diff --git a/cities/modeling/modeling_utils.py b/cities/modeling/modeling_utils.py index 80eddc8e..af44e993 100644 --- a/cities/modeling/modeling_utils.py +++ b/cities/modeling/modeling_utils.py @@ -9,38 +9,44 @@ from pyro.optim import Adam from scipy.stats import spearmanr - from cities.utils.data_grabber import ( DataGrabber, list_available_features, list_tensed_features, ) + def drop_high_correlation(df, threshold=0.85): - df_var = df.iloc[:,2:].copy() + df_var = df.iloc[:, 2:].copy() correlation_matrix, _ = spearmanr(df_var) - high_correlation_pairs = [(df_var.columns[i], df_var.columns[j]) - for i in range(df_var.shape[1]) - for j in range(i + 1, df_var.shape[1]) - if abs(correlation_matrix[i, j]) > threshold and abs(correlation_matrix[i, j]) < 1.0] - high_correlation_pairs = [(var1, var2) for var1, var2 in high_correlation_pairs if var1 != var2] + high_correlation_pairs = [ + (df_var.columns[i], df_var.columns[j]) + for i in range(df_var.shape[1]) + for j in range(i + 1, df_var.shape[1]) + if abs(correlation_matrix[i, j]) > threshold + and abs(correlation_matrix[i, j]) < 1.0 + ] + high_correlation_pairs = [ + (var1, var2) for var1, var2 in high_correlation_pairs if var1 != var2 + ] removed = set() - print(f"Highly correlated pairs: {high_correlation_pairs}, second elements will be dropped") + print( + f"Highly correlated pairs: {high_correlation_pairs}, second elements will be dropped" + ) for var1, var2 in high_correlation_pairs: assert var2 in df_var.columns for var1, var2 in high_correlation_pairs: if var2 in df_var.columns: removed.add(var2) - df_var.drop(var2, axis =1, inplace=True) + df_var.drop(var2, axis=1, inplace=True) result = pd.concat([df.iloc[:, :2], df_var], axis=1) print(f"Removed {removed} due to correlation > {threshold}") return result - def prep_wide_data_for_inference( outcome_dataset: str, intervention_dataset: str, forward_shift: int ): @@ -115,7 +121,7 @@ def prep_wide_data_for_inference( ) f_covariates_joint = drop_high_correlation(f_covariates_joint) - + assert f_covariates_joint["GeoFIPS"].equals(intervention["GeoFIPS"]) # extract data for which intervention and outcome overlap @@ -198,7 +204,7 @@ def prep_wide_data_for_inference( "y": y, "years_available": years_available, "outcome_years": outcome_years_to_keep, - "covariates_df": f_covariates_joint + "covariates_df": f_covariates_joint, } diff --git a/cities/modeling/training_pipeline.py b/cities/modeling/training_pipeline.py index 38b019ed..3f4ebc72 100644 --- a/cities/modeling/training_pipeline.py +++ b/cities/modeling/training_pipeline.py @@ -84,7 +84,7 @@ remaining -= 1 logging.info( f"Training of {guide_name} completed in {duration:.2f} seconds. " - f"{remaining} out of {N_combinations} guides remain to be trained." + f"{int(remaining)} out of {N_combinations} guides remain to be trained." ) logging.info("All guides are now available.") diff --git a/data/model_guides/.training.log b/data/model_guides/.training.log index c0ed1771..f16ef6cf 100644 --- a/data/model_guides/.training.log +++ b/data/model_guides/.training.log @@ -1,15 +1,452 @@ -<<<<<<< HEAD -2023-11-27 05:02:59 → root → INFO: 248.0 guides already exist. Starting to train 4.0 out of 252 guides needed. -2023-11-27 05:02:59 → root → INFO: Training spending_HHS_medianHouseholdIncome_2 for 4000 iterations. -2023-11-27 05:05:35 → root → INFO: Training of spending_HHS_medianHouseholdIncome_2 completed in 156.07 seconds. 3.0 out of 252 guides remain to be trained. -2023-11-27 05:05:35 → root → INFO: Training spending_HHS_medianHouseholdIncome_3 for 4000 iterations. -2023-11-27 05:06:42 → root → INFO: Training of spending_HHS_medianHouseholdIncome_3 completed in 67.55 seconds. 2.0 out of 252 guides remain to be trained. -2023-11-27 05:06:42 → root → INFO: Training spending_commerce_povertyAllprct_2 for 4000 iterations. -2023-11-27 05:07:50 → root → INFO: Training of spending_commerce_povertyAllprct_2 completed in 67.82 seconds. 1.0 out of 252 guides remain to be trained. -2023-11-27 05:07:50 → root → INFO: Training spending_commerce_povertyAllprct_3 for 4000 iterations. -2023-11-27 05:08:58 → root → INFO: Training of spending_commerce_povertyAllprct_3 completed in 67.89 seconds. 0.0 out of 252 guides remain to be trained. -2023-11-27 05:08:58 → root → INFO: All guides are now available. -======= -2023-11-27 16:33:36 → root → INFO: 252.0 guides already exist. Starting to train -45.0 out of 207 guides needed. -2023-11-27 16:33:36 → root → INFO: All guides are now available. ->>>>>>> 07d87a3d4df13b6d63c34887d05dd2ed00cfacb9 +2024-02-02 11:56:54 → root → INFO: 36.0 guides already exist. Starting to train 225.0 out of 261 guides needed. +2024-02-02 11:56:54 → root → INFO: Training spending_HHS_industry_mining_total_1 for 4000 iterations. +2024-02-02 12:00:41 → root → INFO: Training of spending_HHS_industry_mining_total_1 completed in 226.27 seconds. 224 out of 261 guides remain to be trained. +2024-02-02 12:00:41 → root → INFO: Training spending_HHS_industry_mining_total_2 for 4000 iterations. +2024-02-02 12:04:21 → root → INFO: Training of spending_HHS_industry_mining_total_2 completed in 220.48 seconds. 223 out of 261 guides remain to be trained. +2024-02-02 12:04:21 → root → INFO: Training spending_HHS_industry_mining_total_3 for 4000 iterations. +2024-02-02 12:08:02 → root → INFO: Training of spending_HHS_industry_mining_total_3 completed in 220.68 seconds. 222 out of 261 guides remain to be trained. +2024-02-02 12:08:02 → root → INFO: Training spending_HHS_industry_other_services_total_1 for 4000 iterations. +2024-02-02 12:11:35 → root → INFO: Training of 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4000 iterations. +2024-02-02 15:01:24 → root → INFO: Training of spending_commerce_industry_construction_total_1 completed in 139.96 seconds. 158 out of 261 guides remain to be trained. +2024-02-02 15:01:24 → root → INFO: Training spending_commerce_industry_construction_total_2 for 4000 iterations. +2024-02-02 15:03:44 → root → INFO: Training of spending_commerce_industry_construction_total_2 completed in 139.95 seconds. 157 out of 261 guides remain to be trained. +2024-02-02 15:03:44 → root → INFO: Training spending_commerce_industry_construction_total_3 for 4000 iterations. +2024-02-02 15:06:07 → root → INFO: Training of spending_commerce_industry_construction_total_3 completed in 143.12 seconds. 156 out of 261 guides remain to be trained. +2024-02-02 15:06:07 → root → INFO: Training spending_commerce_industry_educational_services_total_1 for 4000 iterations. +2024-02-02 15:08:26 → root → INFO: Training of spending_commerce_industry_educational_services_total_1 completed in 138.86 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spending_commerce_industry_finance_insurance_total_2 for 4000 iterations. +2024-02-02 15:17:46 → root → INFO: Training of spending_commerce_industry_finance_insurance_total_2 completed in 140.80 seconds. 151 out of 261 guides remain to be trained. +2024-02-02 15:17:46 → root → INFO: Training spending_commerce_industry_finance_insurance_total_3 for 4000 iterations. +2024-02-02 15:20:10 → root → INFO: Training of spending_commerce_industry_finance_insurance_total_3 completed in 143.39 seconds. 150 out of 261 guides remain to be trained. +2024-02-02 15:20:10 → root → INFO: Training spending_commerce_industry_healthcare_social_services_total_1 for 4000 iterations. +2024-02-02 15:22:33 → root → INFO: Training of spending_commerce_industry_healthcare_social_services_total_1 completed in 143.35 seconds. 149 out of 261 guides remain to be trained. +2024-02-02 15:22:33 → root → INFO: Training spending_commerce_industry_healthcare_social_services_total_2 for 4000 iterations. +2024-02-02 15:24:54 → root → INFO: Training of spending_commerce_industry_healthcare_social_services_total_2 completed in 141.06 seconds. 148 out of 261 guides remain to be trained. +2024-02-02 15:24:54 → root → INFO: Training spending_commerce_industry_healthcare_social_services_total_3 for 4000 iterations. +2024-02-02 15:27:13 → root → INFO: Training of spending_commerce_industry_healthcare_social_services_total_3 completed in 139.06 seconds. 147 out of 261 guides remain to be trained. +2024-02-02 15:27:13 → root → INFO: Training spending_commerce_industry_information_total_1 for 4000 iterations. +2024-02-02 15:29:32 → root → INFO: Training of spending_commerce_industry_information_total_1 completed in 139.28 seconds. 146 out of 261 guides remain to be trained. +2024-02-02 15:29:32 → root → INFO: Training spending_commerce_industry_information_total_2 for 4000 iterations. +2024-02-02 15:31:56 → root → INFO: Training of spending_commerce_industry_information_total_2 completed in 143.08 seconds. 145 out of 261 guides remain to be trained. +2024-02-02 15:31:56 → root → INFO: Training spending_commerce_industry_information_total_3 for 4000 iterations. +2024-02-02 15:34:18 → root → INFO: Training of spending_commerce_industry_information_total_3 completed in 142.91 seconds. 144 out of 261 guides remain to be trained. +2024-02-02 15:34:18 → root → INFO: Training spending_commerce_industry_management_enterprises_total_1 for 4000 iterations. +2024-02-02 15:36:42 → root → INFO: Training of spending_commerce_industry_management_enterprises_total_1 completed in 143.10 seconds. 143 out of 261 guides remain to be trained. +2024-02-02 15:36:42 → root → INFO: Training spending_commerce_industry_management_enterprises_total_2 for 4000 iterations. +2024-02-02 15:39:02 → root → INFO: Training of spending_commerce_industry_management_enterprises_total_2 completed in 140.10 seconds. 142 out of 261 guides remain to be trained. +2024-02-02 15:39:02 → root → INFO: Training spending_commerce_industry_management_enterprises_total_3 for 4000 iterations. +2024-02-02 15:41:21 → root → INFO: Training of spending_commerce_industry_management_enterprises_total_3 completed in 139.71 seconds. 141 out of 261 guides remain to be trained. +2024-02-02 15:41:21 → root → INFO: Training spending_commerce_industry_manufacturing_total_1 for 4000 iterations. +2024-02-02 15:43:45 → root → INFO: Training of spending_commerce_industry_manufacturing_total_1 completed in 143.24 seconds. 140 out of 261 guides remain to be trained. +2024-02-02 15:43:45 → root → INFO: Training spending_commerce_industry_manufacturing_total_2 for 4000 iterations. +2024-02-02 15:46:04 → root → INFO: Training of spending_commerce_industry_manufacturing_total_2 completed in 139.76 seconds. 139 out of 261 guides remain to be trained. +2024-02-02 15:46:04 → root → INFO: Training spending_commerce_industry_manufacturing_total_3 for 4000 iterations. +2024-02-02 15:48:27 → root → INFO: Training of spending_commerce_industry_manufacturing_total_3 completed in 142.48 seconds. 138 out of 261 guides remain to be trained. +2024-02-02 15:48:27 → root → INFO: Training spending_commerce_industry_mining_total_1 for 4000 iterations. +2024-02-02 15:50:47 → root → INFO: Training of spending_commerce_industry_mining_total_1 completed in 140.09 seconds. 137 out of 261 guides remain to be trained. +2024-02-02 15:50:47 → root → INFO: Training spending_commerce_industry_mining_total_2 for 4000 iterations. +2024-02-02 15:53:07 → root → INFO: Training of spending_commerce_industry_mining_total_2 completed in 140.07 seconds. 136 out of 261 guides remain to be trained. +2024-02-02 15:53:07 → root → INFO: Training spending_commerce_industry_mining_total_3 for 4000 iterations. +2024-02-02 15:55:29 → root → INFO: Training of spending_commerce_industry_mining_total_3 completed in 142.16 seconds. 135 out of 261 guides remain to be trained. +2024-02-02 15:55:29 → root → INFO: Training spending_commerce_industry_other_services_total_1 for 4000 iterations. +2024-02-02 15:57:51 → root → INFO: Training of spending_commerce_industry_other_services_total_1 completed in 142.00 seconds. 134 out of 261 guides remain to be trained. +2024-02-02 15:57:51 → root → INFO: Training spending_commerce_industry_other_services_total_2 for 4000 iterations. +2024-02-02 16:00:17 → root → INFO: Training of spending_commerce_industry_other_services_total_2 completed in 145.36 seconds. 133 out of 261 guides remain to be trained. +2024-02-02 16:00:17 → root → INFO: Training spending_commerce_industry_other_services_total_3 for 4000 iterations. +2024-02-02 16:02:48 → root → INFO: Training of spending_commerce_industry_other_services_total_3 completed in 151.38 seconds. 132 out of 261 guides remain to be trained. +2024-02-02 16:02:48 → root → INFO: Training spending_commerce_industry_professional_services_total_1 for 4000 iterations. +2024-02-02 16:05:18 → root → INFO: Training of spending_commerce_industry_professional_services_total_1 completed in 150.15 seconds. 131 out of 261 guides remain to be trained. +2024-02-02 16:05:18 → root → INFO: Training spending_commerce_industry_professional_services_total_2 for 4000 iterations. +2024-02-02 16:07:52 → root → INFO: Training of spending_commerce_industry_professional_services_total_2 completed in 153.57 seconds. 130 out of 261 guides remain to be trained. +2024-02-02 16:07:52 → root → INFO: Training spending_commerce_industry_professional_services_total_3 for 4000 iterations. +2024-02-02 16:10:19 → root → INFO: Training of spending_commerce_industry_professional_services_total_3 completed in 147.02 seconds. 129 out of 261 guides remain to be trained. +2024-02-02 16:10:19 → root → INFO: Training spending_commerce_industry_public_administration_total_1 for 4000 iterations. +2024-02-02 16:12:46 → root → INFO: Training of spending_commerce_industry_public_administration_total_1 completed in 147.13 seconds. 128 out of 261 guides remain to be trained. +2024-02-02 16:12:46 → root → INFO: Training spending_commerce_industry_public_administration_total_2 for 4000 iterations. +2024-02-02 16:14:52 → root → INFO: Training of spending_commerce_industry_public_administration_total_2 completed in 125.78 seconds. 127 out of 261 guides remain to be trained. +2024-02-02 16:14:52 → root → INFO: Training spending_commerce_industry_public_administration_total_3 for 4000 iterations. +2024-02-02 16:17:24 → root → INFO: Training of spending_commerce_industry_public_administration_total_3 completed in 152.20 seconds. 126 out of 261 guides remain to be trained. +2024-02-02 16:17:24 → root → INFO: Training spending_commerce_industry_real_estate_total_1 for 4000 iterations. +2024-02-02 16:19:33 → root → INFO: Training of spending_commerce_industry_real_estate_total_1 completed in 129.74 seconds. 125 out of 261 guides remain to be trained. +2024-02-02 16:19:33 → root → INFO: Training spending_commerce_industry_real_estate_total_2 for 4000 iterations. +2024-02-02 16:22:30 → root → INFO: Training of spending_commerce_industry_real_estate_total_2 completed in 176.28 seconds. 124 out of 261 guides remain to be trained. +2024-02-02 16:22:30 → root → INFO: Training spending_commerce_industry_real_estate_total_3 for 4000 iterations. +2024-02-02 16:24:58 → root → INFO: Training of spending_commerce_industry_real_estate_total_3 completed in 148.40 seconds. 123 out of 261 guides remain to be trained. +2024-02-02 16:24:58 → root → INFO: Training spending_commerce_industry_retail_trade_total_1 for 4000 iterations. +2024-02-02 16:27:49 → root → INFO: Training of spending_commerce_industry_retail_trade_total_1 completed in 170.55 seconds. 122 out of 261 guides remain to be trained. +2024-02-02 16:27:49 → root → INFO: Training spending_commerce_industry_retail_trade_total_2 for 4000 iterations. +2024-02-02 16:30:02 → root → INFO: Training of spending_commerce_industry_retail_trade_total_2 completed in 132.95 seconds. 