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

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

Type Parameters:

NV - Type of the NumberVector being visualized.

All Implemented Interfaces:

ResultProcessor, InspectionUtilFrequentlyScanned, Parameterizable, VisFactory

Enclosing class:

EMClusterVisualization<NV extends NumberVector<NV,?>>

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

Visualizer for generating SVG-Elements containing ellipses for first, second and third standard deviation

Constructor Summary

EMClusterVisualization.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.
EMClusterVisualization<NV>	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

EMClusterVisualization.Factory

public EMClusterVisualization.Factory()

Constructor

Method Detail

makeVisualization

public EMClusterVisualization<NV> 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.