Package org.databene.benerator.sample

Provides Generators that are based on collections of samples.

See:
Description

Class Summary

AbstractSampleGenerator<E>	Generates values from a list of samples.
AttachedWeightSampleGenerator<E>	Generates values from a weighted or non-weighted set of samples.
ConstantGenerator<E>	Generator implementation that always returns the same value.
IndividualWeightGenerator<E>	Generator for IndividualWeight distributions.
MappedSampleGenerator<E>	IndividualWeightGenerator implementation that organizes sample data in a Map of value-weight associations.
OneShotGenerator<E>	Returns a value only once and then becomes unavailable immediately.
SampleGenerator<E>	Generates values from a non-weighted list of samples, applying an explicitly defined distribution.
SampleGeneratorUtil	Provides utility methods for sample-based generators.
SeedGenerator<E>	Generates value sequences derived from seed sequences.
SeedManager<E>	Counts frequencies of atoms and provides random atoms with the same frequency.
SequencedCSVSampleGenerator<E>	Sample Generator for values that are read from a CSV file.
SequenceGenerator<E>	Creates a predefined sequence of objects.
StateGenerator<E>	Generates states as configured by a state machine.
StateTransitionGenerator<E>	Generates state transitions of a state machine.
WeightedCSVSampleGenerator<E>	Sample Generator for values that are read from a CSV file.
WeightedSample<E>	Represents a single sample value for a generator.

Package org.databene.benerator.sample Description

Provides Generators that are based on collections of samples. Samples may have individual weights.