https://github.com/muehlefeldt/ajd.jl

Julia Package for calculating the Approximate Joint Diagonalization of matrices as part of a student project at Technische Universität Berlin
https://github.com/muehlefeldt/ajd.jl

ajd julia julia-language

Last synced: about 1 year ago
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Julia Package for calculating the Approximate Joint Diagonalization of matrices as part of a student project at Technische Universität Berlin

• Host: GitHub
• URL: https://github.com/muehlefeldt/ajd.jl
• Owner: muehlefeldt
• License: mit
• Created: 2024-11-27T14:53:43.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2025-02-20T15:10:45.000Z (over 1 year ago)
• Last Synced: 2025-03-28T23:43:56.601Z (about 1 year ago)
• Topics: ajd, julia, julia-language
• Language: Julia
• Homepage:
• Size: 3.94 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# AJD.jl :straight_ruler:

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://muehlefeldt.github.io/AJD.jl/dev/)

[![Build Status](https://github.com/gericke-n/AJD.jl/actions/workflows/CI.yml/badge.svg?branch=master)](https://github.com/gericke-n/AJD.jl/actions/workflows/CI.yml?query=branch%3Amaster)

[![Coverage](https://codecov.io/gh/muehlefeldt/AJD.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/muehlefeldt/AJD.jl)

This repository is part of a group project at Technische Universität Berlin for the course [Julia Programming for Machine Learning](https://adrianhill.de/julia-ml-course/) during the winter semester 2024 / 25.

> [!NOTE]

> This package is part of a student project at Technische Universität Berlin only and will not be actively maintained.

## Overview

A Julia package for Approximate Joint Diagonalization (AJD) of matrices is provided. The algorithms JDiag and FFDiag are implemented. Orthogonal and non-orthogonal AJD is supported. 

## Documentation

The [documentation](https://muehlefeldt.github.io/AJD.jl/dev/) includes a brief [Getting Started](https://muehlefeldt.github.io/AJD.jl/dev/getting-started/) guide and further information on the package.