Uses of Interface
nz.ac.waikato.mcennis.rat.graph.Graph

Packages that use Graph

nz.ac.waikato.bibliography
nz.ac.waikato.bibliography.algorithm
nz.ac.waikato.mcennis.rat.dataAquisition
nz.ac.waikato.mcennis.rat.graph
nz.ac.waikato.mcennis.rat.graph.algorithm
nz.ac.waikato.mcennis.rat.graph.algorithm.aggregators
nz.ac.waikato.mcennis.rat.graph.algorithm.clustering
nz.ac.waikato.mcennis.rat.graph.algorithm.collaborativefiltering
nz.ac.waikato.mcennis.rat.graph.algorithm.evaluation
nz.ac.waikato.mcennis.rat.graph.algorithm.machinelearning
nz.ac.waikato.mcennis.rat.graph.algorithm.prestige
nz.ac.waikato.mcennis.rat.graph.algorithm.reusablecores
nz.ac.waikato.mcennis.rat.graph.algorithm.similarity
nz.ac.waikato.mcennis.rat.graph.algorithm.transformToArray
nz.ac.waikato.mcennis.rat.graph.algorithm.visual
nz.ac.waikato.mcennis.rat.graph.persistence
nz.ac.waikato.mcennis.rat.graph.property
nz.ac.waikato.mcennis.rat.parser.xmlHandler
nz.ac.waikato.mcennis.rat.scheduler

Uses of Graph in nz.ac.waikato.bibliography

Methods in nz.ac.waikato.bibliography that return Graph

Graph	LoadBibliographyAndClass.get()
Graph	LoadBibliographyXML.get()

Methods in nz.ac.waikato.bibliography with parameters of type Graph

void	LoadBibliographyAndClass.set(Graph g)
void	LoadBibliographyXML.set(Graph g)

Uses of Graph in nz.ac.waikato.bibliography.algorithm

Methods in nz.ac.waikato.bibliography.algorithm with parameters of type Graph

void	OutputBibliographyXML.execute(Graph g)
void	OutputBridgesByCluster.execute(Graph g)
void	OutputDifference.execute(Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.dataAquisition

Methods in nz.ac.waikato.mcennis.rat.dataAquisition that return Graph

Graph	CrawlLastFM.get()
Graph	CrawlLiveJournal.get()
Graph	DataAquisition.get() Obtain a reference to the graph this object holds
Graph	FileReader.get()
Graph	FileReader2Pass.get()
Graph	GetArtistTags.get()
Graph	LastFMTagFileReader.get()
Graph	ReadAudioFiles.get()
Graph	ReadLastFMProfileFile.get()
Graph	ReadMemGraphXMLFile.get()

Methods in nz.ac.waikato.mcennis.rat.dataAquisition with parameters of type Graph

void	CrawlLastFM.set(Graph g)
void	CrawlLiveJournal.set(Graph g)
void	DataAquisition.set(Graph g) Set the graph to be populated by this object
void	FileReader.set(Graph g)
void	FileReader2Pass.set(Graph g)
void	GetArtistTags.set(Graph g)
void	LastFMTagFileReader.set(Graph g)
void	ReadAudioFiles.set(Graph g)
void	ReadLastFMProfileFile.set(Graph g)
void	ReadMemGraphXMLFile.set(Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph

Classes in nz.ac.waikato.mcennis.rat.graph that implement Graph

class	Clique Class for describing a completely connected subgraph.
class	DerbyGraph Class that implements all the JDBC code for a Derby backed graph model.
class	MemGraph A graph object that is held entirely in memory
class	NullGraph Class that retains no information and implements null operations on every node.
class	PostgresqlGraph Sub-class of the DerbyGraph Object to work with postgresql databases
class	Tree Class for describing a tree.
class	UserIDList Class that records only those users that initiate links.
class	UserList Aquires a list of all actors that have been seen.

