Coverage for credoai/modules/metric_utils.py: 25%

1import textwrap 

2from collections import defaultdict 

3 

4from credoai.modules.metrics import ALL_METRICS, MODEL_METRIC_CATEGORIES 

5from pandas import DataFrame 

6 

7 

8def list_metrics(verbose=True): 

9 metrics = defaultdict(set) 

10 for metric in ALL_METRICS: 

11 if metric.metric_category in MODEL_METRIC_CATEGORIES: 

12 metrics[metric.metric_category] |= metric.equivalent_names 

13 if verbose: 

14 for key, val in metrics.items(): 

15 metric_str = textwrap.fill( 

16 ", ".join(sorted(list(val))), 

17 width=50, 

18 initial_indent="\t", 

19 subsequent_indent="\t", 

20 ) 

21 print(key) 

22 print(metric_str) 

23 print("") 

24 return metrics 

25 

26 

27def table_metrics(): 

28 output = DataFrame( 

29 [ 

30 [ 

31 metric.name, 

32 metric.metric_category, 

33 list(metric.equivalent_names), 

34 metric.get_fun_doc, 

35 ] 

36 for metric in ALL_METRICS 

37 ], 

38 columns=["metric_name", "metric_category", "synonyms", "doc"], 

39 ) 

40 

41 def remove(list1, str1): 

42 list1 = [x for x in list1 if x != str1] 

43 return list1 

44 

45 output["synonyms"] = output.apply( 

46 lambda row: remove(row.synonyms, row.metric_name), axis=1 

47 ) 

48 output["synonyms"] = output.synonyms.apply(lambda x: ", ".join(x)) 

49 return output