Package elki.clustering.dbscan

Class GriDBSCAN.Instance<V extends elki.data.NumberVector>

java.lang.Object

elki.clustering.dbscan.GriDBSCAN.Instance<V>

Type Parameters:

V - Vector type

Enclosing class:

GriDBSCAN<V extends elki.data.NumberVector>

protected static class GriDBSCAN.Instance<V extends elki.data.NumberVector>
extends java.lang.Object

Instance, for a single run.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
private Border[]	borders	Border identifier objects (shared to conserve memory).
protected int[]	cells	Number of cells per dimension.
private elki.database.datastore.WritableDataStore<Assignment>	clusterids	Cluster assignments.
private Core[]	cores	Core identifier objects (shared to conserve memory).
protected int	dim	Dimensionality.
protected elki.distance.Distance<? super V>	distance	Distance function used.
protected double[][]	domain	Value domain.
protected double	epsilon	Holds the epsilon radius threshold.
(package private) it.unimi.dsi.fastutil.longs.Long2ObjectOpenHashMap<elki.database.ids.ModifiableDBIDs>	grid	Data grid partitioning.
protected double	gridwidth	Width of the grid cells.
protected int	minpts	Holds the minimum cluster size.
protected static int	NOISE	Noise IDs.
protected double[]	offset	Grid offset.
private boolean	overflown	Indicates that the number of grid cells has overflown.
private elki.database.datastore.WritableIntegerDataStore	temporary	Temporary assignments of a single run.
protected static int	UNPROCESSED	Unprocessed IDs.

Constructor Summary

Constructors

Constructor	Description
Instance(elki.distance.Distance<? super V> distance, double epsilon, int minpts, double gridwidth)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected void	buildGrid(elki.database.relation.Relation<V> relation, int numcells, double[] offset)	Build the data grid.
protected Clustering<Model>	buildResult(elki.database.ids.DBIDs ids, int clusterid)	Assemble the clustering result.
protected int	checkGridCellSizes(int size, long numcell)	Perform some sanity checks on the grid cells.
private long	computeGridBaseOffsets(int size)	Compute the grid base offset.
protected int	expandCluster(elki.database.ids.DBIDRef seed, int clusterid, elki.database.datastore.WritableIntegerDataStore clusterids, elki.database.ids.ModifiableDoubleDBIDList neighbors, elki.database.ids.ArrayModifiableDBIDs activeSet, elki.database.query.range.RangeSearcher<elki.database.ids.DBIDRef> rq, elki.logging.progress.FiniteProgress pprog)	Set-based expand cluster implementation.
private void	insertIntoGrid(elki.database.ids.DBIDRef id, V obj, int d, int v)	Insert a single object into the grid; potentially into multiple cells (at most 2^d) via recursion.
protected void	mergeClusterInformation(elki.database.ids.ModifiableDBIDs cellids, elki.database.datastore.WritableIntegerDataStore temporary, elki.database.datastore.WritableDataStore<Assignment> clusterids)	Merge cluster information.
protected int	processCorePoint(elki.database.ids.DBIDRef seed, elki.database.ids.DoubleDBIDList newneighbors, int clusterid, elki.database.datastore.WritableIntegerDataStore clusterids, elki.database.ids.ArrayModifiableDBIDs activeSet)	Process a single core point.
Clustering<Model>	run(elki.database.relation.Relation<V> relation)	Performs the DBSCAN algorithm on the given database.
private int	runDBSCANOnCell(elki.database.ids.DBIDs cellids, elki.database.relation.Relation<V> relation, elki.database.ids.ModifiableDoubleDBIDList neighbors, elki.database.ids.ArrayModifiableDBIDs activeSet, int clusterid)
private void	updateCoreBorderObjects(int clusterid)	Update the shared arrays for core points (to conserve memory)

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

distance

protected elki.distance.Distance<? super V extends elki.data.NumberVector> distance

Distance function used.

epsilon

protected double epsilon

Holds the epsilon radius threshold.

minpts

protected int minpts

Holds the minimum cluster size.

gridwidth

protected double gridwidth

Width of the grid cells. Must be at least 2 epsilon!

domain

protected double[][] domain

Value domain.

