# Copyright (c) 2023 Predibase, Inc., 2019 Uber Technologies, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """ludwig.visualize package — backward-compatible re-exports. All public and private symbols that were importable from ``ludwig.visualize`` when it was a single module remain importable from this package. """ # --------------------------------------------------------------------------- # Private helpers / data-loading utilities # --------------------------------------------------------------------------- from ludwig.visualize._utils import ( _convert_ground_truth, _CSV_SUFFIX, _encode_categorical_feature, _extract_ground_truth_values, _get_cols_from_predictions, _get_ground_truth_df, _load_training_stats, _PARQUET_SUFFIX, _PREDICTIONS_SUFFIX, _PROBABILITIES_SUFFIX, _validate_output_feature_name_from_test_stats, _validate_output_feature_name_from_train_stats, _vectorize_ground_truth, convert_to_list, generate_filename_template_path, load_data_for_viz, load_training_stats_for_viz, validate_conf_thresholds_and_probabilities_2d_3d, ) # --------------------------------------------------------------------------- # CLI entry point + registry # --------------------------------------------------------------------------- from ludwig.visualize.cli import ( cli, get_visualizations_registry, ) # --------------------------------------------------------------------------- # Confusion matrix # --------------------------------------------------------------------------- from ludwig.visualize.confusion import ( confusion_matrix, confusion_matrix_cli, ) # --------------------------------------------------------------------------- # ROC, precision-recall, calibration curves # --------------------------------------------------------------------------- from ludwig.visualize.curves import ( calibration_1_vs_all, calibration_1_vs_all_cli, calibration_multiclass, calibration_multiclass_cli, precision_recall_curves, precision_recall_curves_cli, precision_recall_curves_from_test_statistics, precision_recall_curves_from_test_statistics_cli, roc_curves, roc_curves_cli, roc_curves_from_test_statistics, roc_curves_from_test_statistics_cli, ) # --------------------------------------------------------------------------- # Hyperopt # --------------------------------------------------------------------------- from ludwig.visualize.hyperopt import ( _convert_space_to_dtype, hyperopt_hiplot, hyperopt_hiplot_cli, hyperopt_report, hyperopt_report_cli, hyperopt_results_to_dataframe, ) # --------------------------------------------------------------------------- # Performance comparisons + frequency # --------------------------------------------------------------------------- from ludwig.visualize.performance import ( compare_classifiers_multiclass_multimetric, compare_classifiers_multiclass_multimetric_cli, compare_classifiers_performance_changing_k, compare_classifiers_performance_changing_k_cli, compare_classifiers_performance_from_pred, compare_classifiers_performance_from_pred_cli, compare_classifiers_performance_from_prob, compare_classifiers_performance_from_prob_cli, compare_classifiers_performance_subset, compare_classifiers_performance_subset_cli, compare_classifiers_predictions, compare_classifiers_predictions_cli, compare_classifiers_predictions_distribution, compare_classifiers_predictions_distribution_cli, compare_performance, compare_performance_cli, frequency_vs_f1, frequency_vs_f1_cli, ) # --------------------------------------------------------------------------- # Confidence thresholding + binary threshold # --------------------------------------------------------------------------- from ludwig.visualize.threshold import ( binary_threshold_vs_metric, binary_threshold_vs_metric_cli, confidence_thresholding, confidence_thresholding_2thresholds_2d, confidence_thresholding_2thresholds_2d_cli, confidence_thresholding_2thresholds_3d, confidence_thresholding_2thresholds_3d_cli, confidence_thresholding_cli, confidence_thresholding_data_vs_acc, confidence_thresholding_data_vs_acc_cli, confidence_thresholding_data_vs_acc_subset, confidence_thresholding_data_vs_acc_subset_cli, confidence_thresholding_data_vs_acc_subset_per_class, confidence_thresholding_data_vs_acc_subset_per_class_cli, ) # --------------------------------------------------------------------------- # Training / learning curves # --------------------------------------------------------------------------- from ludwig.visualize.training import ( learning_curves, learning_curves_cli, ) __all__ = [ # constants "_PREDICTIONS_SUFFIX", "_PROBABILITIES_SUFFIX", "_CSV_SUFFIX", "_PARQUET_SUFFIX", # private helpers "_convert_ground_truth", "_vectorize_ground_truth", "_encode_categorical_feature", "_get_ground_truth_df", "_extract_ground_truth_values", "_get_cols_from_predictions", "_load_training_stats", "_validate_output_feature_name_from_train_stats", "_validate_output_feature_name_from_test_stats", # public utils "validate_conf_thresholds_and_probabilities_2d_3d", "load_data_for_viz", "load_training_stats_for_viz", "convert_to_list", "generate_filename_template_path", # training "learning_curves_cli", "learning_curves", # performance "compare_performance_cli", "compare_performance", "compare_classifiers_performance_from_prob_cli", "compare_classifiers_performance_from_prob", "compare_classifiers_performance_from_pred_cli", "compare_classifiers_performance_from_pred", "compare_classifiers_performance_subset_cli", "compare_classifiers_performance_subset", "compare_classifiers_performance_changing_k_cli", "compare_classifiers_performance_changing_k", "compare_classifiers_multiclass_multimetric_cli", "compare_classifiers_multiclass_multimetric", "compare_classifiers_predictions_cli", "compare_classifiers_predictions", "compare_classifiers_predictions_distribution_cli", "compare_classifiers_predictions_distribution", "frequency_vs_f1_cli", "frequency_vs_f1", # threshold "confidence_thresholding_cli", "confidence_thresholding", "confidence_thresholding_data_vs_acc_cli", "confidence_thresholding_data_vs_acc", "confidence_thresholding_data_vs_acc_subset_cli", "confidence_thresholding_data_vs_acc_subset", "confidence_thresholding_data_vs_acc_subset_per_class_cli", "confidence_thresholding_data_vs_acc_subset_per_class", "confidence_thresholding_2thresholds_2d_cli", "confidence_thresholding_2thresholds_2d", "confidence_thresholding_2thresholds_3d_cli", "confidence_thresholding_2thresholds_3d", "binary_threshold_vs_metric_cli", "binary_threshold_vs_metric", # curves "precision_recall_curves_cli", "precision_recall_curves", "precision_recall_curves_from_test_statistics_cli", "precision_recall_curves_from_test_statistics", "roc_curves_cli", "roc_curves", "roc_curves_from_test_statistics_cli", "roc_curves_from_test_statistics", "calibration_1_vs_all_cli", "calibration_1_vs_all", "calibration_multiclass_cli", "calibration_multiclass", # confusion "confusion_matrix_cli", "confusion_matrix", # hyperopt "hyperopt_report_cli", "hyperopt_report", "hyperopt_hiplot_cli", "hyperopt_hiplot", "_convert_space_to_dtype", "hyperopt_results_to_dataframe", # cli "get_visualizations_registry", "cli", ]