o xi @sfdZddlmZddlZddlZddlmZmZede dd ddZ       dd d Z dS)z4Define plots used by multiple sklearn model classes.) simplefilterN) calculateutilsignore)actioncategoryc Csntj|||||d}tj|||||d}t|}|r1|r3|r5t|||||}td|idSdSdSdS)atLogs a chart depicting summary metrics for a model. Should only be called with a fitted model (otherwise an error is thrown). Args: model: (clf or reg) Takes in a fitted regressor or classifier. X: (arr) Training set features. y: (arr) Training set labels. X_test: (arr) Test set features. y_test: (arr) Test set labels. Returns: None: To see plots, go to your W&B run page then expand the 'media' tab under 'auto visualizations'. Example: ```python wandb.sklearn.plot_summary_metrics(model, X_train, y_train, X_test, y_test) ``` )modelXyX_testy_testsummary_metricsN)r test_missing test_types test_fittedrr wandblog) rr r r r not_missing correct_types model_fitted metrics_chartrY/home/ubuntu/.local/lib/python3.10/site-packages/wandb/integration/sklearn/plot/shared.pyr s     r Fc Cs|tj|||d} tj|||d} | r:| r<|durtddd}t|}t||||||||| } t d| idSdSdS)aLogs a plot depicting model performance against dataset size. Please note this function fits the model to datasets of varying sizes when called. Args: model: (clf or reg) Takes in a fitted regressor or classifier. X: (arr) Dataset features. y: (arr) Dataset labels. For details on the other keyword arguments, see the documentation for `sklearn.model_selection.learning_curve`. Returns: None: To see plots, go to your W&B run page then expand the 'media' tab under 'auto visualizations'. Example: ```python wandb.sklearn.plot_learning_curve(model, X, y) ``` )rr r Ng?g?learning_curve) rrrnplinspaceasarrayrrrr) rr r cvshuffle random_state train_sizesn_jobsscoringrrlearning_curve_chartrrrr0s  r)NNNNN) NNNNFNNrN) __doc__warningsrnumpyrrwandb.integration.sklearnrr FutureWarningr rrrrrs"   #