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

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  • License: GNU General Public License v3 (GPLv3) (GNU General Public License v3.0)
  • Author: Molass Community
  • Maintainer: Molass Community
  • Tags SEC-SAXS
  • Requires: Python <3.15, >=3.12
  • Provides-Extra: excel , testing
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Project description

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 3.14 on Windows 11
  • 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

Community

To join the community, see:

Especially for testing, see the first two sections in

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.

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for freesemt from gravatar.com freesemt Avatar for nshimizu0721 from gravatar.com nshimizu0721

Unverified details

These details have not been verified by PyPI
Meta
  • License: GNU General Public License v3 (GPLv3) (GNU General Public License v3.0)
  • Author: Molass Community
  • Maintainer: Molass Community
  • Tags SEC-SAXS
  • Requires: Python <3.15, >=3.12
  • Provides-Extra: excel , testing
Classifiers

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0.9.5

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