{"id":17222864,"url":"https://github.com/cheind/py-dimensional-analysis","last_synced_at":"2025-07-28T13:32:56.269Z","repository":{"id":47203265,"uuid":"327272855","full_name":"cheind/py-dimensional-analysis","owner":"cheind","description":"Dimensional analysis and modeling in Python","archived":false,"fork":false,"pushed_at":"2021-09-08T16:17:39.000Z","size":1000,"stargazers_count":4,"open_issues_count":1,"forks_count":1,"subscribers_count":2,"default_branch":"develop","last_synced_at":"2024-10-16T04:06:31.030Z","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cheind.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-01-06T10:12:01.000Z","updated_at":"2024-07-29T04:49:44.000Z","dependencies_parsed_at":"2022-09-19T18:01:13.548Z","dependency_job_id":null,"html_url":"https://github.com/cheind/py-dimensional-analysis","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheind%2Fpy-dimensional-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheind%2Fpy-dimensional-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheind%2Fpy-dimensional-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheind%2Fpy-dimensional-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cheind","download_url":"https://codeload.github.com/cheind/py-dimensional-analysis/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":227915773,"owners_count":17839480,"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":[],"created_at":"2024-10-15T04:06:33.558Z","updated_at":"2024-12-03T12:22:03.983Z","avatar_url":"https://github.com/cheind.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# py-dimensional-analysis\n\nThis Python package addresses physical dimensional analysis. In\nparticular, `py-dimensional-analysis` calculates from a given system of\n(dimensional) variables those products that yield a desired target\ndimension.\n\nThe following example illustrates how the variables mass, force, time\nand pressure must relate to each other in order to produce the dimension\nlength\\*time.\n\n``` python\nimport danalysis as da\n\nsi = da.standard_systems.SI         # predefined standard units\ns = da.Solver(\n    {\n        'a' : si.M,                 # [a] is mass\n        'b' : si.L*si.M*si.T**-2,   # [b] is force (alt. si.F)\n        'c' : si.T,                 # [c] is time\n        'd' : si.Pressure           # [d] is pressure\n    },\n    si.L*si.T                       # target dimension\n)\nprint(s.solve())\n```\n\nWhich prints\n\n    Found 2 variable products of variables\n    {\n            a:Q(M),\n            b:Q(L*M*T**-2),\n            c:Q(T),\n            d:Q(L**-1*M*T**-2)\n    }, each of dimension L*T:\n            1: [a*c**-1*d**-1] = L*T\n            2: [b**0.5*c*d**-0.5] = L*T\n\nThis library is based on (Szirtes 2007), and also incorporates ideas and\nexamples from (Santiago 2019; Sonin 2001).\n\n## Solver\nThe solver is based on the Buckingham’s *π* theorem. For more information, see (Szirtes 2007).\n\n## References\n\n\u003cdiv id=\"refs\" class=\"references csl-bib-body hanging-indent\"\u003e\n\n\u003cdiv id=\"ref-santiago2019first\" class=\"csl-entry\"\u003e\n\nSantiago, Juan G. 2019. *A First Course in Dimensional Analysis:\nSimplifying Complex Phenomena Using Physical Insight*. MIT Press.\n\n\u003c/div\u003e\n\n\u003cdiv id=\"ref-sonin2001dimensional\" class=\"csl-entry\"\u003e\n\nSonin, Ain A. 2001. “Dimensional Analysis.” Technical report,\nMassachusetts Institute of Technology.\n\u003chttp://web.mit.edu/2.25/www/pdf/DA_unified.pdf\u003e.\n\n\u003c/div\u003e\n\n\u003cdiv id=\"ref-szirtes2007applied\" class=\"csl-entry\"\u003e\n\nSzirtes, Thomas. 2007. *Applied Dimensional Analysis and Modeling*.\nButterworth-Heinemann.\n\n\u003c/div\u003e\n\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcheind%2Fpy-dimensional-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcheind%2Fpy-dimensional-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcheind%2Fpy-dimensional-analysis/lists"}