Coverage for mlos_viz/mlos_viz/dabl.py: 100%

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5"""Small wrapper functions for dabl plotting functions via mlos_bench data.""" 

6import warnings 

7from typing import Dict, Literal, Optional 

8 

9import dabl 

10import pandas 

11 

12from mlos_bench.storage.base_experiment_data import ExperimentData 

13from mlos_viz.util import expand_results_data_args 

14 

15 

16def plot( 

17 exp_data: Optional[ExperimentData] = None, 

18 *, 

19 results_df: Optional[pandas.DataFrame] = None, 

20 objectives: Optional[Dict[str, Literal["min", "max"]]] = None, 

21) -> None: 

22 """ 

23 Plots the Experiment results data using dabl. 

24 

25 Parameters 

26 ---------- 

27 exp_data : ExperimentData 

28 The ExperimentData (e.g., obtained from the storage layer) to plot. 

29 results_df : Optional["pandas.DataFrame"] 

30 Optional results_df to plot. 

31 If not provided, defaults to exp_data.results_df property. 

32 objectives : Optional[Dict[str, Literal["min", "max"]]] 

33 Optional objectives to plot. 

34 If not provided, defaults to exp_data.objectives property. 

35 """ 

36 (results_df, obj_cols) = expand_results_data_args(exp_data, results_df, objectives) 

37 for obj_col in obj_cols: 

38 dabl.plot(X=results_df, target_col=obj_col) 

39 

40 

41def ignore_plotter_warnings() -> None: 

42 """Add some filters to ignore warnings from the plotter.""" 

43 # pylint: disable=import-outside-toplevel 

44 warnings.filterwarnings("ignore", category=FutureWarning) 

45 warnings.filterwarnings( 

46 "ignore", 

47 module="dabl", 

48 category=UserWarning, 

49 message="Could not infer format", 

50 ) 

51 warnings.filterwarnings( 

52 "ignore", 

53 module="dabl", 

54 category=UserWarning, 

55 message="(Dropped|Discarding) .* outliers", 

56 ) 

57 warnings.filterwarnings( 

58 "ignore", 

59 module="dabl", 

60 category=UserWarning, 

61 message="Not plotting highly correlated", 

62 ) 

63 warnings.filterwarnings( 

64 "ignore", 

65 module="dabl", 

66 category=UserWarning, 

67 message="Missing values in target_col have been removed for regression", 

68 ) 

69 from sklearn.exceptions import UndefinedMetricWarning 

70 

71 warnings.filterwarnings( 

72 "ignore", 

73 module="sklearn", 

74 category=UndefinedMetricWarning, 

75 message="Recall is ill-defined", 

76 ) 

77 warnings.filterwarnings( 

78 "ignore", 

79 category=DeprecationWarning, 

80 message="is_categorical_dtype is deprecated and will be removed in a future version.", 

81 ) 

82 warnings.filterwarnings( 

83 "ignore", 

84 category=DeprecationWarning, 

85 module="sklearn", 

86 message="is_sparse is deprecated and will be removed in a future version.", 

87 ) 

88 from matplotlib._api.deprecation import MatplotlibDeprecationWarning 

89 

90 warnings.filterwarnings( 

91 "ignore", 

92 category=MatplotlibDeprecationWarning, 

93 module="dabl", 

94 message="The legendHandles attribute was deprecated in Matplotlib 3.7 and will be removed", 

95 )