dim

protected int dim

Dimensionality.

offset

protected double[] offset

Grid offset.

cells

protected int[] cells

Number of cells per dimension.

grid

it.unimi.dsi.fastutil.longs.Long2ObjectOpenHashMap<elki.database.ids.ModifiableDBIDs> grid

Data grid partitioning.

cores

private Core[] cores

Core identifier objects (shared to conserve memory).

borders

private Border[] borders

Border identifier objects (shared to conserve memory).

clusterids

private elki.database.datastore.WritableDataStore<Assignment> clusterids

Cluster assignments.

temporary

private elki.database.datastore.WritableIntegerDataStore temporary

Temporary assignments of a single run.

overflown

private boolean overflown

Indicates that the number of grid cells has overflown.

Constructor Detail

Instance

public Instance(elki.distance.Distance<? super V> distance,
                double epsilon,
                int minpts,
                double gridwidth)

Constructor.

Parameters:

distance - Distance function

epsilon - Epsilon

minpts - MinPts

gridwidth - Grid width

Method Detail

run

public Clustering<Model> run(elki.database.relation.Relation<V> relation)

Performs the DBSCAN algorithm on the given database.

Parameters:

relation - Relation to process

runDBSCANOnCell

private int runDBSCANOnCell(elki.database.ids.DBIDs cellids,
                            elki.database.relation.Relation<V> relation,
                            elki.database.ids.ModifiableDoubleDBIDList neighbors,
                            elki.database.ids.ArrayModifiableDBIDs activeSet,
                            int clusterid)

updateCoreBorderObjects

private void updateCoreBorderObjects(int clusterid)

Update the shared arrays for core points (to conserve memory)

Parameters:

clusterid - Number of clusters

computeGridBaseOffsets

private long computeGridBaseOffsets(int size)

Compute the grid base offset.

Parameters:

size - Data set size

Returns:

Total number of grid cells

buildGrid

protected void buildGrid(elki.database.relation.Relation<V> relation,
                         int numcells,
                         double[] offset)

Build the data grid.

Parameters:

relation - Data relation

numcells - Total number of cells

offset - Offset

insertIntoGrid

private void insertIntoGrid(elki.database.ids.DBIDRef id,
                            V obj,
                            int d,
                            int v)

Insert a single object into the grid; potentially into multiple cells (at most 2^d) via recursion.

Parameters:

id - Object ID

obj - Object

d - Current dimension

v - Current cell value

checkGridCellSizes

protected int checkGridCellSizes(int size,
                                 long numcell)

Perform some sanity checks on the grid cells.

Parameters:

numcell - Number of cells

size - Relation size

Returns:

Number of cells with minPts points

expandCluster

protected int expandCluster(elki.database.ids.DBIDRef seed,
                            int clusterid,
                            elki.database.datastore.WritableIntegerDataStore clusterids,
                            elki.database.ids.ModifiableDoubleDBIDList neighbors,
                            elki.database.ids.ArrayModifiableDBIDs activeSet,
                            elki.database.query.range.RangeSearcher<elki.database.ids.DBIDRef> rq,
                            elki.logging.progress.FiniteProgress pprog)

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.

rq - Range query

pprog - Object progress

Returns:

cluster size

processCorePoint

protected int processCorePoint(elki.database.ids.DBIDRef seed,
                               elki.database.ids.DoubleDBIDList newneighbors,
                               int clusterid,
                               elki.database.datastore.WritableIntegerDataStore clusterids,
                               elki.database.ids.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

mergeClusterInformation

protected void mergeClusterInformation(elki.database.ids.ModifiableDBIDs cellids,
                                       elki.database.datastore.WritableIntegerDataStore temporary,
                                       elki.database.datastore.WritableDataStore<Assignment> clusterids)

Merge cluster information.

Parameters:

cellids - IDs in current cell

temporary - Temporary assignments

clusterids - Merged cluster assignment

buildResult

protected Clustering<Model> buildResult(elki.database.ids.DBIDs ids,
                                        int clusterid)

Assemble the clustering result.

Parameters:

ids - Object IDs

clusterid - Largest valid cluster number

Returns:

Clustering