added 'all_nodes' param to 'plot_states_network_glass' method

Author: Alvaro

pyleida/_data_loader.py

@@ -1344,7 +1344,7 @@ def plot_clustering_performance(self):
         performance = pd.read_csv(f'{self._clustering_}/clustering_performance.csv',sep='\t')
         plot_clustering_scores(performance)
 
-    def plot_states_network_glass(self,k=2,darkstyle=False):
+    def plot_states_network_glass(self,k=2,all_nodes=False,darkstyle=False):
         """
         Create a glass brain (axial view) showing the
         network representation of each phase-locking
@@ -1355,6 +1355,11 @@ def plot_states_network_glass(self,k=2,darkstyle=False):
         k : int.
             Select the partition of interest.
 
+        all_nodes : bool. Default: False.
+            Specify whether to show all
+            nodes or just the nodes of
+            the current state.
+
         darkstyle : bool.
             Whether to use a dark theme for
             the plots.
@@ -1363,7 +1368,7 @@ def plot_states_network_glass(self,k=2,darkstyle=False):
         pl_states = self.load_centroids(k=k).values
 
         with plt.style.context("dark_background" if darkstyle else "default"):
-            states_k_glass(pl_states,self.rois_coordinates_,darkstyle=darkstyle)
+            states_k_glass(pl_states,self.rois_coordinates_,all_nodes=all_nodes,darkstyle=darkstyle)
 
     def plot_states_in_bold(self,subject_id,k=2,alpha=.5,darkstyle=False):
         """

pyleida/_leida.py

@@ -1711,7 +1711,7 @@ def plot_clustering_performance(self):
         self._check_is_fitted()
         plot_clustering_scores(self._clustering_.performance)
 
-    def plot_states_network_glass(self,k=2,darkstyle=False):
+    def plot_states_network_glass(self,k=2,all_nodes=False,darkstyle=False):
         """
         Create a glass brain (axial view) showing the
         network representation of each phase-locking
@@ -1722,6 +1722,11 @@ def plot_states_network_glass(self,k=2,darkstyle=False):
         k : int.
             Select the partition of interest.
 
+        all_nodes : bool. Default: False.
+            Specify whether to show all
+            nodes or just the nodes of
+            the current state.
+        
         darkstyle : bool.
             Whether to use a dark theme for
             the plots.
@@ -1735,7 +1740,7 @@ def plot_states_network_glass(self,k=2,darkstyle=False):
         pl_states = self.load_centroids(k=k).values
 
         with plt.style.context("dark_background" if darkstyle else "default"):
-            states_k_glass(pl_states,self.rois_coordinates,darkstyle=darkstyle)
+            states_k_glass(pl_states,self.rois_coordinates_,all_nodes=all_nodes,darkstyle=darkstyle)
 
     def plot_states_on_surf(self,k=2,state='all',parcellation=None,discretize=True,cmap='auto',darkstyle=False,open=True,save=False):
         """

pyleida/plotting/_plotting.py

@@ -448,7 +448,7 @@ def brain_states_on_surf2(centroid,parcellation=None,surface='pial',hemi='right'
 
     return fig_
 
-def states_k_glass(centroids,coords,darkstyle=False):
+def states_k_glass(centroids,coords,all_nodes=False,darkstyle=False):
     """
     Create a glass brain (axial view) showing the
     network representation of each PL pattern for
@@ -462,6 +462,11 @@ def states_k_glass(centroids,coords,darkstyle=False):
 
     coords : ndarray with shape (N_rois, 3).
         ROIs coordinates in MNI space.
+
+    all_nodes : bool. Default: False.
+        Specify whether to show all
+        nodes or just the nodes of
+        the current state.
         
     darkstyle : bool.
         Whether to use a dark theme for the plots.
@@ -507,10 +512,14 @@ def states_k_glass(centroids,coords,darkstyle=False):
         edges_lw = {'linewidth':sizes_and_lws['lw'][n_columns-2],'color':'firebrick'}
         centroid = centroids[state_idx,:]
         network = centroid2network(centroid)
+        if not all_nodes:
+            rois_idxs = centroid>0
+            network = network[rois_idxs,:]
+            network = network[:,rois_idxs]
 
         plot_connectome(
             network, 
-            coords, 
+            coords if all_nodes else coords[rois_idxs], 
             node_color='blue' if not np.any(network) else 'black' if not darkstyle else 'white', 
             node_size=sizes_and_lws['node_size'][n_columns-2], 
             #edge_cmap=<matplotlib.colors.LinearSegmentedColormap object>,