gov.sandia.cognition.statistics

Class AbstractDataDistribution<KeyType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.collection.AbstractScalarMap<KeyType,MutableDouble>

gov.sandia.cognition.collection.AbstractMutableDoubleMap<KeyType>

gov.sandia.cognition.statistics.AbstractDataDistribution<KeyType>

Type Parameters:

KeyType - The type of data stored at the indices, the hash keys.

All Implemented Interfaces:

NumericMap<KeyType>, ScalarMap<KeyType>, ComputableDistribution<KeyType>, DataDistribution<KeyType>, DiscreteDistribution<KeyType>, Distribution<KeyType>, EstimableDistribution<KeyType,DataDistribution<KeyType>>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

DefaultDataDistribution

public abstract class AbstractDataDistribution<KeyType>
extends AbstractMutableDoubleMap<KeyType>
implements DataDistribution<KeyType>

An abstract implementation of the DataDistribution interface.

Since:

3.3.0

Author:

Justin Basilico, Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.collection.AbstractMutableDoubleMap

AbstractMutableDoubleMap.Entry<KeyType>, AbstractMutableDoubleMap.SimpleEntry<KeyType>, AbstractMutableDoubleMap.SimpleEntrySet<KeyType>, AbstractMutableDoubleMap.SimpleIterator<KeyType>

Nested classes/interfaces inherited from interface gov.sandia.cognition.statistics.DataDistribution

DataDistribution.PMF<KeyType>

Nested classes/interfaces inherited from interface gov.sandia.cognition.collection.ScalarMap

ScalarMap.Entry<KeyType>

Field Summary

Fields inherited from class gov.sandia.cognition.collection.AbstractScalarMap

map

Constructor Summary

Constructors

Constructor and Description
AbstractDataDistribution(java.util.Map<KeyType,MutableDouble> map) Creates a new AbstractDataDistribution.

Method Summary

Modifier and Type	Method and Description
AbstractDataDistribution<KeyType>	clone() This makes public the clone method on the Object class and removes the exception that it throws.
void	fromInfiniteVector(InfiniteVector<? extends KeyType> vector) Replaces the entries in this data distribution with the entries in the given infinite vector.
java.util.Set<KeyType>	getDomain() Returns an object that allows an iteration through the domain (x-axis, independent variable) of the Distribution
int	getDomainSize() Gets the size of the domain.
double	getEntropy() Computes the information-theoretic entropy of the vector in bits.
double	getFraction(KeyType key) Gets the fraction of the counts represented by the given key.
double	getLogFraction(KeyType key) Gets the natural logarithm of the fraction of the counts represented by the given key.
double	getMaxValue() The maximum value associated with any key in the map.
double	getMinValue() The minimum value associated with any key in the map.
KeyType	sample(java.util.Random random) Draws a single random sample from the distribution.
java.util.ArrayList<KeyType>	sample(java.util.Random random, int numSamples) Draws multiple random samples from the distribution.
void	sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super KeyType> output) Draws multiple random samples from the distribution and puts the result into the given collection.
InfiniteVector<KeyType>	toInfiniteVector() Converts this data distribution to an infinite vector.

Methods inherited from class gov.sandia.cognition.collection.AbstractMutableDoubleMap

asMap, compact, entrySet, get, increment, set

Methods inherited from class gov.sandia.cognition.collection.AbstractScalarMap

clear, containsKey, decrement, decrement, decrementAll, decrementAll, getMaxValueKey, getMaxValueKeys, getMinValueKey, getMinValueKeys, increment, incrementAll, incrementAll, isEmpty, keySet, setAll, setAll, size

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.statistics.DataDistribution

getEstimator, getProbabilityFunction, getTotal

Methods inherited from interface gov.sandia.cognition.collection.ScalarMap

asMap, decrement, decrement, decrementAll, decrementAll, entrySet, get, increment, increment, incrementAll, incrementAll, set, setAll, setAll

Methods inherited from interface gov.sandia.cognition.collection.NumericMap

clear, containsKey, getMaxValueKey, getMaxValueKeys, getMinValueKey, getMinValueKeys, isEmpty, keySet, size

Constructor Detail

AbstractDataDistribution

public AbstractDataDistribution(java.util.Map<KeyType,MutableDouble> map)

Creates a new AbstractDataDistribution.

