{"id":21156336,"url":"https://github.com/vitroid/delaunayextrapolation","last_synced_at":"2025-09-18T16:45:14.180Z","repository":{"id":62567566,"uuid":"328849265","full_name":"vitroid/DelaunayExtrapolation","owner":"vitroid","description":"Linear extrapolation of scattered samples","archived":false,"fork":false,"pushed_at":"2024-08-11T16:18:21.000Z","size":343,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-01-21T08:44:56.917Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/vitroid.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":"2021-01-12T02:27:52.000Z","updated_at":"2024-08-11T16:18:24.000Z","dependencies_parsed_at":"2024-11-20T11:54:48.689Z","dependency_job_id":"0593d1c5-dfcc-4013-91ab-055b76287176","html_url":"https://github.com/vitroid/DelaunayExtrapolation","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/vitroid%2FDelaunayExtrapolation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vitroid%2FDelaunayExtrapolation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vitroid%2FDelaunayExtrapolation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vitroid%2FDelaunayExtrapolation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vitroid","download_url":"https://codeload.github.com/vitroid/DelaunayExtrapolation/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243597798,"owners_count":20316845,"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":"2024-11-20T11:42:44.532Z","updated_at":"2025-09-18T16:45:09.095Z","avatar_url":"https://github.com/vitroid.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DelaunayExtrapolation\n\n## Explanation\n\nDelaunay三角形分割を利用した内挿法です。\n\n1. 点群をまず準備します。\n2. それをDelaunay三角形分割します。\n3. 点群に含まれない任意の点が、点群の構成する三角形のどれに含まれているかを割り出します。\n4. さらに、三角形の中での相対位置(混合比)を算出します。\n\n`scipy.spatial.Delaunay`を利用すれば内挿は容易にできますが、三角形に含まれない点にまで外挿することができないので、Delaunayクラスを拡張しました。\n\n「三角形分割」と書いていますが、3次元以上でも問題なく動くはずです。\n\n## Installation\n\n```shell\n$ pip install delaunayextrapolation\n```\n\n## Example\n\n`test.py`に使用例があります。\n\n## Known Issues\n\n* 一点ずつしか内挿できません。多数の点を同時に内挿できると良いですよね。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvitroid%2Fdelaunayextrapolation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvitroid%2Fdelaunayextrapolation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvitroid%2Fdelaunayextrapolation/lists"}