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> preprocessor)
           
 

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)
           
IndexBasedSampleGeneratorProxy(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 granularity, long initial, long minIncrement, long maxIncrement, Distribution incrementDistribution)
           
RepeatSequence(int minRepetitions, int maxRepetitions, int repetitionGranularity, 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
 Distribution StochasticGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
           
 Distribution SerialGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
           
abstract  Distribution GeneratorFactory.defaultDistribution(Uniqueness uniqueness)
           
 Distribution EquivalenceGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
           
 Distribution CoverageGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
           
protected  Distribution StochasticGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness, boolean required)
           
protected  Distribution SerialGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness, boolean required)
           
protected abstract  Distribution GeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness, boolean required)
           
protected  Distribution EquivalenceGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness, boolean required)
           
static Distribution FactoryUtil.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.script.Expression<Distribution> FactoryUtil.getDistributionExpression(java.lang.String spec, Uniqueness uniqueness, boolean required)
           
 

Methods in org.databene.benerator.factory with parameters of type Distribution
 Generator<java.util.Date> SerialGeneratorFactory.createDateGenerator(java.util.Date min, java.util.Date max, long granularity, Distribution distribution)
           
 Generator<java.util.Date> GeneratorFactory.createDateGenerator(java.util.Date min, java.util.Date max, long granularity, Distribution distribution)
          Creates a Date generator that generates random dates.
 Generator<java.util.Date> EquivalenceGeneratorFactory.createDateGenerator(java.util.Date min, java.util.Date max, long granularity, Distribution distribution)
           
 Generator<java.util.Date> CoverageGeneratorFactory.createDateGenerator(java.util.Date min, java.util.Date max, long granularity, Distribution distribution)
           
<T> Generator<T>
StochasticGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec, java.lang.Class<T> targetType, Distribution distribution, boolean unique)
           
<T> Generator<T>
SerialGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec, java.lang.Class<T> targetType, Distribution distribution, boolean unique)
           
abstract
<T> Generator<T>
GeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec, java.lang.Class<T> targetType, Distribution distribution, boolean unique)
           
<T> Generator<T>
EquivalenceGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec, java.lang.Class<T> targetType, Distribution distribution, boolean unique)
           
<T extends java.lang.Number>
NonNullGenerator<T>
SerialGeneratorFactory.createNumberGenerator(java.lang.Class<T> numberType, T min, java.lang.Boolean minInclusive, T max, java.lang.Boolean maxInclusive, T granularity, Distribution distribution, Uniqueness uniqueness)
           
<T extends java.lang.Number>
NonNullGenerator<T>
GeneratorFactory.createNumberGenerator(java.lang.Class<T> numberType, T min, java.lang.Boolean minInclusive, T max, java.lang.Boolean maxInclusive, T granularity, Distribution distribution, Uniqueness uniqueness)
          Creates a generator for numbers.
<T extends java.lang.Number>
NonNullGenerator<T>
EquivalenceGeneratorFactory.createNumberGenerator(java.lang.Class<T> numberType, T min, java.lang.Boolean minInclusive, T max, java.lang.Boolean maxInclusive, T granularity, Distribution distribution, Uniqueness uniqueness)
           
<T extends java.lang.Number>
NonNullGenerator<T>
CoverageGeneratorFactory.createNumberGenerator(java.lang.Class<T> numberType, T min, java.lang.Boolean minInclusive, T max, java.lang.Boolean maxInclusive, T granularity, Distribution distribution, Uniqueness uniqueness)
           
 NonNullGenerator<java.lang.String> StochasticGeneratorFactory.createStringGenerator(java.util.Set<java.lang.Character> chars, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
 NonNullGenerator<java.lang.String> SerialGeneratorFactory.createStringGenerator(java.util.Set<java.lang.Character> chars, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
abstract  NonNullGenerator<java.lang.String> GeneratorFactory.createStringGenerator(java.util.Set<java.lang.Character> chars, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
 NonNullGenerator<java.lang.String> EquivalenceGeneratorFactory.createStringGenerator(java.util.Set<java.lang.Character> chars, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
 NonNullGenerator<java.lang.String> CoverageGeneratorFactory.createStringGenerator(java.util.Set<java.lang.Character> chars, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
 Generator<java.lang.String> GeneratorFactory.createStringGenerator(java.lang.String pattern, java.util.Locale locale, java.lang.Integer minLength, java.lang.Integer maxLength, int lengthGranularity, Distribution lengthDistribution, Uniqueness uniqueness)
           
 

Uses of Distribution in org.databene.benerator.primitive
 

Fields in org.databene.benerator.primitive declared as Distribution
protected  Distribution LuhnGenerator.lengthDistribution
           
 

Fields in org.databene.benerator.primitive with type parameters of type Distribution
protected  org.databene.script.Expression<? extends Distribution> DynamicLongGenerator.distribution
           
 

Methods in org.databene.benerator.primitive that return Distribution
 Distribution StringGenerator.getLengthDistribution()
           
 

Methods in org.databene.benerator.primitive with parameters of type Distribution
 void StringGenerator.setLengthDistribution(Distribution lengthDistribution)
           
 

Constructors in org.databene.benerator.primitive with parameters of type Distribution
LuhnGenerator(java.lang.String prefix, int minLength, int maxLength, int lengthGranularity, Distribution lengthDistribution)
           
RandomVarLengthStringGenerator(java.util.Set<java.lang.Character> chars, int minLength, int maxLength, int lengthGranularity, Distribution lengthDistribution)
           
RandomVarLengthStringGenerator(java.lang.String pattern, int minLength, int maxLength, int lengthGranularity, Distribution lengthDistribution)
           
StringGenerator(java.lang.String charSet, java.util.Locale locale, boolean unique, boolean ordered, java.lang.String prefix, java.lang.Character minInitial, java.lang.String suffix, int minLength, int maxLength, int lengthGranularity, Distribution lengthDistribution)
           
 

Constructor parameters in org.databene.benerator.primitive with type arguments of type Distribution
DynamicCountGenerator(org.databene.script.Expression<java.lang.Long> min, org.databene.script.Expression<java.lang.Long> max, org.databene.script.Expression<java.lang.Long> granularity, org.databene.script.Expression<? extends Distribution> distribution, org.databene.script.Expression<java.lang.Boolean> unique, boolean resetToMin)
           
DynamicLongGenerator(org.databene.script.Expression<java.lang.Long> min, org.databene.script.Expression<java.lang.Long> max, org.databene.script.Expression<java.lang.Long> granularity, org.databene.script.Expression<? extends Distribution> distribution, org.databene.script.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 granularity, Distribution distribution)
          Initializes the generator to create dates of a Sequence or WeightFunction
DateGenerator(java.util.Date min, java.util.Date max, long granularity, 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
 

Constructors in org.databene.benerator.sample with parameters of type Distribution
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 that return Distribution
 Distribution LengthGenerator.getLengthDistribution()
           
 

Methods in org.databene.benerator.wrapper with parameters of type Distribution
 void LengthGenerator.setLengthDistribution(Distribution lengthDistribution)
           
 

Constructors in org.databene.benerator.wrapper with parameters of type Distribution
ByteArrayGenerator(Generator<java.lang.Byte> source, int minLength, int maxLength, Distribution distribution)
           
CardinalGenerator(Generator<S> source, boolean resettingCardinalGenerator, int minCardinal, int maxCardinal, int cardinalGranularity, Distribution cardinalDistribution)
           
CollectionGenerator(java.lang.Class<C> collectionType, Generator<I> source, int minSize, int maxSize, Distribution sizeDistribution)
           
LengthGenerator(Generator<S> source, boolean resettingLengthGenerator, int minLength, int maxLength, int lengthGranularity, Distribution lengthDistribution)
           
RepeatGeneratorProxy(Generator<E> source, int minRepetitions, int maxRepetitions, int repetitionGranularity, Distribution repetitionDistribution)
           
SingleSourceArrayGenerator(Generator<S> source, java.lang.Class<S> componentType, int minLength, int maxLength, Distribution lengthDistribution)
           
SkipGeneratorProxy(Generator<E> source, int minIncrement, int maxIncrement, Distribution incrementDistribution, java.lang.Integer 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
 



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