Faster alternative for find and sort in MATLAB - matlab

Question

I am working on community detection with a genetic algorithm. Communities are represented in locus-based representation, that each index(gene) and it's value are in same community.
For example in the figure below, if the chromosome is (b) the communities will be (d)
So to extract communities from a chromosome, I need to iteratively find the indexes and values, to do this, I have written this code:
while (SumComms)~=nVar
j=find(Sol>0,1,'first');%find the first node which has not placed in any community
Com=[j,Sol(j)];%index of the node and it's value
Comsize=0;
while Comsize<numel(Com)
Comsize=numel(Com);
x=find(ismembc(Sol,sort([Com,Sol(Com)])));%Indexes which Com occure in Sol
Com=unique([Com,x,Sol(x)]);
end
Sol(Com)=0;
i=i+1;
SumComms=SumComms+numel(Com);
Communities{i}=Com;
end
But x=find(ismembc(Sol,sort([Com,Sol(Com)]))) is very time consuming in even mid-size networks. Do you know any faster way?

Answer 1

Here is a solution using logical vector. Instead of operation on indices we can define Com as a logical vector so operations on indices such as ismember can be reduced to indexing operations:
i=0;
SumComms=0;
nVar = 9;
Sol = [3 0 3 1 5 6 4 7 7]+1;
while SumComms ~= nVar
j=find(Sol>1,1,'first');
Com = false(1,nVar);
Com([j Sol(j)])=true;
Comsize=0;
sumcom = 2;
while Comsize<sumcom
Comsize=sum(Com);
Com(Sol(Com))=true;
Com = Com(Sol);
Com(Sol(Com))=true;
sumcom = sum(Com);
end
Sol(Com)=1;
i = i + 1;
SumComms=SumComms+sumcom;
Communities{i}=find(Com);
end
Result of a test in Octave shows that the proposed method is at least 10x faster than the original method .