molass 0.9.1

Matrix Optimization with Low-rank factorization for Automated analysis of SEC-SAXS

Molass Library is a rewrite of MOLASS, a tool for the analysis of SEC-SAXS experiment data currently hosted at the Japanese synchrotron radiation facilities, Photon Factory and SPring-8

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

• Beginner Onboarding: https://github.com/biosaxs-dev/molass-beginner — Agent-mode first-run guide, for first-time users
• 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

• Testing: https://biosaxs-dev.github.io/molass-develop/chapters/06/testing.html

Copilot Usage

Context is auto-loaded from .github/copilot-instructions.md when using GitHub Copilot in Agent mode (AI Context Standard v0.7).

For behavioral rules and user-type guidance, see Copilot/copilot-guidelines.md.

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 excel extra installs pywin32, which is required for Excel reporting and only works on Windows.