Uses of Class
oracle.pgx.api.VertexProperty

Packages that use VertexProperty

Package	Description
oracle.pgx.api	This package contains the main Java APIs.
oracle.pgx.api.mllib	This package contains graph machine learning tools for use with PGX.

Uses of VertexProperty in oracle.pgx.api

Subclasses of VertexProperty in oracle.pgx.api

Modifier and Type	Class	Description
class	VertexLabels<ID>

Fields in oracle.pgx.api with type parameters of type VertexProperty

Modifier and Type	Field	Description
static java.util.Set<VertexProperty<?,?>>	VertexProperty.ALL
static java.util.Set<VertexProperty<?,?>>	VertexProperty.NONE

Methods in oracle.pgx.api that return VertexProperty

Modifier and Type	Method	Description
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentrality(PgxGraph graph, int k)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentrality(PgxGraph graph, int k, VertexProperty<ID,java.lang.Double> bc)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentralityFromSeeds(PgxGraph graph, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentralityFromSeeds(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, boolean norm)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max, boolean norm)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Boolean>	Analyst.bipartiteCheck(PgxGraph graph, VertexProperty<ID,java.lang.Boolean> isLeft)	Bipartite check verifies whether are graph is a bipartite graph.
VertexProperty<ID,V>	VertexProperty.clone()	Blocking version of cloneAsync().
VertexProperty<ID,V>	VertexProperty.clone(java.lang.String newPropertyName)	Blocking version of cloneAsync(String).
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityDoubleLength(PgxGraph graph, EdgeProperty<java.lang.Double> cost)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityDoubleLength(PgxGraph graph, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityUnitLength(PgxGraph graph)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityUnitLength(PgxGraph graph, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.combineVertexPropertiesIntoVectorProperty(java.util.List<VertexProperty<ID,V>> vertexPropertyList)	Blocking version of PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List) Calls PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List) and waits for the returned PgxFuture to complete.
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.combineVertexPropertiesIntoVectorProperty(java.util.List<VertexProperty<ID,V>> vertexPropertyList, java.lang.String name)	Blocking version of PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List, String) Calls PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List, String) and waits for the returned PgxFuture to complete.
<ID> VertexProperty<ID,PgxVect<java.lang.Integer>>	Analyst.createDistanceIndex(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices)	Computes an index with distances to each high-degree vertex.
<ID> VertexProperty<ID,PgxVect<java.lang.Integer>>	Analyst.createDistanceIndex(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes an index with distances to each high-degree vertex.
<ID,V> VertexProperty<ID,V>	PgxGraph.createVertexProperty(PropertyType type)	Blocking version of PgxGraph.createVertexPropertyAsync(PropertyType).
<ID,V> VertexProperty<ID,V>	PgxGraph.createVertexProperty(PropertyType type, int dimension, java.lang.String name, boolean hardName)	Blocking version of PgxGraph.createVertexPropertyAsync(PropertyType, int, String, boolean).
<ID,V> VertexProperty<ID,V>	PgxGraph.createVertexProperty(PropertyType type, java.lang.String name)	Blocking version of PgxGraph.createVertexPropertyAsync(PropertyType, String).
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.createVertexVectorProperty(PropertyType type, int dimension)	Blocking version of PgxGraph.createVertexVectorPropertyAsync(PropertyType, int).
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.createVertexVectorProperty(PropertyType type, int dimension, java.lang.String name)	Blocking version of PgxGraph.createVertexVectorPropertyAsync(PropertyType, int, String).
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.degreeCentrality(PgxGraph graph)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.degreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredWeightedSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredWeightedSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredWeightedSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
VertexProperty<ID,java.lang.Long>	Partition.getComponentsProperty()	Returns the property that contains for each vertex, its associated component ID
VertexProperty<ID,java.lang.Double>	MatrixFactorizationModel.getEstimatedRatings(PgxVertex<ID> estimateRatingsFor)	Blocking version of MatrixFactorizationModel.getEstimatedRatingsAsync(PgxVertex)
VertexProperty<ID,PgxVect<java.lang.Double>>	MatrixFactorizationModel.getFeatures()	Gets the features of this model.
<ID> VertexProperty<ID,java.lang.Boolean>	BipartiteGraph.getIsLeftProperty()	Blocking version of BipartiteGraph.getIsLeftPropertyAsync().
<ID,V> VertexProperty<ID,V>	PgxGraph.getOrCreateVertexProperty(PropertyType type, java.lang.String name)	Blocking version of PgxGraph.getOrCreateVertexPropertyAsync(PropertyType, String).
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.getOrCreateVertexVectorProperty(PropertyType type, int dimension, java.lang.String name)	Blocking version of PgxGraph.getOrCreateVertexVectorPropertyAsync(PropertyType, int, String).
<ID,V> VertexProperty<ID,V>	PgxGraph.getVertexProperty(java.lang.String name)	Blocking version of PgxGraph.getVertexPropertyAsync(String).
<ID,V> VertexProperty<ID,V>	PgxGraph.getVertexProperty(Namespace namespace, java.lang.String name)	Blocking version of PgxGraph.getVertexPropertyAsync(Namespace, String).
<ID> VertexProperty<ID,java.lang.Double>	Analyst.harmonicCentrality(PgxGraph graph)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.harmonicCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> hc)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.inDegreeCentrality(PgxGraph graph)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.inDegreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Long>	Analyst.louvain(PgxGraph graph, EdgeProperty<java.lang.Double> weight)	Louvain can detect communities in a large graph relatively fast.
<ID> VertexProperty<ID,java.lang.Long>	Analyst.louvain(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter)	Louvain can detect communities in a large graph relatively fast.
<ID> VertexProperty<ID,java.lang.Long>	Analyst.louvain(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter, int nbrPass, double tol, VertexProperty<ID,java.lang.Long> community)	Louvain can detect communities in a large graph relatively fast.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.matrixFactorizationRecommendations(BipartiteGraph graph, ID user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Convenience wrapper around Analyst.matrixFactorizationRecommendations(BipartiteGraph, PgxVertex, int, VertexProperty, VertexProperty) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.matrixFactorizationRecommendations(BipartiteGraph graph, PgxVertex<ID> user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Estimate rating can be used as a prediction algorithm for bipartite graphs
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.outDegreeCentrality(PgxGraph graph)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.outDegreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, boolean norm)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max, boolean norm)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph)	Faster, but less accurate than pagerank.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph, double e, double d, int max)	Faster, but less accurate than pagerank.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max)	Convenience wrapper around {@link #personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int,)} taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm)	Convenience wrapper around Analyst.personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, ID v, java.math.BigDecimal d, int maxIterations, java.math.BigDecimal maxDiff)	Convenience wrapper around Analyst.personalizedSalsa(BipartiteGraph, PgxVertex, BigDecimal, int, BigDecimal) taking a vertex ID instead of PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, ID v, java.math.BigDecimal d, int maxIterations, java.math.BigDecimal maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Convenience wrapper around #personalizedSalsa(BipartiteGraph, PgxVertex, BigDecimal, int, BigDecimal, VertexProperty<ID, Double>) taking a vertex ID instead of PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	Convenience wrapper around Analyst.personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean, EdgeProperty) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean, EdgeProperty, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, EdgeProperty<java.lang.Double> weight)	Convenience wrapper around Analyst.personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, EdgeProperty) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, EdgeProperty, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph)	SALSA computes ranking scores.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph, double maxDiff, int maxIter)	SALSA computes ranking scores.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph, double maxDiff, int maxIter, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> VertexProperty<ID,java.lang.String>	Analyst.speakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.speakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.speakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSchedule(PgxGraph graph, VertexSet<ID> source)	Topological schedule gives an order of visit for the reachable vertices from the source
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSchedule(PgxGraph graph, VertexSet<ID> source, VertexProperty<ID,java.lang.Integer> topoSched)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSort(PgxGraph graph)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSort(PgxGraph graph, VertexProperty<ID,java.lang.Integer> topoSort)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> VertexProperty<ID,java.lang.Double>	Analyst.vertexBetweennessCentrality(PgxGraph graph)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.vertexBetweennessCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.String>	Analyst.weightedSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.weightedSpeakerListenerLabelPropagation(PgxGraph graph, java.lang.String labelsPropName, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.weightedSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.

