Public Member Functions | |
void | addValue (double p, int[] state) |
void | applyWeight (WeightedSample s, int sampledValue) |
BackSamplingDistribution (Sampler sampler) | |
void | construct (BeliefNode node, int[] nodeDomainIndices) |
Public Attributes | |
Vector< Double > | distribution |
Vector< int[]> | states |
Protected Member Functions | |
void | construct (int i, int[] addr, CPF cpf, int[] nodeDomainIndices) |
Protected Attributes | |
Sampler | sampler |
Package Attributes | |
double | Z |
Definition at line 31 of file BackwardSampling.java.
edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::BackSamplingDistribution | ( | Sampler | sampler | ) | [inline] |
Definition at line 37 of file BackwardSampling.java.
void edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::addValue | ( | double | p, | |
int[] | state | |||
) | [inline] |
Definition at line 44 of file BackwardSampling.java.
void edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::applyWeight | ( | WeightedSample | s, | |
int | sampledValue | |||
) | [inline] |
Reimplemented in edu::tum::cs::bayesnets::inference::BackwardSamplingWithPriors::BackSamplingDistribution.
Definition at line 50 of file BackwardSampling.java.
void edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::construct | ( | int | i, | |
int[] | addr, | |||
CPF | cpf, | |||
int[] | nodeDomainIndices | |||
) | [inline, protected] |
recursively constructs the distribution to backward sample from
i | the node to instantiate next (as an index into the CPF's domain product) | |
addr | the current setting of node indices of the CPF's domain product | |
cpf | the conditional probability function of the node we are backward sampling | |
d | the distribution to fill |
Reimplemented in edu::tum::cs::bayesnets::inference::BackwardSamplingWithChildren::BackSamplingDistribution, edu::tum::cs::bayesnets::inference::BackwardSamplingWithPriors::BackSamplingDistribution, and edu::tum::cs::srl::bayesnets::inference::LiftedBackwardSampling::Sampler::BackSamplingDistribution.
Definition at line 69 of file BackwardSampling.java.
void edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::construct | ( | BeliefNode | node, | |
int[] | nodeDomainIndices | |||
) | [inline] |
Definition at line 54 of file BackwardSampling.java.
Vector<Double> edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::distribution |
Definition at line 32 of file BackwardSampling.java.
Sampler edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::sampler [protected] |
Definition at line 35 of file BackwardSampling.java.
Vector<int[]> edu::tum::cs::bayesnets::inference::BackwardSampling::BackSamplingDistribution::states |
Definition at line 33 of file BackwardSampling.java.
Definition at line 34 of file BackwardSampling.java.