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Functions675 in github.com/COVIDAnalytics/DELPHI

↓ 1 callersMethodsave_all_datasets
(self, save_since_100_cases=False, website=False)
archive/V1 - No Jump/DELPHI_utils.py:30
↓ 1 callersMethodsave_all_datasets
(self, i, save_since_100_cases=False, website=False)
archive/backtesting_archived/DELPHI_backtest_utils_ventilator.py:42
↓ 1 callersMethodsave_all_datasets_continuous_retraining
(self, save_since_100_cases=False, website=False)
archive/V1 - No Jump/DELPHI_utils.py:61
↓ 1 callersMethodsave_policy_predictions_to_dict_pickle
(self, website=False, local_delphi=False)
archive/V1 - No Jump/DELPHI_utils.py:141
↓ 1 callersMethodsave_policy_predictions_to_json
Saves the policy predictions as a JSON file based on the different flags :param website: boolean, whether or not we want to save the
DELPHI_utils_V4_static.py:129
↓ 1 callersMethodsave_policy_predictions_to_json
Saves the policy predictions as a JSON file based on the different flags :param website: boolean, whether or not we want to save the
archive/V3 Model/DELPHI_utils_V3_static.py:97
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
DELPHI_model_V4_predict.py:246
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
DELPHI_model_V4.py:357
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
DELPHI_model_V4_with_policies.py:257
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
Connecticut/DELPHI_model_HHC.py:299
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
Connecticut/DELPHI_model_CT.py:345
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
KIT/DELPHI_model_KIT.py:270
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
CDC/DELPHI_model_CDC.py:267
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V1 - No Jump/DELPHI_model.py:219
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V1 - No Jump/DELPHI_policy_predictions_international_V1.py:213
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_model_V3_trust.py:244
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_model_V3_annealing.py:267
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Test Models for V3/ArcTan Jump/DELPHI_model_V4.py:258
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Test Models for V3/Discrete Jump/DELPHI_model_V2.py:247
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/backtesting_archived/DELPHI_backtest_old.py:201
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/backtesting_archived/DELPHI_backtest_model_ventilator.py:235
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/backtesting_archived/DELPHI_backtest_scenarios.py:190
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/backtesting_archived/DELPHI_backtest_scenarios_reopening.py:171
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Adaptive Policy Model - Continuous Retraining/DELPHI_model_cr_with_policies.py:949
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Adaptive Policy Model - Continuous Retraining/DELPHI_policy_predictions_international_with_cr.py:567
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V3 Model/DELPHI_model_V3_with_policies.py:261
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V3 Model/DELPHI_model_V3_serology.py:351
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V3 Model/DELPHI_model_V3.py:343
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/V3 Model/DELPHI_model_V3_predict.py:228
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Other Analyses/DELPHI_secondwave.py:246
↓ 1 callersFunctionsolve_best_params_and_predict
(optimal_params)
archive/Other Analyses/DELPHI_model_with_testing_US_only.py:269
↓ 1 callersFunctionupdate_n_params_fitted_without_policy_change
When we do not update the policy (i.e. there hasn't been any change in policy) then both current_policy and last_policy are susceptible to ch
archive/Adaptive Policy Model - Continuous Retraining/DELPHI_policies_utils_cr.py:89
↓ 1 callersFunctionupdate_tracking_fitted_params
( df_updated: pd.DataFrame, n_policy_shifts_fitted: int, new_best_params_fitted_polici
archive/Adaptive Policy Model - Continuous Retraining/DELPHI_policies_utils_cr.py:289
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str,
DELPHI_utils_V4_static.py:19
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, be
DELPHI_utils_V4_static.py:248
Method__init__
( self, path_to_folder_danger_map: str, prediction_date: str, n_days_backtest: int, ge
DELPHI_utils_V4_static.py:1620
Method__init__
( self, path_to_folder_danger_map: str, path_to_folder_data_sandbox: str, glob
DELPHI_utils_V4_dynamic.py:828
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str,
Connecticut/DELPHI_utils_CT_static.py:19
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, be
Connecticut/DELPHI_utils_CT_static.py:248
Method__init__
( self, path_to_folder_danger_map: str, prediction_date: str, n_days_backtest: int, ge
Connecticut/DELPHI_utils_CT_static.py:1689
Method__init__
( self, path_to_folder_danger_map: str, path_to_folder_data_sandbox: str, glob
Connecticut/DELPHI_utils_CT_dynamic.py:837
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
KIT/DELPHI_utils_KIT.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
KIT/DELPHI_utils_KIT.py:122
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
CDC/DELPHI_utils_CDC.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
CDC/DELPHI_utils_CDC.py:122
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/V1 - No Jump/DELPHI_utils.py:15
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/V1 - No Jump/DELPHI_utils.py:177
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_trust.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_trust.py:149
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_annealing.py:15
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_annealing.py:147
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Test Models for V3/ArcTan Jump/DELPHI_utils_V4.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Test Models for V3/ArcTan Jump/DELPHI_utils_V4.py:149
