contrast: Contrast Profile Computation

In matrixprofiler: Matrix Profile for R

Contrast Profile Computation

Description

Computes the contrast profile of two (classes of) time series.

Usage

contrast(
  negative_data,
  positive_data,
  window_size,
  positive_matrix = NULL,
  exclusion_zone = 0.5,
  distance = c("euclidean", "pearson"),
  n_workers = 1L,
  progress = TRUE
)

Arguments

negative_data	Required. Any 1-dimension series of numbers (matrix, vector, ts etc.) where the pattern is not present
positive_data	Required. Any 1-dimension series of numbers (matrix, vector, ts etc.) where the pattern is present
window_size	Required. An integer defining the rolling window size.
positive_matrix	Optional. A precomputed self-similar matrix profile of the positive data.
exclusion_zone	A numeric. Defines the size of the area around the rolling window that will be ignored to avoid trivial matches. Default is 0.5, i.e., half of the window_size.
distance	A string. Currently accepts euclidean and pearson. Defaults to euclidean.
n_workers	An integer. The number of threads using for computing. Defaults to 1.
progress	A logical. If TRUE (the default) will show a progress bar. Useful for long computations.

Details

Constrast Profile

This algorithm returns the contrast profile of two time series, which shows the position of patters that are similar in the positive data, but at the same time very dissimilar in the negative data. In other words, this means that such a pattern represents well positive data and may be taken as a "signature" of that class. More information can be found in the references.

Value

Returns a list with the contrast_profile, plato, plato_nn, plato_idx, plato_nn_idx, w, ez, euclidean values

References

• R. Mercer, S. Alaee, A. Abdoli, S. Singh, A. Murillo and E. Keogh, "Matrix Profile XXIII: Contrast Profile: A Novel Time Series Primitive that Allows Real World Classification," 2021 IEEE International Conference on Data Mining (ICDM), 2021, pp. 1240-1245, doi: 10.1109/ICDM51629.2021.00151.

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

Examples

cp <- contrast(motifs_discords_small, rev(motifs_discords_small), 50)

matrixprofiler documentation built on Feb. 16, 2023, 5:57 p.m.