【正文】
ion 29Aug2000% % to node 39。% D = |s| x |t| matrix of shortest path distances from 39。 = [] (default), paths to all nodes% s = FROM node indices% A(i,j) = NaN = Arc (i,j) exists with 0 weight)% = Arc (i,j) does not exist。 to nodes 39。 %To target nodesD_Nodal s = s(:)。 s = (1:N)39。N = length(gMatrix)。 [D_Global, D_Nodal] = CCM_AvgShortestPath(G)。nograph39。第二個文件: error(39。 = g3./c3。c3 = D.*(D1) 2*diag(A^2)。D(g3 == 0) = inf。g3 = diag(G^3)/2。 %adjacency matrixALL39。 %3cycles no exist,let Cp=0%D = gMatrix + gMatrix39。 %case 39。 total outsetDIRECTED39。%WEIGHTED39。end n_weight Num = sum(n_weight)。% Weighted network arithmetic mean end if(Num 1), = gMatrix(neighbor, neighbor)。 temp = sum(neighbor)。for i = 1:NBINARY39。%Clear selfedgesCp_Nodal = zeros(N,1)。 Networks. Social Networks31(2).% See also CCM_Transitivity% Written by Yong Liu, Oct,2007% Center for Computational Medicine (CCM),% National Laboratory of Pattern Recognition (NLPR),% Institute of Automation,Chinese Academy of Sciences (IACAS), China.% Revise by Hu Yong, Nov, 2010% Email: % based on Matlab 2006a% $Revision: , Copywrite (c) 2007error(nargchk(1,2,nargin,39。 [1] Barrat et al. (2004) The architecture of the plex weighted networks. % 3) 39。t satisfy with that as % 1) one node have vaule 0, while which only has a neighbour or none.% G = CCM_TestGraph1(39。 clustering coefficients for all nodes Cp_Nodal and average clustering%(default).% Usage:%,39。 type of graph: 39。 adjacency matrix% gMatrixweighted39。all39。% as nonvacuous: jik and kij,if don39。s BCT toolkit.% Refer:%