Uses of Interface
com.jgalgo.graph.Graph

Packages that use Graph

Package	Description
com.jgalgo.alg	Algorithms for solving graph problems.
com.jgalgo.gen	Graph generators used to generate (possibly random) graphs with different distributions and structures.
com.jgalgo.graph	Graphs object are the fundamental building blocks of the JGAlgo library.

Uses of Graph in com.jgalgo.alg

Methods in com.jgalgo.alg that return Graph

Modifier and Type	Method	Description
default Graph<Integer,E>	VertexPartition.blocksGraph()	Create a new graph representing the edges between the blocks.
Graph<Integer,E>	VertexPartition.blocksGraph(boolean parallelEdges, boolean selfEdges)	Create a new graph representing the edges between the blocks.
default Graph<V,E>	VertexPartition.blockSubGraph(int block)	Create a new graph that contains only the vertices and edges that are contained in a block.
default Graph<V,E>	VertexPartition.blockSubGraph(int block, boolean copyVerticesWeights, boolean copyEdgesWeights)	Create a new graph that contains only the vertices and edges that are contained in a block with option to copy weights.
default Graph<V,E>	KVertexConnectedComponentsAlgo.Result.componentSubGraph(int compIndex)	The subgraph of the k-vertex connected component with the given index.
Graph<V,E>	KVertexConnectedComponentsAlgo.Result.graph()	The graph on which the k-vertex connected components were found.
Graph<V,E>	VertexPartition.graph()	Get the graph that the partition is defined on.

