Generate standardized model input files (NOTE: commented unstandardized sections!)
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@ -545,8 +545,10 @@ if config["PARAMS_FOR_ANALYSIS"]["BASELINE"]["COMPUTE"]:
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# Targets (labels)
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if config["PARAMS_FOR_ANALYSIS"]["TARGET"]["COMPUTE"]:
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files_to_compute.extend(expand("data/processed/models/individual_model/{pid}/input.csv", pid=config["PIDS"]))
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files_to_compute.extend(expand("data/processed/models/population_model/input.csv"))
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# files_to_compute.extend(expand("data/processed/models/individual_model/{pid}/input.csv", pid=config["PIDS"]))
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# files_to_compute.extend(expand("data/processed/models/population_model/input.csv"))
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files_to_compute.extend(expand("data/processed/models/individual_model/{pid}/z_input.csv", pid=config["PIDS"]))
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files_to_compute.extend(expand("data/processed/models/population_model/z_input.csv"))
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#files_to_compute.extend(expand("data/processed/models/individual_model/{pid}/output_{cv_method}/baselines.csv", pid=config["PIDS"], cv_method=config["PARAMS_FOR_ANALYSIS"]["CV_METHODS"]))
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# Put the for loop over STANDARDIZATION providers if all are COMPUTE == True
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@ -30,22 +30,43 @@ rule baseline_features:
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rule select_target:
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input:
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cleaned_sensor_features = "data/processed/features/{pid}/all_sensor_features_cleaned_rapids_R.csv"
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cleaned_sensor_features = "data/processed/features/{pid}/z_all_sensor_features_cleaned_rapids_R.csv"
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params:
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target_variable = config["PARAMS_FOR_ANALYSIS"]["TARGET"]["LABEL"]
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output:
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"data/processed/models/individual_model/{pid}/input.csv"
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"data/processed/models/individual_model/{pid}/z_input.csv"
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script:
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"../src/models/select_targets.py"
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rule merge_features_and_targets_for_population_model:
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input:
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cleaned_sensor_features = "data/processed/features/all_participants/all_sensor_features_cleaned_rapids_R.csv",
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cleaned_sensor_features = "data/processed/features/all_participants/z_all_sensor_features_cleaned_rapids_R.csv",
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demographic_features = expand("data/processed/features/{pid}/baseline_features.csv", pid=config["PIDS"]),
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params:
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target_variable=config["PARAMS_FOR_ANALYSIS"]["TARGET"]["LABEL"]
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output:
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"data/processed/models/population_model/input.csv"
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"data/processed/models/population_model/z_input.csv"
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script:
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"../src/models/merge_features_and_targets_for_population_model.py"
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# rule select_target:
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# input:
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# cleaned_sensor_features = "data/processed/features/{pid}/all_sensor_features_cleaned_rapids_R.csv"
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# params:
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# target_variable = config["PARAMS_FOR_ANALYSIS"]["TARGET"]["LABEL"]
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# output:
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# "data/processed/models/individual_model/{pid}/input.csv"
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# script:
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# "../src/models/select_targets.py"
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# rule merge_features_and_targets_for_population_model:
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# input:
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# cleaned_sensor_features = "data/processed/features/all_participants/all_sensor_features_cleaned_rapids_R.csv",
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# demographic_features = expand("data/processed/features/{pid}/baseline_features.csv", pid=config["PIDS"]),
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# params:
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# target_variable=config["PARAMS_FOR_ANALYSIS"]["TARGET"]["LABEL"]
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# output:
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# "data/processed/models/population_model/input.csv"
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# script:
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# "../src/models/merge_features_and_targets_for_population_model.py"
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