{"id":29190882,"url":"https://github.com/yelyzavetav/trispectral","last_synced_at":"2025-07-02T00:12:13.667Z","repository":{"id":251622704,"uuid":"822748500","full_name":"YelyzavetaV/trispectral","owner":"YelyzavetaV","description":"NumPy-based Python package for numerical differentiation using spectral methods","archived":false,"fork":false,"pushed_at":"2025-02-24T21:01:48.000Z","size":1866,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-24T22:19:57.733Z","etag":null,"topics":["numerical-differentiation","numerical-integration","spectral-methods"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/YelyzavetaV.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","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":"2024-07-01T18:34:05.000Z","updated_at":"2025-02-24T21:01:51.000Z","dependencies_parsed_at":"2024-08-29T16:07:52.619Z","dependency_job_id":null,"html_url":"https://github.com/YelyzavetaV/trispectral","commit_stats":null,"previous_names":["yelyzavetav/pytrispectral"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/YelyzavetaV/trispectral","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YelyzavetaV%2Ftrispectral","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YelyzavetaV%2Ftrispectral/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YelyzavetaV%2Ftrispectral/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YelyzavetaV%2Ftrispectral/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/YelyzavetaV","download_url":"https://codeload.github.com/YelyzavetaV/trispectral/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YelyzavetaV%2Ftrispectral/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263052434,"owners_count":23406106,"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":["numerical-differentiation","numerical-integration","spectral-methods"],"created_at":"2025-07-02T00:12:12.762Z","updated_at":"2025-07-02T00:12:13.627Z","avatar_url":"https://github.com/YelyzavetaV.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003e\n    \u003cspan style=\"color:blue\"\u003eTris\u003c/span\u003e\u003cspan style=\"color:green\"\u003e\u003c/span\u003e\u003cspan style=\"color:E0E31D\"\u003epectral\u003c/span\u003e\n\u003c/h1\u003e\n\n[![tests](https://github.com/YelyzavetaV/trispectral/actions/workflows/tests.yml/badge.svg)](https://github.com/YelyzavetaV/trispectral/actions/workflows/tests.yml)\n[![coverage](https://codecov.io/github/YelyzavetaV/trispectral/graph/badge.svg?token=gFMctOGnuv)](https://codecov.io/github/YelyzavetaV/trispectral)\n\nTrispectral is a NumPy-based Python package for numerical differentiation using spectral collocation methods.\n\nThe user interface of Trispectral is compact and intuitive. For example, consider the function $f(x,y) = xe^{-(x^2 + y^2)}$ for $-1 \\le x, y \\le 1$. Using Trispectral we can compute the gradient of $f$ as follows:\n```python\ngrid = Grid.from_bounds(\n    [-1., 1., 41], [-1., 1., 41], discs=[\"chebyshev\"] * 2\n)\nx, y = grid\n\nf = x * numpy.exp(-x**2 - y**2)\ngrad = gradient_operator(grid) @ f\n```\nHere, the object `grid` represents a $41\\times 41$ Chebyshev-Chebyshev grid.\n\nCombined with SciPy, Trispectral also provides tools for solving linear boundary-value problems and linear eigenvalue problems (including the problems of hydrodynamic linear stability). See the [Trispectral tutorials](https://github.com/YelyzavetaV/trispectral/tree/main/tutorials) for more information.\n\nTrispectral currently supports\n\n- 1D, 2D and 3D Cartesian geometries\n- Polar geometry","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyelyzavetav%2Ftrispectral","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyelyzavetav%2Ftrispectral","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyelyzavetav%2Ftrispectral/lists"}