Methods in com.jgalgo.alg with parameters of type Graph

Modifier and Type	Method	Description
default <V,E> List<Set<V>>	ClosuresEnumerator.allClosures(Graph<V,E> g)	Find all closures in the given graph.
default <V,E> List<Path<V,E>>	CyclesEnumerator.allCycles(Graph<V,E> g)	Find all cycles in the given graph.
default <V,E> List<Set<V>>	MaximalCliquesEnumerator.allMaximalCliques(Graph<V,E> g)	Finds all the maximal cliques in a graph.
default <V,E> List<VertexBiPartition<V,E>>	MinimumEdgeCutAllST.allMinimumCuts(Graph<V,E> g, WeightFunction<E> w, V source, V sink)	Compute all the minimum edge-cuts in a graph between two terminal vertices.
default <V,E> List<Set<V>>	MinimumVertexCutAllGlobal.allMinimumCuts(Graph<V,E> g, WeightFunction<V> w)	Find all the minimum vertex-cuts in a graph.
default <V,E> List<Set<V>>	MinimumVertexCutAllST.allMinimumCuts(Graph<V,E> g, WeightFunction<V> w, V source, V sink)	Compute all the minimum vertex-cuts in a graph between two terminal vertices.
default <V,E> List<Path<V,E>>	SimplePathsEnumerator.allSimplePaths(Graph<V,E> g, V source, V target)	Find all the simple paths between a source and a target vertices in the given graph.
<V,E> Iterator<Set<V>>	ClosuresEnumerator.closuresIter(Graph<V,E> g)	Iterate over all closures in the given graph.
<V,E> ShortestPathAllPairs.Result<V,E>	ShortestPathAllPairs.computeAllShortestPaths(Graph<V,E> g, WeightFunction<E> w)	Compute the shortest path between each pair of vertices in a graph.
<V,E> VertexPartition<V,E>	ColoringAlgo.computeColoring(Graph<V,E> g)	Assign a color to each vertex of the given graph, resulting in a valid coloring.
default <V,E> CoresAlgo.Result<V,E>	CoresAlgo.computeCores(Graph<V,E> g)	Compute the cores of the graph with respect to both in and out degree of the vertices.
<V,E> CoresAlgo.Result<V,E>	CoresAlgo.computeCores(Graph<V,E> g, EdgeDirection degreeType)	Compute the cores of the graph with respect the given degree type.
<V,E> Path<V,E>	EulerianTourAlgo.computeEulerianTour(Graph<V,E> g)	Compute an Eulerian tour in the graph that visit all edges exactly once.
<V,E> TreePathMaxima.Result<V,E>	TreePathMaxima.computeHeaviestEdgeInTreePaths(Graph<V,E> tree, WeightFunction<E> w, TreePathMaxima.Queries<V,E> queries)	Compute the heaviest edge in multiple tree paths.
<V,E> VertexPartition<V,E>	KEdgeConnectedComponentsAlgo.computeKEdgeConnectedComponents(Graph<V,E> g, int k)	Compute the k-edge connected components of a graph.
<V,E> List<Path<V,E>>	KShortestPathsST.computeKShortestPaths(Graph<V,E> g, WeightFunction<E> w, V source, V target, int k)	Compute the K shortest paths from a source vertex to a target vertex.
<V,E> Flow<V,E>	MaximumFlow.computeMaximumFlow(Graph<V,E> g, WeightFunction<E> capacity, Collection<V> sources, Collection<V> sinks)	Calculate the maximum flow in a network between a set of sources and a set of sinks.
<V,E> Flow<V,E>	MaximumFlow.computeMaximumFlow(Graph<V,E> g, WeightFunction<E> capacity, V source, V sink)	Calculate the maximum flow in a network between a source and a sink.
<V,E> Matching<V,E>	MatchingAlgo.computeMaximumMatching(Graph<V,E> g, WeightFunction<E> w)	Compute the maximum weighted matching of a weighted undirected graph.
<V,E> Matching<V,E>	MatchingAlgo.computeMaximumPerfectMatching(Graph<V,E> g, WeightFunction<E> w)	Compute the maximum perfect matching of a weighted undirected graph.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, WeightFunction<E> lowerBound, WeightFunction<V> supply)	Compute the min-cost (not maximum!) flow in a network given a supply for each vertex and a lower bound for the edges flows.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, WeightFunction<V> supply)	Compute the min-cost (not maximum!) flow in a network given a supply for each vertex.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostMaxFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, WeightFunction<E> lowerBound, Collection<V> sources, Collection<V> sinks)	Compute the min-cost max-flow in a network between a set of sources and a set of sinks given a lower bound for the edges flows.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostMaxFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, WeightFunction<E> lowerBound, V source, V sink)	Compute the min-cost max-flow in a network between a source and a sink given a lower bound for the edges flows.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostMaxFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, Collection<V> sources, Collection<V> sinks)	Compute the min-cost max-flow in a network between a set of sources and a set of sinks.
