diff --git a/gtsam/hybrid/HybridBayesTree.cpp b/gtsam/hybrid/HybridBayesTree.cpp index 400cac5e7..ff07f1817 100644 --- a/gtsam/hybrid/HybridBayesTree.cpp +++ b/gtsam/hybrid/HybridBayesTree.cpp @@ -11,7 +11,8 @@ /** * @file HybridBayesTree.cpp - * @brief Hybrid Bayes Tree, the result of eliminating a HybridJunctionTree + * @brief Hybrid Bayes Tree, the result of eliminating a + * HybridGaussianJunctionTree * @date Mar 11, 2022 * @author Fan Jiang */ @@ -26,7 +27,7 @@ namespace gtsam { // Instantiate base class template class BayesTreeCliqueBase; + HybridGaussianFactorGraph>; template class BayesTree; /* ************************************************************************* */ diff --git a/gtsam/hybrid/HybridBayesTree.h b/gtsam/hybrid/HybridBayesTree.h index 610181458..28d9ef809 100644 --- a/gtsam/hybrid/HybridBayesTree.h +++ b/gtsam/hybrid/HybridBayesTree.h @@ -11,15 +11,16 @@ /** * @file HybridBayesTree.h - * @brief Hybrid Bayes Tree, the result of eliminating a HybridJunctionTree + * @brief Hybrid Bayes Tree, the result of eliminating a + * HybridGaussianJunctionTree * @date Mar 11, 2022 * @author Fan Jiang */ #pragma once -#include #include +#include #include #include #include @@ -38,10 +39,10 @@ class VectorValues; */ class GTSAM_EXPORT HybridBayesTreeClique : public BayesTreeCliqueBase { + HybridGaussianFactorGraph> { public: typedef HybridBayesTreeClique This; - typedef BayesTreeCliqueBase + typedef BayesTreeCliqueBase Base; typedef boost::shared_ptr shared_ptr; typedef boost::weak_ptr weak_ptr; diff --git a/gtsam/hybrid/HybridConditional.h b/gtsam/hybrid/HybridConditional.h index 9592b0c69..887b49f12 100644 --- a/gtsam/hybrid/HybridConditional.h +++ b/gtsam/hybrid/HybridConditional.h @@ -18,9 +18,9 @@ #pragma once #include -#include #include #include +#include #include #include #include @@ -34,7 +34,7 @@ namespace gtsam { -class GaussianHybridFactorGraph; +class HybridGaussianFactorGraph; /** * Hybrid Conditional Density diff --git a/gtsam/hybrid/HybridEliminationTree.cpp b/gtsam/hybrid/HybridEliminationTree.cpp index 148685327..c2df2dd60 100644 --- a/gtsam/hybrid/HybridEliminationTree.cpp +++ b/gtsam/hybrid/HybridEliminationTree.cpp @@ -21,17 +21,17 @@ namespace gtsam { // Instantiate base class -template class EliminationTree; +template class EliminationTree; /* ************************************************************************* */ HybridEliminationTree::HybridEliminationTree( - const GaussianHybridFactorGraph& factorGraph, + const HybridGaussianFactorGraph& factorGraph, const VariableIndex& structure, const Ordering& order) : Base(factorGraph, structure, order) {} /* ************************************************************************* */ HybridEliminationTree::HybridEliminationTree( - const GaussianHybridFactorGraph& factorGraph, const Ordering& order) + const HybridGaussianFactorGraph& factorGraph, const Ordering& order) : Base(factorGraph, order) {} /* ************************************************************************* */ diff --git a/gtsam/hybrid/HybridEliminationTree.h b/gtsam/hybrid/HybridEliminationTree.h index 04bd9cd35..77a84fea8 100644 --- a/gtsam/hybrid/HybridEliminationTree.h +++ b/gtsam/hybrid/HybridEliminationTree.h @@ -17,8 +17,8 @@ #pragma once -#include #include +#include #include namespace gtsam { @@ -27,12 +27,12 @@ namespace gtsam { * Elimination Tree type for Hybrid */ class GTSAM_EXPORT HybridEliminationTree - : public EliminationTree { + : public EliminationTree { private: friend class ::EliminationTreeTester; public: - typedef EliminationTree + typedef EliminationTree Base; ///< Base class typedef HybridEliminationTree This; ///< This class typedef boost::shared_ptr shared_ptr; ///< Shared pointer to this class @@ -49,7 +49,7 @@ class GTSAM_EXPORT HybridEliminationTree * named constructor instead. * @return The elimination tree */ - HybridEliminationTree(const GaussianHybridFactorGraph& factorGraph, + HybridEliminationTree(const HybridGaussianFactorGraph& factorGraph, const VariableIndex& structure, const Ordering& order); /** Build