunc_R0 <- colSums(var_R0_temp_trunc)/(fold*n)\n    r_lowerCI_trunc <- r_est_trunc-qnorm(0.975)*sqrt(r_var_trunc)\n    r_lowerCI_trunc_R1 <- r_est_trunc_R1-qnorm(0.975)*sqrt(r_var_trunc_R1)\n    r_lowerCI_trunc_R0 <- r_est_trunc_R0-qnorm(0.975)*sqrt(r_var_trunc_R0)\n    r_upperCI_trunc <- r_est_trunc+qnorm(0.975)*sqrt(r_var_trunc) \n    r_upperCI_trunc_R1 <- r_est_trunc_R1+qnorm(0.975)*sqrt(r_var_trunc_R1) \n    r_upperCI_trunc_R0 <- r_est_trunc_R0+qnorm(0.975)*sqrt(r_var_trunc_R0) \n    r_est_trunc_diff <- colMeans(est_temp_trunc_diff)\n    r_est_trunc_R1_diff <- colMeans(est_R1_temp_trunc_diff)\n    r_est_trunc_R0_diff <- colMeans(est_R0_temp_trunc_diff)\n    r_var_trunc_diff <- colSums(var_temp_trunc_diff)/(fold*n)\n    r_var_trunc_R1_diff <- colSums(var_R1_temp_trunc_diff)/(fold*n)\n    r_var_trunc_R0_diff <- colSums(var_R0_temp_trunc_diff)/(fold*n)\n    r_lowerCI_trunc_diff <- r_est_trunc_diff-qnorm(0.975)*sqrt(r_var_trunc_diff)\n    r_lowerCI_trunc_R1_diff <- r_est_trunc_R1_diff-qnorm(0.975)*sqrt(r_var_trunc_R1_diff)\n    r_lowerCI_trunc_R0_diff <- r_est_trunc_R0_diff-qnorm(0.975)*sqrt(r_var_trunc_R0_diff)\n    r_upperCI_trunc_diff <- r_est_trunc_diff+qnorm(0.975)*sqrt(r_var_trunc_diff) \n    r_upperCI_trunc_R1_diff <- r_est_trunc_R1_diff+qnorm(0.975)*sqrt(r_var_trunc_R1_diff) \n    r_upperCI_trunc_R0_diff <- r_est_trunc_R0_diff+qnorm(0.975)*sqrt(r_var_trunc_R0_diff) \n\n  }\n  \n  ## another variance estimation & skewness & multiplier bootstrap: empty container\n  # r_var_2 <- r_var_R1_2 <- r_var_R0_2 <- c()\n  # r_var_diff_2 <- r_var_R1_diff_2 <- r_var_R0_diff_2 <- c()\n  # skew <- skew_R1 <- skew_R0 <- c()\n  # skew_diff <- skew_R1_diff <- skew_R0_diff <- c()\n  # if(!simple_trunc){\n  #   r_var_trunc_2 <- r_var_trunc_R1_2 <- r_var_trunc_R0_2 <- c()\n  #   r_var_trunc_diff_2 <- r_var_trunc_R1_diff_2 <- r_var_trunc_R0_diff_2 <- c()\n  #   skew_trunc <- skew_trunc_R1 <- skew_trunc_R0 <- c()\n  #   skew_trunc_diff <- skew_trunc_R1_diff <- skew_trunc_R0_diff <- c()\n  #   \n  #   B <- 2000\n  #   q <- q_R1 <- q_R0 <- c()\n  #   q_diff <- q_R1_diff <- q_R0_diff <- c()\n  # }\n\n  ## another variance estimation & skewness & multiplier bootstrap\n  # for (g in 1:length(gamma)){\n  #   \n  #   r_var_2 <- c(r_var_2, sum((IF[[g]]-mean(IF[[g]]))^2)/(n*(n-1)))\n  #   r_var_R1_2 <- c(r_var_R1_2, sum((IF_R1[[g]]-vector_R1*mean(IF_R1[[g]]))^2)/(n*(n-1)))\n  #   r_var_R0_2 <- c(r_var_R0_2, sum((IF_R0[[g]]-vector_R0*mean(IF_R0[[g]]))^2)/(n*(n-1)))\n  #   r_var_diff_2 <- c(r_var_diff_2, sum((IF_diff[[g]]-mean(IF_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_R1_diff_2 <- c(r_var_R1_diff_2, sum((IF_R1_diff[[g]]-vector_R1*mean(IF_R1_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_R0_diff_2 <- c(r_var_R0_diff_2, sum((IF_R0_diff[[g]]-vector_R0*mean(IF_R0_diff[[g]]))^2)/(n*(n-1)))\n  #   \n  #   skew <- c(skew, mean(IF[[g]]^3)/(mean(IF[[g]]^2)^(3/2)))\n  #   skew_R1 <- c(skew_R1, mean(IF_R1[[g]]^3)/(mean(IF_R1[[g]]^2)^(3/2)))\n  #   skew_R0 <- c(skew_R0, mean(IF_R0[[g]]^3)/(mean(IF_R0[[g]]^2)^(3/2)))\n  #   skew_diff <- c(skew_diff, mean(IF_diff[[g]]^3)/(mean(IF_diff[[g]]^2)^(3/2)))\n  #   skew_R1_diff <- c(skew_R1_diff, mean(IF_R1_diff[[g]]^3)/(mean(IF_R1_diff[[g]]^2)^(3/2)))\n  #   skew_R0_diff <- c(skew_R0_diff, mean(IF_R0_diff[[g]]^3)/(mean(IF_R0_diff[[g]]^2)^(3/2)))\n  #   \n  #   if(!simple_trunc){\n  #     \n  #   r_var_trunc_2 <- c(r_var_trunc_2, sum((IF_trunc[[g]]-mean(IF_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R1_2 <- c(r_var_trunc_R1_2, sum((IF_R1_trunc[[g]]-vector_R1*mean(IF_R1_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R0_2 <- c(r_var_trunc_R0_2, sum((IF_R0_trunc[[g]]-vector_R0*mean(IF_R0_trunc[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_diff_2 <- c(r_var_trunc_diff_2, sum((IF_trunc_diff[[g]]-mean(IF_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R1_diff_2 <- c(r_var_trunc_R1_diff_2, sum((IF_R1_trunc_diff[[g]]-vector_R1*mean(IF_R1_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   r_var_trunc_R0_diff_2 <- c(r_var_trunc_R0_diff_2, sum((IF_R0_trunc_diff[[g]]-vector_R0*mean(IF_R0_trunc_diff[[g]]))^2)/(n*(n-1)))\n  #   \n  #   skew_trunc <- c(skew_trunc, mean(IF_trunc[[g]]^3)/(mean(IF_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_R1 <- c(skew_trunc_R1, mean(IF_R1_trunc[[g]]^3)/(mean(IF_R1_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_R0 <- c(skew_trunc_R0, mean(IF_R0_trunc[[g]]^3)/(mean(IF_R0_trunc[[g]]^2)^(3/2)))\n  #   skew_trunc_diff <- c(skew_trunc_diff, mean(IF_trunc_diff[[g]]^3)/(mean(IF_trunc_diff[[g]]^2)^(3/2)))\n  #   skew_trunc_R1_diff <- c(skew_trunc_R1_diff, mean(IF_R1_trunc_diff[[g]]^3)/(mean(IF_R1_trunc_diff[[g]]^2)^(3/2)))\n  #   skew_trunc_R0_diff <- c(skew_trunc_R0_diff, mean(IF_R0_trunc_diff[[g]]^3)/(mean(IF_R0_trunc_diff[[g]]^2)^(3/2)))\n  #   \n  #   wi <- matrix(sample(c(-1, 1), n*B, replace=TRUE), nrow=B, ncol=n)\n  #   est_star <- r_est_trunc[g]+rowMeans(wi*(IF_trunc[[g]]-mean(IF[[g]])))\n  #   est_R1_star <- r_est_trunc_R1[g]+rowMeans(wi*(IF_R1_trunc[[g]]-vector_R1*mean(IF_R1_trunc[[g]])))\n  #   est_R0_star <- r_est_trunc_R0[g]+rowMeans(wi*(IF_R0_trunc[[g]]-vector_R0*mean(IF_R0_trunc[[g]])))\n  #   est_diff_star <- r_est_trunc_diff[g]+rowMeans(wi*(IF_trunc_diff[[g]]-mean(IF_trunc_diff[[g]])))\n  #   est_R1_diff_star <- r_est_trunc_R1_diff[g]+rowMeans(wi*(IF_R1_trunc_diff[[g]]-vector_R1*mean(IF_R1_trunc_diff[[g]])))\n  #   est_R0_diff_star <- r_est_trunc_R0_diff[g]+rowMeans(wi*(IF_R0_trunc_diff[[g]]-vector_R0*mean(IF_R0_trunc_diff[[g]])))\n  #   \n  #   t_star <- (est_star-r_est_trunc[g])/sqrt(r_var_trunc[g])\n  #   t_R1_star <- (est_R1_star-r_est_trunc_R1[g])/sqrt(r_var_trunc_R1[g])\n  #   t_R0_star <- (est_R0_star-r_est_trunc_R0[g])/sqrt(r_var_trunc_R0[g])\n  #   t_diff_star <- (est_diff_star-r_est_trunc_diff[g])/sqrt(r_var_trunc_diff[g])\n  #   t_R1_diff_star <- (est_R1_diff_star-r_est_trunc_R1_diff[g])/sqrt(r_var_trunc_R1_diff[g])\n  #   t_R0_diff_star <- (est_R0_diff_star-r_est_trunc_R0_diff[g])/sqrt(r_var_trunc_R0_diff[g])\n  #   \n  #   q <- c(q, quantile(abs(t_star), 1-0.05))\n  #   q_R1 <- c(q_R1, quantile(abs(t_R1_star), 1-0.05))\n  #   q_R0 <- c(q_R0, quantile(abs(t_R0_star), 1-0.05))\n  #   q_diff <- c(q_diff, quantile(abs(t_diff_star), 1-0.05))\n  #   q_R1_diff <- c(q_R1_diff, quantile(abs(t_R1_diff_star), 1-0.05))\n  #   q_R0_diff <- c(q_R0_diff, quantile(abs(t_R0_diff_star), 1-0.05))\n  #   \n  #   }\n  # }\n  \n  ## one-step jackknife\n  # jack_est_trunc <- c()\n  # jack_est_trunc_R0 <- c()\n  # jack_est_trunc_R1 <- c()\n  # for (g in 1:length(gamma)){\n  #   jack_est_trunc <- cbind(jack_est_trunc, r_est_trunc[g]-IF_trunc[[g]]/(n-1))\n  #   jack_est_trunc_R0 <- cbind(jack_est_trunc_R0, r_est_trunc_R0[g]-IF_R0_trunc[[g]]/(n-1))\n  #   jack_est_trunc_R1 <- cbind(jack_est_trunc_R1, r_est_trunc_R1[g]-IF_R1_trunc[[g]]/(n-1))\n  # }\n  # jack_var_trunc <- (n-1)/n*colSums((jack_est_trunc-matrix(colMeans(jack_est_trunc), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # jack_var_trunc_R0 <- (n-1)/n*colSums((jack_est_trunc_R0-matrix(colMeans(jack_est_trunc_R0), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # jack_var_trunc_R1 <- (n-1)/n*colSums((jack_est_trunc_R1-matrix(colMeans(jack_est_trunc_R1), nrow=n, ncol=length(gamma), byrow=T))^2)\n  # \n  ## output final results\n  if(IF_output){\n    if(simple_trunc){\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0, \n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0, \n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0, \n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff, \n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff, \n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     IF=IF, IF_R1=IF_R1, IF_R0=IF_R0, \n                     IF_diff=IF_diff, IF_R1_diff=IF_R1_diff, IF_R0_diff=IF_R0_diff, \n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1, \n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n    }else{\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     est_mat=est_temp, est_R1_mat=est_R1_temp, est_R0_mat=est_R0_temp, \n                     est_trunc=r_est_trunc, est_trunc_R1=r_est_trunc_R1, est_trunc_R0=r_est_trunc_R0,\n                     est_trunc_mat=est_temp_trunc, est_trunc_R1_mat=est_R1_temp_trunc, est_trunc_R0_mat=est_R0_temp_trunc, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0,\n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     var_trunc=r_var_trunc, var_trunc_R1=r_var_trunc_R1, var_trunc_R0=r_var_trunc_R0,\n                     # var_trunc_2=r_var_trunc_2, var_trunc_R1_2=r_var_trunc_R1_2, var_trunc_R0_2=r_var_trunc_R0_2, \n                     # skew_trunc=skew_trunc, skew_trunc_R1=skew_trunc_R1, skew_trunc_R0=skew_trunc_R0,\n                     # jack_var_trunc=jack_var_trunc, jack_var_trunc_R0=jack_var_trunc_R0, jack_var_trunc_R1=jack_var_trunc_R1, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0,\n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0,\n                     lowerCI_trunc=r_lowerCI_trunc, lowerCI_trunc_R1=r_lowerCI_trunc_R1, lowerCI_trunc_R0=r_lowerCI_trunc_R0,\n                     upperCI_trunc=r_upperCI_trunc, upperCI_trunc_R1=r_upperCI_trunc_R1, upperCI_trunc_R0=r_upperCI_trunc_R0,\n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff,\n                     est_diff_mat=est_temp_diff, est_R1_diff_mat=est_R1_temp_diff, est_R0_diff_mat=est_R0_temp_diff, \n                     est_trunc_diff=r_est_trunc_diff, est_trunc_R1_diff=r_est_trunc_R1_diff, est_trunc_R0_diff=r_est_trunc_R0_diff,\n                     est_trunc_diff_mat=est_temp_trunc_diff, est_R1_trunc_diff_mat=est_R1_temp_trunc_diff, est_R0_trunc_diff_mat=est_R0_temp_trunc_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff,\n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     var_trunc_diff=r_var_trunc_diff, var_trunc_R1_diff=r_var_trunc_R1_diff, var_trunc_R0_diff=r_var_trunc_R0_diff,\n                     # var_trunc_diff_2=r_var_trunc_diff_2, var_trunc_R1_diff_2=r_var_trunc_R1_diff_2, var_trunc_R0_diff_2=r_var_trunc_R0_diff_2, \n                     # skew_trunc_diff=skew_trunc_diff, skew_trunc_R1_diff=skew_trunc_R1_diff, skew_trunc_R0_diff=skew_trunc_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff,\n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     lowerCI_trunc_diff=r_lowerCI_trunc_diff, lowerCI_trunc_R1_diff=r_lowerCI_trunc_R1_diff, lowerCI_trunc_R0_diff=r_lowerCI_trunc_R0_diff, \n                     upperCI_trunc_diff=r_upperCI_trunc_diff, upperCI_trunc_R1_diff=r_upperCI_trunc_R1_diff, upperCI_trunc_R0_diff=r_upperCI_trunc_R0_diff, \n                     IF=IF, IF_R1=IF_R1, IF_R0=IF_R0,\n                     IF_trunc=IF_trunc, IF_trunc_R1=IF_R1_trunc, IF_trunc_R0=IF_R0_trunc,\n                     IF_diff=IF_diff, IF_R1_diff=IF_R1_diff, IF_R0_diff=IF_R0_diff,\n                     IF_trunc_diff=IF_trunc_diff, IF_trunc_R1_diff=IF_R1_trunc_diff, IF_trunc_R0_diff=IF_R0_trunc_diff,\n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1,\n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n                     # q=q, q_R1=q_R1, q_R0=q_R0, q_diff=q_diff, q_R1_diff=q_R1_diff, q_R0_diff=q_R0_diff)\n    }\n  }else{\n    if(simple_trunc){\n      result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0, \n                     var=r_var, var_R1=r_var_R1, var_R0=r_var_R0, \n                     # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                     # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                     lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0, \n                     upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0, \n                     est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff, \n                     var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff, \n                     # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                     # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                     lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff, \n                     upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff, \n                     pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1, \n                     pain_bq_reordered_R0=pain_bq_reordered_R0, \n                     id_list=id_list)\n    }else{\n        result <- list(est=r_est, est_R1=r_est_R1, est_R0=r_est_R0,\n                       est_mat=est_temp, est_R1_mat=est_R1_temp, est_R0_mat=est_R0_temp, \n                       est_trunc=r_est_trunc, est_trunc_R1=r_est_trunc_R1, est_trunc_R0=r_est_trunc_R0,\n                       est_trunc_mat=est_temp_trunc, est_trunc_R1_mat=est_R1_temp_trunc, est_trunc_R0_mat=est_R0_temp_trunc, \n                       var=r_var, var_R1=r_var_R1, var_R0=r_var_R0,\n                       # var_2=r_var_2, var_R1_2=r_var_R1_2, var_R0_2=r_var_R0_2, \n                       # skew=skew, skew_R1=skew_R1, skew_R0=skew_R0, \n                       var_trunc=r_var_trunc, var_trunc_R1=r_var_trunc_R1, var_trunc_R0=r_var_trunc_R0,\n                       # var_trunc_2=r_var_trunc_2, var_trunc_R1_2=r_var_trunc_R1_2, var_trunc_R0_2=r_var_trunc_R0_2, \n                       # skew_trunc=skew_trunc, skew_trunc_R1=skew_trunc_R1, skew_trunc_R0=skew_trunc_R0,\n                       # jack_var_trunc=jack_var_trunc, jack_var_trunc_R0=jack_var_trunc_R0, jack_var_trunc_R1=jack_var_trunc_R1, \n                       lowerCI=r_lowerCI, lowerCI_R1=r_lowerCI_R1, lowerCI_R0=r_lowerCI_R0,\n                       upperCI=r_upperCI, upperCI_R1=r_upperCI_R1, upperCI_R0=r_upperCI_R0,\n                       lowerCI_trunc=r_lowerCI_trunc, lowerCI_trunc_R1=r_lowerCI_trunc_R1, lowerCI_trunc_R0=r_lowerCI_trunc_R0,\n                       upperCI_trunc=r_upperCI_trunc, upperCI_trunc_R1=r_upperCI_trunc_R1, upperCI_trunc_R0=r_upperCI_trunc_R0,\n                       est_diff=r_est_diff, est_R1_diff=r_est_R1_diff, est_R0_diff=r_est_R0_diff,\n                       est_diff_mat=est_temp_diff, est_R1_diff_mat=est_R1_temp_diff, est_R0_diff_mat=est_R0_temp_diff, \n                       est_trunc_diff=r_est_trunc_diff, est_trunc_R1_diff=r_est_trunc_R1_diff, est_trunc_R0_diff=r_est_trunc_R0_diff,\n                       est_trunc_diff_mat=est_temp_trunc_diff, est_R1_trunc_diff_mat=est_R1_temp_trunc_diff, est_R0_trunc_diff_mat=est_R0_temp_trunc_diff, \n                       var_diff=r_var_diff, var_R1_diff=r_var_R1_diff, var_R0_diff=r_var_R0_diff,\n                       # var_diff_2=r_var_diff_2, var_R1_diff_2=r_var_R1_diff_2, var_R0_diff_2=r_var_R0_diff_2, \n                       # skew_diff=skew_diff, skew_R1_diff=skew_R1_diff, skew_R0_diff=skew_R0_diff, \n                       var_trunc_diff=r_var_trunc_diff, var_trunc_R1_diff=r_var_trunc_R1_diff, var_trunc_R0_diff=r_var_trunc_R0_diff,\n                       # var_trunc_diff_2=r_var_trunc_diff_2, var_trunc_R1_diff_2=r_var_trunc_R1_diff_2, var_trunc_R0_diff_2=r_var_trunc_R0_diff_2, \n                       # skew_trunc_diff=skew_trunc_diff, skew_trunc_R1_diff=skew_trunc_R1_diff, skew_trunc_R0_diff=skew_trunc_R0_diff, \n                       lowerCI_diff=r_lowerCI_diff, lowerCI_R1_diff=r_lowerCI_R1_diff, lowerCI_R0_diff=r_lowerCI_R0_diff,\n                       upperCI_diff=r_upperCI_diff, upperCI_R1_diff=r_upperCI_R1_diff, upperCI_R0_diff=r_upperCI_R0_diff,\n                       lowerCI_trunc_diff=r_lowerCI_trunc_diff, lowerCI_trunc_R1_diff=r_lowerCI_trunc_R1_diff, lowerCI_trunc_R0_diff=r_lowerCI_trunc_R0_diff,\n                       upperCI_trunc_diff=r_upperCI_trunc_diff, upperCI_trunc_R1_diff=r_upperCI_trunc_R1_diff, upperCI_trunc_R0_diff=r_upperCI_trunc_R0_diff,\n                       pain_bq_reordered=pain_bq_reordered, pain_bq_reordered_R1=pain_bq_reordered_R1,\n                       pain_bq_reordered_R0=pain_bq_reordered_R0,\n                       id_list=id_list)\n                       # q=q, q_R1=q_R1, q_R0=q_R0, q_diff=q_diff, q_R1_diff=q_R1_diff, q_R0_diff=q_R0_diff)\n    }\n  }\n  \n}\n\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/est_s_t_y.R"},{"filename":"/singleindexmodelfunctions.R","content":"# single index model's function\n\n# return the initial value for beta\ncumuSIR <- function(X, Y, eps = 1e-7){\n  X <- as.matrix(X)\n  Y <- as.matrix(Y)\n  \n  number_n <- dim(X)[1]\n  number_p <- dim(X)[2]\n  \n  Y.CP <- matrix(\n    Y[rep(1:number_n, times = number_n), ]<=\n      Y[rep(1:number_n, each = number_n), ],\n    nrow = number_n, ncol = number_n\n  )\n  \n  # centralizing covariates\n  X.cs <- t(t(X)-colMeans(X))\n  \n  # calculating m(y)=\\E[X_i 1(Y_i\\leq y)]\n  m.y <- t(X.cs) %*% Y.CP/number_n\n  # calculating K=\\E[m(Y_i)m(Y_i)^T]\n  Km <- m.y %*% t(m.y)/number_n\n  \n  Bhat <- eigen(solve(var(X) + eps*diag(number_p), Km))$vectors[, 1]\n  \n  return(Bhat)\n}\n\n\n# find the optimal bandwidth, default set for kernel is \nSIDRnew_h2 <- function(X, Y,\n                       Y.CP = NULL,\n                       beta = NULL,\n                       kernel = \"K2_Biweight\",\n                       method = \"optim\",\n                       optim_method = \"BFGS\",\n                       abs.tol = 1e-4,\n                       initial_bandwidth = NULL,\n                       wi.boot = NULL, penalty=0)\n{\n  X <- as.matrix(X)\n  Y <- as.matrix(Y)\n  \n  number_n <- dim(X)[1]\n  number_p <- dim(X)[2]\n  \n  if (is.null(beta))\n  {\n    beta <- c(1, rep(0, number_p-1))\n  }else\n  {\n    beta <- as.vector(beta)\n    beta <- beta/beta[1]\n  }\n  \n  if (is.null(initial_bandwidth))\n  {\n    if (kernel==\"K2_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)\n          b <- beta\n          h <- exp(parameter)\n          xb <- c(X%*%b) \n          y <- Y\n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(xb-xb[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2+penalty*h)\n        }\n        \n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                  h = h))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K2_Biweight kernel.