Uses of Class
oracle.pgx.api.Partition

Packages that use Partition

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

Uses of Partition in oracle.pgx.api

Methods in oracle.pgx.api that return Partition

Modifier and Type	Method	Description
<ID> Partition<ID>	Analyst.communitiesConductanceMinimization(PgxGraph graph)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> Partition<ID>	Analyst.communitiesConductanceMinimization(PgxGraph graph, int maxIterations)	Soman and Narang can find communities in a graph taking weighted edges into account
<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> 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> Partition<ID>	Analyst.communitiesLabelPropagation(PgxGraph graph)	Label propagation can find communities in a graph relatively fast
<ID> Partition<ID>	Analyst.communitiesLabelPropagation(PgxGraph graph, int maxIterations)	Label propagation can find communities in a graph relatively fast
<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> Partition<ID>	PgxGraph.createComponents(VertexProperty<ID,java.lang.Long> components, long numComponents)	Blocking version of PgxGraph.createComponentsAsync(VertexProperty, long).
<ID> Partition<ID>	Analyst.sccKosaraju(PgxGraph graph)	Kosaraju finds strongly connected components in a graph
<ID> Partition<ID>	Analyst.sccKosaraju(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Kosaraju finds strongly connected components in a graph
<ID> Partition<ID>	Analyst.sccTarjan(PgxGraph graph)	Tarjan 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> Partition<ID>	Analyst.wcc(PgxGraph graph)	Identifying weakly connected components can be useful for clustering graph data
<ID> Partition<ID>	Analyst.wcc(PgxGraph graph, VertexProperty<ID,java.lang.Long> partitionDistribution)	Identifying weakly connected components can be useful for clustering graph data

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

Modifier and Type	Method	Description
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesConductanceMinimizationAsync(PgxGraph graph)	Soman and Narang can find communities in a graph taking weighted edges into account
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesConductanceMinimizationAsync(PgxGraph graph, int max)	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> 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> PgxFuture<Partition<ID>>	Analyst.communitiesLabelPropagationAsync(PgxGraph graph)	Label propagation can find communities in a graph relatively fast
<ID> PgxFuture<Partition<ID>>	Analyst.communitiesLabelPropagationAsync(PgxGraph graph, int maxIterations)	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> 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> PgxFuture<Partition<ID>>	Analyst.sccKosarajuAsync(PgxGraph graph)	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> PgxFuture<Partition<ID>>	Analyst.sccTarjanAsync(PgxGraph graph)	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> PgxFuture<Partition<ID>>	Analyst.wccAsync(PgxGraph graph)	Identifying weakly connected components can be useful for clustering graph data
<ID> PgxFuture<Partition<ID>>	Analyst.wccAsync(PgxGraph graph, java.lang.String partitonDistributionName)
<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

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

Modifier and Type	Method	Description
<ID> Scalar<java.lang.Double>	Analyst.conductance(PgxGraph graph, Partition<ID> partition, long partitionIndex)	Conductance assesses the quality of a partition in a graph
<ID> Scalar<java.lang.Double>	Analyst.conductance(PgxGraph graph, Partition<ID> partition, long partitionIndex, Scalar<java.lang.Double> conductance)	Conductance assesses the quality of a partition in a graph
<ID> PgxFuture<Scalar<java.lang.Double>>	Analyst.conductanceAsync(PgxGraph graph, Partition<ID> partition, long partitionIndex)	Conductance assesses the quality of a partition in a graph
<ID> PgxFuture<Scalar<java.lang.Double>>	Analyst.conductanceAsync(PgxGraph graph, Partition<ID> partition, long partitionIndex, Scalar<java.lang.Double> conductance)	Conductance assesses the quality of a partition in a graph
<ID> Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>	Analyst.partitionConductance(PgxGraph graph, Partition<ID> partition)	Partition conductance assesses the quality of many partitions in a graph
<ID> Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>	Analyst.partitionConductance(PgxGraph graph, Partition<ID> partition, Scalar<java.lang.Double> avgConductance, Scalar<java.lang.Double> minConductance)	Partition conductance assesses the quality of many partitions in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>>	Analyst.partitionConductanceAsync(PgxGraph graph, Partition<ID> partition)	Partition conductance assesses the quality of many partitions in a graph
<ID> PgxFuture<Pair<Scalar<java.lang.Double>,Scalar<java.lang.Double>>>	Analyst.partitionConductanceAsync(PgxGraph graph, Partition<ID> partition, Scalar<java.lang.Double> avgConductance, Scalar<java.lang.Double> minConductance)	Partition conductance assesses the quality of many partitions in a graph
<ID> Scalar<java.lang.Double>	Analyst.partitionModularity(PgxGraph graph, Partition<ID> partition)	Modularity summarizes information about the quality of components in a graph
<ID> Scalar<java.lang.Double>	Analyst.partitionModularity(PgxGraph graph, Partition<ID> partition, Scalar<java.lang.Double> modularity)	Modularity summarizes information about the quality of components in a graph
<ID> PgxFuture<Scalar<java.lang.Double>>	Analyst.partitionModularityAsync(PgxGraph graph, Partition<ID> partition)	Modularity summarizes information about the quality of components in a graph
<ID> PgxFuture<Scalar<java.lang.Double>>	Analyst.partitionModularityAsync(PgxGraph graph, Partition<ID> partition, java.lang.String modularityName)
<ID> PgxFuture<Scalar<java.lang.Double>>	Analyst.partitionModularityAsync(PgxGraph graph, Partition<ID> partition, Scalar<java.lang.Double> modularity)	Modularity summarizes information about the quality of components in a graph