energy_fault_detector

The anomaly-detection-iee package

• energy_fault_detector.anomaly_scores
  • energy_fault_detector.anomaly_scores.mahalanobis_score
    • MahalanobisScore
      • MahalanobisScore.fit()
      • MahalanobisScore.transform()
  • energy_fault_detector.anomaly_scores.rmse_score
    • RMSEScore
      • RMSEScore.scale
      • RMSEScore.fit()
      • RMSEScore.transform()
• energy_fault_detector.autoencoders
  • energy_fault_detector.autoencoders.conditional_autoencoder
    • ConditionalAE
      • ConditionalAE.model
      • ConditionalAE.encoder
      • ConditionalAE.history
      • ConditionalAE.create_model()
  • energy_fault_detector.autoencoders.multilayer_autoencoder
    • MultilayerAutoencoder
      • MultilayerAutoencoder.model
      • MultilayerAutoencoder.encoder
      • MultilayerAutoencoder.history
      • MultilayerAutoencoder.create_model()
• energy_fault_detector.config
  • energy_fault_detector.config.base_config
    • BaseConfig
      • BaseConfig.read_config()
      • BaseConfig.update_config()
      • BaseConfig.write_config()
    • InvalidConfigFile
  • energy_fault_detector.config.config
    • Config
      • Config.arcana_params
      • Config.data_clipping
      • Config.data_clipping_params
      • Config.data_split_params
      • Config.dtype
      • Config.fit_threshold_on_val
      • Config.max_criticality
      • Config.root_cause_analysis
      • Config.verbose
  • energy_fault_detector.config.quickstart_config
    • generate_quickstart_config()
• energy_fault_detector.core
  • energy_fault_detector.core.anomaly_score
    • AnomalyScore
      • AnomalyScore.fit()
      • AnomalyScore.transform()
  • energy_fault_detector.core.autoencoder
    • Autoencoder
      • Autoencoder.is_conditional
      • Autoencoder.model
      • Autoencoder.encoder
      • Autoencoder.history
      • Autoencoder.callbacks
      • Autoencoder.__call__()
      • Autoencoder.compile_model()
      • Autoencoder.create_model()
      • Autoencoder.encode()
      • Autoencoder.fit()
      • Autoencoder.get_reconstruction_error()
      • Autoencoder.load()
      • Autoencoder.predict()
      • Autoencoder.save()
      • Autoencoder.tune()
      • Autoencoder.tune_decoder()
    • split_inputs()
  • energy_fault_detector.core.data_transformer
    • DataTransformer
      • DataTransformer.fit()
      • DataTransformer.get_feature_names_out()
      • DataTransformer.inverse_transform()
      • DataTransformer.transform()
  • energy_fault_detector.core.fault_detection_model
    • FaultDetectionModel
      • FaultDetectionModel.anomaly_score
      • FaultDetectionModel.autoencoder
      • FaultDetectionModel.threshold_selector
      • FaultDetectionModel.data_preprocessor
      • FaultDetectionModel.save_timestamps
      • FaultDetectionModel.fit()
      • FaultDetectionModel.load_models()
      • FaultDetectionModel.predict()
      • FaultDetectionModel.save_models()
      • FaultDetectionModel.train()
      • FaultDetectionModel.train_val_split()
    • NoTrainingData
  • energy_fault_detector.core.fault_detection_result
    • FaultDetectionResult
      • FaultDetectionResult.anomaly_score
      • FaultDetectionResult.arcana_losses
      • FaultDetectionResult.bias_data
      • FaultDetectionResult.criticality()
      • FaultDetectionResult.load()
      • FaultDetectionResult.predicted_anomalies
      • FaultDetectionResult.recon_error
      • FaultDetectionResult.reconstruction
      • FaultDetectionResult.save()
      • FaultDetectionResult.tracked_bias
    • ModelMetadata
      • ModelMetadata.model_date
      • ModelMetadata.model_path
      • ModelMetadata.train_recon_error
      • ModelMetadata.val_recon_error
  • energy_fault_detector.core.model_factory
    • ModelFactory
      • ModelFactory.anomaly_score
      • ModelFactory.autoencoder
      • ModelFactory.data_preprocessor
      • ModelFactory.threshold_selector
  • energy_fault_detector.core.save_load_mixin
    • SaveLoadMixin
      • SaveLoadMixin.load()
      • SaveLoadMixin.save()
  • energy_fault_detector.core.threshold_selector