\")\n      }\n    }else if (kernel == \"dnorm\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) dnorm(x/h, 0, 1)\n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = h))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        # wi.boot <- as.vector(wi.boot)\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = h, w = wi.boot))^2)\n        #   return(cv)\n        # }\n        stop(\"There's no weighted version of the dnorm kernel.\")\n      }\n    }else if (kernel==\"K4_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.bh <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   h <- exp(parameter[number_p])\n        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                            h = h), 0), 1))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K4_Biweight kernel.\")\n      }\n    }\n    \n    if(method == \"nlminb\")\n    {\n      esti <- nlminb(start = 0, \n                     objective = Eij3,\n                     control = list(abs.tol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }else if (method == \"optim\")\n    {\n      # the new optimize function using optim, you can change the lower and upper\n      esti <- optim(par = 0, \n                    fn = Eij3,\n                    method = optim_method,\n                    control = list(abstol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }\n    else if (method == \"optimize\")\n    {\n      #   # esti <- nmk(par = 0, \n      #   #             fn = Eij3,\n      #   #             control = list(tol = abs.tol))\n      esti <- optimize(Eij3,\n                       interval = c(-10, 10))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$minimum),\n                      details = esti)\n    }\n    \n  }else\n  {\n    if (kernel==\"K2_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)\n          b <- beta\n          h <- exp(parameter)\n          xb <- c(X%*%b) \n          y <- Y\n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(xb-xb[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2+penalty*h)\n        }\n        \n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                  h = bandwidth))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K2_Biweight kernel.\")\n      }\n    }else if (kernel==\"dnorm\") \n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) dnorm(x/h,0,1) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        \n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = bandwidth))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        # wi.boot <- as.vector(wi.boot)\n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,\n        #                                    h = bandwidth, w = wi.boot))^2)\n        #   return(cv)\n        # }\n        stop(\"There's no weighted version of the dnorm kernel.\")\n      }\n    }else if (kernel==\"K4_Biweight\")\n    {\n      if (is.null(wi.boot))\n      {\n        Eij3 <- function(parameter){\n          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) \n          \n          b <- beta\n          h <- exp(parameter)\n          \n          x <- c(X%*%b) \n          y <- Y\n          \n          n <- length(y)\n          yo <- order(y)\n          ys <- y[yo]\n          uy <- rle(ys)[[1]]\n          cols <- cumsum(uy)\n          ei <- rep(0, n)\n          for (i in 1:n){\n            Kih <- K(x-x[i],h=h)\n            Kih[i] <- 0\n            denom <- sum(Kih)\n            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)\n          }\n          return(sum(ei)/n^2)\n        }\n        # cv.b <- function(parameter)\n        # {\n        #   b <- c(1, parameter[1:(number_p-1)])\n        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,\n        #                                            h = bandwidth), 0), 1))^2)\n        #   return(cv)\n        # }\n      }else\n      {\n        stop(\"There's no weighted version of the K4_Biweight kernel.\")\n      }\n    }\n    \n    if(method == \"nlminb\")\n    {\n      esti <- nlminb(start = initial_bandwidth, \n                     objective = Eij3,\n                     control = list(abs.tol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }else if (method == \"optim\")\n    {\n      # the new optimize function using optim, you can change the lower and upper\n      esti <- optim(par = initial_bandwidth, \n                    fn = Eij3,\n                    method = optim_method,\n                    control = list(abstol = abs.tol))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$par),\n                      details = esti)\n    }\n    else if (method == \"optimize\")\n    {\n      #   # esti <- nmk(par = initial_bandwidth, \n      #   #             fn = Eij3,\n      #   #             control = list(tol = abs.tol))\n      esti <- optimize(Eij3,\n                       interval = c(-10, 10))\n      results <- list(coef = beta,\n                      bandwidth = exp(esti$minimum),\n                      details = esti)\n      \n    }\n  }\n  \n  return(results)\n}\n\n\n# return the prediction using \"K2_Biweight\" kernel\nNW_new <- function(Xb, Y, xb, y, h, kernel = \"K2_Biweight\"){\n  \n  if(kernel == \"dnorm\"){\n    K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian \n  } else if(kernel == \"K2_Biweight\"){\n    K <- function(x, h){15/16*(1-(x/h)^2)^2 * (abs(x) <= h)} # K2_Biweight\n  } else if(kernel==\"K4_Biweight\"){\n    K <- function(x, h){105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) }# K4_Biweight\n  }\n  \n  Kxb <- sapply(xb, function(x, Xb) K(Xb-x, h), Xb=Xb)\n  \n  Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)\n  \n  denom <- colSums(Kxb)\n  \n  fyxb <- (denom!=0)*crossprod(Kxb, Ylty)/(denom + (denom==0))\n  \n  return(fyxb)\n  \n}\n\n","normpath":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/singleindexmodelfunctions.R"}],"prof_output":"/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/Comprehensive_cohort_final/.Rproj.user/8F38D36A/profiles-cache/file3da7fa9291d.Rprof","highlight":{"output":["^output\\$"],"gc":["^<GC>$"],"stacktrace":["^\\.\\.stacktraceo(n|ff)\\.\\.$"]},"split":"h"}},"evals":[],"jsHooks":[]}</script>
+<script type="application/htmlwidget-sizing" data-for="htmlwidget-fe773d8b3d0235254c42">{"viewer":{"width":450,"height":350,"padding":0,"fill":true},"browser":{"width":960,"height":500,"padding":0,"fill":true}}</script>
+</body>
+</html>
diff --git a/simulation_est_slurm_double_pboot.R b/simulation_est_slurm_double_pboot.R
index 2db2c7a..71e380f 100644
--- a/simulation_est_slurm_double_pboot.R
+++ b/simulation_est_slurm_double_pboot.R
@@ -1,46 +1,20 @@
-indx <- as.numeric(commandArgs(trailingOnly=TRUE))
-
-scenarios <- expand.grid(sim.size_list=500, index=1:50, imputed=1, 
-                         kernel="dnorm", method="optim", 
-                         single_index_method="norm1coef")
-scenarios <- scenarios[order(scenarios$sim.size_list),]
-
-
-sim.size <- scenarios$sim.size_list[indx]
-index <- scenarios$index[indx]
-imputed <- scenarios$imputed[indx]
-kernel <- as.character(scenarios$kernel[indx])
-method <- as.character(scenarios$method[indx])
-single_index_method <- as.character(scenarios$single_index_method[indx])
-
 ###################
 ## load packages ##
 ###################
 library(tidyverse)
 library(splines)
 library(gridExtra)
-library(parallel)
-library(foreach)
-library(doParallel)
-
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/HelperFunction.R")
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/singleindexmodelfunctions.R")
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/est_s_t_y.R")
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SIDR_Ravinew.R")
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SIDRnew.R")
-source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SensIAT_sim_outcome_modeler_mave.R")
+library(profvis)
 
