pybaseline_file

pybaseline_file is a graphical Python application for batch processing and baseline correction of SWV (Square Wave Voltammetry) data files. It provides a user-friendly interface to select input folders, configure data import options, process multiple .txt files, and export results with baseline correction and peak analysis.

Features

• Batch Processing: Analyze all .txt files in a selected folder.
• Baseline Correction: Uses asPLS (asymmetric penalized least squares) for robust baseline estimation.
• Peak Detection: Automatically finds the main peak in each signal.
• Signal Smoothing: Applies Savitzky-Golay filter for noise reduction.
• Export Options: Save cleaned data as CSV or Excel files.
• Result Summary: Generates a summary Excel file with peak voltages, currents, and calculated charges.
• Visualization: Saves annotated plots of each processed signal.
• Progress Tracking: Displays a progress bar and log during processing.
• Cross-platform: Works on Windows, macOS, and Linux.

Requirements

• Python 3.8+
• numpy
• pandas
• matplotlib
• pybaselines
• scipy
• openpyxl
• tkinter (usually included with Python)

Install dependencies with:

pip install numpy pandas matplotlib pybaselines scipy openpyxl

Usage

1. Run the Application

   python pybaseline_file.py

2. Select Input Folder

   • Click Parcourir to choose the folder containing your .txt files.

3. Configure Import Options

   • Choose the column separator (Tabulation, Virgule, Point-virgule, Espace).
   • Choose the decimal separator (Point or Virgule).
   • Select export format: no export, CSV, or Excel.

4. Start Analysis

   • Click Lancer l'analyse to process all files.
   • Progress and logs will be displayed in the interface.

5. View Results

   • Processed data and plots are saved in a new folder named <input_folder> (results) next to your input folder.
   • Click Ouvrir le dossier de résultats to open the results folder.

Input File Format

• Each .txt file should contain at least two columns: Potential and Current.
• The first row is skipped (assumed to be a header).
• The script expects the data to be in columns 0 and 1.

Output

• Plots: Annotated PNG plots for each file.
• Cleaned Data: CSV or Excel files for each input file (optional).
• Summary Excel: A summary file with peak voltages, currents, and calculated charges for each electrode.

How It Works

• Baseline Correction: Uses aspls from pybaselines.whittaker to estimate and subtract the baseline.
• Peak Detection: Finds the maximum (after smoothing) away from the edges.
• Charge Calculation: For each electrode, the charge is calculated as current divided by frequency (50 Hz by default).

Troubleshooting

• If you get errors about missing modules, ensure all dependencies are installed.
• If files are not processed, check that they match the expected format and encoding (latin1).

License

MIT License. See LICENCE for details.

Note:
This application uses the asPLS algorithm from pybaselines for baseline correction.