| cmsc_tw {GCSM} | R Documentation |
Composite similarity on temporal windows
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 |
comp |
Variable to return. If |
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)