temporarily removed digest from seed_var evaluation

cami_src/evaluation_scripts/seed_variation_script.py

@@ -17,7 +17,7 @@ def predict_and_make_consensus(cami, vis=False):
         if vis:
             cami.use_nvenn(download=True)
             
-def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=True):
+def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=False):
     identifier = cami.uid
     base_seeds = cami.origin_seed_lst
     original_seeds = [cami.ppi_vertex2gene[seed] for seed in base_seeds]
@@ -52,11 +52,11 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Tru
             for tool in prediction_tools:
                 res_table.write(f'\t{tool}_msr_ks_pvalue')
             
-            with open(os.path.join(cami.tmp_dir, f'{used_tools[0]}_{cami.uid}_relevance_scores.tsv'), 'r') as f:
-                for line in f:
-                    val_name = line.split('\t')[0]
-                    redisc_table.write(f'\t{val_name}')
-            res_table.write('\n')
+            # with open(os.path.join(cami.tmp_dir, f'{used_tools[0]}_{cami.uid}_relevance_scores.tsv'), 'r') as f:
+            #     for line in f:
+            #         val_name = line.split('\t')[0]
+            #         redisc_table.write(f'\t{val_name}')
+            # res_table.write('\n')
             # result dictionaries of the form {tool:list(value for each iteration)}
             
             tp_rate_dict = {k:list() for k in used_tools}
@@ -142,10 +142,10 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Tru
                                                                      list(module_size_dict[pred_tool]))
                     res_table.write(f'\t{p_val}')
                     
-                with open(os.path.join(cami.tmp_dir, f'{tool}_{identifier}_relevance_scores.tsv)'), 'r') as f:
-                    for line in f:
-                        rel_score = line.split('\t')[1].strip()
-                        res_table.write(f'\t{rel_score}')
+                # with open(os.path.join(cami.tmp_dir, f'{tool}_{identifier}_relevance_scores.tsv)'), 'r') as f:
+                #     for line in f:
+                #         rel_score = line.split('\t')[1].strip()
+                #         res_table.write(f'\t{rel_score}')
                 res_table.write('\n')
     
     print(f'Result tables are saved in the following locations:')
@@ -171,7 +171,7 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Tru
         #PLOT
         # Create a figure instance
         #print(sys.getrecursionlimit())
-        fig1, (ax1, ax5, ax4) = plt.subplots(3, 1, figsize=(20,20))
+        fig1, (ax1, ax5) = plt.subplots(2, 1, figsize=(20,20))
         fig1.subplots_adjust(left=0.2)
         # Extract Figure and Axes instance
 
@@ -200,26 +200,26 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Tru
 
         ax1.set_ylabel('Rediscovery rate (<rediscovered seeds>/<removed seeds>)', wrap=True, fontsize=14)
 
-        violins2 = ax4.violinplot([tp_rate_dict[tool] for tool in tools], showmeans=True, showextrema=True)
-        for violinpart in list(violins2.keys())[2:]:
-            violins2[violinpart].set_color('k')
-        for violin, tool in zip(violins2['bodies'], tools):
-            if tool in [tw.name for tw in cami.tool_wrappers]:        
-                violin.set_facecolor('tan')
-            elif tool == 'first_neighbors':
-                violin.set_facecolor('peachpuff')
-            elif tool in ['union', 'intersection']:
-                violin.set_facecolor('orange')
-            else:
-                violin.set_facecolor('darkorange')
-        # Add title
-        ax4.set_title(f'True positive rates after randomly removing {nof_removals} seeds {nof_iterations} times from {identifier} seeds.', wrap=True, fontsize=14)
-
-        ax4.set_xticks(list(range(1,len(tools)+1)))
-        ax4.set_xticklabels(tool_labels)
-        ax4.tick_params(axis='x', labelsize=11)
-
-        ax4.set_ylabel('Sensitivity (TP/TP + FN)', wrap=True, fontsize=14)
+        # violins2 = ax4.violinplot([tp_rate_dict[tool] for tool in tools], showmeans=True, showextrema=True)
+        # for violinpart in list(violins2.keys())[2:]:
+        #     violins2[violinpart].set_color('k')
+        # for violin, tool in zip(violins2['bodies'], tools):
+        #     if tool in [tw.name for tw in cami.tool_wrappers]:        
+        #         violin.set_facecolor('tan')
+        #     elif tool == 'first_neighbors':
+        #         violin.set_facecolor('peachpuff')
+        #     elif tool in ['union', 'intersection']:
+        #         violin.set_facecolor('orange')
+        #     else:
+        #         violin.set_facecolor('darkorange')
+        # # Add title
+        # ax4.set_title(f'True positive rates after randomly removing {nof_removals} seeds {nof_iterations} times from {identifier} seeds.', wrap=True, fontsize=14)
+
+        # ax4.set_xticks(list(range(1,len(tools)+1)))
+        # ax4.set_xticklabels(tool_labels)
+        # ax4.tick_params(axis='x', labelsize=11)
+
+        # ax4.set_ylabel('Sensitivity (TP/TP + FN)', wrap=True, fontsize=14)
 
         violins3 = ax5.violinplot([module_size_dict[tool] for tool in tools], showmeans=True, showextrema=True)
         # Add title