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Multivariate STOMP Algorithm

Source: R/mstomp.R
mstomp.Rd

Computes the Matrix Profile and Profile Index for Multivariate Time Series.

Usage

mstomp(
  data,
  window_size,
  exclusion_zone = 0.5,
  must_dim = NULL,
  exc_dim = NULL,
  n_workers = 1L,
  progress = TRUE
)

Arguments

data

a matrix of numeric, where each column is a time series. Accepts vector, list and data.frame too.

window_size

an int with the size of the sliding window.

exclusion_zone

a numeric. Size of the exclusion zone, based on window size (default is 0.5).

must_dim

an int or vector of which dimensions to forcibly include (default is NULL).

exc_dim

an int or vector of which dimensions to exclude (default is NULL).

n_workers

an int. Number of workers for parallel execution (default is 1). For parallel execution across processes, prefer a PSOCK cluster and use n_workers = 1 within each worker. See matrixprofiler for fork limitations.

progress

a logical. If TRUE will show a progress bar. (Default is TRUE).

Value

Returns a list with the matrix profile matrix_profile, profile index profile_index, left and right matrix profiles left_matrix_profile, right_matrix_profile and profile indices left_profile_index, right_profile_index, window size w, number of dimensions n_dim, exclusion zone ez, must dimensions must and excluded dimensions exc.

References

  • Yeh CM, Kavantzas N, Keogh E. Matrix Profile VI : Meaningful Multidimensional Motif Discovery.

  • Zhu Y, Imamura M, Nikovski D, Keogh E. Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining. Knowl Inf Syst. 2018 Jun 2;1-27.

Website: https://sites.google.com/view/mstamp/

Website: http://www.cs.ucr.edu/~eamonn/MatrixProfile.html

See also

Other matrix profile computations: stamp()

Examples

mp <- mstomp(motifs_discords_small, 50, progress = FALSE)