createDifferencestest.py

import os
import pandas as pd
from glob import glob

def create_differences():
    # Get the directory where the current script is located (inside the folder just before /collected/)
    script_dir = os.path.dirname(os.path.abspath(__file__))

    # Define the relative path to trial_number.txt based on the current script directory
    trial_path = os.path.join(script_dir, 'trial_number.txt')

    # Step 1: Open the file and read the trial number, then set it as the trial variable
    with open(trial_path, 'r') as file:
        trial = int(file.read())  # Read the trial number from the file and convert it to an integer

    # Step 2: Define the path to the folder containing CSV files relative to the script location
    folder_path = os.path.join(script_dir, 'collected', str(trial))
    # List all CSV files in the folder
    csv_files = glob(os.path.join(folder_path, '*.csv'))

    # Extract unique movements and planes from the CSV filenames
    movements = set()
    planes = set()
    ids = set()

    for file in csv_files:
        parts = os.path.basename(file).split('_')  # Use os.path.basename to get the file name only
        movements.add(parts[2])
        planes.add(parts[1])
        ids.add(parts[0])

    print(f"IDs: {ids}")
    print(f"Movements: {movements}")
    print(f"Planes: {planes}")

    # Create a 'NEW' folder if it doesn't exist
    new_folder = os.path.join(folder_path, 'diffs')
    os.makedirs(new_folder, exist_ok=True)

    print(f"New folder path: {new_folder}")

    # Iterate through each movement, plane, and angle
    for movement in movements:
        for plane in planes:
            for angle_column in ['Plane of Elevation', 'Angle of Elevation', 'Rotation', 'Flexion Extension', 'Pronation Supination', 'Carrying Angle']:
                # Create an empty DataFrame to store differences for each participant
                diff_df = pd.DataFrame()

                for id in ids:
                    # Find CSV files for the specified movement, plane, and devices
                    matching_files_kinect = [file for file in csv_files if f"{id}_{plane}_{movement}_angles_kinect_processed.csv" in os.path.basename(file)]
                    matching_files_mm = [file for file in csv_files if f"{id}_{plane}_{movement}_angles_mm_processed.csv" in os.path.basename(file)]

                    # Skip if no files are found for the current combination
                    if not matching_files_kinect or not matching_files_mm:
                        print(f"No files found for id {id}, plane {plane}, movement {movement}")
                        continue

                    # Load CSV files for both devices
                    df_kinect = pd.read_csv(matching_files_kinect[0])
                    df_mm = pd.read_csv(matching_files_mm[0])

                    # Calculate the difference for the specific angle
                    diff = df_mm[angle_column] - df_kinect[angle_column]

                    # Add the difference to the DataFrame with participant column name
                    diff_df[f"Participant {id}"] = diff

                if not diff_df.empty:
                    # Save the DataFrame to a new CSV file
                    diff_filename = f"{plane}_{movement}_{angle_column.replace(' ', '_')}_diff.csv"
                    diff_filepath = os.path.join(new_folder, diff_filename)
                    diff_df.to_csv(diff_filepath, index=False)

                    print(f"Differences saved to {diff_filepath}")
                else:
                    print(f"No data to save for {plane}, {movement}, {angle_column}")

if __name__ == "__main__":
    create_differences()