Merge branch 'release-1.0.24'

Author: tesar-stepan

.classpath

@@ -4,6 +4,7 @@
 		<attributes>
 			<attribute name="optional" value="true"/>
 			<attribute name="maven.pomderived" value="true"/>
+			<attribute name="test" value="true"/>
 		</attributes>
 	</classpathentry>
 	<classpathentry including="**/*.java" kind="src" output="target/classes" path="src">

pom.xml

@@ -5,7 +5,7 @@
 	<name>baseCode</name>
 	<groupId>baseCode</groupId>
 	<artifactId>baseCode</artifactId>
-	<version>1.0.23</version>
+	<version>1.0.24</version>
 	<inceptionYear>2003</inceptionYear>
 	<description>
 	<![CDATA[Data structures, math and statistics tools, and utilities that are often needed across projects.]]>

src/ubic/basecode/dataStructure/matrix/MatrixUtil.java

@@ -31,13 +31,12 @@
 
 /**
  * @author Paul
- * @version $Id$
  */
 public class MatrixUtil {
 
     /**
-     * @param d
-     * @return true if any of the values are very close to zero.
+     * @param  d
+     * @return   true if any of the values are very close to zero.
      */
     public static boolean containsNearlyZeros( DoubleMatrix1D d ) {
         for ( int i = 0; i < d.size(); i++ ) {
@@ -49,7 +48,7 @@ public static boolean containsNearlyZeros( DoubleMatrix1D d ) {
     /**
      * Extract the diagonal from a matrix.
      * 
-     * @param matrix
+     * @param  matrix
      * @return
      */
     public static DoubleMatrix1D diagonal( DoubleMatrix2D matrix ) {
@@ -63,8 +62,8 @@ public static DoubleMatrix1D diagonal( DoubleMatrix2D matrix ) {
     }
 
     /**
-     * @param n
-     * @param indexToDrop
+     * @param  n
+     * @param  indexToDrop
      * @return
      */
     public static DoubleMatrix2D dropColumn( DoubleMatrix2D n, int indexToDrop ) {
@@ -108,7 +107,7 @@ public static DoubleMatrix2D dropColumns( DoubleMatrix2D n, Collection<Integer>
     /**
      * Makes a copy
      * 
-     * @param list
+     * @param  list
      * @return
      */
     public static DoubleMatrix1D fromList( DoubleArrayList list ) {
@@ -120,12 +119,12 @@ public static DoubleMatrix1D fromList( DoubleArrayList list ) {
     }
 
     /**
-     * @param <R>
-     * @param <C>
-     * @param <V>
-     * @param matrix
-     * @param rowIndex
-     * @param colIndex
+     * @param           <R>
+     * @param           <C>
+     * @param           <V>
+     * @param  matrix
+     * @param  rowIndex
+     * @param  colIndex
      * @return
      */
     public static <R, C, V> V getObject( Matrix2D<R, C, V> matrix, int rowIndex, int colIndex ) {
@@ -139,11 +138,11 @@ public static <R, C, V> V getObject( Matrix2D<R, C, V> matrix, int rowIndex, int
     }
 
     /**
-     * @param <R>
-     * @param <C>
-     * @param <V>
-     * @param matrix
-     * @param rowIndex
+     * @param           <R>
+     * @param           <C>
+     * @param           <V>
+     * @param  matrix
+     * @param  rowIndex
      * @return
      */
     public static <R, C, V> V[] getRow( Matrix2D<R, C, V> matrix, int rowIndex ) {
@@ -178,8 +177,8 @@ public static DoubleMatrix1D multWithMissing( DoubleMatrix1D a, DoubleMatrix2D b
     }
 