<V,E> Flow<V,E>	MinimumCostFlow.computeMinCostMaxFlow(Graph<V,E> g, WeightFunction<E> capacity, WeightFunction<E> cost, V source, V sink)	Compute the min-cost max-flow in a network between a source and a sink.
<V,E> VertexBiPartition<V,E>	MinimumEdgeCutGlobal.computeMinimumCut(Graph<V,E> g, WeightFunction<E> w)	Compute the global minimum edge-cut in a graph.
<V,E> VertexBiPartition<V,E>	MinimumEdgeCutST.computeMinimumCut(Graph<V,E> g, WeightFunction<E> w, Collection<V> sources, Collection<V> sinks)	Compute the minimum edge-cut in a graph between two sets of vertices.
<V,E> VertexBiPartition<V,E>	MinimumEdgeCutST.computeMinimumCut(Graph<V,E> g, WeightFunction<E> w, V source, V sink)	Compute the minimum edge-cut in a graph between two terminal vertices.
<V,E> Set<V>	MinimumVertexCutGlobal.computeMinimumCut(Graph<V,E> g, WeightFunction<V> w)	Compute the global minimum vertex-cut in a graph.
<V,E> Set<V>	MinimumVertexCutST.computeMinimumCut(Graph<V,E> g, WeightFunction<V> w, V source, V sink)	Compute the minimum vertex-cut in a graph between two terminal vertices.
<V,E> MinimumSpanningTree.Result<V,E>	MinimumDirectedSpanningTree.computeMinimumDirectedSpanningTree(Graph<V,E> g, WeightFunction<E> w, V root)	Compute a minimum directed spanning tree (MDST) in a directed graph, rooted at the given vertex.
default <V,E> Set<V>	DominatingSetAlgo.computeMinimumDominationSet(Graph<V,E> g, WeightFunction<V> w)	Compute a minimum dominating set of the graph with respect to the in-degree + out-degree of the vertices.
<V,E> Set<V>	DominatingSetAlgo.computeMinimumDominationSet(Graph<V,E> g, WeightFunction<V> w, EdgeDirection dominanceDirection)	Compute a minimum dominating set of the graph with respect to the given edges direction.
<V,E> Set<E>	EdgeCover.computeMinimumEdgeCover(Graph<V,E> g, WeightFunction<E> w)	Compute a minimum edge cover of a graph with respect to an edge weight function.
<V,E> Matching<V,E>	MatchingAlgo.computeMinimumMatching(Graph<V,E> g, WeightFunction<E> w)	Compute the minimum weighted matching of a weighted undirected graph.
<V,E> Path<V,E>	MinimumMeanCycle.computeMinimumMeanCycle(Graph<V,E> g, WeightFunction<E> w)	Compute the minimum mean cycle in a graph.
<V,E> Matching<V,E>	MatchingAlgo.computeMinimumPerfectMatching(Graph<V,E> g, WeightFunction<E> w)	Compute the minimum perfect matching of a weighted undirected graph.
<V,E> MinimumSpanningTree.Result<V,E>	MinimumSpanningTree.computeMinimumSpanningTree(Graph<V,E> g, WeightFunction<E> w)	Compute the minimum spanning tree (MST) of a given graph.
<V,E> Set<V>	VertexCover.computeMinimumVertexCover(Graph<V,E> g, WeightFunction<V> w)	Compute a minimum vertex cover of a graph with respect to a vertex weight function.
<V,E> Path<V,E>	ChinesePostman.computeShortestEdgeVisitorCircle(Graph<V,E> g, WeightFunction<E> w)	Compute the shortest circuit that visits all edges in the graph at least once.
<V,E> Path<V,E>	ShortestPathHeuristicST.computeShortestPath(Graph<V,E> g, WeightFunction<E> w, V source, V target, ToDoubleFunction<V> vHeuristic)	Compute the shortest path between two vertices in a graph.
<V,E> Path<V,E>	ShortestPathST.computeShortestPath(Graph<V,E> g, WeightFunction<E> w, V source, V target)	Compute the shortest path from a source vertex to a target vertex.
<V,E> ShortestPathSingleSource.Result<V,E>	ShortestPathSingleSource.computeShortestPaths(Graph<V,E> g, WeightFunction<E> w, V source)	Compute the shortest paths from a source to any other vertex in a graph.
<V,E> Path<V,E>	TspMetric.computeShortestTour(Graph<V,E> g, WeightFunction<E> w)	Compute the shortest tour that visit all vertices.
<V,E> SteinerTreeAlgo.Result<V,E>	SteinerTreeAlgo.computeSteinerTree(Graph<V,E> g, WeightFunction<E> w, Collection<V> terminals)	Compute the minimum Steiner tree of a given graph.
<V,E> ShortestPathAllPairs.Result<V,E>	ShortestPathAllPairs.computeSubsetShortestPaths(Graph<V,E> g, Collection<V> verticesSubset, WeightFunction<E> w)	Compute the shortest path between each pair of vertices in a given subset of the vertices of the graph.
<V,E> TopologicalOrderAlgo.Result<V,E>	TopologicalOrderAlgo.computeTopologicalSorting(Graph<V,E> g)	Compute the topological order of a DAG vertices.
<V,E> VoronoiAlgo.Result<V,E>	VoronoiAlgo.computeVoronoiCells(Graph<V,E> g, Collection<V> sites, WeightFunction<E> w)	Compute the Voronoi cells of a graph with respect to a set of sites and an edge weight function.
static <V,E> boolean	GraphsUtils.containsParallelEdges(Graph<V,E> g)	Check whether a graph contain parallel edges.
static <V,E> boolean	GraphsUtils.containsSelfEdges(Graph<V,E> g)	Check whether a graph contain self edges.
<V,E> Iterator<Path<V,E>>	CyclesEnumerator.cyclesIter(Graph<V,E> g)	Iterate over all cycles in the given graph.
<V,E> BiConnectedComponentsAlgo.Result<V,E>	BiConnectedComponentsAlgo.findBiConnectedComponents(Graph<V,E> g)	Compute all maximal bi-connected components of a graph.
<V,E> KVertexConnectedComponentsAlgo.Result<V,E>	KVertexConnectedComponentsAlgo.findKVertexConnectedComponents(Graph<V,E> g, int k)	Find all k-vertex connected components in a graph.
<V,E> LowestCommonAncestorOffline.Result<V,E>	LowestCommonAncestorOffline.findLCAs(Graph<V,E> tree, V root, LowestCommonAncestorOffline.Queries<V,E> queries)	Find the lowest common ancestors of the given queries.
static <V,E> Optional<VertexBiPartition<V,E>>	BipartiteGraphs.findPartition(Graph<V,E> g)	Find a bipartite partition of the given graph (if one exists).
static <V,E> Optional<VertexBiPartition<V,E>>	BipartiteGraphs.findPartition(Graph<V,E> g, boolean addPartitionWeight)	Find a bipartite partition of the given graph (if one exists), and optionally add the partition as vertex weights.
static <V,E> Path<V,E>	Path.findPath(Graph<V,E> g, V source, V target)	Find a valid path from \(u\) to \(v\).
<V,E> VertexPartition<V,E>	StronglyConnectedComponentsAlgo.findStronglyConnectedComponents(Graph<V,E> g)	Find all strongly connected components in a graph.
<V,E> VertexPartition<V,E>	WeaklyConnectedComponentsAlgo.findWeaklyConnectedComponents(Graph<V,E> g)	Compute all weakly connected components in a graph.
static <V,E> VertexBiPartition<V,E>	VertexBiPartition.fromMap(Graph<V,E> g, Object2BooleanMap<V> map)	Create a new vertex bi-partition from a vertex-side map.
static <V,E> VertexPartition<V,E>	VertexPartition.fromMap(Graph<V,E> g, Object2IntMap<V> map)	Create a new vertex partition from a vertex-blockIndex map.
static <V,E> VertexBiPartition<V,E>	VertexBiPartition.fromMapping(Graph<V,E> g, Predicate<V> mapping)	Create a new vertex bi-partition from a vertex-side mapping function.
static <V,E> VertexPartition<V,E>	VertexPartition.fromMapping(Graph<V,E> g, ToIntFunction<V> mapping)	Create a new vertex partition from a vertex-blockIndex mapping function.
static <V,E> Optional<VertexBiPartition<V,E>>	BipartiteGraphs.getExistingPartition(Graph<V,E> g)	Get the existing bipartite partition of the given graph (if one exists).
static <V,E> boolean	BipartiteGraphs.isBipartite(Graph<V,E> g)	Check whether the given graph is bipartite or not.
static <V,E> boolean	ClosuresEnumerator.isClosure(Graph<V,E> g, Set<V> c)	Check whether the given set is a closure in the given graph.
static <V,E> boolean	ColoringAlgo.isColoring(Graph<V,E> g, ToIntFunction<V> mapping)	Check whether a given mapping is a valid coloring of a graph.
static <V,E> boolean	EdgeCover.isCover(Graph<V,E> g, Collection<E> edges)	Check whether a set of edges is a edge cover of a graph.
static <V,E> boolean	VertexCover.isCover(Graph<V,E> g, Collection<V> vertices)	Check whether a set of vertices is a vertex cover of a graph.
