| Name | sleepeegpy JSON |
| Version |
0.6.0
JSON |
| download |
| home_page | None |
| Summary | Sleep EEG preprocessing, analysis and visualization |
| upload_time | 2024-10-08 14:55:53 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.12,>=3.10 |
| license | MIT |
| keywords |
sleep
eeg
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# sleepeegpy
**sleepeegpy** is a high-level package built on top of [mne-python](https://mne.tools/stable/index.html), [yasa](https://raphaelvallat.com/yasa/build/html/index.html) and [specparam (fooof)](https://fooof-tools.github.io/fooof/) for preprocessing, analysis, and visualization of sleep EEG data.
## Installation
0. Make sure you have [Python](https://www.python.org/downloads/) version installed. Requires Python >3.9, <3.12.
1. Create a Python virtual environment, for more info you can refer to python [venv](https://docs.python.org/3/tutorial/venv.html), [virtualenv](https://virtualenv.pypa.io/en/latest/user_guide.html) or [conda](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html).
2. Activate the environment
3.
```
pip install sleepeegpy
```
4. [Download](https://github.com/NirLab-TAU/sleepeegpy/archive/refs/heads/main.zip) this repository zip folder, you will need only the notebooks folder.
## Quickstart
1. Open the complete pipeline notebook in the created environment.
2. Follow the notebook's instructions.
## RAM requirements
For overnight, high-density (256 channels) EEG recordings downsampled to 250 Hz expect at least 64 GB RAM expenditure for cleaning, spectral analyses and event detection.
## Retrieve example dataset
```
odie = pooch.create(
path=pooch.os_cache("sleepeegpy_dataset"),
base_url="doi:10.5281/zenodo.10362189",
)
odie.load_registry_from_doi()
bad_channels = odie.fetch("bad_channels.txt")
annotations = odie.fetch("annotations.txt")
path_to_eeg = odie.fetch("resampled_raw.fif")
for i in range(1,4):
odie.fetch(f"resampled_raw-{i}.fif")
```
Raw data
{
"_id": null,
"home_page": null,
"name": "sleepeegpy",
"maintainer": null,
"docs_url": null,
"requires_python": "<3.12,>=3.10",
"maintainer_email": null,
"keywords": "sleep, eeg",
"author": null,
"author_email": "Gennadiy Belonosov <gennadiyb@mail.tau.ac.il>, Rotem Falach <rotemfalach@mail.tau.ac.il>",
"download_url": "https://files.pythonhosted.org/packages/c1/0c/c59b90b26af2454d1093594fc44eeec55a8d9e396aaf5d861749757deb56/sleepeegpy-0.6.0.tar.gz",
"platform": null,
"description": "# sleepeegpy\n**sleepeegpy** is a high-level package built on top of [mne-python](https://mne.tools/stable/index.html), [yasa](https://raphaelvallat.com/yasa/build/html/index.html) and [specparam (fooof)](https://fooof-tools.github.io/fooof/) for preprocessing, analysis, and visualization of sleep EEG data.\n## Installation\n0. Make sure you have [Python](https://www.python.org/downloads/) version installed. Requires Python >3.9, <3.12.\n1. Create a Python virtual environment, for more info you can refer to python [venv](https://docs.python.org/3/tutorial/venv.html), [virtualenv](https://virtualenv.pypa.io/en/latest/user_guide.html) or [conda](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html).\n2. Activate the environment\n3. \n ```\n pip install sleepeegpy\n ```\n4. [Download](https://github.com/NirLab-TAU/sleepeegpy/archive/refs/heads/main.zip) this repository zip folder, you will need only the notebooks folder.\n\n## Quickstart\n1. Open the complete pipeline notebook in the created environment.\n2. Follow the notebook's instructions. \n\n## RAM requirements\nFor overnight, high-density (256 channels) EEG recordings downsampled to 250 Hz expect at least 64 GB RAM expenditure for cleaning, spectral analyses and event detection.\n\n## Retrieve example dataset\n```\nodie = pooch.create(\n path=pooch.os_cache(\"sleepeegpy_dataset\"),\n base_url=\"doi:10.5281/zenodo.10362189\",\n)\nodie.load_registry_from_doi()\nbad_channels = odie.fetch(\"bad_channels.txt\")\nannotations = odie.fetch(\"annotations.txt\")\npath_to_eeg = odie.fetch(\"resampled_raw.fif\")\nfor i in range(1,4):\n odie.fetch(f\"resampled_raw-{i}.fif\")\n```\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Sleep EEG preprocessing, analysis and visualization",
"version": "0.6.0",
"project_urls": {
"Documentation": "https://nirlab-tau.github.io/sleepeegpy/",
"Homepage": "https://github.com/NirLab-TAU/sleepeegpy"
},
"split_keywords": [
"sleep",
" eeg"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "b98592c3ba36540f66588ea4501b546b45c7965f05abf5ef113daf87be58e3d8",
"md5": "bb5c33262e1373e54b3a9fac2ca539ee",
"sha256": "622788053c9aa9188b68511f77272aea64ea65a34a211de6995deadbd010479c"
},
"downloads": -1,
"filename": "sleepeegpy-0.6.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "bb5c33262e1373e54b3a9fac2ca539ee",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<3.12,>=3.10",
"size": 28295,
"upload_time": "2024-10-08T14:55:51",
"upload_time_iso_8601": "2024-10-08T14:55:51.902945Z",
"url": "https://files.pythonhosted.org/packages/b9/85/92c3ba36540f66588ea4501b546b45c7965f05abf5ef113daf87be58e3d8/sleepeegpy-0.6.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "c10cc59b90b26af2454d1093594fc44eeec55a8d9e396aaf5d861749757deb56",
"md5": "8cf6050e94a1f67cc8f2bd1086474e98",
"sha256": "cec03c5a70cefa9cafeda0975eb4b77e59460d80fe8b2311c1f32c7bda61f421"
},
"downloads": -1,
"filename": "sleepeegpy-0.6.0.tar.gz",
"has_sig": false,
"md5_digest": "8cf6050e94a1f67cc8f2bd1086474e98",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<3.12,>=3.10",
"size": 27710,
"upload_time": "2024-10-08T14:55:53",
"upload_time_iso_8601": "2024-10-08T14:55:53.188448Z",
"url": "https://files.pythonhosted.org/packages/c1/0c/c59b90b26af2454d1093594fc44eeec55a8d9e396aaf5d861749757deb56/sleepeegpy-0.6.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-10-08 14:55:53",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "NirLab-TAU",
"github_project": "sleepeegpy",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "sleepeegpy"
}
