API Reference

• pyESD Documentation
  • Submodules
  • pyESD.StationOperator module
    • StationOperator
      • StationOperator.climate_score()
      • StationOperator.cross_validate_and_predict()
      • StationOperator.ensemble_transform()
      • StationOperator.evaluate()
      • StationOperator.fit()
      • StationOperator.fit_predictor()
      • StationOperator.get_explained_variance()
      • StationOperator.get_var()
      • StationOperator.predict()
      • StationOperator.predictor_correlation()
      • StationOperator.relative_predictor_importance()
      • StationOperator.save()
      • StationOperator.selected_names()
      • StationOperator.set_model()
      • StationOperator.set_predictors()
      • StationOperator.set_standardizer()
      • StationOperator.set_transform()
      • StationOperator.tree_based_feature_importance()
      • StationOperator.tree_based_feature_permutation_importance()
    • load_station()
  • pyESD.ESD_utils module
    • ComputeStat()
    • Dataset
      • Dataset.get()
    • MidpointNormalize
    • StackArray()
    • StatTest()
    • _get_month()
    • extract_indices_around()
    • extract_region()
    • haversine()
    • levene_test()
    • load_all_stations()
    • load_csv()
    • load_pickle()
    • map_to_xarray()
    • plot_background()
    • plot_ks_stats()
    • ranksums_test()
    • store_csv()
    • store_pickle()
  • pyESD.Predictor_Base module
    • Predictor
      • Predictor.fit()
      • Predictor.get()
      • Predictor.load()
      • Predictor.plot()
      • Predictor.save()
  • pyESD.Predictor_Generator module
    • RegionalAverage
  • pyESD.Weatherstation module
    • read_station_csv()
    • read_weatherstationnames()
    • read_weatherstations()
  • pyESD.dense_models module
    • DeepLearningRegressor
      • DeepLearningRegressor.build_model()
      • DeepLearningRegressor.compile_model()
      • DeepLearningRegressor.convert_to_sklearn_regressor()
      • DeepLearningRegressor.fit()
      • DeepLearningRegressor.plot_network()
      • DeepLearningRegressor.predict()
  • pyESD.ensemble_models module
    • EnsembleRegressor
      • EnsembleRegressor.cross_val_predict()
      • EnsembleRegressor.cross_val_score()
      • EnsembleRegressor.cross_validate()
      • EnsembleRegressor.fit()
      • EnsembleRegressor.get_params()
      • EnsembleRegressor.predict()
      • EnsembleRegressor.predict_average()
      • EnsembleRegressor.score()
      • EnsembleRegressor.transform()
  • pyESD.feature_selection module
    • RecursiveFeatureElimination
      • RecursiveFeatureElimination.cv_test_score()
      • RecursiveFeatureElimination.fit()
      • RecursiveFeatureElimination.print_selected_features()
      • RecursiveFeatureElimination.score()
      • RecursiveFeatureElimination.transform()
    • SequentialFeatureSelection
      • SequentialFeatureSelection.fit()
      • SequentialFeatureSelection.print_selected_features()
      • SequentialFeatureSelection.score()
      • SequentialFeatureSelection.transform()
    • TreeBasedSelection
      • TreeBasedSelection.feature_importance()
      • TreeBasedSelection.fit()
      • TreeBasedSelection.permutation_importance_()
      • TreeBasedSelection.print_selected_features()
      • TreeBasedSelection.transform()
  • pyESD.metrics module
    • Evaluate
      • Evaluate.MAE()
      • Evaluate.MSE()
      • Evaluate.NSE()
      • Evaluate.R2_score()
      • Evaluate.RMSE()
      • Evaluate.adjusted_r2()
      • Evaluate.explained_variance()
      • Evaluate.max_error()
  • pyESD.models module
    • HyperparameterOptimize
      • HyperparameterOptimize.best_estimator()
      • HyperparameterOptimize.cross_val_predict()
      • HyperparameterOptimize.cross_val_score()
      • HyperparameterOptimize.cross_validate()
      • HyperparameterOptimize.fit()
      • HyperparameterOptimize.predict_log_proba()
      • HyperparameterOptimize.score()
      • HyperparameterOptimize.transform()
