Random raster
Create a random raster or raster stack using specified distribution
random.raster(
r = NULL,
n.row = 50,
n.col = 50,
n.layers = 1,
x = seq(1, 10),
min = 0,
max = 1,
mean = 0,
sd = 1,
p = 0.5,
s = 1.5,
distribution = c("random", "normal", "seq", "binominal", "gaussian")
)r |
Optional existing raster defining nrow/ncol |
n.row |
Number of rows |
n.col |
Number of columns |
n.layers |
Number of layers in resulting raster stack |
x |
A vector of values to sample if distribution is "sample" |
min |
Minimum value of raster |
max |
Maximum value of raster |
mean |
Mean of centered distribution |
sd |
Standard deviation of centered distribution |
p |
p-value for binominal distribution |
s |
sigma value for Gaussian distribution |
distribution |
Available distributions, c("random", "normal", "seq", "binominal", "gaussian", "sample") |
Options for distributions are for random, normal, seq, binominal, gaussian and sample raster(s)
RasterLayer or RasterStack object with random rasters
Jeffrey S. Evans <jeffrey_evans@tnc.org>
library(raster)
# Using existing raster to create random binominal
r <- raster(system.file("external/rlogo.grd", package="raster"))
r <- random.raster(r, distribution="binominal")
# default; random, nrows=50, ncols=50, nlayers=1
rr <- random.raster(n.layer=5)
# specified; binominal, nrows=20, ncols=20, nlayers=5
rr <- random.raster(n.layer=5, n.col=20, n.row=20,
distribution="binominal")
# specified; gaussian, nrows=50, ncols=50, nlayers=1
rr <- random.raster(n.col=50, n.row=50, s=8,
distribution="gaussian")
# specified; sample, nrows=50, ncols=50, nlayers=1
rr <- random.raster(n.layer=1, x=c(2,6,10,15), distribution="sample" )
freq(rr)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.