the elimination tree of a factor graph. Note that this has to @@ -57,7 +57,7 @@ class GTSAM_EXPORT HybridEliminationTree * this precomputed, use the other constructor instead. * @param factorGraph The factor graph for which to build the elimination tree */ - HybridEliminationTree(const GaussianHybridFactorGraph& factorGraph, + HybridEliminationTree(const HybridGaussianFactorGraph& factorGraph, const Ordering& order); /// @} diff --git a/gtsam/hybrid/GaussianHybridFactorGraph.cpp b/gtsam/hybrid/HybridGaussianFactorGraph.cpp similarity index 94% rename from gtsam/hybrid/GaussianHybridFactorGraph.cpp rename to gtsam/hybrid/HybridGaussianFactorGraph.cpp index 3354d5b4d..0ac2c2656 100644 --- a/gtsam/hybrid/GaussianHybridFactorGraph.cpp +++ b/gtsam/hybrid/HybridGaussianFactorGraph.cpp @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file GaussianHybridFactorGraph.cpp + * @file HybridGaussianFactorGraph.cpp * @brief Hybrid factor graph that uses type erasure * @author Fan Jiang * @author Varun Agrawal @@ -23,7 +23,6 @@ #include #include #include -#include #include #include #include @@ -31,7 +30,8 @@ #include #include #include -#include +#include +#include #include #include #include @@ -53,7 +53,7 @@ namespace gtsam { -template class EliminateableFactorGraph; +template class EliminateableFactorGraph; /* ************************************************************************ */ static GaussianMixtureFactor::Sum &addGaussian( @@ -78,7 +78,7 @@ static GaussianMixtureFactor::Sum &addGaussian( /* ************************************************************************ */ std::pair -continuousElimination(const GaussianHybridFactorGraph &factors, +continuousElimination(const HybridGaussianFactorGraph &factors, const Ordering &frontalKeys) { GaussianFactorGraph gfg; for (auto &fp : factors) { @@ -103,7 +103,7 @@ continuousElimination(const GaussianHybridFactorGraph &factors, /* ************************************************************************ */ std::pair -discreteElimination(const GaussianHybridFactorGraph &factors, +discreteElimination(const HybridGaussianFactorGraph &factors, const Ordering &frontalKeys) { DiscreteFactorGraph dfg; for (auto &fp : factors) { @@ -129,7 +129,7 @@ discreteElimination(const GaussianHybridFactorGraph &factors, /* ************************************************************************ */ std::pair -hybridElimination(const GaussianHybridFactorGraph &factors, +hybridElimination(const HybridGaussianFactorGraph &factors, const Ordering &frontalKeys, const KeySet &continuousSeparator, const std::set &discreteSeparatorSet) { @@ -236,7 +236,7 @@ hybridElimination(const GaussianHybridFactorGraph &factors, } /* ************************************************************************ */ std::pair // -EliminateHybrid(const GaussianHybridFactorGraph &factors, +EliminateHybrid(const HybridGaussianFactorGraph &factors, const Ordering &frontalKeys) { // NOTE: Because we are in the Conditional Gaussian regime there are only // a few cases: @@ -345,22 +345,22 @@ EliminateHybrid(const GaussianHybridFactorGraph &factors, } /* ************************************************************************ */ -void GaussianHybridFactorGraph::add(JacobianFactor &&factor) { +void HybridGaussianFactorGraph::add(JacobianFactor &&factor) { FactorGraph::add(boost::make_shared(std::move(factor))); } /* ************************************************************************ */ -void GaussianHybridFactorGraph::add(JacobianFactor::shared_ptr factor) { +void HybridGaussianFactorGraph::add(JacobianFactor::shared_ptr factor) { FactorGraph::add(boost::make_shared(factor)); } /* ************************************************************************ */ -void GaussianHybridFactorGraph::add(DecisionTreeFactor &&factor) { +void HybridGaussianFactorGraph::add(DecisionTreeFactor &&factor) { FactorGraph::add(boost::make_shared(std::move(factor))); } /* ************************************************************************ */ -void GaussianHybridFactorGraph::add(DecisionTreeFactor::shared_ptr factor) { +void HybridGaussianFactorGraph::add(DecisionTreeFactor::shared_ptr factor) { FactorGraph::add(boost::make_shared(factor)); } diff --git a/gtsam/hybrid/GaussianHybridFactorGraph.h b/gtsam/hybrid/HybridGaussianFactorGraph.h similarity index 77% rename from gtsam/hybrid/GaussianHybridFactorGraph.h rename to gtsam/hybrid/HybridGaussianFactorGraph.h index c8e0718fc..6944af510 100644 --- a/gtsam/hybrid/GaussianHybridFactorGraph.h +++ b/gtsam/hybrid/HybridGaussianFactorGraph.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file GaussianHybridFactorGraph.h + * @file HybridGaussianFactorGraph.h * @brief Linearized Hybrid factor graph that uses type erasure * @author Fan Jiang * @date Mar 11, 2022 @@ -26,36 +26,37 @@ namespace gtsam { // Forward declarations -class GaussianHybridFactorGraph; +class HybridGaussianFactorGraph; class HybridConditional; class HybridBayesNet; class HybridEliminationTree; class HybridBayesTree; -class HybridJunctionTree; +class HybridGaussianJunctionTree; class DecisionTreeFactor; class JacobianFactor; -/** Main elimination function for GaussianHybridFactorGraph */ +/** Main elimination function for HybridGaussianFactorGraph */ GTSAM_EXPORT std::pair, HybridFactor::shared_ptr> -EliminateHybrid(const GaussianHybridFactorGraph& factors, const Ordering& keys); +EliminateHybrid(const HybridGaussianFactorGraph& factors, const Ordering& keys); /* ************************************************************************* */ template <> -struct EliminationTraits { +struct EliminationTraits { typedef HybridFactor FactorType; ///< Type of factors in factor graph - typedef GaussianHybridFactorGraph + typedef HybridGaussianFactorGraph FactorGraphType; ///< Type of the factor graph (e.g. - ///< GaussianHybridFactorGraph) + ///< HybridGaussianFactorGraph) typedef HybridConditional ConditionalType; ///< Type of conditionals from elimination typedef HybridBayesNet BayesNetType; ///< Type of Bayes net from sequential elimination typedef HybridEliminationTree - EliminationTreeType; ///< Type of elimination tree - typedef HybridBayesTree BayesTreeType; ///< Type of Bayes tree - typedef HybridJunctionTree JunctionTreeType; ///< Type of Junction tree + EliminationTreeType; ///< Type of elimination tree + typedef HybridBayesTree BayesTreeType; ///< Type of Bayes tree + typedef HybridGaussianJunctionTree + JunctionTreeType; ///< Type of Junction tree /// The default dense elimination function static std::pair, boost::shared_ptr > @@ -70,12 +71,12 @@ struct EliminationTraits { * This is the linearized version of a hybrid factor graph. * Everything inside needs to be hybrid factor or hybrid conditional. */ -class GaussianHybridFactorGraph +class HybridGaussianFactorGraph : public FactorGraph, - public EliminateableFactorGraph { + public EliminateableFactorGraph { public: using Base = FactorGraph; - using This = GaussianHybridFactorGraph; ///< this class + using This = HybridGaussianFactorGraph; ///< this class using BaseEliminateable = EliminateableFactorGraph; ///< for elimination using shared_ptr = boost::shared_ptr; ///< shared_ptr to This @@ -86,7 +87,7 @@ class GaussianHybridFactorGraph /// @name Constructors /// @{ - GaussianHybridFactorGraph() = default; + HybridGaussianFactorGraph() = default; /** * Implicit copy/downcast constructor to override explicit template container @@ -94,7 +95,7 @@ class GaussianHybridFactorGraph * `cachedSeparatorMarginal_.reset(*separatorMarginal)` * */ template - GaussianHybridFactorGraph(const FactorGraph& graph) + HybridGaussianFactorGraph(const FactorGraph& graph) : Base(graph) {} /// @} diff --git a/gtsam/hybrid/HybridISAM.cpp b/gtsam/hybrid/HybridGaussianISAM.cpp similarity index 84% rename from gtsam/hybrid/HybridISAM.cpp rename to gtsam/hybrid/HybridGaussianISAM.cpp index 476149126..7783a88dd 100644 --- a/gtsam/hybrid/HybridISAM.cpp +++ b/gtsam/hybrid/HybridGaussianISAM.cpp @@ -10,16 +10,16 @@ * -------------------------------------------------------------------------- */ /** - * @file HybridISAM.h + * @file HybridGaussianISAM.h * @date March 31, 