Methods in oracle.pgx.api that return types with arguments of type VertexProperty

Modifier and Type	Method	Description
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityAsync(PgxGraph graph, int k)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityAsync(PgxGraph graph, int k, VertexProperty<ID,java.lang.Double> bc)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityFromSeedsAsync(PgxGraph graph, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityFromSeedsAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, boolean norm)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max, boolean norm)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Boolean>>	Analyst.bipartiteCheckAsync(PgxGraph graph, VertexProperty<ID,java.lang.Boolean> isLeft)	Bipartite check verifies whether are graph is a bipartite graph.
PgxFuture<VertexProperty<ID,V>>	VertexProperty.cloneAsync()	Create a copy of this property. Convenience method for cloneAsync(String) passing newPropertyName as null
PgxFuture<VertexProperty<ID,V>>	VertexProperty.cloneAsync(java.lang.String newPropertyName)	Creates a copy of this property.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityDoubleLengthAsync(PgxGraph graph, EdgeProperty<java.lang.Double> cost)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityDoubleLengthAsync(PgxGraph graph, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityUnitLengthAsync(PgxGraph graph)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityUnitLengthAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(java.util.List<VertexProperty<ID,V>> vertexPropertyList)	Takes a list of scalar vertex properties of same type and creates a new vertex vector property by combining them.
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(java.util.List<VertexProperty<ID,V>> vertexPropertyList, java.lang.String name)	Takes a list of scalar vertex properties of same type and creates a new vertex vector property by combining them.
<ID> PgxFuture<VertexProperty<ID,PgxVect<java.lang.Integer>>>	Analyst.createDistanceIndexAsync(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices)	Computes an index with distances to each high-degree vertex.
<ID> PgxFuture<VertexProperty<ID,PgxVect<java.lang.Integer>>>	Analyst.createDistanceIndexAsync(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes an index with distances to each high-degree vertex.
<ID,V> PgxFuture<VertexProperty<ID,V>>	PgxGraph.createVertexPropertyAsync(PropertyType type)	Creates a session-bound vertex property
<ID,V> PgxFuture<VertexProperty<ID,V>>	PgxGraph.createVertexPropertyAsync(PropertyType type, java.lang.String name)	Creates a session-bound vertex property
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.createVertexVectorPropertyAsync(PropertyType type, int dimension)	Creates a session-bound vertex vector property
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.createVertexVectorPropertyAsync(PropertyType type, int dimension, java.lang.String name)	Creates a session-bound vertex vector property
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.degreeCentralityAsync(PgxGraph graph)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.degreeCentralityAsync(PgxGraph graph, java.lang.String propertyName)
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.degreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.diameter(PgxGraph graph)	Diameter/radius gives an overview of the distances in a graph
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.diameter(PgxGraph graph, Scalar<java.lang.Integer> diameter, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.diameterAsync(PgxGraph graph)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.diameterAsync(PgxGraph graph, Scalar<java.lang.Integer> diameter, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<S> java.util.List<VertexProperty<ID,S>>	VertexProperty.expand()	Blocking version of expandAsync().
<S> java.util.List<VertexProperty<ID,S>>	VertexProperty.expand(java.lang.String namePrefix)	Blocking version of expandAsync(String).
<S> PgxFuture<java.util.List<VertexProperty<ID,S>>>	VertexProperty.expandAsync()	If this is a vector property, expands this property into a list of scalar properties of same type.
<S> PgxFuture<java.util.List<VertexProperty<ID,S>>>	VertexProperty.expandAsync(java.lang.String namePrefix)	If this is a vector property, expands this property into a list of scalar properties of same type.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, ID root)	Convenience wrapper around Analyst.filteredBfs(PgxGraph, PgxVertex) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, ID root)	Convenience wrapper around Analyst.filteredBfs(PgxGraph, PgxVertex) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, ID root, int maxDepth)	Convenience wrapper around Analyst.filteredBfs(PgxGraph, PgxVertex, int) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, ID root, int maxDepth)	Convenience wrapper around Analyst.filteredBfs(PgxGraph, PgxVertex, int) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, ID root)	Convenience wrapper around Analyst.filteredDfs(PgxGraph, PgxVertex) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, ID root)	Convenience wrapper around Analyst.filteredDfs(PgxGraph, PgxVertex) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, ID root, int maxDepth)	Convenience wrapper around Analyst.filteredDfs(PgxGraph, PgxVertex, int) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, ID root, int maxDepth)	Convenience wrapper around Analyst.filteredDfs(PgxGraph, PgxVertex, int) taking a vertex ID instead of PgxVertex.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, int maxDepth)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredWeightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredWeightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredWeightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
PgxFuture<VertexProperty<ID,java.lang.Double>>	MatrixFactorizationModel.getEstimatedRatingsAsync(PgxVertex<ID> estimateRatingsFor)	Computes estimated ratings for a specific vertex.
<ID> PgxFuture<VertexProperty<ID,java.lang.Boolean>>	BipartiteGraph.getIsLeftPropertyAsync()	Gets the 'is Left' vertex property of the graph.
<ID,V> PgxFuture<VertexProperty<ID,V>>	PgxGraph.getOrCreateVertexPropertyAsync(PropertyType type, java.lang.String name)	Gets or creates a vertex property
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.getOrCreateVertexVectorPropertyAsync(PropertyType type, int dimension, java.lang.String name)	Gets or creates a vertex vector property
java.util.Set<VertexProperty<?,?>>	PgxGraph.getVertexProperties()	Blocking version of PgxGraph.getVertexPropertiesAsync().
PgxFuture<java.util.Set<VertexProperty<?,?>>>	PgxGraph.getVertexPropertiesAsync()	Get the set of vertex properties belonging to this graph.
<ID,V> PgxFuture<VertexProperty<ID,V>>	PgxGraph.getVertexPropertyAsync(java.lang.String name)	Gets a vertex property of this graph.
<ID,V> PgxFuture<VertexProperty<ID,V>>	PgxGraph.getVertexPropertyAsync(Namespace namespace, java.lang.String name)	Gets a vertex property of this graph in the given namespace.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.harmonicCentralityAsync(PgxGraph graph)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.harmonicCentralityAsync(PgxGraph graph, java.lang.String propertyName)
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.harmonicCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> hc)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.inDegreeCentralityAsync(PgxGraph graph)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.inDegreeCentralityAsync(PgxGraph graph, java.lang.String propertyName)
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.inDegreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, int minCore, int maxCore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, int minCore, int maxCore, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, int minCore, int maxCore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, int minCore, int maxCore, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Long>>	Analyst.louvainAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight)	Louvain can detect communities in a large graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.Long>>	Analyst.louvainAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter)	Louvain can detect communities in a large graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.Long>>	Analyst.louvainAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter, int nbrPass, double tol, VertexProperty<ID,java.lang.Long> community)	Louvain can detect communities in a large graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.matrixFactorizationRecommendationsAsync(BipartiteGraph graph, PgxVertex<ID> user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Estimate rating can be used as a prediction algorithm for bipartite graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.outDegreeCentralityAsync(PgxGraph graph)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.outDegreeCentralityAsync(PgxGraph graph, java.lang.String propertyName)
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.outDegreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph, double e, double d, int max)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, boolean norm)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.radius(PgxGraph graph)	Diameter/radius gives an overview of the distances in a graph
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.radius(PgxGraph graph, Scalar<java.lang.Integer> radius, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.radiusAsync(PgxGraph graph)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.radiusAsync(PgxGraph graph, Scalar<java.lang.Integer> radius, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph, double maxDiff, int maxIter)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph, double maxDiff, int maxIter, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.speakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.speakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.speakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalScheduleAsync(PgxGraph graph, VertexSet<ID> source)	Topological schedule gives an order of visit for the reachable vertices from the source
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalScheduleAsync(PgxGraph graph, VertexSet<ID> source, VertexProperty<ID,java.lang.Integer> topoSched)	Topological schedule gives an order of visit for the reachable vertices from the source
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalSortAsync(PgxGraph graph)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalSortAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> topoSort)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.vertexBetweennessCentralityAsync(PgxGraph graph)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.vertexBetweennessCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.weightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.weightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, java.lang.String labelsPropName, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.weightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.