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Test Models for V3/Discrete Jump/DELPHI_utils_V2.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Test Models for V3/Discrete Jump/DELPHI_utils_V2.py:149
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/backtesting_archived/DELPHI_backtest_utils_ventilator.py:29
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/backtesting_archived/DELPHI_backtest_utils_ventilator.py:157
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str,
archive/V3 Model/DELPHI_utils_V3_static_serology.py:19
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, be
archive/V3 Model/DELPHI_utils_V3_static_serology.py:216
Method__init__
( self, path_to_folder_danger_map: str, prediction_date: str, n_days_backtest: int, ge
archive/V3 Model/DELPHI_utils_V3_static_serology.py:1591
Method__init__
( self, path_to_folder_danger_map: str, path_to_folder_data_sandbox: str, glob
archive/V3 Model/DELPHI_utils_V3_dynamic.py:819
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str,
archive/V3 Model/DELPHI_utils_V3_static.py:19
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, be
archive/V3 Model/DELPHI_utils_V3_static.py:216
Method__init__
( self, path_to_folder_danger_map: str, prediction_date: str, n_days_backtest: int, ge
archive/V3 Model/DELPHI_utils_V3_static.py:1587
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Other Analyses/DELPHI_utils_secondwave.py:15
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Other Analyses/DELPHI_utils_secondwave.py:177
Method__init__
( self, path_to_folder_danger_map: str, path_to_website_predicted: str, df
archive/Other Analyses/DELPHI_utils_new.py:14
Method__init__
( self, x_sol_final: np.array, date_day_since100: datetime, best_params: np.array, con
archive/Other Analyses/DELPHI_utils_new.py:145
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
KIT/DELPHI_utils_KIT.py:949
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
CDC/DELPHI_utils_CDC.py:948
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_trust.py:976
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_annealing.py:1197
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Test Models for V3/ArcTan Jump/DELPHI_utils_V4.py:976
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Test Models for V3/Discrete Jump/DELPHI_utils_V2.py:974
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/backtesting_archived/DELPHI_backtest_utils_ventilator.py:1011
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Other Analyses/DELPHI_utils_secondwave.py:1021
Functionadd_aggregations_backtest
(df_backtest_performance: pd.DataFrame)
archive/Other Analyses/DELPHI_utils_new.py:971
Methodappend_all_aggregations
Creates and appends all the predictions' aggregations at the country, continent and world levels :param df_predictions: dataframe wit
DELPHI_utils_V4_static.py:1223
Methodappend_all_aggregations
Creates and appends all the policy predictions' aggregations at the country, continent and world levels :param df_predictions: datafr
DELPHI_utils_V4_static.py:1595
Methodappend_all_aggregations
Creates and appends all the predictions' aggregations at the country, continent and world levels :param df_predictions: dataframe wit
Connecticut/DELPHI_utils_CT_static.py:1292
Methodappend_all_aggregations
Creates and appends all the policy predictions' aggregations at the country, continent and world levels :param df_predictions: datafr
Connecticut/DELPHI_utils_CT_static.py:1664
Methodappend_all_aggregations
(df: pd.DataFrame)
KIT/DELPHI_utils_KIT.py:458
Methodappend_all_aggregations
(df: pd.DataFrame)
CDC/DELPHI_utils_CDC.py:458
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/V1 - No Jump/DELPHI_utils.py:528
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_trust.py:485
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_annealing.py:627
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Test Models for V3/Normal Jump + Trust Solver/DELPHI_utils_V3_annealing.py:675
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Test Models for V3/ArcTan Jump/DELPHI_utils_V4.py:485
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Test Models for V3/Discrete Jump/DELPHI_utils_V2.py:483
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/backtesting_archived/DELPHI_backtest_utils_ventilator.py:562
Methodappend_all_aggregations
Creates and appends all the predictions' aggregations at the country, continent and world levels :param df_predictions: dataframe wit
archive/V3 Model/DELPHI_utils_V3_static_serology.py:1195
Methodappend_all_aggregations
Creates and appends all the policy predictions' aggregations at the country, continent and world levels :param df_predictions: datafr
archive/V3 Model/DELPHI_utils_V3_static_serology.py:1566
Methodappend_all_aggregations
Creates and appends all the policy predictions' aggregations at the country, continent and world levels :param df_predictions: datafr
archive/V3 Model/DELPHI_utils_V3_static.py:1562
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Other Analyses/DELPHI_utils_secondwave.py:482
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Other Analyses/DELPHI_utils_secondwave.py:530
Methodappend_all_aggregations
(df: pd.DataFrame)
archive/Other Analyses/DELPHI_utils_new.py:480
Methodappend_all_aggregations_cf
Creates and appends all the predictions' aggregations & Confidnece Intervals at the country, continent and world levels :para
Connecticut/DELPHI_utils_CT_static.py:1560
Methodappend_all_aggregations_cf
Creates and appends all the predictions' aggregations & Confidnece Intervals at the country, continent and world levels :para
archive/V3 Model/DELPHI_utils_V3_static_serology.py:1462
Methodcompare_metric
Computes the given metric for predictions with annealing and tnc and the MAPE for annealing. Returns the metrics along with a flag sh
Connecticut/DELPHI_utils_CT_dynamic.py:910
Functioncompute_mape_daily_delta_since_last_train
Computed the Mean Absolute Percentage Error between the daily differences of prediction between a previous train and a current train true/pre
DELPHI_utils_V4_static.py:1960
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