Tessero\Csgraph

apply(string $name, mixed ...$args): mixed

Call a function by its SciPy/NumPy name: Csgraph::apply('log_ndtr', $x).

bellmanFord(mixed $csgraph, mixed $directed = true, mixed $indices = null, mixed $returnPredecessors = false, mixed $unweighted = false): mixed

Bellman-Ford all-pairs shortest paths, allows negative weights (scipy.sparse.csgraph.bellman_ford; indices=None).

breadthFirstOrder(mixed $csgraph, mixed $iStart, mixed $directed = true, mixed $returnPredecessors = true): mixed

Breadth-first traversal order and predecessors (scipy.sparse.csgraph.breadth_first_order).

breadthFirstTree(mixed $csgraph, mixed $iStart, mixed $directed = true): mixed

Breadth-first spanning tree, returned dense (scipy.sparse.csgraph.breadth_first_tree).

connectedComponents(mixed $csgraph, mixed $directed = true, mixed $connection = 'weak'): mixed

Connected components of a graph, weak connectivity (scipy.sparse.csgraph.connected_components).

constructDistMatrix(mixed $graph, mixed $predecessors, mixed $directed = true): mixed

Distance matrix from a predecessor tree (scipy.sparse.csgraph.construct_dist_matrix).

csgraphFromDense(mixed $graph, mixed $nullValue = 0, mixed $nanNull = true, mixed $infinityNull = true): mixed

CSR triple (indptr, indices, data) from a dense adjacency matrix (scipy.sparse.csgraph.csgraph_from_dense).

csgraphToDense(mixed $data, mixed $indices, mixed $indptr, mixed $nNodes, mixed $nullValue = 0): mixed

Dense adjacency matrix from a CSR triple (scipy.sparse.csgraph.csgraph_to_dense; CSR passed as data/indices/indptr/n_nodes).

depthFirstOrder(mixed $csgraph, mixed $iStart, mixed $directed = true, mixed $returnPredecessors = true): mixed

Depth-first traversal order and predecessors (scipy.sparse.csgraph.depth_first_order).

depthFirstTree(mixed $csgraph, mixed $iStart, mixed $directed = true): mixed

Depth-first spanning tree, returned dense (scipy.sparse.csgraph.depth_first_tree).

dijkstra(mixed $csgraph, mixed $directed = true, mixed $indices = null, mixed $returnPredecessors = false, mixed $unweighted = false): mixed

Dijkstra all-pairs shortest paths, non-negative weights (scipy.sparse.csgraph.dijkstra; indices=None).

floydWarshall(mixed $csgraph, mixed $directed = true, mixed $returnPredecessors = false, mixed $unweighted = false, mixed $overwrite = false): mixed

Floyd-Warshall all-pairs shortest paths (scipy.sparse.csgraph.floyd_warshall).

johnson(mixed $csgraph, mixed $directed = true, mixed $indices = null, mixed $returnPredecessors = false, mixed $unweighted = false): mixed

Johnson all-pairs shortest paths (scipy.sparse.csgraph.johnson; indices=None).

laplacian(mixed $csgraph, mixed $normed = false): mixed

Graph Laplacian, plain or symmetric-normalized (scipy.sparse.csgraph.laplacian).

maximumBipartiteMatching(mixed $graph, mixed $permType = 'row'): mixed

Maximum bipartite matching of a sparse bipartite graph (scipy.sparse.csgraph.maximum_bipartite_matching).

maximumFlow(mixed $csgraph, mixed $source, mixed $sink, mixed $method = 'dinic'): mixed

Maximum single-source single-sink flow on a dense integer capacity matrix via Dinic's algorithm (scipy.sparse.csgraph.maximum_flow).

minWeightFullBipartiteMatching(mixed $biadjacencyMatrix, mixed $maximize = false): mixed

Minimum-weight full bipartite matching of a square biadjacency (scipy.sparse.csgraph.min_weight_full_bipartite_matching).

minimumSpanningTree(mixed $csgraph, mixed $overwrite = false): mixed

Minimum spanning tree of an undirected graph, returned dense (scipy.sparse.csgraph.minimum_spanning_tree).

reconstructPath(mixed $csgraph, mixed $predecessors, mixed $directed = true): mixed

Reconstruct the tree of a shortest-path predecessor list, returned dense (scipy.sparse.csgraph.reconstruct_path).

reverseCuthillMckee(mixed $graph, mixed $symmetricMode = false): mixed

Reverse Cuthill-McKee ordering of a sparse symmetric matrix (scipy.sparse.csgraph.reverse_cuthill_mckee).

shortestPath(mixed $csgraph, mixed $method = 'auto', mixed $directed = true, mixed $returnPredecessors = false, mixed $unweighted = false, mixed $overwrite = false, mixed $indices = null): mixed

All-pairs shortest path distance matrix (scipy.sparse.csgraph.shortest_path; dense, indices=None).

structuralRank(mixed $graph): mixed

Structural rank of a graph's sparsity pattern (scipy.sparse.csgraph.structural_rank).

yen(mixed $csgraph, mixed $source, mixed $sink, mixed $K, mixed $directed = true): mixed

K shortest loopless paths' distances via Yen's algorithm (scipy.sparse.csgraph.yen).