theft (version 0.8.2)

calculate_features: 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
)

Value

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

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

Author

Trent Henderson

Examples

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