Methods in oracle.pgx.api with parameters of type VertexProperty

Modifier and Type	Method	Description
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentrality(PgxGraph graph, int k, VertexProperty<ID,java.lang.Double> bc)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityAsync(PgxGraph graph, int k, VertexProperty<ID,java.lang.Double> bc)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.approximateVertexBetweennessCentralityFromSeeds(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.approximateVertexBetweennessCentralityFromSeedsAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc, PgxVertex<ID>... seeds)	Faster, but less accurate than betweenness centrality, it identifies important vertices for the flow of information
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.articleRank(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.articleRankAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	ArticleRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Boolean>	Analyst.bipartiteCheck(PgxGraph graph, VertexProperty<ID,java.lang.Boolean> isLeft)	Bipartite check verifies whether are graph is a bipartite graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Boolean>>	Analyst.bipartiteCheckAsync(PgxGraph graph, VertexProperty<ID,java.lang.Boolean> isLeft)	Bipartite check verifies whether are graph is a bipartite graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityDoubleLength(PgxGraph graph, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityDoubleLengthAsync(PgxGraph graph, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on weighted distances, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.closenessCentralityUnitLength(PgxGraph graph, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.closenessCentralityUnitLengthAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> cc)	Closeness centrality measures the centrality of the vertices based on distances, allowing to find well-connected vertices
<ID> Partition<ID>	Analyst.communitiesConductanceMinimization(PgxGraph graph, int maxIterations, VertexProperty<ID,java.lang.Long> partitionDistribution)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> Partition<ID>	Analyst.communitiesConductanceMinimization(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesConductanceMinimizationAsync(PgxGraph graph, int maxIterations, VertexProperty<ID,java.lang.Long> partitionDistribution)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesConductanceMinimizationAsync(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> Partition<ID>	Analyst.communitiesInfomap(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight)	Infomap can find high quality communities in a graph.
<ID> Partition<ID>	Analyst.communitiesInfomap(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, double tau, double tol, int maxIter)	Infomap can find high quality communities in a graph.
<ID> Partition<ID>	Analyst.communitiesInfomap(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, double tau, double tol, int maxIter, VertexProperty<ID,java.lang.Long> module)	Infomap can find high quality communities in a graph.
<ID> Partition<ID>	Analyst.communitiesInfomap(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Long> module)	Infomap can find high quality communities in a graph.
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesInfomapAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight)	Infomap can find high quality communities in a graph.
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesInfomapAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, double tau, double tol, int maxIter)	Infomap can find high quality communities in a graph.
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesInfomapAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, double tau, double tol, int maxIter, VertexProperty<ID,java.lang.Long> module)	Infomap can find high quality communities in a graph.
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesInfomapAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Long> module)	Infomap can find high quality communities in a graph.
<ID> Partition<ID>	Analyst.communitiesLabelPropagation(PgxGraph graph, int maxIterations, VertexProperty<ID,java.lang.Long> partitionDistribution)	Label propagation can find communities in a graph relatively fast
<ID> Partition<ID>	Analyst.communitiesLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitonDistribution)	Label propagation can find communities in a graph relatively fast
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesLabelPropagationAsync(PgxGraph graph, int maxIterations, VertexProperty<ID,java.lang.Long> partitionDistribution)	Label propagation can find communities in a graph relatively fast
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Label propagation can find communities in a graph relatively fast
<ID> AllPaths<ID>	PgxGraph.createAllPaths(PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> dist, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Blocking version of PgxGraph.createAllPathsAsync(PgxVertex, EdgeProperty, VertexProperty, VertexProperty, VertexProperty).
<ID> PgxFuture<AllPaths<ID>>	PgxGraph.createAllPathsAsync(PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> dist, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Creates a AllPaths object representing all the shortest paths from a single source to all the possible destinations (shortest regarding the given edge costs).
<ID> Partition<ID>	PgxGraph.createComponents(VertexProperty<ID,java.lang.Long> components, long numComponents)	Blocking version of PgxGraph.createComponentsAsync(VertexProperty, long).
<ID> PgxFuture<Partition<ID>>	PgxGraph.createComponentsAsync(VertexProperty<ID,java.lang.Long> components, long numComponents)	Creates a Partition object holding a collection of vertex sets, each representing a component.
<ID> VertexProperty<ID,PgxVect<java.lang.Integer>>	Analyst.createDistanceIndex(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes an index with distances to each high-degree vertex.
<ID> PgxFuture<VertexProperty<ID,PgxVect<java.lang.Integer>>>	Analyst.createDistanceIndexAsync(PgxGraph graph, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes an index with distances to each high-degree vertex.
<ID> PgxPath<ID>	PgxGraph.createPath(PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Blocking version of PgxGraph.createPathAsync(PgxVertex, PgxVertex, EdgeProperty, VertexProperty, VertexProperty).
<ID> PgxFuture<PgxPath<ID>>	PgxGraph.createPathAsync(PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Creates a PgxPath object representing the shortest path from one source to one destination (shortest regarding the given edge costs).
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.degreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.degreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.diameter(PgxGraph graph, Scalar<java.lang.Integer> diameter, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.diameterAsync(PgxGraph graph, Scalar<java.lang.Integer> diameter, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
B	MutationStrategyBuilder.dropVertexProperty(VertexProperty<?,?> vertexProperty)	Set vertex property that will be dropped after the mutation.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> VertexProperty<ID,java.lang.Double>	Analyst.eigenvectorCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph, int max, double maxDiff, boolean useL2Norm, boolean useInEdge, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.eigenvectorCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> ec)	Eigenvector centrality gets the centrality of the vertices in an intricate way using neighbors, allowing to find well-connected vertices
