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docs: build documentation using mkdocs
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JantineSmit authored Oct 16, 2024
2 parents 4bc88e1 + c946919 commit 4082346
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26 changes: 8 additions & 18 deletions .github/workflows/documentation.yml
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contents: write

on:
workflow_dispatch:
push:
branches:
- main
- drcandacemakedamoore/improve_docu
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
branches:
- main
- drcandacemakedamoore/improve_docu

jobs:
build-documentation:
if: github.event.pull_request.draft == false
name: Build documentation
runs-on: ubuntu-latest
strategy:
fail-fast: false
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python 3.10
uses: actions/setup-python@v2
with:
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- name: Upgrade pip and install dependencies
run: |
python3 -m pip install --upgrade pip setuptools
python3 -m pip install .[dev,publishing]
- name: Install pandoc using apt
run: sudo apt install pandoc
python3 -m pip install .[docs]
- name: Build documentation
run: make html
working-directory: docs
- name: Publish Docs to Pages
uses: JamesIves/github-pages-deploy-action@4.1.1
with:
branch: gh-pages
folder: docs/_build/html
run: mkdocs build
- name: Deploy documentation
run: mkdocs gh-deploy
2 changes: 2 additions & 0 deletions .gitignore
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**/test_data/*
.helpers/dock_test_data/*
.helpers/dock_test_add/*

/site/
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43 changes: 20 additions & 23 deletions README.md
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| License | [![github license badge](https://img.shields.io/github/license/EIT-ALIVE/eitprocessing)](git@github.com:EIT-ALIVE/eitprocessing) |
| Citation | [![DOI](https://zenodo.org/badge/617944717.svg)](https://zenodo.org/badge/latestdoi/617944717) |
| Fairness | [![OpenSSF Best Practices](https://www.bestpractices.dev/projects/9147/badge)](https://www.bestpractices.dev/projects/9147) [![fair-software badge](https://img.shields.io/badge/fair--software.eu-%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8B-yellow)](https://fair-software.eu) |
| GitHub Actions | ![build](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/build.yml/badge.svg) ![dash_actions](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/dash_actions.yml/badge.svg) ![lint](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/lint.yml/badge.svg) ![documentation](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/documentation.yml/badge.svg) ![cffconvert](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/cffconvert.yml/badge.svg) |
| GitHub Actions | ![build](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/build.yml/badge.svg) ![lint](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/lint.yml/badge.svg) ![documentation](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/documentation.yml/badge.svg) ![cffconvert](https://github.com/EIT-ALIVE/eitprocessing/actions/workflows/cffconvert.yml/badge.svg) |
| Python | ![Python](https://img.shields.io/badge/python-3.10-blue.svg) |

# Contents <!-- omit in toc -->

- [What is eitprocessing?](#what-is-eitprocessing)
- [Introduction](#introduction)
- [Installation](#installation)
- [Virtual environment](#virtual-environment)
- [Install using `pip`](#install-using-pip)
- [Install from PyPi](#install-from-pypi)
- [Developer install](#developer-install)
- [Documentation](#documentation)
- [Contributing](#contributing)
- [Credits](#credits)

# What is eitprocessing?

Processing of data from electrical impedance tomography and other respiratory monitoring tools.
# 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
Expand All @@ -36,40 +34,39 @@ and Timpel, as well as data from other sources. Several pre-processing tools and

[eit_dash](https://github.com/EIT-ALIVE/eit_dash) provides an accompanying GUI.

We welcome any [contributions or suggestions](CONTRIBUTING.md)

# Installation

## Virtual environment
# Installation

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).

For conda (using 'eit-alive' as example environment name; you can choose your own):
## Install from PyPi

eitprocessing can be installed from PyPi as follows:

```
conda create -n eit-alive python=3.10
conda activate eit-alive
pip install eitprocessing
```

## Install using `pip`

eitprocessing can be installed from PyPi as follows:
### Developer install
For full developer options (testing, etc):

- For basic use: `pip install eitprocessing`
- For full developer options (testing, etc):
- `git clone git@github.com:EIT-ALIVE/eitprocessing.git`
- `cd eitprocessing`
- `pip install -e ".[dev]"`
```
git clone git@github.com:EIT-ALIVE/eitprocessing.git
cd eitprocessing
pip install -e ".[dev]"
```

# Documentation

Please see our [usage documentation](https://eit-alive.github.io/eitprocessing/) for a detailed explanation of the package.
Please see our [user documentation](https://eit-alive.github.io/eitprocessing/) for a detailed explanation of the package.

# Contributing

If you want to contribute to the development of eitprocessing,
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
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# Categories

::: eitprocessing.categories.Category
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# Data containers

::: eitprocessing.datahandling.sequence.Sequence

::: eitprocessing.datahandling.eitdata.EITData

::: eitprocessing.datahandling.continuousdata.ContinuousData

::: eitprocessing.datahandling.sparsedata.SparseData

::: eitprocessing.datahandling.intervaldata.IntervalData

::: eitprocessing.datahandling.datacollection.DataCollection

::: eitprocessing.datahandling.breath.Breath

::: eitprocessing.datahandling.event.Event
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# Feature extraction

::: eitprocessing.features.breath_detection.BreathDetection


::: eitprocessing.features.moving_average.MovingAverage
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# Filters

::: eitprocessing.filters.butterworth_filters.LowPassFilter

::: eitprocessing.filters.butterworth_filters.HighPassFilter

::: eitprocessing.filters.butterworth_filters.BandStopFilter

::: eitprocessing.filters.butterworth_filters.BandPassFilter

::: eitprocessing.filters.butterworth_filters.ButterworthFilter

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# Loading functions

::: eitprocessing.datahandling.loading.load_eit_data
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# Parameters

::: eitprocessing.parameters.eeli.EELI
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Under construction
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div.doc-contents:not(.first) {
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}
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# Welcome to EITprocessing

# Introduction

Welcome to the documentation of the ALIVE software tool designed to load, analyze, and extract parameters from Electrical Impedance Tomography (EIT) data.
This software was designed by a joined effort of the Rotterdam Advanced Respiratory Care research group (ROTARC) of the Intensive Care of the Erasmus Medical Center and the Netherlands e-Science center. [Grant ID: NLESC.OEC.2022.002](https://research-software-directory.org/projects/alive)

EIT is a bedside non-invasive lung imaging tool: it continuously and real-time visualizes changes in lung volume. Our software tool serves as a comprehensive solution for handling EIT data from multiple leading manufacturers, including Sentec, Dräger, and Timpel.

The software tool includes a back-end for researchers that are familair with programming [eitprocessing](https://github.com/EIT-ALIVE/eitprocessing) and also a user-friendly dashboard [eit_dash](https://github.com/EIT-ALIVE/eit_dash) for clinical researchers allowing to quickly import datasets from various formats and sources and perform processing and analysis. This documentation page concerns eitprocessing.

Our tool offers robust analysis features. From basic filters to advanced signal processing techniques, you can extract meaningful parameters from your EIT data. With our dashboard we aim to provide default analysis pipelines and many opportunities for customization according to the user needs. Visualizations and interactive graphs make it easy to interpret the results and understand the underlying physiological processes.

It is important to note that the software tool is a work in progress, so not all fuctionalities are available yet. If you would like to contribute to coding you can reach out to us.

## Getting Started
To start using our software you can you use the [installation](installation.md) guide to set up the software on your system. Once installed, you can load your first dataset and explore the basic features.
We are committed to supporting your journey with EIT data analysis and extraction. If you encounter any issues or have questions you can put a pull request via github or emailadres.




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