# EITprocessing <!-- omit in toc -->
## Introduction
[Electrical Impedance Tomography](https://en.wikipedia.org/wiki/Electrical_impedance_tomography) (EIT) is a noninvasive
and radiation-free continuous imaging tool for monitoring respiratory mechanics. eitprocessing aims to provide a
versatile, user-friendly, reproducible and reliable workflow for the processing and analysis of EIT data and related
waveform data, like pressures and flow.
`eitprocessing` includes tools to load data exported from EIT-devices from several manufacturers, including Dräger, SenTec
and Timpel, as well as data from other sources. Several pre-processing tools and analysis tools are provided.
<!-- TODO when available, add summarisation and reporting -->
<!-- TODO extend with short list of available tools when applicable -->
| Badges | |
| :------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Registry | [](https://www.research-software.nl/software/eitprocessing) [](https://pypi.python.org/project/eitprocessing/) [](git@github.com:EIT-ALIVE/eitprocessing) |
| License | [](git@github.com:EIT-ALIVE/eitprocessing) |
| Citation | [](https://zenodo.org/badge/latestdoi/617944717) |
| Fairness | [](https://www.bestpractices.dev/projects/9147) [](https://fair-software.eu) |
| GitHub Actions |     [](https://coveralls.io/github/EIT-ALIVE/eitprocessing?branch=main) |
| Python Support |     |
| Linting | [](https://github.com/astral-sh/ruff) |
## Contents <!-- omit in toc -->
- [Introduction](#introduction)
- [Installation](#installation)
- [Install from PyPi](#install-from-pypi)
- [Developer install](#developer-install)
- [Documentation](#documentation)
- [Contributing](#contributing)
- [Credits](#credits)
## Installation <!-- --8<-- [start:install] -->
It is advised to install eitprocessing in a dedicated virtual environment. See e.g. [Install packages in a virtual
environment using pip and
venv](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/) or [Getting started
with conda](https://docs.conda.io/projects/conda/en/stable/user-guide/getting-started.html).
### Install from PyPi
eitprocessing can be installed from PyPi as follows:
```bash
pip install eitprocessing
```
### Developer install
For full developer options (testing, etc):
```bash
git clone git@github.com:EIT-ALIVE/eitprocessing.git
cd eitprocessing
pip install -e ".[dev]"
```
<!-- --8<-- [end:install] -->
## Documentation
Please see our [user documentation](https://eit-alive.github.io/eitprocessing/) for a detailed explanation of the package.
## Contributing
We welcome any contributions or suggestions. If you want to contribute to the development of eitprocessing,
have a look at the [contribution guidelines](CONTRIBUTING.md) and the [developer documentation](README.dev.md).
## Credits
This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [NLeSC/python-template](https://github.com/NLeSC/python-template).
Raw data
{
"_id": null,
"home_page": null,
"name": "eitprocessing",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "Mechanical lung ventilation, Electrical impedance tomography, Image/data processing, Advanced respiratory care",
"author": null,
"author_email": "Dani Bodor <d.bodor@esciencecenter.nl>, Peter Somhorst <p.somhorst@erasmusmc.nl>, Annemijn Jonkman <a.jonkman@erasmusmc.nl>, Walter Baccinelli <w.baccinelli@esciencecenter.nl>, Jantine Wisse-Smit <j.j.smit@erasmusmc.nl>, Juliette Francovich <j.francovich@erasmusmc.nl>",
"download_url": "https://files.pythonhosted.org/packages/ec/5f/db32c9277c37b3657292c99b0d09ffc2e2522aa295fc79600e02ff8a6149/eitprocessing-1.5.1.tar.gz",
"platform": null,
"description": "# EITprocessing <!-- omit in toc -->\n\n## Introduction\n\n[Electrical Impedance Tomography](https://en.wikipedia.org/wiki/Electrical_impedance_tomography) (EIT) is a noninvasive\nand radiation-free continuous imaging tool for monitoring respiratory mechanics. eitprocessing aims to provide a\nversatile, user-friendly, reproducible and reliable workflow for the processing and analysis of EIT data and related\nwaveform data, like pressures and flow.\n\n`eitprocessing` includes tools to load data exported from EIT-devices from several manufacturers, including Dr\u00e4ger, SenTec\nand Timpel, as well as data from other sources. Several pre-processing tools and analysis tools are provided.\n\n<!-- TODO when available, add summarisation and reporting -->\n<!