| runifpoint {spatstat} | R Documentation |
Generate a random point pattern containing n independent uniform random points.
runifpoint(n, win=owin(c(0,1),c(0,1)), giveup=1000)
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. |
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:
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.
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.
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.
The simulated point pattern (an object of class "ppp").
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
ppp.object,
owin.object,
rpoispp,
rpoint
# 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))