Methods in nz.ac.waikato.mcennis.rat.graph that return Graph

Graph	GraphFactory.create(java.util.Properties args) Create a graph object without directly exposing the underlying types Types of graphs are pulled from the "Graph" key with "GraphID" for their unique ID.
Graph[]	Clique.getChildren() Leaf graph only, so intentionally null
Graph[]	DerbyGraph.getChildren() FIXME: Does not properly access database
Graph[]	Graph.getChildren() Returns the children graphs of this object or null if none exist
Graph[]	MemGraph.getChildren()
Graph[]	NullGraph.getChildren()
Graph[]	UserIDList.getChildren()
Graph[]	UserList.getChildren()
Graph	Clique.getChildren(java.lang.String id) Leaf graph only, so intentionally null
Graph	DerbyGraph.getChildren(java.lang.String id) FIXME: Does not properly access database
Graph	Graph.getChildren(java.lang.String id) Returns the children graph with the given id or null if there is not a child with that name.
Graph	MemGraph.getChildren(java.lang.String id)
Graph	NullGraph.getChildren(java.lang.String id)
Graph	UserIDList.getChildren(java.lang.String id)
Graph	UserList.getChildren(java.lang.String id)
Graph[]	GraphIndex.getGraph(Actor a) Return an array of all graphs that contain the actor or null if no indexed graph contains the actor.
Graph	GraphIndex.getGraph(java.lang.String s) Returns the graph with the given ID or null if no graph with this ID is indexed.
Graph[]	Clique.getGraphs(java.util.regex.Pattern pattern)
Graph[]	DerbyGraph.getGraphs(java.util.regex.Pattern pattern) FIXME: does not return graphs properly
Graph[]	Graph.getGraphs(java.util.regex.Pattern pattern) Creates an array of graph objects.
Graph[]	MemGraph.getGraphs(java.util.regex.Pattern pattern)
Graph[]	NullGraph.getGraphs(java.util.regex.Pattern pattern)
Graph[]	UserIDList.getGraphs(java.util.regex.Pattern pattern)
Graph[]	UserList.getGraphs(java.util.regex.Pattern pattern)
Graph	Clique.getParent()
Graph	DerbyGraph.getParent() FIXME: Does not properly access database
Graph	Graph.getParent() Returns the parent graph of this object or null if this is a root graph
Graph	MemGraph.getParent()
Graph	NullGraph.getParent()
Graph	UserIDList.getParent()
Graph	UserList.getParent()
Graph	Clique.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor) Intentionally null since this graph can have no children.
Graph	DerbyGraph.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor) FIXME: write subgraph code for Derby Graph
Graph	Graph.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor) Creates a new graph from the current graph using the Properties props containing the actors actor and all links that link between actors in actor.
Graph	MemGraph.getSubGraph(java.util.Properties props, java.util.Set<Actor> actorList)
Graph	NullGraph.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor)
Graph	UserIDList.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor)
Graph	UserList.getSubGraph(java.util.Properties props, java.util.Set<Actor> actor)
Graph[]	Clique.getSubGraph(Query q)
Graph[]	DerbyGraph.getSubGraph(Query q)
Graph[]	Graph.getSubGraph(Query q) Return newly created subgraphs that matches the given query FIXME: Currently not implemented in any graph.
Graph[]	MemGraph.getSubGraph(Query q)
Graph[]	NullGraph.getSubGraph(Query q)
Graph[]	UserIDList.getSubGraph(Query q)
Graph[]	UserList.getSubGraph(Query q)

Methods in nz.ac.waikato.mcennis.rat.graph with parameters of type Graph

void	Clique.add(Graph g)
void	DerbyGraph.add(Graph g)
void	Graph.add(Graph g) Add a graph (g) to the graph.
void	MemGraph.add(Graph uid)
void	NullGraph.add(Graph g)
void	UserIDList.add(Graph g)
void	UserList.add(Graph g)
void	GraphIndex.addActor(Actor a, Graph g) Add a reference between a graph and an actor.
void	Clique.addChild(Graph g) Leaf graph only, so intentionally null
void	DerbyGraph.addChild(Graph g) FIXME: Does not save to database
void	Graph.addChild(Graph g) Set the given graph to be a child of the current graph.
void	MemGraph.addChild(Graph g)
void	NullGraph.addChild(Graph g)
void	UserIDList.addChild(Graph g)
void	UserList.addChild(Graph g)
void	GraphIndex.addGraph(Graph g) Adds a graph reference to the object
java.util.HashSet<Clique>	Clique.expand(Graph g) Given this clique (and the graph) - generate all cliques of one bigger size that have this clique as a subclique where the new actor is greater (by compareTo) than any other actor in the clique.

