Nothing
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# Function:
# fssi2d() and fssi3d() functions calculates the relative
# frequency distribution of isotropic 2D & 3D clusters
# with Moore d-neighborhood.
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# Arguments:
# n - sample size;
# x - linear dimension of the percolation lattice;
# p0 - relative fraction of accessible sites
# (occupation probability) for percolation lattice;
# p1, p2 - p1 value, weighted by 2D & 3D d-neighborhood;
# set - vector of linear indexes of starting sites subset;
# all - trigger "Do we mark all starting sites or only accessible?";
# shape - vector of shape parameters of beta-distributed random variables,
# weighting the percolation lattice sites.
# Value:
# rfq - matrix of relative frequencies for sites of the percolation lattice.
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
fssi2d <- function(n=1000,
x=33, p0=0.5, p1=p0/2,
set=(x^2+1)/2, all=TRUE,
shape=c(1,1)) {
rfq <- array(0, dim=rep(x, times=2))
for (i in seq(n))
rfq <- rfq + (ssi2d(x, p0, p1, set, all, shape) > 1)
return(rfq/n)
}
fssi3d <- function(n=1000,
x=33, p0=0.2, p1=p0/2, p2=p0/3,
set=(x^3+1)/2, all=TRUE,
shape=c(1,1)) {
rfq <- array(0, dim=rep(x, times=3))
for (i in seq(n))
rfq <- rfq + (ssi3d(x, p0, p1, p2, set, all, shape) > 1)
return(rfq/n)
}
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