    • ThresholdSelector
      • ThresholdSelector.threshold
      • ThresholdSelector.__sklearn_is_fitted__()
      • ThresholdSelector.fit()
      • ThresholdSelector.predict()
• energy_fault_detector.data_preprocessing
  • energy_fault_detector.data_preprocessing.angle_transformer
    • AngleTransformer
      • AngleTransformer.angles
      • AngleTransformer.trust_bad_angles
      • AngleTransformer.fit()
      • AngleTransformer.get_feature_names_out()
      • AngleTransformer.inverse_transform()
      • AngleTransformer.transform()
  • energy_fault_detector.data_preprocessing.column_selector
    • ColumnSelector
      • ColumnSelector.feature_names_in_
      • ColumnSelector.n_features_in_
      • ColumnSelector.feature_names_out_
      • ColumnSelector.columns_dropped_
      • ColumnSelector.fit()
      • ColumnSelector.get_feature_names_out()
      • ColumnSelector.inverse_transform()
      • ColumnSelector.transform()
  • energy_fault_detector.data_preprocessing.counter_diff_transformer
    • CounterDiffTransformer
      • CounterDiffTransformer.fit()
      • CounterDiffTransformer.get_feature_names_out()
      • CounterDiffTransformer.inverse_transform()
      • CounterDiffTransformer.transform()
  • energy_fault_detector.data_preprocessing.data_clipper
    • DataClipper
      • DataClipper.fit()
      • DataClipper.get_feature_names_out()
      • DataClipper.inverse_transform()
      • DataClipper.transform()
  • energy_fault_detector.data_preprocessing.data_preprocessor
    • DataPreprocessor
      • DataPreprocessor.NAME_ALIASES
      • DataPreprocessor.STEP_REGISTRY
      • DataPreprocessor.fit_transform()
      • DataPreprocessor.inverse_transform()
      • DataPreprocessor.transform()
  • energy_fault_detector.data_preprocessing.duplicate_value_to_nan
    • DuplicateValuesToNan
      • DuplicateValuesToNan.feature_names_in_
      • DuplicateValuesToNan.feature_names_out_
      • DuplicateValuesToNan.fit()
      • DuplicateValuesToNan.get_feature_names_out()
      • DuplicateValuesToNan.inverse_transform()
      • DuplicateValuesToNan.transform()
  • energy_fault_detector.data_preprocessing.low_unique_value_filter
    • LowUniqueValueFilter
      • LowUniqueValueFilter.feature_names_in_
      • LowUniqueValueFilter.n_features_in_
      • LowUniqueValueFilter.feature_names_out_
      • LowUniqueValueFilter.columns_dropped_
      • LowUniqueValueFilter.fit()
      • LowUniqueValueFilter.get_feature_names_out()
      • LowUniqueValueFilter.inverse_transform()
      • LowUniqueValueFilter.transform()
• energy_fault_detector.data_splitting
  • energy_fault_detector.data_splitting.data_splitter
    • BlockDataSplitter
      • BlockDataSplitter.train_selection
      • BlockDataSplitter.val_selection
      • BlockDataSplitter.split()
• energy_fault_detector.evaluation
  • energy_fault_detector.evaluation.care2compare
    • Care2CompareDataset
      • Care2CompareDataset.format_event_dataset()
      • Care2CompareDataset.get_event_info()
      • Care2CompareDataset.iter_datasets()
      • Care2CompareDataset.iter_formatted_datasets()
      • Care2CompareDataset.iter_train_datasets_per_asset()
      • Care2CompareDataset.load_and_format_event_dataset()
      • Care2CompareDataset.load_event_dataset()
      • Care2CompareDataset.update_c2c_config()
  • energy_fault_detector.evaluation.care_score
    • CAREScore
      • CAREScore.calculate_avg_accuracy()
      • CAREScore.calculate_avg_coverage()
      • CAREScore.calculate_avg_earliness()
      • CAREScore.calculate_reliability()
      • CAREScore.create_ground_truth()
      • CAREScore.evaluate_event()
      • CAREScore.evaluated_events
      • CAREScore.get_final_score()
      • CAREScore.load_evaluated_events()
      • CAREScore.save_evaluated_events()
  • energy_fault_detector.evaluation.predist_dataset
    • PreDistDataset
      • PreDistDataset.events
      • PreDistDataset.FAULT_HOURS_AFTER
      • PreDistDataset.FAULT_HOURS_BEFORE
      • PreDistDataset.create_normal_flag()
      • PreDistDataset.get_event_data()
