{"id":30957156,"url":"https://github.com/cbueth/delaynet","last_synced_at":"2025-10-04T13:57:15.796Z","repository":{"id":210754362,"uuid":"727362558","full_name":"cbueth/delaynet","owner":"cbueth","description":"Analyze delay propagation in transportation networks.","archived":false,"fork":false,"pushed_at":"2025-08-14T17:59:18.000Z","size":803,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-24T08:50:29.718Z","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":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cbueth.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2023-12-04T18:01:41.000Z","updated_at":"2025-08-25T14:34:39.000Z","dependencies_parsed_at":"2025-09-09T21:34:58.595Z","dependency_job_id":"7fc6ea0a-60d3-4c28-8b27-7b88920294e5","html_url":"https://github.com/cbueth/delaynet","commit_stats":null,"previous_names":["cbueth/delaynet"],"tags_count":5,"template":false,"template_full_name":null,"purl":"pkg:github/cbueth/delaynet","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbueth%2Fdelaynet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbueth%2Fdelaynet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbueth%2Fdelaynet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbueth%2Fdelaynet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cbueth","download_url":"https://codeload.github.com/cbueth/delaynet/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbueth%2Fdelaynet/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278322146,"owners_count":25967874,"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","status":"online","status_checked_at":"2025-10-04T02:00:05.491Z","response_time":63,"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":"2025-09-11T13:16:48.647Z","updated_at":"2025-10-04T13:57:15.791Z","avatar_url":"https://github.com/cbueth.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv style=\"text-align: center; max-width: 700px; margin: 0 auto;\"\u003e\n  \u003ca href=\"https://delaynet.readthedocs.io/\"\u003e\n    \u003cpicture\u003e\n      \u003csource media=\"(prefers-color-scheme: light)\" srcset=\"https://raw.githubusercontent.com/cbueth/delaynet/refs/heads/main/docs/_static/dn_banner.png\"\u003e\n      \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://raw.githubusercontent.com/cbueth/delaynet/refs/heads/main/docs/_static/dn_banner_dark.png\"\u003e\n      \u003cimg src=\"https://raw.githubusercontent.com/cbueth/delaynet/refs/heads/main/docs/_static/dn_banner.png\" style=\"max-width: 80%; height: auto;\" alt=\"delaynet logo\"\u003e\n    \u003c/picture\u003e\n  \u003c/a\u003e\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca href=\"\"\u003e[![Documentation](https://readthedocs.org/projects/delaynet/badge/)](https://delaynet.readthedocs.io/)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![PyPI Version](https://badge.fury.io/py/delaynet.svg)](https://pypi.org/project/delaynet/)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![Python Version](https://img.shields.io/pypi/pyversions/delaynet)](https://pypi.org/project/delaynet/)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![Anaconda Version](https://anaconda.org/conda-forge/delaynet/badges/version.svg)](https://anaconda.org/conda-forge/delaynet)\u003c/a\u003e\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca href=\"\"\u003e[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.16875272.svg)](https://doi.org/10.5281/zenodo.16875272)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-1.2-4baaaa.svg)](CODE_OF_CONDUCT.md)\u003c/a\u003e\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca href=\"\"\u003e[![pipeline status](https://gitlab.ifisc.uib-csic.es/carlson/delaynet/badges/main/pipeline.svg)](https://gitlab.ifisc.uib-csic.es/carlson/delaynet/-/commits/main)\u003c/a\u003e\n\u003ca href=\"\"\u003e[![coverage report](https://gitlab.ifisc.uib-csic.es/carlson/delaynet/badges/main/coverage.svg)](https://gitlab.ifisc.uib-csic.es/carlson/delaynet/-/jobs)\u003c/a\u003e\n\n\u003c/div\u003e\n\nPython package to reconstruct and analyse delay functional networks from time series.