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java.lang.Object de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R> de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,D,CollectionResult<DoubleVector>> de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses<O,D>
O
- Object typeD
- Distance type@Title(value="Distance Histogram") @Description(value="Computes a histogram over the distances occurring in the data set.") public class DistanceStatisticsWithClasses<O,D extends NumberDistance<D,?>>
Algorithm to gather statistics over the distance distribution in the data set.
Nested Class Summary | |
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static class |
DistanceStatisticsWithClasses.Parameterizer<O,D extends NumberDistance<D,?>>
Parameterization class. |
Field Summary | |
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private boolean |
exact
Sampling |
static OptionID |
EXACT_ID
Flag to compute exact value range for binning. |
static OptionID |
HISTOGRAM_BINS_ID
Option to configure the number of bins to use. |
private static Logging |
logger
The logger for this class. |
private int |
numbin
Number of bins to use in sampling. |
private boolean |
sampling
Sampling |
static OptionID |
SAMPLING_ID
Flag to enable sampling |
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm |
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DISTANCE_FUNCTION_ID |
Constructor Summary | |
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DistanceStatisticsWithClasses(DistanceFunction<? super O,D> distanceFunction,
int numbins,
boolean exact,
boolean sampling)
Constructor. |
Method Summary | |
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private DoubleMinMax |
exactMinMax(Relation<O> database,
DistanceQuery<O,D> distFunc)
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TypeInformation[] |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query. |
protected Logging |
getLogger()
Get the (STATIC) logger for this class. |
HistogramResult<DoubleVector> |
run(Database database)
Iterates over all points in the database. |
private DoubleMinMax |
sampleMinMax(Relation<O> database,
DistanceQuery<O,D> distFunc)
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private void |
shrinkHeap(TreeSet<FCPair<Double,DBID>> hotset,
int k)
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Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm |
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getDistanceFunction |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm |
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makeParameterDistanceFunction |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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private static final Logging logger
public static final OptionID EXACT_ID
public static final OptionID SAMPLING_ID
public static final OptionID HISTOGRAM_BINS_ID
private int numbin
private boolean sampling
private boolean exact
Constructor Detail |
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public DistanceStatisticsWithClasses(DistanceFunction<? super O,D> distanceFunction, int numbins, boolean exact, boolean sampling)
distanceFunction
- Distance function to usenumbins
- Number of binsexact
- Exactness flagsampling
- Sampling flagMethod Detail |
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public HistogramResult<DoubleVector> run(Database database) throws IllegalStateException
run
in interface Algorithm
run
in class AbstractAlgorithm<CollectionResult<DoubleVector>>
database
- the database to run the algorithm on
IllegalStateException
- if the algorithm has not been initialized
properly (e.g. the setParameters(String[]) method has been failed
to be called).private DoubleMinMax sampleMinMax(Relation<O> database, DistanceQuery<O,D> distFunc)
private DoubleMinMax exactMinMax(Relation<O> database, DistanceQuery<O,D> distFunc)
private void shrinkHeap(TreeSet<FCPair<Double,DBID>> hotset, int k)
public TypeInformation[] getInputTypeRestriction()
AbstractAlgorithm
getInputTypeRestriction
in interface Algorithm
getInputTypeRestriction
in class AbstractAlgorithm<CollectionResult<DoubleVector>>
protected Logging getLogger()
AbstractAlgorithm
getLogger
in class AbstractAlgorithm<CollectionResult<DoubleVector>>
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