configfile: "config.yaml" include: "../rules/common.smk" include: "../rules/renv.smk" include: "../rules/preprocessing.smk" include: "../rules/features.smk" include: "../rules/models.smk" include: "../rules/reports.smk" import itertools files_to_compute = [] if len(config["PIDS"]) == 0: raise ValueError("Add participants IDs to PIDS in config.yaml. Remember to create their participant files in data/external") for provider in config["PHONE_DATA_YIELD"]["PROVIDERS"].keys(): if config["PHONE_DATA_YIELD"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=map(str.lower, config["PHONE_DATA_YIELD"]["SENSORS"]))) files_to_compute.extend(expand("data/interim/{pid}/phone_yielded_timestamps.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_yielded_timestamps_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_data_yield_features/phone_data_yield_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_DATA_YIELD"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_data_yield.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_MESSAGES"]["PROVIDERS"].keys(): if config["PHONE_MESSAGES"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_messages_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_messages_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_messages_features/phone_messages_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_MESSAGES"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_messages.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_CALLS"]["PROVIDERS"].keys(): if config["PHONE_CALLS"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_calls_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_calls_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_calls_with_datetime_unified.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_calls_features/phone_calls_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_CALLS"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_calls.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_BLUETOOTH"]["PROVIDERS"].keys(): if config["PHONE_BLUETOOTH"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_bluetooth_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_bluetooth_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_bluetooth_features/phone_bluetooth_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_BLUETOOTH"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_bluetooth.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_ACTIVITY_RECOGNITION"]["PROVIDERS"].keys(): if config["PHONE_ACTIVITY_RECOGNITION"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_activity_recognition_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_activity_recognition_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_activity_recognition_with_datetime_unified.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_activity_recognition_episodes.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_activity_recognition_episodes_resampled.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_activity_recognition_episodes_resampled_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_activity_recognition_features/phone_activity_recognition_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_ACTIVITY_RECOGNITION"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_activity_recognition.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_BATTERY"]["PROVIDERS"].keys(): if config["PHONE_BATTERY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_battery_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_battery_episodes.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_battery_episodes_resampled.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_battery_episodes_resampled_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_battery_features/phone_battery_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_BATTERY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_battery.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_SCREEN"]["PROVIDERS"].keys(): if config["PHONE_SCREEN"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_screen_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_screen_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_screen_with_datetime_unified.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_screen_episodes.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_screen_episodes_resampled.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_screen_episodes_resampled_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_screen_features/phone_screen_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_SCREEN"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_screen.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_LIGHT"]["PROVIDERS"].keys(): if config["PHONE_LIGHT"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_light_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_light_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_light_features/phone_light_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_LIGHT"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_light.csv", pid=config["PIDS"],)) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_ACCELEROMETER"]["PROVIDERS"].keys(): if config["PHONE_ACCELEROMETER"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_accelerometer_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_accelerometer_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_accelerometer_features/phone_accelerometer_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_ACCELEROMETER"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_accelerometer.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_APPLICATIONS_FOREGROUND"]["PROVIDERS"].keys(): if config["PHONE_APPLICATIONS_FOREGROUND"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_applications_foreground_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_applications_foreground_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_applications_foreground_with_datetime_with_categories.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_applications_foreground_features/phone_applications_foreground_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_APPLICATIONS_FOREGROUND"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_applications_foreground.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_WIFI_VISIBLE"]["PROVIDERS"].keys(): if config["PHONE_WIFI_VISIBLE"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_wifi_visible_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_wifi_visible_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_wifi_visible_features/phone_wifi_visible_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_WIFI_VISIBLE"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_wifi_visible.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_WIFI_CONNECTED"]["PROVIDERS"].keys(): if config["PHONE_WIFI_CONNECTED"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_wifi_connected_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_wifi_connected_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_wifi_connected_features/phone_wifi_connected_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_WIFI_CONNECTED"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_wifi_connected.