{"id":13426079,"url":"https://github.com/uhlerlab/causaldag","last_synced_at":"2025-03-15T20:32:00.868Z","repository":{"id":40141184,"uuid":"142711225","full_name":"uhlerlab/causaldag","owner":"uhlerlab","description":"Python package for the creation, manipulation, and learning of Causal DAGs","archived":false,"fork":false,"pushed_at":"2023-04-12T05:29:30.000Z","size":9201,"stargazers_count":147,"open_issues_count":13,"forks_count":19,"subscribers_count":8,"default_branch":"master","last_synced_at":"2024-10-28T04:25:18.594Z","etag":null,"topics":["causal-dags","causal-inference","causal-models","causality","inference"],"latest_commit_sha":null,"homepage":null,"language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/uhlerlab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-07-28T21:27:11.000Z","updated_at":"2024-10-23T14:19:01.000Z","dependencies_parsed_at":"2024-01-12T17:34:32.669Z","dependency_job_id":"b51cfdc5-b8dc-4d32-add4-48d78ebccd9d","html_url":"https://github.com/uhlerlab/causaldag","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uhlerlab%2Fcausaldag","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uhlerlab%2Fcausaldag/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uhlerlab%2Fcausaldag/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uhlerlab%2Fcausaldag/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/uhlerlab","download_url":"https://codeload.github.com/uhlerlab/causaldag/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243790939,"owners_count":20348378,"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":["causal-dags","causal-inference","causal-models","causality","inference"],"created_at":"2024-07-31T00:01:25.867Z","updated_at":"2025-03-15T20:31:55.849Z","avatar_url":"https://github.com/uhlerlab.png","language":"JavaScript","funding_links":[],"categories":["JavaScript","Toolboxes"],"sub_categories":["Causal Discovery"],"readme":"[![PyPI version](https://badge.fury.io/py/causaldag.svg)](https://badge.fury.io/py/causaldag)\n\n**This package is nearing a V1 release, with potential (minor) breaking changes. After the release, future breaking changes will occur less frequently and with more notice. Please raise issues as needed.**\n\n`causaldag` is common wrapper for the following packages:\n* https://github.com/uhlerlab/graphical_models\n* https://github.com/uhlerlab/conditional_independence\n* https://github.com/uhlerlab/graphical_model_learning\n\nInstalling and importing `causaldag` should be sufficient for most use cases.\n\nCausalDAG is a Python package for the creation, manipulation, and learning\nof Causal DAGs. CausalDAG requires Python 3.5+\n\n### Install\nInstall the latest version of CausalDAG:\n```\n$ pip3 install causaldag\n```\n\n### Cite\nYou may use the following bibtex for citing `causaldag`:\n```\n@manual{squires2018causaldag,\n  title={{\\texttt{causaldag}: creation, manipulation, and learning of causal models}},\n  author={{Chandler Squires}},\n  year={2018},\n  url={https://github.com/uhlerlab/causaldag},\n}\n```\n\nOr the following text:\n\n\u003e Chandler Squires. _causaldag: creation, manipulation, and learning of causal models_, 2018. URL https://github.com/uhlerlab/causaldag\n\n### Documentation\nDocumentation for each subpackage is available at:\n* graphical_models: https://graphical-models.readthedocs.io/en/latest/\n* graphical_model_learning: https://graphical-model-learning.readthedocs.io/en/latest/\n* conditional_independence: https://conditional-independence.readthedocs.io/en/latest/\n\nExamples for specific algorithms can be found at https://uhlerlab.github.io/causaldag/\n\n### Simple Example\nFind the CPDAG (complete partially directed acyclic graph,\nAKA the *essential graph*) corresponding to a DAG:\n```\n\u003e\u003e\u003e from causaldag import rand, partial_correlation_suffstat, partial_correlation_test, MemoizedCI_Tester, gsp\n\u003e\u003e\u003e import numpy as np\n\u003e\u003e\u003e np.random.seed(12312)\n\u003e\u003e\u003e nnodes = 5\n\u003e\u003e\u003e nodes = set(range(nnodes))\n\u003e\u003e\u003e dag = rand.directed_erdos(nnodes, .5)\n\u003e\u003e\u003e gdag = rand.rand_weights(dag)\n\u003e\u003e\u003e samples = gdag.sample(100)\n\u003e\u003e\u003e suffstat = partial_correlation_suffstat(samples)\n\u003e\u003e\u003e ci_tester = MemoizedCI_Tester(partial_correlation_test, suffstat, alpha=1e-3)\n\u003e\u003e\u003e est_dag = gsp(nodes, ci_tester)\n\u003e\u003e\u003e dag.shd_skeleton(est_dag)\n```\n\n### License\n\nReleased under the 3-Clause BSD license (see LICENSE.txt):\n```\nCopyright (C) 2018\nChandler Squires \u003ccsquires@mit.edu\u003e\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuhlerlab%2Fcausaldag","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuhlerlab%2Fcausaldag","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuhlerlab%2Fcausaldag/lists"}