[ENH] made sure everything has the same number of digits after decimal point

Author: hadifawaz1999

MCM/MCM.py

@@ -282,7 +282,7 @@ def get_heatmap(analysis=None,
 
                 string_to_add = ''
 
-                string_to_add = string_to_add + str(round(pairwise_content['mean'],4))
+                string_to_add = string_to_add + str(format(round(pairwise_content['mean'],4), '.4f'))
                 string_to_add = string_to_add + '\n'
                 n_info_per_line += 1
 
@@ -296,16 +296,16 @@ def get_heatmap(analysis=None,
 
                 if 'p_x_wins' in pairwise_keys:
 
-                    string_to_add = string_to_add + str(round(pairwise_content['p-x-wins'],4)) + ' / '
-                    string_to_add = string_to_add + str(round(pairwise_content['p-rope'],4)) + ' / '
-                    string_to_add = string_to_add + str(round(pairwise_content['p-y-wins'],4))
+                    string_to_add = string_to_add + str(format(round(pairwise_content['p-x-wins'],4), '.4f')) + ' / '
+                    string_to_add = string_to_add + str(format(round(pairwise_content['p-rope'],4), '.4f')) + ' / '
+                    string_to_add = string_to_add + str(format(round(pairwise_content['p-y-wins'],4), '.4f'))
                     string_to_add = string_to_add + '\n'
                     n_info_per_line += 1
 
                 if 'pvalue' in pairwise_keys:
 
                     string_to_add = string_to_add 
-                    _p_value = round(pairwise_content['pvalue'],4)
+                    _p_value = format(round(pairwise_content['pvalue'],4), '.4f')
                     if _p_value == 0:
                         string_to_add = string_to_add + "< " + str(1e-4)
                     else:
@@ -694,7 +694,7 @@ def _get_line_heatmap(proposed_method,
 
         string_to_add = ''
 
-        string_to_add = string_to_add + str(round(pairwise_content['mean'],4))
+        string_to_add = string_to_add + str(format(round(pairwise_content['mean'],4), '.4f'))
         string_to_add = string_to_add + '\n'
         n_info_per_line += 1
 
@@ -708,16 +708,16 @@ def _get_line_heatmap(proposed_method,
 
         if 'p_x_wins' in pairwise_keys:
 
-            string_to_add = string_to_add + str(round(pairwise_content['p-x-wins'],4)) + ' / '
-            string_to_add = string_to_add + str(round(pairwise_content['p-rope'],4)) + ' / '
-            string_to_add = string_to_add + str(round(pairwise_content['p-y-wins'],4))
+            string_to_add = string_to_add + str(format(round(pairwise_content['p-x-wins'],4), '.4f')) + ' / '
+            string_to_add = string_to_add + str(format(round(pairwise_content['p-rope'],4), '.4f')) + ' / '
+            string_to_add = string_to_add + str(format(round(pairwise_content['p-y-wins'],4), '.4f'))
             string_to_add = string_to_add + '\n'
             n_info_per_line += 1
 
         if 'pvalue' in pairwise_keys:
 
             string_to_add = string_to_add 
-            _p_value = round(pairwise_content['pvalue'],4)
+            _p_value = format(round(pairwise_content['pvalue'],4), '.4f')
             if _p_value == 0:
                 string_to_add = string_to_add + "< " + str(1e-4)
             else:

MCM/utils.py

@@ -172,7 +172,7 @@ def re_order_classifiers(df_results, analysis):
             np_results = np.asarray(df_results.drop([analysis['dataset-column']],axis=1))
         else:
             np_results = np.asarray(df_results)
-            
+
         df = pd.DataFrame(columns=['classifier-name','values'])
 
         for i, classifier_name in enumerate(analysis['classifier-names']):
@@ -268,7 +268,7 @@ def get_ticks(analysis):
 
     for i in range(analysis['n-classifiers']):
         yticks.append(analysis['ordered-classifier-names'][i])
-        xticks.append(analysis['ordered-classifier-names'][i] + '\n' + ordering + str(round(analysis['ordered-stats'][i], 4)))
+        xticks.append(analysis['ordered-classifier-names'][i] + '\n' + ordering + str(format(round(analysis['ordered-stats'][i], 4), '.4f')))
 
         if first_tick:
             first_tick = False
@@ -310,10 +310,10 @@ def get_ticks_heatline(analysis, proposed_method):
     for i in range(analysis['n-classifiers']):
 
         if analysis['ordered-classifier-names'][i] == proposed_method:
-            yticks.append(proposed_method)
+            yticks.append(proposed_method+'\n'+str(format(round(analysis['ordered-stats'][i], 4), '.4f')))
 
         else:
-            xticks.append(analysis['ordered-classifier-names'][i] + '\n' + ordering + str(round(analysis['ordered-stats'][i], 4)))
+            xticks.append(analysis['ordered-classifier-names'][i] + '\n' + ordering + str(format(round(analysis['ordered-stats'][i], 4), '.4f')))
 
         if first_tick:
             first_tick = False

main.py

@@ -12,13 +12,11 @@
     analysis = MCM.get_analysis(df_results=df_results,
                                      save_as_json=True,
                                      plot_1v1_comparisons=False,
-                                     output_dir=output_dir,
-                                     order_stats='average-rank')
+                                     output_dir=output_dir)
 
     MCM.get_heatmap(output_dir=output_dir,
                          colormap='coolwarm',
                          show_symetry=True)
 
     MCM.get_line_heatmap(proposed_methods=['clf1','clf2'],
-                         order_stats='average-rank',
                          output_dir=output_dir)