    • MetaAttributes
      • MetaAttributes.alpha()
      • MetaAttributes.best_estimator()
      • MetaAttributes.best_params()
      • MetaAttributes.coef()
      • MetaAttributes.get_params()
      • MetaAttributes.intercept()
      • MetaAttributes.set_params()
    • Regressors
      • Regressors.cross_val_predict()
      • Regressors.cross_val_score()
      • Regressors.cross_validate()
      • Regressors.fit()
      • Regressors.predict()
      • Regressors.score()
      • Regressors.set_model()
  • pyESD.plot module
    • barplot()
    • boxplot()
    • correlation_heatmap()
    • heatmaps()
    • lineplot()
    • plot_monthly_mean()
    • plot_projection_comparison()
    • plot_time_series()
    • scatterplot()
  • pyESD.plot_utils module
    • apply_style()
    • barplot_data()
    • boxplot_data()
    • correlation_data()
    • count_predictors()
    • extract_comparison_data_means()
    • extract_time_series()
    • monthly_mean()
    • prediction_example_data()
    • resample_monthly()
    • resample_seasonally()
    • seasonal_mean()
  • pyESD.predictand module
    • PredictandTimeseries
      • PredictandTimeseries.climate_score()
      • PredictandTimeseries.cross_validate_and_predict()
      • PredictandTimeseries.ensemble_transform()
      • PredictandTimeseries.evaluate()
      • PredictandTimeseries.fit()
      • PredictandTimeseries.fit_predictor()
      • PredictandTimeseries.get()
      • PredictandTimeseries.predict()
      • PredictandTimeseries.predictor_correlation()
      • PredictandTimeseries.relative_predictor_importance()
      • PredictandTimeseries.selected_names()
      • PredictandTimeseries.set_model()
      • PredictandTimeseries.set_predictors()
      • PredictandTimeseries.set_standardizer()
      • PredictandTimeseries.set_transform()
      • PredictandTimeseries.tree_based_feature_importance()
      • PredictandTimeseries.tree_based_feature_permutation_importance()
  • pyESD.splitter module
    • MonthlyBooststrapper
      • MonthlyBooststrapper.split()
    • Splitter
      • Splitter.get_n_splits()
      • Splitter.split()
    • YearlyBootstrapper
      • YearlyBootstrapper.split()
  • pyESD.standardizer module
    • MonthlyStandardizer
      • MonthlyStandardizer.fit()
      • MonthlyStandardizer.inverse_transform()
      • MonthlyStandardizer.transform()
    • NoStandardizer
      • NoStandardizer.fit()
      • NoStandardizer.inverse_transform()
      • NoStandardizer.transform()
    • PCAScaling
      • PCAScaling.fit()
      • PCAScaling.fit_transform()
      • PCAScaling.inverse_transform()
      • PCAScaling.transform()
    • StandardScaling
      • StandardScaling.fit()
      • StandardScaling.inverse_transform()
      • StandardScaling.transform()
    • add_seasonal_cycle()
    • get_annual_mean_cycle()
    • get_mean_prediction()
    • remove_seasonal_cycle()
  • pyESD.teleconnections module
    • EA
      • EA.plot_cov_matrix()
    • EAWR
      • EAWR.plot_cov_matrix()
    • MEI
    • NAO
      • NAO.plot_cov_matrix()
    • SCAN
      • SCAN.plot_cov_matrix()
    • _get_month()
    • eof_analysis()
    • extract_region()
  • pyESD.data_preprocessing_utils module
  • pyESD.MLR module
    • BootstrappedForwardSelection
    • BootstrappedRegression
      • BootstrappedRegression.fit()
      • BootstrappedRegression.fit_predict()
      • BootstrappedRegression.predict()
    • ForwardSelection
      • ForwardSelection.average_additional_results()
      • ForwardSelection.average_coefs()
      • ForwardSelection.fit()
      • ForwardSelection.fit_active()
      • ForwardSelection.predict()
      • ForwardSelection.predict_active()
      • ForwardSelection.set_additional_results()
    • MultipleLSRegression
      • MultipleLSRegression.fit()
      • MultipleLSRegression.predict()
      • MultipleLSRegression.set_expand_coefs()
    • _get_active()

Warning

This package is under active development and would require upgrade to benefit from its extension