rWalkRast,GRaster-method {fasterRaster} | R Documentation |
Create raster representing one or more random walks
Description
This function creates a raster where the cell values represent the number of times one or more random "walkers" traverse the cell. If you simulate multiple random walkers, you can do computation in parallel, which can be controlled by allowing fasterRaster to use multiple cores and more memory using the "cores" and "memory" arguments in the faster()
function.
Usage
## S4 method for signature 'GRaster'
rWalkRast(
x,
n = 1,
steps = 1e+05,
directions = 8,
avoid = FALSE,
sameStart = FALSE,
seed = NULL,
check = TRUE
)
Arguments
x |
A |
n |
Numeric: Number of walkers. Default is 1. |
steps |
Numeric: Number of steps taken by each walker. Default is 100000. |
directions |
Either 4 or 8: Directions in which a walker can turn at any point. If 4, then walks are confined to north/south/east/west directions (Rook's case). If 8, then the cardinal and subcardinal directions are allowed (Queen's case). |
avoid |
Logical: If |
sameStart |
Logical: If |
seed |
Integer or |
check |
Logical: If |
Details
This function needs the GRASS addon r.random.walk
. If it is not installed, it will try to install it.#'
Value
A GRaster
with cell values representing the number of times one or more walkers traversed the cell.
See Also
rNormRast()
, rUnifRast()
, rSpatialDepRast()
, fractalRast()
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)
}