Matrix Optimization with Low-rank factorization for Automated analysis of SEC-SAXS
Project description
Molass Library is a rewrite of MOLASS, a tool for the analysis of SEC-SAXS experiment data currently hosted at Photon Factory and SPring-8, Japan.
Tested Platforms
- Python 3.13 on Windows 11
- Python 3.12 on Windows 11
- Python 3.12 on Ubuntu 22.04.4 LTS (WSL2)
Installation
To install this package, use pip as follows:
pip install -U molass
Documentation
- Tutorial: https://biosaxs-dev.github.io/molass-tutorial — practical usage, for beginners
- Essence: https://biosaxs-dev.github.io/molass-essence — theory, for researchers
- Technical Report: https://biosaxs-dev.github.io/molass-technical — technical details, for advanced users
- Reference: https://biosaxs-dev.github.io/molass-library — function reference, for coding
- Legacy Repository: https://github.com/biosaxs-dev/molass-legacy — legacy code
Community
To join the community, see:
- Handbook: https://biosaxs-dev.github.io/molass-develop — maintenance, for developers
Especially for testing, see the first two sections in
Copilot Usage
Before starting a Copilot chat session with this repository, please use the following magic phrase to ensure Copilot follows project rules:
For details on Copilot rules and usage, see Copilot/copilot-guidelines.md.
“Please follow the Copilot guidelines in this project for all advice and responses.”
Optional Features
Excel reporting (Windows only):
If you want to use Excel reporting features (Windows only) for backward compatibility, install with the excel extra:
pip install -U molass[excel]
Note: The
excelextra installspywin32, which is required for Excel reporting and only works on Windows.
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