<ID> AllPaths<ID>	Analyst.fattestPath(PgxGraph graph, ID rootId, EdgeProperty<java.lang.Double> capacity, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.fattestPath(PgxGraph, PgxVertex, EdgeProperty, VertexProperty, VertexProperty, VertexProperty) taking a vertex ID instead of a PgxVertex.
<ID> AllPaths<ID>	Analyst.fattestPath(PgxGraph graph, PgxVertex<ID> root, EdgeProperty<java.lang.Double> capacity, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Fattest path is a fast algorithm for finding a shortest path adding constraints for flowing related matters
<ID> AllPaths<ID>	Analyst.fattestPath(PgxGraph graph, PgxVertex<ID> root, EdgeProperty<java.lang.Double> capacity, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected Fattest path is variation of the fattest graph algorithm that ignores edge directions.
<ID> PgxFuture<AllPaths<ID>>	Analyst.fattestPathAsync(PgxGraph graph, PgxVertex<ID> root, EdgeProperty<java.lang.Double> capacity, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Fattest path is a fast algorithm for finding a shortest path adding constraints for flowing related matters
<ID> PgxFuture<AllPaths<ID>>	Analyst.fattestPathAsync(PgxGraph graph, PgxVertex<ID> root, EdgeProperty<java.lang.Double> capacity, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected Fattest path is variation of the fattest graph algorithm that ignores edge directions.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Breadth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredDfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, int maxDepth, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredDfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter navigator, boolean initWithInf, VertexProperty<ID,java.lang.Integer> distance, VertexProperty<ID,PgxVertex<ID>> parent)	A Depth-First Search implementation with an option to filter edges during the traversal of the graph.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.String>	Analyst.filteredWeightedSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.filteredWeightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight, EdgeFilter filter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.harmonicCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> hc)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.harmonicCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> hc)	Harmonic centrality measures node importance by considering the reciprocal of the sum of shortest path distances in the network.
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> auth, VertexProperty<ID,java.lang.Double> hubs)	HITS assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.inDegreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.inDegreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	In-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
java.lang.Boolean	PgxGraph.isBipartiteGraph(VertexProperty<?,java.lang.Boolean> isLeft)	Blocking version of PgxGraph.isBipartiteGraphAsync(VertexProperty).
<ID> PgxFuture<java.lang.Boolean>	PgxGraph.isBipartiteGraphAsync(VertexProperty<ID,java.lang.Boolean> isLeft)	Checks whether a given graph is a bipartite graph.
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, int minCore, int maxCore, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, int minCore, int maxCore, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, Scalar<java.lang.Long> maxKCore, VertexProperty<ID,java.lang.Long> kcore)	k-core decomposes a graph into layers revealing subgraphs with particular properties
<ID> Pair<VertexSequence<ID>,EdgeSequence>	Analyst.limitedShortestPathHopDist(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes the k-hop limited shortest path between two vertices.
<ID> Pair<VertexSequence<ID>,EdgeSequence>	Analyst.limitedShortestPathHopDist(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, VertexSequence<ID> pathVertices, EdgeSequence pathEdges)	Computes the k-hop limited shortest path between two vertices.
<ID> PgxFuture<Pair<VertexSequence<ID>,EdgeSequence>>	Analyst.limitedShortestPathHopDistAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index)	Computes the k-hop limited shortest path between two vertices.
<ID> PgxFuture<Pair<VertexSequence<ID>,EdgeSequence>>	Analyst.limitedShortestPathHopDistAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, VertexSequence<ID> pathVertices, EdgeSequence pathEdges)	Computes the k-hop limited shortest path between two vertices.
<ID> Pair<VertexSequence<ID>,EdgeSequence>	Analyst.limitedShortestPathHopDistFiltered(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, EdgeFilter filter)	Computes the k-hop limited shortest path between two vertices.
<ID> Pair<VertexSequence<ID>,EdgeSequence>	Analyst.limitedShortestPathHopDistFiltered(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, EdgeFilter filter, VertexSequence<ID> pathVertices, EdgeSequence pathEdges)	Computes the k-hop limited shortest path between two vertices.
<ID> PgxFuture<Pair<VertexSequence<ID>,EdgeSequence>>	Analyst.limitedShortestPathHopDistFilteredAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, EdgeFilter filter)	Computes the k-hop limited shortest path between two vertices.
<ID> PgxFuture<Pair<VertexSequence<ID>,EdgeSequence>>	Analyst.limitedShortestPathHopDistFilteredAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, int maxHops, PgxMap<java.lang.Integer,PgxVertex<ID>> highDegreeVertexMapping, VertexSet<ID> highDegreeVertices, VertexProperty<ID,PgxVect<java.lang.Integer>> index, EdgeFilter filter, VertexSequence<ID> pathVertices, EdgeSequence pathEdges)	Computes the k-hop limited shortest path between two vertices.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Double>	Analyst.localClusteringCoefficient(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc)	LCC gives information about potential clustering options in a graph
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.localClusteringCoefficientAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> lcc, boolean ignoreEdgeDirection)	LCC gives information about potential clustering options in a graph
<ID> VertexProperty<ID,java.lang.Long>	Analyst.louvain(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter, int nbrPass, double tol, VertexProperty<ID,java.lang.Long> community)	Louvain can detect communities in a large graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.Long>>	Analyst.louvainAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight, int maxIter, int nbrPass, double tol, VertexProperty<ID,java.lang.Long> community)	Louvain can detect communities in a large graph relatively fast.
<ID> MatrixFactorizationModel<ID>	Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph, EdgeProperty<java.lang.Double> weight, double learningRate, double changePerStep, double lambda, int maxStep, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> features)	Matrix factorization can be used as a recommendation algorithm for bipartite graphs
<ID> MatrixFactorizationModel<ID>	Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,PgxVect<java.lang.Double>> features)	Matrix factorization can be used as a recommendation algorithm for bipartite graphs
<ID> PgxFuture<MatrixFactorizationModel<ID>>	Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph, EdgeProperty<java.lang.Double> weight, double learningRate, double changePerStep, double lambda, int maxStep, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> features)	Matrix factorization can be used as a recommendation algorithm for bipartite graphs
<ID> PgxFuture<MatrixFactorizationModel<ID>>	Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,PgxVect<java.lang.Double>> features)	Matrix factorization can be used as a recommendation algorithm for bipartite graphs
