R package for the calculation of 22 CAnonical Time-series CHaracteristics. The package is an efficient implementation that calculates time-series features coded in C.
You can install the stable version of Rcatch22 from CRAN using the
following:
install.packages("Rcatch22")You can install the development version of Rcatch22 from GitHub using
the following:
devtools::install_github("hendersontrent/Rcatch22")You might also be interested in a related R package called
theft (Tools for Handling
Extraction of Features from Time series) which provides standardised
access to Rcatch22 and 5 other feature sets (including 3 feature sets
from Python libraries) for a total of ~1,200 features. theft also
includes extensive functionality for processing and analysing
time-series features, including automatic time-series classification,
top performing feature identification, and a range of statistical data
visualisations.
Please open the included vignette within an R environment or visit the
detailed Rcatch22
Wiki for information
and tutorials.
With features coded in C, Rcatch22 is highly computationally
efficient, scaling nearly linearly with time-series size. Computation
time in seconds for a range of time series lengths is presented below.
An option to include the mean and standard deviation as features in
addition to catch22 is available through setting the catch24
argument to TRUE:
features <- catch22_all(x, catch24 = TRUE)A DOI is provided at the top of this README. Alternatively, the package can be cited using the following:
To cite package 'Rcatch22' in publications use:
Trent Henderson (2022). Rcatch22: Calculation of 22 CAnonical
Time-Series CHaracteristics. R package version 0.2.2.
A BibTeX entry for LaTeX users is
@Manual{,
title = {Rcatch22: Calculation of 22 CAnonical Time-Series CHaracteristics},
author = {Trent Henderson},
year = {2022},
note = {R package version 0.2.2},
}
Please also cite the original catch22 paper: