This repository contains various utility functions for recurrence quantitative analysis (RQA) of time series data as well as a tutorial notebook which introduces recurrence analysis. The notebook (RQA_Tutorial.ipynb) contains several interactive widgets for exploring recurrence plots and metrics for some characteristic dynamical systems can be found in the repository's root directory.

Both the tutorial and source code make use of the package pyunicorn for performing RQA. The code depends on an older version of pyunicorn which contains methods that were removed in subsequent versions. Because this older version mysteriously is no longer found on their repository, I've included this specific version of pyunicorn via a cached copy in my repositories as a project dependency. For the latest version of pyunicorn, along with the software's license and README, please visit their official repository.

The tutorial also requires this project (and LaTeX) to be installed before it can be run. The notebook can be opened in Google Colab if you'd like to run the notebook without needing to install anything locally -- just make sure to run the first cell of the notebook to download the necessary dependencies in your Colab runtime.

In the case that you want to run the tutorial locally, please ensure that you've installed this project before running the notebook and that your local environment has a working LaTeX compiler/distribution. If you don't have LaTeX (or don't want to install it) and you run into matplotlib errors about strings not getting compiled because the command latex couldn't be found, try running the following lines before re-running any of the code cells in the tutorial notebook to tell matplotlib not to use LaTeX for typesetting: import matplotlib as mpl mpl.rcParams['text.usetex'] = False

The tutorial notebook doesn't ship with the project's source code, so if you'd like a copy of the notebook along with the RQA utilities, you'll need to clone this repository to your local machine (i.e., pip install git+https://github.com/keriheuer/rqa will only install the source code as the package rqa). For both the notebook and source code, after using the command git clone on this repository, simply cd into the cloned directory and run pip install . inside it.