<ID> VertexProperty<ID,java.lang.Double>	Analyst.matrixFactorizationRecommendations(BipartiteGraph graph, ID user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Convenience wrapper around Analyst.matrixFactorizationRecommendations(BipartiteGraph, PgxVertex, int, VertexProperty, VertexProperty) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.matrixFactorizationRecommendations(BipartiteGraph graph, PgxVertex<ID> user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Estimate rating can be used as a prediction algorithm for bipartite graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.matrixFactorizationRecommendationsAsync(BipartiteGraph graph, PgxVertex<ID> user, int vectorLength, VertexProperty<ID,PgxVect<java.lang.Double>> feature, VertexProperty<ID,java.lang.Double> estimatedRating)	Estimate rating can be used as a prediction algorithm for bipartite graphs
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.outDegreeCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.outDegreeCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> dc)	Out-degree centrality measures the centrality of the vertices based on its degree, letting you see how a vertex influences its neighborhood
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerank(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.pagerankApproximate(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankApproximateAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	Faster, but less accurate than pagerank.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.pagerankAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> rank)	PageRank computes ranking scores based on the edges in a graph.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedPagerank(PgxGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> rank)	Personalized PageRank for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, ID v, java.math.BigDecimal d, int maxIterations, java.math.BigDecimal maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Convenience wrapper around #personalizedSalsa(BipartiteGraph, PgxVertex, BigDecimal, int, BigDecimal, VertexProperty<ID, Double>) taking a vertex ID instead of PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a vertex of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices, double d, int maxIter, double maxDiff, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices, VertexProperty<ID,java.lang.Double> salsaRank)	Personalized salsa for a set of vertices of interest.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, boolean, EdgeProperty, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, ID vertexId, java.math.BigDecimal e, java.math.BigDecimal d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Convenience wrapper around #personalizedWeightedPagerank(PgxGraph, PgxVertex, BigDecimal, BigDecimal, int, EdgeProperty, VertexProperty<ID, Double>) taking a vertex ID instead of a PgxVertex.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.personalizedWeightedPagerank(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, PgxVertex<ID> v, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized weighted pagerank for a vertex and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.personalizedWeightedPagerankAsync(PgxGraph graph, VertexSet<ID> vertices, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	Personalized pagerank for a set of vertices and weighted edges.
<ID> Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>	Analyst.radius(PgxGraph graph, Scalar<java.lang.Integer> radius, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Integer>,VertexProperty<ID,java.lang.Integer>>>	Analyst.radiusAsync(PgxGraph graph, Scalar<java.lang.Integer> radius, VertexProperty<ID,java.lang.Integer> eccentricity)	Diameter/radius gives an overview of the distances in a graph
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph, double maxDiff, int maxIter, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.salsa(BipartiteGraph graph, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph, double maxDiff, int maxIter, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.salsaAsync(BipartiteGraph graph, VertexProperty<ID,java.lang.Double> salsaRank)	SALSA computes ranking scores.
<ID> Partition<ID>	Analyst.sccKosaraju(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Kosaraju finds strongly connected components in a graph
<ID> PgxFuture<Partition<ID>>	Analyst.sccKosarajuAsync(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Kosaraju finds strongly connected components in a graph
<ID> Partition<ID>	Analyst.sccTarjan(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Tarjan finds strongly connected components in a graph
<ID> PgxFuture<Partition<ID>>	Analyst.sccTarjanAsync(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitonDistribution)	Tarjan finds strongly connected components in a graph
<ID> AllPaths<ID>	Analyst.shortestPathBellmanFord(PgxGraph graph, ID srcId, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathBellmanFord(PgxGraph, PgxVertex, EdgeProperty, VertexProperty, VertexProperty, VertexProperty) taking a vertex ID instead of PgxVertex.
<ID> AllPaths<ID>	Analyst.shortestPathBellmanFord(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bellman-ford finds multiple shortest paths at the same time
<ID> AllPaths<ID>	Analyst.shortestPathBellmanFord(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Bellman-ford finds multiple shortest paths at the same time
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathBellmanFordAsync(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bellman-ford finds multiple shortest paths at the same time
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathBellmanFordAsync(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Bellman-ford finds multiple shortest paths at the same time
<ID> AllPaths<ID>	Analyst.shortestPathBellmanFordReverse(PgxGraph graph, ID srcId, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathBellmanFordReverse(PgxGraph, PgxVertex, EdgeProperty, VertexProperty, VertexProperty, VertexProperty) taking a vertex ID instead of PgxVertex.
<ID> AllPaths<ID>	Analyst.shortestPathBellmanFordReverse(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Reversed bellman-ford finds multiple shortest paths at the same time
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathBellmanFordReverseAsync(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Reversed bellman-ford finds multiple shortest paths at the same time
<ID> PgxPath<ID>	Analyst.shortestPathDijkstra(PgxGraph graph, ID srcId, ID dstId, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathDijkstra(PgxGraph, PgxVertex, PgxVertex, EdgeProperty) taking vertex IDs instead of PgxVertex.
<ID> PgxPath<ID>	Analyst.shortestPathDijkstra(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Dijkstra is a fast algorithm for finding a shortest path in a graph
<ID> PgxPath<ID>	Analyst.shortestPathDijkstra(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected Dijkstra's algorithm is a variant of Dijkstra's algorithm that ignores edge directions.
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathDijkstraAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Dijkstra is a fast algorithm for finding a shortest path in a graph
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathDijkstraAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected Dijkstra's algorithm is a variant of Dijkstra's algorithm that ignores edge directions.
<ID> PgxPath<ID>	Analyst.shortestPathDijkstraBidirectional(PgxGraph graph, ID srcId, ID dstId, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathDijkstraBidirectional(PgxGraph, PgxVertex, PgxVertex, EdgeProperty) taking vertex IDs instead of PgxVertex.
<ID> PgxPath<ID>	Analyst.shortestPathDijkstraBidirectional(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bidirectional dijkstra is a fast algorithm for finding a shortest path in a graph
