{"id":20956433,"url":"https://github.com/bluebrain/dmt","last_synced_at":"2026-04-27T06:32:01.380Z","repository":{"id":44499407,"uuid":"248259984","full_name":"BlueBrain/DMT","owner":"BlueBrain","description":null,"archived":false,"fork":false,"pushed_at":"2022-02-10T10:32:49.000Z","size":49422,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-12-30T13:15:00.870Z","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":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BlueBrain.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-03-18T14:50:45.000Z","updated_at":"2022-02-10T10:32:54.000Z","dependencies_parsed_at":"2022-09-01T16:22:31.977Z","dependency_job_id":null,"html_url":"https://github.com/BlueBrain/DMT","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BlueBrain/DMT","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BlueBrain%2FDMT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BlueBrain%2FDMT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BlueBrain%2FDMT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BlueBrain%2FDMT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BlueBrain","download_url":"https://codeload.github.com/BlueBrain/DMT/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BlueBrain%2FDMT/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32325840,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-26T23:26:28.701Z","status":"online","status_checked_at":"2026-04-27T02:00:06.769Z","response_time":128,"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":"2024-11-19T01:25:57.068Z","updated_at":"2026-04-27T06:32:01.351Z","avatar_url":"https://github.com/BlueBrain.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"We present a framework and library to help with analyzing models and\nvalidating them against empirical data.\n\n# Philosophy\n\nDMT decouples scientific computer models from *in-silico* analyses, such\nthat any analysis can be run on any model to which it is applicable, and\nany model can be analyzed by all applicable analyses.\n\n# Usage\n\n``` python\nfrom dmt import AdapterInterface \n\nclass SomeValueAnalysisInterface(AdapterInterface):\n    \"\"\"\n    Methods documented in this class must be provided\n    by an adapter.\n    \"\"\"\n    def get_somevalue(self, model):\n      \"\"\"\n      Get some value for a model.\n      \"\"\"\n      raise NotImplementedError\n\ndef some_value_analysis(model, adapter, threshold=123456):\n  \"\"\"\n  Analysis for a model using a given adapter.\n  An analysis may be a simple function.\n  \"\"\"\n    model_prediction = adapter.get_somevalue(model)\n    report = dict(\n        measurement=model_prediction,\n        verdict=model_prediction \u003e threshold)\n    return report\n```\n\nthen\n\n``` python\nfrom models import MyModel, TheirModel\nfrom analyses import SomeValueAnalysis\n\nmy_model = MyModel()\ntheir_model = TheirModel()\n\nclass InvalidAdapter():\n   pass\n\nclass MyModelAdapter():\n\n   def get_somevalue(self, model):\n       return model.something / model.someotherthing\n\nclass TheirModelAdapter():\n\n   def get_somevalue(self, model):\n       return model.get_somevalue('someparameter')\n\n# produces a report\nreport_mine = some_value_analysis(my_model, MyModelAdapter())\n# produces a report\nreport_theirs = some_value_analysis(their_model, TheirModelAdapter())\n# raises an informative error\nsome_value_analysis(InvalidAdapter())\n```\n\n# Installation\n\nDownload the repository, `cd` to it's directory, and\n\n    pip install  .\n    \n# Funding \u0026 Acknowledgment\n \nThe development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government's ETH Board of the Swiss Federal Institutes of Technology.\n \nCopyright © 2020-2022 Blue Brain Project/EPFL\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbluebrain%2Fdmt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbluebrain%2Fdmt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbluebrain%2Fdmt/lists"}