Tools for Handling Extraction of Features from Time series (theft)
Coming to CRAN soon… Stay posted!
You can install the development version of theft from GitHub using the
following:
devtools::install_github("hendersontrent/theft")theft is a software package for R that facilitates user-friendly
access to a structured analytical pipeline for the computation,
analysis, and visualisation of time-series features. The package
provides a single point of access to a large number of time-series
features from a range of existing R and Python packages and lets the
user specify which groups (or all) of the these features to calculate.
The packages which theft currently ‘steals’ features from include:
Note that Kats, tsfresh and tsfel are Python packages. The R
package reticulate is used to call Python code that uses these
packages and applies it within the broader tidy data philosophy
embodied by theft. At present, depending on the input time series,
theft provides access to >1300 features. Prior to using theft
(only if you want to use the Kats, tsfresh or tsfel feature sets -
the R-based sets will run fine) you should have a working Python
installation and download Kats using the instructions located
here, tsfresh
here or tsfel
here.
The package also contains a suite of tools for automatic processing of extracted feature vectors, low dimensional projections, data matrix visualisations, top feature and multivariate feature classification analyses, and various other statistical and graphical procedures.
An interactive web
application
has been built on top of theft which enables users to access most of
the functionality included in the package from within a web browser
without any code. The application automates the entire workflow included
in theft, converts all static graphics included in the package into
interactive visualisations, and enables downloads of feature
calculations. Note that since theft is an active development project,
not all functionality has been copied across to the webtool yet.
To cite package 'theft' in publications use:
Trent Henderson (2022). theft: Tools for Handling Extraction of
Features from Time series. R package version 0.3.8.9.
A BibTeX entry for LaTeX users is
@Manual{,
title = {theft: Tools for Handling Extraction of Features from Time series},
author = {Trent Henderson},
year = {2022},
note = {R package version 0.3.8.9},
}