-ntasks <- Sys.getenv("SLURM_NTASKS")
-if (ntasks == '') {
-  ntasks <- 4
-} else {
-  ntasks <- strtoi(ntasks) }
-cat("This script use ", ntasks, " cores\n")
+source(paste0(getwd(), "/HelperFunction.R"))
+source(paste0(getwd(), "/singleindexmodelfunctions.R"))
+source(paste0(getwd(), "/est_s_t_y.R"))
+source(paste0(getwd(), "/SIDR_Ravinew.R"))
+source(paste0(getwd(), "/SIDRnew.R"))
+source(paste0(getwd(), "/SensIAT_sim_outcome_modeler_mave.R"))
 
-package_list <- c("splines", "tidyverse", "gridExtra")
-
-nboot_B <- 500
-nboot_C <- 100
+nboot_B <- 2
+nboot_C <- 5
 grid <- expand.grid(b = 1:nboot_B, c = 1:nboot_C)
 
 gamma_length <- length(seq(-5, 5, by=1))
@@ -49,45 +23,62 @@ gamma_length <- length(seq(-5, 5, by=1))
 ## simulation ##
 ################
 
-## parametric bootstrap
+pv <- profvis({
 
-cl <- makeCluster(ntasks)
-registerDoParallel(cl)
+## empty containers
+Boot.Est <- matrix(NA, nrow=nrow(grid), ncol=264)
 
-for (j in (40*(index-1)+1):(40*index)){
-  
-  set.seed(1000090+j)
-  seed_B <- sample(1:10000000, size=nboot_B)
+## parametric bootstrap
+load("/Users/shiyaoxu/Documents/2025_2026/research/comprehensive_cohort/simData/imputed1/n500/sim1.rds")
+X_sim = data.frame(dplyr::select(data, c(age, pain_bq, expectationb, ChronicPainb)))
+
+for(i in 1:nboot_B){
   
-  load(paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simData/imputed", imputed, "/n", sim.size, "/sim", j, ".rds"))
-  X_sim = data.frame(dplyr::select(data, c(age, pain_bq, expectationb, ChronicPainb)))
+  boot_b_temp <- pboot(data=data, X_sim=X_sim, sim.size=500, seed=NULL)
+  data.new <- boot_b_temp$data.new
+  X.new <- data.frame(dplyr::select(data.new, c(age, pain_bq, expectationb, ChronicPainb)))
+  topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1, coef_g.fit=boot_b_temp$coef_g.fit, 
+                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, 
+                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)
+  oral_vals    <- fit_one(data=data.new, X=X.new, trt_val=0, coef_g.fit=boot_b_temp$coef_g.fit, 
+                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, 
+                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)
+  Boot.Est[which(grid$b==i&grid$c==1), ] <- c(topical_vals, oral_vals)
   
