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136 6 ⋅ software in various ways). Most of the algorithms wrapped in MatlabBGL do not change the graph; thus we focus on the access concepts. For example, the strong_components BGL function requires a graph type that supports the VertexListGraph and IncidenceGraph concepts. These con- cepts allow the algorithm to iterate over all vertices in the graph and access the out-edges for an arbitrary vertex. This access to the graph suffices to implement Tarjan’s algorithm for strongly connected components [Tarjan, 1972]. The other access concepts are EdgeListGraph BidirectionalGraph AdjacencyGraph iterate over the edges of the graph access in-edges to an arbitrary vertex, and access adjacent (out-edge connected) ver- tices to an arbitrary vertex. Most algorithms are like strong_components and require only the VertexList- Graph and IncidenceGraph concepts. Two notable exceptions are maximum flow (push_relabel_max_flow, kolmogorov_max_flow), and planar graph triangulation (make_maximal_planar). In this document, we focus on the common cases and leave the exceptions to the source code documentation and help files of MatlabBGL. 6.3.2 Matlab and Boost graph library interface Before describing the interface, we reiterate one main point of MatlabBGL. To integrate cleanly with Matlab, MatlabBGL uses the Matlab sparse matrix type as the graph type. Thus, the goal of the interface between Matlab and the Boost graph library is to take a Matlab sparse matrix data structure and view it as a C++ type that implements the VertexListGraph and IncidenceGraph concepts. (Our actual implementation also supports the EdgeListGraph and AdjacencyGraph concepts.) With such an interface, we can access the majority of graph analysis algorithms in the Boost graph library. What is lost from the BGL is largely irrelevant to MatlabBGL. There is no need for the copy_graph function from Boost, for example. Next, figure 6.2 shows the high level architecture of MatlabBGL. There are four main components: m-files, mex-files, libmbgl, and BGL functions. Let’s illustrate a typical call to a MatlabBGL function: dfs for a depth-first search through the graph. First, the dfs.m file (an M code) receives the sparse matrix representation of the graph and the identifier of a vertex that originates the search. It per- forms some basic parameter checking on the data, transposes the matrix toPDF Image | Instagram Cheat Sheet
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