Generates a pattern of dummy points in a window, given a data point pattern. The dummy points lie on the radii of circles emanating from each data point.
spokes(x, y, nrad = 3, nper = 3, fctr = 1.5, Mdefault = 1)Vector of \(x\) coordinates of data points, or a list
with components x and y, or a point pattern
(an object of class ppp).
Vector of \(y\) coordinates of data points. Ignored
unless x is a vector.
Number of radii emanating from each data point.
Number of dummy points per radius.
Scale factor.
Length of largest spoke radius is fctr * M
where M is the mean nearest neighbour distance
for the data points.
Value of M to be used if x has length 1.
If argument x is a point pattern, a point pattern with
window equal to that of x. Otherwise a list with two
components x and y. In either case the components
x and y of the value are numeric vectors giving
the coordinates of the dummy points.
This function is useful in creating dummy points for quadrature
schemes (see quadscheme).
Given the data points, the function creates a collection of
nrad * nper * length(x) dummy points.
Around each data point (x[i],y[i]) there are
nrad * nper dummy points, lying on nrad radii
emanating from (x[i],y[i]), with nper dummy points
equally spaced along each radius.
The (equal) spacing of dummy points along each radius is
controlled by the factor fctr.
The distance from a data point to the furthest of its associated
dummy points is fctr * M
where M is the mean nearest neighbour distance
for the data points.
If there is only one data point the nearest neighbour distance
is infinite, so the value Mdefault will be used in place
of M.
If x is a point pattern, then the value returned is
also a point pattern, which is clipped to the window
of x. Hence there may be fewer than
nrad * nper * length(x) dummy points in the pattern
returned.
quad.object,
quadscheme,
inside.owin,
gridcentres,
stratrand
# NOT RUN {
dat <- runifrect(10)
dum <- spokes(dat$x, dat$y, 5, 3, 0.7)
plot(dum)
Q <- quadscheme(dat, dum, method="dirichlet")
plot(Q, tiles=TRUE)
# }
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