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, inMemory = FALSE, ...)

## Arguments

- x
A spatial object (e.g., a `RasterLayer`

).

- scale
The spatial scale in map units of the Gaussian pattern.

- var
Spatial variance.

- speedup
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.

- inMemory
Should the RasterLayer be forced to be in memory?
Default `FALSE`

.

- ...
Additional arguments to `raster`

.

## Value

A raster map with same extent as `x`

, with a Gaussian random pattern.

## See also

`RFsimulate`

and `extent`

## Examples

## Not run: ------------------------------------
# library(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)
# Plot(map1)
## ---------------------------------------------