      • PreDistDataset.load_substation_data()
• energy_fault_detector.quick_fault_detection
  • energy_fault_detector.quick_fault_detection.configuration
    • select_config()
    • update_autoencoder_config()
    • update_preprocessor_config()
    • update_threshold_config()
  • energy_fault_detector.quick_fault_detection.data_loading
    • apply_boolean_mapping()
    • detect_encoding()
    • detect_separator()
    • get_boolean_feature()
    • get_sensor_data()
    • load_data()
    • load_train_test_data()
    • read_csv_file()
    • validate_mapping()
  • energy_fault_detector.quick_fault_detection.optimization
    • automatic_hyper_opt()
  • energy_fault_detector.quick_fault_detection.output
    • generate_output_plots()
  • energy_fault_detector.quick_fault_detection.quick_fault_detector
    • analyze_event()
    • quick_fault_detector()
• energy_fault_detector.root_cause_analysis
  • energy_fault_detector.root_cause_analysis.arcana
    • Arcana
      • Arcana.opt
      • Arcana.draw_samples()
      • Arcana.find_arcana_bias()
      • Arcana.initialize_x_bias()
      • Arcana.update_x_bias()
  • energy_fault_detector.root_cause_analysis.arcana_utils
    • calculate_arcana_importance_time_series()
    • calculate_mean_arcana_importances()
• energy_fault_detector.threshold_selectors
  • energy_fault_detector.threshold_selectors.adaptive_threshold
    • AdaptiveThresholdSelector
      • AdaptiveThresholdSelector.fit()
      • AdaptiveThresholdSelector.predict()
    • RegressionNN
      • RegressionNN.create_model()
      • RegressionNN.fit()
      • RegressionNN.predict()
  • energy_fault_detector.threshold_selectors.fbeta_threshold
    • FbetaSelector
      • FbetaSelector.threshold
      • FbetaSelector.fit()
      • FbetaSelector.mark_normal_outliers()
  • energy_fault_detector.threshold_selectors.fdr_threshold
    • FDRSelector
      • FDRSelector.threshold
      • FDRSelector.actual_false_discovery_rate_
      • FDRSelector.fit()
  • energy_fault_detector.threshold_selectors.quantile_threshold
    • QuantileThresholdSelector
      • QuantileThresholdSelector.threshold
      • QuantileThresholdSelector.fit()
• energy_fault_detector.utils
  • energy_fault_detector.utils.analysis
    • calculate_criticality()
    • create_events()
  • energy_fault_detector.utils.data_downloads
    • download_file()
    • download_zenodo_data()
    • fetch_record()
    • list_files()
    • parse_record_id()
    • prepare_output_dir()
    • recursive_safe_extract()
    • safe_extract_zip()
  • energy_fault_detector.utils.visualisation
    • animate_bias()
    • animate_corrected_input()
    • plot_arcana_importance_series()
    • plot_arcana_losses()
    • plot_arcana_mean_importances()
    • plot_learning_curve()
    • plot_reconstruction()
    • plot_reconstruction_with_model()
    • plot_score_with_threshold()

• energy_fault_detector.fault_detector
  • FaultDetector
    • FaultDetector.anomaly_score
    • FaultDetector.autoencoder
    • FaultDetector.threshold_selector
    • FaultDetector.data_preprocessor
    • FaultDetector.save_timestamps
    • FaultDetector.fit()
    • FaultDetector.predict()
    • FaultDetector.predict_anomalies()
    • FaultDetector.predict_anomaly_score()
    • FaultDetector.preprocess_train_data()
    • FaultDetector.run_root_cause_analysis()
    • FaultDetector.tune()
• energy_fault_detector.main
  • Options
    • Options.angle_features
    • Options.automatic_optimization
    • Options.csv_test_data_path
    • Options.enable_debug_plots
    • Options.features_to_exclude
    • Options.min_anomaly_length
    • Options.status_data_column_name
    • Options.status_label_confidence_percentage
    • Options.status_mapping
    • Options.time_column_name
    • Options.train_test_column_name
    • Options.train_test_mapping
  • load_options_from_yaml()
  • main()
• energy_fault_detector.registration
  • Registry
    • Registry.get()
    • Registry.get_alternative_class_names()
    • Registry.print_available_classes()
    • Registry.register()
  • register()