QuantaTrap Python Project

This is a local Python implementation of the QuantaTrap Thermoluminescence (TL) analysis tool. It processes TL glow curves, performs Computerized Glow Curve Deconvolution (CGCD) to quantify continuous trap distributions, and generates comprehensive reports.

Project Structure

QuantaTrap_Python/
├── main.py            # 1. Main entry point: reads data, plots TL curves, generates reports
├── fitting.py         # 2. CGCD algorithm for multi-peak fitting and Trap Distribution
├── data/              # 3. Folder for input CSV/TXT files (Temperature, Intensity)
├── reports/           # 4. Folder for output reports (CSV, PDF, JSON)
└── requirements.txt   # Python dependencies

Setup Instructions

1. Ensure you have Python 3.8+ installed on your system.
2. Open a terminal or command prompt in this directory.
3. Install the required dependencies:

   pip install -r requirements.txt

How to Run

1. Place your raw TL glow curve data files (.csv or .txt) inside the data/ folder.
   • The files should contain two columns: Temperature and Intensity (separated by commas, spaces, or tabs).
   • Note: If the data/ folder is empty, the script will automatically generate a sample file (sample_glow_curve.csv) for testing.
2. Run the main script:

   python main.py

3. Check the reports/ folder for the output. For each input file, you will get:
   • [filename]_report.pdf: High-quality plots of the Glow Curve, CGCD fit, and Trap Distribution.
   • [filename]_results.csv: A table of the deconvoluted peaks (Energy, Tm, Intensity).
   • [filename]_results.json: A structured JSON file containing the peak data for programmatic use.