add plot_rois to post_analysis

rest_dFC/functions/post_analysis_funcs.py

@@ -14,6 +14,7 @@
 import statsmodels.api as sm
 from statsmodels.formula.api import ols
 from sklearn.manifold import TSNE
+from math import ceil
 
 import matplotlib.pyplot as plt
 import matplotlib as mpl
@@ -116,7 +117,75 @@ def plot_sample_dFC(D, x,
     else:
         plt.show()
 
+
+def plot_rois(
+        node_networks, 
+        nodes_locs, 
+        save_image=False, 
+        output_root=None
+    ):
+
+    networks = list(np.unique(node_networks))
+
+    fig_width = 25
+    fig_height = len(networks)
+
+    fig, axes = plt.subplots(ceil(len(networks)/3), 3, figsize=(fig_width, fig_height), 
+        facecolor='w', edgecolor='k')
 
+    axes = axes.ravel()
+
+    fig.subplots_adjust(
+        bottom=0.1, 
+        top=0.85, 
+        left=0.1, 
+        right=0.9,
+        wspace=0.03, 
+        hspace=0.3
+    )
+
+    for i, target_network in enumerate(networks):
+
+        locs = []
+        node_values = []
+        for node_id, node_network in enumerate(node_networks):
+            if node_network == target_network:
+                node_values.append(1)
+                locs.append(nodes_locs[node_id])
+
+        node_values = np.array(node_values)
+        locs = np.array(locs)
+
+        plot_markers(
+            node_values=node_values, 
+            node_coords=locs, 
+            node_size=100,
+            node_cmap='Reds', 
+            node_vmax=1,
+            node_vmin=0,
+            annotate=True,
+            colorbar=False, axes=axes[i],
+        )
+
+    title = f"Resting State Networks"
+    # set subplot titles
+    for i, network in enumerate(networks):
+        axes[i].title.set_text(f"{network} network")
+        axes[i].title.set_size(20)
+        axes[i].title.set_weight('bold')
+
+    if save_image:
+        folder = output_root[:output_root.rfind('/')]
+        if not os.path.exists(folder):
+            os.makedirs(folder)
+        fig.savefig(output_root+title.replace(" ", "_")+'.'+save_fig_format, 
+            dpi=fig_dpi, bbox_inches=fig_bbox_inches, pad_inches=fig_pad, format=save_fig_format
+        ) 
+        plt.close()
+    else:
+        plt.show()
+
+
 def pairwise_cat_plots(data=None, x=None, y=None, z=None,
     title='', 
     label_dict={},

rest_dFC/visualization.py

@@ -57,6 +57,17 @@
         save_image=save_image, output_root=output_root+'FCS/'
     )
 
+################################# RSNs visualization #################################
+
+measure = ALL_RESULTS['measure_lst'][0]
+
+plot_rois(
+    node_networks, 
+    measure.TS_info['nodes_locs'], 
+    save_image=save_image, 
+    output_root=f"{output_root}RSNs/"
+)
+
 ################################# dFC values distributions #################################
 dFC_dist_plot = True