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_CONVERSATION"]["PROVIDERS"].keys(): if config["PHONE_CONVERSATION"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/phone_conversation_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_conversation_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/phone_conversation_with_datetime_unified.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_conversation_features/phone_conversation_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_CONVERSATION"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_conversation.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["PHONE_LOCATIONS"]["PROVIDERS"].keys(): if config["PHONE_LOCATIONS"]["PROVIDERS"][provider]["COMPUTE"]: if config["PHONE_LOCATIONS"]["LOCATIONS_TO_USE"] == "FUSED_RESAMPLED": if "PHONE_LOCATIONS" in config["PHONE_DATA_YIELD"]["SENSORS"]: files_to_compute.extend(expand("data/interim/{pid}/phone_yielded_timestamps.csv", pid=config["PIDS"])) else: raise ValueError("Error: Add PHONE_LOCATIONS (and as many PHONE_SENSORS as you have) to [PHONE_DATA_YIELD][SENSORS] in config.yaml. This is necessary to compute phone_yielded_timestamps (time when the smartphone was sensing data) which is used to resample fused location data (RESAMPLED_FUSED)") files_to_compute.extend(expand("data/raw/{pid}/phone_locations_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_locations_processed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_locations_processed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/phone_locations_features/phone_locations_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["PHONE_LOCATIONS"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/phone_locations.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["FITBIT_HEARTRATE_SUMMARY"]["PROVIDERS"].keys(): if config["FITBIT_HEARTRATE_SUMMARY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_summary_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_summary_parsed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_summary_parsed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/fitbit_heartrate_summary_features/fitbit_heartrate_summary_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_HEARTRATE_SUMMARY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_heartrate_summary.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"].keys(): if config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_parsed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_parsed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/fitbit_heartrate_intraday_features/fitbit_heartrate_intraday_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_heartrate_intraday.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["FITBIT_SLEEP_SUMMARY"]["PROVIDERS"].keys(): if config["FITBIT_SLEEP_SUMMARY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/fitbit_sleep_summary_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_sleep_summary_parsed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_sleep_summary_parsed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/fitbit_sleep_summary_features/fitbit_sleep_summary_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_SLEEP_SUMMARY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_sleep_summary.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["FITBIT_STEPS_SUMMARY"]["PROVIDERS"].keys(): if config["FITBIT_STEPS_SUMMARY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_summary_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_summary_parsed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_summary_parsed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/fitbit_steps_summary_features/fitbit_steps_summary_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_STEPS_SUMMARY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_steps_summary.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") for provider in config["FITBIT_STEPS_INTRADAY"]["PROVIDERS"].keys(): if config["FITBIT_STEPS_INTRADAY"]["PROVIDERS"][provider]["COMPUTE"]: files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_intraday_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_intraday_parsed.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/fitbit_steps_intraday_parsed_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/interim/{pid}/fitbit_steps_intraday_features/fitbit_steps_intraday_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_STEPS_INTRADAY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower())) files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_steps_intraday.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") # Analysis Workflow Example models, scalers = [], [] for model_name in config["PARAMS_FOR_ANALYSIS"]["MODEL_NAMES"]: models = models + [model_name] * len(config["PARAMS_FOR_ANALYSIS"]["MODEL_SCALER"][model_name]) scalers = scalers + config["PARAMS_FOR_ANALYSIS"]["MODEL_SCALER"][model_name] results = config["PARAMS_FOR_ANALYSIS"]["RESULT_COMPONENTS"] # Demographic features files_to_compute.extend(expand("data/raw/{pid}/participant_info_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/features/{pid}/demographic_features.csv", pid=config["PIDS"])) # Targets files_to_compute.extend(expand("data/raw/{pid}/participant_target_raw.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/raw/{pid}/participant_target_with_datetime.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/targets/{pid}/parsed_targets.csv", pid=config["PIDS"])) # Individual model files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features_cleaned.csv", pid=config["PIDS"])) files_to_compute.extend(expand("data/processed/models/individual_model/{pid}/input.csv", pid=config["PIDS"])) 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"])) files_to_compute.extend(expand( expand("data/processed/models/individual_model/{pid}/output_{cv_method}/{{model}}/{{scaler}}/{result}.csv", pid=config["PIDS"], cv_method=config["PARAMS_FOR_ANALYSIS"]["CV_METHODS"], result = results), zip, model=models, scaler=scalers)) # Population model files_to_compute.append("data/processed/features/all_participants/all_sensor_features_cleaned.csv") files_to_compute.append("data/processed/models/population_model/input.csv") files_to_compute.extend(expand("data/processed/models/population_model/output_{cv_method}/baselines.csv", cv_method=config["PARAMS_FOR_ANALYSIS"]["CV_METHODS"])) files_to_compute.extend(expand( expand("data/processed/models/population_model/output_{cv_method}/{{model}}/{{scaler}}/{result}.csv", cv_method=config["PARAMS_FOR_ANALYSIS"]["CV_METHODS"], result = results), zip, model=models, scaler=scalers)) rule all: input: files_to_compute rule clean: shell: "rm -rf data/raw/* && rm -rf data/interim/* && rm -rf data/processed/* && rm -rf reports/figures/* && rm -rf reports/*.zip && rm -rf reports/compliance/*"