33 lines
1.1 KiB
Matlab
33 lines
1.1 KiB
Matlab
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% Calculating the Pearson coefficient for a degree sequence.
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% Source: "Assortative Mixing in Networks", M.E.J. Newman, Phys Rev Let 2002
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%
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% INPUTs: M - (adjacency) matrix, nxn (square)
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% OUTPUTs: r - Pearson coefficient
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%
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% Other routines used: degrees.m, numEdges.m, adj2inc.m
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% See also pearsonW.m
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% GB: last updated, October 1, 2012
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function r = pearson(M)
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[degs,~,~] = degrees(M); % get the total degree sequence
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m = numEdges(M); % number of edges in M
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inc = adj2inc(M); % get incidence matrix for convience
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% j,k - remaining degrees of adjacent nodes for a given edge
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% sumjk - sum of all products jk
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% sumjplusk - sum of all sums j+k
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% sumj2plusk2 - sum of all sums of squares j^2+k^2
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% compute sumjk, sumjplusk, sumj2plusk2
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sumjk = 0; sumjplusk = 0; sumj2plusk2 = 0;
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for i=1:m
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[v] = find(inc(:,i)==1);
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j = degs(v(1))-1; k = degs(v(2))-1; % remaining degrees of 2 end-nodes
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sumjk = sumjk + j*k;
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sumjplusk = sumjplusk + 0.5*(j+k);
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sumj2plusk2 = sumj2plusk2 + 0.5*(j^2+k^2);
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end
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% Pearson coefficient formula
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r = (sumjk - sumjplusk^2/m)/(sumj2plusk2-sumjplusk^2/m);
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