runifpoint

From spatstat v1.55-1 by Adrian Baddeley

Generate N Uniform Random Points

Generate a random point pattern containing \(n\) independent uniform random points.

Keywords: spatial, datagen

Usage

runifpoint(n, win=owin(c(0,1),c(0,1)), giveup=1000, warn=TRUE, …,
            nsim=1, drop=TRUE, ex=NULL)

Arguments

n: Number of points.
win: Window in which to simulate the pattern. An object of class "owin" or something acceptable to as.owin.
giveup: Number of attempts in the rejection method after which the algorithm should stop trying to generate new points.
warn: Logical. Whether to issue a warning if n is very large. See Details.
…: Ignored.
nsim: Number of simulated realisations to be generated.
drop: Logical. If nsim=1 and drop=TRUE (the default), the result will be a point pattern, rather than a list containing a point pattern.
ex: Optional. A point pattern to use as the example. If ex is given and n and win are missing, then n and win will be calculated from the point pattern ex.

Details

This function generates n independent random points, uniformly distributed in the window win. (For nonuniform distributions, see rpoint.)

The algorithm depends on the type of window, as follows:

If win is a rectangle then \(n\) independent random points, uniformly distributed in the rectangle, are generated by assigning uniform random values to their cartesian coordinates.
If win is a binary image mask, then a random sequence of pixels is selected (using sample) with equal probabilities. Then for each pixel in the sequence we generate a uniformly distributed random point in that pixel.
If win is a polygonal window, the algorithm uses the rejection method. It finds a rectangle enclosing the window, generates points in this rectangle, and tests whether they fall in the desired window. It gives up when giveup * n tests have been performed without yielding n successes.

The algorithm for binary image masks is faster than the rejection method but involves discretisation.

If warn=TRUE, then a warning will be issued if n is very large. The threshold is spatstat.options("huge.npoints"). This warning has no consequences, but it helps to trap a number of common errors.

Value

A point pattern (an object of class "ppp") if nsim=1, or a list of point patterns if nsim > 1.

Examples

# NOT RUN {
 # 100 random points in the unit square
 pp <- runifpoint(100)
 # irregular window
 data(letterR)
 # polygonal
 pp <- runifpoint(100, letterR)
 # binary image mask
 pp <- runifpoint(100, as.mask(letterR))
 ##
 # randomising an existing point pattern
 runifpoint(npoints(cells), win=Window(cells))
 runifpoint(ex=cells)
# }

Documentation reproduced from package spatstat, version 1.55-1, License: GPL (>= 2)

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