SPECK: Spectrometric Toolkit

SPECK is an open‑source collection of utilities and datasets for the visualisation and analysis of optical spectra. It targets educational settings where simple yet powerful tools are needed to handle Horiba .LAB files or standard CSV data.

The repository contains both Python applications and a JavaScript web viewer. Example spectra from discharge lamps, lasers and fluorescence samples are included.

Repository Layout

labparser.py # CLI converter: .lab → CSV (+ PDF preview) spectra_lab_viewer.py # PyQt5 GUI to inspect and fit spectra index.html # Browser‑based viewer powered by Chart.js compare.html # Web tool for multi‑spectrum comparison gallery.html # HTML gallery of CCD screenshots about.html # Project information and credits csv_out/ # Sample spectra in CSV format with a PDF summary speckdata/ # Original .lab files images/ # Logos and UI graphics

Python tools

• spectralabviewer.py – A full desktop application (PyQt5 + Matplotlib) to load one or multiple spectra, overlay them, adjust axes scales (linear, log, √) and fit peaks within a selected ROI. Spectra can be exported as plots or simulated CCD images.
• labparser.py – Batch converter for Horiba .LAB files. It generates CSV files and collects all spectra in a single PDF document. Titles are read from list.json if present next to the input files.

Both scripts only depend on widely available packages (PyQt5, matplotlib, numpy, scipy, pillow). They can be compiled with Python ≥ 3.9.

Web interface

index.html and compare.html implement a lightweight viewer entirely in JavaScript. They read the CSV files under csv_out/ (or directly .lab files via a built‑in parser) and render interactive plots using Chart.js. A simulated CCD bar displays the colour distribution along the wavelength axis. The web tools run fully offline and are suitable for classroom use on any modern browser.

The about.html page summarises the project goals and lists third‑party dependencies—all released under the MIT licence. Logos and screenshots are located in images/.

Data

Example spectra reside in speckdata/ as original .lab files accompanied by list.json containing human‑readable titles. The csv_out/ directory holds the converted CSV tables and a precompiled PDF (spettri.pdf). The accompanying titoli.json maps file names to titles and is used by the HTML viewer.

Installation

Install the required Python packages with:

bash pip install pyqt5 matplotlib numpy scipy pillow

No additional setup is required for the web viewer—simply open index.html in a browser.

Usage

Run the desktop GUI:

bash python spectra_lab_viewer.py

Convert .lab files to CSV and PDF:

bash python labparser.py /path/to/lab_folder -o csv_out

License

All original code in this repository is released under the MIT License. See about.html for credits of the JavaScript libraries used in the web interface.