de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Class GeneralizedDBSCAN.Instance<T>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance<T>

Enclosing class:

GeneralizedDBSCAN

public static class GeneralizedDBSCAN.Instance<T>
extends java.lang.Object

Instance for a particular data set.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	coremodel Track which objects are "core" objects.
protected CorePredicate.Instance<? super T>	corepred The core object property
protected static int	NOISE Noise IDs
protected NeighborPredicate.Instance<T>	npred The neighborhood predicate
protected static int	UNPROCESSED Unprocessed IDs

Constructor Summary

Constructors

Constructor and Description
Instance(NeighborPredicate.Instance<T> npred, CorePredicate.Instance<? super T> corepred, boolean coremodel) Full Constructor

Method Summary

Modifier and Type	Method and Description
protected int	expandCluster(DBIDRef seed, int clusterid, WritableIntegerDataStore clusterids, T neighbors, ArrayModifiableDBIDs activeSet, FiniteProgress progress) Set-based expand cluster implementation.
protected int	processCorePoint(DBIDRef seed, T newneighbors, int clusterid, WritableIntegerDataStore clusterids, ArrayModifiableDBIDs activeSet) Process a single core point.
Clustering<Model>	run() Run the actual GDBSCAN algorithm.

Methods inherited from class java.lang.Object

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

Field Detail

UNPROCESSED

protected static final int UNPROCESSED

Unprocessed IDs

See Also:

Constant Field Values

NOISE

protected static final int NOISE

Noise IDs

See Also:

Constant Field Values

npred

protected final NeighborPredicate.Instance<T> npred

The neighborhood predicate

corepred

protected final CorePredicate.Instance<? super T> corepred

The core object property

coremodel

protected boolean coremodel

Track which objects are "core" objects.

Constructor Detail

Instance

public Instance(NeighborPredicate.Instance<T> npred,
                CorePredicate.Instance<? super T> corepred,
                boolean coremodel)

Full Constructor

Parameters:

npred - Neighborhood predicate

corepred - Core object predicate

coremodel - Keep track of core points.

Method Detail

run

public Clustering<Model> run()

Run the actual GDBSCAN algorithm.

Returns:

Clustering result

expandCluster

protected int expandCluster(DBIDRef seed,
                            int clusterid,
                            WritableIntegerDataStore clusterids,
                            T neighbors,
                            ArrayModifiableDBIDs activeSet,
                            FiniteProgress progress)

Set-based expand cluster implementation.

Parameters:

clusterid - ID of the current cluster.

clusterids - Current object to cluster mapping.

neighbors - Neighbors acquired by initial getNeighbors call.

activeSet - Set to manage active candidates.

progress - Progress logging

Returns:

cluster size

processCorePoint

protected int processCorePoint(DBIDRef seed,
                               T newneighbors,
                               int clusterid,
                               WritableIntegerDataStore clusterids,
                               ArrayModifiableDBIDs activeSet)

Process a single core point.

Parameters:

seed - Point to process

newneighbors - New neighbors

clusterid - Cluster to add to

clusterids - Cluster assignment storage.

activeSet - Active set of cluster seeds

Returns:

Number of new points added to cluster