{"id":43565576,"url":"https://github.com/richardkoehler/pte-decode","last_synced_at":"2026-02-03T21:20:28.084Z","repository":{"id":41958338,"uuid":"454016163","full_name":"richardkoehler/pte-decode","owner":"richardkoehler","description":"PTE Decode is an open-source software package for neural decoding.","archived":false,"fork":false,"pushed_at":"2025-04-03T05:58:14.000Z","size":277,"stargazers_count":2,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-03T06:35:02.958Z","etag":null,"topics":["adbs","dbs","ecog","ieeg","lfp","machine-learning"],"latest_commit_sha":null,"homepage":"","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/richardkoehler.png","metadata":{"files":{"readme":"README.md","changelog":null,"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":"2022-01-31T13:26:01.000Z","updated_at":"2024-01-11T16:53:15.000Z","dependencies_parsed_at":"2024-02-13T12:54:59.146Z","dependency_job_id":"52177fed-319f-4a12-99dc-d9bf94047de7","html_url":"https://github.com/richardkoehler/pte-decode","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/richardkoehler/pte-decode","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richardkoehler%2Fpte-decode","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richardkoehler%2Fpte-decode/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richardkoehler%2Fpte-decode/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richardkoehler%2Fpte-decode/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/richardkoehler","download_url":"https://codeload.github.com/richardkoehler/pte-decode/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richardkoehler%2Fpte-decode/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29057518,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-03T20:13:53.544Z","status":"ssl_error","status_checked_at":"2026-02-03T20:13:40.507Z","response_time":96,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["adbs","dbs","ecog","ieeg","lfp","machine-learning"],"created_at":"2026-02-03T21:20:27.360Z","updated_at":"2026-02-03T21:20:28.076Z","avatar_url":"https://github.com/richardkoehler.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Homepage][homepage-shield]][homepage-url]\n[![License][license-shield]][license-url]\n[![Contributors][contributors-shield]][contributors-url]\n[![Code Style][codestyle-shield]][codestyle-url]\n\n# PTE Decode - Python tools for electrophysiology\n\nPTE Decode is an open-source software package for neural decoding.\n\nIt builds upon [PTE](https://github.com/richardkoehler/pte) and aims at decoding\nintracranial EEG (iEEG) signals such as local field potentials (LFP)\nelectrocorticography (ECoG).\n\nPTE Decode implements sample-wise decoding and lets you define epochs based on\nspecific events to avoid circular training.\n\n## Installing PTE Decode\n\nFirst, get the current development version of PTE using\n[git](https://git-scm.com/). Then type the following command into a terminal:\n\n```bash\ngit clone https://github.com/richardkoehler/pte-decode\n```\n\nUse the package manager\n[conda](https://docs.conda.io/projects/conda/en/latest/index.html) to set up a\nnew working environment. To do so, use `cd` in your terminal to navigate to the\nPTE root directory and type:\n\n```bash\nconda env create -f env.yml\n```\n\nThis will set up a new conda environment called `pte-decode`.\n\nTo activate the environment then type:\n\n```bash\nconda activate pte-decode\n```\n\nFinally, to install PTE Decode in an editable development version inside your\nenvironment type the following inside the PTE Decode root directory:\n\n```bash\npip install -e .\n```\n\n## Usage\n\n```python\nimport pte_decode\n\n# Examples\n```\n\n## Contributing\n\nPlease feel free to contribute.\n\nFor any minor additions or bugfixes, you may simply create a **pull request**.\n\nFor any major changes, make sure to open an **issue** first. When you then\ncreate a pull request, be sure to **link the pull request** to the open issue in\norder to close the issue automatically after merging.\n\nTo contribute, consider installing the full conda development environment to\ninclude such tools as black, pylint and isort:\n\n```bash\nconda env create -f env_dev.yml\nconda activate pte-decode-dev\n```\n\nContinuous Integration (CI) including automated testing are set up.\n\n## License\n\nPTE is licensed under the [MIT license](license-url).\n\n\u003c!-- MARKDOWN LINKS \u0026 IMAGES --\u003e\n\u003c!-- https://www.markdownguide.org/basic-syntax/#reference-style-links --\u003e\n\n[contributors-shield]:\n  https://img.shields.io/github/contributors/richardkoehler/pte.svg?style=for-the-badge\n[contributors-url]: https://github.com/richardkoehler/pte/graphs/contributors\n[license-shield]:\n  https://img.shields.io/static/v1?label=License\u0026message=MIT\u0026logoColor=black\u0026labelColor=grey\u0026logoWidth=20\u0026color=yellow\u0026style=for-the-badge\n[license-url]: https://github.com/richardkoehler/pte/blob/main/LICENSE/\n[codestyle-shield]:\n  https://img.shields.io/static/v1?label=CodeStyle\u0026message=black\u0026logoColor=black\u0026labelColor=grey\u0026logoWidth=20\u0026color=black\u0026style=for-the-badge\n[codestyle-url]: https://github.com/psf/black\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frichardkoehler%2Fpte-decode","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frichardkoehler%2Fpte-decode","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frichardkoehler%2Fpte-decode/lists"}