Research Investigation of Timeseries with Multiday Oscillations
Project description
Research Investigation of Timeseries with Multiday Oscillations (RITMO)
This package provides a python toolbox for assessing the slow-drifting correlation and causation between two oscialltory timeseries' with multiday patterns. It includes three well-estabilised approaches:
- Empirical Dynamic Modelling (also known as EDM)
- Phase locking value
- Mutual information
Installation
Command line using the Python pip module: python -m pip install ritmo
Usage
Example usage at the python prompt:
>>> from ritmo import Ritmo
>>> import numpy as np
>>> x = np.arange(0, 100*24*3.6e6, 3.6e6) # UNIX timestamps in milliseconds
>>> y1 = np.random.random(x.size) # first random timeseries
>>> y2 = np.ra6ndom.random(x.size) # second random timeseries
>>> ritmo = Ritmo(y1 = y1, y2 = y2, x1 = x)
>>> ritmo.run()
References
Stirling et al. 2022. A methodology to assess cyclical correlates: case study of the heart and the epileptic brain.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
RITMO-1.0.4-py3-none-any.whl
(12.2 kB
view hashes)