{"id":16805918,"url":"https://github.com/pkgw/neurosynchro","last_synced_at":"2025-03-17T07:44:34.638Z","repository":{"id":32772502,"uuid":"142176457","full_name":"pkgw/neurosynchro","owner":"pkgw","description":"Train and use neural networks to quickly approximate polarized synchrotron radiative transfer coefficients","archived":false,"fork":false,"pushed_at":"2022-11-22T02:18:06.000Z","size":93,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-16T09:41:30.594Z","etag":null,"topics":["neural-networks","radiative-transfer","science","synchrotron-radiation"],"latest_commit_sha":null,"homepage":null,"language":"Python","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/pkgw.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-07-24T15:15:00.000Z","updated_at":"2021-11-10T20:28:28.000Z","dependencies_parsed_at":"2023-01-14T22:11:11.110Z","dependency_job_id":null,"html_url":"https://github.com/pkgw/neurosynchro","commit_stats":null,"previous_names":[],"tags_count":4,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pkgw%2Fneurosynchro","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pkgw%2Fneurosynchro/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pkgw%2Fneurosynchro/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pkgw%2Fneurosynchro/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pkgw","download_url":"https://codeload.github.com/pkgw/neurosynchro/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243997036,"owners_count":20380980,"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":["neural-networks","radiative-transfer","science","synchrotron-radiation"],"created_at":"2024-10-13T09:49:36.454Z","updated_at":"2025-03-17T07:44:34.610Z","avatar_url":"https://github.com/pkgw.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# neurosynchro\n\n*Neurosynchro* is a small Python package for creating and using neural networks\nto quickly approximate the coefficients needed for fully-polarized synchrotron\nradiative transfer. It builds on the [Keras](https://keras.io/) deep learning\nlibrary.\n\nSay that you have a code — such as\n[Rimphony](https://github.com/pkgw/rimphony/) or\n[Symphony](https://github.com/AFD-Illinois/symphony) — that calculates\nsynchrotron radiative transfer coefficients as a function of some input model\nparameters (electron temperature, particle energy index, etc.). These\ncalculations are often accurate but slow. With *neurosynchro*, you can train a\nneural network that will quickly approximate these calculations with good\naccuracy. The achievable level of accuracy will depend on the particulars of\nyour target distribution function, range of input parameters, and so on.\n\nThis code is specific to synchrotron radiation because it makes certain\nassumptions about how the coefficients scale with input parameters such as the\nobserving frequency.\n\nNeurosynchro is written by Peter K. G. Williams (\u003cpwilliams@cfa.harvard.edu\u003e).\n\n## Documentation\n\n*Neurosynchro’s* documentation\n [is on ReadTheDocs](https://neurosynchro.readthedocs.io/en/stable/).\n\n## Requirements\n\n\u003c!-- Keep synchronized with setup.py and doc/requirements.txt --\u003e\n\n- [keras](https://keras.io/) version 2.1 or greater.\n- [numpy](https://www.numpy.org/) version 1.10 or greater.\n- [pandas](https://pandas.pydata.org/) version 0.23.0 or greater.\n- [pwkit](https://github.com/pkgw/pwkit/) version 0.8.19 or greater.\n- [pytoml](https://github.com/avakar/pytoml) version 0.1.0 or greater.\n- [six](https://six.readthedocs.io/) version 1.10 or greater.\n\n## Recent Changes\n\nSee [the changelog](CHANGELOG.md).\n\n## Copyright and License\n\nThis code is copyright Peter K. G. Williams and collaborators. It is licensed\nunder the [MIT License](https://opensource.org/licenses/MIT).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpkgw%2Fneurosynchro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpkgw%2Fneurosynchro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpkgw%2Fneurosynchro/lists"}