Uses of Interface
gov.sandia.cognition.graph.DirectedNodeEdgeGraph

Packages that use DirectedNodeEdgeGraph

Package	Description
gov.sandia.cognition.graph
gov.sandia.cognition.graph.community
gov.sandia.cognition.graph.inference

Uses of DirectedNodeEdgeGraph in gov.sandia.cognition.graph

Subinterfaces of DirectedNodeEdgeGraph in gov.sandia.cognition.graph

Modifier and Type	Interface and Description
interface	DirectedWeightedNodeEdgeGraph<NodeNameType> Adds the necessary methods for a graph with weighted edges.

Classes in gov.sandia.cognition.graph that implement DirectedNodeEdgeGraph

Modifier and Type	Class and Description
class	DenseMemoryGraph<NodeNameType> Most basic-est of graph types.
class	WeightedDenseMemoryGraph<NodeNameType> Implementation for a weighted graph type

Methods in gov.sandia.cognition.graph that return DirectedNodeEdgeGraph

Modifier and Type	Method and Description
static <NodeType> DirectedNodeEdgeGraph<NodeType>	GraphUtil.deepCopy(DirectedNodeEdgeGraph<NodeType> src) Makes a deep copy of the input graph, matching implementation of the interface.

Methods in gov.sandia.cognition.graph with parameters of type DirectedNodeEdgeGraph

Modifier and Type	Method and Description
static <NodeType> DirectedNodeEdgeGraph<NodeType>	GraphUtil.deepCopy(DirectedNodeEdgeGraph<NodeType> src) Makes a deep copy of the input graph, matching implementation of the interface.

Constructors in gov.sandia.cognition.graph with parameters of type DirectedNodeEdgeGraph

Constructor and Description
GraphMetrics(DirectedNodeEdgeGraph<NodeNameType> graph) Initialize this as an empty metrics class surrounding the input graph.
GraphWalker(DirectedNodeEdgeGraph<NodeNameType> graph, GraphWalker.NextNodeSelector<NodeNameType> selector) Initializes a new graph walker with as-yet empty metrics
GraphWalker(DirectedNodeEdgeGraph<NodeNameType> graph, GraphWalker.NextNodeSelector<NodeNameType> selector, GraphMetrics<NodeNameType> metrics) Initializes a new graph walker with the input values

Uses of DirectedNodeEdgeGraph in gov.sandia.cognition.graph.community

Methods in gov.sandia.cognition.graph.community with parameters of type DirectedNodeEdgeGraph

Modifier and Type	Method and Description
static <NodeNameType> double	CommunityMetrics.computeConductance(DirectedNodeEdgeGraph<NodeNameType> graph, java.util.Set<NodeNameType> community)
static <NodeNameType> double	CommunityMetrics.computeGraphPermanance(DirectedNodeEdgeGraph<NodeNameType> graph, GraphMetrics<NodeNameType> metrics, NodePartitioning<NodeNameType> partitions) Computes the average permanence for the partitioning of the entire graph
static <NodeNameType> double	CommunityMetrics.computeModularity(DirectedNodeEdgeGraph<NodeNameType> graph, NodePartitioning<NodeNameType> communities) Computes the modularity of the input graph into the input set of communities.
static <NodeNameType> double	CommunityMetrics.computeModularity(DirectedNodeEdgeGraph<NodeNameType> graph, java.util.Set<java.util.Set<NodeNameType>> communities) Computes the modularity of the input graph into the input set of communities.
static <NodeNameType> double	CommunityMetrics.computeOneNodePermanence(GraphMetrics<NodeNameType> metrics, NodePartitioning<NodeNameType> partitions, NodeNameType node, DirectedNodeEdgeGraph<NodeNameType> graph)
static <NodeNameType> double	CommunityMetrics.computeOneNodePermanenceById(GraphMetrics<NodeNameType> metrics, NodePartitioning<NodeNameType> partitions, int nodeId, DirectedNodeEdgeGraph<NodeNameType> graph) Computes the permanence for one node in the graph.

Constructors in gov.sandia.cognition.graph.community with parameters of type DirectedNodeEdgeGraph

Constructor and Description
Louvain(DirectedNodeEdgeGraph<NodeNameType> graph) Initializes the internal Louvain datatypes that store the necessaries to run Louvain on the input graph.
Louvain(DirectedNodeEdgeGraph<NodeNameType> graph, int maxNumPasses, double minModularityGain) Initializes the internal Louvain datatypes that store the necessaries to run Louvain on the input graph.
Permanence(DirectedNodeEdgeGraph<NodeNameType> graph, int maxNumPasses, double minPermanenceGain) Initialize the class with the input graph and parameters
PersonalizedPageRank(DirectedNodeEdgeGraph<NodeNameType> graph) Initializes all of the internal data-structures for the input graph.
PersonalizedPageRank(DirectedNodeEdgeGraph<NodeNameType> graph, double tolerance) Initializes all of the internal data-structures for the input graph.

Uses of DirectedNodeEdgeGraph in gov.sandia.cognition.graph.inference

Methods in gov.sandia.cognition.graph.inference with parameters of type DirectedNodeEdgeGraph

Modifier and Type	Method and Description
double	GraphWrappingEnergyFunction.PotentialHandler.getPairwisePotential(DirectedNodeEdgeGraph<NodeNameType> graph, int edgeId, LabelType ilabel, LabelType jlabel) Provide the pairwise potential for the specified edge
java.util.List<LabelType>	GraphWrappingEnergyFunction.PotentialHandler.getPossibleLabels(DirectedNodeEdgeGraph<NodeNameType> graph, int nodeId) Get the possible labels for the specified node
double	GraphWrappingEnergyFunction.PotentialHandler.getUnaryPotential(DirectedNodeEdgeGraph<NodeNameType> graph, int i, LabelType label, LabelType assignedLabel) Provide the unary potential for the specified node

Constructors in gov.sandia.cognition.graph.inference with parameters of type DirectedNodeEdgeGraph

Constructor and Description
GraphWrappingEnergyFunction(DirectedNodeEdgeGraph<NodeNameType> graph, GraphWrappingEnergyFunction.PotentialHandler<LabelType,NodeNameType> handler) Creates a new instance of this class containing the input graph (shallow copy -- don't change it after this!) and the handler for problem-specific details (also only a shallow copy).