de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d
Class ClusterMeanVisualization.Factory<NV extends NumberVector<NV,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisFactory
      de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d.ClusterMeanVisualization.Factory<NV>

Type Parameters:

NV - Type of the NumberVector being visualized.

All Implemented Interfaces:

ResultProcessor, InspectionUtilFrequentlyScanned, Parameterizable, VisFactory

Enclosing class:

ClusterMeanVisualization<NV extends NumberVector<NV,?>>

public static class ClusterMeanVisualization.Factory<NV extends NumberVector<NV,?>>
extends AbstractVisFactory

Factory for visualizers to generate an SVG-Element containing a marker for the mean in a KMeans-Clustering

Constructor Summary

ClusterMeanVisualization.Factory()
Constructor

Method Summary

private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>>	findMeanModel(Clustering<?> c) Test if the given clustering has a mean model.
Visualization	makeVisualization(VisualizationTask task) Produce a visualization instance for the given task
void	processNewResult(HierarchicalResult baseResult, Result result) Add visualizers for the given result (tree) to the context.

Methods inherited from class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisFactory

allowThumbnails, makeVisualizationOrThumbnail

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ClusterMeanVisualization.Factory

public ClusterMeanVisualization.Factory()

Constructor

Method Detail

makeVisualization

public Visualization makeVisualization(VisualizationTask task)

Description copied from interface: VisFactory

Produce a visualization instance for the given task

Specified by:

makeVisualization in interface VisFactory

Specified by:

makeVisualization in class AbstractVisFactory

Parameters:

task - Visualization task

Returns:

Visualization

processNewResult

public void processNewResult(HierarchicalResult baseResult,
                             Result result)

Description copied from interface: VisFactory

Add visualizers for the given result (tree) to the context.

Parameters:

baseResult - Context to work with

result - Result to process

findMeanModel

private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>> findMeanModel(Clustering<?> c)

Test if the given clustering has a mean model.

Type Parameters:

NV - Vector type

Parameters:

c - Clustering to inspect

Returns:

the clustering cast to return a mean model, null otherwise.