rapids/example_profile/Snakefile

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")

# Visualization for Data Exploration
if config["HISTOGRAM_PHONE_DATA_YIELD"]["PLOT"]:
    files_to_compute.append("reports/data_exploration/histogram_phone_data_yield.html")

# 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/*"