121 out of 261 guides remain to be trained. +2024-02-02 16:30:02 → root → INFO: Training spending_commerce_industry_retail_trade_total_3 for 4000 iterations. +2024-02-02 16:32:23 → root → INFO: Training of spending_commerce_industry_retail_trade_total_3 completed in 141.51 seconds. 120 out of 261 guides remain to be trained. +2024-02-02 16:32:23 → root → INFO: Training spending_commerce_industry_transportation_warehousing_total_1 for 4000 iterations. +2024-02-02 16:35:15 → root → INFO: Training of spending_commerce_industry_transportation_warehousing_total_1 completed in 172.10 seconds. 119 out of 261 guides remain to be trained. +2024-02-02 16:35:15 → root → INFO: Training spending_commerce_industry_transportation_warehousing_total_2 for 4000 iterations. +2024-02-02 16:37:32 → root → INFO: Training of spending_commerce_industry_transportation_warehousing_total_2 completed in 136.59 seconds. 118 out of 261 guides remain to be trained. +2024-02-02 16:37:32 → root → INFO: Training spending_commerce_industry_transportation_warehousing_total_3 for 4000 iterations. +2024-02-02 16:40:16 → root → INFO: Training of spending_commerce_industry_transportation_warehousing_total_3 completed in 164.46 seconds. 117 out of 261 guides remain to be trained. +2024-02-02 16:40:16 → root → INFO: Training spending_commerce_industry_utilities_total_1 for 4000 iterations. +2024-02-02 16:42:51 → root → INFO: Training of spending_commerce_industry_utilities_total_1 completed in 154.76 seconds. 116 out of 261 guides remain to be trained. +2024-02-02 16:42:51 → root → INFO: Training spending_commerce_industry_utilities_total_2 for 4000 iterations. +2024-02-02 16:45:22 → root → INFO: Training of spending_commerce_industry_utilities_total_2 completed in 150.88 seconds. 115 out of 261 guides remain to be trained. +2024-02-02 16:45:22 → root → INFO: Training spending_commerce_industry_utilities_total_3 for 4000 iterations. +2024-02-02 16:47:32 → root → INFO: Training of spending_commerce_industry_utilities_total_3 completed in 130.01 seconds. 114 out of 261 guides remain to be trained. +2024-02-02 16:47:32 → root → INFO: Training spending_commerce_industry_wholesale_trade_total_1 for 4000 iterations. +2024-02-02 16:50:30 → root → INFO: Training of spending_commerce_industry_wholesale_trade_total_1 completed in 177.93 seconds. 113 out of 261 guides remain to be trained. +2024-02-02 16:50:30 → root → INFO: Training spending_commerce_industry_wholesale_trade_total_2 for 4000 iterations. +2024-02-02 16:53:11 → root → INFO: Training of spending_commerce_industry_wholesale_trade_total_2 completed in 160.85 seconds. 112 out of 261 guides remain to be trained. +2024-02-02 16:53:11 → root → INFO: Training spending_commerce_industry_wholesale_trade_total_3 for 4000 iterations. +2024-02-02 16:55:26 → root → INFO: Training of spending_commerce_industry_wholesale_trade_total_3 completed in 135.35 seconds. 111 out of 261 guides remain to be trained. +2024-02-02 16:55:26 → root → INFO: Training spending_commerce_medianHouseholdIncome_1 for 4000 iterations. +2024-02-02 16:58:08 → root → INFO: Training of spending_commerce_medianHouseholdIncome_1 completed in 161.60 seconds. 110 out of 261 guides remain to be trained. +2024-02-02 16:58:08 → root → INFO: Training spending_commerce_medianHouseholdIncome_2 for 4000 iterations. +2024-02-02 17:00:09 → root → INFO: Training of spending_commerce_medianHouseholdIncome_2 completed in 121.19 seconds. 109 out of 261 guides remain to be trained. +2024-02-02 17:00:09 → root → INFO: Training spending_commerce_medianHouseholdIncome_3 for 4000 iterations. +2024-02-02 17:02:29 → root → INFO: Training of spending_commerce_medianHouseholdIncome_3 completed in 139.98 seconds. 108 out of 261 guides remain to be trained. +2024-02-02 17:02:29 → root → INFO: Training spending_commerce_population_1 for 4000 iterations. +2024-02-02 17:04:38 → root → INFO: Training of spending_commerce_population_1 completed in 128.80 seconds. 107 out of 261 guides remain to be trained. +2024-02-02 17:04:38 → root → INFO: Training spending_commerce_population_2 for 4000 iterations. +2024-02-02 17:06:53 → root → INFO: Training of spending_commerce_population_2 completed in 135.38 seconds. 106 out of 261 guides remain to be trained. +2024-02-02 17:06:53 → root → INFO: Training spending_commerce_population_3 for 4000 iterations. +2024-02-02 17:08:59 → root → INFO: Training of spending_commerce_population_3 completed in 125.98 seconds. 105 out of 261 guides remain to be trained. +2024-02-02 17:08:59 → root → INFO: Training spending_commerce_population_density_1 for 4000 iterations. +2024-02-02 17:10:31 → root → INFO: Training of spending_commerce_population_density_1 completed in 91.70 seconds. 104 out of 261 guides remain to be trained. +2024-02-02 17:10:31 → root → INFO: Training spending_commerce_population_density_2 for 4000 iterations. +2024-02-02 17:12:33 → root → INFO: Training of spending_commerce_population_density_2 completed in 122.51 seconds. 103 out of 261 guides remain to be trained. +2024-02-02 17:12:33 → root → INFO: Training spending_commerce_population_density_3 for 4000 iterations. +2024-02-02 17:14:08 → root → INFO: Training of spending_commerce_population_density_3 completed in 94.68 seconds. 102 out of 261 guides remain to be trained. +2024-02-02 17:14:08 → root → INFO: Training spending_commerce_povertyAll_1 for 4000 iterations. +2024-02-02 17:16:12 → root → INFO: Training of spending_commerce_povertyAll_1 completed in 123.58 seconds. 101 out of 261 guides remain to be trained. +2024-02-02 17:16:12 → root → INFO: Training spending_commerce_povertyAll_2 for 4000 iterations. +2024-02-02 17:18:17 → root → INFO: Training of spending_commerce_povertyAll_2 completed in 125.16 seconds. 100 out of 261 guides remain to be trained. +2024-02-02 17:18:17 → root → INFO: Training spending_commerce_povertyAll_3 for 4000 iterations. +2024-02-02 17:21:04 → root → INFO: Training of spending_commerce_povertyAll_3 completed in 167.00 seconds. 99 out of 261 guides remain to be trained. +2024-02-02 17:21:04 → root → INFO: Training spending_commerce_povertyAllprct_1 for 4000 iterations. +2024-02-02 17:23:25 → root → INFO: Training of spending_commerce_povertyAllprct_1 completed in 141.64 seconds. 98 out of 261 guides remain to be trained. +2024-02-02 17:23:25 → root → INFO: Training spending_commerce_povertyAllprct_2 for 4000 iterations. +2024-02-02 17:25:57 → root → INFO: Training of spending_commerce_povertyAllprct_2 completed in 151.49 seconds. 97 out of 261 guides remain to be trained. +2024-02-02 17:25:57 → root → INFO: Training spending_commerce_povertyAllprct_3 for 4000 iterations. +2024-02-02 17:28:15 → root → INFO: Training of spending_commerce_povertyAllprct_3 completed in 137.94 seconds. 96 out of 261 guides remain to be trained. +2024-02-02 17:28:15 → root → INFO: Training spending_commerce_povertyUnder18_1 for 4000 iterations. +2024-02-02 17:31:06 → root → INFO: Training of spending_commerce_povertyUnder18_1 completed in 171.37 seconds. 95 out of 261 guides remain to be trained. +2024-02-02 17:31:06 → root → INFO: Training spending_commerce_povertyUnder18_2 for 4000 iterations. +2024-02-02 17:33:26 → root → INFO: Training of spending_commerce_povertyUnder18_2 completed in 140.08 seconds. 94 out of 261 guides remain to be trained. +2024-02-02 17:33:26 → root → INFO: Training spending_commerce_povertyUnder18_3 for 4000 iterations. +2024-02-02 17:36:11 → root → INFO: Training of spending_commerce_povertyUnder18_3 completed in 164.90 seconds. 93 out of 261 guides remain to be trained. +2024-02-02 17:36:11 → root → INFO: Training spending_commerce_povertyUnder18prct_1 for 4000 iterations. +2024-02-02 17:38:57 → root → INFO: Training of spending_commerce_povertyUnder18prct_1 completed in 166.12 seconds. 92 out of 261 guides remain to be trained. +2024-02-02 17:38:57 → root → INFO: Training spending_commerce_povertyUnder18prct_2 for 4000 iterations. +2024-02-02 17:41:20 → root → INFO: Training of spending_commerce_povertyUnder18prct_2 completed in 142.28 seconds. 91 out of 261 guides remain to be trained. +2024-02-02 17:41:20 → root → INFO: Training spending_commerce_povertyUnder18prct_3 for 4000 iterations. +2024-02-02 17:43:35 → root → INFO: Training of spending_commerce_povertyUnder18prct_3 completed in 135.79 seconds. 90 out of 261 guides remain to be trained. +2024-02-02 17:43:35 → root → INFO: Training spending_commerce_unemployment_rate_1 for 4000 iterations. +2024-02-02 17:45:55 → root → INFO: Training of spending_commerce_unemployment_rate_1 completed in 139.64 seconds. 89 out of 261 guides remain to be trained. +2024-02-02 17:45:55 → root → INFO: Training spending_commerce_unemployment_rate_2 for 4000 iterations. +2024-02-02 17:48:42 → root → INFO: Training of spending_commerce_unemployment_rate_2 completed in 166.60 seconds. 88 out of 261 guides remain to be trained. +2024-02-02 17:48:42 → root → INFO: Training spending_commerce_unemployment_rate_3 for 4000 iterations. +2024-02-02 17:51:28 → root → INFO: Training of spending_commerce_unemployment_rate_3 completed in 166.65 seconds. 87 out of 261 guides remain to be trained. +2024-02-02 17:51:28 → root → INFO: Training spending_transportation_gdp_1 for 4000 iterations. +2024-02-02 17:54:01 → root → INFO: Training of spending_transportation_gdp_1 completed in 152.97 seconds. 86 out of 261 guides remain to be trained. +2024-02-02 17:54:01 → root → INFO: Training spending_transportation_gdp_2 for 4000 iterations. +2024-02-02 17:55:49 → root → INFO: Training of spending_transportation_gdp_2 completed in 107.46 seconds. 85 out of 261 guides remain to be trained. +2024-02-02 17:55:49 → root → INFO: Training spending_transportation_gdp_3 for 4000 iterations. +2024-02-02 17:58:02 → root → INFO: Training of spending_transportation_gdp_3 completed in 133.09 seconds. 84 out of 261 guides remain to be trained. +2024-02-02 17:58:02 → root → INFO: Training spending_transportation_industry_accommodation_food_services_total_1 for 4000 iterations. +2024-02-02 17:59:57 → root → INFO: Training of spending_transportation_industry_accommodation_food_services_total_1 completed in 114.97 seconds. 83 out of 261 guides remain to be trained. +2024-02-02 17:59:57 → root → INFO: Training spending_transportation_industry_accommodation_food_services_total_2 for 4000 iterations. +2024-02-02 18:01:17 → root → INFO: Training of spending_transportation_industry_accommodation_food_services_total_2 completed in 79.78 seconds. 82 out of 261 guides remain to be trained. +2024-02-02 18:01:17 → root → INFO: Training spending_transportation_industry_accommodation_food_services_total_3 for 4000 iterations. +2024-02-02 18:03:55 → root → INFO: Training of spending_transportation_industry_accommodation_food_services_total_3 completed in 158.63 seconds. 81 out of 261 guides remain to be trained. +2024-02-02 18:03:55 → root → INFO: Training spending_transportation_industry_admin_support_services_total_1 for 4000 iterations. +2024-02-02 18:05:44 → root → INFO: Training of spending_transportation_industry_admin_support_services_total_1 completed in 108.91 seconds. 80 out of 261 guides remain to be trained. +2024-02-02 18:05:44 → root → INFO: Training spending_transportation_industry_admin_support_services_total_2 for 4000 iterations. +2024-02-02 18:07:32 → root → INFO: Training of spending_transportation_industry_admin_support_services_total_2 completed in 108.28 seconds. 79 out of 261 guides remain to be trained. +2024-02-02 18:07:32 → root → INFO: Training spending_transportation_industry_admin_support_services_total_3 for 4000 iterations. +2024-02-02 18:09:18 → root → INFO: Training of spending_transportation_industry_admin_support_services_total_3 completed in 105.82 seconds. 78 out of 261 guides remain to be trained. +2024-02-02 18:09:18 → root → INFO: Training spending_transportation_industry_agriculture_total_1 for 4000 iterations. +2024-02-02 18:12:13 → root → INFO: Training of spending_transportation_industry_agriculture_total_1 completed in 175.06 seconds. 77 out of 261 guides remain to be trained. +2024-02-02 18:12:13 → root → INFO: Training spending_transportation_industry_agriculture_total_2 for 4000 iterations. +2024-02-02 18:15:08 → root → INFO: Training of spending_transportation_industry_agriculture_total_2 completed in 174.97 seconds. 76 out of 261 guides remain to be trained. +2024-02-02 18:15:08 → root → INFO: Training spending_transportation_industry_agriculture_total_3 for 4000 iterations. +2024-02-02 18:17:21 → root → INFO: Training of spending_transportation_industry_agriculture_total_3 completed in 132.73 seconds. 75 out of 261 guides remain to be trained. +2024-02-02 18:17:21 → root → INFO: Training spending_transportation_industry_arts_recreation_total_1 for 4000 iterations. +2024-02-02 18:19:43 → root → INFO: Training of spending_transportation_industry_arts_recreation_total_1 completed in 142.06 seconds. 74 out of 261 guides remain to be trained. +2024-02-02 18:19:43 → root → INFO: Training spending_transportation_industry_arts_recreation_total_2 for 4000 iterations. +2024-02-02 18:22:10 → root → INFO: Training of spending_transportation_industry_arts_recreation_total_2 completed in 147.00 seconds. 73 out of 261 guides remain to be trained. +2024-02-02 18:22:10 → root → INFO: Training spending_transportation_industry_arts_recreation_total_3 for 4000 iterations. +2024-02-02 18:24:34 → root → INFO: Training of spending_transportation_industry_arts_recreation_total_3 completed in 143.93 seconds. 72 out of 261 guides remain to be trained. +2024-02-02 18:24:34 → root → INFO: Training spending_transportation_industry_construction_total_1 for 4000 iterations. +2024-02-02 18:27:21 → root → INFO: Training of spending_transportation_industry_construction_total_1 completed in 167.53 seconds. 71 out of 261 guides remain to be trained. +2024-02-02 18:27:21 → root → INFO: Training spending_transportation_industry_construction_total_2 for 4000 iterations. +2024-02-02 18:28:58 → root → INFO: Training of spending_transportation_industry_construction_total_2 completed in 96.68 seconds. 70 out of 261 guides remain to be trained. +2024-02-02 18:28:58 → root → INFO: Training spending_transportation_industry_construction_total_3 for 4000 iterations. +2024-02-02 18:31:34 → root → INFO: Training of spending_transportation_industry_construction_total_3 completed in 155.92 seconds. 69 out of 261 guides remain to be trained. +2024-02-02 18:31:34 → root → INFO: Training spending_transportation_industry_educational_services_total_1 for 4000 iterations. +2024-02-02 18:34:15 → root → INFO: Training of spending_transportation_industry_educational_services_total_1 completed in 161.38 seconds. 68 out of 261 guides remain to be trained. +2024-02-02 18:34:15 → root → INFO: Training spending_transportation_industry_educational_services_total_2 for 4000 iterations. +2024-02-02 18:37:07 → root → INFO: Training of spending_transportation_industry_educational_services_total_2 completed in 171.49 seconds. 67 out of 261 guides remain to be trained. +2024-02-02 18:37:07 → root → INFO: Training spending_transportation_industry_educational_services_total_3 for 4000 iterations. +2024-02-02 18:39:12 → root → INFO: Training of spending_transportation_industry_educational_services_total_3 completed in 125.02 seconds. 66 out of 261 guides remain to be trained. +2024-02-02 18:39:12 → root → INFO: Training spending_transportation_industry_finance_insurance_total_1 for 4000 iterations. +2024-02-02 18:41:06 → root → INFO: Training of spending_transportation_industry_finance_insurance_total_1 completed in 113.74 seconds. 65 out of 261 guides remain to be trained. +2024-02-02 18:41:06 → root → INFO: Training spending_transportation_industry_finance_insurance_total_2 for 4000 iterations. +2024-02-02 18:43:02 → root → INFO: Training of spending_transportation_industry_finance_insurance_total_2 completed in 116.69 seconds. 64 out of 261 guides remain to be trained. +2024-02-02 18:43:02 → root → INFO: Training spending_transportation_industry_finance_insurance_total_3 for 4000 iterations. +2024-02-02 18:45:58 → root → INFO: Training of spending_transportation_industry_finance_insurance_total_3 completed in 175.49 seconds. 63 out of 261 guides remain to be trained. +2024-02-02 18:45:58 → root → INFO: Training spending_transportation_industry_healthcare_social_services_total_1 for 4000 iterations. +2024-02-02 18:48:34 → root → INFO: Training of spending_transportation_industry_healthcare_social_services_total_1 completed in 156.28 seconds. 62 out of 261 guides remain to be trained. +2024-02-02 18:48:34 → root → INFO: Training spending_transportation_industry_healthcare_social_services_total_2 for 4000 iterations. +2024-02-02 18:50:30 → root → INFO: Training of spending_transportation_industry_healthcare_social_services_total_2 completed in 115.60 seconds. 61 out of 261 guides remain to be trained. +2024-02-02 18:50:30 → root → INFO: Training spending_transportation_industry_healthcare_social_services_total_3 for 4000 iterations. +2024-02-02 18:53:17 → root → INFO: Training of spending_transportation_industry_healthcare_social_services_total_3 completed in 167.30 seconds. 60 out of 261 guides remain to be trained. +2024-02-02 18:53:17 → root → INFO: Training spending_transportation_industry_information_total_1 for 4000 iterations. +2024-02-02 18:55:59 → root → INFO: Training of spending_transportation_industry_information_total_1 completed in 162.21 seconds. 59 out of 261 guides remain to be trained. +2024-02-02 18:55:59 → root → INFO: Training spending_transportation_industry_information_total_2 for 4000 iterations. +2024-02-02 18:57:58 → root → INFO: Training of spending_transportation_industry_information_total_2 completed in 118.35 seconds. 58 out of 261 guides remain to be trained. +2024-02-02 18:57:58 → root → INFO: Training spending_transportation_industry_information_total_3 for 4000 iterations. +2024-02-02 19:00:47 → root → INFO: Training of spending_transportation_industry_information_total_3 completed in 169.64 seconds. 57 out of 261 guides remain to be trained. +2024-02-02 19:00:47 → root → INFO: Training spending_transportation_industry_management_enterprises_total_1 for 4000 iterations. +2024-02-02 19:02:58 → root → INFO: Training of spending_transportation_industry_management_enterprises_total_1 completed in 131.01 seconds. 56 out of 261 guides remain to be trained. +2024-02-02 19:02:58 → root → INFO: Training spending_transportation_industry_management_enterprises_total_2 for 4000 iterations. +2024-02-02 19:05:18 → root → INFO: Training of spending_transportation_industry_management_enterprises_total_2 completed in 139.80 seconds. 55 out of 261 guides remain to be trained. +2024-02-02 19:05:18 → root → INFO: Training spending_transportation_industry_management_enterprises_total_3 for 4000 iterations. +2024-02-02 19:07:35 → root → INFO: Training of spending_transportation_industry_management_enterprises_total_3 completed in 136.53 seconds. 54 out of 261 guides remain to be trained. +2024-02-02 19:07:35 → root → INFO: Training spending_transportation_industry_manufacturing_total_1 for 4000 iterations. +2024-02-02 19:10:11 → root → INFO: Training of spending_transportation_industry_manufacturing_total_1 completed in 156.90 seconds. 53 out of 261 guides remain to be trained. +2024-02-02 19:10:11 → root → INFO: Training spending_transportation_industry_manufacturing_total_2 for 4000 iterations. +2024-02-02 19:12:21 → root → INFO: Training of spending_transportation_industry_manufacturing_total_2 completed in 129.25 seconds. 52 out of 261 guides remain to be trained. +2024-02-02 19:12:21 → root → INFO: Training spending_transportation_industry_manufacturing_total_3 for 4000 iterations. +2024-02-02 19:14:24 → root → INFO: Training of spending_transportation_industry_manufacturing_total_3 completed in 123.11 seconds. 51 out of 261 guides remain to be trained. +2024-02-02 19:14:24 → root → INFO: Training spending_transportation_industry_mining_total_1 for 4000 iterations. +2024-02-02 19:16:45 → root → INFO: Training of spending_transportation_industry_mining_total_1 completed in 141.24 seconds. 50 out of 261 guides remain to be trained. +2024-02-02 19:16:45 → root → INFO: Training spending_transportation_industry_mining_total_2 for 4000 iterations. +2024-02-02 19:18:11 → root → INFO: Training of spending_transportation_industry_mining_total_2 completed in 85.93 seconds. 49 out of 261 guides remain to be trained. +2024-02-02 19:18:11 → root → INFO: Training spending_transportation_industry_mining_total_3 for 4000 iterations. +2024-02-02 19:20:49 → root → INFO: Training of spending_transportation_industry_mining_total_3 completed in 157.68 seconds. 48 out of 261 guides remain to be trained. +2024-02-02 19:20:49 → root → INFO: Training spending_transportation_industry_other_services_total_1 for 4000 iterations. +2024-02-02 19:23:19 → root → INFO: Training of spending_transportation_industry_other_services_total_1 completed in 149.83 seconds. 47 out of 261 guides remain to be trained. +2024-02-02 19:23:19 → root → INFO: Training spending_transportation_industry_other_services_total_2 for 4000 iterations. +2024-02-02 19:24:44 → root → INFO: Training of spending_transportation_industry_other_services_total_2 completed in 85.65 seconds. 46 out of 261 guides remain to be trained. +2024-02-02 19:24:44 → root → INFO: Training spending_transportation_industry_other_services_total_3 for 4000 iterations. +2024-02-02 19:26:44 → root → INFO: Training of spending_transportation_industry_other_services_total_3 completed in 119.95 seconds. 45 out of 261 guides remain to be trained. +2024-02-02 19:26:44 → root → INFO: Training spending_transportation_industry_professional_services_total_1 for 4000 iterations. +2024-02-02 19:28:43 → root → INFO: Training of spending_transportation_industry_professional_services_total_1 completed in 119.34 seconds. 44 out of 261 guides remain to be trained. +2024-02-02 19:28:43 → root → INFO: Training spending_transportation_industry_professional_services_total_2 for 4000 iterations. +2024-02-02 19:31:32 → root → INFO: Training of spending_transportation_industry_professional_services_total_2 completed in 168.07 seconds. 43 out of 261 guides remain to be trained. +2024-02-02 19:31:32 → root → INFO: Training spending_transportation_industry_professional_services_total_3 for 4000 iterations. +2024-02-02 19:34:18 → root → INFO: Training of spending_transportation_industry_professional_services_total_3 completed in 166.89 seconds. 42 out of 261 guides remain to be trained. +2024-02-02 19:34:18 → root → INFO: Training spending_transportation_industry_public_administration_total_1 for 4000 iterations. +2024-02-02 19:37:09 → root → INFO: Training of spending_transportation_industry_public_administration_total_1 completed in 170.17 seconds. 41 out of 261 guides remain to be trained. +2024-02-02 19:37:09 → root → INFO: Training spending_transportation_industry_public_administration_total_2 for 4000 iterations. +2024-02-02 19:39:34 → root → INFO: Training of spending_transportation_industry_public_administration_total_2 completed in 145.17 seconds. 40 out of 261 guides remain to be trained. +2024-02-02 19:39:34 → root → INFO: Training spending_transportation_industry_public_administration_total_3 for 4000 iterations. +2024-02-02 19:42:09 → root → INFO: Training of spending_transportation_industry_public_administration_total_3 completed in 155.24 seconds. 39 out of 261 guides remain to be trained. +2024-02-02 19:42:09 → root → INFO: Training spending_transportation_industry_real_estate_total_1 for 4000 iterations. +2024-02-02 19:44:33 → root → INFO: Training of spending_transportation_industry_real_estate_total_1 completed in 143.88 seconds. 38 out of 261 guides remain to be trained. +2024-02-02 19:44:33 → root → INFO: Training spending_transportation_industry_real_estate_total_2 for 4000 iterations. +2024-02-02 19:46:22 → root → INFO: Training of spending_transportation_industry_real_estate_total_2 completed in 109.34 seconds. 37 out of 261 guides remain to be trained. +2024-02-02 19:46:22 → root → INFO: Training spending_transportation_industry_real_estate_total_3 for 4000 iterations. +2024-02-02 19:48:14 → root → INFO: Training of spending_transportation_industry_real_estate_total_3 completed in 111.38 seconds. 36 out of 261 guides remain to be trained. +2024-02-02 19:48:14 → root → INFO: Training spending_transportation_industry_retail_trade_total_1 for 4000 iterations. +2024-02-02 19:49:54 → root → INFO: Training of spending_transportation_industry_retail_trade_total_1 completed in 100.28 seconds. 35 out of 261 guides remain to be trained. +2024-02-02 19:49:54 → root → INFO: Training spending_transportation_industry_retail_trade_total_2 for 4000 iterations. +2024-02-02 19:52:05 → root → INFO: Training of spending_transportation_industry_retail_trade_total_2 completed in 130.73 seconds. 34 out of 261 guides remain to be trained. +2024-02-02 19:52:05 → root → INFO: Training spending_transportation_industry_retail_trade_total_3 for 4000 iterations. +2024-02-02 19:54:57 → root → INFO: Training of spending_transportation_industry_retail_trade_total_3 completed in 172.40 seconds. 33 out of 261 guides remain to be trained. +2024-02-02 19:54:57 → root → INFO: Training spending_transportation_industry_transportation_warehousing_total_1 for 4000 iterations. +2024-02-02 19:57:19 → root → INFO: Training of spending_transportation_industry_transportation_warehousing_total_1 completed in 141.62 seconds. 32 out of 261 guides remain to be trained. +2024-02-02 19:57:19 → root → INFO: Training spending_transportation_industry_transportation_warehousing_total_2 for 4000 iterations. +2024-02-02 19:59:27 → root → INFO: Training of spending_transportation_industry_transportation_warehousing_total_2 completed in 128.75 seconds. 31 out of 261 guides remain to be trained. +2024-02-02 19:59:27 → root → INFO: Training spending_transportation_industry_transportation_warehousing_total_3 for 4000 iterations. +2024-02-02 20:00:55 → root → INFO: Training of spending_transportation_industry_transportation_warehousing_total_3 completed in 87.34 seconds. 30 out of 261 guides remain to be trained. +2024-02-02 20:00:55 → root → INFO: Training spending_transportation_industry_utilities_total_1 for 4000 iterations. +2024-02-02 20:02:47 → root → INFO: Training of spending_transportation_industry_utilities_total_1 completed in 111.90 seconds. 29 out of 261 guides remain to be trained. +2024-02-02 20:02:47 → root → INFO: Training spending_transportation_industry_utilities_total_2 for 4000 iterations. +2024-02-02 20:05:13 → root → INFO: Training of spending_transportation_industry_utilities_total_2 completed in 146.72 seconds. 28 out of 261 guides remain to be trained. +2024-02-02 20:05:13 → root → INFO: Training spending_transportation_industry_utilities_total_3 for 4000 iterations. +2024-02-02 20:07:47 → root → INFO: Training of spending_transportation_industry_utilities_total_3 completed in 153.54 seconds. 27 out of 261 guides remain to be trained. +2024-02-02 20:07:47 → root → INFO: Training spending_transportation_industry_wholesale_trade_total_1 for 4000 iterations. +2024-02-02 20:10:38 → root → INFO: Training of spending_transportation_industry_wholesale_trade_total_1 completed in 171.06 seconds. 26 out of 261 guides remain to be trained. +2024-02-02 20:10:38 → root → INFO: Training spending_transportation_industry_wholesale_trade_total_2 for 4000 iterations. +2024-02-02 20:13:02 → root → INFO: Training of spending_transportation_industry_wholesale_trade_total_2 completed in 144.28 seconds. 25 out of 261 guides remain to be trained. +2024-02-02 20:13:02 → root → INFO: Training spending_transportation_industry_wholesale_trade_total_3 for 4000 iterations. +2024-02-02 20:15:16 → root → INFO: Training of spending_transportation_industry_wholesale_trade_total_3 completed in 133.49 seconds. 24 out of 261 guides remain to be trained. +2024-02-02 20:15:16 → root → INFO: Training spending_transportation_medianHouseholdIncome_1 for 4000 iterations. +2024-02-02 20:17:29 → root → INFO: Training of spending_transportation_medianHouseholdIncome_1 completed in 132.92 seconds. 23 out of 261 guides remain to be trained. +2024-02-02 20:17:29 → root → INFO: Training spending_transportation_medianHouseholdIncome_2 for 4000 iterations. +2024-02-02 20:20:01 → root → INFO: Training of spending_transportation_medianHouseholdIncome_2 completed in 151.92 seconds. 22 out of 261 guides remain to be trained. +2024-02-02 20:20:01 → root → INFO: Training spending_transportation_medianHouseholdIncome_3 for 4000 iterations. +2024-02-02 20:22:16 → root → INFO: Training of spending_transportation_medianHouseholdIncome_3 completed in 135.45 seconds. 21 out of 261 guides remain to be trained. +2024-02-02 20:22:16 → root → INFO: Training spending_transportation_population_1 for 4000 iterations. +2024-02-02 20:24:32 → root → INFO: Training of spending_transportation_population_1 completed in 136.26 seconds. 20 out of 261 guides remain to be trained. +2024-02-02 20:24:32 → root → INFO: Training spending_transportation_population_2 for 4000 iterations. +2024-02-02 20:26:33 → root → INFO: Training of spending_transportation_population_2 completed in 120.36 seconds. 19 out of 261 guides remain to be trained. +2024-02-02 20:26:33 → root → INFO: Training spending_transportation_population_3 for 4000 iterations. +2024-02-02 20:28:43 → root → INFO: Training of spending_transportation_population_3 completed in 129.82 seconds. 18 out of 261 guides remain to be trained. +2024-02-02 20:28:43 → root → INFO: Training spending_transportation_population_density_1 for 4000 iterations. +2024-02-02 20:30:35 → root → INFO: Training of spending_transportation_population_density_1 completed in 112.55 seconds. 17 out of 261 guides remain to be trained. +2024-02-02 20:30:35 → root → INFO: Training spending_transportation_population_density_2 for 4000 iterations. +2024-02-02 20:33:16 → root → INFO: Training of spending_transportation_population_density_2 completed in 160.88 seconds. 16 out of 261 guides remain to be trained. +2024-02-02 20:33:16 → root → INFO: Training spending_transportation_population_density_3 for 4000 iterations. +2024-02-02 20:35:16 → root → INFO: Training of spending_transportation_population_density_3 completed in 120.15 seconds. 15 out of 261 guides remain to be trained. +2024-02-02 20:35:16 → root → INFO: Training spending_transportation_povertyAll_1 for 4000 iterations. +2024-02-02 20:37:26 → root → INFO: Training of spending_transportation_povertyAll_1 completed in 130.36 seconds. 14 out of 261 guides remain to be trained. +2024-02-02 20:37:26 → root → INFO: Training spending_transportation_povertyAll_2 for 4000 iterations. +2024-02-02 20:39:33 → root → INFO: Training of spending_transportation_povertyAll_2 completed in 126.11 seconds. 13 out of 261 guides remain to be trained. +2024-02-02 20:39:33 → root → INFO: Training spending_transportation_povertyAll_3 for 4000 iterations. +2024-02-02 20:41:46 → root → INFO: Training of spending_transportation_povertyAll_3 completed in 133.69 seconds. 