<ID> PgxPath<ID>	Analyst.shortestPathDijkstraBidirectional(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected bidirectional dijkstra is a variant of bidirectional dijkstra that ignores edge directions
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathDijkstraBidirectionalAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bidirectional dijkstra is a fast algorithm for finding a shortest path in a graph
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathDijkstraBidirectionalAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected bidirectional dijkstra is a variant of bidirectional dijkstra that ignores edge directions
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstra(PgxGraph graph, ID srcId, ID dstId, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathFilteredDijkstra(PgxGraph, PgxVertex, PgxVertex, EdgeProperty, GraphFilter) taking vertex IDs instead of PgxVertex.
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstra(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Filtered Dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstra(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected filtered djkstra is variation of the filtered djkstra's algorithm that ignores edge directions.
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathFilteredDijkstraAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Filtered Dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathFilteredDijkstraAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Undirected filtered djkstra is variation of the filtered djkstra's algorithm that ignores edge directions.
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstraBidirectional(PgxGraph graph, ID srcId, ID dstId, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathFilteredDijkstraBidirectional(PgxGraph, PgxVertex, PgxVertex, EdgeProperty, GraphFilter) taking vertex IDs instead of PgxVertex.
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstraBidirectional(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bidirectional dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> PgxPath<ID>	Analyst.shortestPathFilteredDijkstraBidirectional(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Bidirectional dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathFilteredDijkstraBidirectionalAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Bidirectional dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> PgxFuture<PgxPath<ID>>	Analyst.shortestPathFilteredDijkstraBidirectionalAsync(PgxGraph graph, PgxVertex<ID> src, PgxVertex<ID> dst, EdgeProperty<java.lang.Double> cost, GraphFilter filterExpr, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge, boolean ignoreEdgeDirection)	Bidirectional dijkstra is a fast algorithm for finding a shortest path while also filtering edges
<ID> AllPaths<ID>	Analyst.shortestPathHopDist(PgxGraph graph, ID srcId, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathHopDist(PgxGraph, PgxVertex, VertexProperty, VertexProperty, VertexProperty) taking a vertex ID instead of PgxVertex.
<ID> AllPaths<ID>	Analyst.shortestPathHopDist(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Hop distance can give a relatively fast insight on the distances in a graph
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathHopDistAsync(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Hop distance can give a relatively fast insight on the distances in a graph
<ID> AllPaths<ID>	Analyst.shortestPathHopDistReverse(PgxGraph graph, ID srcId, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Convenience wrapper around Analyst.shortestPathHopDistReverse(PgxGraph, PgxVertex, VertexProperty, VertexProperty, VertexProperty) taking a vertex ID instead of PgxVertex.
<ID> AllPaths<ID>	Analyst.shortestPathHopDistReverse(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Backwards hop distance can give a relatively fast insight on the distances in a graph
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathHopDistReverseAsync(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Backwards hop distance can give a relatively fast insight on the distances in a graph
<ID> AllPaths<ID>	Analyst.shortestPathHopDistUndirected(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Undirected hop distance can give a relatively fast insight on the distances in a graph
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathHopDistUndirectedAsync(PgxGraph graph, PgxVertex<ID> src, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Undirected hop distance can give a relatively fast insight on the distances in a graph
<ID> AllPaths<ID>	Analyst.shortestPathMultiDestinationDijkstra(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Dijkstra is a fast algorithm for finding a shortest path in a graph and goes to all destinations.
<ID> PgxFuture<AllPaths<ID>>	Analyst.shortestPathMultiDestinationDijkstraAsync(PgxGraph graph, PgxVertex<ID> src, EdgeProperty<java.lang.Double> cost, VertexProperty<ID,java.lang.Double> distance, VertexProperty<ID,PgxVertex<ID>> parent, VertexProperty<ID,PgxEdge> parentEdge)	Dijkstra is a fast algorithm for finding a shortest path in a graph and goes to all destinations.
<ID> VertexProperty<ID,java.lang.String>	Analyst.speakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.speakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSchedule(PgxGraph graph, VertexSet<ID> source, VertexProperty<ID,java.lang.Integer> topoSched)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalScheduleAsync(PgxGraph graph, VertexSet<ID> source, VertexProperty<ID,java.lang.Integer> topoSched)	Topological schedule gives an order of visit for the reachable vertices from the source
<ID> VertexProperty<ID,java.lang.Integer>	Analyst.topologicalSort(PgxGraph graph, VertexProperty<ID,java.lang.Integer> topoSort)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> PgxFuture<VertexProperty<ID,java.lang.Integer>>	Analyst.topologicalSortAsync(PgxGraph graph, VertexProperty<ID,java.lang.Integer> topoSort)	Topological sort gives an order of visit for vertices in directed acyclic graphs
<ID> VertexProperty<ID,java.lang.Double>	Analyst.vertexBetweennessCentrality(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.vertexBetweennessCentralityAsync(PgxGraph graph, VertexProperty<ID,java.lang.Double> bc)	Betweenness centrality measures the centrality of the vertices to identify important vertices for the flow of information
<ID> Partition<ID>	Analyst.wcc(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Identifying weakly connected components can be useful for clustering graph data
<ID> PgxFuture<Partition<ID>>	Analyst.wccAsync(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Identifying weakly connected components can be useful for clustering graph data
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.Double>	Analyst.weightedPagerank(PgxGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, boolean norm, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, double e, double d, int max, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>>	Analyst.weightedPagerankAsync(PgxGraph graph, EdgeProperty<java.lang.Double> weight, VertexProperty<ID,java.lang.Double> rank)	PageRank on weighted edges.
<ID> VertexProperty<ID,java.lang.String>	Analyst.weightedSpeakerListenerLabelPropagation(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.
<ID> PgxFuture<VertexProperty<ID,java.lang.String>>	Analyst.weightedSpeakerListenerLabelPropagationAsync(PgxGraph graph, VertexProperty<ID,java.lang.String> labels, int maxIter, double threshold, java.lang.String delimiter, EdgeProperty<java.lang.Double> weight)	Speaker listener label propagation can find overlaping and multiple communities in a graph relatively fast.