static <V,E> boolean	MinimumVertexCutGlobal.isCut(Graph<V,E> g, Set<V> cut)	Check whether the given vertices form a vertex cut in the graph.
static <V,E> boolean	DominatingSetAlgo.isDominatingSet(Graph<V,E> g, Collection<V> dominatingSet, EdgeDirection dominanceDirection)	Check whether a given set of vertices is a dominating set of a graph.
static <V,E> boolean	Trees.isForest(Graph<V,E> g)	Check if a graph is a forest.
static <V,E> boolean	Matching.isMatching(Graph<V,E> g, Collection<E> edges)	Check whether the given collection of edges form a valid matching in the graph.
static <V,E> boolean	VertexBiPartition.isPartition(Graph<V,E> g, Predicate<V> mapping)	Check if a mapping is a valid bi-partition of the vertices of a graph.
static <V,E> boolean	VertexPartition.isPartition(Graph<V,E> g, ToIntFunction<V> mapping)	Check if a mapping is a valid partition of the vertices of a graph.
static <V,E> boolean	Path.isPath(Graph<V,E> g, V source, V target, List<E> edges)	Check whether the given edge list is a valid path in the given graph.
static <V,E> boolean	MinimumSpanningTree.isSpanningForest(Graph<V,E> g, Collection<E> edges)	Check whether a given set of edges is a spanning forest of a given graph.
static <V,E> boolean	MinimumSpanningTree.isSpanningTree(Graph<V,E> g, Collection<E> edges)	Check whether a given set of edges is a spanning tree of a given graph.
static <V,E> boolean	SteinerTreeAlgo.isSteinerTree(Graph<V,E> g, Collection<V> terminals, Collection<E> edges)	Check whether a given set of edges is a valid Steiner tree for a given graph and terminals.
<V,E> boolean	StronglyConnectedComponentsAlgo.isStronglyConnected(Graph<V,E> g)	Check whether a graph is strongly connected.
static <V,E> boolean	Trees.isTree(Graph<V,E> g)	Check if an undirected graph is a tree.
static <V,E> boolean	Trees.isTree(Graph<V,E> g, V root)	Check if a graph is a tree rooted as some vertex.
<V,E> boolean	WeaklyConnectedComponentsAlgo.isWeaklyConnected(Graph<V,E> g)	Check whether a graph is weakly connected.
<V,E> Iterator<Set<V>>	MaximalCliquesEnumerator.maximalCliquesIter(Graph<V,E> g)	Iterate over all maximal cliques in a graph.
<V,E> Iterator<VertexBiPartition<V,E>>	MinimumEdgeCutAllST.minimumCutsIter(Graph<V,E> g, WeightFunction<E> w, V source, V sink)	Iterate over all the minimum edge-cuts in a graph between two terminal vertices.
<V,E> Iterator<Set<V>>	MinimumVertexCutAllGlobal.minimumCutsIter(Graph<V,E> g, WeightFunction<V> w)	Iterate over all the minimum vertex-cuts in a graph.
<V,E> Iterator<Set<V>>	MinimumVertexCutAllST.minimumCutsIter(Graph<V,E> g, WeightFunction<V> w, V source, V sink)	Iterate over all the minimum vertex-cuts in a graph between two terminal vertices.
static <V,E> Bfs.Iter<V,E>	Bfs.newInstance(Graph<V,E> g, V source)	Create a BFS iterator.
static <V,E> Dfs.Iter<V,E>	Dfs.newInstance(Graph<V,E> g, V source)	Create a DFS iterator.
static <V,E> LowestCommonAncestorOffline.Queries<V,E>	LowestCommonAncestorOffline.Queries.newInstance(Graph<V,E> g)	Create an empty queries container.
static <V,E> Path<V,E>	Path.newInstance(Graph<V,E> g, V source, V target, List<E> edges)	Create a new path from an edge list, a source and a target vertices.
static <V,E> Bfs.Iter<V,E>	Bfs.newInstanceBackward(Graph<V,E> g, V source)	Create a backward BFS iterator.
<V,E> LowestCommonAncestorStatic.DataStructure<V,E>	LowestCommonAncestorStatic.preProcessTree(Graph<V,E> tree, V root)	Perform a static pre processing of a tree for future LCA (Lowest common ancestor) queries.
static <V,E> Set<V>	Path.reachableVertices(Graph<V,E> g, Iterator<V> sources)	Find all the vertices reachable from a given set of source vertices.
static <V,E> Set<V>	Path.reachableVertices(Graph<V,E> g, V source)	Find all the vertices reachable from a given source vertex.
<V,E> Iterator<Path<V,E>>	SimplePathsEnumerator.simplePathsIter(Graph<V,E> g, V source, V target)	Iterate over all the simple paths between a source and a target vertices in the given graph.
static <V,E> boolean	TreePathMaxima.verifyMST(Graph<V,E> g, WeightFunction<E> w, Collection<E> mstEdges, TreePathMaxima tpmAlgo)	Verify that the given edges actually form an MST of a graph.

