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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, HybridValues HybridBayesNet::sample(VectorValues given, std::mt19937_64 *rng) const {
SharedDiagonal model) const {
DiscreteBayesNet dbn; DiscreteBayesNet dbn;
for (size_t idx = 0; idx < size(); idx++) { for (size_t idx = 0; idx < size(); idx++) {
if (factors_.at(idx)->isDiscrete()) { 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. // Select the continuous bayes net corresponding to the assignment.
GaussianBayesNet gbn = this->choose(assignment); GaussianBayesNet gbn = this->choose(assignment);
// Sample from the gaussian bayes net. // Sample from the gaussian bayes net.
VectorValues sample = gbn.sample(given, rng, model); VectorValues sample = gbn.sample(given, rng);
return HybridValues(assignment, sample); return HybridValues(assignment, sample);
} }
/* ************************************************************************* */ /* ************************************************************************* */
HybridValues HybridBayesNet::sample(std::mt19937_64 *rng, HybridValues HybridBayesNet::sample(std::mt19937_64 *rng) const {
SharedDiagonal model) const {
VectorValues given; VectorValues given;
return sample(given, rng, model); return sample(given, rng);
} }
/* ************************************************************************* */ /* ************************************************************************* */
HybridValues HybridBayesNet::sample(VectorValues given, HybridValues HybridBayesNet::sample(VectorValues given) const {
SharedDiagonal model) const { return sample(given, &kRandomNumberGenerator);
return sample(given, &kRandomNumberGenerator, model);
} }
/* ************************************************************************* */ /* ************************************************************************* */
HybridValues HybridBayesNet::sample(SharedDiagonal model) const { HybridValues HybridBayesNet::sample() const {
return sample(&kRandomNumberGenerator, model); 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 given Values of missing variables.
* @param rng The pseudo-random number generator. * @param rng The pseudo-random number generator.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues * @return HybridValues
*/ */
HybridValues sample(VectorValues given, std::mt19937_64 *rng, HybridValues sample(VectorValues given, std::mt19937_64 *rng) const;
SharedDiagonal model = nullptr) const;
/** /**
* @brief Sample using ancestral sampling. * @brief Sample using ancestral sampling.
@ -144,28 +142,24 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
* auto sample = bn.sample(&rng); * auto sample = bn.sample(&rng);
* *
* @param rng The pseudo-random number generator. * @param rng The pseudo-random number generator.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues * @return HybridValues
*/ */
HybridValues sample(std::mt19937_64 *rng, HybridValues sample(std::mt19937_64 *rng) const;
SharedDiagonal model = nullptr) const;
/** /**
* @brief Sample from an incomplete BayesNet, use default rng. * @brief Sample from an incomplete BayesNet, use default rng.
* *
* @param given Values of missing variables. * @param given Values of missing variables.
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues * @return HybridValues
*/ */
HybridValues sample(VectorValues given, SharedDiagonal model = nullptr) const; HybridValues sample(VectorValues given) const;
/** /**
* @brief Sample using ancestral sampling, use default rng. * @brief Sample using ancestral sampling, use default rng.
* *
* @param model Optional diagonal noise model to use in sampling.
* @return HybridValues * @return HybridValues
*/ */
HybridValues sample(SharedDiagonal model = nullptr) const; HybridValues sample() const;
/// Prune the Hybrid Bayes Net such that we have at most maxNrLeaves leaves. /// Prune the Hybrid Bayes Net such that we have at most maxNrLeaves leaves.
HybridBayesNet prune(size_t maxNrLeaves); HybridBayesNet prune(size_t maxNrLeaves);