Parameters:

map - Map that stores the data

Method Detail

clone

public AbstractDataDistribution<KeyType> clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface DataDistribution<KeyType>

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractMutableDoubleMap<KeyType>

Returns:

A clone of this object.

getDomainSize

public int getDomainSize()

Description copied from interface: DiscreteDistribution

Gets the size of the domain.

Specified by:

getDomainSize in interface DiscreteDistribution<KeyType>

Returns:

The size of the domain.

getEntropy

public double getEntropy()

Description copied from interface: DataDistribution

Computes the information-theoretic entropy of the vector in bits.

Specified by:

getEntropy in interface DataDistribution<KeyType>

Returns:

Entropy in bits of the distribution.

getLogFraction

public double getLogFraction(KeyType key)

Description copied from interface: DataDistribution

Gets the natural logarithm of the fraction of the counts represented by the given key.

Specified by:

getLogFraction in interface DataDistribution<KeyType>

Parameters:

key - Key to consider

Returns:

Natural logarithm of the fraction of the counts represented by the key

getFraction

public double getFraction(KeyType key)

Description copied from interface: DataDistribution

Gets the fraction of the counts represented by the given key.

Specified by:

getFraction in interface DataDistribution<KeyType>

Parameters:

key - The key.

Returns:

The fraction of the total count represented by the key, if it exists. Otherwise, 0.0.

sample

public KeyType sample(java.util.Random random)

Description copied from interface: Distribution

Draws a single random sample from the distribution.

Specified by:

sample in interface Distribution<KeyType>

Parameters:

random - Random-number generator to use in order to generate random numbers.

Returns:

Sample drawn according to this distribution.

sample

public java.util.ArrayList<KeyType> sample(java.util.Random random,
                                           int numSamples)

Description copied from interface: Distribution

Draws multiple random samples from the distribution. It is generally more efficient to use this multiple-sample method than multiple calls of the single-sample method. (But not always.)

Specified by:

sample in interface Distribution<KeyType>

Parameters:

random - Random-number generator to use in order to generate random numbers.

numSamples - Number of samples to draw from the distribution.

Returns:

Samples drawn according to this distribution.

sampleInto

public void sampleInto(java.util.Random random,
                       int sampleCount,
                       java.util.Collection<? super KeyType> output)

Description copied from interface: Distribution

Draws multiple random samples from the distribution and puts the result into the given collection.

Specified by:

sampleInto in interface Distribution<KeyType>

Parameters:

random - Random number generator to use.

sampleCount - The number of samples to draw. Cannot be negative.

output - The collection to add the samples into.

toInfiniteVector

public InfiniteVector<KeyType> toInfiniteVector()

Description copied from interface: DataDistribution

Converts this data distribution to an infinite vector.

Specified by:

toInfiniteVector in interface DataDistribution<KeyType>

Returns:

A new InfiniteVector with values from this data distribution.

fromInfiniteVector

public void fromInfiniteVector(InfiniteVector<? extends KeyType> vector)

Description copied from interface: DataDistribution

Replaces the entries in this data distribution with the entries in the given infinite vector.

Specified by:

fromInfiniteVector in interface DataDistribution<KeyType>

Parameters:

vector - The infinite vector to use to populate this data distribution.

getMaxValue

public double getMaxValue()

Description copied from interface: ScalarMap

The maximum value associated with any key in the map.

Specified by:

getMaxValue in interface ScalarMap<KeyType>

Overrides:

getMaxValue in class AbstractScalarMap<KeyType,MutableDouble>

Returns:

The maximum value associated with any key in the map. If the map is empty, then Double.NEGATIVE_INFINITY is returned.

getMinValue

public double getMinValue()

Description copied from interface: ScalarMap

The minimum value associated with any key in the map.

Specified by:

getMinValue in interface ScalarMap<KeyType>

Overrides:

getMinValue in class AbstractScalarMap<KeyType,MutableDouble>

Returns:

The minimum value associated with any key in the map. If the map is empty, then Double.POSITIVE_INFINITY is returned.

getDomain

public java.util.Set<KeyType> getDomain()

Description copied from interface: DiscreteDistribution

Returns an object that allows an iteration through the domain (x-axis, independent variable) of the Distribution

Specified by:

getDomain in interface DiscreteDistribution<KeyType>

Returns:

Collection that enumerates each value that the domain can take