{"id":19855808,"url":"https://github.com/ray-chew/pycsam","last_synced_at":"2025-02-28T21:41:32.013Z","repository":{"id":228362521,"uuid":"773769451","full_name":"ray-chew/pyCSAM","owner":"ray-chew","description":"pyCSAM is a robust approach for approximating geodesic subgrid-scale orographic spectra with applications to weather forecasting and broader data analysis","archived":false,"fork":false,"pushed_at":"2024-05-14T20:48:22.000Z","size":72171,"stargazers_count":0,"open_issues_count":4,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-05-15T17:07:12.832Z","etag":null,"topics":["data-analysis","gmted","icon-model","merit-dem","orographic","spectral-analysis","topography","weather-forecast"],"latest_commit_sha":null,"homepage":"https://ray-chew.github.io/pyCSAM/","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/ray-chew.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.rst","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":"2024-03-18T11:16:39.000Z","updated_at":"2024-05-20T15:06:00.817Z","dependencies_parsed_at":"2024-03-26T12:42:06.241Z","dependency_job_id":"1bf5739d-3c85-4376-b065-47c8b78a120e","html_url":"https://github.com/ray-chew/pyCSAM","commit_stats":null,"previous_names":["ray-chew/spec_appx","ray-chew/pycsam"],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2FpyCSAM","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2FpyCSAM/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2FpyCSAM/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2FpyCSAM/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ray-chew","download_url":"https://codeload.github.com/ray-chew/pyCSAM/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241245642,"owners_count":19933296,"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":["data-analysis","gmted","icon-model","merit-dem","orographic","spectral-analysis","topography","weather-forecast"],"created_at":"2024-11-12T14:13:45.735Z","updated_at":"2025-02-28T21:41:31.983Z","avatar_url":"https://github.com/ray-chew.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://ray-chew.github.io/pyCSAM/index.html\"\u003e\n  \u003cimg alt=\"CSAM Logo\" src=\"https://ray-chew.github.io/pyCSAM/_static/logo.png\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003ch2 align=\"center\"\u003eConstrained Spectral Approximation Method\u003c/h2\u003e\n\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://github.com/ray-chew/pyCSAM/actions/workflows/documentation.yml\"\u003e\n\u003cimg alt=\"GitHub Actions: docs\" src=https://img.shields.io/github/actions/workflow/status/ray-chew/pyCSAM/documentation.yml?logo=github\u0026label=docs\u003e\n\u003c/a\u003e\n\u003ca href=\"https://www.gnu.org/licenses/gpl-3.0\"\u003e\n\u003cimg alt=\"License: GPL v3\" src=https://img.shields.io/badge/License-GPLv3-blue.svg\u003e\n\u003c/a\u003e\n\u003ca href=\"https://github.com/psf/black\"\u003e\n\u003cimg alt=\"Code style: black\" src=https://img.shields.io/badge/code%20style-black-000000.svg\u003e\n\u003c/a\u003e\n\u003c/p\u003e\n\n\nThe Constrained Spectral Approximation Method (CSAM) is a physically sound and robust method for approximating the spectrum of subgrid-scale orography. It operates under the following constraints:\n\n* Utilises a limited number of spectral modes (no more than 100)\n* Significantly reduces the complexity of physical terrain by over 500 times\n* Maintains the integrity of physical information to a large extent\n* Compatible with unstructured geodesic grids\n* Inherently scale-aware\n\nThis method is primarily used to represent terrain for weather forecasting purposes, but it also shows promise for broader data analysis applications.\n\n---\n\n**[Read the documentation here](https://ray-chew.github.io/pyCSAM/index.html)**\n\n---\n\n## Requirements\n\nSee [`requirements.txt`](https://github.com/ray-chew/pyCSAM/blob/main/requirements.txt)\n\n\u003e **NOTE:**  The Sphinx dependencies can be found in [`docs/conf.py`](https://github.com/ray-chew/pyCSAM/blob/main/docs/source/conf.py).\n\n\n## Usage\n\n### Installation\n\nFork this repository and clone your remote fork.\n\n### Configuration\n\nThe user-defined input parameters are in the [`inputs`](https://github.com/ray-chew/pyCSAM/tree/main/inputs) subpackage. These parameters are imported into the run scripts in [`runs`](https://github.com/ray-chew/pyCSAM/tree/main/runs). \n\n### Execution\n\nA simple setup can be found in [`runs.idealised_isosceles`](https://github.com/ray-chew/pyCSAM/blob/main/runs/idealised_isosceles.py). To execute this run script:\n\n```console\npython3 ./runs/idealised_isosceles.py\n```\n\nHowever, the codebase is structured such that the user can easily assemble a run script to define their own experiments. Refer to the documentation for the [available APIs](https://ray-chew.github.io/pyCSAM/api.html).\n\n## License\n\nGNU GPL v3 (tentative)\n\n## Contributions\n\nRefer to the open issues that require attention.\n\nAny changes, improvements, or bug fixes can be submitted to upstream via a pull request.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Fpycsam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fray-chew%2Fpycsam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Fpycsam/lists"}