\nIt provides tools for data preparation and detrending, multiple connectivity measures\n(e.g. Granger causality, transfer entropy, correlations), optimal-lag network\nreconstruction, and network analysis.\n\n### Features\n\n- Connectivity measures with hypothesis testing and optimal-lag reconstruction\n- Network analysis: betweenness, eigenvector centrality, link density, transitivity,\n  reciprocity, isolated nodes, global efficiency\n- Null-model normalisation for metrics: report z-scores vs directed G(n,m) random\n  graphs (igraph-based; binary-only; on-the-fly generation)\n- Comprehensive documentation and examples\n- Tested across multiple Python versions with high coverage\n\n---\n\nFor details on how to use this package, see the\n[Guide](https://delaynet.readthedocs.io/en/latest/guide/) or\nthe [Documentation](https://delaynet.readthedocs.io/en/latest/).\n\n## Setup\n\nThis package can be installed from PyPI using pip:\n\n```bash\npip install delaynet  # when public on PyPI\n```\n\nThis will automatically install all the necessary dependencies as specified in the\n`pyproject.toml` file. It is recommended to use a virtual environment, e.g., using\n`conda`, `mamba` or `micromamba` (they can be used interchangeably).\n\n```bash\nmicromamba create -n delay_net -c conda-forge python\nmicromamba activate delay_net\npip install delaynet  # or `micromamba install delaynet` when on conda-forge\n```\n\n### Quickstart\n\n```python\nimport numpy as np\nimport delaynet as dn\n\n# Generate toy data: 5 nodes, 300 time points\nrng = np.random.default_rng(1520)\ndata = rng.standard_normal((300, 5))\n\n# Compute a connectivity p-value and lag for one pair\npval, lag = dn.connectivity(data[:, 0], data[:, 1], metric=\"gc\", lag_steps=10)\nprint(f\"GC p-value={pval:.3g}, best lag={lag}\")\n\n# Reconstruct a delay network (p-value matrix and lag matrix)\nweights, lags = dn.reconstruct_network(data, connectivity_measure=\"gc\", lag_steps=5)\nprint(weights.shape, lags.shape)\n```\n\n## Development Setup\n\nFor development, we recommend using [`uv`](https://docs.astral.sh/uv/)  or `micromamba`\nto create a virtual environment.\nAfter cloning the repository, navigate to the root folder and\ncreate the environment.\nWhen using `uv`, the environment can be created with the following command:\n\n```bash\nuv sync\n```\n\nOr, if you prefer to use `micromamba`,\nwith the desired Python version and the dependencies.\n\n```bash\nmicromamba create -n delay_net -c conda-forge -f requirements.txt\nmicromamba activate delay_net\n```\n\nEither way, using `pip` to install the package in editable mode will also install the\ndevelopment dependencies.\n\n```bash\npip install -e \".[all]\"\n```\n\nOr, to let `micromamba` handle the dependencies, use the `requirements.txt` file\n\n```bash\nmicromamba install --file requirements.txt\npip install --no-build-isolation --no-deps -e .\n```\n\nNow, the package can be imported and used in the python environment, from anywhere on\nthe system if the environment is activated.\n\n## Set up Jupyter kernel\n\nIf you want to use `delaynet` with its environment `delay_net` in Jupyter, run:\n\n```bash\npip install --user ipykernel\npython -m ipykernel install --user --name=delay_net\n```\n\nThis allows you to run Jupyter with the kernel `delay_net` (Kernel \u003e Change Kernel \u003e\nim_env)\n\n## Acknowledgments\n\nThis project has received funding from the European Research Council (ERC) under the\nEuropean Union's Horizon 2020 research and innovation programme (grant agreement No\n851255).\nThis work was partially supported by the María de Maeztu project CEX2021-001164-M funded\nby the MICIU/AEI/10.13039/501100011033 and FEDER, EU.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbueth%2Fdelaynet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcbueth%2Fdelaynet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbueth%2Fdelaynet/lists"}