Method parameters in oracle.pgx.api with type arguments of type VertexProperty

Modifier and Type	Method	Description
BipartiteGraph	PgxGraph.bipartiteSubGraphFromInDegree(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName)	Blocking version of PgxGraph.bipartiteSubGraphFromInDegreeAsync(Collection, Collection, String).
BipartiteGraph	PgxGraph.bipartiteSubGraphFromInDegree(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName, java.lang.String isLeftPropName, boolean inPlace)	Blocking version of PgxGraph.bipartiteSubGraphFromInDegreeAsync(Collection, Collection, String, String, boolean).
PgxFuture<BipartiteGraph>	PgxGraph.bipartiteSubGraphFromInDegreeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName)	Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
PgxFuture<BipartiteGraph>	PgxGraph.bipartiteSubGraphFromInDegreeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName, java.lang.String isLeftPropName, boolean inPlace)	Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
BipartiteGraph	PgxGraph.bipartiteSubGraphFromLeftSet(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, VertexSet<?> vertexSet, java.lang.String newGraphName)	Blocking version of PgxGraph.bipartiteSubGraphFromLeftSetAsync(Collection, Collection, VertexSet, String).
BipartiteGraph	PgxGraph.bipartiteSubGraphFromLeftSet(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, VertexSet<?> vertexSet, java.lang.String newGraphName, java.lang.String isLeftPropName)	Blocking version of PgxGraph.bipartiteSubGraphFromLeftSetAsync(Collection, Collection, VertexSet, String, String).
PgxFuture<BipartiteGraph>	PgxGraph.bipartiteSubGraphFromLeftSetAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, VertexSet<?> vertexSet, java.lang.String newGraphName)	Create a bipartite version of this graph with the given vertex set being the left set.
PgxFuture<BipartiteGraph>	PgxGraph.bipartiteSubGraphFromLeftSetAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, VertexSet<?> vertexSet, java.lang.String newGraphName, java.lang.String isLeftPropName)	Create a bipartite version of this graph with the given vertex set being the left set.
PgxGraph	PgxGraph.clone(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName)	Blocking version of PgxGraph.cloneAsync().
PgxFuture<PgxGraph>	PgxGraph.cloneAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.lang.String newGraphName)	Creates a deep copy of this graph.
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.combineVertexPropertiesIntoVectorProperty(java.util.List<VertexProperty<ID,V>> vertexPropertyList)	Blocking version of PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List) Calls PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List) and waits for the returned PgxFuture to complete.
<ID,V> VertexProperty<ID,PgxVect<V>>	PgxGraph.combineVertexPropertiesIntoVectorProperty(java.util.List<VertexProperty<ID,V>> vertexPropertyList, java.lang.String name)	Blocking version of PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List, String) Calls PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(List, String) and waits for the returned PgxFuture to complete.
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(java.util.List<VertexProperty<ID,V>> vertexPropertyList)	Takes a list of scalar vertex properties of same type and creates a new vertex vector property by combining them.
<ID,V> PgxFuture<VertexProperty<ID,PgxVect<V>>>	PgxGraph.combineVertexPropertiesIntoVectorPropertyAsync(java.util.List<VertexProperty<ID,V>> vertexPropertyList, java.lang.String name)	Takes a list of scalar vertex properties of same type and creates a new vertex vector property by combining them.
B	MutationStrategyBuilder.dropVertexProperties(java.util.Collection<VertexProperty<?,?>> vertexProperties)	Set vertex properties that will be dropped after the mutation.
PgxGraph	PgxGraph.filter(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, GraphFilter graphFilter, java.lang.String newGraphName)	Blocking version of PgxGraph.filterAsync(Collection, Collection, GraphFilter, String).
PgxFuture<PgxGraph>	PgxGraph.filterAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, GraphFilter graphFilter, java.lang.String newGraphName)	Create a subgraph of this graph.
void	PgxGraph.publish(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps)
PgxFuture<java.lang.Void>	PgxGraph.publishAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps)	Publishes the graph so It can be shared between sessions.
void	PgxGraph.publishWithSnapshots(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps)	Blocking version of PgxGraph.publishWithSnapshotsAsync(Collection, Collection).
PgxFuture<java.lang.Void>	PgxGraph.publishWithSnapshotsAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps)	Publishes the graph and all its snapshots so they can be shared between sessions.
B	MutationStrategyBuilder.setKeptVertexProperties(java.util.Collection<VertexProperty<?,?>> propsToKeep)	Set vertex properties that will be kept By default (without calling this) all vertexProperties will be kept.
PgxGraph	PgxGraph.simplify(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.MultiEdges multiEdges, PgxGraph.SelfEdges selfEdges, PgxGraph.TrivialVertices trivialVertices, PgxGraph.Mode mode, java.lang.String newGraphName)	Blocking version of PgxGraph.simplifyAsync(Collection, Collection, MultiEdges, SelfEdges, TrivialVertices, Mode, String).
PgxFuture<PgxGraph>	PgxGraph.simplifyAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.MultiEdges multiEdges, PgxGraph.SelfEdges selfEdges, PgxGraph.TrivialVertices trivialVertices, PgxGraph.Mode mode, java.lang.String newGraphName)	Create a simplified version of a graph.
