molass 0.7.2

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 Photon Factory and SPring-8, Japan.

Tested Platforms

• 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

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

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