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm with parameters of type Graph

protected void	AddGeodesicProperties.addDiameter(Graph g) Diamter defined as the longest geodesic path.
protected void	AddGeodesicProperties.addInEccentricity(Graph g)
protected void	AddGeodesicProperties.addOutEccentricity(Graph g)
void	AddDegreeGraphProperties.calculateAbsoluteDensity(Graph g) Calculate the density of the graph using the absolute value of all link strengths
void	AddDegreeGraphProperties.calculateDensity(Graph g) Calculate the density of the graph
void	AddDegreeGraphProperties.calculateInDegree(Graph g) Calculate the in-degree of each node.
void	AddDegreeGraphProperties.calculateOutDegree(Graph g) Calculate the out-degree of each node.
protected abstract void	OptimizedPathBase.doCleanup(PathNode[] path, Graph g) Any additional calculations to be performed before control returns to the scheduler
void	AddBasicGeodesicPaths.execute(Graph g) Calculate each path using a variation of Djikstra's algorithm for spanning trees with modification for recording multiple same-cost minimum paths.
void	AddBasicInterestLink.execute(Graph g) Reads a property list on each actors and calculate all similar actors connected with a given link set.
void	AddDegreeGraphProperties.execute(Graph g)
void	AddGeodesicProperties.execute(Graph g) Calculates properties of a node: (In/Out) Eccentricity - Wasserman and Faust p111 - modified for directional links Diameter - Wasserman and Faust p111.
void	AddMusicLinks.execute(Graph g) Execute the algorithm against the current graph
void	AddMusicRecommendations.execute(Graph g) Build a set of music recommendations based on existing links
void	AddMusicReferences.execute(Graph g) Takes interest links, determines which are artists, then creates an artist actor and links the user to this artist.
void	Algorithm.execute(Graph g) execute the algorithm against the given graph
void	Difference.execute(Graph g)
void	ExtractMusicCoverage.execute(Graph g) Generate a list of all artists linked to in this graph.
void	IdentifyBridges.execute(Graph g)
void	OptimizedPathBase.execute(Graph g) Generates a spanning tree for a given actor.
void	PrincipalComponentsAnalysis.execute(Graph g)
void	RankingProperties.execute(Graph g)
void	TrimEdgeUsers.execute(Graph g) Remove actors without outgoing links.
protected Actor[]	AddDegreeGraphProperties.getActor(Graph g)
protected void	AddBasicGeodesicPaths.nextStepNodes(Graph g) Place node expansion into node expansion map.
protected void	AddBasicGeodesicPaths.processVectors(Graph g) for each vector in the list process end node for each geodesic

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.aggregators

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.aggregators with parameters of type Graph

weka.core.Instances	AggregateLinks.buildInstances(Graph g)
void	AggregateByGraph.execute(Graph g)
void	AggregateByLinkProperty.execute(Graph g)
void	AggregateLinks.execute(Graph g)
void	AggregateOnActor.execute(Graph g)
void	CombineProperty.execute(Graph g)
void	FromGraphToActor.execute(Graph g)
void	PropertyToLink.execute(Graph g)
protected java.util.HashMap<Actor,java.lang.Double>	AggregateByLinkProperty.getMap(Actor tag, java.util.HashSet<Actor> total, Graph g)
protected java.util.HashMap<Actor,java.lang.Double>	AggregateLinks.getMap(Actor tag, java.util.HashSet<Actor> total, Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.clustering

