{"id":16556289,"url":"https://github.com/mshawon/numerical-method","last_synced_at":"2025-03-04T22:19:32.836Z","repository":{"id":112036677,"uuid":"264056675","full_name":"MShawon/Numerical-Method","owner":"MShawon","description":"Several numerical methods are provided here written in Python.","archived":false,"fork":false,"pushed_at":"2021-01-16T16:34:10.000Z","size":256,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-15T07:27:53.284Z","etag":null,"topics":["curve","data-fitting","exponential-fitting","fitting-curve","least-sqaure-method","least-square-regression","numerical-methods","python","straight-line-fitting"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MShawon.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-05-15T00:28:30.000Z","updated_at":"2024-01-05T07:13:26.000Z","dependencies_parsed_at":"2023-06-29T15:18:28.034Z","dependency_job_id":null,"html_url":"https://github.com/MShawon/Numerical-Method","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MShawon%2FNumerical-Method","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MShawon%2FNumerical-Method/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MShawon%2FNumerical-Method/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MShawon%2FNumerical-Method/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MShawon","download_url":"https://codeload.github.com/MShawon/Numerical-Method/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241928955,"owners_count":20043908,"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":["curve","data-fitting","exponential-fitting","fitting-curve","least-sqaure-method","least-square-regression","numerical-methods","python","straight-line-fitting"],"created_at":"2024-10-11T20:04:05.295Z","updated_at":"2025-03-04T22:19:32.807Z","avatar_url":"https://github.com/MShawon.png","language":"Python","readme":"\n# Numerical-Method\n\n**Numerical-Method:** Numerical methods, is approximation fast solution for mathematical problems. Such problems can be in any field in engineering. So any result you get from it is approximated not exact, it give you the solution faster than normal ones, also it’s easy to be programmed.\n\n**Least-Squares-Method:** The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems by minimizing the sum of the squares of the residuals made in the results of every single equation. The most important application is in data fitting.\n\nFollowing curve is used for data fitting:\n1. Straight Line (y=mx+c)\n2. Second Degree Parabola (y=ax\u003csup\u003e2\u003c/sup\u003e+bx+c or y=a+bx+cx\u003csup\u003e2\u003c/sup\u003e)\n3. Exponential Equation (y=ae\u003csup\u003ebx\u003c/sup\u003e)\n4. Curve y=ab\u003csup\u003ex\u003c/sup\u003e and\n5. Another curve y=ax\u003csup\u003eb\u003c/sup\u003e\n\n# Installation\n * Python 3.x\n \n \n Open command prompt and type\n ```bash\n git clone https://github.com/MShawon/Numerical-Method.git\n\n cd Numerical-Method\n\n pip install -r requirements.txt\n ```\n \n# Usage\n Open command prompt in Numerical-Method folder and type\n ```\n python leastSquareMethod.py\n ```\n \n![alt text](https://github.com/MShawon/Numerical-Method/blob/master/Demo/welcome.png \"Welcome screen\")\n\n![alt text](https://github.com/MShawon/Numerical-Method/blob/master/Demo/input.png \"Input\")\n\n![alt text](https://github.com/MShawon/Numerical-Method/blob/master/Demo/output.png \"Result\")\n\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmshawon%2Fnumerical-method","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmshawon%2Fnumerical-method","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmshawon%2Fnumerical-method/lists"}