{"id":19835194,"url":"https://github.com/equinor/dass","last_synced_at":"2025-10-13T03:52:19.386Z","repository":{"id":39708131,"uuid":"492727406","full_name":"equinor/dass","owner":"equinor","description":"Data Assimilation in Python for teaching purposes","archived":false,"fork":false,"pushed_at":"2024-08-07T07:50:36.000Z","size":13822,"stargazers_count":10,"open_issues_count":4,"forks_count":11,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-08-07T11:28:15.832Z","etag":null,"topics":["data-assimilation","history-matching"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/equinor.png","metadata":{"files":{"readme":"README.md","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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-05-16T07:28:03.000Z","updated_at":"2024-08-07T07:50:40.000Z","dependencies_parsed_at":"2024-01-15T15:09:31.342Z","dependency_job_id":"3d15c8c5-7a76-4e0f-8d45-ecb0a3cdc5c7","html_url":"https://github.com/equinor/dass","commit_stats":{"total_commits":43,"total_committers":3,"mean_commits":"14.333333333333334","dds":"0.046511627906976716","last_synced_commit":"22ee8ccb0f6d41f131495b3c69cd9b7e8a84d07e"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/equinor%2Fdass","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/equinor%2Fdass/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/equinor%2Fdass/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/equinor%2Fdass/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/equinor","download_url":"https://codeload.github.com/equinor/dass/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224270276,"owners_count":17283649,"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":["data-assimilation","history-matching"],"created_at":"2024-11-12T12:07:01.072Z","updated_at":"2025-10-13T03:52:14.356Z","avatar_url":"https://github.com/equinor.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Assimilation\n\n`dass` is tool for learning about data assimilation / history matching created by the developers of [ERT](https://github.com/equinor/ert).\nIt is inspired by [DAPPER](https://github.com/nansencenter/DAPPER) and [HistoryMatching](https://github.com/patnr/HistoryMatching).\n\nIt includes implementations of Ensemble Smoother (ES) as given in [1], see [dass/analysis.py](dass/analysis.py).\nThe implementation of ES can easily be extended to the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) as described in [2].\n\nFor notebooks with examples and tutorials see the `notebooks/` folder.\n\n**NB!** notice that there are no `.ipynb` files in the `notebooks/` folder.\nThis is because we use [Jupytext](https://github.com/mwouts/jupytext) to sync `.py` and `.ipynb` files,\nwhich means that we only need to keep the `.py` files in source control.\n\n## Installation\n\n```bash\ngit clone https://github.com/equinor/dass.git\ncd dass\n# dass supports Python 3.8 and above.\npython3.9 -m venv .venvdass\nsource .venvdass/bin/activate\n# Add -e if you want to make changes.\npip install -e .\n# Install additional requirements for developers.\npip install -r dev-requirements.txt\n# Start jupyter notebook\njupyter notebook\n# To make sure everything works, run on the of the notebooks in the notebooks/ folder.\n```\n\n## References\n\n[1] - [Data Assimilation\nThe Ensemble Kalman Filter](https://link.springer.com/book/10.1007/978-3-642-03711-5)\n\n[2] - [Ensemble smoother with multiple data assimilation](https://www.sciencedirect.com/science/article/pii/S0098300412000994)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fequinor%2Fdass","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fequinor%2Fdass","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fequinor%2Fdass/lists"}