Fields in nz.ac.waikato.mcennis.rat.graph.algorithm.clustering declared as Graph

Graph

NaiveImplementClique.SubGroup.g

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.clustering with parameters of type Graph

protected void	NormanGirvanEdgeBetweenessClustering.calculateBetweeness(Graph root, Duples<java.lang.Double,Link>[] orderedBetweeness)
void	BicomponentClusterer.execute(Graph g)
void	EnumerateMaximalCliques.execute(Graph g)
void	FindStronglyConnectedComponents.execute(Graph g)
void	FindWeaklyConnectedComponents.execute(Graph g)
void	NaiveImplementClique.execute(Graph g) A naive implementation of the clique algorithm for runtime comparison to the optimized version EnumerateMaximalCliques
void	NormanGirvanEdgeBetweenessClustering.execute(Graph g)
void	TraditionalEdgeBetweenessClustering.execute(Graph g)
void	WekaClassifierClusterer.execute(Graph g)
void	WekaProbablisticClusterer.execute(Graph g)
protected void	BicomponentClusterer.findBiconnectedComponents(Graph g, Actor v, java.util.Set<java.util.Set<Actor>> bicomponents) Stores, in bicomponents, all the biconnected components that are reachable from v.
protected void	FindWeaklyConnectedComponents.getComponent(Actor seed, Graph g)
protected void	FindWeaklyConnectedComponents.getGraph(Graph g)
protected Link[]	BicomponentClusterer.getLinks(Graph g, Actor v)
protected void	TraditionalEdgeBetweenessClustering.splitGraph(Graph base, int top, java.lang.String prefix)
protected void	NormanGirvanEdgeBetweenessClustering.splitGraph(Graph base, java.lang.String prefix)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.collaborativefiltering

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.collaborativefiltering with parameters of type Graph

protected void	Item2Item.createCorrelation(Graph g, Actor u, double strength, Actor a)
protected void	Item2Item.createRecommendation(Graph g, Actor u, double strength, Actor a)
protected void	User2User.doRecommendation(Graph g, Actor left, cern.colt.matrix.DoubleMatrix1D leftArray, Actor right, cern.colt.matrix.DoubleMatrix1D rightArray, double sim)
void	AssociativeMining.execute(Graph g)
void	Item2Item.execute(Graph g)
void	User2User.execute(Graph g)
protected java.util.HashSet<Actor>	AssociativeMining.getGiven(Graph g, Actor u)
protected cern.colt.matrix.DoubleMatrix1D	User2User.getUserVector(Graph g, Actor u, int numArtists)

Constructors in nz.ac.waikato.mcennis.rat.graph.algorithm.collaborativefiltering with parameters of type Graph

AssociativeMiningItems(Graph g, java.lang.String relation, Actor value)
Create a new association on this graph, with this relation, using this actor.

AssociativeMiningItemSetGroup(Graph g, java.lang.String relation)
Creates a new association group in the given (sub)graph over the given link relation

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.evaluation

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.evaluation with parameters of type Graph

protected void	RecommendationError.AdHoc(Graph g)
void	HalfLife.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	KendallTau.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	MeanErrorEvaluation.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	PearsonCorrelation.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	PrecisionRecallFMeasure.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	ROCAreaEvaluation.execute(Graph g) Calculate all the evaluation metrics against the given graph.
void	RecommendationError.execute(Graph g) Calculate all the evaluation metrics against the given graph.
protected void	HalfLife.halfLife(Graph g)
protected void	KendallTau.kendallTau(Graph g)
protected void	MeanErrorEvaluation.meanError(Graph g)
protected void	MeanErrorEvaluation.meanSquaredError(Graph g)
protected void	PrecisionRecallFMeasure.negativeFMeasure(Graph g)
protected void	PrecisionRecallFMeasure.negativePrecision(Graph g)
protected void	PrecisionRecallFMeasure.negativeRecall(Graph g)
protected void	PearsonCorrelation.pearsonsCorrelation(Graph g)
protected void	PrecisionRecallFMeasure.positiveFMeasure(Graph g)
protected void	PrecisionRecallFMeasure.positivePrecision(Graph g)
protected void	PrecisionRecallFMeasure.positiveRecall(Graph g)
protected void	ROCAreaEvaluation.ROCArea(Graph g)
protected void	MeanErrorEvaluation.rootMeanSquaredError(Graph g)
protected void	MeanErrorEvaluation.scaleRecommendations(Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.machinelearning

