{"id":20841044,"url":"https://github.com/benchopt/benchmark_linear_ica","last_synced_at":"2026-03-10T04:02:56.762Z","repository":{"id":45648005,"uuid":"372237677","full_name":"benchopt/benchmark_linear_ica","owner":"benchopt","description":"Benchopt benchmark for linear ICA","archived":false,"fork":false,"pushed_at":"2025-11-28T12:22:05.000Z","size":17,"stargazers_count":0,"open_issues_count":1,"forks_count":5,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-11-30T19:27:55.945Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/benchopt.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-05-30T14:35:37.000Z","updated_at":"2025-11-28T12:22:10.000Z","dependencies_parsed_at":"2023-01-21T19:29:55.184Z","dependency_job_id":null,"html_url":"https://github.com/benchopt/benchmark_linear_ica","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":"benchopt/template_benchmark","purl":"pkg:github/benchopt/benchmark_linear_ica","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_linear_ica","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_linear_ica/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_linear_ica/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_linear_ica/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benchopt","download_url":"https://codeload.github.com/benchopt/benchmark_linear_ica/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_linear_ica/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30324185,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-10T01:36:58.598Z","status":"online","status_checked_at":"2026-03-10T02:00:06.579Z","response_time":106,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2024-11-18T01:18:37.681Z","updated_at":"2026-03-10T04:02:56.713Z","avatar_url":"https://github.com/benchopt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Benchopt Benchmark for Linear ICA\n=================================\n|Build Status| |Python 3.6+|\n\nBenchopt is a package to simplify and make more transparent and\nreproducible the comparisons of optimization algorithms.\nThis benchmark is dedicated to Independent Component Analysis (ICA):\n\n$$X = A S$$\n\nwhere\n\n$$X \\\\in \\\\mathbb{R}^{p \\\\times n}, A \\\\in \\\\mathbb{R}^{p \\\\times p} \\\\text{ and } S \\\\in \\\\mathbb{R}^{p \\\\times n}$$\n\nsuch that $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features.\nThe purpose of linear ICA is to recover the mixing matrix $A$ from $X$.\n\nwhere X is n_features x n_samples, A is n_features x n_features and S\nis n_features x n_samples. The purpose of ICA is to recover the\nmixing matrix A from X.\n\nInstall\n--------\n\nThis benchmark can be run using the following commands:\n\n.. code-block::\n\n   $ pip install -U benchopt\n   $ git clone https://github.com/benchopt/benchmark_linear_ica\n   $ benchopt run benchmark_linear_ica\n\nApart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:\n\n.. code-block::\n\n\t$ benchopt run benchmark_linear_ica -s fastica -d simulated --max-runs 10 --n-repetitions 10\n\n\nUse ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.\n\n.. |Build Status| image:: https://github.com/benchopt/benchmark_linear_ica/workflows/Tests/badge.svg\n   :target: https://github.com/benchopt/benchmark_linear_ica/actions\n.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue\n   :target: https://www.python.org/downloads/release/python-360/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_linear_ica","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenchopt%2Fbenchmark_linear_ica","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_linear_ica/lists"}