Add a few more BFS-based algorithms#51
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eriknw merged 7 commits intopython-graphblas:mainfrom Apr 15, 2023
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- Components - `is_connected` - `is_weakly_connected` - `node_connected_component` - Shortest Paths - `all_pairs_shortest_path_length` - `negative_edge_cycle` - `single_source_shortest_path_length` - `single_target_shortest_path_length` - Traversal - `bfs_layers` - `descendants_at_distance`
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I'm also not sure if these are the best algorithms for connected component-related functions. Connected components are an important class of algorithms that we should add soon (for example, we have an implementation of FastSV in a Jupyter notebook that we can port over), so perhaps we'll revisit these algorithms then. |
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## main #51 +/- ##
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+ Coverage 69.16% 71.62% +2.46%
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Merging so we can do a release before PyConUS. May be able to benchmark and shakedown some algorithms later, but they're probably good enough. |
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BFS is a workhorse! There are still many BFS-based algorithms still to do.
My main TODO is to benchmark these to give them a proper shakedown. I like to shake down most algorithms we add. Also, I wonder whether we should use
A.TorATin a couple places. I also wonder if we can come up with a heuristic to detect negative cycles.It may be nice to know whether directed graphs are structurally symmetric. If we knew this, we could improve
is_weakly_connectedand other algorithms.Also, there may be a couple NetworkX bugs to fix or behaviors to match.
Implemented:
is_connectedis_weakly_connectednode_connected_componentall_pairs_shortest_path_lengthnegative_edge_cyclesingle_source_shortest_path_lengthsingle_target_shortest_path_lengthbfs_layersdescendants_at_distance