ssi2d {SPSL} | R Documentation |
Site cluster on Square Isotropic 2D lattice with (1,d)-neighborhood
Description
ssi2d()
function provides sites labeling of the isotropic cluster on 2D square lattice with Moore (1,d)-neighborhood.
Usage
ssi2d(x=33, p0=0.5, p1=p0/2,
set=(x^2+1)/2, all=TRUE, shape=c(1,1))
Arguments
x |
a linear dimension of 2D square percolation lattice. |
p0 |
a relative fraction |
p1 |
|
set |
a vector of linear indexes of a starting sites subset. |
all |
logical; if |
shape |
a vector with two shape parameters of beta-distributed random variables, weighting the percolation lattice sites. |
Details
The percolation is simulated on 2D square lattice with uniformly weighted sites acc
and the constant parameters p0
and p1
.
The isotropic cluster is formed from the accessible sites connected with initial sites subset set
.
To form the cluster the condition acc[set+eN]<pN
is iteratively tested for sites of the Moore (1,d)-neighborhood eN
for the current cluster perimeter set
, where eN
is equal to e0
or e1
vector; pN
is equal to p0
or p1
value.
Moore (1,d)-neighborhood on 2D square lattice consists of sites, at least one coordinate of which is different from the current site by one: e=c(e0,e1)
, where
e0=c(-1,
1,
-x,
x,
-x^2,
x^2)
;
e1=colSums(matrix(e0[c(1,3,
2,3,
1,4,
2,4)], nrow=2))
.
Minkowski distance between sites a
and b
depends on the exponent d
:
rhoM <- function(a, b, d=1)
if (is.infinite(d)) return(apply(abs(b-a), 2, max))
else return(apply(abs(b-a)^d, 2, sum)^(1/d))
.
Minkowski distance for sites from e1
subset with the exponent d=1
is equal to rhoMe1=2
.
Forming cluster ends with the exhaustion of accessible sites in Moore (1,d)-neighborhood of the current cluster perimeter.
Value
acc |
an accessibility matrix for 2D square percolation lattice: |
Author(s)
Pavel V. Moskalev <moskalefff@gmail.com>
References
[1] Moskalev, P.V. Percolation modeling of porous structures. Moscow: URSS, 2018. 240 pp; in Russian.
[2] Moskalev, P.V. (2014) Estimates of threshold and strength of percolation clusters on square lattices with (1,d)-neighborhood. Computer Research and Modeling, Vol.6, No.3, pp.405–414; in Russian.
See Also
fssi2d, ssi3d, ssi20, ssi30, ssa2d, ssa3d
Examples
set.seed(20120507)
x <- y <- seq(33)
image(x, y, ssi2d(), zlim=c(0,2),
main="Isotropic (1,1)-cluster")
abline(h=17, lty=2); abline(v=17, lty=2)