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Use TableFactor in hybrid elimination

release/4.3a0
Varun Agrawal 2023-07-13 16:39:55 -04:00
parent baf25de684
commit 9c88e3ed96
5 changed files with 21 additions and 21 deletions
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6
gtsam/hybrid/GaussianMixture.cpp
View File

@ -234,7 +234,7 @@ std::set<DiscreteKey> DiscreteKeysAsSet(const DiscreteKeys &discreteKeys) {
*/
std::function<GaussianConditional::shared_ptr(
const Assignment<Key> &, const GaussianConditional::shared_ptr &)>
GaussianMixture::prunerFunc(const DecisionTreeFactor &discreteProbs) {
GaussianMixture::prunerFunc(const TableFactor &discreteProbs) {
// Get the discrete keys as sets for the decision tree
// and the gaussian mixture.
auto discreteProbsKeySet = DiscreteKeysAsSet(discreteProbs.discreteKeys());
@ -285,9 +285,7 @@ GaussianMixture::prunerFunc(const DecisionTreeFactor &discreteProbs) {
}
/* *******************************************************************************/
void GaussianMixture::prune(const DecisionTreeFactor &discreteProbs) {
auto discreteProbsKeySet = DiscreteKeysAsSet(discreteProbs.discreteKeys());
auto gmKeySet = DiscreteKeysAsSet(this->discreteKeys());
void GaussianMixture::prune(const TableFactor &discreteProbs) {
// Functional which loops over all assignments and create a set of
// GaussianConditionals
auto pruner = prunerFunc(discreteProbs);

5
gtsam/hybrid/GaussianMixture.h
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@ -23,6 +23,7 @@
#include <gtsam/discrete/DecisionTree.h>
#include <gtsam/discrete/DecisionTreeFactor.h>
#include <gtsam/discrete/DiscreteKey.h>
#include <gtsam/discrete/TableFactor.h>
#include <gtsam/hybrid/GaussianMixtureFactor.h>
#include <gtsam/hybrid/HybridFactor.h>
#include <gtsam/inference/Conditional.h>
@ -80,7 +81,7 @@ class GTSAM_EXPORT GaussianMixture
*/
std::function<GaussianConditional::shared_ptr(
const Assignment<Key> &, const GaussianConditional::shared_ptr &)>
prunerFunc(const DecisionTreeFactor &discreteProbs);
prunerFunc(const TableFactor &discreteProbs);
public:
/// @name Constructors
@ -238,7 +239,7 @@ class GTSAM_EXPORT GaussianMixture
*
* @param discreteProbs A pruned set of probabilities for the discrete keys.
*/
void prune(const DecisionTreeFactor &discreteProbs);
void prune(const TableFactor &discreteProbs);
/**
* @brief Merge the Gaussian Factor Graphs in `this` and `sum` while

2
gtsam/hybrid/HybridBayesNet.cpp
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@ -64,7 +64,7 @@ DecisionTreeFactor::shared_ptr HybridBayesNet::discreteConditionals() const {
* @return std::function<double(const Assignment<Key> &, double)>
*/
std::function<double(const Assignment<Key> &, double)> prunerFunc(
const DecisionTreeFactor &prunedDiscreteProbs,
const TableFactor &prunedDiscreteProbs,
const HybridConditional &conditional) {
// Get the discrete keys as sets for the decision tree
// and the Gaussian mixture.

1
gtsam/hybrid/HybridBayesNet.h
View File

@ -17,7 +17,6 @@
#pragma once
#include <gtsam/discrete/DecisionTreeFactor.h>
#include <gtsam/global_includes.h>
#include <gtsam/hybrid/HybridConditional.h>
#include <gtsam/hybrid/HybridValues.h>

28
gtsam/hybrid/HybridBayesTree.cpp
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@ -175,14 +175,15 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
void HybridBayesTree::prune(const size_t maxNrLeaves) {
auto discreteProbs = this->roots_.at(0)->conditional()->asDiscrete();
DecisionTreeFactor prunedDiscreteProbs = discreteProbs->prune(maxNrLeaves);
discreteProbs->root_ = prunedDiscreteProbs.root_;
// TODO(Varun)
// TableFactor prunedDiscreteProbs = discreteProbs->prune(maxNrLeaves);
// discreteProbs->root_ = prunedDiscreteProbs.root_;
/// Helper struct for pruning the hybrid bayes tree.
struct HybridPrunerData {
/// The discrete decision tree after pruning.
DecisionTreeFactor prunedDiscreteProbs;
HybridPrunerData(const DecisionTreeFactor& prunedDiscreteProbs,
TableFactor prunedDiscreteProbs;
HybridPrunerData(const TableFactor& prunedDiscreteProbs,
const HybridBayesTree::sharedNode& parentClique)
: prunedDiscreteProbs(prunedDiscreteProbs) {}
@ -210,15 +211,16 @@ void HybridBayesTree::prune(const size_t maxNrLeaves) {
}
};
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);
}
// 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);
// }
}
} // namespace gtsam