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# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Function:
# fssi20() and fssi30() functions calculates the relative
# frequency distribution of isotropic 2D & 3D clusters
# with von Neumann neighborhood.
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Arguments:
# n - sample size;
# x - linear dimension of the percolation lattice;
# p - relative fraction of accessible sites
# (occupation probability) for percolation lattice;
# 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 sampling frequencies for sites of
# the percolation lattice.
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
fssi20 <- function(n=1000,
x=33, p=0.592746,
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 + (ssi20(x, p, set, all, shape) > 1)
return(rfq/n)
}
fssi30 <- function(n=1000,
x=33, p=0.311608,
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 + (ssi30(x, p, set, all, shape) > 1)
return(rfq/n)
}
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