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142 6 ⋅ software • edge_not_relaxed(ei,u,v) • finish_vertex(u) Rather than implementing 7 functions ourselves, we define two helper func- tions. There is one helper that returns a vertex visitor and one helper than returns an edge visitor: vertex_vis_print_func = @(str) @(u) ... fprintf(’%s called on %s\n’, str, char(labels{u})); edge_vis_print_func = @(str) @(ei,u,v) ... fprintf(’%s called on (%s,%s)\n’, str, char(labels{u}), char(labels{v})); We are almost done. We just have to setup the visitor structure to pass to the dijkstra_sp call: vis = struct(); vis.initialize_vertex = vertex_vis_print_func(’initialize_vertex’); vis.discover_vertex = vertex_vis_print_func(’discover_vertex’); vis.examine_vertex = vertex_vis_print_func(’examine_vertex’); vis.finish_vertex = vertex_vis_print_func(’finish_vertex’); vis.examine_edge = edge_vis_print_func(’examine_edge’); vis.edge_relaxed = edge_vis_print_func(’edge_relaxed’); vis.edge_not_relaxed = edge_vis_print_func(’edge_not_relaxed’); With the visitor set up, all that remains is to call the function: dijkstra_sp(A,1,struct(’visitor’, vis)); stopping an algorithm early Atanypoint,ifavisitorfunction returns a zero value, the algorithm halts. This behavior may be desirable. Consider the following example with astar_search: load graphs/bgl_cities.mat goal = 11; % Binghamton start = 9; % Buffalo % Use the Euclidean distance to the goal as the heuristic h = @(u) norm(xy(u,:) - xy(goal,:)); % Setup a routine to stop when we find the goal ev = @(u) (u ≠ goal); [d pred f] = astar_search(A, start, h, ... struct(’visitor’, struct(’examine_vertex’, ev))); The examine_vertex function returns 0 when the vertex is a targeted vertex. In this example, we want to find the shortest path between Binghamton and Buffalo. Once we find a shortest path to Buffalo, we can halt the algorithm! discover_vertex called on s examine_vertex called on s examine_edge called on (s,u) edge_relaxed called on (s,u) discover_vertex called on u ...PDF Image | Instagram Cheat Sheet
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