{"id":22620453,"url":"https://github.com/sebsikora/curve_fitting","last_synced_at":"2026-04-13T03:34:50.573Z","repository":{"id":201446294,"uuid":"57203692","full_name":"sebsikora/curve_fitting","owner":"sebsikora","description":"A short guide to using Python tools to perform arbitrary curve-fitting of research data via constrained minimisation.","archived":false,"fork":false,"pushed_at":"2021-09-30T16:02:04.000Z","size":354,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-29T02:13:18.199Z","etag":null,"topics":["curve-fitting","minimisation","numpy","optimisation","python","scipy"],"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/sebsikora.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}},"created_at":"2016-04-27T10:04:59.000Z","updated_at":"2021-10-04T09:12:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"a867d440-3523-4fa4-aeb4-6cf1531129ff","html_url":"https://github.com/sebsikora/curve_fitting","commit_stats":null,"previous_names":["sebsikora/curve_fitting"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sebsikora/curve_fitting","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sebsikora%2Fcurve_fitting","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sebsikora%2Fcurve_fitting/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sebsikora%2Fcurve_fitting/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sebsikora%2Fcurve_fitting/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sebsikora","download_url":"https://codeload.github.com/sebsikora/curve_fitting/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sebsikora%2Fcurve_fitting/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279018221,"owners_count":26086307,"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":"2025-10-14T02:00:06.444Z","response_time":60,"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":["curve-fitting","minimisation","numpy","optimisation","python","scipy"],"created_at":"2024-12-08T22:13:49.931Z","updated_at":"2025-10-14T07:37:26.630Z","avatar_url":"https://github.com/sebsikora.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Piece-wise curve-fitting with Python tools - A tutorial\n\n© 2021 Dr Sebastien Sikora.\n\n[seb.nf.sikora@protonmail.com](mailto:seb.nf.sikora@protonmail.com)\n\nUpdated 29/09/2021.\n\nWhat is it?\n-------------------------\n\nThis IPython notebook forms a tutorial that I wrote some years ago while working as a research fellow in the Department of Mechanical Engineering at Leeds University.\n\nIt is a guide to using Python tools including numpy and scipy to work with research data, in this case to perform arbitrary curve-fitting, for the benefit of scientist colleagues comfortable with the algebra but uncomfortable moving beyond Microsoft Excel or the odd bit of Matlab to perform their analyses.\n\nMore broadly, the same approach can be used to solve for unknowns in any multivariate scalar function, via constrained minimisation.\n\n[The tutorial](tutorial_ipython_notebook.ipynb)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsebsikora%2Fcurve_fitting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsebsikora%2Fcurve_fitting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsebsikora%2Fcurve_fitting/lists"}