calculate_features: Compute features on an input time series dataset

In theft: Tools for Handling Extraction of Features from Time Series

Compute features on an input time series dataset

Description

Compute features on an input time series dataset

Usage

calculate_features(
  data,
  feature_set = c("catch22", "feasts", "tsfeatures", "kats", "tsfresh", "tsfel",
    "quantiles", "moments"),
  features = NULL,
  catch24 = FALSE,
  tsfresh_cleanup = FALSE,
  use_compengine = FALSE,
  seed = 123,
  z_score = FALSE,
  n_jobs = 0,
  warn = TRUE
)

Arguments

data	tbl_ts containing the time series data
feature_set	character or vector of character denoting the set of time-series features to calculate. Can be one of "catch22", "feasts", "tsfeatures", "tsfresh", "tsfel", "kats", "quantiles", and or "moments"
features	named list containing a set of user-supplied functions to calculate on data. Each function should take a single argument which is the time series. Defaults to NULL for no manually-specified features. Each list entry must have a name as calculate_features looks for these to name the features. If you don't want to use the existing feature sets and only compute those passed to features, set feature_set = NULL
catch24	Boolean specifying whether to compute catch24 in addition to catch22 if catch22 is one of the feature sets selected. Defaults to FALSE
tsfresh_cleanup	Boolean specifying whether to use the in-built tsfresh relevant feature filter or not. Defaults to FALSE
use_compengine	Boolean specifying whether to use the "compengine" features in tsfeatures. Defaults to FALSE to provide immense computational efficiency benefits
seed	integer denoting a fixed number for R's random number generator to ensure reproducibility. Defaults to 123
z_score	Boolean specifying whether to z-score the time-series before computing features. Defaults to FALSE
n_jobs	integer denoting the number of parallel processes to use if "tsfresh" or "tsfel" are specified in "feature_set". Defaults to 0 for no parallelisation
warn	Boolean specifying whether to produce warnings from feature set packages. Defaults to TRUE

Value

object of class feature_calculations that contains the summary statistics for each feature

Author(s)

Trent Henderson

Examples

featMat <- calculate_features(data = simData, 
  feature_set = "catch22")

theft documentation built on Aug. 8, 2025, 7:27 p.m.