12 out of 261 guides remain to be trained. +2024-02-02 20:41:46 → root → INFO: Training spending_transportation_povertyAllprct_1 for 4000 iterations. +2024-02-02 20:44:11 → root → INFO: Training of spending_transportation_povertyAllprct_1 completed in 144.49 seconds. 11 out of 261 guides remain to be trained. +2024-02-02 20:44:11 → root → INFO: Training spending_transportation_povertyAllprct_2 for 4000 iterations. +2024-02-02 20:46:18 → root → INFO: Training of spending_transportation_povertyAllprct_2 completed in 127.46 seconds. 10 out of 261 guides remain to be trained. +2024-02-02 20:46:18 → root → INFO: Training spending_transportation_povertyAllprct_3 for 4000 iterations. +2024-02-02 20:48:13 → root → INFO: Training of spending_transportation_povertyAllprct_3 completed in 115.09 seconds. 9 out of 261 guides remain to be trained. +2024-02-02 20:48:13 → root → INFO: Training spending_transportation_povertyUnder18_1 for 4000 iterations. +2024-02-02 20:49:43 → root → INFO: Training of spending_transportation_povertyUnder18_1 completed in 89.29 seconds. 8 out of 261 guides remain to be trained. +2024-02-02 20:49:43 → root → INFO: Training spending_transportation_povertyUnder18_2 for 4000 iterations. +2024-02-02 20:51:04 → root → INFO: Training of spending_transportation_povertyUnder18_2 completed in 81.08 seconds. 7 out of 261 guides remain to be trained. +2024-02-02 20:51:04 → root → INFO: Training spending_transportation_povertyUnder18_3 for 4000 iterations. +2024-02-02 20:53:04 → root → INFO: Training of spending_transportation_povertyUnder18_3 completed in 120.60 seconds. 6 out of 261 guides remain to be trained. +2024-02-02 20:53:04 → root → INFO: Training spending_transportation_povertyUnder18prct_1 for 4000 iterations. +2024-02-02 20:54:46 → root → INFO: Training of spending_transportation_povertyUnder18prct_1 completed in 101.38 seconds. 5 out of 261 guides remain to be trained. +2024-02-02 20:54:46 → root → INFO: Training spending_transportation_povertyUnder18prct_2 for 4000 iterations. +2024-02-02 20:56:45 → root → INFO: Training of spending_transportation_povertyUnder18prct_2 completed in 118.92 seconds. 4 out of 261 guides remain to be trained. +2024-02-02 20:56:45 → root → INFO: Training spending_transportation_povertyUnder18prct_3 for 4000 iterations. +2024-02-02 20:59:36 → root → INFO: Training of spending_transportation_povertyUnder18prct_3 completed in 171.63 seconds. 3 out of 261 guides remain to be trained. +2024-02-02 20:59:36 → root → INFO: Training spending_transportation_unemployment_rate_1 for 4000 iterations. +2024-02-02 21:02:05 → root → INFO: Training of spending_transportation_unemployment_rate_1 completed in 148.87 seconds. 2 out of 261 guides remain to be trained. +2024-02-02 21:02:05 → root → INFO: Training spending_transportation_unemployment_rate_2 for 4000 iterations. +2024-02-02 21:04:24 → root → INFO: Training of spending_transportation_unemployment_rate_2 completed in 138.99 seconds. 1 out of 261 guides remain to be trained. +2024-02-02 21:04:24 → root → INFO: Training spending_transportation_unemployment_rate_3 for 4000 iterations. +2024-02-02 21:06:55 → root → INFO: Training of spending_transportation_unemployment_rate_3 completed in 151.15 seconds. 0 out of 261 guides remain to be trained. +2024-02-02 21:06:55 → root → INFO: All guides are now available. diff --git 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a/data/model_guides/spending_transportation_unemployment_rate_1_guide.pkl b/data/model_guides/spending_transportation_unemployment_rate_1_guide.pkl index 9b591708..0ab4f865 100644 Binary files a/data/model_guides/spending_transportation_unemployment_rate_1_guide.pkl and b/data/model_guides/spending_transportation_unemployment_rate_1_guide.pkl differ diff --git a/data/model_guides/spending_transportation_unemployment_rate_1_params.pth b/data/model_guides/spending_transportation_unemployment_rate_1_params.pth index 618398ab..6e82f748 100644 Binary files a/data/model_guides/spending_transportation_unemployment_rate_1_params.pth and b/data/model_guides/spending_transportation_unemployment_rate_1_params.pth differ diff --git a/data/model_guides/spending_transportation_unemployment_rate_2_guide.pkl b/data/model_guides/spending_transportation_unemployment_rate_2_guide.pkl index fa2660a5..1e76abd8 100644 Binary files a/data/model_guides/spending_transportation_unemployment_rate_2_guide.pkl and 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100644 Binary files a/data/model_guides/spending_transportation_unemployment_rate_3_params.pth and b/data/model_guides/spending_transportation_unemployment_rate_3_params.pth differ diff --git a/data/tau_samples/.sampling.log b/data/tau_samples/.sampling.log index b676c31b..156bbeb0 100644 --- a/data/tau_samples/.sampling.log +++ b/data/tau_samples/.sampling.log @@ -1,164 +1,176 @@ -2023-12-21 18:54:10 → root → INFO: 3 sample dictionaries already exist. Starting to obtain 81 out of 84 sample dictionaries needed. -2023-12-21 18:54:10 → root → INFO: Sampling gdp/spending_HHS pair now. -2023-12-21 18:54:15 → root → INFO: Done sampling gdp/spending_HHS pair, completed in 5.13 seconds.80 out of 84 samples remain. -2023-12-21 18:54:15 → root → INFO: Sampling industry_accommodation_food_services_total/spending_HHS pair now. -2023-12-21 18:54:20 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_HHS pair, completed in 5.45 seconds.79 out of 84 samples remain. -2023-12-21 18:54:20 → root → INFO: Sampling industry_admin_support_services_total/spending_HHS pair now. -2023-12-21 18:54:26 → root → INFO: Done sampling industry_admin_support_services_total/spending_HHS pair, completed in 5.49 seconds.78 out of 84 samples remain. -2023-12-21 18:54:26 → root → INFO: Sampling industry_agriculture_total/spending_HHS pair now. -2023-12-21 18:54:31 → root → INFO: Done sampling industry_agriculture_total/spending_HHS pair, completed in 5.50 seconds.77 out of 84 samples remain. -2023-12-21 18:54:31 → root → INFO: Sampling industry_arts_recreation_total/spending_HHS pair now. -2023-12-21 18:54:35 → root → INFO: Done sampling industry_arts_recreation_total/spending_HHS pair, completed in 3.66 seconds.76 out of 84 samples remain. -2023-12-21 18:54:35 → root → INFO: Sampling industry_construction_total/spending_HHS pair now. -2023-12-21 18:54:39 → root → INFO: Done sampling industry_construction_total/spending_HHS pair, completed in 3.67 seconds.75 out of 84 samples remain. -2023-12-21 18:54:39 → root → INFO: Sampling industry_educational_services_total/spending_HHS pair now. -2023-12-21 18:54:42 → root → INFO: Done sampling industry_educational_services_total/spending_HHS pair, completed in 3.70 seconds.74 out of 84 samples remain. -2023-12-21 18:54:42 → root → INFO: Sampling industry_finance_insurance_total/spending_HHS pair now. -2023-12-21 18:54:48 → root → INFO: Done sampling industry_finance_insurance_total/spending_HHS pair, completed in 5.53 seconds.73 out of 84 samples remain. -2023-12-21 18:54:48 → root → INFO: Sampling industry_healthcare_social_services_total/spending_HHS pair now. -2023-12-21 18:54:52 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_HHS pair, completed in 4.31 seconds.72 out of 84 samples remain. -2023-12-21 18:54:52 → root → INFO: Sampling industry_information_total/spending_HHS pair now. -2023-12-21 18:54:58 → root → INFO: Done sampling industry_information_total/spending_HHS pair, completed in 5.50 seconds.71 out of 84 samples remain. -2023-12-21 18:54:58 → root → INFO: Sampling industry_management_enterprises_total/spending_HHS pair now. -2023-12-21 18:55:03 → root → INFO: Done sampling industry_management_enterprises_total/spending_HHS pair, completed in 5.44 seconds.70 out of 84 samples remain. -2023-12-21 18:55:03 → root → INFO: Sampling industry_manufacturing_total/spending_HHS pair now. -2023-12-21 18:55:09 → root → INFO: Done sampling industry_manufacturing_total/spending_HHS pair, completed in 5.40 seconds.69 out of 84 samples remain. -2023-12-21 18:55:09 → root → INFO: Sampling industry_mining_total/spending_HHS pair now. -2023-12-21 18:55:14 → root → INFO: Done sampling industry_mining_total/spending_HHS pair, completed in 5.49 seconds.68 out of 84 samples remain. -2023-12-21 18:55:14 → root → INFO: Sampling industry_other_services_total/spending_HHS pair now. -2023-12-21 18:55:20 → root → INFO: Done sampling industry_other_services_total/spending_HHS pair, completed in 5.50 seconds.67 out of 84 samples remain. -2023-12-21 18:55:20 → root → INFO: Sampling industry_professional_services_total/spending_HHS pair now. -2023-12-21 18:55:25 → root → INFO: Done sampling industry_professional_services_total/spending_HHS pair, completed in 5.59 seconds.66 out of 84 samples remain. -2023-12-21 18:55:25 → root → INFO: Sampling industry_public_administration_total/spending_HHS pair now. -2023-12-21 18:55:31 → root → INFO: Done sampling industry_public_administration_total/spending_HHS pair, completed in 5.58 seconds.65 out of 84 samples remain. -2023-12-21 18:55:31 → root → INFO: Sampling industry_real_estate_total/spending_HHS pair now. -2023-12-21 18:55:36 → root → INFO: Done sampling industry_real_estate_total/spending_HHS pair, completed in 5.59 seconds.64 out of 84 samples remain. -2023-12-21 18:55:36 → root → INFO: Sampling industry_retail_trade_total/spending_HHS pair now. -2023-12-21 18:55:42 → root → INFO: Done sampling industry_retail_trade_total/spending_HHS pair, completed in 5.64 seconds.63 out of 84 samples remain. -2023-12-21 18:55:42 → root → INFO: Sampling industry_transportation_warehousing_total/spending_HHS pair now. -2023-12-21 18:55:46 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_HHS pair, completed in 4.50 seconds.62 out of 84 samples remain. -2023-12-21 18:55:46 → root → INFO: Sampling industry_utilities_total/spending_HHS pair now. -2023-12-21 18:55:52 → root → INFO: Done sampling industry_utilities_total/spending_HHS pair, completed in 5.46 seconds.61 out of 84 samples remain. -2023-12-21 18:55:52 → root → INFO: Sampling industry_wholesale_trade_total/spending_HHS pair now. -2023-12-21 18:55:58 → root → INFO: Done sampling industry_wholesale_trade_total/spending_HHS pair, completed in 5.61 seconds.60 out of 84 samples remain. -2023-12-21 18:55:58 → root → INFO: Sampling medianHouseholdIncome/spending_HHS pair now. -2023-12-21 18:56:03 → root → INFO: Done sampling medianHouseholdIncome/spending_HHS pair, completed in 5.36 seconds.59 out of 84 samples remain. -2023-12-21 18:56:03 → root → INFO: Sampling population/spending_HHS pair now. -2023-12-21 18:56:08 → root → INFO: Done sampling population/spending_HHS pair, completed in 5.44 seconds.58 out of 84 samples remain. -2023-12-21 18:56:08 → root → INFO: Sampling povertyAll/spending_HHS pair now. -2023-12-21 18:56:14 → root → INFO: Done sampling povertyAll/spending_HHS pair, completed in 5.42 seconds.57 out of 84 samples remain. -2023-12-21 18:56:14 → root → INFO: Sampling povertyAllprct/spending_HHS pair now. -2023-12-21 18:56:19 → root → INFO: Done sampling povertyAllprct/spending_HHS pair, completed in 5.47 seconds.56 out of 84 samples remain. -2023-12-21 18:56:19 → root → INFO: Sampling povertyUnder18/spending_HHS pair now. -2023-12-21 18:56:25 → root → INFO: Done sampling povertyUnder18/spending_HHS pair, completed in 5.47 seconds.55 out of 84 samples remain. -2023-12-21 18:56:25 → root → INFO: Sampling povertyUnder18prct/spending_HHS pair now. -2023-12-21 18:56:30 → root → INFO: Done sampling povertyUnder18prct/spending_HHS pair, completed in 5.49 seconds.54 out of 84 samples remain. -2023-12-21 18:56:30 → root → INFO: Sampling unemployment_rate/spending_HHS pair now. -2023-12-21 18:56:36 → root → INFO: Done sampling unemployment_rate/spending_HHS pair, completed in 5.48 seconds.53 out of 84 samples remain. -2023-12-21 18:56:36 → root → INFO: Sampling gdp/spending_commerce pair now. -2023-12-21 18:56:41 → root → INFO: Done sampling gdp/spending_commerce pair, completed in 5.38 seconds.52 out of 84 samples remain. -2023-12-21 18:56:41 → root → INFO: Sampling industry_accommodation_food_services_total/spending_commerce pair now. -2023-12-21 18:56:47 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_commerce pair, completed in 5.67 seconds.51 out of 84 samples remain. -2023-12-21 18:56:47 → root → INFO: Sampling industry_admin_support_services_total/spending_commerce pair now. -2023-12-21 18:56:52 → root → INFO: Done sampling industry_admin_support_services_total/spending_commerce pair, completed in 5.61 seconds.50 out of 84 samples remain. -2023-12-21 18:56:52 → root → INFO: Sampling industry_agriculture_total/spending_commerce pair now. -2023-12-21 18:56:58 → root → INFO: Done sampling industry_agriculture_total/spending_commerce pair, completed in 5.50 seconds.49 out of 84 samples remain. -2023-12-21 18:56:58 → root → INFO: Sampling industry_arts_recreation_total/spending_commerce pair now. -2023-12-21 18:57:03 → root → INFO: Done sampling industry_arts_recreation_total/spending_commerce pair, completed in 5.68 seconds.48 out of 84 samples remain. -2023-12-21 18:57:03 → root → INFO: Sampling industry_construction_total/spending_commerce pair now. -2023-12-21 18:57:09 → root → INFO: Done sampling industry_construction_total/spending_commerce pair, completed in 5.59 seconds.47 out of 84 samples remain. -2023-12-21 18:57:09 → root → INFO: Sampling industry_educational_services_total/spending_commerce pair now. -2023-12-21 18:57:15 → root → INFO: Done sampling industry_educational_services_total/spending_commerce pair, completed in 5.65 seconds.46 out of 84 samples remain. -2023-12-21 18:57:15 → root → INFO: Sampling industry_finance_insurance_total/spending_commerce pair now. -2023-12-21 18:57:20 → root → INFO: Done sampling industry_finance_insurance_total/spending_commerce pair, completed in 5.63 seconds.45 out of 84 samples remain. -2023-12-21 18:57:20 → root → INFO: Sampling industry_healthcare_social_services_total/spending_commerce pair now. -2023-12-21 18:57:26 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_commerce pair, completed in 5.47 seconds.44 out of 84 samples remain. -2023-12-21 18:57:26 → root → INFO: Sampling industry_information_total/spending_commerce pair now. -2023-12-21 18:57:32 → root → INFO: Done sampling industry_information_total/spending_commerce pair, completed in 6.59 seconds.43 out of 84 samples remain. -2023-12-21 18:57:32 → root → INFO: Sampling industry_manufacturing_total/spending_commerce pair now. -2023-12-21 18:57:38 → root → INFO: Done sampling industry_manufacturing_total/spending_commerce pair, completed in 5.59 seconds.42 out of 84 samples remain. -2023-12-21 18:57:38 → root → INFO: Sampling industry_mining_total/spending_commerce pair now. -2023-12-21 18:57:43 → root → INFO: Done sampling industry_mining_total/spending_commerce pair, completed in 5.44 seconds.41 out of 84 samples remain. -2023-12-21 18:57:43 → root → INFO: Sampling industry_other_services_total/spending_commerce pair now. -2023-12-21 18:57:49 → root → INFO: Done sampling industry_other_services_total/spending_commerce pair, completed in 5.40 seconds.40 out of 84 samples remain. -2023-12-21 18:57:49 → root → INFO: Sampling industry_professional_services_total/spending_commerce pair now. -2023-12-21 18:57:54 → root → INFO: Done sampling industry_professional_services_total/spending_commerce pair, completed in 5.38 seconds.39 out of 84 samples remain. -2023-12-21 18:57:54 → root → INFO: Sampling industry_public_administration_total/spending_commerce pair now. -2023-12-21 18:58:00 → root → INFO: Done sampling industry_public_administration_total/spending_commerce pair, completed in 5.44 seconds.38 out of 84 samples remain. -2023-12-21 18:58:00 → root → INFO: Sampling industry_real_estate_total/spending_commerce pair now. -2023-12-21 18:58:05 → root → INFO: Done sampling industry_real_estate_total/spending_commerce pair, completed in 5.41 seconds.37 out of 84 samples remain. -2023-12-21 18:58:05 → root → INFO: Sampling industry_retail_trade_total/spending_commerce pair now. -2023-12-21 18:58:11 → root → INFO: Done sampling industry_retail_trade_total/spending_commerce pair, completed in 5.44 seconds.36 out of 84 samples remain. -2023-12-21 18:58:11 → root → INFO: Sampling industry_transportation_warehousing_total/spending_commerce pair now. -2023-12-21 18:58:16 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_commerce pair, completed in 5.62 seconds.35 out of 84 samples remain. -2023-12-21 18:58:16 → root → INFO: Sampling industry_utilities_total/spending_commerce pair now. -2023-12-21 18:58:22 → root → INFO: Done sampling industry_utilities_total/spending_commerce pair, completed in 5.65 seconds.34 out of 84 samples remain. -2023-12-21 18:58:22 → root → INFO: Sampling industry_wholesale_trade_total/spending_commerce pair now. -2023-12-21 18:58:27 → root → INFO: Done sampling industry_wholesale_trade_total/spending_commerce pair, completed in 5.55 seconds.33 out of 84 samples remain. -2023-12-21 18:58:27 → root → INFO: Sampling medianHouseholdIncome/spending_commerce pair now. -2023-12-21 18:58:33 → root → INFO: Done sampling medianHouseholdIncome/spending_commerce pair, completed in 5.61 seconds.32 out of 84 samples remain. -2023-12-21 18:58:33 → root → INFO: Sampling population/spending_commerce pair now. -2023-12-21 18:58:39 → root → INFO: Done sampling population/spending_commerce pair, completed in 5.64 seconds.31 out of 84 samples remain. -2023-12-21 18:58:39 → root → INFO: Sampling povertyAll/spending_commerce pair now. -2023-12-21 18:58:44 → root → INFO: Done sampling povertyAll/spending_commerce pair, completed in 5.63 seconds.30 out of 84 samples remain. -2023-12-21 18:58:44 → root → INFO: Sampling povertyAllprct/spending_commerce pair now. -2023-12-21 18:58:50 → root → INFO: Done sampling povertyAllprct/spending_commerce pair, completed in 5.59 seconds.29 out of 84 samples remain. -2023-12-21 18:58:50 → root → INFO: Sampling povertyUnder18/spending_commerce pair now. -2023-12-21 18:58:55 → root → INFO: Done sampling povertyUnder18/spending_commerce pair, completed in 5.62 seconds.28 out of 84 samples remain. -2023-12-21 18:58:55 → root → INFO: Sampling povertyUnder18prct/spending_commerce pair now. -2023-12-21 18:59:01 → root → INFO: Done sampling povertyUnder18prct/spending_commerce pair, completed in 5.65 seconds.27 out of 84 samples remain. -2023-12-21 18:59:01 → root → INFO: Sampling gdp/spending_transportation pair now. -2023-12-21 18:59:07 → root → INFO: Done sampling gdp/spending_transportation pair, completed in 5.46 seconds.26 out of 84 samples remain. -2023-12-21 18:59:07 → root → INFO: Sampling industry_accommodation_food_services_total/spending_transportation pair now. -2023-12-21 18:59:12 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_transportation pair, completed in 5.66 seconds.25 out of 84 samples remain. -2023-12-21 18:59:12 → root → INFO: Sampling industry_admin_support_services_total/spending_transportation pair now. -2023-12-21 18:59:18 → root → INFO: Done sampling industry_admin_support_services_total/spending_transportation pair, completed in 5.54 seconds.24 out of 84 samples remain. -2023-12-21 18:59:18 → root → INFO: Sampling industry_agriculture_total/spending_transportation pair now. -2023-12-21 18:59:23 → root → INFO: Done sampling industry_agriculture_total/spending_transportation pair, completed in 5.60 seconds.23 out of 84 samples remain. -2023-12-21 18:59:23 → root → INFO: Sampling industry_arts_recreation_total/spending_transportation pair now. -2023-12-21 18:59:29 → root → INFO: Done sampling industry_arts_recreation_total/spending_transportation pair, completed in 5.64 seconds.22 out of 84 samples remain. -2023-12-21 18:59:29 → root → INFO: Sampling industry_construction_total/spending_transportation pair now. -2023-12-21 18:59:35 → root → INFO: Done sampling industry_construction_total/spending_transportation pair, completed in 5.64 seconds.21 out of 84 samples remain. -2023-12-21 18:59:35 → root → INFO: Sampling industry_educational_services_total/spending_transportation pair now. -2023-12-21 18:59:40 → root → INFO: Done sampling industry_educational_services_total/spending_transportation pair, completed in 5.67 seconds.20 out of 84 samples remain. -2023-12-21 18:59:40 → root → INFO: Sampling industry_finance_insurance_total/spending_transportation pair now. -2023-12-21 18:59:46 → root → INFO: Done sampling industry_finance_insurance_total/spending_transportation pair, completed in 5.62 seconds.19 out of 84 samples remain. -2023-12-21 18:59:46 → root → INFO: Sampling industry_healthcare_social_services_total/spending_transportation pair now. -2023-12-21 18:59:52 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_transportation pair, completed in 5.60 seconds.18 out of 84 samples remain. -2023-12-21 18:59:52 → root → INFO: Sampling industry_information_total/spending_transportation pair now. -2023-12-21 18:59:57 → root → INFO: Done sampling industry_information_total/spending_transportation pair, completed in 5.68 seconds.17 out of 84 samples remain. -2023-12-21 18:59:57 → root → INFO: Sampling industry_management_enterprises_total/spending_transportation pair now. -2023-12-21 19:00:03 → root → INFO: Done sampling industry_management_enterprises_total/spending_transportation pair, completed in 5.59 seconds.16 out of 84 samples remain. -2023-12-21 19:00:03 → root → INFO: Sampling industry_manufacturing_total/spending_transportation pair now. -2023-12-21 19:00:08 → root → INFO: Done sampling industry_manufacturing_total/spending_transportation pair, completed in 5.61 seconds.15 out of 84 samples remain. -2023-12-21 19:00:08 → root → INFO: Sampling industry_mining_total/spending_transportation pair now. -2023-12-21 19:00:14 → root → INFO: Done sampling industry_mining_total/spending_transportation pair, completed in 5.61 seconds.14 out of 84 samples remain. -2023-12-21 19:00:14 → root → INFO: Sampling industry_other_services_total/spending_transportation pair now. -2023-12-21 19:00:20 → root → INFO: Done sampling industry_other_services_total/spending_transportation pair, completed in 5.60 seconds.13 out of 84 samples remain. -2023-12-21 19:00:20 → root → INFO: Sampling industry_professional_services_total/spending_transportation pair now. -2023-12-21 19:00:25 → root → INFO: Done sampling industry_professional_services_total/spending_transportation pair, completed in 5.60 seconds.12 out of 84 samples remain. -2023-12-21 19:00:25 → root → INFO: Sampling industry_public_administration_total/spending_transportation pair now. -2023-12-21 19:00:31 → root → INFO: Done sampling industry_public_administration_total/spending_transportation pair, completed in 5.68 seconds.11 out of 84 samples remain. -2023-12-21 19:00:31 → root → INFO: Sampling industry_real_estate_total/spending_transportation pair now. -2023-12-21 19:00:37 → root → INFO: Done sampling industry_real_estate_total/spending_transportation pair, completed in 5.63 seconds.10 out of 84 samples remain. -2023-12-21 19:00:37 → root → INFO: Sampling industry_retail_trade_total/spending_transportation pair now. -2023-12-21 19:00:42 → root → INFO: Done sampling industry_retail_trade_total/spending_transportation pair, completed in 5.66 seconds.9 out of 84 samples remain. -2023-12-21 19:00:42 → root → INFO: Sampling industry_transportation_warehousing_total/spending_transportation pair now. -2023-12-21 19:00:48 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_transportation pair, completed in 5.73 seconds.8 out of 84 samples remain. -2023-12-21 19:00:48 → root → INFO: Sampling industry_utilities_total/spending_transportation pair now. -2023-12-21 19:00:54 → root → INFO: Done sampling industry_utilities_total/spending_transportation pair, completed in 5.63 seconds.7 out of 84 samples remain. -2023-12-21 19:00:54 → root → INFO: Sampling industry_wholesale_trade_total/spending_transportation pair now. -2023-12-21 19:00:59 → root → INFO: Done sampling industry_wholesale_trade_total/spending_transportation pair, completed in 5.61 seconds.6 out of 84 samples remain. -2023-12-21 19:00:59 → root → INFO: Sampling medianHouseholdIncome/spending_transportation pair now. -2023-12-21 19:01:05 → root → INFO: Done sampling medianHouseholdIncome/spending_transportation pair, completed in 5.70 seconds.5 out of 84 samples remain. -2023-12-21 19:01:05 → root → INFO: Sampling population/spending_transportation pair now. -2023-12-21 19:01:11 → root → INFO: Done sampling population/spending_transportation pair, completed in 5.73 seconds.4 out of 84 samples remain. -2023-12-21 19:01:11 → root → INFO: Sampling povertyAll/spending_transportation pair now. -2023-12-21 19:01:16 → root → INFO: Done sampling povertyAll/spending_transportation pair, completed in 5.64 seconds.3 out of 84 samples remain. -2023-12-21 19:01:16 → root → INFO: Sampling povertyAllprct/spending_transportation pair now. -2023-12-21 19:01:22 → root → INFO: Done sampling povertyAllprct/spending_transportation pair, completed in 5.65 seconds.2 out of 84 samples remain. -2023-12-21 19:01:22 → root → INFO: Sampling povertyUnder18/spending_transportation pair now. -2023-12-21 19:01:27 → root → INFO: Done sampling povertyUnder18/spending_transportation pair, completed in 5.62 seconds.1 out of 84 samples remain. -2023-12-21 19:01:27 → root → INFO: Sampling povertyUnder18prct/spending_transportation pair now. -2023-12-21 19:01:33 → root → INFO: Done sampling povertyUnder18prct/spending_transportation pair, completed in 5.54 seconds.0 out of 84 samples remain. -2023-12-21 19:01:33 → root → INFO: All samples are now available. Sampling took 448.84 seconds, or 7.48 minutes. +2024-02-05 07:59:32 → root → INFO: 1 sample dictionaries already exist. Starting to obtain 86 out of 87 sample dictionaries needed. +2024-02-05 07:59:32 → root → INFO: Sampling gdp/spending_HHS pair now. +2024-02-05 07:59:43 → root → INFO: Done sampling gdp/spending_HHS pair, completed in 10.96 seconds. 85 out of 87 samples remain. +2024-02-05 07:59:43 → root → INFO: Sampling industry_accommodation_food_services_total/spending_HHS pair now. +2024-02-05 07:59:54 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_HHS pair, completed in 11.45 seconds. 84 out of 87 samples remain. +2024-02-05 07:59:54 → root → INFO: Sampling industry_admin_support_services_total/spending_HHS pair now. +2024-02-05 08:00:05 → root → INFO: Done sampling industry_admin_support_services_total/spending_HHS pair, completed in 11.16 seconds. 83 out of 87 samples remain. +2024-02-05 08:00:05 → root → INFO: Sampling industry_agriculture_total/spending_HHS pair now. +2024-02-05 08:00:16 → root → INFO: Done sampling industry_agriculture_total/spending_HHS pair, completed in 10.50 seconds. 82 out of 87 samples remain. +2024-02-05 08:00:16 → root → INFO: Sampling industry_arts_recreation_total/spending_HHS pair now. +2024-02-05 08:00:27 → root → INFO: Done sampling industry_arts_recreation_total/spending_HHS pair, completed in 11.46 seconds. 81 out of 87 samples remain. +2024-02-05 08:00:27 → root → INFO: Sampling industry_construction_total/spending_HHS pair now. +2024-02-05 08:00:36 → root → INFO: Done sampling industry_construction_total/spending_HHS pair, completed in 8.85 seconds. 80 out of 87 samples remain. +2024-02-05 08:00:36 → root → INFO: Sampling industry_educational_services_total/spending_HHS pair now. +2024-02-05 08:00:46 → root → INFO: Done sampling industry_educational_services_total/spending_HHS pair, completed in 9.51 seconds. 79 out of 87 samples remain. +2024-02-05 08:00:46 → root → INFO: Sampling industry_finance_insurance_total/spending_HHS pair now. +2024-02-05 08:00:57 → root → INFO: Done sampling industry_finance_insurance_total/spending_HHS pair, completed in 11.20 seconds. 78 out of 87 samples remain. +2024-02-05 08:00:57 → root → INFO: Sampling industry_healthcare_social_services_total/spending_HHS pair now. +2024-02-05 08:01:08 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_HHS pair, completed in 11.40 seconds. 77 out of 87 samples remain. +2024-02-05 08:01:08 → root → INFO: Sampling industry_information_total/spending_HHS pair now. +2024-02-05 08:01:18 → root → INFO: Done sampling industry_information_total/spending_HHS pair, completed in 10.28 seconds. 76 out of 87 samples remain. +2024-02-05 08:01:18 → root → INFO: Sampling industry_management_enterprises_total/spending_HHS pair now. +2024-02-05 08:01:29 → root → INFO: Done sampling industry_management_enterprises_total/spending_HHS pair, completed in 10.24 seconds. 75 out of 87 samples remain. +2024-02-05 08:01:29 → root → INFO: Sampling industry_manufacturing_total/spending_HHS pair now. +2024-02-05 08:01:39 → root → INFO: Done sampling industry_manufacturing_total/spending_HHS pair, completed in 10.77 seconds. 74 out of 87 samples remain. +2024-02-05 08:01:39 → root → INFO: Sampling industry_mining_total/spending_HHS pair now. +2024-02-05 08:01:50 → root → INFO: Done sampling industry_mining_total/spending_HHS pair, completed in 10.71 seconds. 73 out of 87 samples remain. +2024-02-05 08:01:50 → root → INFO: Sampling industry_other_services_total/spending_HHS pair now. +2024-02-05 08:02:01 → root → INFO: Done sampling industry_other_services_total/spending_HHS pair, completed in 10.87 seconds. 72 out of 87 samples remain. +2024-02-05 08:02:01 → root → INFO: Sampling industry_professional_services_total/spending_HHS pair now. +2024-02-05 08:02:13 → root → INFO: Done sampling industry_professional_services_total/spending_HHS pair, completed in 11.57 seconds. 71 out of 87 samples remain. +2024-02-05 08:02:13 → root → INFO: Sampling industry_public_administration_total/spending_HHS pair now. +2024-02-05 08:02:24 → root → INFO: Done sampling industry_public_administration_total/spending_HHS pair, completed in 11.62 seconds. 70 out of 87 samples remain. +2024-02-05 08:02:24 → root → INFO: Sampling industry_real_estate_total/spending_HHS pair now. +2024-02-05 08:02:36 → root → INFO: Done sampling industry_real_estate_total/spending_HHS pair, completed in 11.42 seconds. 69 out of 87 samples remain. +2024-02-05 08:02:36 → root → INFO: Sampling industry_retail_trade_total/spending_HHS pair now. +2024-02-05 08:02:48 → root → INFO: Done sampling industry_retail_trade_total/spending_HHS pair, completed in 12.24 seconds. 68 out of 87 samples remain. +2024-02-05 08:02:48 → root → INFO: Sampling industry_transportation_warehousing_total/spending_HHS pair now. +2024-02-05 08:02:59 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_HHS pair, completed in 11.54 seconds. 67 out of 87 samples remain. +2024-02-05 08:02:59 → root → INFO: Sampling industry_utilities_total/spending_HHS pair now. +2024-02-05 08:03:11 → root → INFO: Done sampling industry_utilities_total/spending_HHS pair, completed in 11.30 seconds. 66 out of 87 samples remain. +2024-02-05 08:03:11 → root → INFO: Sampling industry_wholesale_trade_total/spending_HHS pair now. +2024-02-05 08:03:22 → root → INFO: Done sampling industry_wholesale_trade_total/spending_HHS pair, completed in 10.93 seconds. 65 out of 87 samples remain. +2024-02-05 08:03:22 → root → INFO: Sampling medianHouseholdIncome/spending_HHS pair now. +2024-02-05 08:03:32 → root → INFO: Done sampling medianHouseholdIncome/spending_HHS pair, completed in 10.51 seconds. 