-Boot.Est <- foreach(i=1:nrow(grid), .combine=rbind, .packages=package_list, .errorhandling = "pass") %dopar% {
+  boot_b_fit <- pboot_model(data=data.new, X_sim=X.new)
+  coef_g.fit <- coef(boot_b_fit$g.fit)
+  coef_t_R0.fit <- coef(boot_b_fit$t_R0.fit)
+  coef_t_R1.fit <- coef(boot_b_fit$t_R1.fit)
+  coef_M_R0.fit <- coef(boot_b_fit$M_R0.fit)
+  coef_M_R1.fit <- coef(boot_b_fit$M_R1.fit)
   
-  ## simulate outer bootstrap sample
-  data.new <- pboot(data=data, X_sim=X_sim, sim.size=sim.size, seed=seed_B[grid$b[i]])
-  X.new <- data.frame(dplyr::select(data.new, c(age, pain_bq, expectationb, ChronicPainb)))
-  if(grid$c[i]==1){
-    ## outer estimator
-    topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1)
-    oral_vals    <- fit_one(data=data.new, X=X.new, trt_val=0)
-  }else{
-    topical_vals <- rep(NA_real_, 6*gamma_length)
-    oral_vals <- rep(NA_real_, 6*gamma_length)
+  for(j in 1:nboot_C){
+    
+    data.new2 <- pboot_sim(data=data.new, X_sim=X.new, sim.size=500, seed=NULL, 
+                             fit_t_R0_h=boot_b_fit$fit_t_R0_h, fit_t_R1_h=boot_b_fit$fit_t_R1_h, 
+                             fit_t0_R0_h=boot_b_fit$fit_t0_R0_h, fit_t0_R1_h=boot_b_fit$fit_t0_R1_h, 
+                             g.fit=boot_b_fit$g.fit, t_R0.fit=boot_b_fit$t_R0.fit, M_R0.fit=boot_b_fit$M_R0.fit, 
+                             M_R1.fit=boot_b_fit$M_R1.fit)
+    X.new2 <- data.frame(dplyr::select(data.new2, c(age, pain_bq, expectationb, ChronicPainb)))
+    ## inner estimator
+    temp_topical <- fit_one(data=data.new2, X=X.new2, trt_val=1, coef_g.fit=coef_g.fit, 
+                            coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,
+                            coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)
+    temp_oral <- fit_one(data=data.new2, X=X.new2, trt_val=0, coef_g.fit=coef_g.fit, 
+                         coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,
+                         coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)
+    Boot.Est[which(grid$b==i&grid$c==j), 133:264] <- c(temp_topical, temp_oral)
+    
   }
-
-  ## simulate inner bootstrap sample
-  data.new2 <- pboot(data=data.new, X_sim=X.new, sim.size=sim.size, seed=NULL)
-  X.new2 <- data.frame(dplyr::select(data.new2, c(age, pain_bq, expectationb, ChronicPainb)))
-  ## inner estimator
-  temp_topical <- fit_one(data=data.new2, X=X.new2, trt_val=1)
-  temp_oral <- fit_one(data=data.new2, X=X.new2, trt_val=0)
   
-  ## return result
-  c(topical_vals, oral_vals, temp_topical, temp_oral)
+  print(i)
   
 }
 
+})
+
+htmlwidgets::saveWidget(pv, "profvis_initial_coef.html")
+  
 load(paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simResult/imputed", imputed, "/n", sim.size, "/", kernel, "_", single_index_method, "_fold5/sim", j, ".RData"))
 Q_b_topical <- sapply(1:nboot_B, function(x){
   loc <- which(grid$b==x)
@@ -326,27 +317,6 @@ var_R0_oral_boot <- sapply(1:nboot_B, function(x){
   Boot.Est[loc_b, 122:132]
 })
 
-## bootstrap result
-save(est_topical_boot, est_R1_topical_boot, est_R0_topical_boot, 
-     est_oral_boot, est_R1_oral_boot, est_R0_oral_boot, 
-     var_topical_boot, var_R1_topical_boot, var_R0_topical_boot, 
-     var_oral_boot, var_R1_oral_boot, var_R0_oral_boot, 
-     Q_b_topical, Q_b_R1_topical, Q_b_R0_topical, 
-     Q_b_oral, Q_b_R1_oral, Q_b_R0_oral, 
-     t_b_topical, t_b_R1_topical, t_b_R0_topical, 
-     t_b_oral, t_b_R1_oral, t_b_R0_oral, 
-     Q_t_b_topical, Q_t_b_R1_topical, Q_t_b_R0_topical, 
-     Q_t_b_oral, Q_t_b_R1_oral, Q_t_b_R0_oral, 
-     abs_Q_t_b_topical, abs_Q_t_b_R1_topical, abs_Q_t_b_R0_topical, 
-     abs_Q_t_b_oral, abs_Q_t_b_R1_oral, abs_Q_t_b_R0_oral, 
-     t_b_sd_topical, t_b_R1_sd_topical, t_b_R0_sd_topical, 
-     t_b_sd_oral, t_b_R1_sd_oral, t_b_R0_sd_oral,
-     file=paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simResult/imputed", imputed, "/double_pboot_n", sim.size, "/", kernel, "_", single_index_method, "/sim", j, ".RData"))
-  print(j)
-  
-}
-
-stopCluster(cl)
 
 
 
