gcsm_tw: Composite similarity on temporal windows

In GCSM: Implements Generic Composite Similarity Measure

Description

Compute composite measures, GCSM or CMSC, on temporal windows.

Usage

cmsc_tw(
  xxx,
  yyy,
  rescale = FALSE,
  xmin = NA_real_,
  xmax = NA_real_,
  ymin = NA_real_,
  ymax = NA_real_,
  comp = "si"
)

cmsc_e1_tw(
  xxx,
  yyy,
  rescale = FALSE,
  xmin = NA_real_,
  xmax = NA_real_,
  ymin = NA_real_,
  ymax = NA_real_,
  comp = "si"
)

cmsc_e2_tw(
  xxx,
  yyy,
  rescale = FALSE,
  xmin = NA_real_,
  xmax = NA_real_,
  ymin = NA_real_,
  ymax = NA_real_,
  comp = "si"
)

gcsm_tw(
  xxx,
  yyy,
  rescale = FALSE,
  xmin = NA_real_,
  xmax = NA_real_,
  ymin = NA_real_,
  ymax = NA_real_,
  comp = "si"
)

Arguments

xxx	A 3-d array with the 3rd dimension representing time.
yyy	The other 3-d array.
rescale	Rescale or not before computation.
xmin, xmax, ymin, ymax	Normalization parameters. If NA, are calculated from the ranges of xxx and yyy, respectively. See Details.
comp	Variable to return. If "si", the composite measure, if "s1","s2" or "s3", the corresponding component.

Details

These functions slide the temporal window over space. Missing values are omitted. Normalization parameters are used to rescale xxx and yyy, and determine the global minimum (min) and maximum (max). If rescale is TRUE, xxx and yyy are rescaled to (xxx-xmin)/(xmax-xmin) and (yyy-ymin)/(ymax-ymin); and set min=0, max=1. If FALSE, min=min(xmin,ymin), max=max(xmax,ymax). OpenMP is used for parallel computing.

Value

A matrix.

Examples

x = array(runif(81), dim = c(3, 3, 9))

gcsm_tw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)
cmsc_tw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)

GCSM documentation built on March 27, 2021, 5:06 p.m.