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@ -173,8 +173,7 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
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/* ************************************************************************* */
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void HybridBayesTree::prune(const size_t maxNrLeaves) {
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auto decisionTree =
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this->roots_.at(0)->conditional()->asDiscrete();
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auto decisionTree = this->roots_.at(0)->conditional()->asDiscrete();
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DecisionTreeFactor prunedDecisionTree = decisionTree->prune(maxNrLeaves);
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decisionTree->root_ = prunedDecisionTree.root_;
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@ -70,8 +70,7 @@ Ordering HybridGaussianISAM::GetOrdering(
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/* ************************************************************************* */
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void HybridGaussianISAM::updateInternal(
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const HybridGaussianFactorGraph& newFactors,
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HybridBayesTree::Cliques* orphans,
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const std::optional<size_t>& maxNrLeaves,
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HybridBayesTree::Cliques* orphans, const std::optional<size_t>& maxNrLeaves,
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const std::optional<Ordering>& ordering,
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const HybridBayesTree::Eliminate& function) {
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// Remove the contaminated part of the Bayes tree
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@ -101,8 +100,8 @@ void HybridGaussianISAM::updateInternal(
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}
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// eliminate all factors (top, added, orphans) into a new Bayes tree
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HybridBayesTree::shared_ptr bayesTree =
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factors.eliminateMultifrontal(elimination_ordering, function, std::cref(index));
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HybridBayesTree::shared_ptr bayesTree = factors.eliminateMultifrontal(
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elimination_ordering, function, std::cref(index));
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if (maxNrLeaves) {
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bayesTree->prune(*maxNrLeaves);
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