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- function C=clustering_coef_wu(W)
- %CLUSTERING_COEF_WU Clustering coefficient
- %
- % C = clustering_coef_wu(W);
- %
- % The weighted clustering coefficient is the average "intensity"
- % (geometric mean) of all triangles associated with each node.
- %
- % Input: W, weighted undirected connection matrix
- % (all weights must be between 0 and 1)
- %
- % Output: C, clustering coefficient vector
- %
- % Note: All weights must be between 0 and 1.
- % This may be achieved using the weight_conversion.m function,
- % W_nrm = weight_conversion(W, 'normalize');
- %
- % Reference: Onnela et al. (2005) Phys Rev E 71:065103
- %
- %
- % Mika Rubinov, UNSW/U Cambridge, 2007-2015
- % Modification history:
- % 2007: original
- % 2015: expanded documentation
- K=sum(W~=0,2);
- cyc3=diag((W.^(1/3))^3);
- K(cyc3==0)=inf; %if no 3-cycles exist, make C=0 (via K=inf)
- C=cyc3./(K.*(K-1)); %clustering coefficient
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