SPECTROview
A free, open-source software designed for advanced spectroscopic data analysis.
It supports discrete spectra and hyperspectral datasets such as 2D maps and wafer maps,
with integrated visualization tools that streamline your analytical workflow.
✨ Key Features
| Feature | Description |
|---|---|
| 🤖 AI Chat Agent | Talk to SPECTROview in plain language to filter data, run analyses, and create or customize multiple plots — powered by your own local (Ollama) or cloud LLM |
| 🔌 Local MCP Server | Opt-in localhost access to the running datasets, spectra, maps, fits, and graphs for external MCP clients |
| ⚡ Vectorized Batch Fit Engine | Ultra-fast fitting via batched matrix operations — simultaneously fit multiple spectra or large 2D maps |
| 🧩 Custom Fit Models | Build and reuse custom fit models tailored to your specific spectroscopic profiles |
| 📊 Versatile Data Processing | Seamlessly handle both 1D spectral data and 2D hyperspectral data |
| 📋 Unified Results | Collect and compile all best-fit results with a single click |
| 🎨 Advanced Visualization | Dedicated workspace for fast, publication-ready visualizations |
| 🖥️ Optimized UI | Designed for quick inspection, filtering, and comparison of large spectral datasets |
🎬 Demonstrations
📁 Dedicated workspaces for discrete spectra, hyperspectral data, and visualization
📐 Design custom fit models and simultaneously process multiple spectra
📈 Rapidly generate publication-ready data visualizations
🚀 Quick Start
SPECTROview requires Python 3.8 – 3.12.
Install from PyPI:
pip install spectroview
Or install the latest development version from GitHub:
pip install git+https://github.com/CEA-MetroCarac/SPECTROview.git
Launch:
spectroview
📚 Documentation
Full documentation is available at CEA-MetroCarac.github.io/SPECTROview:
| Resource | Link |
|---|---|
| 📖 User Manual | Online manual (also accessible within the app) |
| 🛠️ Developer Guide | Developer docs |
| 📝 Changelog | Release notes |
| 📂 Examples | /examples — sample datasets and supported formats |
🙏 Acknowledgements
This work was carried out at the CEA — Platform for Nanocharacterisation (PFNC) and supported by the "Recherche Technologique de Base" program of the French National Research Agency (ANR).
📄 Citation
If you use SPECTROview in your work, please cite:
Le, Van Hoan. "SPECTROview: An Open-Source Application for Interactive Spectroscopic Data Processing, Fitting, and Visualization." SoftwareX 35 (September 2026): 102862. https://doi.org/10.1016/j.softx.2026.102862.
BibTeX
@article{le2026spectroview,
title = {SPECTROview: An Open-Source Application for Interactive
Spectroscopic Data Processing, Fitting, and Visualization},
author = {Le, Van Hoan},
journal = {SoftwareX},
volume = {35},
pages = {102862},
year = {2026},
month = sep,
publisher = {Elsevier},
doi = {10.1016/j.softx.2026.102862}
}
1 maintainer
Metadata
1 maintainer
Release files for spectroview 26.37.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| spectroview-26.37.3.tar.gz | 43.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| spectroview-26.37.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 87.5 MB
Release files / spectroview-26.37.3.tar.gz
| Download URL | spectroview-26.37.3.tar.gz |
|---|---|
| Size | 43.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
9437c4402590032e5b51000d29d0a66a9c7583af995247ed049e8b372e3944e0
|
|
BLAKE2b-256 checksum How to use checksums |
2812196df9ae80b71416c10b5c3e04a879af609e38dd707eda2e59e862c4a4cc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 20, 2026.
Transparency logRelease files / spectroview-26.37.3-py3-none-any.whl
| Download URL | spectroview-26.37.3-py3-none-any.whl |
|---|---|
| Size | 43.8 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
56a57f25487083de846cb4e3a0a67a4b86231deb3fb45c96d52bbe834a228c46
|
|
BLAKE2b-256 checksum How to use checksums |
d287b5ff48e7b8f26385d864705ab15822135f8e445a168f74f7b45858eaea0c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 20, 2026.
Transparency log
