| Name | autocleaneeg-pipeline JSON |
| Version |
2.2.6
JSON |
| download |
| home_page | None |
| Summary | A modular framework for automated EEG data processing, built on MNE-Python |
| upload_time | 2025-09-10 15:39:59 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.10 |
| license | MIT License Copyright (c) 2024 Cincinnati Children's Hospital Medical Center Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
bids
eeg
electrophysiology
mne-python
neuroscience
preprocessing
signal-processing
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# AutoCleanEEG Pipeline
[](https://www.python.org/downloads/)
[](LICENSE)
[](https://github.com/psf/black)
A modular framework for automated EEG data processing, built on MNE-Python.
## Features
- Framework for automated EEG preprocessing with "lego block" modularity
- Support for multiple EEG paradigms (ASSR, Chirp, MMN, Resting State)
- BIDS-compatible data organization and comprehensive quality control
- Extensible plugin system for file formats, montages, and event processing
- Research-focused workflow: single file testing → parameter tuning → batch processing
- Detailed output: logs (stored in your AutoClean workspace), stage files, metadata, and quality control visualizations
## Installation (uv)
Use Astral's uv for fast, isolated installs. If you don't have uv yet, see https://docs.astral.sh/uv/
- Install CLI (recommended for users):
```bash
uv tool install autocleaneeg-pipeline
autocleaneeg-pipeline --help
```
- Upgrade or remove:
```bash
uv tool upgrade autocleaneeg-pipeline
uv tool uninstall autocleaneeg-pipeline
```
- Development install from source:
```bash
git clone https://github.com/cincibrainlab/autoclean_pipeline.git
cd autoclean_pipeline
uv venv && source .venv/bin/activate # Windows: .venv\\Scripts\\activate
uv pip install -e .
# Optional extras
# uv pip install -e '.[gui]' # GUI review tool dependencies
# uv pip install -e '.[docs]' # Documentation tooling
```
## Quick Start
Process a file using a built-in task:
```bash
autocleaneeg-pipeline process RestingEyesOpen /path/to/data.raw
```
List tasks and show overrides:
```bash
autocleaneeg-pipeline list-tasks --overrides
```
## Theme and Color
AutoClean’s CLI uses Rich with semantic styles and adaptive themes for readable output across light/dark terminals, limited color depth, and colorless logs.
- Flag: `--theme auto|dark|light|hc|mono` (default: `auto`)
- `mono`: Monochrome (no hues), ideal for logs or unknown backgrounds
- `hc`: High-contrast, accessible on both dark and light backgrounds
- Env overrides:
- `AUTOCLEAN_THEME=auto|dark|light|hc|mono`
- `AUTOCLEAN_COLOR_DEPTH=auto|8|256|truecolor`
- `NO_COLOR=1` disables color
- `FORCE_COLOR=1` forces color even in non-TTY (e.g., CI)
Examples:
```bash
autocleaneeg-pipeline --theme light list-tasks
AUTOCLEAN_THEME=hc autocleaneeg-pipeline version
NO_COLOR=1 autocleaneeg-pipeline list-tasks
```
## Documentation
Full documentation is available at [https://cincibrainlab.github.io/autoclean_pipeline/](https://cincibrainlab.github.io/autoclean_pipeline/)
## Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- Cincinnati Children's Hospital Research Foundation
- Built with [MNE-Python](https://mne.tools/)
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"description": "# AutoCleanEEG Pipeline\n\n[](https://www.python.org/downloads/)\n[](LICENSE)\n[](https://github.com/psf/black)\n\nA modular framework for automated EEG data processing, built on MNE-Python.\n\n\n\n## Features\n\n- Framework for automated EEG preprocessing with \"lego block\" modularity\n- Support for multiple EEG paradigms (ASSR, Chirp, MMN, Resting State) \n- BIDS-compatible data organization and comprehensive quality control\n- Extensible plugin system for file formats, montages, and event processing\n- Research-focused workflow: single file testing \u2192 parameter tuning \u2192 batch processing\n- Detailed output: logs (stored in your AutoClean workspace), stage files, metadata, and quality control visualizations\n\n## Installation (uv)\n\nUse Astral's uv for fast, isolated installs. If you don't have uv yet, see https://docs.astral.sh/uv/\n\n- Install CLI (recommended for users):\n\n```bash\nuv tool install autocleaneeg-pipeline\nautocleaneeg-pipeline --help\n```\n\n- Upgrade or remove:\n\n```bash\nuv tool upgrade autocleaneeg-pipeline\nuv tool uninstall autocleaneeg-pipeline\n```\n\n- Development install from source:\n\n```bash\ngit clone https://github.com/cincibrainlab/autoclean_pipeline.git\ncd autoclean_pipeline\nuv venv && source .venv/bin/activate # Windows: .venv\\\\Scripts\\\\activate\nuv pip install -e .\n# Optional extras\n# uv pip install -e '.[gui]' # GUI review tool dependencies\n# uv pip install -e '.[docs]' # Documentation tooling\n```\n\n## Quick Start\n\nProcess a file using a built-in task:\n\n```bash\nautocleaneeg-pipeline process RestingEyesOpen /path/to/data.raw\n```\n\nList tasks and show overrides:\n\n```bash\nautocleaneeg-pipeline list-tasks --overrides\n```\n\n## Theme and Color\n\nAutoClean\u2019s CLI uses Rich with semantic styles and adaptive themes for readable output across light/dark terminals, limited color depth, and colorless logs.\n\n- Flag: `--theme auto|dark|light|hc|mono` (default: `auto`)\n - `mono`: Monochrome (no hues), ideal for logs or unknown backgrounds\n - `hc`: High-contrast, accessible on both dark and light backgrounds\n- Env overrides:\n - `AUTOCLEAN_THEME=auto|dark|light|hc|mono`\n - `AUTOCLEAN_COLOR_DEPTH=auto|8|256|truecolor`\n - `NO_COLOR=1` disables color\n - `FORCE_COLOR=1` forces color even in non-TTY (e.g., CI)\n\nExamples:\n\n```bash\nautocleaneeg-pipeline --theme light list-tasks\nAUTOCLEAN_THEME=hc autocleaneeg-pipeline version\nNO_COLOR=1 autocleaneeg-pipeline list-tasks\n```\n\n## Documentation\n\nFull documentation is available at [https://cincibrainlab.github.io/autoclean_pipeline/](https://cincibrainlab.github.io/autoclean_pipeline/)\n\n## Contributing\n\nWe welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Acknowledgments\n\n- Cincinnati Children's Hospital Research Foundation\n- Built with [MNE-Python](https://mne.tools/)\n",
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