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144 6 ⋅ software Using the vector is easy. The trivial usage [d pred] = shortest_paths(A,1); d(2) gives the wrong answer: Instead, use [d pred] = shortest_paths(As,1,struct(’edge_weight’,ws)); d(2) to find the correct distance using all the zero-weight edges: 6.3.7 Usage MatlabBGL has been used in over 10 publications (that we are aware of) and downloaded over 7,000 times. We highlight three of these publications. In Honey et al. [2007], the authors utilize the shortest path computations to analyze the functional connectivity of a macaque neocortex. Next, Lin et al. [2008] use the connected component, betweenness centrality, and cluster coefficients functions to study a network of co-authorship relationships in abstracts presented at the Society for Neuroscience. Third, and finally, Raman and Chandra [2008] use the shortest path routine to analyze a subset of the interactome network of M. tuberculosis. MatlabBGL continues to be a highly downloaded file from the Matlab central file exchange and we hope to continue improving it in the future. 6.4 gaimc The gaimc library implements a similar set of graph algorithms. It is written entirely in Matlab and the project is maintained at GitHub, http: //github.com/dgleich/gaimc. It follows the motivation of MatlabBGL closely and also uses the Matlab sparse matrix as its graph type. In the following example, we generate a random weighted graph and compute a minimum spanning tree: randn(’state’,0); rand(’state’,0); A=abs(sprandsym(10,0.2)); % symmetric random graph T = mst_prim(A); sum(sum(T))/2 % output the MST weight ans = 1 ans = 0PDF Image | Instagram Cheat Sheet
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