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remove model

release/4.3a0
Varun Agrawal 2022-12-24 07:13:40 +05:30
parent 789b5d2eb6
commit c245264388
2 changed files with 12 additions and 21 deletions
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19
gtsam/hybrid/HybridBayesNet.cpp
View File

@ -236,8 +236,7 @@ VectorValues HybridBayesNet::optimize(const DiscreteValues &assignment) const {
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(VectorValues given, std::mt19937_64 *rng,
SharedDiagonal model) const {
HybridValues HybridBayesNet::sample(VectorValues given, std::mt19937_64 *rng) const {
DiscreteBayesNet dbn;
for (size_t idx = 0; idx < size(); idx++) {
if (factors_.at(idx)->isDiscrete()) {
@ -250,26 +249,24 @@ HybridValues HybridBayesNet::sample(VectorValues given, std::mt19937_64 *rng,
// Select the continuous bayes net corresponding to the assignment.
GaussianBayesNet gbn = this->choose(assignment);
// Sample from the gaussian bayes net.
VectorValues sample = gbn.sample(given, rng, model);
VectorValues sample = gbn.sample(given, rng);
return HybridValues(assignment, sample);
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(std::mt19937_64 *rng,
SharedDiagonal model) const {
HybridValues HybridBayesNet::sample(std::mt19937_64 *rng) const {
VectorValues given;
return sample(given, rng, model);
return sample(given, rng);
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(VectorValues given,
SharedDiagonal model) const {
return sample(given, &kRandomNumberGenerator, model);
HybridValues HybridBayesNet::sample(VectorValues given) const {
return sample(given, &kRandomNumberGenerator);
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(SharedDiagonal model) const {
return sample(&kRandomNumberGenerator, model);
HybridValues HybridBayesNet::sample() const {
return sample(&kRandomNumberGenerator);
}
/* ************************************************************************* */

14
gtsam/hybrid/HybridBayesNet.h
View File

@ -130,11 +130,9 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
*
* @param given Values of missing variables.
* @param rng The pseudo-random number generator.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues
*/
HybridValues sample(VectorValues given, std::mt19937_64 *rng,
SharedDiagonal model = nullptr) const;
HybridValues sample(VectorValues given, std::mt19937_64 *rng) const;
/**
* @brief Sample using ancestral sampling.
@ -144,28 +142,24 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
* auto sample = bn.sample(&rng);
*
* @param rng The pseudo-random number generator.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues
*/
HybridValues sample(std::mt19937_64 *rng,
SharedDiagonal model = nullptr) const;
HybridValues sample(std::mt19937_64 *rng) const;
/**
* @brief Sample from an incomplete BayesNet, use default rng.
*
* @param given Values of missing variables.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues
*/
HybridValues sample(VectorValues given, SharedDiagonal model = nullptr) const;
HybridValues sample(VectorValues given) const;
/**
* @brief Sample using ancestral sampling, use default rng.
*
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues
*/
HybridValues sample(SharedDiagonal model = nullptr) const;
HybridValues sample() const;
/// Prune the Hybrid Bayes Net such that we have at most maxNrLeaves leaves.
HybridBayesNet prune(size_t maxNrLeaves);