def load_time_series()

in prediction_postprocessing_scripts/dynamic_time_warping_analysis.py [0:0]

• 13 lines of code
• 11 McCabe index (conditional complexity)

def load_time_series(input_folder, signature_ids_to_consider=None):
    """Recursively loads all available time series from the input folder and subfolders, filtering by provided signature IDs."""
    time_series_dict = {}
    for root, _, files in os.walk(input_folder):
        for filename in files:
            if filename.endswith("_timeseries_data.csv"):
                sig_id = int(filename.split("_")[0])
                # Only load the file if its signature ID is in the provided list, or if no filter is applied
                if signature_ids_to_consider is not None and sig_id not in signature_ids_to_consider:
                    continue
                df = pd.read_csv(os.path.join(root, filename))
                if "push_timestamp" in df.columns and "value" in df.columns:
                    df = df.sort_values(by="push_timestamp")
                    time_series_dict[sig_id] = df["value"].dropna().values
    return time_series_dict