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.machinelearning with parameters of type Graph

protected void	MultiInstanceSVM.addInstances(Graph g, weka.core.Instances dataSet, Actor artist, int skipCount, int positiveSkipCount)
protected void	SVM.addInstances(Graph g, weka.core.Instances dataSet, Actor artist, int skipCount, int positiveSkipCount)
protected int	MultiInstanceSVM.countTotal(Graph g)
protected void	MultiInstanceSVM.evaluateClassifier(weka.classifiers.Classifier classifier, weka.core.Instances dataSet, Graph g, Actor toBePredicted)
protected void	SVM.evaluateClassifier(weka.classifiers.Classifier classifier, weka.core.Instances dataSet, Graph g, Actor toBePredicted)
void	MultiInstanceSVM.execute(Graph g) Generate music predictions for a user as follows: Calculate all artists A present in the data set.
void	SVM.execute(Graph g)
void	WekaClassifierMultiAttribute.execute(Graph g)
void	WekaClassifierOneAttribute.execute(Graph g)
int	MultiInstanceSVM.totalYes(Graph g, Actor a)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.prestige

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.prestige with parameters of type Graph

protected void	AddBasicBetweenessCentrality.calculateBetweeness(Graph g) Adds Betweeness properties to every actor of the given relation.
void	AddBasicBetweenessCentrality.calculateBetweenessSD(Graph g) Calculates SD of betweeness as a graph property.
protected void	OptimizedBetweeness.calculateBetweenessSD(Graph g)
void	AddClosenessCentrality.calculateCentrality(Graph g) Calculates (MinSum of distances in a graph)/(Sum of shortest paths from this node) for every actor of the given type (mode).If the value is Infinite (because of unconnected graphs) the centrality is 0.0.
void	AddDegreeCentrality.calculateCentrality(Graph g) Calaculate Out-Degree of each actor
void	AddBasicBetweenessCentrality.calculateGraphBetweeness(Graph g) Calculates mean betweeness as a graph property.
protected void	OptimizedBetweeness.calculateGraphBetweeness(Graph g)
void	AddClosenessCentrality.calculateGraphCentrality(Graph g) Calculate the mean value for actor centrality.
void	AddCombinedCloseness.calculateGraphCentrality(Graph g) Calculate the mean value for actor centrality.
void	AddDegreeCentrality.calculateGraphCentrality(Graph g) Calculate mean Degree Centrality as given by Freeman79
protected void	OptimizedCloseness.calculateGraphCentrality(Graph g)
void	AddClosenessCentrality.calculateGraphCentralitySD(Graph g) Calculate Standard Deviation for actor centrality.
void	AddCombinedCloseness.calculateGraphCentralitySD(Graph g) Calculate Standard Deviation for actor centrality.
void	AddDegreeCentrality.calculateGraphCentralitySD(Graph g) Calculate standard deviation of Degree Centrality as given by Freeman79
protected void	OptimizedCloseness.calculateGraphCentralitySD(Graph g)
void	AddClosenessCentrality.calculateGraphPrestige(Graph g) Calculate the mean value for actor prestige.
void	AddCombinedCloseness.calculateGraphPrestige(Graph g) Calculate the mean value for actor prestige.
void	AddDegreeCentrality.calculateGraphPrestige(Graph g) Calculate mean Degree Prestige as given by Freeman79
protected void	OptimizedCloseness.calculateGraphPrestige(Graph g)
void	AddClosenessCentrality.calculateGraphPrestigeSD(Graph g) Calculate Standard Deviation for actor prestige.
void	AddCombinedCloseness.calculateGraphPrestigeSD(Graph g) Calculate Standard Deviation for actor prestige.
void	AddDegreeCentrality.calculateGraphPrestigeSD(Graph g) Calculate standard deviation of Degree Prestige as given by Freeman79
protected void	OptimizedCloseness.calculateGraphPrestigeSD(Graph g)
void	AddClosenessCentrality.calculatePrestige(Graph g) Calculates (MinSum of distances in a graph)/(Sum of shortest paths to this node) for every actor of the given type (mode).
void	AddDegreeCentrality.calculatePrestige(Graph g) Calaculate In-Degree of each actor
protected void	OptimizedBetweeness.doCleanup(PathNode[] path, Graph g)
protected void	OptimizedCloseness.doCleanup(PathNode[] path, Graph g)
protected void	OptimizedLinkBetweeness.doCleanup(PathNode[] path, Graph g)
void	AddBasicBetweenessCentrality.execute(Graph g) Implements betweeness as in Freeman79 except multiple geodesic paths of the same type are treated as independent geodesic paths.
void	AddClosenessCentrality.execute(Graph g)
void	AddCombinedCloseness.execute(Graph g) Uses Djikstra's algorithm for spanning trees.
void	AddDegreeCentrality.execute(Graph g)
void	AddPageRankPrestige.execute(Graph g) Implements the PageRank algorithm in a naive fashion - directly calculating the eigenvector matrix and taking the largest eigenvector (using the Colt scientific computing toolkit.)
void	HITSPrestige.execute(Graph g) Implements the HITS algorithm by directly calculating the eigenvector matrix using Colt's matrix operators.
void	OptimizedLinkBetweeness.execute(Graph g)
void	ScalableHitsPrestige.execute(Graph g) Implements the following algorithm: Iterate(G,k) G: a collection of n linked pages k: a natural number Let z denote the vector (1, 1, 1, .
void	ScalablePageRankPrestige.execute(Graph g) Implements the power version of the Page Rank algorithm using the colt library.
protected Actor[]	AddDegreeCentrality.getActor(Graph g)
protected void	AddCombinedCloseness.nextStepNodes(Graph g) Place node expansion into node expansion map.
protected void	AddCombinedCloseness.processVectors(Graph g, int userNumber) for each vector in the list process end node for each geodesic

