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release/4.3a0
Varun Agrawal 2023-07-23 17:09:51 -04:00
parent 52f26e3e97
commit 2df3cc80a9
2 changed files with 16 additions and 17 deletions
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28
gtsam/hybrid/HybridBayesTree.cpp
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@ -175,15 +175,14 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
void HybridBayesTree::prune(const size_t maxNrLeaves) {
auto discreteProbs = this->roots_.at(0)->conditional()->asDiscrete();
// TODO(Varun)
// TableFactor prunedDiscreteProbs = discreteProbs->prune(maxNrLeaves);
// discreteProbs->root_ = prunedDiscreteProbs.root_;
DecisionTreeFactor prunedDiscreteProbs = discreteProbs->prune(maxNrLeaves);
discreteProbs->root_ = prunedDiscreteProbs.root_;
/// Helper struct for pruning the hybrid bayes tree.
struct HybridPrunerData {
/// The discrete decision tree after pruning.
TableFactor prunedDiscreteProbs;
HybridPrunerData(const TableFactor& prunedDiscreteProbs,
DecisionTreeFactor prunedDiscreteProbs;
HybridPrunerData(const DecisionTreeFactor& prunedDiscreteProbs,
const HybridBayesTree::sharedNode& parentClique)
: prunedDiscreteProbs(prunedDiscreteProbs) {}
@ -211,16 +210,15 @@ void HybridBayesTree::prune(const size_t maxNrLeaves) {
}
};
// TODO(Varun)
// HybridPrunerData rootData(prunedDiscreteProbs, 0);
// {
// treeTraversal::no_op visitorPost;
// // Limits OpenMP threads since we're mixing TBB and OpenMP
// TbbOpenMPMixedScope threadLimiter;
// treeTraversal::DepthFirstForestParallel(
// *this, rootData, HybridPrunerData::AssignmentPreOrderVisitor,
// visitorPost);
// }
HybridPrunerData rootData(prunedDiscreteProbs, 0);
{
treeTraversal::no_op visitorPost;
// Limits OpenMP threads since we're mixing TBB and OpenMP
TbbOpenMPMixedScope threadLimiter;
treeTraversal::DepthFirstForestParallel(
*this, rootData, HybridPrunerData::AssignmentPreOrderVisitor,
visitorPost);
}
}
} // namespace gtsam

5
gtsam/hybrid/HybridGaussianFactorGraph.cpp
View File

@ -273,8 +273,9 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
DecisionTree<Key, double> probabilities(eliminationResults, probability);
return {std::make_shared<HybridConditional>(gaussianMixture),
std::make_shared<TableFactor>(discreteSeparator, probabilities)};
return {
std::make_shared<HybridConditional>(gaussianMixture),
std::make_shared<DecisionTreeFactor>(discreteSeparator, probabilities)};
} else {
// Otherwise, we create a resulting GaussianMixtureFactor on the separator,
// taking care to correct for conditional constant.