Related Time-Series Resources

Resources related to HCTSA including talks/demos, workflow examples and related packages.

A collection of good resources for time-series analysis (including in other programming languages like python and R) are listed here. See also larger collections of time-series resources, by Lukasz Mentel and, focused on python: Max Christ.

Time-Series Data

CompEngine

Accompanying web resource that provides a self-organising database of time-series data. It allows users to upload, explore, and compare thousands of different types of time-series data.

pyspi

pyspi is a comprehensive python library for computing hundreds of statistics of pairwise interactions (SPIs) directly from multivariate time series (MTS) data.

Feature sets derived from hctsa

catch22

This reduced set of 22 features, determined through a combination of classification performance (across 93 problems) and mutual redundancy (as explained in this 📗 paper), is available here as an efficiently coded C implementation.

catchamouse16

A reduced set of 16 features (trained on mouse fMRI data), coded in C with wrappers for use in python, R, etc.

hctsa

autohctsa

Provides code for setting a hctsa feature-extraction job running on a computing cluster without leaving your local machine (with associated Julia helper code).

distributedhctsa

Provides MATLAB code for distributing hctsa calculations across nodes of a computing cluster (using pbs or slurm schedulers).

Candidate Feature Lab

A repository for testing new time-series analysis algorithms for redundancy (and assessing whether to include into hctsa).

hctsa-py

A work in progress to recode many hctsa time-series analysis features into native python code.

pyopy

This excellent repository allows users to run hctsa software from within python.

hctsaAnalysisPython

Some preliminary python code for analyzing the results of hctsa calculations.

Feature-based time-series packages developed by others

There is a list of python-based packages for time-series analysis here that is worth taking a look at, in addition to those packages highlighted below:

tsfresh

Native python time-series code to extract hundreds of time-series features, with in-built feature filtering. See the paper.

Kats

Kats is a toolkit for analysing time-series data in python, and includes basic feature extraction functionality.

theft

theft (Tools for Handling Extraction of Features from Time series) allows users to compute various open time-series features sets and contains associated tools for visualising and analysing the results.

TSFEL

TSFEL, 'Time Series Feature Extraction Library', is a python package with implementations of 60 simple time-series features (with unit tests).

tsflex

A flexible and efficient toolkit for flexible time-series processing & feature extraction, that makes minimal assumptions about sequential data. Includes support for a range of feature sets, including tsfresh, catch22, TSFEL, and Kats.

NeuroKit

Includes a wide range of useful signal processing tools (like power spectral densities, detrending and bandpass filtering, and empirical mode decomposition). It also includes estimation of complexity parameters (many entropies and correlation dimensions, see part of readme here) as well as detrended fluctuation analysis.

tscompdata

Makes available existing collections of time-series data for analysis.

tsfeatures

Includes implementations of a range of time-series features.

feasts

Provides a collection of tools for the analysis of tidy time-series data represented as a tsibble.

Other packages and resources

sktime

A unified framework for machine learning with time series.

Khiva

An open-source library of efficient algorithms to analyse time series using GPU and CPU.

pyunicorn

A python-based nonlinear time-series analysis and complex systems code package. See this publication.

tslearn

A python package for performing machine learning using time-series data, including loading datasets from the UCR/UAE repository.

TSFuse

A python package that can extract features from multivariate time series.

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