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.reusablecores

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.reusablecores that return Graph

Graph[]	FindStronglyConnectedComponentsCore.getGraph() Array of newly created subgraphs.
protected Graph	FindStronglyConnectedComponentsCore.getGraph(Graph g)

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.reusablecores with parameters of type Graph

protected void	ActorDistanceMatrixCore.doCleanup(PathNode[] path, Graph g)
protected void	OptimizedLinkBetweenessCore.doCleanup(PathNode[] path, Graph g)
protected abstract void	PathBaseCore.doCleanup(PathNode[] path, Graph g) Any additional calculations to be performed before control returns to the scheduler
void	FindStronglyConnectedComponentsCore.execute(Graph g) Creates sub-graphs consisting of all strongly connected componenents in the graph.
void	PathBaseCore.execute(Graph g) Generates a spanning tree for a given actor.
protected Graph	FindStronglyConnectedComponentsCore.getGraph(Graph g)
protected void	FindStronglyConnectedComponentsCore.strongConnect(Actor start, Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.similarity

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.similarity with parameters of type Graph

void	GraphSimilarityByProperty.execute(Graph g)
void	HierarchyByCooccurance.execute(Graph g)
void	SimilarityByLink.execute(Graph g)
void	SimilarityByProperty.execute(Graph g)
protected java.util.HashMap<Actor,java.lang.Double>	SimilarityByLink.getMap(Actor tag, java.util.HashSet<Actor> total, Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.transformToArray

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.transformToArray with parameters of type Graph

void	ActorDistanceMatrix.execute(Graph g)
void	DirectedTriplesHistogram.execute(Graph g)
void	UndirectedTriplesHistogram.execute(Graph g)
protected java.util.TreeSet<Actor>	DirectedTriplesHistogram.getLinks(Graph g, Actor v, Actor comparator)
protected java.util.TreeSet<Actor>	UndirectedTriplesHistogram.getLinks(Graph g, Actor v, Actor comparator)
protected int	DirectedTriplesHistogram.getLinkType(Graph g, Actor left, Actor right)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.algorithm.visual

Methods in nz.ac.waikato.mcennis.rat.graph.algorithm.visual with parameters of type Graph

void	BasicDisplayGraph.execute(Graph g)
void	ColoredByPropertyGraph.execute(Graph g)
void	DisplayAll.execute(Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.persistence

