rUnifRast,GRaster-method {fasterRaster} | R Documentation |
Create a raster with random values drawn from a uniform distribution
Description
rUnifRast()
creates a raster with values drawn from a uniform (flat) distribution.
Usage
## S4 method for signature 'GRaster'
rUnifRast(x, n = 1, low = 0, high = 1, seed = NULL)
Arguments
x |
A |
n |
A numeric integer: Number of rasters to generate. |
low , high |
Numeric: Minimum and maximum values from which to select. |
seed |
Numeric integer vector or |
Value
A GRaster
.
See Also
rNormRast()
, rSpatialDepRast()
, fractalRast()
, rWalkRast()
, GRASS manual page for tool r.random.surface
(see grassHelp("r.random.surface")
)
Examples
if (grassStarted()) {
# Setup
library(sf)
library(terra)
# Elevation raster
madElev <- fastData("madElev")
# Convert a SpatRaster to a GRaster:
elev <- fast(madElev)
### Create a raster with values drawn from a uniform distribution:
unif <- rUnifRast(elev)
plot(unif)
### Create a raster with values drawn from a normal distribution:
norms <- rNormRast(elev, n = 2, mu = c(5, 10), sigma = c(2, 1))
plot(norms)
hist(norms, bins = 100)
# Create a raster with random, seemingly normally-distributed values:
rand <- rSpatialDepRast(elev, dist = 1000)
plot(rand)
# Values appear normal on first inspection:
hist(rand)
# ... but actually are patterned:
hist(rand, bins = 100)
# Create a fractal raster:
fractal <- fractalRast(elev, n = 2, dimension = c(2.1, 2.8))
plot(fractal)
hist(fractal)
### Random walker rasters
# One random walker
walk <- rWalkRast(elev)
plot(walk)
# Random walker with self-avoidance:
walkAvoid <- rWalkRast(elev, steps = 1000, avoid = TRUE, seed = 1)
plot(walkAvoid)
# 10 random walkers:
walk10 <- rWalkRast(elev, n = 10)
plot(walk10)
# 10 random walkers starting in same place:
walkSame10 <- rWalkRast(elev, n = 10, sameStart = TRUE)
plot(walkSame10)
}
[Package fasterRaster version 8.4.1.0 Index]