-- TODO extend with short list of available tools when applicable -->\n\n| Badges | |\n| :------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Registry | [](https://www.research-software.nl/software/eitprocessing) [](https://pypi.python.org/project/eitprocessing/) [](git@github.com:EIT-ALIVE/eitprocessing) |\n| License | [](git@github.com:EIT-ALIVE/eitprocessing) |\n| Citation | [](https://zenodo.org/badge/latestdoi/617944717) |\n| Fairness | [](https://www.bestpractices.dev/projects/9147) [](https://fair-software.eu) |\n| GitHub Actions |     [](https://coveralls.io/github/EIT-ALIVE/eitprocessing?branch=main) |\n| Python Support |     |\n| Linting | [](https://github.com/astral-sh/ruff) |\n\n## Contents <!-- omit in toc -->\n\n- [Introduction](#introduction)\n- [Installation](#installation)\n - [Install from PyPi](#install-from-pypi)\n - [Developer install](#developer-install)\n- [Documentation](#documentation)\n- [Contributing](#contributing)\n- [Credits](#credits)\n\n## Installation <!-- --8<-- [start:install] -->\n\nIt is advised to install eitprocessing in a dedicated virtual environment. See e.g. [Install packages in a virtual\nenvironment using pip and\nvenv](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/) or [Getting started\nwith conda](https://docs.conda.io/projects/conda/en/stable/user-guide/getting-started.html).\n\n### Install from PyPi\n\neitprocessing can be installed from PyPi as follows:\n\n```bash\npip install eitprocessing\n```\n\n### Developer install\n\nFor full developer options (testing, etc):\n\n```bash\ngit clone git@github.com:EIT-ALIVE/eitprocessing.git\ncd eitprocessing\npip install -e \".[dev]\"\n```\n\n<!-- --8<-- [end:install] -->\n\n## Documentation\n\nPlease see our [user documentation](https://eit-alive.github.io/eitprocessing/) for a detailed explanation of the package.\n\n## Contributing\n\nWe welcome any contributions or suggestions. If you want to contribute to the development of eitprocessing,\nhave a look at the [contribution guidelines](CONTRIBUTING.md) and the [developer documentation](README.dev.md).\n\n## Credits\n\nThis package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [NLeSC/python-template](https://github.com/NLeSC/python-template).\n",
"bugtrack_url": null,
"license": "Apache-2.0 license",
"summary": "Processing of lung image data from electrical impedance tomography.",
"version": "1.5.1",
"project_urls": {
"Changelog": "https://github.com/EIT-ALIVE/eitprocessing/blob/main/CHANGELOG.md",
"Documentation": "https://github.com/EIT-ALIVE/eitprocessing/blob/main/README.md",
"Repository": "https://github.com/EIT-ALIVE/eitprocessing/"
},
"split_keywords": [
"mechanical lung ventilation",
" electrical impedance tomography",
" image/data processing",
" advanced respiratory care"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "5b39276729df2fd961cd9f14650150b448d22e34f41874097bc027af80107fcf",
"md5": "a907e04173e98a3be2ce4c6a3b2eb7e3",
"sha256": "b5300052f7e68783779562eff9678d0130ac50f7d7184489151bc401d1a51317"
},
"downloads": -1,
"filename": "eitprocessing-1.5.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "a907e04173e98a3be2ce4c6a3b2eb7e3",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 64569,
"upload_time": "2024-12-18T20:28:48",
"upload_time_iso_8601": "2024-12-18T20:28:48.217188Z",
"url": "https://files.pythonhosted.org/packages/5b/39/276729df2fd961cd9f14650150b448d22e34f41874097bc027af80107fcf/eitprocessing-1.5.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ec5fdb32c9277c37b3657292c99b0d09ffc2e2522aa295fc79600e02ff8a6149",
"md5": "73e0d7e0467bdbef1b2a723092a940e9",
"sha256": "1476993f162ecaf3440ddaad8431e40cbf2a98293a57b16a9e0fba6c01462378"
},
"downloads": -1,
"filename": "eitprocessing-1.5.1.tar.gz",
"has_sig": false,
"md5_digest": "73e0d7e0467bdbef1b2a723092a940e9",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 71519,
"upload_time": "2024-12-18T20:28:49",
"upload_time_iso_8601": "2024-12-18T20:28:49.659646Z",
"url": "https://files.pythonhosted.org/packages/ec/5f/db32c9277c37b3657292c99b0d09ffc2e2522aa295fc79600e02ff8a6149/eitprocessing-1.5.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-18 20:28:49",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "EIT-ALIVE",
"github_project": "eitprocessing",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "eitprocessing"
}
JSON
