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

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5""" 

6Small wrapper functions for dabl plotting functions via mlos_bench data. 

7""" 

8from typing import Dict, Optional, Literal 

9 

10import warnings 

11 

12import dabl 

13import pandas 

14 

15from mlos_bench.storage.base_experiment_data import ExperimentData 

16 

17from mlos_viz.util import expand_results_data_args 

18 

19 

20def plot(exp_data: Optional[ExperimentData] = None, *, 

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

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

23 ) -> None: 

24 """ 

25 Plots the Experiment results data using dabl. 

26 

27 Parameters 

28 ---------- 

29 exp_data : ExperimentData 

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

31 results_df : Optional["pandas.DataFrame"] 

32 Optional results_df to plot. 

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

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

35 Optional objectives to plot. 

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

37 """ 

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

39 for obj_col in obj_cols: 

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

41 

42 

43def ignore_plotter_warnings() -> None: 

44 """ 

45 Add some filters to ignore warnings from the plotter. 

46 """ 

47 # pylint: disable=import-outside-toplevel 

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

49 warnings.filterwarnings("ignore", module="dabl", category=UserWarning, message="Could not infer format") 

50 warnings.filterwarnings("ignore", module="dabl", category=UserWarning, message="(Dropped|Discarding) .* outliers") 

51 warnings.filterwarnings("ignore", module="dabl", category=UserWarning, message="Not plotting highly correlated") 

52 warnings.filterwarnings("ignore", module="dabl", category=UserWarning, 

53 message="Missing values in target_col have been removed for regression") 

54 from sklearn.exceptions import UndefinedMetricWarning 

55 warnings.filterwarnings("ignore", module="sklearn", category=UndefinedMetricWarning, message="Recall is ill-defined") 

56 warnings.filterwarnings("ignore", category=DeprecationWarning, 

57 message="is_categorical_dtype is deprecated and will be removed in a future version.") 

58 warnings.filterwarnings("ignore", category=DeprecationWarning, module="sklearn", 

59 message="is_sparse is deprecated and will be removed in a future version.") 

60 from matplotlib._api.deprecation import MatplotlibDeprecationWarning 

61 warnings.filterwarnings("ignore", category=MatplotlibDeprecationWarning, module="dabl", 

62 message="The legendHandles attribute was deprecated in Matplotlib 3.7 and will be removed")