diff --git a/simulation_est_slurm_double_pboot2.R b/simulation_est_slurm_double_pboot2.R
new file mode 100644
index 0000000..6beb837
--- /dev/null
+++ b/simulation_est_slurm_double_pboot2.R
@@ -0,0 +1,260 @@
+###################
+## load packages ##
+###################
+library(tidyverse)
+library(splines)
+library(gridExtra)
+library(parallel)
+library(foreach)
+library(doParallel)
+
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/HelperFunction.R")
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/singleindexmodelfunctions.R")
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/est_s_t_y.R")
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SIDR_Ravinew.R")
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SIDRnew.R")
+source("/uufs/chpc.utah.edu/common/home/u6070035/CCS/code/SensIAT_sim_outcome_modeler_mave.R")
+
+ntasks <- Sys.getenv("SLURM_NTASKS")
+if (ntasks == '') {
+  ntasks <- 4
+} else {
+  ntasks <- strtoi(ntasks) }
+cat("This script use ", ntasks, " cores\n")
+
+package_list <- c("splines", "tidyverse", "gridExtra")
+
+nboot_B <- 500
+
+################
+## simulation ##
+################
+
+cl <- makeCluster(ntasks)
+registerDoParallel(cl)
+
+for (j in (40*(index-1)+1):(40*index)){
+  
+load(paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simData/imputed", imputed, "/n", sim.size, "/sim", j, ".rds"))
+X_sim = data.frame(dplyr::select(data, c(age, pain_bq, expectationb, ChronicPainb)))
+  
+load(paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simResult/imputed", imputed, "/n", sim.size, "/", kernel, "_", single_index_method, "_fold5/sim", j, ".RData"))
+  
+Boot.Est <- foreach(i=1:nboot_B, .combine=rbind, .packages=package_list, .errorhandling = "pass") %dopar% {
+    
+  gamma_length <- length(seq(-5, 5, by=1))
+  nboot_C <- 100
+  
+  ## simulate outer bootstrap sample
+  boot_b_temp <- pboot(data=data, X_sim=X_sim, sim.size=sim.size, seed=NULL)
+  data.new <- boot_b_temp$data.new
+  
+  X.new <- data.frame(dplyr::select(data.new, c(age, pain_bq, expectationb, ChronicPainb)))
+  topical_vals <- fit_one(data=data.new, X=X.new, trt_val=1, coef_g.fit=boot_b_temp$coef_g.fit, 
+                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, 
+                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)
+  oral_vals    <- fit_one(data=data.new, X=X.new, trt_val=0, coef_g.fit=boot_b_temp$coef_g.fit, 
+                          coef_t_R0.fit=boot_b_temp$coef_t_R0.fit, coef_t_R1.fit=boot_b_temp$coef_t_R1.fit, 
+                          coef_M_R0.fit=boot_b_temp$coef_M_R0.fit, coef_M_R1.fit=boot_b_temp$coef_M_R1.fit)
+  boot_b_fit <- pboot_model(data=data.new, X_sim=X.new)
+  coef_g.fit <- coef(boot_b_fit$g.fit)
+  coef_t_R0.fit <- coef(boot_b_fit$t_R0.fit)
+  coef_t_R1.fit <- coef(boot_b_fit$t_R1.fit)
+  coef_M_R0.fit <- coef(boot_b_fit$M_R0.fit)
+  coef_M_R1.fit <- coef(boot_b_fit$M_R1.fit)
+
+  t_b_topical <- (topical_vals[1:11]-topical_WOMAC_12m$est_trunc)/sqrt(topical_vals[34:44])
+  t_b_R1_topical <- (topical_vals[12:22]-topical_WOMAC_12m$est_trunc_R1)/sqrt(topical_vals[45:55])
+  t_b_R0_topical <- (topical_vals[23:33]-topical_WOMAC_12m$est_trunc_R0)/sqrt(topical_vals[56:66])
+  t_b_oral <- (oral_vals[1:11]-oral_WOMAC_12m$est_trunc)/sqrt(oral_vals[34:44])
+  t_b_R1_oral <- (oral_vals[12:22]-oral_WOMAC_12m$est_trunc_R1)/sqrt(oral_vals[45:55])
+  t_b_R0_oral <- (oral_vals[23:33]-oral_WOMAC_12m$est_trunc_R0)/sqrt(oral_vals[56:66])
+  
+  ## empty containers
+  Q_b_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  Q_b_R1_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  Q_b_R0_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  Q_b_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  Q_b_R1_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_R1_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_R0_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_R1_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  t_bc_R0_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_R1_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_R0_topical <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_R1_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  est_R0_oral <- matrix(NA, nrow=nboot_C, ncol=gamma_length)
+  num_NA_topical <- 0
+  num_NA_oral <- 0
+  
+  for(z in 1:nboot_C){
+    
+    data.new2 <- pboot_sim(data=data.new, X_sim=X.new, sim.size=sim.size, seed=NULL, 
+                           fit_t_R0_h=boot_b_fit$fit_t_R0_h, fit_t_R1_h=boot_b_fit$fit_t_R1_h, 
+                           fit_t0_R0_h=boot_b_fit$fit_t0_R0_h, fit_t0_R1_h=boot_b_fit$fit_t0_R1_h, 
+                           g.fit=boot_b_fit$g.fit, t_R0.fit=boot_b_fit$t_R0.fit, M_R0.fit=boot_b_fit$M_R0.fit, 
+                           M_R1.fit=boot_b_fit$M_R1.fit)
+    X.new2 <- data.frame(dplyr::select(data.new2, c(age, pain_bq, expectationb, ChronicPainb)))
+    ## inner estimator
+    temp_topical <- fit_one(data=data.new2, X=X.new2, trt_val=1, coef_g.fit=coef_g.fit, 
+                            coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,
+                            coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)
+    temp_oral <- fit_one(data=data.new2, X=X.new2, trt_val=0, coef_g.fit=coef_g.fit, 
+                         coef_t_R0.fit=coef_t_R0.fit, coef_t_R1.fit=coef_t_R1.fit,
+                         coef_M_R0.fit=coef_M_R0.fit, coef_M_R1.fit=coef_M_R1.fit)
+    
+    Q_b_topical[z, ] <- as.numeric(temp_topical[1:11]<=topical_WOMAC_12m$est_trunc)
+    Q_b_R1_topical[z, ] <- as.numeric(temp_topical[12:22]<=topical_WOMAC_12m$est_trunc_R1)
+    Q_b_R0_topical[z, ] <- as.numeric(temp_topical[23:33]<=topical_WOMAC_12m$est_trunc_R0)
+    Q_b_oral[z, ] <- as.numeric(temp_oral[1:11]<=oral_WOMAC_12m$est_trunc)
+    Q_b_R1_oral[z, ] <- as.numeric(temp_oral[12:22]<=oral_WOMAC_12m$est_trunc_R1)
+    Q_b_R0_oral[z, ] <- as.numeric(temp_oral[23:33]<=oral_WOMAC_12m$est_trunc_R0)
+    
+    t_bc_topical[z, ] <- (temp_topical[1:11]-topical_vals[1:11])/sqrt(temp_topical[34:44])
+    t_bc_R1_topical[z, ] <- (temp_topical[12:22]-topical_vals[12:22])/sqrt(temp_topical[45:55])
+    t_bc_R0_topical[z, ] <- (temp_topical[23:33]-topical_vals[23:33])/sqrt(temp_topical[56:66])
+    t_bc_oral[z, ] <- (temp_oral[1:11]-oral_vals[1:11])/sqrt(temp_oral[34:44])
+    t_bc_R1_oral[z, ] <- (temp_oral[12:22]-oral_vals[12:22])/sqrt(temp_oral[45:55])
+    t_bc_R0_oral[z, ] <- (temp_oral[23:33]-oral_vals[23:33])/sqrt(temp_oral[56:66])
+    
+    est_topical[z, ] <- temp_topical[1:11]
+    est_R1_topical[z, ] <- temp_topical[12:22]
+    est_R0_topical[z, ] <- temp_topical[23:33]
+    est_oral[z, ] <- temp_oral[1:11]
+    est_R1_oral[z, ] <- temp_oral[12:22]
+    est_R0_oral[z, ] <- temp_oral[23:33]
+    
+    num_NA_topical <- num_NA_topical+as.numeric(any(is.na(temp_topical[1:33])))
+    num_NA_oral <- num_NA_oral+as.numeric(any(is.na(temp_oral[1:33])))
+    
+  }
+  
+  r_Q_b_topical <- colMeans(Q_b_topical, na.rm=T)
+  r_Q_b_R1_topical <- colMeans(Q_b_R1_topical, na.rm=T)
+  r_Q_b_R0_topical <- colMeans(Q_b_R0_topical, na.rm=T)
+  r_Q_b_oral <- colMeans(Q_b_oral, na.rm=T)
+  r_Q_b_R1_oral <- colMeans(Q_b_R1_oral, na.rm=T)
+  r_Q_b_R0_oral <- colMeans(Q_b_R0_oral, na.rm=T)
+  Q_t_b_topical <- colMeans(t_bc_topical<=matrix(t_b_topical, nrow=nboot_C, ncol=gamma_length, 
+                                                 byrow=T), na.rm=T)
+  abs_Q_t_b_topical <- colMeans(abs(t_bc_topical)<=matrix(abs(t_b_topical), nrow=nboot_C, ncol=gamma_length, 
+                                                          byrow=T), na.rm=T)
+  Q_t_b_R1_topical <- colMeans(t_bc_R1_topical<=matrix(t_b_R1_topical, nrow=nboot_C, ncol=gamma_length, 
+                                                       byrow=T), na.rm=T)
