rapidhrv 0.2.7

A package for preprocessing, analyzing and visualizing cardiac data

RapidHRV

RapidHRV is a data processing pipeline for the analysis and visualization of cardiac data.

Please provide credit where appropriate:

Kirk, P. A., Bryan, A. D., Garfinkel, S. N., & Robinson, O. J. (2022). RapidHRV: An open-source toolbox for extracting heart rate and heart rate variability. PeerJ, 10, e13147. https://doi.org/10.7717/peerj.13147

This library is distributed under an MIT License

Installation

pip install rapidhrv

Usage

Given a numpy array, or something convertable to it (such as a list), rapidhrv.preprocess can generate input suitable for analysis with rapidhrv.analyze, which will return a pandas dataframe containing HRV data.

import numpy as np
import rapidhrv as rhv

my_data = np.load("my_data.npy")  # Load data
data = rhv.Signal(my_data, sample_rate=50)  # Convert to rhv Signal class
preprocessed = rhv.preprocess(data)  # Preprocess: may interpolate data, check the docstring on `rapidhrv.preprocess`
result = rhv.analyze(preprocessed)  # Analyze signal

Documentation

Please see the included tutorial notebook.

Development

In order to get a working development environment, please install Poetry for your platform, and run poetry install to generate a virtual environment.

If you plan on making any changes to the included notebooks, please run nbstripout --install from within the poetry venv before committing any changes.

To run said notebooks from the environment provided by poetry, install the required dependencies with poetry install --extras notebooks.