Uses of Graph in com.jgalgo.gen

Methods in com.jgalgo.gen that return Graph

Modifier and Type	Method	Description
static <V,E> Graph<V,E>	EmptyGraphGenerator.emptyGraph(Collection<V> vertices)	Generate a new empty undirected graph.
default Graph<V,E>	GraphGenerator.generate()	Generates an immutable graph.
default Graph<V,E>	GraphGenerator.generateMutable()	Generates a mutable graph.

Uses of Graph in com.jgalgo.graph

Subinterfaces of Graph in com.jgalgo.graph

Modifier and Type	Interface	Description
interface	IndexGraph	A graph whose vertices and edges identifiers are indices.
interface	IntGraph	A discrete graph with int vertices and edges.

Classes in com.jgalgo.graph that implement Graph

Modifier and Type	Class	Description
class	GraphBaseWithEdgeEndpointsContainer

Methods in com.jgalgo.graph that return Graph

Modifier and Type	Method	Description
Graph<V,E>	GraphBuilder.build()	Build a new immutable graph with the builder vertices and edges.
Graph<V,E>	GraphBuilder.buildMutable()	Build a new mutable graph with the builder vertices and edges.
default Graph<V,E>	Graph.copy()	Create a copy of this graph, with the same vertices and edges, without copying weights.
default Graph<V,E>	Graph.copy(boolean copyWeights)	Create a copy of this graph, with the same vertices and edges, with/without copying weights.
default Graph<V,E>	Graph.immutableCopy()	Create an immutable copy of this graph, with the same vertices and edges, without copying weights.
default Graph<V,E>	Graph.immutableCopy(boolean copyWeights)	Create an immutable copy of this graph, with the same vertices and edges, with/without copying weights.
default Graph<V,E>	Graph.immutableView()	Get an immutable view of this graph.
default Graph<V,E>	GraphFactory.newCopyOf(Graph<V,E> g)	Create a copy of a given graph, with the same vertices and edges, without copying weights.
Graph<V,E>	GraphFactory.newCopyOf(Graph<V,E> g, boolean copyWeights)	Create a copy of a given graph, with the same vertices and edges, with/without copying weights.
static <V,E> Graph<V,E>	Graph.newDirected()	Create a new directed empty graph.
Graph<V,E>	GraphFactory.newGraph()	Create a new empty graph.
static <V,E> Graph<V,E>	Graph.newUndirected()	Create a new undirected empty graph.
default Graph<V,E>	Graph.reverseView()	Get a reversed view of this graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices)	Create a new graph that is an induced subgraph of the given graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices, Collection<E> edges)	Create a new graph that is a subgraph of the given graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices, Collection<E> edges, boolean copyVerticesWeights, boolean copyEdgesWeights)	Create a new graph that is a subgraph of the given graph, with option to copy weights.
default Graph<V,E>	Graph.subGraphCopy(Collection<V> vertices, Collection<E> edges)	Create a new graph that is a subgraph of this graph.
default Graph<V,E>	Graph.undirectedView()	Get an undirected view of this (directed) graph.

Methods in com.jgalgo.graph with parameters of type Graph

Modifier and Type	Method	Description
static <E,T,WeightsT extends Weights<E,T>> WeightsT	Weights.createExternalEdgesWeights(Graph<?,E> g, Class<? super T> type)	Create an external edge weights container.
static <E,T,WeightsT extends Weights<E,T>> WeightsT	Weights.createExternalEdgesWeights(Graph<?,E> g, Class<? super T> type, T defVal)	Create an external edge weights container with default values.
static <V,T,WeightsT extends Weights<V,T>> WeightsT	Weights.createExternalVerticesWeights(Graph<V,?> g, Class<? super T> type)	Create an external vertex weights container.
static <V,T,WeightsT extends Weights<V,T>> WeightsT	Weights.createExternalVerticesWeights(Graph<V,?> g, Class<? super T> type, T defVal)	Create an external vertex weights container with default values.
static <V,E> EdgeIter<V,E>	IndexIdMaps.indexToIdEdgeIter(Graph<V,E> g, IEdgeIter indexIter)	Create an IEdgeIter that return IDs of vertices and edges from an IEdgeIter that return indices of vertices and edges.
default Graph<V,E>	GraphFactory.newCopyOf(Graph<V,E> g)	Create a copy of a given graph, with the same vertices and edges, without copying weights.
Graph<V,E>	GraphFactory.newCopyOf(Graph<V,E> g, boolean copyWeights)	Create a copy of a given graph, with the same vertices and edges, with/without copying weights.
default IndexGraph	IndexGraphFactory.newCopyOf(Graph<Integer,Integer> g)
IndexGraph	IndexGraphFactory.newCopyOf(Graph<Integer,Integer> g, boolean copyWeights)
default IntGraph	IntGraphFactory.newCopyOf(Graph<Integer,Integer> g)
IntGraph	IntGraphFactory.newCopyOf(Graph<Integer,Integer> g, boolean copyWeights)
static <V,E> GraphBuilder<V,E>	GraphBuilder.newFrom(Graph<V,E> g)	Create a new builder initialized with an existing graph vertices and edges, without copying the weights.
static <V,E> GraphBuilder<V,E>	GraphBuilder.newFrom(Graph<V,E> g, boolean copyWeights)	Create a new builder initialized with an existing graph vertices and edges, with/without copying the weights.
static <V,E> GraphFactory<V,E>	GraphFactory.newFrom(Graph<V,E> g)	Create a new graph factory based on a given implementation.
static <E> E	Graphs.randEdge(Graph<?,E> g, Random rand)	Get a random edge from the given graph.
static <V> V	Graphs.randVertex(Graph<V,?> g, Random rand)	Get a random vertex from the given graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices)	Create a new graph that is an induced subgraph of the given graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices, Collection<E> edges)	Create a new graph that is a subgraph of the given graph.
static <V,E> Graph<V,E>	Graphs.subGraph(Graph<V,E> g, Collection<V> vertices, Collection<E> edges, boolean copyVerticesWeights, boolean copyEdgesWeights)	Create a new graph that is a subgraph of the given graph, with option to copy weights.