edited seed variation plots

cami_src/cami.py

@@ -143,6 +143,7 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
         if nvenn or save_image:
             print('Sending results to nVenn')
             url = cami.use_nvenn()
+            if url:
                 if nvenn:
                     webbrowser.open(url)
                 if save_image:
@@ -164,7 +165,7 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
         
     # SEED VARIATION
     if seed_variation:
-        def make_consensus(vis=False):
+        def predict_and_make_consensus(vis=False):
             result_sets = cami.make_predictions()
             cami.create_consensus(result_sets)
             if nvenn and vis:
@@ -182,12 +183,12 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
         print(f'Initializing CAMI and the seed variation by running CAMI with all given seeds:{original_seeds}')
         
         with open('/Users/Mia/cami_local/cami/data/output/explorativeness.tsv', 'a') as f:
-            make_consensus(vis=True)
+            predict_and_make_consensus(vis=True)
             seedname = seeds
             for tool in cami.result_gene_sets:
                 f.write(f'\n{seedname}\t{len(cami.seed_lst)}\t{tool}\t{len(cami.result_gene_sets[tool])}')
         
-        #make_consensus(vis=True)
+        #predict_and_make_consensus(vis=True)
         
         random.seed(50)
         removal_frac = 0.2
@@ -235,9 +236,9 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
                             
                             # repeat consensus
                             if ident%5==0:     
-                                make_consensus(vis=True)
+                                predict_and_make_consensus(vis=True)
                             else:
-                                make_consensus()
+                                predict_and_make_consensus()
                             
                             used_seeds = [cami.ppi_vertex2gene[seed] for seed in cami.seed_lst]
                             
@@ -278,20 +279,23 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
         rediscovery_rates_results = [results[0] for results in variation_results]
 #        print(rediscovery_rates_results)
         tools = [tool for tool in rediscovery_rates_results[0].keys()]
-        for idx,tool in enumerate(tools):
-            if '_' in tool:
-                tmp_lst = tool.split('_')
-                linebreak_pos = len(tmp_lst)//2
-                added_linebreak_lst = tmp_lst[:linebreak_pos] + ['\n'] + tmp_lst[linebreak_pos]
-                tools[idx] = ''.join(added_linebreak_lst)
+        tool_labels = tools.copy()
         redisc_rates = [[res[tool] for res in rediscovery_rates_results] for tool in tools]
+        for idx,tool in enumerate(tool_labels):
+            if '_' in tool:
+                # find the index of the second occurrence of the character
+                second_occurrence_index = tool.find('_', tool.find('_') + 1)
+                if second_occurrence_index > -1:
+                    # replace the character at that index with the replacement character
+                    tool_name = tool[:second_occurrence_index] + '\n' + tool[second_occurrence_index + 1:]
+
+                    tool_labels[idx] = tool_name
         
 
         #PLOT
         
         # Create a figure instance
-        plt.figure(figsize=(50,8))
-        
+        plt.figure(figsize=(48,12))
         # Extract Figure and Axes instance
         ax1 = plt.subplot(1,2,1, label='ax1')
 
@@ -303,10 +307,11 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
         for violin in violins1['bodies']:
             violin.set_facecolor('red')
         # Add title
-        ax1.set_title(f'Rediscovery rate after randomly removing {nof_removals} seeds\n{nof_iterations} times from {identifier} seeds.', wrap=True)
+        ax1.set_title(f'Rediscovery rate after randomly removing {nof_removals} seeds {nof_iterations} times from {identifier} seeds.', wrap=True, fontsize=14)
 
         ax1.set_xticks(list(range(1,len(tools)+1)))
-        ax1.set_xticklabels(tools)
+        ax1.set_xticklabels(tool_labels)
+        ax1.tick_params(axis='x', labelsize=11)
 
         ax1.set_ylabel('Rediscovery rate (<rediscovered seeds>/<removed seeds>)', wrap=True)
         
@@ -332,12 +337,13 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
             
         for violin in violins3['bodies']:
             violin.set_facecolor('blue')
-        ax5.set_title(f'Ratio of number of rediscovered seeds and predicted module size\nafter removing {nof_removals} seeds {nof_iterations} times from {identifier} seeds.', wrap=True)
+        ax5.set_title(f'Ratio of number of rediscovered seeds and predicted module size after removing {nof_removals} seeds {nof_iterations} times from {identifier} seeds.', wrap=True, fontsize=14)
 
         ax5.set_xticks(list(range(1,len(tools)+1)))
-        ax5.set_xticklabels(tools)
+        ax5.set_xticklabels(tool_labels)
         
         ax5.set_ylabel('(<rediscovered seeds>/<module size>)')
+        ax5.tick_params(axis='x', labelsize=11)
         plt.tight_layout
         plt.savefig(f'{output_dir}/00_{identifier}_seed_variation_result.png')