{"id":17968520,"url":"https://github.com/inducer/modepy","last_synced_at":"2025-03-25T10:32:16.782Z","repository":{"id":8302698,"uuid":"9846038","full_name":"inducer/modepy","owner":"inducer","description":"Modes and nodes for high-order discretizations","archived":false,"fork":false,"pushed_at":"2025-03-14T19:27:46.000Z","size":1473,"stargazers_count":17,"open_issues_count":5,"forks_count":7,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-03-20T01:02:26.833Z","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":"akirk/url_cleanser","license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/inducer.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2013-05-03T22:38:03.000Z","updated_at":"2025-03-14T19:27:51.000Z","dependencies_parsed_at":"2023-10-16T13:43:34.771Z","dependency_job_id":"0fcda16a-2ad2-4e8e-9b61-560901d1c280","html_url":"https://github.com/inducer/modepy","commit_stats":{"total_commits":375,"total_committers":8,"mean_commits":46.875,"dds":0.36,"last_synced_commit":"9f5eb94b7723d9b1e1066e0f661739f7a5b99d26"},"previous_names":[],"tags_count":8,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inducer%2Fmodepy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inducer%2Fmodepy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inducer%2Fmodepy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/inducer%2Fmodepy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/inducer","download_url":"https://codeload.github.com/inducer/modepy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245444236,"owners_count":20616345,"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":"2024-10-29T14:40:34.621Z","updated_at":"2025-03-25T10:32:16.770Z","avatar_url":"https://github.com/inducer.png","language":"Python","readme":"modepy: Basis Functions, Node Sets, Quadratures\n===============================================\n\n.. image:: https://gitlab.tiker.net/inducer/modepy/badges/main/pipeline.svg\n    :alt: Gitlab Build Status\n    :target: https://gitlab.tiker.net/inducer/modepy/commits/main\n.. image:: https://github.com/inducer/modepy/actions/workflows/ci.yml/badge.svg\n    :alt: Github Build Status\n    :target: https://github.com/inducer/modepy/actions/workflows/ci.yml\n.. image:: https://badge.fury.io/py/modepy.png\n    :alt: Python Package Index Release Page\n    :target: https://pypi.org/project/modepy/\n.. image:: https://zenodo.org/badge/9846038.svg\n    :alt: Zenodo DOI for latest release\n    :target: https://zenodo.org/doi/10.5281/zenodo.11105051\n\n``modepy`` helps you create well-behaved high-order discretizations on\nsimplices (i.e. segments, triangles and tetrahedra) and tensor products of\nsimplices (i.e. squares, cubes, prisms, etc.). These are a key building block\nfor high-order unstructured discretizations, as often used in a finite\nelement context. Features include:\n\n- Support for simplex and tensor product elements in any dimension.\n- Orthogonal bases:\n    - Jacobi polynomials with derivatives\n    - Orthogonal polynomials for simplices up to 3D and tensor product elements\n      and their derivatives.\n    - All bases permit symbolic evaluation, for code generation.\n- Access to numerous quadrature rules:\n    - Jacobi-Gauss, Jacobi-Gauss-Lobatto in 1D\n      (includes Legendre, Chebyshev, ultraspherical, Gegenbauer)\n    - Clenshaw-Curtis and Fejér in 1D\n    - Grundmann-Möller on the simplex\n    - Xiao-Gimbutas on the simplex\n    - Vioreanu-Rokhlin on the simplex\n    - Jaśkowiec-Sukumar on the tetrahedron\n    - Witherden-Vincent on the hypercube\n    - Generic tensor products built on the above, e.g. for prisms and hypercubes\n- Tools to construct new quadrature rules:\n    - A basic iterative Gauss-Newton process to optimize/tighten rules\n    - Vioreanu-Rokhlin node initial generation based on multiplication operators\n- Matrices for FEM, usable across all element types:\n    - generalized Vandermonde,\n    - mass matrices (including lumped diagonal),\n    - face mass matrices,\n    - differentiation matrices, and\n    - resampling matrices.\n- Objects to represent 'element shape' and 'function space',\n  generic node/mode/quadrature retrieval based on them.\n\nIts roots closely followed the approach taken in the book\n\n  Hesthaven, Jan S., and Tim Warburton. \"Nodal Discontinuous Galerkin Methods:\n  Algorithms, Analysis, and Applications\". 1st ed. Springer, 2007.\n  `Book web page \u003chttp://nudg.org\u003e`_\n\nbut much has been added beyond that basic functionality.\n\nResources:\n\n* `documentation \u003chttp://documen.tician.de/modepy\u003e`_\n* `wiki home page \u003chttp://wiki.tiker.net/ModePy\u003e`_\n* `source code via git \u003chttp://github.com/inducer/modepy\u003e`_\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finducer%2Fmodepy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finducer%2Fmodepy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finducer%2Fmodepy/lists"}