PgxGraph	PgxGraph.sortByDegree(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.SortOrder sortOrder, PgxGraph.Degree degree, PgxGraph.Mode mode, java.lang.String newGraphName)	Blocking version of PgxGraph.sortByDegreeAsync(Collection, Collection, SortOrder, Degree, Mode, String).
PgxFuture<PgxGraph>	PgxGraph.sortByDegreeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.SortOrder sortOrder, PgxGraph.Degree degree, PgxGraph.Mode mode, java.lang.String newGraphName)	Create a sorted version of a graph and all its properties.
PgxGraph	PgxGraph.sparsify(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, double e, java.lang.String newGraphName)	Blocking version of PgxGraph.sparsifyAsync(Collection, Collection, double, String).
PgxFuture<PgxGraph>	PgxGraph.sparsifyAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, double e, java.lang.String newGraphName)	Sparsifies the given graph and returns a new graph with less edges.
FileGraphConfig	PgxGraph.store(Format targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(Format, String, int, Collection, Collection, boolean).
FileGraphConfig	PgxGraph.store(Format targetFormat, java.lang.String targetPath, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(Format, String, Collection, Collection, boolean).
FileGraphConfig	PgxGraph.store(Format targetFormat, FileGraphStoringConfig storingConfig, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(Format, FileGraphStoringConfig, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, String, int, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, String, int, Set, Set, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.lang.String targetBasePath, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, String, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.lang.String targetBasePath, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, String, Set, Set, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.util.Map<java.lang.String,FileGraphStoringConfig> vertexStoringConfigs, java.util.Map<java.lang.String,FileGraphStoringConfig> edgeStoringConfigs, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, Map, Map, Collection, Collection, boolean).
PartitionedGraphConfig	PgxGraph.store(ProviderFormat targetFormat, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Map<java.lang.String,FileGraphStoringConfig> vertexStoringConfigs, java.util.Map<java.lang.String,FileGraphStoringConfig> edgeStoringConfigs, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Blocking version of PgxGraph.storeAsync(ProviderFormat, Set, Set, Map, Map, Collection, Collection, boolean).
PgxFuture<FileGraphConfig>	PgxGraph.storeAsync(Format targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxFuture<FileGraphConfig>	PgxGraph.storeAsync(Format targetFormat, java.lang.String targetPath, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format on a file system.
PgxFuture<FileGraphConfig>	PgxGraph.storeAsync(Format targetFormat, FileGraphStoringConfig storingConfig, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.lang.String targetBasePath, int numPartitions, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.lang.String targetBasePath, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.lang.String targetBasePath, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.util.Map<java.lang.String,FileGraphStoringConfig> vertexStoringConfigs, java.util.Map<java.lang.String,FileGraphStoringConfig> edgeStoringConfigs, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxFuture<PartitionedGraphConfig>	PgxGraph.storeAsync(ProviderFormat targetFormat, java.util.Set<java.lang.String> vertexProvidersToStore, java.util.Set<java.lang.String> edgeProvidersToStore, java.util.Map<java.lang.String,FileGraphStoringConfig> vertexStoringConfigs, java.util.Map<java.lang.String,FileGraphStoringConfig> edgeStoringConfigs, java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, boolean overwrite)	Stores this graph in a given file format in multiple partitions on a file system.
PgxGraph	PgxGraph.transpose(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.util.Map<java.lang.String,java.lang.String> edgeLabelMapping, PgxGraph.Mode mode, java.lang.String newGraphName)	Blocking version of PgxGraph.transposeAsync(Collection, Collection, Map, Mode, String)
PgxFuture<PgxGraph>	PgxGraph.transposeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, java.util.Map<java.lang.String,java.lang.String> edgeLabelMapping, PgxGraph.Mode mode, java.lang.String newGraphName)	Creates a transpose of this graph.
PgxGraph	PgxGraph.undirect(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.MultiEdges multiEdges, PgxGraph.SelfEdges selfEdges, PgxGraph.TrivialVertices trivialVertices, PgxGraph.Mode mode, java.lang.String newGraphName)	Blocking version of PgxGraph.undirectAsync(Collection, Collection, MultiEdges, SelfEdges, Mode, String).
PgxFuture<PgxGraph>	PgxGraph.undirectAsync(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, PgxGraph.MultiEdges multiEdges, PgxGraph.SelfEdges selfEdges, PgxGraph.Mode mode, java.lang.String newGraphName)	Convenience method to create for PgxGraph.undirectAsync(MutationStrategy).

Uses of VertexProperty in oracle.pgx.api.mllib

Methods in oracle.pgx.api.mllib that return VertexProperty

Modifier and Type	Method	Description
VertexProperty<ID,java.lang.Float>	GnnExplanation.getVertexImportanceProperty()	Gets the vertex property that contains the computed vertex importance.

Methods in oracle.pgx.api.mllib that return types with arguments of type VertexProperty

Modifier and Type	Method	Description
java.util.Map<VertexProperty<ID,?>,java.lang.Float>	GnnExplanation.getVertexFeatureImportance()	Gets the feature importances as a map from property to importance value.