Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

de.lmu.ifi.dbs.elki.algorithm.clustering
Class OPTICS<O extends DatabaseObject,D extends Distance<D>>

java.lang.Object
  extended by de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      extended by de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          extended by de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<O,R>
              extended by de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm<O,D,ClusterOrderResult<D>>
                  extended by de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS<O,D>
Type Parameters:
O - the type of DatabaseObjects handled by the algorithm
D - the type of Distance used to discern objects
All Implemented Interfaces:
Algorithm<O,ClusterOrderResult<D>>, Parameterizable

public class OPTICS<O extends DatabaseObject,D extends Distance<D>>
extends DistanceBasedAlgorithm<O,D,ClusterOrderResult<D>>

OPTICS provides the OPTICS algorithm.

Reference: M. Ankerst, M. Breunig, H.-P. Kriegel, and J. Sander: OPTICS: Ordering Points to Identify the Clustering Structure.
In: Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD '99).

Author:
Elke Achtert

Nested Class Summary
 class OPTICS.COEntry
          Encapsulates an entry in the cluster order.
 
Field Summary
private  ClusterOrderResult<D> clusterOrder
          Provides the result of the algorithm.
private  String epsilon
          Hold the value of EPSILON_PARAM.
static OptionID EPSILON_ID
          OptionID for EPSILON_PARAM
private  PatternParameter EPSILON_PARAM
          Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.
private  Heap<D,OPTICS.COEntry> heap
          The priority queue for the algorithm.
private  int minpts
          Holds the value of MINPTS_PARAM.
static OptionID MINPTS_ID
          OptionID for MINPTS_PARAM
private  IntParameter MINPTS_PARAM
          Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.
private  Set<Integer> processedIDs
          Holds a set of processed ids.
 
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm
DISTANCE_FUNCTION_ID, DISTANCE_FUNCTION_PARAM
 
Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
optionHandler
 
Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable
debug, logger
 
Constructor Summary
OPTICS()
          Provides the OPTICS algorithm, adding parameters EPSILON_PARAM and MINPTS_PARAM to the option handler additionally to parameters of super class.
 
Method Summary
protected  void expandClusterOrder(Database<O> database, Integer objectID, FiniteProgress progress)
          OPTICS-function expandClusterOrder.
 Description getDescription()
          Returns a description of the algorithm.
 ClusterOrderResult<D> getResult()
          Returns the result of the algorithm.
protected  ClusterOrderResult<D> runInTime(Database<O> database)
          Performs the OPTICS algorithm on the given database.
 List<String> setParameters(List<String> args)
          Calls the super method and sets additionally the values of the parameters EPSILON_PARAM and MINPTS_PARAM.
private  void updateHeap(D reachability, OPTICS.COEntry entry)
          Adds the specified entry with the specified key tp the heap.
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm
getDistanceFunction
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm
isTime, isVerbose, run, setTime, setVerbose
 
Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
addOption, addParameterizable, addParameterizable, checkGlobalParameterConstraints, collectOptions, getAttributeSettings, getParameters, rememberParametersExcept, removeOption, removeParameterizable, shortDescription
 
Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable
debugFine, debugFiner, debugFinest, exception, progress, verbose, warning
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable
checkGlobalParameterConstraints, collectOptions, getParameters, shortDescription
 

Field Detail

EPSILON_ID

public static final OptionID EPSILON_ID
OptionID for EPSILON_PARAM


EPSILON_PARAM

private final PatternParameter EPSILON_PARAM
Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.

Key: -optics.epsilon


epsilon

private String epsilon
Hold the value of EPSILON_PARAM.


MINPTS_ID

public static final OptionID MINPTS_ID
OptionID for MINPTS_PARAM


MINPTS_PARAM

private final IntParameter MINPTS_PARAM
Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.

Key: -optics.minpts


minpts

private int minpts
Holds the value of MINPTS_PARAM.


clusterOrder

private ClusterOrderResult<D extends Distance<D>> clusterOrder
Provides the result of the algorithm.


processedIDs

private Set<Integer> processedIDs
Holds a set of processed ids.


heap

private Heap<D extends Distance<D>,OPTICS.COEntry> heap
The priority queue for the algorithm.

Constructor Detail

OPTICS

public OPTICS()
Provides the OPTICS algorithm, adding parameters EPSILON_PARAM and MINPTS_PARAM to the option handler additionally to parameters of super class.

Method Detail

runInTime

protected ClusterOrderResult<D> runInTime(Database<O> database)
Performs the OPTICS algorithm on the given database.

Specified by:
runInTime in class AbstractAlgorithm<O extends DatabaseObject,ClusterOrderResult<D extends Distance<D>>>
Parameters:
database - the database to run the algorithm on
Returns:
the Result computed by this algorithm

expandClusterOrder

protected void expandClusterOrder(Database<O> database,
                                  Integer objectID,
                                  FiniteProgress progress)
OPTICS-function expandClusterOrder.

Parameters:
database - the database on which the algorithm is run
objectID - the currently processed object
progress - the progress object to actualize the current progress if the algorithm

getDescription

public Description getDescription()
Description copied from interface: Algorithm
Returns a description of the algorithm.

Returns:
a description of the algorithm

setParameters

public List<String> setParameters(List<String> args)
                           throws ParameterException
Calls the super method and sets additionally the values of the parameters EPSILON_PARAM and MINPTS_PARAM.

Specified by:
setParameters in interface Parameterizable
Overrides:
setParameters in class DistanceBasedAlgorithm<O extends DatabaseObject,D extends Distance<D>,ClusterOrderResult<D extends Distance<D>>>
Parameters:
args - parameters to set the attributes accordingly to
Returns:
a list containing the unused parameters
Throws:
ParameterException - in case of wrong parameter-setting

getResult

public ClusterOrderResult<D> getResult()
Description copied from interface: Algorithm
Returns the result of the algorithm.

Returns:
the result of the algorithm

updateHeap

private void updateHeap(D reachability,
                        OPTICS.COEntry entry)
Adds the specified entry with the specified key tp the heap. If the entry's object is already in the heap, it will only be updated.

Parameters:
reachability - the reachability of the entry's object
entry - the entry to be added

Release 0.2 (2009-07-06_1820)