add annotations to cluster plot

nuc_morph_analysis/analyses/linear_regression/analysis_plots.py

@@ -60,23 +60,25 @@ def plot_feature_cluster_correlations(df_track_level_features, feature_list, fig
     data = df_track_level_features[feature_list]
 
     cluster_grid = sns.clustermap(data.corr(), vmin=-1, vmax=1, cmap='vlag', 
-                                  cbar_pos=(0.45, 0.5, 0.18, 0.02), 
-                                  cbar_kws={"orientation": "horizontal"})
+                                  cbar_pos=(0.7, 0.13, 0.18, 0.02), 
+                                  cbar_kws={"orientation": "horizontal"},
+                                  annot=True, fmt=".1f", annot_kws={"size": 12},
+                                  figsize=(20, 20))
 
     # Get the reordered labels using the dendrogram information
     reordered_column_index = cluster_grid.dendrogram_col.reordered_ind
 
     reordered_labels = [get_plot_labels_for_metric(data.columns[i])[1] for i in reordered_column_index]
 
     # Ensure the number of labels matches the number of ticks
-    cluster_grid.ax_heatmap.set_xticks(range(len(reordered_labels)))
+    cluster_grid.ax_heatmap.set_xticks([x + 0.5 for x in range(len(reordered_labels))])
     cluster_grid.ax_heatmap.set_xticklabels(reordered_labels, rotation=90)
-    cluster_grid.ax_heatmap.set_yticks(range(len(reordered_labels)))
+    cluster_grid.ax_heatmap.set_yticks([y + 0.5 for y in range(len(reordered_labels))])
     cluster_grid.ax_heatmap.set_yticklabels(reordered_labels, rotation=0)
 
     # Adjust the padding between the labels and the heatmap
-    cluster_grid.ax_heatmap.tick_params(axis='x', labelsize=8, width=0.7)
-    cluster_grid.ax_heatmap.tick_params(axis='y', labelsize=8, width=0.7)
+    cluster_grid.ax_heatmap.tick_params(axis='x', labelsize=12, width=0.7)
+    cluster_grid.ax_heatmap.tick_params(axis='y', labelsize=12, width=0.7)
 
     save_and_show_plot(f'{figdir}/feature_correlation_clustermap', figure=cluster_grid.fig, dpi=300)