Uses of Class
de.lmu.ifi.dbs.elki.result.optics.ClusterOrderResult

Packages that use ClusterOrderResult

de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.projector	Projectors are responsible for finding appropriate projections for data relations.
de.lmu.ifi.dbs.elki.visualization.visualizers.optics	Visualizers that do work on OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d	Visualizers based on 2D projections.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.algorithm.clustering

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return ClusterOrderResult

ClusterOrderResult<D>	OPTICSTypeAlgorithm.run(Database database)
ClusterOrderResult<D>	DeLiClu.run(Database database, Relation<NV> relation)
ClusterOrderResult<D>	OPTICS.run(Database database, Relation<O> relation) Run OPTICS on the database.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type ClusterOrderResult

protected void	OPTICS.expandClusterOrder(ClusterOrderResult<D> clusterOrder, Database database, RangeQuery<O,D> rangeQuery, DBID objectID, D epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected void	OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
private Clustering<OPTICSModel>	OPTICSXi.extractClusters(ClusterOrderResult<N> clusterOrderResult, Relation<?> relation, double ixi, int minpts) Extract clusters from a cluster order result.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type ClusterOrderResult

private Clustering<SubspaceModel<V>>	DiSH.computeClusters(Relation<V> database, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance> clusterOrder, DiSHDistanceFunction.Instance<V> distFunc) Computes the hierarchical clusters according to the cluster order.
private Map<BitSet,List<Pair<BitSet,ArrayModifiableDBIDs>>>	DiSH.extractClusters(Relation<V> database, DiSHDistanceFunction.Instance<V> distFunc, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance> clusterOrder) Extracts the clusters from the cluster order.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.opticsplot

Fields in de.lmu.ifi.dbs.elki.visualization.opticsplot declared as ClusterOrderResult

(package private) ClusterOrderResult<D>

OPTICSPlot.co The result to plot

Methods in de.lmu.ifi.dbs.elki.visualization.opticsplot that return ClusterOrderResult

ClusterOrderResult<D>

OPTICSPlot.getClusterOrder() Get the cluster order we are attached to.

Methods in de.lmu.ifi.dbs.elki.visualization.opticsplot with parameters of type ClusterOrderResult

static <D extends Distance<D>> boolean	OPTICSPlot.canPlot(ClusterOrderResult<D> co) Test whether this class can produce an OPTICS plot for the given cluster order.
private static <D extends Distance<D>> OPTICSDistanceAdapter<D>	OPTICSPlot.getAdapterForDistance(ClusterOrderResult<D> co) Try to find a distance adapter.
static <D extends Distance<D>> Clustering<Model>	OPTICSCut.makeOPTICSCut(ClusterOrderResult<D> co, OPTICSDistanceAdapter<D> adapter, double epsilon) Compute an OPTICS cut clustering
static <D extends Distance<D>> OPTICSPlot<D>	OPTICSPlot.plotForClusterOrder(ClusterOrderResult<D> co, VisualizerContext context) Static method to find an optics plot for a result, or to create a new one using the given context.

Constructors in de.lmu.ifi.dbs.elki.visualization.opticsplot with parameters of type ClusterOrderResult

OPTICSPlot(ClusterOrderResult<D> co, OPTICSColorAdapter colors)
Constructor, with automatic distance adapter detection.

OPTICSPlot(ClusterOrderResult<D> co, OPTICSColorAdapter colors, OPTICSDistanceAdapter<D> distanceAdapter)
Constructor.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.projector

Fields in de.lmu.ifi.dbs.elki.visualization.projector declared as ClusterOrderResult

private ClusterOrderResult<D>

OPTICSProjector.clusterOrder Cluster order result

Methods in de.lmu.ifi.dbs.elki.visualization.projector that return ClusterOrderResult

ClusterOrderResult<D>

OPTICSProjector.getResult() Get the cluster order

Constructors in de.lmu.ifi.dbs.elki.visualization.projector with parameters of type ClusterOrderResult

OPTICSProjector(ClusterOrderResult<D> co)
Constructor.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.visualizers.optics

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.optics with parameters of type ClusterOrderResult

protected static OPTICSXi.SteepAreaResult

OPTICSSteepAreaVisualization.findSteepAreaResult(ClusterOrderResult<?> co) Find the OPTICS clustering child of a cluster order.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d

Fields in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d declared as ClusterOrderResult

protected ClusterOrderResult<?>

ClusterOrderVisualization.result The result we visualize