Uses of Interface
org.databene.benerator.distribution.Distribution

Packages that use Distribution

org.databene.benerator.csv	Provides String generators that parse CSV sources.
org.databene.benerator.distribution
org.databene.benerator.distribution.cumulative
org.databene.benerator.distribution.function
org.databene.benerator.distribution.sequence
org.databene.benerator.engine.parser
org.databene.benerator.factory
org.databene.benerator.primitive	Implements Generators for simple Java types.
org.databene.benerator.primitive.datetime
org.databene.benerator.primitive.number	Defines a small framework for generating numbers of all built-in Java number types (byte, short, int, long, BigInteger, float, double, BigDecimal) resulting from a sequence or being distributed according a distribution function.
org.databene.benerator.sample	Provides Generators that are based on collections of samples.
org.databene.benerator.wrapper	Defines generators that wrap other generators and forward or convert their products
org.databene.domain.math

Uses of Distribution in org.databene.benerator.csv

Constructors in org.databene.benerator.csv with parameters of type Distribution

SequencedDatasetCSVGenerator(java.lang.String filenamePattern, char separator, java.lang.String datasetName, java.lang.String nesting, Distribution distribution, java.lang.String encoding, org.databene.commons.Context context)

SequencedDatasetCSVGenerator(java.lang.String filenamePattern, char separator, java.lang.String datasetName, java.lang.String nesting, Distribution distribution, java.lang.String encoding, org.databene.commons.Converter<java.lang.String,E> converter)

Uses of Distribution in org.databene.benerator.distribution

Subinterfaces of Distribution in org.databene.benerator.distribution

interface	Weight Common parent class for all Generators that are based on weights.
interface	WeightFunction Common interface for weight functions.

Classes in org.databene.benerator.distribution that implement Distribution

class	AbstractWeightFunction Abstract implementation of the WeightFunction interface.
class	AttachedWeight<E> IndividualWeight implementation that weighs objects individually.
class	CumulativeDistributionFunction Distribution implementation which uses the inverse of a probability function integral for efficiently generating numbers with a given probability distribution.
class	FeatureWeight Implements the IndividualWeight function for arbitrary feature names, supporting e.g. properties, attributes, or Map keys.
class	IndividualWeight<E> Distribution type that provides an individual weight for each object.
class	LongBasedSequence Helper class that serves as parent for individual Sequence implementations that are based on a Long-value generator (Generator<Long>).
class	Sequence Provides access to specific Sequence number Generators.

Methods in org.databene.benerator.distribution that return Distribution

Distribution	WeightedLongGenerator.getDistribution()
Distribution	WeightedDoubleGenerator.getDistribution()

Methods in org.databene.benerator.distribution with parameters of type Distribution

void	WeightedLongGenerator.setDistribution(Distribution distribution)

Constructors in org.databene.benerator.distribution with parameters of type Distribution

DistributingGenerator(Generator<E> dataProvider, Distribution distribution, boolean unique)

DistributingSampleGeneratorProxy(Generator<E> dataProvider, Distribution distribution, boolean unique)

Uses of Distribution in org.databene.benerator.distribution.cumulative

Classes in org.databene.benerator.distribution.cumulative that implement Distribution

class

ExponentialDensityIntegral Inverse of the integral of the probability density f(x) = a e^{-ax} (x > 0), which resolves to F^{-1}(x) = - log(1 - x) / a.

Uses of Distribution in org.databene.benerator.distribution.function

Classes in org.databene.benerator.distribution.function that implement Distribution

class	ConstantFunction Returns a constant value, independent of the argument.
class	DiscreteFunction Discrete function that is based on an array.
class	ExponentialFunction Exponential function. a * e^bx.
class	GaussianFunction Gaussian Function. 1/(deviation*sqrt(2PI)) * e^(-(x - average)^2/(4 * deviation^2)).

Uses of Distribution in org.databene.benerator.distribution.sequence

Classes in org.databene.benerator.distribution.sequence that implement Distribution

class	BitReverseSequence Sequence implementation for a distribution that creates the bit-reverses (r) of a continuous series, e.g. r(1), r(2), r(3), ...; the numbers produced by a related generator are unique as long as the generator is not reset.
class	CumulatedSequence Sequence implementation for an efficient bell-like distribution.
class	ExpandSequence Sequence implementation that makes use of Benerator's ExpandGeneratorProxy for distributing data of unlimited volume in a unique or non-unique manner.
class	HeadSequence Sequence implementation that returns the first n values of another Generator (default 1).
class	LiteralSequence Sequence implementation that provides values specified in a comma-separated value list, use like "new PredefinedSequence('A', 'B', 'C')" or "new PredefinedSequence(5, 7, 11)".
class	RandomSequence Sequence implementation that creates generators with a random uniform distribution.
class	RandomWalkSequence Random Walk Sequence implementation that supports a variable step width.
class	RepeatSequence Distribution that repeats consecutive elements or numbers.
class	ShuffleSequence Sequence implementation that implements a 'shuffle' behavior, by continuously incrementing a base value by a constant value and, when iterated through the number range, restarts with a value incremented by one.
class	StepSequence Creates numbers by continuously incrementing a base value by a constant amount.
class	WedgeSequence Sequence implementation that creates Number Generator with a wedge distribution.
class	WeightedNumbers<E> Generates numbers with weights that are defined using a literal, for example "1^3,2^7" would cause generation of 30% '1' values and 70% '2' values.

Constructors in org.databene.benerator.distribution.sequence with parameters of type Distribution

RandomWalkLongGenerator(long min, long max, long precision, long initial, long minIncrement, long maxIncrement, Distribution incrementDistribution)

RepeatSequence(int minRepetitions, int maxRepetitions, int repetitionPrecision, Distribution repetitionDistribution)

Uses of Distribution in org.databene.benerator.engine.parser

Methods in org.databene.benerator.engine.parser that return Distribution

Distribution

String2DistributionConverter.convert(java.lang.String stringOrScript)

Uses of Distribution in org.databene.benerator.factory

Methods in org.databene.benerator.factory that return Distribution

static Distribution

GeneratorFactoryUtil.getDistribution(java.lang.String spec, Uniqueness uniqueness, boolean required, BeneratorContext context) Extracts distribution information from the descriptor.

Methods in org.databene.benerator.factory that return types with arguments of type Distribution

static org.databene.commons.Expression<Distribution>

GeneratorFactoryUtil.getDistributionExpression(java.lang.String spec, Uniqueness uniqueness, boolean required)

Methods in org.databene.benerator.factory with parameters of type Distribution

static <T> Generator<T>	GeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec, java.lang.Class<T> targetType, Distribution distribution, boolean unique)
static <T> Generator<T[]>	GeneratorFactory.getArrayGenerator(Generator<T> source, java.lang.Class<T> type, int minSize, int maxSize, Distribution sizeDistribution) Creates a generator that combines several products of a source generator to a collection.
static <C extends java.util.Collection<I>,I> Generator<C>	GeneratorFactory.getCollectionGenerator(java.lang.Class<C> collectionType, Generator<I> source, int minSize, int maxSize, Distribution sizeDistribution) Creates a generator that combines several products of a source generator to a collection.
static Generator<java.util.Date>	GeneratorFactory.getDateGenerator(java.util.Date min, java.util.Date max, long precision, Distribution distribution) Creates a Date generator that generates random dates.
static <T extends java.lang.Number> Generator<T>	GeneratorFactory.getNumberGenerator(java.lang.Class<T> numberType, T min, T max, int totalDigits, int fractionDigits, T precision, Distribution distribution, boolean unique) Creates a generator for numbers.
static <T extends java.lang.Number> Generator<T>	GeneratorFactory.getNumberGenerator(java.lang.Class<T> numberType, T min, T max, T precision, Distribution distribution, boolean unique) Creates a generator for numbers.

Uses of Distribution in org.databene.benerator.primitive

Fields in org.databene.benerator.primitive with type parameters of type Distribution

protected org.databene.commons.Expression<? extends Distribution>

DynamicLongGenerator.distribution

Constructor parameters in org.databene.benerator.primitive with type arguments of type Distribution

DynamicCountGenerator(org.databene.commons.Expression<java.lang.Long> min, org.databene.commons.Expression<java.lang.Long> max, org.databene.commons.Expression<java.lang.Long> precision, org.databene.commons.Expression<? extends Distribution> distribution, org.databene.commons.Expression<java.lang.Boolean> unique, boolean resetToMin)

DynamicLongGenerator(org.databene.commons.Expression<java.lang.Long> min, org.databene.commons.Expression<java.lang.Long> max, org.databene.commons.Expression<java.lang.Long> precision, org.databene.commons.Expression<? extends Distribution> distribution, org.databene.commons.Expression<java.lang.Boolean> unique)

Uses of Distribution in org.databene.benerator.primitive.datetime

Fields in org.databene.benerator.primitive.datetime declared as Distribution

protected Distribution

DayGenerator.distribution

Methods in org.databene.benerator.primitive.datetime with parameters of type Distribution

void	DateTimeGenerator.setDateDistribution(Distribution distribution)
void	DayGenerator.setDistribution(Distribution distribution)
void	DateGenerator.setDistribution(Distribution distribution) Sets the distribution to use
void	DateTimeGenerator.setTimeDistribution(Distribution distribution)

Constructors in org.databene.benerator.primitive.datetime with parameters of type Distribution

DateGenerator(java.util.Date min, java.util.Date max, long precision, Distribution distribution)
Initializes the generator to create dates of a Sequence or WeightFunction

DateGenerator(java.util.Date min, java.util.Date max, long precision, Distribution distribution, boolean unique)
Initializes the generator to create dates of a Sequence or WeightFunction

DayGenerator(java.util.Date min, java.util.Date max, Distribution distribution, boolean unique)

Uses of Distribution in org.databene.benerator.primitive.number

Methods in org.databene.benerator.primitive.number that return Distribution

Distribution

NoiseInducer.getNoiseDistribution()

Methods in org.databene.benerator.primitive.number with parameters of type Distribution

void	NoiseInducer.setNoiseDistribution(Distribution noiseDistribution)

Uses of Distribution in org.databene.benerator.sample

Methods in org.databene.benerator.sample that return Distribution

Distribution

AttachedWeightSampleGenerator.getDistribution()

Methods in org.databene.benerator.sample with parameters of type Distribution

void	AttachedWeightSampleGenerator.setDistribution(Distribution distribution)

Constructors in org.databene.benerator.sample with parameters of type Distribution

AttachedWeightSampleGenerator(java.lang.Class<E> generatedType, Distribution distribution, E... values)
Initializes the generator to an unweighted sample list

AttachedWeightSampleGenerator(java.lang.Class<E> generatedType, Distribution distribution, java.lang.Iterable<E> values)
Initializes the generator to an unweighted sample list

SampleGenerator(java.lang.Class<E> generatedType, Distribution distribution, boolean unique, java.lang.Iterable<E> values)
Initializes the generator to a sample list

SampleGenerator(java.lang.Class<E> generatedType, Distribution distribution, E... values)
Initializes the generator to a sample list

Uses of Distribution in org.databene.benerator.wrapper

Methods in org.databene.benerator.wrapper with parameters of type Distribution

void	CardinalGenerator.setCountDistribution(Distribution distribution)

Constructors in org.databene.benerator.wrapper with parameters of type Distribution

AbstractArrayGenerator(Generator<E> source, java.lang.Class<E> componentType, java.lang.Class<A> generatedType, int minLength, int maxLength, Distribution lengthDistribution)

ByteArrayGenerator(Generator<java.lang.Byte> source, int minLength, int maxLength, Distribution distribution)

CardinalGenerator(Generator<S> source, long minCount, long maxCount, long countPrecision, Distribution countDistribution)

CollectionGenerator(java.lang.Class<C> collectionType, Generator<I> source, int minSize, int maxSize, Distribution sizeDistribution)

RepeatGeneratorProxy(Generator<E> source, long minRepetitions, long maxRepetitions, int repetitionPrecision, Distribution repetitionDistribution)

SimpleArrayGenerator(Generator<E> source, java.lang.Class<E> componentType, int minLength, int maxLength, Distribution lengthDistribution)

SkipGeneratorProxy(Generator<E> source, java.lang.Long minIncrement, java.lang.Long maxIncrement, Distribution incrementDistribution, java.lang.Long limit)
Initializes the generator to use a random increment of uniform distribution

Uses of Distribution in org.databene.domain.math

Classes in org.databene.domain.math that implement Distribution

class	FibonacciSequence Sequence-based implementation of the Fibonacci Sequence Created at 03.07.2009 10:43:09
class	PadovanSequence Sequence-based implementation of the Padovan Sequence Created at 03.07.2009 13:14:05