com.luciad.model.transformation.clustering

LuciadFusionClass TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder

java.lang.Object

com.luciad.model.transformation.clustering.TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder

Enclosing class:

TLcdClusteringTransformer.Builder

public static final class TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder
extends Object

Builder to configure parameters for a specific classification.

Since:

2016.0

Method Summary

Modifier and Type	Method and Description
TLcdClusteringTransformer.Builder	build() Applies the specified settings and returns the original Builder instance.
TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder	clusterSize(double aClusterSize) Sets the approximate cluster size in pixels.
TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder	minimumPoints(int aMinimumPoints) Sets the minimum number of points required to form a cluster.
TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder	noClustering() Indicates that no clustering should happen.
TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder	shapeProvider(ILcdClusterShapeProvider aProvider) Sets an ILcdClusterShapeProvider which determines the shape of the cluster based on its contained elements

Methods inherited from class java.lang.Object

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

Method Detail

clusterSize

public TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder clusterSize(double aClusterSize)

Sets the approximate cluster size in pixels. This size indicates the area of the cluster in screen space. For example, when passing 200 as value, the clustering algorithm will try to create clusters that are 200 pixels apart.

Note that the given size is an approximate size. The clustering algorithm may create smaller or larger clusters, depending on the data. The size of the cluster is influenced by:

• This setting
• The proximity of other clusters. Different clusters can start competing, trying to include the same point. This will cause clusters to be closer together than indicated by this setting, and thus be smaller.
• The amount of points in the cluster. Clusters with a small amount of points will break down sooner than clusters with many points. This means that clusters with a small amount of points will typically be smaller.

Parameters:

aClusterSize - the approximate cluster size in pixels.

Returns:

This builder

minimumPoints

public TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder minimumPoints(int aMinimumPoints)

Sets the minimum number of points required to form a cluster. For example when set to 3, there will never be a cluster which only represents 2 points. Each cluster will at least contain 3 points.

Parameters:

aMinimumPoints - the minimum number of points required to form a cluster

Returns:

This builder

noClustering

public TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder noClustering()

Indicates that no clustering should happen.

Returns:

This builder

shapeProvider

public TLcdClusteringTransformer.Builder.ClassificationSpecificBuilder shapeProvider(ILcdClusterShapeProvider aProvider)

Sets an ILcdClusterShapeProvider which determines the shape of the cluster based on its contained elements

Parameters:

aProvider - The cluster shape provider

Returns:

This builder

build

public TLcdClusteringTransformer.Builder build()

Applies the specified settings and returns the original Builder instance.

Returns:

the original Builder instance.