Uses of Class
oracle.pgx.common.Pair

Packages that use Pair

Package	Description
oracle.pgx.api	This package contains the main Java APIs.

Uses of Pair in oracle.pgx.api

Methods in oracle.pgx.api that return Pair

Modifier and Type	Method and Description
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter filter, VertexFilter navigator) Blocking version of Analyst.filteredBfsAsync(PgxGraph, PgxVertex, VertexFilter, VertexFilter).
<ID> Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>	Analyst.filteredBfs(PgxGraph graph, PgxVertex<ID> root, VertexFilter filter, VertexFilter navigator, boolean initWithInf) Blocking version of Analyst.filteredBfsAsync(PgxGraph, PgxVertex, VertexFilter, VertexFilter, boolean).
<ID> Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>	Analyst.hits(PgxGraph graph, int max) Blocking version of Analyst.hitsAsync(PgxGraph, int).
<ID> Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>	Analyst.kcore(PgxGraph graph, int minCore, int maxCore) Blocking version of Analyst.kcoreAsync(PgxGraph, int, int).
<ID> Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>	Analyst.partitionConductance(PgxGraph graph, Partition<ID> components) Blocking version of Analyst.partitionModularityAsync(PgxGraph, Partition).
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.salsa(BipartiteGraph graph, int k) Blocking version of Analyst.salsaAsync(BipartiteGraph, int).
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.salsa(BipartiteGraph graph, int k, double maxDiff, double d, int maxIter) Blocking version of Analyst.salsaAsync(BipartiteGraph, int, double, double, int).
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.whomToFollow(PgxGraph graph, ID vertexId, int max) Convenience wrapper around Analyst.whomToFollow(PgxGraph, PgxVertex, int) taking a vertex ID instead of a PgxVertex.
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.whomToFollow(PgxGraph graph, ID vertexId, int max, int circleOfTrustSize, int randomWalkSteps, double randomWalkResetProbablitiy, double salsaDampingFactor, int salsaMaxIterations, double salsaMaxDiff) Convenience wrapper around Analyst.whomToFollow(PgxGraph, PgxVertex, int, int, int, double, double, int, double) taking a vertex ID instead of a PgxVertex.
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.whomToFollow(PgxGraph graph, PgxVertex<ID> vertex, int max) Blocking version of Analyst.whomToFollowAsync(PgxGraph, PgxVertex, int).
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>>	Analyst.whomToFollow(PgxGraph graph, PgxVertex<ID> vertex, int max, int circleOfTrustSize, int randomWalkSteps, double randomWalkResetProbablitiy, double salsaDampingFactor, int salsaMaxIterations, double salsaMaxDiff) Blocking version of Analyst.whomToFollowAsync(PgxGraph, PgxVertex, int, int, int, double, double, int, double).

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

Modifier and Type	Method and Description
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter filter, VertexFilter navigator)
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Integer>,VertexProperty<ID,PgxVertex<ID>>>>	Analyst.filteredBfsAsync(PgxGraph graph, PgxVertex<ID> root, VertexFilter filter, VertexFilter navigator, boolean initWithInf)
<ID> PgxFuture<Pair<VertexProperty<ID,java.lang.Double>,VertexProperty<ID,java.lang.Double>>>	Analyst.hitsAsync(PgxGraph graph, int max) This is the Hyperlink-Induced Topic Search (HITS) algorithm, also known as Hubs and Authorities..
<ID> PgxFuture<Pair<Scalar<java.lang.Long>,VertexProperty<ID,java.lang.Long>>>	Analyst.kcoreAsync(PgxGraph graph, int minCore, int maxCore) Computes the k-core decomposition of the graph.
<ID> PgxFuture<Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>>	Analyst.partitionConductanceAsync(PgxGraph graph, Partition<ID> partition) Compute the average and minimum conductance among all partitions in a vertex partition.
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>>	Analyst.salsaAsync(BipartiteGraph graph, int k) Convenience method around Analyst.salsaAsync(BipartiteGraph, int, double, double, int) using maxDiff = 0.01 d = 0.85 maxIter = 1000
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>>	Analyst.salsaAsync(BipartiteGraph graph, int k, double maxDiff, double d, int maxIter) SALSA recommendation algorithm.
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>>	Analyst.whomToFollowAsync(PgxGraph graph, PgxVertex<ID> vertex, int max) Convenience method around Analyst.whomToFollowAsync(PgxGraph, PgxVertex, int, int, int, double, double, int, double) using circleOfTrustSize = 500 randomWalkSteps = 50000 randomWalkResetProbablitiy = 0.15 salsaDampingFactor = 0.85 salsaMaxIterations = 1000 salsaMaxDiff = 0.01
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>>	Analyst.whomToFollowAsync(PgxGraph graph, PgxVertex<ID> vertex, int max, int circleOfTrustSize, int randomWalkSteps, double randomWalkResetProbablitiy, double salsaDampingFactor, int salsaMaxIterations, double salsaMaxDiff) The Who to Follow recommendation algorithm by Twitter, Inc.