+  abs_Q_t_b_R1_topical <- colMeans(abs(t_bc_R1_topical)<=matrix(abs(t_b_R1_topical), nrow=nboot_C, ncol=gamma_length, 
+                                                                byrow=T), na.rm=T)
+  Q_t_b_R0_topical <- colMeans(t_bc_R0_topical<=matrix(t_b_R0_topical, nrow=nboot_C, ncol=gamma_length, 
+                                                       byrow=T), na.rm=T)
+  abs_Q_t_b_R0_topical <- colMeans(abs(t_bc_R0_topical)<=matrix(abs(t_b_R0_topical), nrow=nboot_C, ncol=gamma_length, 
+                                                                byrow=T), na.rm=T)
+  Q_t_b_oral <- colMeans(t_bc_oral<=matrix(t_b_oral, nrow=nboot_C, ncol=gamma_length, 
+                                           byrow=T), na.rm=T)
+  abs_Q_t_b_oral <- colMeans(abs(t_bc_oral)<=matrix(abs(t_b_oral), nrow=nboot_C, ncol=gamma_length, 
+                                                    byrow=T), na.rm=T)
+  Q_t_b_R1_oral <- colMeans(t_bc_R1_oral<=matrix(t_b_R1_oral, nrow=nboot_C, ncol=gamma_length, 
+                                                 byrow=T), na.rm=T)
+  abs_Q_t_b_R1_oral <- colMeans(abs(t_bc_R1_oral)<=matrix(abs(t_b_R1_oral), nrow=nboot_C, ncol=gamma_length, 
+                                                          byrow=T), na.rm=T)
+  Q_t_b_R0_oral <- colMeans(t_bc_R0_oral<=matrix(t_b_R0_oral, nrow=nboot_C, ncol=gamma_length, 
+                                                 byrow=T), na.rm=T)
+  abs_Q_t_b_R0_oral <- colMeans(abs(t_bc_R0_oral)<=matrix(abs(t_b_R0_oral), nrow=nboot_C, ncol=gamma_length, 
+                                                          byrow=T), na.rm=T)
+  t_b_sd_topical <- (topical_vals[1:11]-topical_WOMAC_12m$est_trunc)/apply(est_topical, 2, function(x){sd(x, na.rm=TRUE)})
+  t_b_R1_sd_topical <- (topical_vals[12:22]-topical_WOMAC_12m$est_trunc_R1)/apply(est_R1_topical, 2, function(x){sd(x, na.rm=TRUE)})
+  t_b_R0_sd_topical <- (topical_vals[23:33]-topical_WOMAC_12m$est_trunc_R0)/apply(est_R0_topical, 2, function(x){sd(x, na.rm=TRUE)})
+  t_b_sd_oral <- (oral_vals[1:11]-oral_WOMAC_12m$est_trunc)/apply(est_oral, 2, function(x){sd(x, na.rm=TRUE)})
+  t_b_R1_sd_oral <- (oral_vals[12:22]-oral_WOMAC_12m$est_trunc_R1)/apply(est_R1_oral, 2, function(x){sd(x, na.rm=TRUE)})
+  t_b_R0_sd_oral <- (oral_vals[23:33]-oral_WOMAC_12m$est_trunc_R0)/apply(est_R0_oral, 2, function(x){sd(x, na.rm=TRUE)})
+
+return(c(topical_vals, oral_vals, r_Q_b_topical, r_Q_b_R1_topical, r_Q_b_R0_topical, 
+         r_Q_b_oral, r_Q_b_R1_oral, r_Q_b_R0_oral, Q_t_b_topical, Q_t_b_R1_topical, Q_t_b_R0_topical, 
+         Q_t_b_oral, Q_t_b_R1_oral, Q_t_b_R0_oral, abs_Q_t_b_topical, abs_Q_t_b_R1_topical, abs_Q_t_b_R0_topical, 
+         abs_Q_t_b_oral, abs_Q_t_b_R1_oral, abs_Q_t_b_R0_oral, t_b_sd_topical, t_b_R1_sd_topical, t_b_R0_sd_topical, 
+         t_b_sd_oral, t_b_R1_sd_oral, t_b_R0_sd_oral, num_NA_topical, num_NA_oral,
+         t_b_topical, t_b_R1_topical, t_b_R0_topical, t_b_oral, t_b_R1_oral, t_b_R0_oral))
+
+}
+
+est_topical_boot <- Boot.Est[, 1:11]
+est_R1_topical_boot <- Boot.Est[, 12:22]
+est_R0_topical_boot <- Boot.Est[, 23:33]
+var_topical_boot <- Boot.Est[, 34:44]
+var_R1_topical_boot <- Boot.Est[, 45:55]
+var_R0_topical_boot <- Boot.Est[, 56:66]
+
+est_oral_boot <- Boot.Est[, 67:77]
+est_R1_oral_boot <- Boot.Est[, 78:88]
+est_R0_oral_boot <- Boot.Est[, 89:99]
+var_oral_boot <- Boot.Est[, 100:110]
+var_R1_oral_boot <- Boot.Est[, 111:121]
+var_R0_oral_boot <- Boot.Est[, 122:132]
+
+Q_b_topical <- Boot.Est[, 133:143]
+Q_b_R1_topical <- Boot.Est[, 144:154]
+Q_b_R0_topical <- Boot.Est[, 155:165]
+Q_b_oral <- Boot.Est[, 166:176]
+Q_b_R1_oral <- Boot.Est[, 177:187]
+Q_b_R0_oral <- Boot.Est[, 188:198]
+
+Q_t_b_topical <- Boot.Est[, 199:209]
+Q_t_b_R1_topical <- Boot.Est[, 210:220]
+Q_t_b_R0_topical <- Boot.Est[, 221:231]
+Q_t_b_oral <- Boot.Est[, 232:242]
+Q_t_b_R1_oral <- Boot.Est[, 243:253]
+Q_t_b_R0_oral <- Boot.Est[, 254:264]
+
+abs_Q_t_b_topical <- Boot.Est[, 265:275]
+abs_Q_t_b_R1_topical <- Boot.Est[, 276:286]
+abs_Q_t_b_R0_topical <- Boot.Est[, 287:297]
+abs_Q_t_b_oral <- Boot.Est[, 298:308]
+abs_Q_t_b_R1_oral <- Boot.Est[, 309:319]
+abs_Q_t_b_R0_oral <- Boot.Est[, 320:330]
+
+t_b_sd_topical <- Boot.Est[, 331:341]
+t_b_R1_sd_topical <- Boot.Est[, 342:352]
+t_b_R0_sd_topical <- Boot.Est[, 353:363]
+t_b_sd_oral <- Boot.Est[, 364:374]
+t_b_R1_sd_oral <- Boot.Est[, 375:385]
+t_b_R0_sd_oral <- Boot.Est[, 386:396]
+
+num_NA_topical <- Boot.Est[, 397]
+num_NA_oral <- Boot.Est[, 398]
+
+t_b_topical <- Boot.Est[, 399:409]
+t_b_R1_topical <- Boot.Est[, 410:420]
+t_b_R0_topical <- Boot.Est[, 421:431]
+t_b_oral <- Boot.Est[, 432:442]
+t_b_R1_oral <- Boot.Est[, 443:453]
+t_b_R0_oral <- Boot.Est[, 454:464]
+
+## bootstrap result
+save(est_topical_boot, est_R1_topical_boot, est_R0_topical_boot, 
+     est_oral_boot, est_R1_oral_boot, est_R0_oral_boot, 
+     var_topical_boot, var_R1_topical_boot, var_R0_topical_boot, 
+     var_oral_boot, var_R1_oral_boot, var_R0_oral_boot, 
+     Q_b_topical, Q_b_R1_topical, Q_b_R0_topical, 
+     Q_b_oral, Q_b_R1_oral, Q_b_R0_oral, 
+     t_b_topical, t_b_R1_topical, t_b_R0_topical, 
+     t_b_oral, t_b_R1_oral, t_b_R0_oral, 
+     Q_t_b_topical, Q_t_b_R1_topical, Q_t_b_R0_topical, 
+     Q_t_b_oral, Q_t_b_R1_oral, Q_t_b_R0_oral, 
+     abs_Q_t_b_topical, abs_Q_t_b_R1_topical, abs_Q_t_b_R0_topical, 
+     abs_Q_t_b_oral, abs_Q_t_b_R1_oral, abs_Q_t_b_R0_oral, 
+     t_b_sd_topical, t_b_R1_sd_topical, t_b_R0_sd_topical, 
+     t_b_sd_oral, t_b_R1_sd_oral, t_b_R0_sd_oral, num_NA_topical, num_NA_oral, 
+     file=paste0("/uufs/chpc.utah.edu/common/home/u6070035/CCS/simResult/imputed", imputed, "/double_pboot_n", sim.size, "/", kernel, "_", single_index_method, "/sim", j, ".RData"))
+print(j)
+
+}
+
+stopCluster(cl)
+
+
+
+
+
+
diff --git a/singleindexmodelfunctions.R b/singleindexmodelfunctions.R
new file mode 100644
index 0000000..cd4555c
--- /dev/null
+++ b/singleindexmodelfunctions.R
@@ -0,0 +1,400 @@
+# single index model's function
+
+# return the initial value for beta
+cumuSIR <- function(X, Y, eps = 1e-7){
+  X <- as.matrix(X)
+  Y <- as.matrix(Y)
+  
+  number_n <- dim(X)[1]
+  number_p <- dim(X)[2]
+  
+  Y.CP <- matrix(
+    Y[rep(1:number_n, times = number_n), ]<=
+      Y[rep(1:number_n, each = number_n), ],
+    nrow = number_n, ncol = number_n
+  )
+  
+  # centralizing covariates
+  X.cs <- t(t(X)-colMeans(X))
+  
+  # calculating m(y)=\E[X_i 1(Y_i\leq y)]
+  m.y <- t(X.cs) %*% Y.CP/number_n
+  # calculating K=\E[m(Y_i)m(Y_i)^T]
+  Km <- m.y %*% t(m.y)/number_n
+  
+  Bhat <- eigen(solve(var(X) + eps*diag(number_p), Km))$vectors[, 1]
+  
+  return(Bhat)
+}
+
+
+# find the optimal bandwidth, default set for kernel is 
+SIDRnew_h2 <- function(X, Y,
+                       Y.CP = NULL,
+                       beta = NULL,
+                       kernel = "K2_Biweight",
+                       method = "optim",
+                       optim_method = "BFGS",
+                       abs.tol = 1e-4,
+                       initial_bandwidth = NULL,
+                       wi.boot = NULL, penalty=0)
+{
+  X <- as.matrix(X)
+  Y <- as.matrix(Y)
+  
+  number_n <- dim(X)[1]
+  number_p <- dim(X)[2]
+  
+  if (is.null(beta))
+  {
+    beta <- c(1, rep(0, number_p-1))
+  }else
+  {
+    beta <- as.vector(beta)
+    beta <- beta/beta[1]
+  }
+  
+  if (is.null(initial_bandwidth))
+  {
+    if (kernel=="K2_Biweight")
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)
+          b <- beta
+          h <- exp(parameter)
+          xb <- c(X%*%b) 
+          y <- Y
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(xb-xb[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2+penalty*h)
+        }
+        
+        # cv.bh <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   h <- exp(parameter[number_p])
