Percolation/Mean cluster density: Difference between revisions

</pre>

=={{header|zkl}}==

{{trans|C}}

<lang zkl>const X=-1; // the sentinal that marks an untouched cell

var C,N,NN,P;

fcn createC(n,p){

N,P=n,p; NN=N*N;

C=NN.pump(List.createLong(NN),0); // vector of ints

foreach n in (NN){ C[n]=X*(Float.random(1)<=P) } // X is the sentinal

}

fcn showCluster{

alpha:="-ABCDEFGHIJKLMNOPQRSTUVWXYZ" "abcdefghijklmnopqrstuvwxyz";

foreach n in ([0..NN,N]){ C[n,N].pump(String,alpha.get).println() }

}

fcn countClusters{

clusters:=0;

foreach n in (NN){

if(X!=C[n]) continue;

fcn(n,v){

if((0<=n<NN) and C[n]==X){

C[n]=v;

self.fcn(n-N,v); self.fcn(n-1,v); self.fcn(n+1,v); self.fcn(n+N,v);

}

}(n,clusters+=1);

}

clusters

}

fcn tests(N,n,p){

k:=0.0;

foreach z in (n){ createC(N,p); k+=countClusters().toFloat()/NN; }

k/n

}</lang>

<lang zkl>createC(15,0.5);

println("width=%d, p=%.1f, %d clusters:".fmt(N,P,countClusters()));

showCluster();

println("p=0.5, 5 iterations:");

w:=4; do(6){ println("%5d %9.6f".fmt(w,tests(w, 5, 0.5))); w*=4; }</lang>

{{out}}

<pre>

width=15, p=0.5, 16 clusters:

-AAA-BB-BBB---C

------BBBB--D--

E---F---BB--DD-

EE----G-BB---DD

--H-I--J--J--DD

-K--I--JJ-J--D-

-K--I--JJJJ-L--

KK-III-------MM

-K-I--I--NN-I--

I-IIIII-NNN-III

I-II--I-N-N-II-

III-III--NNN-II

I-II-II-O---I--

I-I-IIII-PP-III

I-II--I---P--II

p=0.5, 5 iterations:

4 0.062500

16 0.070312

64 0.067627

256 0.067078

1024 0.065834

4096 0.065771