resurfemg 0.0.4

A package for analysis of respiratory EMG data

ReSurfEMG

ReSurfEMG is an open source collaborative python library for analysis of respiratory electromyography (EMG). On the same site as the repository for this library we keep related resources.

The library was initially built for surface EMG, however many functions will also work for respiratory EMG directly acquired (trans-esophageal). This library supports the ongoing research at University of Twente on respiratory EMG.

Folders and Notebooks

researcher_interface:

• These are a growing series of interactive notebooks that allow researchers to investigate questions about their own EMG data
  • ⚡ Important: in almost all data there will be a time difference between EMG signals and ventilator signals. You can pre-process to correct for this lead or lag with the notebook called lead_lag_mismatch_upsample.

open_work:

• This folder contains experimental work by core members of the ReSurfEMG team (Dr. Eline Mos-Oppersma, Rob Warnaar, Dr. Walter Baccinelli and Dr. Candace Makeda Moore)

Program files

The main program in this repository contains functions for analysis of EMG and other electrophysiological signals. This analysis often includes analysis of signals from machiens i.e. ventilators as well.

Data sets

The notebooks are configured to run on various datasets. Contact Candace Makeda Moore ( 📫 [e-mail]) to discuss any questions on data configuration for your datasets.

Test data

You can get test data by extracting it from the Docker image like this:

mkdir -p not_pushed
cd ./not_pushed
docker create --name test-data crabbone/resurfemg-poly5-test-files:latest
docker cp test-data:/ReSurfEMG/tests/not_pushed/. .
docker rm -f test-data

Getting started

How to get the notebooks running? Assuming the raw data set and metadata is available.

0. If you want to work with the stable version create an empty environment, and install there:

   • Make sure you are in no environment: conda deactivate (repeat if you are in the base environment) You should be in no environment now

   • Create a blank environment conda create -n blank

   • Install within the blank environment: conda activate blank conda install -c conda-forge -c resurfemg resurfemg jupyter

1. To work with the most current versions: Install all Python packages required, using conda and the environment.yml file.

   • The command for Windows/Anaconda users can be something like: conda env create -f environment.yml.
   • Linux users can create their own environment by hand.

2. Open a notebook in researcher_interface and interactively run the cells. Note, if you run with an installed library import appropriately

Generating documentation

Up to date documentation can be generated in command-line as follows (in bash terminal):

python3 -m venv .venv
. ./.venv/bin/activate
pip install wheel sphinx
./setup.py install
./setup.py apidoc
./setup.py build_sphinx

If you are working in a VScode command line interface (terminal cmd):

This is given with cmd.exe in mind:

python3 -m venv .venv
.venv/bin/activate
pip install wheel sphinx
python setup.py install
python setup.py apidoc
python setup.py build_sphinx

Online documentation can be found at https://resurfemg.github.io/ReSurfEMG/ or on https://readthedocs.org/ by searching for ReSurfEMG

Automation

The project comes with several modifications to the typical default setup.py.

At the moment, the support for Anaconda Python is lacking. The instructions and the commands listed below will work in Anaconda installation but due to the difference in management of installed packages, the project will be installed into base environment regardless of the currently active one. We are planning to integrate with Anaconda in near future.

The project has a sub-project of a related dashboard. Dashboard is a GUI that exposes some of the project's fucntionality. There is a legacy dashboard in the same repository with ReSurfEMG code but we have moved the current version of the dashboard into it's own repository: https://github.com/ReSurfEMG/ReSurfEMG-dashboard

As of today, we use out own version of the package TMSiSDK together with our project. Hopefully, this is a temporary measure, and, eventually, TMSiSDK will become just another independent project we may depend on. The TMSiSDK project (which has an Apache 2 license) can be added as a submodule containing our patched fork of the original code. You will need to pull Git submodules in order to be able to properly install and run the project.

New commands

Commands that perform repeating tasks have a --fast option. Use this if you ran setup.py install_dev, and you are sure the dependencies are up to date. Otherwise, these commands will create a new virtual environment and install necessary dependencies there before execution. This is primarily intended for use in CI to create controlled environment.

Please note that documentation is built using sphinx command for setuptools: setup.py build_sphinx, but sphinx is not installed as part of development dependencies, rather it is declared as a dependancy of setup.py itself. There are cases when setup.py will not install its own dependencies. You are advised to install them manually.

• setup.py lint checks that the source code is formatted accoring to PEP-8 recommendations.
• setup.py isort checks that the imports are properly formatted and sorted.
• setup.py apidoc generates RST outlines necessary to generate documentation.
• setup.py install_dev installs dependencies necessary for development.

Modified commands

• setup.py test the original command is overloaded with a new one. Similarly to most of the new commands, this command takes --fast as an option with the same meaning. Unlike its predecessor, this command will create a clean environment and install all necessary dependencies before running the test (the original did install dependencies, but ran the test in the source directory, this made it impossible to test code that relied on being installed).

Installing from source

The traditional way to install from source is to run setup.py install or setup.py develop. Both of these will work... sort of. This is because of the default behavior inherited from setuptools. The problem here is that instead of creating a distributable package and installing that, setuptools does it in the other order: it installs the package in order to create a distributable one.

As was already mentioned earlier, Anaconda Python will need better support, at which point, setup.py install will have to change to enable that.

We are not planning on patching setup.py develop as we don't believe it is a good practice to use this command. It is not removed, however, and should work in the same way it would work with a typical setuptools project.

Note that pip install -e . and pip install -e '.[dev]' are discouranged by association (since that is just a wrapper around setup.py develop.) Similarly to setup.py develop they might work, but you have to be careful with interpreting the results. If those don't work, it's on you.

Testing

The project doesn't include testing data. It was packaged into a Docker image which can be found at crabbone/resurfemg-poly5-test-files:latest. This test data was created by taking a signal from equipment, not a human, and certainly not a patient.

It is possible to run tests in container created from this image. Alternatively, you may download the image and extract directory /ReSurfEMG/tests/not_pushed into not_pushed in the root of the project.

Below is a snippet that may help you to run the tests in a container:

docker run --rm -v $(pwd):/ci \
    --cap-add=SYS_ADMIN \
    --privileged=true \
    crabbone/resurfemg-poly5-test-files \
    sh -c 'set -xe
        cd /ci
        mkdir -p ./not_pushed/
        mount --bind /ReSurfEMG/tests/not_pushed/ ./not_pushed/
        python setup.py test'

✨Copyright 2022 Netherlands eScience Center and U. Twente Licensed under the Apache License, version 2.0. See LICENSE for details.✨