44 lines
1.3 KiB
Matlab
44 lines
1.3 KiB
Matlab
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% Degree-preserving random rewiring.
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% Every rewiring decreases the assortativity (pearson coefficient).
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%
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% Note 1: There are rare cases of neutral rewiring (pearson coefficient stays the same within numerical error).
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% Note 2: Assume unweighted undirected graph.
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%
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% INPUTS: edge list, el and number of rewirings, k (integer)
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% OUTPUTS: rewired edge list
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%
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% Other routines used: degrees.m, edgeL2adj.m
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% GB: last updated, Sep 27 2012
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function el = rewireDisassort(el,k)
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[deg,~,~]=degrees(edgeL2adj(el));
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rew=0;
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while rew<k
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% pick two random edges
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ind = randi(length(el),1,2);
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edge1=el(ind(1),:); edge2=el(ind(2),:);
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if length(intersect(edge1(1:2),edge2(1:2)))>0; continue; end % the two edges cannot overlap
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nodes=[edge1(1) edge1(2) edge2(1) edge2(2)];
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[~,Y]=sort(deg(nodes));
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% connect nodes(Y(1))-nodes(Y(4)) and nodes(Y(2))-nodes(Y(3))
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if ismember([nodes(Y(1)),nodes(Y(4)),1],el,'rows') || ismember([nodes(Y(2)),nodes(Y(3)),1],el,'rows'); continue; end
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el(ind(1),:)=[nodes(Y(1)),nodes(Y(4)),1];
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el(ind(2),:)=[nodes(Y(2)),nodes(Y(3)),1];
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[~,inds1] = ismember([edge1(2),edge1(1),1],el,'rows');
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el(inds1,:)=[nodes(Y(4)),nodes(Y(1)),1];
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[~,inds2] = ismember([edge2(2),edge2(1),1],el,'rows');
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el(inds2,:)=[nodes(Y(3)),nodes(Y(2)),1];
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rew=rew+1;
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end
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