{"id":20287544,"url":"https://github.com/steviecurran/prediction-plot","last_synced_at":"2025-08-08T17:06:36.738Z","repository":{"id":146278156,"uuid":"618149682","full_name":"steviecurran/prediction-plot","owner":"steviecurran","description":"Code to performs machine learning (k-nearest neighbours regression) and plot the predicted versus measured values","archived":false,"fork":false,"pushed_at":"2025-02-18T21:41:44.000Z","size":250,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-04T04:15:23.296Z","etag":null,"topics":["astrophysics","c","data-analysis","high-redshift","machine-learning","pgplot","python","statistics","tensorflow","visualization"],"latest_commit_sha":null,"homepage":"https://ui.adsabs.harvard.edu/abs/2022MNRAS.514....1C/abstract","language":"C","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/steviecurran.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":"2023-03-23T21:19:10.000Z","updated_at":"2025-02-18T21:41:47.000Z","dependencies_parsed_at":null,"dependency_job_id":"aab440fd-0540-4547-9772-b2b7314a3965","html_url":"https://github.com/steviecurran/prediction-plot","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/steviecurran/prediction-plot","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/steviecurran%2Fprediction-plot","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/steviecurran%2Fprediction-plot/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/steviecurran%2Fprediction-plot/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/steviecurran%2Fprediction-plot/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/steviecurran","download_url":"https://codeload.github.com/steviecurran/prediction-plot/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/steviecurran%2Fprediction-plot/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269457772,"owners_count":24420289,"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":"2025-08-08T02:00:09.200Z","response_time":72,"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":["astrophysics","c","data-analysis","high-redshift","machine-learning","pgplot","python","statistics","tensorflow","visualization"],"created_at":"2024-11-14T14:40:26.947Z","updated_at":"2025-08-08T17:06:36.691Z","avatar_url":"https://github.com/steviecurran.png","language":"C","readme":"# prediction-plot\n\nCode to perform machine learning (k-nearest neighbours regression) and plot the predicted versus measured values. This is all contained within kNN.py and supersedes the all of the C code above (thus not requiring me to write my own grey-scale function, etc.).\n\n![](https://raw.githubusercontent.com/steviecurran/prediction-plot/refs/heads/main/DESI_trun.csv_df_GRZW1W2_kNN.png)\n\n## Previous C version\n\nUseful for large datasets, as produces a grey scale and error bars of equally binned data instead of individal points. \n\nAlso returns a sub-plot showing the distribution of the difference in the predicted and measured values and gives the mean difference, the standard deviation and outlier fraction.\n\n![](https://raw.githubusercontent.com/steviecurran/prediction-plot/refs/heads/main/cmp22-Fig9.png)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsteviecurran%2Fprediction-plot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsteviecurran%2Fprediction-plot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsteviecurran%2Fprediction-plot/lists"}