# Common.smk ##########################################################################################################

def infer_participant_platform(participant_file):
    with open(participant_file, encoding="ISO-8859-1") as external_file:
        external_file_content = external_file.readlines()
    platforms = external_file_content[1].strip().split(",")
    if platforms[0] == "multiple" or (len(platforms) > 1 and "android" in platforms and "ios" in platforms):
        platform = "android"
    else:
        platform = platforms[0]

    if platform not in ["android", "ios"]:
        raise ValueError("Platform (line 2) in a participant file should be 'android', 'ios', or 'multiple'. You typed '" + platforms + "'")

    return platform

# Features.smk #########################################################################################################
def find_features_files(wildcards):
    feature_files = []
    for provider_key, provider in config[(wildcards.sensor_key).upper()]["PROVIDERS"].items():
        if provider["COMPUTE"]:
            feature_files.extend(expand("data/interim/{{pid}}/{sensor_key}_features/{sensor_key}_{language}_{provider_key}.csv", sensor_key=wildcards.sensor_key.lower(), language=provider["SRC_LANGUAGE"].lower(), provider_key=provider_key.lower()))
    return(feature_files)

def optional_steps_sleep_input(wildcards):
    if config["STEP"]["EXCLUDE_SLEEP"]["EXCLUDE"] == True and config["STEP"]["EXCLUDE_SLEEP"]["TYPE"] == "FITBIT_BASED":
        return  "data/raw/{pid}/fitbit_sleep_summary_with_datetime.csv"
    else:
        return []

# Models.smk ###########################################################################################################

def input_merge_features_of_single_participant(wildcards):
    if wildcards.source == "phone_fitbit_features":
        return expand("data/processed/{pid}/{features}_{day_segment}.csv", pid=wildcards.pid, features=config["PARAMS_FOR_ANALYSIS"]["PHONE_FEATURES"] + config["PARAMS_FOR_ANALYSIS"]["FITBIT_FEATURES"], day_segment=wildcards.day_segment)
    else:
        return expand("data/processed/{pid}/{features}_{day_segment}.csv", pid=wildcards.pid, features=config["PARAMS_FOR_ANALYSIS"][wildcards.source.upper()], day_segment=wildcards.day_segment)

def optional_input_days_to_include(wildcards):
    if config["PARAMS_FOR_ANALYSIS"]["DAYS_TO_ANALYSE"]["ENABLED"]:
        # This input automatically trigers the rule days_to_analyse in mystudy.snakefile
        return ["data/interim/{pid}/days_to_analyse" + \
                    "_" + str(config["PARAMS_FOR_ANALYSIS"]["DAYS_TO_ANALYSE"]["DAYS_BEFORE_SURGERY"]) + \
                    "_" + str(config["PARAMS_FOR_ANALYSIS"]["DAYS_TO_ANALYSE"]["DAYS_IN_HOSPITAL"]) + \
                    "_" + str(config["PARAMS_FOR_ANALYSIS"]["DAYS_TO_ANALYSE"]["DAYS_AFTER_DISCHARGE"]) + ".csv"]
    else:
        return []

def optional_input_valid_sensed_days(wildcards):
    if config["PARAMS_FOR_ANALYSIS"]["DROP_VALID_SENSED_DAYS"]["ENABLED"]:
        # This input automatically trigers the rule phone_valid_sensed_days in preprocessing.snakefile
        return ["data/interim/{pid}/phone_valid_sensed_days_{min_valid_hours_per_day}hours_{min_valid_bins_per_hour}bins.csv"]
    else:
        return []

# Reports.smk ###########################################################################################################

def optional_heatmap_days_by_sensors_input(wildcards):
    platform = infer_participant_platform("data/external/"+wildcards.pid)
    
    if platform == "android":
        tables_platform = [table for table in config["HEATMAP_DAYS_BY_SENSORS"]["DB_TABLES"] if table not in [config["CONVERSATION"]["DB_TABLE"]["IOS"], config["ACTIVITY_RECOGNITION"]["DB_TABLE"]["IOS"]]] # for android, discard any ios tables that may exist
    elif platform == "ios":
        tables_platform = [table for table in config["HEATMAP_DAYS_BY_SENSORS"]["DB_TABLES"] if table not in [config["CONVERSATION"]["DB_TABLE"]["ANDROID"], config["ACTIVITY_RECOGNITION"]["DB_TABLE"]["ANDROID"]]] # for ios, discard any android tables that may exist

    return expand("data/raw/{{pid}}/{table}_with_datetime.csv", table = tables_platform)