     /**
-     * @param a
-     * @param b
+     * @param  a
+     * @param  b
      * @return
      */
     public static DoubleMatrix1D multWithMissing( DoubleMatrix2D a, DoubleMatrix1D b ) {
@@ -212,8 +211,8 @@ public static DoubleMatrix1D multWithMissing( DoubleMatrix2D a, DoubleMatrix1D b
     /**
      * Multiple two matrices, tolerate missing values.
      * 
-     * @param a
-     * @param b
+     * @param  a
+     * @param  b
      * @return
      */
     public static DoubleMatrix2D multWithMissing( DoubleMatrix2D a, DoubleMatrix2D b ) {
@@ -245,16 +244,16 @@ public static DoubleMatrix2D multWithMissing( DoubleMatrix2D a, DoubleMatrix2D b
     }
 
     public static List<Integer> notNearlyZeroIndices( DoubleMatrix1D d ) {
-        List<Integer> result = new ArrayList<Integer>();
+        List<Integer> result = new ArrayList<>();
         for ( int i = 0; i < d.size(); i++ ) {
             if ( Math.abs( d.getQuick( i ) ) > Constants.SMALL ) result.add( i );
         }
         return result;
     }
 
     /**
-     * @param data
-     * @return a copy of the data with missing values removed (might be empty!)
+     * @param  data
+     * @return      a copy of the data with missing values removed (might be empty!)
      */
     public static DoubleMatrix1D removeMissing( DoubleMatrix1D data ) {
         int sizeWithoutMissingValues = sizeWithoutMissingValues( data );
@@ -272,6 +271,31 @@ public static DoubleMatrix1D removeMissing( DoubleMatrix1D data ) {
         return r;
     }
 
+    /**
+     * Remove values from data corresponding to missing values in reference.
+     * 
+     * @param  reference
+     * @param  data
+     * @return
+     */
+    public static DoubleMatrix1D removeMissing( DoubleMatrix1D reference, DoubleMatrix1D data ) {
+        if ( data.size() != reference.size() ) throw new IllegalArgumentException( "Reference and data must have same size" );
+        int sizeWithoutMissingValues = sizeWithoutMissingValues( reference );
+        if ( sizeWithoutMissingValues == reference.size() ) return data; // no missing values.
+        DoubleMatrix1D r = new DenseDoubleMatrix1D( sizeWithoutMissingValues );
+        double[] elements = data.toArray();
+        double[] refels = reference.toArray();
+        int size = data.size();
+        int j = 0;
+        for ( int i = 0; i < size; i++ ) {
+            if ( Double.isNaN( refels[i] ) || Double.isInfinite( refels[i] ) ) {
+                continue;
+            }
+            r.set( j++, elements[i] );
+        }
+        return r;
+    }
+
     public static DoubleMatrix1D select( DoubleMatrix1D v, Collection<Integer> selected ) {
         DoubleMatrix1D result = new DenseDoubleMatrix1D( selected.size() );
         int k = 0;
@@ -301,8 +325,8 @@ public static DoubleMatrix2D selectColumns( DoubleMatrix2D n, Collection<Integer
     }
 
     /**
-     * @param n square matrix
-     * @param selected
+     * @param  n        square matrix
+     * @param  selected
      * @return
      */
     public static DoubleMatrix2D selectColumnsAndRows( DoubleMatrix2D n, Collection<Integer> selected ) {
@@ -371,7 +395,7 @@ public static int sizeWithoutMissingValues( DoubleMatrix1D list ) {
     /**
      * Makes a copy
      * 
-     * @param vector
+     * @param  vector
      * @return
      */
     public static DoubleArrayList toList( DoubleMatrix1D vector ) {

src/ubic/basecode/math/Stats.java

@@ -22,13 +22,7 @@
 import java.util.Set;
 
 import cern.colt.list.DoubleArrayList;
-import cern.colt.matrix.DoubleFactory2D;
-import cern.colt.matrix.DoubleMatrix1D;
-import cern.colt.matrix.DoubleMatrix2D;
-import cern.colt.matrix.linalg.Algebra;
-import cern.jet.math.Functions;
 import cern.jet.stat.Descriptive;
-import ubic.basecode.dataStructure.matrix.MatrixUtil;
 
 /**
  * Miscellaneous functions used for statistical analysis. Some are optimized or specialized versions of methods that can
@@ -281,7 +275,7 @@ public static double quantile( int index, double[] values, int effectiveSize ) {
      * @return double
      */
     public static double range( DoubleArrayList data ) {
-        return Descriptive.max( data ) - Descriptive.min( data );
+        return DescriptiveWithMissing.max( data ) - DescriptiveWithMissing.min( data );
     }
 
     private Stats() { /* block instantiation */

src/ubic/basecode/math/linalg/SingularValueDecomposition.java

@@ -1,8 +1,8 @@
 /*
  * The baseCode project
- * 
+ *
  * Copyright (c) 2008 University of British Columbia
- * 
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
@@ -27,15 +27,15 @@
 
 import org.apache.commons.lang3.time.StopWatch;
 