+        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,
+        #                                  h = h))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        stop("There's no weighted version of the K2_Biweight kernel.")
+      }
+    }else if (kernel == "dnorm")
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) dnorm(x/h, 0, 1)
+          
+          b <- beta
+          h <- exp(parameter)
+          
+          x <- c(X%*%b) 
+          y <- Y
+          
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(x-x[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2)
+        }
+        # cv.bh <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   h <- exp(parameter[number_p])
+        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,
+        #                                    h = h))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        # wi.boot <- as.vector(wi.boot)
+        # cv.bh <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   h <- exp(parameter[number_p])
+        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,
+        #                                    h = h, w = wi.boot))^2)
+        #   return(cv)
+        # }
+        stop("There's no weighted version of the dnorm kernel.")
+      }
+    }else if (kernel=="K4_Biweight")
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) 
+          
+          b <- beta
+          h <- exp(parameter)
+          
+          x <- c(X%*%b) 
+          y <- Y
+          
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(x-x[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2)
+        }
+        # cv.bh <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   h <- exp(parameter[number_p])
+        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,
+        #                                            h = h), 0), 1))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        stop("There's no weighted version of the K4_Biweight kernel.")
+      }
+    }
+    
+    if(method == "nlminb")
+    {
+      esti <- nlminb(start = 0, 
+                     objective = Eij3,
+                     control = list(abs.tol = abs.tol))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$par),
+                      details = esti)
+    }else if (method == "optim")
+    {
+      # the new optimize function using optim, you can change the lower and upper
+      esti <- optim(par = 0, 
+                    fn = Eij3,
+                    method = optim_method,
+                    control = list(abstol = abs.tol))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$par),
+                      details = esti)
+    }
+    else if (method == "optimize")
+    {
+      #   # esti <- nmk(par = 0, 
+      #   #             fn = Eij3,
+      #   #             control = list(tol = abs.tol))
+      esti <- optimize(Eij3,
+                       interval = c(-10, 10))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$minimum),
+                      details = esti)
+    }
+    
+  }else
+  {
+    if (kernel=="K2_Biweight")
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) 15/16*(1-(x/h)^2)^2 * (abs(x) <= h)
+          b <- beta
+          h <- exp(parameter)
+          xb <- c(X%*%b) 
+          y <- Y
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(xb-xb[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2+penalty*h)
+        }
+        
+        # cv.b <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   cv <- mean((Y.CP-NWcv_K2B_rcpp(X = X %*% b, Y = Y.CP,
+        #                                  h = bandwidth))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        stop("There's no weighted version of the K2_Biweight kernel.")
+      }
+    }else if (kernel=="dnorm") 
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) dnorm(x/h,0,1) 
+          
+          b <- beta
+          h <- exp(parameter)
+          
+          x <- c(X%*%b) 
+          y <- Y
+          
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(x-x[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2)
+        }
+        
+        # cv.b <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   cv <- mean((Y.CP-NWcv_dnorm_rcpp(X = X %*% b, Y = Y.CP,
+        #                                    h = bandwidth))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        # wi.boot <- as.vector(wi.boot)
+        # cv.b <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   cv <- mean((Y.CP-NWcv_K2B_w_rcpp(X = X %*% b, Y = Y.CP,
+        #                                    h = bandwidth, w = wi.boot))^2)
+        #   return(cv)
+        # }
+        stop("There's no weighted version of the dnorm kernel.")
+      }
+    }else if (kernel=="K4_Biweight")
+    {
+      if (is.null(wi.boot))
+      {
+        Eij3 <- function(parameter){
+          K <- function(x, h) 105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) 
+          
+          b <- beta
+          h <- exp(parameter)
+          
+          x <- c(X%*%b) 
+          y <- Y
+          
+          n <- length(y)
+          yo <- order(y)
+          ys <- y[yo]
+          uy <- rle(ys)[[1]]
+          cols <- cumsum(uy)
+          ei <- rep(0, n)
+          for (i in 1:n){
+            Kih <- K(x-x[i],h=h)
+            Kih[i] <- 0
+            denom <- sum(Kih)
+            ei[i] <- sum(uy*(1*(y[i] <= ys)[cols] - (denom != 0)* cumsum(Kih[yo])[cols] / (denom + (denom == 0)))^2)
+          }
+          return(sum(ei)/n^2)
+        }
+        # cv.b <- function(parameter)
+        # {
+        #   b <- c(1, parameter[1:(number_p-1)])
+        #   cv <- mean((Y.CP-pmin(pmax(NWcv_K4B_rcpp(X = X %*% b, Y = Y.CP,
+        #                                            h = bandwidth), 0), 1))^2)
+        #   return(cv)
+        # }
+      }else
+      {
+        stop("There's no weighted version of the K4_Biweight kernel.")
+      }
+    }
+    
+    if(method == "nlminb")
+    {
+      esti <- nlminb(start = initial_bandwidth, 
+                     objective = Eij3,
+                     control = list(abs.tol = abs.tol))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$par),
+                      details = esti)
+    }else if (method == "optim")
+    {
+      # the new optimize function using optim, you can change the lower and upper
+      esti <- optim(par = initial_bandwidth, 
+                    fn = Eij3,
+                    method = optim_method,
+                    control = list(abstol = abs.tol))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$par),
+                      details = esti)
+    }
+    else if (method == "optimize")
+    {
+      #   # esti <- nmk(par = initial_bandwidth, 
+      #   #             fn = Eij3,
+      #   #             control = list(tol = abs.tol))
+      esti <- optimize(Eij3,
+                       interval = c(-10, 10))
+      results <- list(coef = beta,
+                      bandwidth = exp(esti$minimum),
+                      details = esti)
+      
+    }
+  }
+  
+  return(results)
+}
+
+
+# return the prediction using "K2_Biweight" kernel
+NW_new <- function(Xb, Y, xb, y, h, kernel = "K2_Biweight"){
+  
+  if(kernel == "dnorm"){
+    K <- function(x, h){dnorm(x/h, 0, 1)} # Gaussian 
+  } else if(kernel == "K2_Biweight"){
+    K <- function(x, h){15/16*(1-(x/h)^2)^2 * (abs(x) <= h)} # K2_Biweight
+  } else if(kernel=="K4_Biweight"){
+    K <- function(x, h){105/64*(1-3*((x/h)^2))*(1-(x/h)^2)^2 * (abs(x) <= h) }# K4_Biweight
+  }
+  
+  Kxb <- sapply(xb, function(x, Xb) K(Xb-x, h), Xb=Xb)
+  
+  Ylty <- sapply(y, function(x, Y) 1*(Y <= x), Y=Y)
+  
+  denom <- colSums(Kxb)
+  
+  fyxb <- (denom!=0)*crossprod(Kxb, Ylty)/(denom + (denom==0))
+  
+  return(fyxb)
+  
+}
+