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release/4.3a0
Frank Dellaert 2024-10-22 13:50:39 -07:00
parent 25f90701c7
commit 5145b8c47a
4 changed files with 14 additions and 22 deletions
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2
gtsam/hybrid/HybridGaussianISAM.cpp
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@ -10,7 +10,7 @@
* -------------------------------------------------------------------------- */
/**
* @file HybridGaussianISAM.h
* @file HybridGaussianISAM.cpp
* @date March 31, 2022
* @author Fan Jiang
* @author Frank Dellaert

8
gtsam/hybrid/HybridNonlinearISAM.cpp
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@ -39,8 +39,8 @@ void HybridNonlinearISAM::update(const HybridNonlinearFactorGraph& newFactors,
if (newFactors.size() > 0) {
// Reorder and relinearize every reorderInterval updates
if (reorderInterval_ > 0 && ++reorderCounter_ >= reorderInterval_) {
// TODO(Varun) Relinearization doesn't take into account pruning
reorder_relinearize();
// TODO(Varun) Re-linearization doesn't take into account pruning
reorderRelinearize();
reorderCounter_ = 0;
}
@ -60,7 +60,7 @@ void HybridNonlinearISAM::update(const HybridNonlinearFactorGraph& newFactors,
}
/* ************************************************************************* */
void HybridNonlinearISAM::reorder_relinearize() {
void HybridNonlinearISAM::reorderRelinearize() {
if (factors_.size() > 0) {
// Obtain the new linearization point
const Values newLinPoint = estimate();
@ -69,7 +69,7 @@ void HybridNonlinearISAM::reorder_relinearize() {
// Just recreate the whole BayesTree
// TODO: allow for constrained ordering here
// TODO: decouple relinearization and reordering to avoid
// TODO: decouple re-linearization and reordering to avoid
isam_.update(*factors_.linearize(newLinPoint), {}, {},
eliminationFunction_);

10
gtsam/hybrid/HybridNonlinearISAM.h
View File

@ -37,7 +37,7 @@ class GTSAM_EXPORT HybridNonlinearISAM {
/// The discrete assignment
DiscreteValues assignment_;
/** The original factors, used when relinearizing */
/** The original factors, used when re-linearizing */
HybridNonlinearFactorGraph factors_;
/** The reordering interval and counter */
@ -52,8 +52,8 @@ class GTSAM_EXPORT HybridNonlinearISAM {
/// @{
/**
* Periodically reorder and relinearize
* @param reorderInterval is the number of updates between reorderings,
* Periodically reorder and re-linearize
* @param reorderInterval is the number of updates between re-orderings,
* 0 never reorders (and is dangerous for memory consumption)
* 1 (default) reorders every time, in worse case is batch every update
* typical values are 50 or 100
@ -124,8 +124,8 @@ class GTSAM_EXPORT HybridNonlinearISAM {
const std::optional<size_t>& maxNrLeaves = {},
const std::optional<Ordering>& ordering = {});
/** Relinearization and reordering of variables */
void reorder_relinearize();
/** Re-linearization and reordering of variables */
void reorderRelinearize();
/// @}
};

16
gtsam/hybrid/tests/testHybridEstimation.cpp
View File

@ -339,12 +339,8 @@ TEST(HybridEstimation, Probability) {
HybridValues hybrid_values = bayesNet->optimize();
// This is the correct sequence as designed
DiscreteValues discrete_seq;
discrete_seq[M(0)] = 1;
discrete_seq[M(1)] = 1;
discrete_seq[M(2)] = 0;
EXPECT(assert_equal(discrete_seq, hybrid_values.discrete()));
DiscreteValues expectedSequence{{M(0), 1}, {M(1), 1}, {M(2), 0}};
EXPECT(assert_equal(expectedSequence, hybrid_values.discrete()));
}
/****************************************************************************/
@ -411,12 +407,8 @@ TEST(HybridEstimation, ProbabilityMultifrontal) {
HybridValues hybrid_values = discreteBayesTree->optimize();
// This is the correct sequence as designed
DiscreteValues discrete_seq;
discrete_seq[M(0)] = 1;
discrete_seq[M(1)] = 1;
discrete_seq[M(2)] = 0;
EXPECT(assert_equal(discrete_seq, hybrid_values.discrete()));
DiscreteValues expectedSequence{{M(0), 1}, {M(1), 1}, {M(2), 0}};
EXPECT(assert_equal(expectedSequence, hybrid_values.discrete()));
}
/*********************************************************************************