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Packages that use Distribution | |
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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 |
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Constructors in org.databene.benerator.csv with parameters of type Distribution | |
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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)
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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)
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Uses of Distribution in org.databene.benerator.distribution |
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Subinterfaces of Distribution in org.databene.benerator.distribution | |
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interface |
Weight
Common parent class for all Generator s that are based on weights. |
interface |
WeightFunction
Common interface for weight functions. |
Classes in org.databene.benerator.distribution that implement Distribution | |
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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 | |
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Distribution |
WeightedLongGenerator.getDistribution()
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Distribution |
WeightedDoubleGenerator.getDistribution()
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Methods in org.databene.benerator.distribution with parameters of type Distribution | |
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void |
WeightedLongGenerator.setDistribution(Distribution distribution)
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Constructors in org.databene.benerator.distribution with parameters of type Distribution | |
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DistributingGenerator(Generator<E> dataProvider,
Distribution distribution,
boolean unique)
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IndexBasedSampleGeneratorProxy(Generator<E> dataProvider,
Distribution distribution,
boolean unique)
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Uses of Distribution in org.databene.benerator.distribution.cumulative |
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Classes in org.databene.benerator.distribution.cumulative that implement Distribution | |
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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 |
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Classes in org.databene.benerator.distribution.function that implement Distribution | |
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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 |
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Classes in org.databene.benerator.distribution.sequence that implement Distribution | |
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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 | |
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RandomWalkLongGenerator(long min,
long max,
long granularity,
long initial,
long minIncrement,
long maxIncrement,
Distribution incrementDistribution)
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RepeatSequence(int minRepetitions,
int maxRepetitions,
int repetitionGranularity,
Distribution repetitionDistribution)
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Uses of Distribution in org.databene.benerator.engine.parser |
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Methods in org.databene.benerator.engine.parser that return Distribution | |
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Distribution |
String2DistributionConverter.convert(java.lang.String stringOrScript)
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Uses of Distribution in org.databene.benerator.factory |
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Methods in org.databene.benerator.factory that return Distribution | |
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Distribution |
StochasticGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
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Distribution |
SerialGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
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abstract Distribution |
GeneratorFactory.defaultDistribution(Uniqueness uniqueness)
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Distribution |
EquivalenceGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
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Distribution |
CoverageGeneratorFactory.defaultDistribution(Uniqueness uniqueness)
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protected Distribution |
StochasticGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness,
boolean required)
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protected Distribution |
SerialGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness,
boolean required)
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protected abstract Distribution |
GeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness,
boolean required)
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protected Distribution |
EquivalenceGeneratorFactory.defaultLengthDistribution(Uniqueness uniqueness,
boolean required)
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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 | |
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static org.databene.script.Expression<Distribution> |
FactoryUtil.getDistributionExpression(java.lang.String spec,
Uniqueness uniqueness,
boolean required)
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Methods in org.databene.benerator.factory with parameters of type Distribution | ||
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Generator<java.util.Date> |
SerialGeneratorFactory.createDateGenerator(java.util.Date min,
java.util.Date max,
long granularity,
Distribution distribution)
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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. |
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Generator<java.util.Date> |
EquivalenceGeneratorFactory.createDateGenerator(java.util.Date min,
java.util.Date max,
long granularity,
Distribution distribution)
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Generator<java.util.Date> |
CoverageGeneratorFactory.createDateGenerator(java.util.Date min,
java.util.Date max,
long granularity,
Distribution distribution)
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StochasticGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec,
java.lang.Class<T> targetType,
Distribution distribution,
boolean unique)
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SerialGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec,
java.lang.Class<T> targetType,
Distribution distribution,
boolean unique)
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abstract
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GeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec,
java.lang.Class<T> targetType,
Distribution distribution,
boolean unique)
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EquivalenceGeneratorFactory.createFromWeightedLiteralList(java.lang.String valueSpec,
java.lang.Class<T> targetType,
Distribution distribution,
boolean unique)
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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)
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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. |
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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Uses of Distribution in org.databene.benerator.primitive |
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Fields in org.databene.benerator.primitive declared as Distribution | |
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protected Distribution |
LuhnGenerator.lengthDistribution
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Fields in org.databene.benerator.primitive with type parameters of type Distribution | |
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protected org.databene.script.Expression<? extends Distribution> |
DynamicLongGenerator.distribution
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Methods in org.databene.benerator.primitive that return Distribution | |
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Distribution |
StringGenerator.getLengthDistribution()
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Methods in org.databene.benerator.primitive with parameters of type Distribution | |
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void |
StringGenerator.setLengthDistribution(Distribution lengthDistribution)
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Constructors in org.databene.benerator.primitive with parameters of type Distribution | |
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LuhnGenerator(java.lang.String prefix,
int minLength,
int maxLength,
int lengthGranularity,
Distribution lengthDistribution)
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RandomVarLengthStringGenerator(java.util.Set<java.lang.Character> chars,
int minLength,
int maxLength,
int lengthGranularity,
Distribution lengthDistribution)
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RandomVarLengthStringGenerator(java.lang.String pattern,
int minLength,
int maxLength,
int lengthGranularity,
Distribution lengthDistribution)
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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)
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Constructor parameters in org.databene.benerator.primitive with type arguments of type Distribution | |
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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)
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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)
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Uses of Distribution in org.databene.benerator.primitive.datetime |
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Fields in org.databene.benerator.primitive.datetime declared as Distribution | |
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protected Distribution |
DayGenerator.distribution
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Methods in org.databene.benerator.primitive.datetime with parameters of type Distribution | |
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void |
DateTimeGenerator.setDateDistribution(Distribution distribution)
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void |
DayGenerator.setDistribution(Distribution distribution)
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void |
DateGenerator.setDistribution(Distribution distribution)
Sets the distribution to use |
void |
DateTimeGenerator.setTimeDistribution(Distribution distribution)
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Constructors in org.databene.benerator.primitive.datetime with parameters of type Distribution | |
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DateGenerator(java.util.Date min,
java.util.Date max,
long granularity,
Distribution distribution)
Initializes the generator to create dates of a Sequence or WeightFunction |
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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)
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Uses of Distribution in org.databene.benerator.primitive.number |
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Methods in org.databene.benerator.primitive.number that return Distribution | |
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Distribution |
NoiseInducer.getNoiseDistribution()
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Methods in org.databene.benerator.primitive.number with parameters of type Distribution | |
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void |
NoiseInducer.setNoiseDistribution(Distribution noiseDistribution)
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Uses of Distribution in org.databene.benerator.sample |
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Constructors in org.databene.benerator.sample with parameters of type Distribution | |
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SampleGenerator(java.lang.Class<E> generatedType,
Distribution distribution,
boolean unique,
java.lang.Iterable<E> values)
Initializes the generator to a sample list |
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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 |
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Methods in org.databene.benerator.wrapper that return Distribution | |
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Distribution |
LengthGenerator.getLengthDistribution()
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Methods in org.databene.benerator.wrapper with parameters of type Distribution | |
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void |
LengthGenerator.setLengthDistribution(Distribution lengthDistribution)
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Constructors in org.databene.benerator.wrapper with parameters of type Distribution | |
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ByteArrayGenerator(Generator<java.lang.Byte> source,
int minLength,
int maxLength,
Distribution distribution)
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CardinalGenerator(Generator<S> source,
boolean resettingCardinalGenerator,
int minCardinal,
int maxCardinal,
int cardinalGranularity,
Distribution cardinalDistribution)
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CollectionGenerator(java.lang.Class<C> collectionType,
Generator<I> source,
int minSize,
int maxSize,
Distribution sizeDistribution)
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LengthGenerator(Generator<S> source,
boolean resettingLengthGenerator,
int minLength,
int maxLength,
int lengthGranularity,
Distribution lengthDistribution)
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RepeatGeneratorProxy(Generator<E> source,
int minRepetitions,
int maxRepetitions,
int repetitionGranularity,
Distribution repetitionDistribution)
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SingleSourceArrayGenerator(Generator<S> source,
java.lang.Class<S> componentType,
int minLength,
int maxLength,
Distribution lengthDistribution)
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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 |
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Classes in org.databene.domain.math that implement Distribution | |
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class |
FibonacciSequence
Sequence -based implementation of the
Fibonacci SequenceCreated at 03.07.2009 10:43:09 |
class |
PadovanSequence
Sequence -based implementation of the
Padovan SequenceCreated at 03.07.2009 13:14:05 |
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