64 out of 87 samples remain. +2024-02-05 08:03:32 → root → INFO: Sampling population/spending_HHS pair now. +2024-02-05 08:03:43 → root → INFO: Done sampling population/spending_HHS pair, completed in 10.44 seconds. 63 out of 87 samples remain. +2024-02-05 08:03:43 → root → INFO: Sampling population_density/spending_HHS pair now. +2024-02-05 08:03:53 → root → INFO: Done sampling population_density/spending_HHS pair, completed in 10.18 seconds. 62 out of 87 samples remain. +2024-02-05 08:03:53 → root → INFO: Sampling povertyAll/spending_HHS pair now. +2024-02-05 08:04:03 → root → INFO: Done sampling povertyAll/spending_HHS pair, completed in 10.01 seconds. 61 out of 87 samples remain. +2024-02-05 08:04:03 → root → INFO: Sampling povertyAllprct/spending_HHS pair now. +2024-02-05 08:04:14 → root → INFO: Done sampling povertyAllprct/spending_HHS pair, completed in 11.40 seconds. 60 out of 87 samples remain. +2024-02-05 08:04:14 → root → INFO: Sampling povertyUnder18/spending_HHS pair now. +2024-02-05 08:04:25 → root → INFO: Done sampling povertyUnder18/spending_HHS pair, completed in 10.35 seconds. 59 out of 87 samples remain. +2024-02-05 08:04:25 → root → INFO: Sampling povertyUnder18prct/spending_HHS pair now. +2024-02-05 08:04:36 → root → INFO: Done sampling povertyUnder18prct/spending_HHS pair, completed in 11.44 seconds. 58 out of 87 samples remain. +2024-02-05 08:04:36 → root → INFO: Sampling unemployment_rate/spending_HHS pair now. +2024-02-05 08:04:48 → root → INFO: Done sampling unemployment_rate/spending_HHS pair, completed in 11.90 seconds. 57 out of 87 samples remain. +2024-02-05 08:04:48 → root → INFO: Sampling gdp/spending_commerce pair now. +2024-02-05 08:04:59 → root → INFO: Done sampling gdp/spending_commerce pair, completed in 10.69 seconds. 56 out of 87 samples remain. +2024-02-05 08:04:59 → root → INFO: Sampling industry_accommodation_food_services_total/spending_commerce pair now. +2024-02-05 08:05:10 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_commerce pair, completed in 11.15 seconds. 55 out of 87 samples remain. +2024-02-05 08:05:10 → root → INFO: Sampling industry_admin_support_services_total/spending_commerce pair now. +2024-02-05 08:05:21 → root → INFO: Done sampling industry_admin_support_services_total/spending_commerce pair, completed in 11.26 seconds. 54 out of 87 samples remain. +2024-02-05 08:05:21 → root → INFO: Sampling industry_agriculture_total/spending_commerce pair now. +2024-02-05 08:05:32 → root → INFO: Done sampling industry_agriculture_total/spending_commerce pair, completed in 11.07 seconds. 53 out of 87 samples remain. +2024-02-05 08:05:32 → root → INFO: Sampling industry_arts_recreation_total/spending_commerce pair now. +2024-02-05 08:05:43 → root → INFO: Done sampling industry_arts_recreation_total/spending_commerce pair, completed in 11.10 seconds. 52 out of 87 samples remain. +2024-02-05 08:05:43 → root → INFO: Sampling industry_construction_total/spending_commerce pair now. +2024-02-05 08:05:55 → root → INFO: Done sampling industry_construction_total/spending_commerce pair, completed in 11.87 seconds. 51 out of 87 samples remain. +2024-02-05 08:05:55 → root → INFO: Sampling industry_educational_services_total/spending_commerce pair now. +2024-02-05 08:06:05 → root → INFO: Done sampling industry_educational_services_total/spending_commerce pair, completed in 10.10 seconds. 50 out of 87 samples remain. +2024-02-05 08:06:05 → root → INFO: Sampling industry_finance_insurance_total/spending_commerce pair now. +2024-02-05 08:06:16 → root → INFO: Done sampling industry_finance_insurance_total/spending_commerce pair, completed in 10.99 seconds. 49 out of 87 samples remain. +2024-02-05 08:06:16 → root → INFO: Sampling industry_healthcare_social_services_total/spending_commerce pair now. +2024-02-05 08:06:28 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_commerce pair, completed in 11.72 seconds. 48 out of 87 samples remain. +2024-02-05 08:06:28 → root → INFO: Sampling industry_information_total/spending_commerce pair now. +2024-02-05 08:06:39 → root → INFO: Done sampling industry_information_total/spending_commerce pair, completed in 10.90 seconds. 47 out of 87 samples remain. +2024-02-05 08:06:39 → root → INFO: Sampling industry_management_enterprises_total/spending_commerce pair now. +2024-02-05 08:06:49 → root → INFO: Done sampling industry_management_enterprises_total/spending_commerce pair, completed in 10.57 seconds. 46 out of 87 samples remain. +2024-02-05 08:06:49 → root → INFO: Sampling industry_manufacturing_total/spending_commerce pair now. +2024-02-05 08:06:59 → root → INFO: Done sampling industry_manufacturing_total/spending_commerce pair, completed in 9.30 seconds. 45 out of 87 samples remain. +2024-02-05 08:06:59 → root → INFO: Sampling industry_mining_total/spending_commerce pair now. +2024-02-05 08:07:09 → root → INFO: Done sampling industry_mining_total/spending_commerce pair, completed in 10.16 seconds. 44 out of 87 samples remain. +2024-02-05 08:07:09 → root → INFO: Sampling industry_other_services_total/spending_commerce pair now. +2024-02-05 08:07:17 → root → INFO: Done sampling industry_other_services_total/spending_commerce pair, completed in 8.35 seconds. 43 out of 87 samples remain. +2024-02-05 08:07:17 → root → INFO: Sampling industry_professional_services_total/spending_commerce pair now. +2024-02-05 08:07:29 → root → INFO: Done sampling industry_professional_services_total/spending_commerce pair, completed in 11.52 seconds. 42 out of 87 samples remain. +2024-02-05 08:07:29 → root → INFO: Sampling industry_public_administration_total/spending_commerce pair now. +2024-02-05 08:07:39 → root → INFO: Done sampling industry_public_administration_total/spending_commerce pair, completed in 10.19 seconds. 41 out of 87 samples remain. +2024-02-05 08:07:39 → root → INFO: Sampling industry_real_estate_total/spending_commerce pair now. +2024-02-05 08:07:49 → root → INFO: Done sampling industry_real_estate_total/spending_commerce pair, completed in 10.43 seconds. 40 out of 87 samples remain. +2024-02-05 08:07:49 → root → INFO: Sampling industry_retail_trade_total/spending_commerce pair now. +2024-02-05 08:08:00 → root → INFO: Done sampling industry_retail_trade_total/spending_commerce pair, completed in 10.61 seconds. 39 out of 87 samples remain. +2024-02-05 08:08:00 → root → INFO: Sampling industry_transportation_warehousing_total/spending_commerce pair now. +2024-02-05 08:08:11 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_commerce pair, completed in 11.18 seconds. 38 out of 87 samples remain. +2024-02-05 08:08:11 → root → INFO: Sampling industry_utilities_total/spending_commerce pair now. +2024-02-05 08:08:22 → root → INFO: Done sampling industry_utilities_total/spending_commerce pair, completed in 11.03 seconds. 37 out of 87 samples remain. +2024-02-05 08:08:22 → root → INFO: Sampling industry_wholesale_trade_total/spending_commerce pair now. +2024-02-05 08:08:33 → root → INFO: Done sampling industry_wholesale_trade_total/spending_commerce pair, completed in 10.73 seconds. 36 out of 87 samples remain. +2024-02-05 08:08:33 → root → INFO: Sampling medianHouseholdIncome/spending_commerce pair now. +2024-02-05 08:08:43 → root → INFO: Done sampling medianHouseholdIncome/spending_commerce pair, completed in 10.64 seconds. 35 out of 87 samples remain. +2024-02-05 08:08:43 → root → INFO: Sampling population/spending_commerce pair now. +2024-02-05 08:08:54 → root → INFO: Done sampling population/spending_commerce pair, completed in 10.71 seconds. 34 out of 87 samples remain. +2024-02-05 08:08:54 → root → INFO: Sampling population_density/spending_commerce pair now. +2024-02-05 08:09:04 → root → INFO: Done sampling population_density/spending_commerce pair, completed in 10.22 seconds. 33 out of 87 samples remain. +2024-02-05 08:09:04 → root → INFO: Sampling povertyAll/spending_commerce pair now. +2024-02-05 08:09:16 → root → INFO: Done sampling povertyAll/spending_commerce pair, completed in 11.75 seconds. 32 out of 87 samples remain. +2024-02-05 08:09:16 → root → INFO: Sampling povertyAllprct/spending_commerce pair now. +2024-02-05 08:09:27 → root → INFO: Done sampling povertyAllprct/spending_commerce pair, completed in 11.15 seconds. 31 out of 87 samples remain. +2024-02-05 08:09:27 → root → INFO: Sampling povertyUnder18/spending_commerce pair now. +2024-02-05 08:09:38 → root → INFO: Done sampling povertyUnder18/spending_commerce pair, completed in 10.48 seconds. 30 out of 87 samples remain. +2024-02-05 08:09:38 → root → INFO: Sampling povertyUnder18prct/spending_commerce pair now. +2024-02-05 08:09:48 → root → INFO: Done sampling povertyUnder18prct/spending_commerce pair, completed in 10.22 seconds. 29 out of 87 samples remain. +2024-02-05 08:09:48 → root → INFO: Sampling unemployment_rate/spending_commerce pair now. +2024-02-05 08:10:00 → root → INFO: Done sampling unemployment_rate/spending_commerce pair, completed in 11.60 seconds. 28 out of 87 samples remain. +2024-02-05 08:10:00 → root → INFO: Sampling gdp/spending_transportation pair now. +2024-02-05 08:10:10 → root → INFO: Done sampling gdp/spending_transportation pair, completed in 10.35 seconds. 27 out of 87 samples remain. +2024-02-05 08:10:10 → root → INFO: Sampling industry_accommodation_food_services_total/spending_transportation pair now. +2024-02-05 08:10:20 → root → INFO: Done sampling industry_accommodation_food_services_total/spending_transportation pair, completed in 10.20 seconds. 26 out of 87 samples remain. +2024-02-05 08:10:20 → root → INFO: Sampling industry_admin_support_services_total/spending_transportation pair now. +2024-02-05 08:10:29 → root → INFO: Done sampling industry_admin_support_services_total/spending_transportation pair, completed in 8.98 seconds. 25 out of 87 samples remain. +2024-02-05 08:10:29 → root → INFO: Sampling industry_agriculture_total/spending_transportation pair now. +2024-02-05 08:10:39 → root → INFO: Done sampling industry_agriculture_total/spending_transportation pair, completed in 10.02 seconds. 24 out of 87 samples remain. +2024-02-05 08:10:39 → root → INFO: Sampling industry_arts_recreation_total/spending_transportation pair now. +2024-02-05 08:10:50 → root → INFO: Done sampling industry_arts_recreation_total/spending_transportation pair, completed in 10.50 seconds. 23 out of 87 samples remain. +2024-02-05 08:10:50 → root → INFO: Sampling industry_construction_total/spending_transportation pair now. +2024-02-05 08:10:59 → root → INFO: Done sampling industry_construction_total/spending_transportation pair, completed in 9.70 seconds. 22 out of 87 samples remain. +2024-02-05 08:10:59 → root → INFO: Sampling industry_educational_services_total/spending_transportation pair now. +2024-02-05 08:11:11 → root → INFO: Done sampling industry_educational_services_total/spending_transportation pair, completed in 11.28 seconds. 21 out of 87 samples remain. +2024-02-05 08:11:11 → root → INFO: Sampling industry_finance_insurance_total/spending_transportation pair now. +2024-02-05 08:11:21 → root → INFO: Done sampling industry_finance_insurance_total/spending_transportation pair, completed in 10.47 seconds. 20 out of 87 samples remain. +2024-02-05 08:11:21 → root → INFO: Sampling industry_healthcare_social_services_total/spending_transportation pair now. +2024-02-05 08:11:32 → root → INFO: Done sampling industry_healthcare_social_services_total/spending_transportation pair, completed in 11.21 seconds. 19 out of 87 samples remain. +2024-02-05 08:11:32 → root → INFO: Sampling industry_information_total/spending_transportation pair now. +2024-02-05 08:11:43 → root → INFO: Done sampling industry_information_total/spending_transportation pair, completed in 11.23 seconds. 18 out of 87 samples remain. +2024-02-05 08:11:43 → root → INFO: Sampling industry_management_enterprises_total/spending_transportation pair now. +2024-02-05 08:11:54 → root → INFO: Done sampling industry_management_enterprises_total/spending_transportation pair, completed in 10.93 seconds. 17 out of 87 samples remain. +2024-02-05 08:11:54 → root → INFO: Sampling industry_manufacturing_total/spending_transportation pair now. +2024-02-05 08:12:06 → root → INFO: Done sampling industry_manufacturing_total/spending_transportation pair, completed in 11.21 seconds. 16 out of 87 samples remain. +2024-02-05 08:12:06 → root → INFO: Sampling industry_mining_total/spending_transportation pair now. +2024-02-05 08:12:16 → root → INFO: Done sampling industry_mining_total/spending_transportation pair, completed in 10.49 seconds. 15 out of 87 samples remain. +2024-02-05 08:12:16 → root → INFO: Sampling industry_other_services_total/spending_transportation pair now. +2024-02-05 08:12:26 → root → INFO: Done sampling industry_other_services_total/spending_transportation pair, completed in 10.13 seconds. 14 out of 87 samples remain. +2024-02-05 08:12:26 → root → INFO: Sampling industry_professional_services_total/spending_transportation pair now. +2024-02-05 08:12:37 → root → INFO: Done sampling industry_professional_services_total/spending_transportation pair, completed in 10.96 seconds. 13 out of 87 samples remain. +2024-02-05 08:12:37 → root → INFO: Sampling industry_public_administration_total/spending_transportation pair now. +2024-02-05 08:12:48 → root → INFO: Done sampling industry_public_administration_total/spending_transportation pair, completed in 10.72 seconds. 12 out of 87 samples remain. +2024-02-05 08:12:48 → root → INFO: Sampling industry_real_estate_total/spending_transportation pair now. +2024-02-05 08:12:58 → root → INFO: Done sampling industry_real_estate_total/spending_transportation pair, completed in 10.54 seconds. 11 out of 87 samples remain. +2024-02-05 08:12:58 → root → INFO: Sampling industry_retail_trade_total/spending_transportation pair now. +2024-02-05 08:13:09 → root → INFO: Done sampling industry_retail_trade_total/spending_transportation pair, completed in 10.14 seconds. 10 out of 87 samples remain. +2024-02-05 08:13:09 → root → INFO: Sampling industry_transportation_warehousing_total/spending_transportation pair now. +2024-02-05 08:13:20 → root → INFO: Done sampling industry_transportation_warehousing_total/spending_transportation pair, completed in 11.12 seconds. 9 out of 87 samples remain. +2024-02-05 08:13:20 → root → INFO: Sampling industry_utilities_total/spending_transportation pair now. +2024-02-05 08:13:30 → root → INFO: Done sampling industry_utilities_total/spending_transportation pair, completed in 9.91 seconds. 8 out of 87 samples remain. +2024-02-05 08:13:30 → root → INFO: Sampling industry_wholesale_trade_total/spending_transportation pair now. +2024-02-05 08:13:41 → root → INFO: Done sampling industry_wholesale_trade_total/spending_transportation pair, completed in 11.18 seconds. 7 out of 87 samples remain. +2024-02-05 08:13:41 → root → INFO: Sampling medianHouseholdIncome/spending_transportation pair now. +2024-02-05 08:13:52 → root → INFO: Done sampling medianHouseholdIncome/spending_transportation pair, completed in 11.54 seconds. 6 out of 87 samples remain. +2024-02-05 08:13:52 → root → INFO: Sampling population/spending_transportation pair now. +2024-02-05 08:14:03 → root → INFO: Done sampling population/spending_transportation pair, completed in 10.41 seconds. 5 out of 87 samples remain. +2024-02-05 08:14:03 → root → INFO: Sampling population_density/spending_transportation pair now. +2024-02-05 08:14:12 → root → INFO: Done sampling population_density/spending_transportation pair, completed in 9.71 seconds. 4 out of 87 samples remain. +2024-02-05 08:14:12 → root → INFO: Sampling povertyAll/spending_transportation pair now. +2024-02-05 08:14:23 → root → INFO: Done sampling povertyAll/spending_transportation pair, completed in 10.15 seconds. 