PNC k shortest simple path (for directed graphs) #40284
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…o this implementation)
src/sage/graphs/path_enumeration.pyx
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| G.delete_edges(G.incoming_edges(source, labels=False)) | ||
| G.delete_edges(G.outgoing_edges(target, labels=False)) | ||
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| if weight_function is not None: |
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this is done by the call to _get_weight_function. No need to duplicate.
src/sage/graphs/path_enumeration.pyx
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| if self.has_loops() or self.allows_multiple_edges(): | ||
| G = self.to_simple(to_undirected=False, keep_label='min', immutable=False) | ||
| else: | ||
| G = self.copy() |
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to be on the safe side, use self.copy(immutable=False)
src/sage/graphs/path_enumeration.pyx
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| reverse_graph = G.reverse() | ||
| dist, successor = shortest_paths(reverse_graph, target, weight_function=reverse_weight_function, | ||
| algorithm='Dijkstra_Boost') | ||
| cdef set unnecessary_vertices = set(G) - set(dist) # no path to target |
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always add 2 spaces before a comment at the end of a line, so set(list) # vertices with no path to target
src/sage/graphs/path_enumeration.pyx
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| # ancestor_idx_dict[v] := the first vertex reachable by edges of | ||
| # first shortest path tree from v | ||
| ancestor_idx_dict = dict() |
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ancestor_idx_dict = {v: i for I, v in enumerate(path)}
Because I want to use priority_queue of C++ standard library, the type of PathCandidate must be struct of C++. Thus, I think I need definition of PathCandidate in .h file. However, There may be another way of doing so without .h file. I am looking for it. |
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isn't it possible to use a tuple instead of PathCandidate ? or may be |
Implement PNC k shortest simple path for directed graphs.
I implemented for only directed graphs for simplicity first.
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⌛ Dependencies
#40248
#40217