-import ubic.basecode.dataStructure.matrix.DenseDoubleMatrix;
-import ubic.basecode.dataStructure.matrix.DoubleMatrix;
 import cern.colt.matrix.DoubleMatrix2D;
 import cern.colt.matrix.impl.DenseDoubleMatrix2D;
+import ubic.basecode.dataStructure.matrix.DenseDoubleMatrix;
+import ubic.basecode.dataStructure.matrix.DoubleMatrix;
 
 /**
  * SVD for DoubleMatrix.
- * 
- * @author paul
+ *
+ * @author  paul
  * @version $Id$
  */
 public class SingularValueDecomposition<R, C> {
@@ -62,7 +62,7 @@ public SingularValueDecomposition( DoubleMatrix<R, C> matrix ) {
 
         computeSVD( dm );
 
-        List<Integer> componentIds = new ArrayList<Integer>();
+        List<Integer> componentIds = new ArrayList<>();
 
         if ( rowNames.size() == 0 ) { // sanity check
             throw new IllegalStateException( "No row names!" );
@@ -72,46 +72,46 @@ public SingularValueDecomposition( DoubleMatrix<R, C> matrix ) {
             componentIds.add( i );
         }
 
-        this.uMatrix = new DenseDoubleMatrix<R, Integer>( svd.getU().toArray() );
+        this.uMatrix = new DenseDoubleMatrix<>( svd.getU().toArray() );
         uMatrix.setRowNames( this.rowNames );
         uMatrix.setColumnNames( componentIds );
 
-        this.vMatrix = new DenseDoubleMatrix<Integer, C>( svd.getV().toArray() );
+        this.vMatrix = new DenseDoubleMatrix<>( svd.getV().toArray() );
         vMatrix.setRowNames( componentIds );
         vMatrix.setColumnNames( this.columnNames );
 
-        this.sMatrix = new DenseDoubleMatrix<Integer, Integer>( svd.getS().toArray() );
+        this.sMatrix = new DenseDoubleMatrix<>( svd.getS().toArray() );
         sMatrix.setRowNames( componentIds );
         sMatrix.setColumnNames( componentIds );
     }
 
     /**
      * @return the condition number of the matrix
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#cond()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#cond()
      */
     public double cond() {
         return svd.cond();
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#getS()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#getS()
      */
     public DoubleMatrix<Integer, Integer> getS() {
         return this.sMatrix;
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#getSingularValues()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#getSingularValues()
      */
     public double[] getSingularValues() {
         return svd.getSingularValues();
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#getU()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#getU()
      */
     public DoubleMatrix<R, Integer> getU() {
         return this.uMatrix;
@@ -120,31 +120,31 @@ public DoubleMatrix<R, Integer> getU() {
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#getV()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#getV()
      */
     public DoubleMatrix<Integer, C> getV() {
         return this.vMatrix;
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#norm2()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#norm2()
      */
     public double norm2() {
         return svd.norm2();
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#rank()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#rank()
      */
     public int rank() {
         return svd.rank();
     }
 
     /**
      * @return
-     * @see cern.colt.matrix.linalg.SingularValueDecomposition#toString()
+     * @see    cern.colt.matrix.linalg.SingularValueDecomposition#toString()
      */
     @Override
     public String toString() {
@@ -158,7 +158,7 @@ private void computeSVD( final DoubleMatrix2D dm ) {
         /*
          * This fails to converge some times, we have to bail.
          */
-        FutureTask<cern.colt.matrix.linalg.SingularValueDecomposition> svdFuture = new FutureTask<cern.colt.matrix.linalg.SingularValueDecomposition>(
+        FutureTask<cern.colt.matrix.linalg.SingularValueDecomposition> svdFuture = new FutureTask<>(
                 new Callable<cern.colt.matrix.linalg.SingularValueDecomposition>() {
                     @Override
                     public cern.colt.matrix.linalg.SingularValueDecomposition call() {