TRaP: An open-source, reproducible framework for Raman spectral processing across heterogeneous systems

Developed at Vanderbilt University.

Features

• 5-step wizard workflow guiding users through the complete processing pipeline
• X-axis calibration using Neon-Argon and Acetaminophen reference spectra
• Spectral response correction via White-Light, NIST SRM, or pre-computed factors
• Full preprocessing pipeline: baseline subtraction, SRC, truncation, binning, noise smoothing (SG / MA / Median), fluorescence background subtraction, and normalization
• Configurable pipeline parameters: truncation range, bin width, FBS polynomial order and max iterations, normalization method (Mean / Max / Area), and smoothing settings
• Detector auto-fill: selecting a detector model pre-fills CCD spectral and spatial pixel dimensions
• Spectrum Batch Processing for multiple spectrum files with shared configuration
• Configuration persistence: save/load JSON config files with field validation
• Interactive cursor on processing plots: snaps to nearest data point and displays wavenumber and intensity
• Real-time visualization with before/after dual-panel comparison
• Modern dark-themed UI with smooth animations

Quick Start

Requirements

• Python 3.8+

Install & Run

pip install PyQt5 numpy pandas scipy matplotlib openpyxl
python TRaP_GUI.py

Workflow

Step 0: Configuration Manager
       Configure instrument & system parameters
                    |
Step 1: X-Axis Calibration
       Neon-Argon + known/unknown laser wavelength  -->  calibration.mat
                    |
Step 2: Spectral Response Correction
       White-Light / NIST SRM / existing factor  -->  correction factor
                    |
Step 3: Spectrum Processing           \
       or                              }--> processed spectra (.txt)
Step 4: Spectrum Batch Processing     /

Processing Pipeline (Steps 3 & 4)

Order	Operation	Description
1	Baseline Subtraction	Remove minimum intensity offset
2	Spectral Response Correction	Apply correction factor from Step 2
3	Cosmic Ray Removal	Reserved placeholder for future integration
4	Truncation	Extract wavenumber range of interest
5	Binning	Rebin to uniform wavenumber spacing
6	Noise Smoothing	Savitzky-Golay / Moving Average / Median filter
7	Fluorescence Background	Iterative polynomial baseline subtraction
8	Normalization	Scale spectrum by mean / max / area

Supported File Formats

Extension	Notes
.txt	Auto-detect delimiter (tab, space, comma)
.csv	Standard CSV
.xlsx / .xls	Excel (first sheet)
.mat	MATLAB binary (calibration files)

Configuration

System parameters are stored as JSON:

{
    "Name": "MyExperiment",
    "System": "Cart",
    "Exc Wavelength": "785",
    "Detector": "256br",
    "Probe": "Microscope",
    "Raman Shift Range": "Fingerprint"
}

Parameter	Options
System	Cart, Renishaw, Portable, MANTIS
Exc Wavelength	785, 680, 830, 730 (nm)
Detector	256br, 400br, Blaze, Kaiser
Probe	Microscope, Handheld, Lensed, SORS, Classic
Raman Shift Range	Fingerprint, High WVN, Full Range, Custom

Project Structure

TRaP_App/
|-- TRaP_GUI.py                       # Main entry point
|-- build_exe.py                      # Build automation (PyInstaller / Nuitka)
|
|-- UI_utils/                         # GUI modules
|   |-- UI_wizard_v2.py              # Wizard orchestrator with navigation shell
|   |-- UI_Config_Manager.py         # Configuration management
|   |-- UI_Calibration_v2.py         # X-axis calibration UI
|   |-- UI_SRCF.py                   # Spectral response correction UI
|   |-- UI_P_Mean_Process.py         # Single spectrum processing UI
|   |-- UI_P_Mean_Batch_Process.py   # Batch processing UI
|   |-- UI_theme.py                  # Dark theme styling
|
|-- utils/                            # Processing & algorithm modules
|   |-- Calibration_v2.py            # Calibration algorithms
|   |-- SpectralPreprocess.py        # Processing pipeline
|   |-- WLCorrection.py              # White-Light / NIST correction
|   |-- io/rdata.py, wdata.py        # File I/O with format auto-detection
|   |-- accuratePeak.py              # Peak detection
|   |-- savgol.py                    # Savitzky-Golay filter
|   |-- spectralBin.py              # Spectral binning
|   |-- lsqpolyfit.py / lsqpolyval.py  # Polynomial fitting

Build Standalone Executable

pip install pyinstaller
python build_exe.py              # PyInstaller (default)
python build_exe.py nuitka       # Nuitka (alternative)

Output: dist/TRaP/TRaP.exe

Contact

• Email: yanfan.zhu@vanderbilt.edu
• GitHub: ZhaishenGForSaken