3 out of 87 samples remain. +2024-02-05 08:14:23 → root → INFO: Sampling povertyAllprct/spending_transportation pair now. +2024-02-05 08:14:33 → root → INFO: Done sampling povertyAllprct/spending_transportation pair, completed in 10.08 seconds. 2 out of 87 samples remain. +2024-02-05 08:14:33 → root → INFO: Sampling povertyUnder18/spending_transportation pair now. +2024-02-05 08:14:42 → root → INFO: Done sampling povertyUnder18/spending_transportation pair, completed in 9.41 seconds. 1 out of 87 samples remain. +2024-02-05 08:14:42 → root → INFO: Sampling povertyUnder18prct/spending_transportation pair now. +2024-02-05 08:14:53 → root → INFO: Done sampling povertyUnder18prct/spending_transportation pair, completed in 10.52 seconds. 0 out of 87 samples remain. +2024-02-05 08:14:53 → root → INFO: Sampling unemployment_rate/spending_transportation pair now. +2024-02-05 08:15:03 → root → INFO: Done sampling unemployment_rate/spending_transportation pair, completed in 10.56 seconds. -1 out of 87 samples remain. +2024-02-05 08:15:03 → root → INFO: All samples are now available.Sampling took 941.25 seconds, or 15.69 minutes. diff --git a/data/tau_samples/spending_HHS_gdp_1000_tau.pkl b/data/tau_samples/spending_HHS_gdp_1000_tau.pkl index 812e9e1c..90486fd0 100644 Binary files a/data/tau_samples/spending_HHS_gdp_1000_tau.pkl and b/data/tau_samples/spending_HHS_gdp_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_gdp_5_tau.pkl b/data/tau_samples/spending_HHS_gdp_5_tau.pkl deleted file mode 100644 index 1d2e66b3..00000000 Binary files a/data/tau_samples/spending_HHS_gdp_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_HHS_industry_accommodation_food_services_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_accommodation_food_services_total_1000_tau.pkl index 6aa8700d..8172b9a9 100644 Binary files a/data/tau_samples/spending_HHS_industry_accommodation_food_services_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_accommodation_food_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_admin_support_services_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_admin_support_services_total_1000_tau.pkl index de095dfe..69ba76a0 100644 Binary files a/data/tau_samples/spending_HHS_industry_admin_support_services_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_admin_support_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_admin_support_services_total_5_tau.pkl b/data/tau_samples/spending_HHS_industry_admin_support_services_total_5_tau.pkl deleted file mode 100644 index c8402b98..00000000 Binary files a/data/tau_samples/spending_HHS_industry_admin_support_services_total_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_HHS_industry_agriculture_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_agriculture_total_1000_tau.pkl index dc2cca83..75fa39ae 100644 Binary files a/data/tau_samples/spending_HHS_industry_agriculture_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_agriculture_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_arts_recreation_total_1000_tau.pkl 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b/data/tau_samples/spending_HHS_industry_educational_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_finance_insurance_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_finance_insurance_total_1000_tau.pkl index 53674335..746e3057 100644 Binary files a/data/tau_samples/spending_HHS_industry_finance_insurance_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_finance_insurance_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_healthcare_social_services_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_healthcare_social_services_total_1000_tau.pkl index f82cbf66..36d8daf0 100644 Binary files a/data/tau_samples/spending_HHS_industry_healthcare_social_services_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_healthcare_social_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_information_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_information_total_1000_tau.pkl index fe485808..5faa99d4 100644 Binary files a/data/tau_samples/spending_HHS_industry_information_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_information_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_information_total_5_tau.pkl b/data/tau_samples/spending_HHS_industry_information_total_5_tau.pkl deleted file mode 100644 index 8808e4aa..00000000 Binary files a/data/tau_samples/spending_HHS_industry_information_total_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_HHS_industry_management_enterprises_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_management_enterprises_total_1000_tau.pkl index b36d1a47..a81e861a 100644 Binary files a/data/tau_samples/spending_HHS_industry_management_enterprises_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_management_enterprises_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_manufacturing_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_manufacturing_total_1000_tau.pkl index f18a8f85..4356fa06 100644 Binary files a/data/tau_samples/spending_HHS_industry_manufacturing_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_manufacturing_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_mining_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_mining_total_1000_tau.pkl index daf244c2..b1f96f5a 100644 Binary files a/data/tau_samples/spending_HHS_industry_mining_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_mining_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_other_services_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_other_services_total_1000_tau.pkl index a8350cbb..5bcaa49c 100644 Binary files a/data/tau_samples/spending_HHS_industry_other_services_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_other_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_professional_services_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_professional_services_total_1000_tau.pkl index 3bd69f1a..7a95f2fe 100644 Binary files a/data/tau_samples/spending_HHS_industry_professional_services_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_professional_services_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_public_administration_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_public_administration_total_1000_tau.pkl index 88a53634..278f2e8f 100644 Binary files a/data/tau_samples/spending_HHS_industry_public_administration_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_public_administration_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_real_estate_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_real_estate_total_1000_tau.pkl index 5933be56..a437d7ba 100644 Binary files a/data/tau_samples/spending_HHS_industry_real_estate_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_real_estate_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_retail_trade_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_retail_trade_total_1000_tau.pkl index 10391759..66e6b469 100644 Binary files a/data/tau_samples/spending_HHS_industry_retail_trade_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_retail_trade_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_transportation_warehousing_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_transportation_warehousing_total_1000_tau.pkl index aeed0355..6f9ae189 100644 Binary files a/data/tau_samples/spending_HHS_industry_transportation_warehousing_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_transportation_warehousing_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_utilities_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_utilities_total_1000_tau.pkl index eaad88a6..c92c4b5f 100644 Binary files a/data/tau_samples/spending_HHS_industry_utilities_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_utilities_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_industry_utilities_total_5_tau.pkl b/data/tau_samples/spending_HHS_industry_utilities_total_5_tau.pkl deleted file mode 100644 index 09fb5202..00000000 Binary files a/data/tau_samples/spending_HHS_industry_utilities_total_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_HHS_industry_wholesale_trade_total_1000_tau.pkl b/data/tau_samples/spending_HHS_industry_wholesale_trade_total_1000_tau.pkl index c3d21355..3c0c8edf 100644 Binary files a/data/tau_samples/spending_HHS_industry_wholesale_trade_total_1000_tau.pkl and b/data/tau_samples/spending_HHS_industry_wholesale_trade_total_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_medianHouseholdIncome_1000_tau.pkl b/data/tau_samples/spending_HHS_medianHouseholdIncome_1000_tau.pkl index 2a007b88..584a5af5 100644 Binary files a/data/tau_samples/spending_HHS_medianHouseholdIncome_1000_tau.pkl and b/data/tau_samples/spending_HHS_medianHouseholdIncome_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_population_1000_tau.pkl b/data/tau_samples/spending_HHS_population_1000_tau.pkl index 75137478..45c9afc7 100644 Binary files a/data/tau_samples/spending_HHS_population_1000_tau.pkl and b/data/tau_samples/spending_HHS_population_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_population_density_1000_tau.pkl b/data/tau_samples/spending_HHS_population_density_1000_tau.pkl new file mode 100644 index 00000000..92ecb1cf Binary files /dev/null and b/data/tau_samples/spending_HHS_population_density_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_povertyAll_1000_tau.pkl b/data/tau_samples/spending_HHS_povertyAll_1000_tau.pkl index 6b83b006..e62021c2 100644 Binary files a/data/tau_samples/spending_HHS_povertyAll_1000_tau.pkl and b/data/tau_samples/spending_HHS_povertyAll_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_povertyAll_5_tau.pkl b/data/tau_samples/spending_HHS_povertyAll_5_tau.pkl deleted file mode 100644 index 51be883a..00000000 Binary files a/data/tau_samples/spending_HHS_povertyAll_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_HHS_povertyAllprct_1000_tau.pkl b/data/tau_samples/spending_HHS_povertyAllprct_1000_tau.pkl index 7ad933db..a3e203c1 100644 Binary files a/data/tau_samples/spending_HHS_povertyAllprct_1000_tau.pkl and b/data/tau_samples/spending_HHS_povertyAllprct_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_povertyUnder18_1000_tau.pkl b/data/tau_samples/spending_HHS_povertyUnder18_1000_tau.pkl index 3f40a1a5..5bcbbc7e 100644 Binary files a/data/tau_samples/spending_HHS_povertyUnder18_1000_tau.pkl and b/data/tau_samples/spending_HHS_povertyUnder18_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_povertyUnder18prct_1000_tau.pkl b/data/tau_samples/spending_HHS_povertyUnder18prct_1000_tau.pkl index dc81cc15..dc50ad25 100644 Binary files a/data/tau_samples/spending_HHS_povertyUnder18prct_1000_tau.pkl and b/data/tau_samples/spending_HHS_povertyUnder18prct_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_unemployment_rate_1000_tau.pkl b/data/tau_samples/spending_HHS_unemployment_rate_1000_tau.pkl index 65b1b00a..e09f5c3b 100644 Binary files a/data/tau_samples/spending_HHS_unemployment_rate_1000_tau.pkl and b/data/tau_samples/spending_HHS_unemployment_rate_1000_tau.pkl differ diff --git a/data/tau_samples/spending_HHS_unemployment_rate_5_tau.pkl b/data/tau_samples/spending_HHS_unemployment_rate_5_tau.pkl deleted file mode 100644 index 29c797bf..00000000 Binary files a/data/tau_samples/spending_HHS_unemployment_rate_5_tau.pkl and /dev/null differ diff --git a/data/tau_samples/spending_commerce_gdp_1000_tau.pkl b/data/tau_samples/spending_commerce_gdp_1000_tau.pkl index 0d0375a9..417d14ff 100644 Binary files a/data/tau_samples/spending_commerce_gdp_1000_tau.pkl and b/data/tau_samples/spending_commerce_gdp_1000_tau.pkl differ diff --git a/data/tau_samples/spending_commerce_industry_accommodation_food_services_total_1000_tau.pkl b/data/tau_samples/spending_commerce_industry_accommodation_food_services_total_1000_tau.pkl index 6747ce39..29a1ae5b 100644 Binary files a/data/tau_samples/spending_commerce_industry_accommodation_food_services_total_1000_tau.pkl and b/data/tau_samples/spending_commerce_industry_accommodation_food_services_total_1000_tau.pkl differ diff --git 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b/data/years_available/spending_commerce_population_density.pkl new file mode 100644 index 00000000..fce20c26 Binary files /dev/null and b/data/years_available/spending_commerce_population_density.pkl differ diff --git a/data/years_available/spending_transportation_population_density.pkl b/data/years_available/spending_transportation_population_density.pkl new file mode 100644 index 00000000..fce20c26 Binary files /dev/null and b/data/years_available/spending_transportation_population_density.pkl differ diff --git a/docs/guides/counterfactual-explained.ipynb b/docs/guides/counterfactual-explained.ipynb index e8e91067..f60fb50b 100644 --- a/docs/guides/counterfactual-explained.ipynb +++ b/docs/guides/counterfactual-explained.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -20,8 +20,7 @@ "import plotly.express as px\n", "import seaborn as sns\n", "\n", - "from cities.queries.causal_insight_slim import \\\n", - "n-placeCausalInsightSlim as CausalInsight\n", + "from cities.queries.causal_insight_slim import CausalInsightSlim\n", "from cities.utils.data_grabber import (DataGrabber, find_repo_root,\n", " list_available_features,\n", " list_interventions, list_outcomes,\n", @@ -34,12 +33,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Suppose you're interested in the impact of the Department of Commerce funding on the unemployment rate. Assume further that you're particularly interested in the fate of Northwest Arctic Borough, AK and what this county has potentially to gain from such funding. Say we want to estimate the causal role such a funding could have had if received in 2016. (this is because we can only fairly reliably estimate three years ahead, and we want to end the estimation period before the Covid pandemic, to avoid complications in the discussion of the result). Since you know it is unreasonable to expect such funding to have immediate impact, you allow for a one year of \"grace period\" and look at the outcome in 2018. The first thing you can you is load the data:" + "Suppose you're interested in the impact of the Department of Commerce funding on the unemployment rate. Assume further that you're particularly interested in the fate of Imperial County, CA and what this county has potentially to gain from such funding. Say we want to estimate the causal role such a funding could have had if received in 2016. (this is because we can only fairly reliably estimate three years ahead, and we want to end the estimation period before the Covid pandemic, to avoid complications in the discussion of the result). Since you know it is unreasonable to expect such funding to have immediate impact, you allow for a one year of \"grace period\" and look at the outcome in 2018. The first thing you can you is load the data:" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -378,9 +377,344 @@ }, "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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GeoFIPSGeoName19901991199219931994199519961997...2013201420152016201720182019202020212022
1906025Imperial County, CA25.426.330.929.426.529.230.126.9...25.324.324.624.219.718.820.722.617.514.7
105821153Magoffin County, KY15.518.016.115.413.715.214.613.9...17.413.915.619.616.012.610.515.611.510.5
1024027Yuma County, AZ20.620.926.627.931.329.530.627.5...25.622.921.819.117.216.916.717.113.112.5
872290Yukon-Koyukuk Census Area, AK14.616.117.715.216.217.517.114.2...18.418.717.817.216.613.713.112.712.37.9
