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release/4.3a0
Varun Agrawal 2023-06-09 10:18:36 -04:00
parent 0cb1316753
commit 76568f2d73
2 changed files with 4 additions and 6 deletions
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3
gtsam/hybrid/HybridBayesTree.cpp
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@ -173,8 +173,7 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
/* ************************************************************************* */ /* ************************************************************************* */
void HybridBayesTree::prune(const size_t maxNrLeaves) { void HybridBayesTree::prune(const size_t maxNrLeaves) {
auto decisionTree = auto decisionTree = this->roots_.at(0)->conditional()->asDiscrete();
this->roots_.at(0)->conditional()->asDiscrete();
DecisionTreeFactor prunedDecisionTree = decisionTree->prune(maxNrLeaves); DecisionTreeFactor prunedDecisionTree = decisionTree->prune(maxNrLeaves);
decisionTree->root_ = prunedDecisionTree.root_; decisionTree->root_ = prunedDecisionTree.root_;

7
gtsam/hybrid/HybridGaussianISAM.cpp
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@ -70,8 +70,7 @@ Ordering HybridGaussianISAM::GetOrdering(
/* ************************************************************************* */ /* ************************************************************************* */
void HybridGaussianISAM::updateInternal( void HybridGaussianISAM::updateInternal(
const HybridGaussianFactorGraph& newFactors, const HybridGaussianFactorGraph& newFactors,
HybridBayesTree::Cliques* orphans, HybridBayesTree::Cliques* orphans, const std::optional<size_t>& maxNrLeaves,
const std::optional<size_t>& maxNrLeaves,
const std::optional<Ordering>& ordering, const std::optional<Ordering>& ordering,
const HybridBayesTree::Eliminate& function) { const HybridBayesTree::Eliminate& function) {
// Remove the contaminated part of the Bayes tree // Remove the contaminated part of the Bayes tree
@ -101,8 +100,8 @@ void HybridGaussianISAM::updateInternal(
} }
// eliminate all factors (top, added, orphans) into a new Bayes tree // eliminate all factors (top, added, orphans) into a new Bayes tree
HybridBayesTree::shared_ptr bayesTree = HybridBayesTree::shared_ptr bayesTree = factors.eliminateMultifrontal(
factors.eliminateMultifrontal(elimination_ordering, function, std::cref(index)); elimination_ordering, function, std::cref(index));
if (maxNrLeaves) { if (maxNrLeaves) {
bayesTree->prune(*maxNrLeaves); bayesTree->prune(*maxNrLeaves);