OPUS Visualizator

A tool for visualizing and analyzing OPUS spectral data with temperature correlation and peak analysis.

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📦 Installation (End-User)

The easiest way to install is by using the prebuilt Windows installer.

1. Download the Installer

1. Go to the Releases page on GitHub.
2. Download the file named similar to: OpusSpectrumVisualizatorInstaller.exe

2. Install

1. Double-click the downloaded .exe file.
2. Follow the installation prompts.

3. Launch

Start the program from the Desktop Icon, Start Menu or search for Opus Spectrum Visualizator.

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📚 Usage Guide

1. Select the folder containing OPUS files.

2. Select one input file (.txt/.csv) for axis data:

   • Temperature file (legacy format), or
   • Custom variable file.

   Custom variable file options:

   • Filename matching (recommended): one numeric value column + one filename column
     (example row: 1.330E+12, 20260205.3) separators can be comma, tab, or semicolon. both plain numbers and scientific notation are accepted. The app uses only the selected input file.
   • Timestamp matching: one timestamp column + one numeric value column
   • Sequence fallback: one numeric value column with exactly one row per spectrum (acquisition order)

   Small examples:

   filename match (2 columns): fluence,filename 0.000E+0,20260205.1 1.330E+12,20260205.3 3.906E+12,20260205.5

   timestamp match: timestamp;temperature 1738660001;298.15 1738660031;298.50 1738660061;300.40

   sequence fallback (value only): laser_power 0.50 0.75 1.00

3. Start the processing.

4. (Optional) Set absorbance range filter to filter out extremes or undesired intervals.

5. Inspect or export processed spectra.

6. For 3D visualization: set desired options, then click Plot 3D.

7. For peak analysis: adjust parameters, then either

   • click Export as CSV to save results, or
   • click Peak Analysis to visualize directly.

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🖼 Screenshots

Main Interface

Spectral Data Visualization

3D Visualization

Peak Analysis

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⚙️ Installation (Developer / Source Build)

If you want to run or modify the program from source, follow these steps:

1. Requirements

• Python 3.10+

2. Clone or Download the Repository

Either clone using Git:

git clone https://github.com/vadondaniel/opus-spectrum-visualizator.git
cd opus-spectrum-visualizator

Or download the repository or a release as a ZIP from GitHub and extract it.

3. Run the Application

Launch with Python:

python main.pyw

(or just open the main.pyw file)

The program will automatically install missing dependencies on first run.

4. Build an Executable

(Optional) Create a standalone .exe using PyInstaller:

pyinstaller --onefile main.spec

The executable will appear in the /dist/ folder as main.exe

5. Build an Installer

(Optional) Using Inno Setup:

If you build with PyInstaller, install pytz first:

python -m pip install pytz

1. Run pyinstaller main.spec.
2. Open installer.iss in Inno Setup.
3. Compile (Ctrl+F9).

The installer will appear in the /Output/ folder as OpusSpectrumVisualizatorInstaller.exe

Using a version installed with the installer starts considerably faster than a standalone executable file from step 4 above.

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🛠 Libraries Used

• PyQt6 – graphical interface
• matplotlib – 2D & 3D plotting
• pandas & numpy – data parsing and correlation
• SpectroChemPy – OPUS file processing

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📄 License & Attribution

This project uses read_opus.py by LCS – Laboratoire Catalyse et Spectrochimie, Caen, France, licensed under CeCILL-B.

• You may use, modify, and distribute this software.
• Attribution must be retained.
• Provided "as-is" without warranty.

Original source: SpectroChemPy GitHub