1836011Colusa County, CA14.218.121.721.719.219.720.119.0...19.117.615.515.614.313.212.916.412.511.6
842188Northwest Arctic Borough, AK14.915.720.217.015.516.317.614.3...16.516.815.515.415.212.813.012.711.59.0
141428063Jefferson County, MS22.928.420.917.817.815.515.315.7...19.216.315.115.215.013.415.918.215.813.0
179335029Luna County, NM13.115.116.716.021.024.826.925.7...18.917.917.514.613.911.812.315.415.39.9
651131Wilcox County, AL12.515.617.917.515.315.614.114.0...19.516.814.714.511.79.57.515.910.57.8
141028055Issaquena County, MS11.913.412.913.514.816.117.914.5...20.417.617.214.312.29.212.28.98.97.3
\n", + "

10 rows × 35 columns

\n", + "
" + ], + "text/plain": [ + " GeoFIPS GeoName 1990 1991 1992 1993 1994 \\\n", + "190 6025 Imperial County, CA 25.4 26.3 30.9 29.4 26.5 \n", + "1058 21153 Magoffin County, KY 15.5 18.0 16.1 15.4 13.7 \n", + "102 4027 Yuma County, AZ 20.6 20.9 26.6 27.9 31.3 \n", + "87 2290 Yukon-Koyukuk Census Area, AK 14.6 16.1 17.7 15.2 16.2 \n", + "183 6011 Colusa County, CA 14.2 18.1 21.7 21.7 19.2 \n", + "84 2188 Northwest Arctic Borough, AK 14.9 15.7 20.2 17.0 15.5 \n", + "1414 28063 Jefferson County, MS 22.9 28.4 20.9 17.8 17.8 \n", + "1793 35029 Luna County, NM 13.1 15.1 16.7 16.0 21.0 \n", + "65 1131 Wilcox County, AL 12.5 15.6 17.9 17.5 15.3 \n", + "1410 28055 Issaquena County, MS 11.9 13.4 12.9 13.5 14.8 \n", + "\n", + " 1995 1996 1997 ... 2013 2014 2015 2016 2017 2018 2019 2020 \\\n", + "190 29.2 30.1 26.9 ... 25.3 24.3 24.6 24.2 19.7 18.8 20.7 22.6 \n", + "1058 15.2 14.6 13.9 ... 17.4 13.9 15.6 19.6 16.0 12.6 10.5 15.6 \n", + "102 29.5 30.6 27.5 ... 25.6 22.9 21.8 19.1 17.2 16.9 16.7 17.1 \n", + "87 17.5 17.1 14.2 ... 18.4 18.7 17.8 17.2 16.6 13.7 13.1 12.7 \n", + "183 19.7 20.1 19.0 ... 19.1 17.6 15.5 15.6 14.3 13.2 12.9 16.4 \n", + "84 16.3 17.6 14.3 ... 16.5 16.8 15.5 15.4 15.2 12.8 13.0 12.7 \n", + "1414 15.5 15.3 15.7 ... 19.2 16.3 15.1 15.2 15.0 13.4 15.9 18.2 \n", + "1793 24.8 26.9 25.7 ... 18.9 17.9 17.5 14.6 13.9 11.8 12.3 15.4 \n", + "65 15.6 14.1 14.0 ... 19.5 16.8 14.7 14.5 11.7 9.5 7.5 15.9 \n", + "1410 16.1 17.9 14.5 ... 20.4 17.6 17.2 14.3 12.2 9.2 12.2 8.9 \n", + "\n", + " 2021 2022 \n", + "190 17.5 14.7 \n", + "1058 11.5 10.5 \n", + "102 13.1 12.5 \n", + "87 12.3 7.9 \n", + "183 12.5 11.6 \n", + "84 11.5 9.0 \n", + "1414 15.8 13.0 \n", + "1793 15.3 9.9 \n", + "65 10.5 7.8 \n", + "1410 8.9 7.3 \n", + "\n", + "[10 rows x 35 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ + "CausalInsight = CausalInsightSlim # hacky way of avoiding isort complaining\n", + "\n", "outcome = \"unemployment_rate\"\n", "intervention = \"spending_commerce\"\n", "forward_shift = 2\n", @@ -388,7 +722,10 @@ "dg = DataGrabber()\n", "dg.get_features_wide([outcome, intervention])\n", "\n", - "display(dg.wide[intervention].head(), dg.wide[outcome].head())" + "display(dg.wide[intervention].head(), dg.wide[outcome].head())\n", + "\n", + "sorted = dg.wide[outcome].sort_values(by=\"2016\", ascending=False)\n", + "display(sorted.head(10))" ] }, { @@ -400,7 +737,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -413,7 +750,7 @@ { "alignmentgroup": "True", "boxpoints": "all", - "hovertemplate": "North Arctic Borough, AK=False
Group=%{x}
out_data=%{y}", + "hovertemplate": "Imperial County, CA=False
Group=%{x}
out_data=%{y}", "legendgroup": "False", "marker": { "color": "#636efa" @@ -2922,6 +3259,7 @@ 5.5, 10.2, 6.9, + 12.8, 8.9, 13.7, 5.8, @@ -3000,7 +3338,6 @@ 4, 13.2, 6.6, - 18.8, 3.9, 8.1, 5.3, @@ -5296,7 +5633,7 @@ { "alignmentgroup": "True", "boxpoints": "all", - "hovertemplate": "North Arctic Borough, AK=True
Group=%{x}
out_data=%{y}", + "hovertemplate": "Imperial County, CA=True
Group=%{x}
out_data=%{y}", "legendgroup": "True", "marker": { "color": "#EF553B" @@ -5313,7 +5650,7 @@ "x0": " ", "xaxis": "x", "y": [ - 12.8 + 18.8 ], "y0": " ", "yaxis": "y" @@ -5333,9 +5670,9 @@ "size": 10 }, "showarrow": false, - "text": "North Arctic Borough, AK", - "x": 0.26, - "y": 13.5 + "text": "Imperial County, CA", + "x": 0.18, + "y": 18 }, { "showarrow": false, @@ -5347,7 +5684,7 @@ "boxmode": "group", "legend": { "title": { - "text": "North Arctic Borough, AK" + "text": "Imperial County, CA" }, "tracegroupgap": 0 }, @@ -5496,15 +5833,14 @@ } ], "source": [ - "# Northwest Arctic Borough, AK, fips = 2188\n", - "\n", "int_data = dg.wide[intervention][\"2016\"]\n", "out_data = dg.wide[outcome][\"2018\"]\n", "\n", "unfunded_mask = int_data <= 0\n", "moderately_funded_mask = int_data > 1 * 1e8\n", "unfunded_data = out_data[unfunded_mask]\n", - "unfunded_fips_2188_mask = dg.wide[outcome][\"GeoFIPS\"][unfunded_mask] == 2188\n", + "\n", + "unfunded_fips_6025_mask = dg.wide[outcome][\"GeoFIPS\"][unfunded_mask] == 6025\n", "moderately_data = out_data[moderately_funded_mask]\n", "false_array = np.tile(False, len(moderately_data))\n", "\n", @@ -5513,9 +5849,7 @@ " \"Group\": [\"no funding\"] * len(unfunded_data)\n", " + [\"$1B < funding\"] * len(moderately_data),\n", " \"out_data\": np.concatenate([unfunded_data, moderately_data]),\n", - " \"North Arctic Borough, AK\": np.concatenate(\n", - " [unfunded_fips_2188_mask, false_array]\n", - " ),\n", + " \"Imperial County, CA\": np.concatenate([unfunded_fips_6025_mask, false_array]),\n", " }\n", ")\n", "\n", @@ -5525,7 +5859,7 @@ " x=\"Group\",\n", " y=\"out_data\",\n", " points=\"all\",\n", - " color=\"North Arctic Borough, AK\",\n", + " color=\"Imperial County, CA\",\n", " title=\"The unfunded vs. the funded (2016 vs. 2018)\",\n", ")\n", "mean_unfunded = unfunded_data.mean()\n", @@ -5534,9 +5868,9 @@ " x=0.3, y=mean_unfunded, text=f\"Mean: {mean_unfunded:.2f}\", showarrow=False\n", ")\n", "fig.add_annotation(\n", - " x=0.26,\n", - " y=13.5,\n", - " text=\"North Arctic Borough, AK\",\n", + " x=0.18,\n", + " y=18,\n", + " text=\"Imperial County, CA\",\n", " font=dict(size=10, color=\"red\"),\n", " showarrow=False,\n", ")\n", @@ -5557,7 +5891,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -5612,7 +5946,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "There are, however, reasons to think that this way of thinking is a bit too hasty. The key problem is that neither U.S. Department of Commerce funding, nor unemployment arise in vacuum. For one thing, obviously, various covariates should be paid attention to, and their use might lead to more precise predictions that would take the specific circumstances of this county into consideration. The problem is deeper though: the protection effect that you think you see might simply arise because the places with high unemployment are under-staffed, under-funded or for some reasons ineligible for the department of commerce funding. The problem then is that the funded places more or less self-selected because some of their covariates caused the unfunded places to remain unfunded. You need to pay attention not only to covariates but also to the causal structure of the problem. This is what our model does, insofar as general application to all intput-output combinations permits." + "There are, however, reasons to think that this is a bit too hasty. The key problem is that neither U.S. Department of Commerce funding, nor unemployment arise in vacuum. For one thing, obviously, various covariates should be paid attention to, and their use might lead to more precise predictions that would take the specific circumstances of this county into consideration. The problem is deeper though: the protection effect that you think you see might simply arise because the places with high unemployment are under-staffed, under-funded or for some reasons ineligible for the department of commerce funding. The problem then is that the funded places more or less self-selected because some of their covariates caused the unfunded places to remain unfunded. You need to pay attention not only to covariates but also to the causal structure of the problem. This is what our model does, insofar as general application to all intput-output combinations permits." ] }, { @@ -5624,7 +5958,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -5663,12 +5997,12 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -5723,7 +6057,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -5758,34 +6092,34 @@ " \n", " 2016\n", " 2016\n", - " 15.4\n", - " 15.4\n", - " 15.4\n", - " 15.4\n", + " 24.2\n", + " 24.2\n", + " 24.2\n", + " 24.2\n", " \n", " \n", " 2017\n", " 2017\n", - " 15.2\n", - " 14.023429\n", - " 13.612568\n", - " 14.465484\n", + " 19.7\n", + " 18.520342\n", + " 17.716211\n", + " 19.459003\n", " \n", " \n", " 2018\n", " 2018\n", - " 12.8\n", - " 11.957299\n", - " 11.601073\n", - " 12.349377\n", + " 18.8\n", + " 17.467766\n", + " 16.659423\n", + " 18.46296\n", " \n", " \n", " 2019\n", " 2019\n", - " 13.0\n", - " 12.116861\n", - " 11.757838\n", - " 12.492489\n", + " 20.7\n", + " 18.389801\n", + " 17.338502\n", + " 19.864349\n", " \n", " \n", "\n", @@ -5793,10 +6127,10 @@ ], "text/plain": [ " year observed mean low high\n", - "2016 2016 15.4 15.4 15.4 15.4\n", - "2017 2017 15.2 14.023429 13.612568 14.465484\n", - "2018 2018 12.8 11.957299 11.601073 12.349377\n", - "2019 2019 13.0 12.116861 11.757838 12.492489" + "2016 2016 24.2 24.2 24.2 24.2\n", + "2017 2017 19.7 18.520342 17.716211 19.459003\n", + "2018 2018 18.8 17.467766 16.659423 18.46296\n", + "2019 2019 20.7 18.389801 17.338502 19.864349" ] }, "metadata": {}, @@ -5815,9 +6149,9 @@ "width": 3 }, "mode": "lines+markers", - "name": "Northwest Arctic Borough, AK", + "name": "Imperial County, CA", "showlegend": false, - "text": "Northwest Arctic Borough, AK", + "text": "Imperial County, CA", "textposition": "top right", "type": "scatter", "x": [ @@ -5856,39 +6190,39 @@ 2022 ], "y": [ - 14.9, + 25.4, + 26.3, + 30.9, + 29.4, + 26.5, + 29.2, + 30.1, + 26.9, + 26, + 23.7, + 17.3, + 16, + 15.1, 15.7, - 20.2, 17, - 15.5, - 16.3, - 17.6, - 14.3, - 11.7, - 13.7, - 9, - 9.8, - 11.3, - 13, - 13.3, - 11.9, - 11.4, - 10.7, - 11.2, - 12.2, - 13.9, - 15.8, 15.9, - 16.5, - 16.8, - 15.5, 15.4, - 15.2, - 12.8, - 13, - 12.7, - 11.5, - 9 + 17.9, + 22.6, + 28.3, + 29.4, + 29.3, + 27.7, + 25.3, + 24.3, + 24.6, + 24.2, + 19.7, + 18.8, + 20.7, + 22.6, + 17.5, + 14.7 ] }, { @@ -5899,10 +6233,10 @@ "mode": "lines", "name": "mean prediction", "text": [ - 15.4, - 14.02342876567345, - 11.957298947940416, - 12.116861408103025 + 24.2, + 18.520342129678873, + 17.4677660898787, + 18.38980072370943 ], "type": "scatter", "x": [ @@ -5912,10 +6246,10 @@ "2019" ], "y": [ - 15.4, - 14.02342876567345, - 11.957298947940416, - 12.116861408103025 + 24.2, + 18.520342129678873, + 17.4677660898787, + 18.38980072370943 ] }, { @@ -5937,14 +6271,14 @@ "2016" ], "y": [ - 15.4, - 14.465484102297477, - 12.349376535175548, - 12.492488781565942, - 11.757838022182563, - 11.601073081843463, - 13.612567619256561, - 15.4 + 24.2, + 19.45900278443401, + 18.462959722422184, + 19.864348591412533, + 17.33850235453402, + 16.659423290772093, + 17.716210592385732, + 24.2 ] } ], @@ -6818,7 +7152,7 @@ "font": { "size": 12 }, - "text": "Predicted unemployment_rate in Northwest Arctic Borough, AK
under intervention [3.0047122e+09] in year 2016
99.739% of counties received a lower intervention
observed intervention: 0.0" + "text": "Predicted unemployment_rate in Imperial, CA
under intervention [3.0047122e+09] in year 2016
99.739% of counties received a lower intervention
observed intervention: 0.0" }, "xaxis": { "title": { @@ -6827,8 +7161,8 @@ }, "yaxis": { "range": [ - 7.2, - 26.26 + 11.76, + 40.17 ], "title": { "text": "Value" @@ -6851,7 +7185,7 @@ "percent_calc = ci.slider_values_to_interventions(intervened_percent=45, year=2016)\n", "ci.get_tau_samples()\n", "\n", - "fips = 2188\n", + "fips = 6025 # 2188\n", "ci.get_fips_predictions(\n", " intervened_value=percent_calc[\"intervened_transformed\"], fips=fips, year=2016\n", ")\n", @@ -6868,7 +7202,7 @@ "Recall now our original question inspired by the initial and misleading data visualisation. Recall that our question was, *which is it, should you expect a drop of \n", ".6% if you get around $3B funding, or should you expect to be protected from the extreme outcomes and hope for an outcome closer to 6%?*\n", "\n", - "The more causally aware our models offer is that neither answer is correct. On one hand, there are some confunding factors that lead to self-selection of funded counties, so the latter belief would be overly optimistic. On the other hand, you should also expect a slightly higher difference, that of .9% rather than .6%." + "The more causally aware our models offer is that neither answer is correct. On one hand, there are some confunding factors that lead to self-selection of funded counties, so the latter belief would be overly optimistic. On the other hand, you should also expect a slightly higher difference, that of 1.2% rather than .6%." ] } ], diff --git a/docs/experimental_notebooks/causal_insights_demo.ipynb b/docs/testing_notebooks/causal_insights_demo.ipynb similarity index 98% rename from docs/experimental_notebooks/causal_insights_demo.ipynb rename to docs/testing_notebooks/causal_insights_demo.ipynb index 7746cbea..61c1d424 100644 --- a/docs/experimental_notebooks/causal_insights_demo.ipynb +++ b/docs/testing_notebooks/causal_insights_demo.ipynb @@ -4,20 +4,7 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'pyro'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mrandom\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mqueries\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcausal_insight\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m CausalInsight\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata_grabber\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (DataGrabber, list_interventions,\n\u001b[1;32m 6\u001b[0m list_outcomes)\n\u001b[1;32m 8\u001b[0m smoke_test \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCI\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m os\u001b[38;5;241m.\u001b[39menviron\n", - "File \u001b[0;32m~/s78projects/cities/cities/queries/causal_insight.py:8\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgraph_objects\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgo\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpyro\u001b[39;00m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msklearn\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpreprocessing\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m StandardScaler\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pyro'" - ] - } - ], + "outputs": [], "source": [ "import os\n", "import random\n", diff --git a/docs/experimental_notebooks/slider.ipynb b/docs/testing_notebooks/slider.ipynb similarity index 100% rename from docs/experimental_notebooks/slider.ipynb rename to docs/testing_notebooks/slider.ipynb diff --git a/docs/experimental_notebooks/slimming/slim_insight.ipynb b/docs/testing_notebooks/slim_insight.ipynb similarity index 100% rename from docs/experimental_notebooks/slimming/slim_insight.ipynb rename to docs/testing_notebooks/slim_insight.ipynb diff --git a/tests/test_inference.py b/tests/test_inference.py index 05914e93..b9e474e0 100644 --- a/tests/test_inference.py +++ b/tests/test_inference.py @@ -20,8 +20,6 @@ intervened_value = 0.9 -# TODO run full tests before you smile - # running for all is too inefficient # let's just run for random on a regular basis # comment out for a full battery of tests diff --git a/tests/test_slim.py b/tests/test_slim.py index 10fe8378..f305f762 100644 --- a/tests/test_slim.py +++ b/tests/test_slim.py @@ -34,6 +34,7 @@ # assert ci.predictions is not None +# @pytest.mark.skip(reason="adding variables for now, training later") def test_slim_full(): for intervention in interventions: for outcome in outcomes: