public final class DataSampler extends Object
takeSample(com.bayesserver.inference.Evidence, java.util.Random, com.bayesserver.data.sampling.DataSamplingOptions) for sample code.| Constructor and Description |
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DataSampler(Network network)
Initializes a new instance of the
DataSampler class. |
DataSampler(Network network,
Evidence fixedData)
Initializes a new instance of the
DataSampler class. |
| Modifier and Type | Method and Description |
|---|---|
Network |
getNetwork()
Gets the Bayesian network or Dynamic Bayesian network that was used in the constructor.
|
void |
setFixedData(Evidence value)
Sets any evidence that should be fixed for each sample.
|
void |
takeSample(Evidence sampleData,
Random random,
DataSamplingOptions options)
Generates sample data from the Bayesian network or Dynamic Bayesian network.
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public DataSampler(Network network)
DataSampler class.network - The Bayesian network or Dynamic Bayesian network the samples will be taken from.public DataSampler(Network network, Evidence fixedData)
DataSampler class.network - The Bayesian network or Dynamic Bayesian network the samples will be taken from.fixedData - Any data that is fixed. Can be null.public Network getNetwork()
public void takeSample(Evidence sampleData, Random random, DataSamplingOptions options) throws InconsistentEvidenceException
takeSample(com.bayesserver.inference.Evidence, java.util.Random, com.bayesserver.data.sampling.DataSamplingOptions) generates a single sample. Call repeatedly to generate multiple samples.
For Dynamic Bayesian networks, see DataSamplingOptions.getSequenceLength() to change the length of generated sequences.
sampleData - Evidence instance to hold the sample data.random - Random number generator.options - The sampling options.InconsistentEvidenceException - Raised if the generation of a sample leads to inconsistent evidence.public void setFixedData(Evidence value)
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