Random graphs with fixed numbers of neighbours
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In connection with Le Monde puzzle #46, I eventually managed to write an R program that generates graphs with a given number n of nodes and a given number k of edges leaving each of those nodes. (My early attempt was simply too myopic to achieve any level of success when n was larger than 10!) Here is the core of the R code:
A=42 #number of nodes L=13 #number of edges ApL=A+L if ((A*L)%%2==1){ print("impossible graph") }else{ con=matrix(0,A,A) diag(con)=A #eliminate self-connection suma=apply(con,1,sum)-A while (min(suma)<L){ if (sum(suma<L)==1){ #bad news: no correspondence! #go back: con=aclrtr(con,L) diag(con)=A suma=apply(con,1,sum)-A }else{ j=sample((1:A)[suma<L],1) slots=(1:A)[con[j,]==0] #remaining connections if (length(slots)==1){ vali=slots if (sum(con[vali,]>ApL-1)) vali=NULL }else{ vali=slots[apply(con[slots,],1,sum)<ApL] } if (length(vali)==0){ con=aclrtr(con,L) diag(con)=A suma=apply(con,1,sum)-A }else{ if (length(vali)==1){ k=vali[1] }else{ k=sample(slots[apply(con[slots,],1,sum)<ApL],1) } con[k,j]=con[j,k]=1 suma=apply(con,1,sum)-A }}}}
and it uses a sort of annealed backward step to avoid simulating a complete new collection of neighbours when reaching culs-de-sac….
aclrtr=function(con,L){ #removes a random number of links among the nodes with L links A=dim(con)[1] ApL=A+L while (max(apply(con,1,sum))==ApL){ don=sample(1:(L-1),1) if (sum(apply(con,1,sum)==ApL)==1){ i=(1:A)[apply(con,1,sum)==ApL] }else{ i=sample((1:A)[apply(con,1,sum)==ApL],1) } off=sample((1:A)[con[i,]==1],don) con[i,off]=0 con[off,i]=0 } con }
There is nothing fancy or optimised about this code so I figure there are much better versions to be found elsewhere…
Ps-As noticed before, sample does not work on a set of length one, which is a bug in my opinion…. Instead, sample(4.5,1) returns a random permutation of (1,2,3,4).
> sample(4.5)
[1] 4 3 1 2
Filed under: R, Statistics Tagged: edges, graphs, Le Monde, nodes, simulation
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