Methods in nz.ac.waikato.mcennis.rat.graph.persistence with parameters of type Graph

void	DerbyPersistance.loadGraph(Graph g)
void	GraphPersistance.loadGraph(Graph g)
void	DerbyPersistance.storeGraph(Graph g)
void	GraphPersistance.storeGraph(Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.graph.property

Methods in nz.ac.waikato.mcennis.rat.graph.property with parameters of type Graph

java.lang.String	AssociativeMiningItemsFactory.exportToString(AssociativeMiningItems type, Graph g)
java.lang.String	DoubleFactory.exportToString(java.lang.Double type, Graph g)
java.lang.String	FileFactory.exportToString(java.io.File type, Graph g)
java.lang.String	HashMapStringDoubleFactory.exportToString(java.util.HashMap<java.lang.String,java.lang.Double> type, Graph g)
java.lang.String	InstanceFactory.exportToString(weka.core.Instance type, Graph g)
java.lang.String	InstancesFactory.exportToString(weka.core.Instances type, Graph g)
java.lang.String	IntegerFactory.exportToString(java.lang.Integer type, Graph g)
java.lang.String	LongFactory.exportToString(java.lang.Long type, Graph g)
java.lang.String	StringFactory.exportToString(java.lang.String type, Graph g)
java.lang.String	PropertyValueFactory.exportToString(Type type, Graph g) Create a string representing the contents of this object.
java.lang.String	URLFactory.exportToString(java.net.URL type, Graph g)
AssociativeMiningItems	AssociativeMiningItemsFactory.importFromString(java.lang.String data, Graph g)
java.lang.Double	DoubleFactory.importFromString(java.lang.String data, Graph g)
java.io.File	FileFactory.importFromString(java.lang.String data, Graph g)
java.util.HashMap<java.lang.String,java.lang.Double>	HashMapStringDoubleFactory.importFromString(java.lang.String data, Graph g)
weka.core.Instance	InstanceFactory.importFromString(java.lang.String data, Graph g)
weka.core.Instances	InstancesFactory.importFromString(java.lang.String data, Graph g)
java.lang.Integer	IntegerFactory.importFromString(java.lang.String data, Graph g)
java.lang.Long	LongFactory.importFromString(java.lang.String data, Graph g)
Type	PropertyValueFactory.importFromString(java.lang.String data, Graph g) Create an instance of this type from a string.
java.lang.String	StringFactory.importFromString(java.lang.String data, Graph g)
java.net.URL	URLFactory.importFromString(java.lang.String data, Graph g)

Uses of Graph in nz.ac.waikato.mcennis.rat.parser.xmlHandler

Methods in nz.ac.waikato.mcennis.rat.parser.xmlHandler with parameters of type Graph

void	FOAF2Graph.setGraph(Graph foaf) Set this graph for loading.
void	GraphReader.setGraph(Graph type) Set the graph from which to load the data from the parsed object
Parser[]	LastFMUserExpansion.setUpParsers(java.io.File toFileDirectory, Graph graph) Create the set of parsers for a crawler to parse.
Parser[]	LastFMUserExpansion.setUpParsers(java.io.File toFileDirectory, Graph graph, java.lang.String[] parserNames) Create the set of parsers for a crawler to parse.

Constructors in nz.ac.waikato.mcennis.rat.parser.xmlHandler with parameters of type Graph

FOAF2Graph(Graph m)
Create a new Parser using this graph to load data into

FOAF2Graph(Graph m, WebCrawler c)
Create a new Parser using this graph and parsing new FOAF sites using this crawler

Uses of Graph in nz.ac.waikato.mcennis.rat.scheduler

Methods in nz.ac.waikato.mcennis.rat.scheduler that return Graph

Graph	BasicScheduler.get()
Graph	Scheduler.get() Return the graph produced and altered by the data aquisition and algorithms.

Methods in nz.ac.waikato.mcennis.rat.scheduler with parameters of type Graph

void	BasicScheduler.set(Graph g)
void	Scheduler.set(Graph g) Set the graph that will serve as the data structure to be executed against