@@ -297,7 +297,7 @@ def convert_list_to_tuple(out):
297297 result = []
298298 for index in range (len (out [0 ])):
299299 val = [x [index ] for x in out ]
300- result .append (tuple (val ))
300+ result .append (tuple (float ( v ) for v in val ))
301301 return concat_tuple (result )
302302
303303info_LOI = ['project' , 'class' , 'method' , 'merge commit' ]
@@ -358,7 +358,7 @@ def convert_list_to_tuple(out):
358358
359359data = {
360360 'Metric' : ['Precision' , 'Recall' , 'F1-score' , 'Accuracy' ],
361- 'Value' : [round (best .higher_precision_value , 2 ), round (best .higher_recall_value , 2 ), round (best .higher_F1_value , 2 ), round (best .higher_accuracy_value , 2 )],
361+ 'Value' : [round (float ( best .higher_precision_value ) , 2 ), round (float ( best .higher_recall_value ) , 2 ), round (float ( best .higher_F1_value ) , 2 ), round (float ( best .higher_accuracy_value ) , 2 )],
362362 'Analyses' : [str (to_string_as_set (get_reverse_name (remove_nested_best (best .higher_precision_analyses_names ))))[:255 ],
363363 str (to_string_as_set (get_reverse_name (remove_nested_best (best .higher_recall_analyses_names ))))[:255 ],
364364 str (to_string_as_set (get_reverse_name (remove_nested_best (best .higher_F1_analyses_names ))))[:255 ],
@@ -490,7 +490,12 @@ def convert_list_to_tuple(out):
490490 actual_dict = best .confusion_matrix (count_fp_fn (m_smaller ), smaller )
491491 l_aux = []
492492 for m in merged_dict ['Metrics' ]:
493- l_aux .append (format (actual_dict [m ], '.2f' ))
493+ #l_aux.append(format(actual_dict[m], '.2f'))
494+ try :
495+ l_aux .append (format (float (actual_dict [m ]), '.2f' ))
496+ except ValueError :
497+ print (f"ValueError: Cannot convert { actual_dict [m ]} to float." )
498+ l_aux .append (actual_dict [m ])
494499
495500 original_name = sum (get_reverse_name ([smaller ]), [])
496501 key = ' or ' .join (original_name )
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