Skip to main content

A python module to process and standardise ECG data

Project description

Schematic

An ECG processing module

version: 1.1.0

This repository host a mixture of function dealing with processing electrocardiogram (ECG) data, and preparing these data for analysis. The processing functions are intended for user defined parametrisation (using user supplied configuration files cnf) about the data which should be extracted, covering signal data such as waveforms or median beats, as well as metadata relevant for downstream QC or as tabular information.

The module implements a basic application programming interface, mapping ECG data from distinct file types (e.g. XML or DICOM) to class attributes providing a fixed interface for downstream analysis and interrogation.

The documentation for ECGProcess can be found here.

Installation

At present, the repository is undergoing development and no packages exist yet on PyPy or in Conda. Therefore it is recommended that it is installed in either of the two ways listed below. First, clone this repository and then cd to the root of the repository.

git clone git@gitlab.com:SchmidtAF/ECGProcess.git
cd ECGProcess

Installation using conda dependencies

A conda environment is provided in a yaml file in the directory ./resources/conda/envs/. A new conda environment called ecgprocess can be built using the command:

# From the root of the repository
conda env create --file ./resources/conda/envs/conda_create.yaml

To add to an existing environment use:

# From the root of the repository
conda env update --file ./resources/conda/envs/conda_update.yaml

Next the package can be installed:

python -m pip install .

Or for an editable (developer) install run the command below from the root of the repository. The difference with this is that you can just to a git pull to update repository, or switch branches without re-installing:

python -m pip install -e .

Installation not using any conda dependencies

If you are not using conda in any way then install the dependencies via pip and install repository as an editable install also via pip:

Install dependencies:

python -m pip install --upgrade -r requirements.txt

Then to install repository you can either do:

python -m pip install .

Or for an editable (developer) install run the command below from the root of the repository. The difference with this is that you can just to a git pull to update repository, or switch branches without re-installing:

python -m pip install -e .

Next steps...

After installation you might wish to try the pytest to confirm everything is in working order.

# From the root of the repository
pytest tests

Usage

Please have a look at the examples in resources for some possible recipes.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ecgprocess-1.1.0.tar.gz (350.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ecgprocess-1.1.0-py3-none-any.whl (369.5 kB view details)

Uploaded Python 3

File details

Details for the file ecgprocess-1.1.0.tar.gz.

File metadata

  • Download URL: ecgprocess-1.1.0.tar.gz
  • Upload date:
  • Size: 350.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for ecgprocess-1.1.0.tar.gz
Algorithm Hash digest
SHA256 9d131a9b9176d5a21fa6cb58df8e7651f07e9a5e3a04a0c9378b35debf3d3416
MD5 7128c132b11ceb133ae71b1a1cada05f
BLAKE2b-256 2c3fcbf648cf834b3308ee1f092810898e3668db918807aae330a70974433e1a

See more details on using hashes here.

File details

Details for the file ecgprocess-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: ecgprocess-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 369.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for ecgprocess-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 18cf1e00f33001e66345f4ded4a2a7d6f5da5baabc89eeab9df7da0e03f6874a
MD5 1ce9641b02b40eeb838c0f4a644c97e7
BLAKE2b-256 9f717f3e2a6608bc448fdea63f008b7d58ef028c129912ae67c5b52b5a4a8442

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page