{"id":25612197,"url":"https://github.com/axsk/pccaplus.jl","last_synced_at":"2026-06-05T16:31:48.932Z","repository":{"id":83903549,"uuid":"424306996","full_name":"axsk/PCCAPlus.jl","owner":"axsk","description":"Julia implementation of PCCA+","archived":false,"fork":false,"pushed_at":"2025-02-15T11:18:02.000Z","size":133,"stargazers_count":0,"open_issues_count":7,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-20T21:18:09.407Z","etag":null,"topics":["julia","package","pcca","zib"],"latest_commit_sha":null,"homepage":"","language":"Julia","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/axsk.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.bib","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2021-11-03T16:47:46.000Z","updated_at":"2025-01-06T15:28:49.000Z","dependencies_parsed_at":"2023-12-12T16:48:39.154Z","dependency_job_id":null,"html_url":"https://github.com/axsk/PCCAPlus.jl","commit_stats":null,"previous_names":["axsk/pccaplus.jl"],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/axsk%2FPCCAPlus.jl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/axsk%2FPCCAPlus.jl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/axsk%2FPCCAPlus.jl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/axsk%2FPCCAPlus.jl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/axsk","download_url":"https://codeload.github.com/axsk/PCCAPlus.jl/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240105465,"owners_count":19748465,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["julia","package","pcca","zib"],"created_at":"2025-02-22T00:17:52.085Z","updated_at":"2025-11-12T16:02:52.497Z","avatar_url":"https://github.com/axsk.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# PCCAPlus\n\n[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://axsk.github.io/PCCAPlus.jl/stable)\n[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://axsk.github.io/PCCAPlus.jl/dev)\n[![Build Status](https://github.com/axsk/PCCAPlus.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/axsk/PCCAPlus.jl/actions/workflows/CI.yml?query=branch%3Amain)\n[![Coverage](https://codecov.io/gh/axsk/PCCAPlus.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/axsk/PCCAPlus.jl)\n\nA [KISS](https://en.wikipedia.org/wiki/KISS_principle) style implementation of PCCA+ (Robust Perron Cluster Analysis) [1,2] with support for non-reversible systems [3].\nFor a similar python implementation see also the [cmdtools](https://github.com/zib-cmd/cmdtools/) package.\n\n## Basic usage\n\n```julia\nusing PCCAPlus\n\nP=rand(10,10)\nP = P ./ sum(P, dims=2) # row stochastic matrix\n\n# basic PCCA+ clustering with 2 clusters (using no weighting and the ISA initial guess only)\nchi = pcca(P, 2)\n\nusing KrylovKit\nusing SparseArrays\nP = sprand(100,100, 0.1)\nP = P ./ sum(P, dims=2) # sparse row stochastic matrix\n\n# solve the PCCA+ problem weighted with the stationary density \n# and optimize for crispness, using the KrylovKit.jl eigensolver\nchi = pcca(P, 2; pi=:stationary, optimize=true, solver=KrylovSolver())\n```\n\nFor sparse matrix support, add either the `ArnoldiMethod.jl` or `KrylovKit.jl` and pass the corresponding `ArnoldiSolver()` or `KrylovSolver()` as a solver.\n\n## References\n1. [2006, M. Weber: Meshless Methods in Conformation Dynamics](https://opus4.kobv.de/opus4-zib/frontdoor/deliver/index/docId/1023/file/promotionweber.pdf)\n2. [2013, S. Röblitz, M. Weber: Fuzzy Spectral Clustering by PCCA+](https://doi.org/10.1007/s11634-013-0134-6)\n3. [2018, K. Fackeldey, A. Sikorski, M. Weber: Spectral Clustering for Non-Reversible Markov Chains](https://doi.org/10.1007/s40314-018-0697-0)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faxsk%2Fpccaplus.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faxsk%2Fpccaplus.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faxsk%2Fpccaplus.jl/lists"}