A modern, user-friendly graphical interface for Detector Calibration, Resolution calculations and plotting with an auto peak detection feature and functional user override to assign ADC and Energy values.

Energy calibration tool for multi-channel detector systems.
Built with Python · PyROOT · PyQt5 · Matplotlib · SciPy

Author: Siddharth Parashari

• Dual ROOT backend: PyROOT (native) or uproot (pure Python) — detected automatically.
• Flexible data loading: TTree filter mode, array-branch mode, custom Draw() expressions, or pre-filled TH1 histograms.
• Three peak detection algorithms: ROOT TSpectrum (standard and HighRes), Sliding Window, and SciPy fallback — all with optional Gaussian confirmation
• Gaussian peak confirmation: Each detected candidate is verified by a Gaussian fit. Accepted peaks are centroid-refined; rejected peaks are shown as red × markers.
• Peak propagation: Detect peaks on one reference channel and automatically search all other channels within a configurable ADC window.
• Three calibration models: Linear, nonlinear scintillator, 3-point nonlinear variant, plus user-defined custom expressions.
• Detect + Fit All: One-click workflow — detect, propagate, and fit all channels simultaneously in a background thread.
• Calibrated spectrum viewer: Full-range energy spectra using session or file-loaded coefficients.
• Energy resolution analysis: Interactive Gaussian fitting with multiple background models, FWHM extraction, and per-channel trend plots.
• Rich output: Human-readable calibration log, compact coefficients table, and resolution results file.

• Python 3.8+
• ROOT (with PyROOT) — must be sourced before running
• Python packages: see requirements.txt

pip install PyQt5 matplotlib numpy scipy

# Source ROOT first
source /opt/root/bin/thisroot.sh

# Run the application
python main.py

1. Open ROOT File — choose TTree branches or TH1 histograms

• Select Branch, ChanelID, and custom user function to populate histograms
• Select channelID range and number of entries

2. ROOT TSpectrum Peak Search / SciPy / Sliding Window

• Select TSpectrum search parameters suitable for your spectrum
• Background threshold
• Sigma (bins)
• Number of peaks to be detected

3. Add global peaks — click on the spectrum to assign energies using CLICK, or use Auto-detect

4. Optionally override peaks for specific channels

5. Choose calibration model (e.g. Linear or User defined)

6. Click Fit All Channels — progress bar tracks the batch

7. Review results in Overview Grid (green = OK, red = bad)

8. Inspect individual channels + residuals in Single Channel tab

9. Check parameter stability in Coefficient Trends tab

10. Export Results — selects output directory, writes both output files

11. Calibrated Spectrum — Use calibration parameters from memory (session memory) or load calibration file to see calibrated spectrum.

12. Per Channel Resolution — Use the built-in peak selector (drag on the spectrum) to select the fit area to calculate the resolution (% or keV)

    • Export Fitted spectrum and/or the resolution results in output files.

Full human-readable report — parameters, uncertainties, χ²/NDF, calibration points and residuals per channel. Bad channels flagged with reason.

Compact analysis-ready table:

# Channel   p0              p1              Chi2/NDF  Status
       0    1.234000e-01    5.678000e+00    1.2300    OK
       1    1.198000e-01    5.701000e+00    0.9800    OK
     512    nan             nan             nan       BAD: No calibration peaks

In the model selector, choose custom and enter an expression using single-letter parameter names (not x):

a*x**2 + b*x + c
a * np.exp(b * x) + c
a*x + b

x is the ADC channel value. np (NumPy) is available in expressions.

DetectorCalibGUI/
├── main.py                  # Entry point
├── requirements.txt
├── README.md
├── generate_test_data.C    # to generate a test data file (.ROOT)
└── src/
    ├── __init__.py
    ├── root_loader.py         # PyROOT file loading (TTree + TH1)
    ├── peak_manager.py        # Peak storage, auto-detection
    ├── calib_fitter.py        # SciPy fitting, bad channel detection
    ├── output_writer.py       # Export: log + coefficients files
    ├── calib_spectrum.py      # Calibrate histograms
    ├── resolution.py          # Calculate Resolution + Export
    ├── calib_spectrum_tab.py  # Calculation tab GUI
    ├── resolution_tab.py      # Resolution tab GUI
    └── main_window.py         # Full PyQt5 GUI

Last Updated: February 21, 2026
Version: 1.0
Maintained by: Siddharth Parashari

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes with clear commit messages
4. Test thoroughly with sample data
5. Document new features in README
6. Submit a pull request

• Issues: Open an issue on GitHub
• Email: [email protected]