This is a wrapper for the RFsimulate
function in the RandomFields
package. The main addition is the speedup
argument which allows
for faster map generation. A speedup
of 1 is normal and will get
progressively faster as the number increases, at the expense of coarser
pixel resolution of the pattern generated.
gaussMap(
x,
scale = 10,
var = 1,
speedup = 1,
method = "RMexp",
alpha = 1,
inMemory = FALSE,
...
)
A spatial object (e.g., a RasterLayer
).
The spatial scale in map units of the Gaussian pattern.
Spatial variance.
An numeric value indicating how much faster than 'normal' to generate maps. It may be necessary to give a value larger than 1 for large maps. Default is 1.
The type of model used to produce the Gaussian pattern.
Should be one of "RMgauss"
(Gaussian covariance model),
"RMstable"
(the stable powered exponential model),
or the default, "RMexp"
(exponential covariance model).
A required parameter of the "RMstable"
model.
Should be in the interval [0,2]
to provide a valid covariance function.
Default is 1.
Should the RasterLayer be forced to be in memory?
Default FALSE
.
Additional arguments to raster
.
A raster map with same extent as x
, with a Gaussian random pattern.
RFsimulate
and extent()
if (FALSE) {
if (require(RandomFields)) {
library(raster)
nx <- ny <- 100L
r <- raster(nrows = ny, ncols = nx, xmn = -nx/2, xmx = nx/2, ymn = -ny/2, ymx = ny/2)
speedup <- max(1, nx/5e2)
map1 <- gaussMap(r, scale = 300, var = 0.03, speedup = speedup, inMemory = TRUE)
if (interactive()) Plot(map1)
# with non-default method
map1 <- gaussMap(r, scale = 300, var = 0.03, method = "RMgauss")
}
}