2022 * @author Fan Jiang * @author Frank Dellaert * @author Richard Roberts */ -#include #include -#include +#include +#include #include #include @@ -31,15 +31,17 @@ namespace gtsam { // template class ISAM; /* ************************************************************************* */ -HybridISAM::HybridISAM() {} +HybridGaussianISAM::HybridGaussianISAM() {} /* ************************************************************************* */ -HybridISAM::HybridISAM(const HybridBayesTree& bayesTree) : Base(bayesTree) {} +HybridGaussianISAM::HybridGaussianISAM(const HybridBayesTree& bayesTree) + : Base(bayesTree) {} /* ************************************************************************* */ -void HybridISAM::updateInternal(const GaussianHybridFactorGraph& newFactors, - HybridBayesTree::Cliques* orphans, - const HybridBayesTree::Eliminate& function) { +void HybridGaussianISAM::updateInternal( + const HybridGaussianFactorGraph& newFactors, + HybridBayesTree::Cliques* orphans, + const HybridBayesTree::Eliminate& function) { // Remove the contaminated part of the Bayes tree BayesNetType bn; const KeySet newFactorKeys = newFactors.keys(); @@ -90,8 +92,8 @@ void HybridISAM::updateInternal(const GaussianHybridFactorGraph& newFactors, } /* ************************************************************************* */ -void HybridISAM::update(const GaussianHybridFactorGraph& newFactors, - const HybridBayesTree::Eliminate& function) { +void HybridGaussianISAM::update(const HybridGaussianFactorGraph& newFactors, + const HybridBayesTree::Eliminate& function) { Cliques orphans; this->updateInternal(newFactors, &orphans, function); } diff --git a/gtsam/hybrid/HybridISAM.h b/gtsam/hybrid/HybridGaussianISAM.h similarity index 76% rename from gtsam/hybrid/HybridISAM.h rename to gtsam/hybrid/HybridGaussianISAM.h index fae7efafd..d5b6271da 100644 --- a/gtsam/hybrid/HybridISAM.h +++ b/gtsam/hybrid/HybridGaussianISAM.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file HybridISAM.h + * @file HybridGaussianISAM.h * @date March 31, 2022 * @author Fan Jiang * @author Frank Dellaert @@ -20,33 +20,33 @@ #pragma once #include -#include #include +#include #include namespace gtsam { -class GTSAM_EXPORT HybridISAM : public ISAM { +class GTSAM_EXPORT HybridGaussianISAM : public ISAM { public: typedef ISAM Base; - typedef HybridISAM This; + typedef HybridGaussianISAM This; typedef boost::shared_ptr shared_ptr; /// @name Standard Constructors /// @{ /** Create an empty Bayes Tree */ - HybridISAM(); + HybridGaussianISAM(); /** Copy constructor */ - HybridISAM(const HybridBayesTree& bayesTree); + HybridGaussianISAM(const HybridBayesTree& bayesTree); /// @} private: /// Internal method that performs the ISAM update. void updateInternal( - const GaussianHybridFactorGraph& newFactors, + const HybridGaussianFactorGraph& newFactors, HybridBayesTree::Cliques* orphans, const HybridBayesTree::Eliminate& function = HybridBayesTree::EliminationTraitsType::DefaultEliminate); @@ -58,13 +58,13 @@ class GTSAM_EXPORT HybridISAM : public ISAM { * @param newFactors Factor graph of new factors to add and eliminate. * @param function Elimination function. */ - void update(const GaussianHybridFactorGraph& newFactors, + void update(const HybridGaussianFactorGraph& newFactors, const HybridBayesTree::Eliminate& function = HybridBayesTree::EliminationTraitsType::DefaultEliminate); }; /// traits template <> -struct traits : public Testable {}; +struct traits : public Testable {}; } // namespace gtsam diff --git a/gtsam/hybrid/HybridJunctionTree.cpp b/gtsam/hybrid/HybridGaussianJunctionTree.cpp similarity index 73% rename from gtsam/hybrid/HybridJunctionTree.cpp rename to gtsam/hybrid/HybridGaussianJunctionTree.cpp index 8fa3aa033..8ceb7c87b 100644 --- a/gtsam/hybrid/HybridJunctionTree.cpp +++ b/gtsam/hybrid/HybridGaussianJunctionTree.cpp @@ -10,14 +10,14 @@ * -------------------------------------------------------------------------- */ /** - * @file HybridJunctionTree.cpp + * @file HybridGaussianJunctionTree.cpp * @date Mar 11, 2022 * @author Fan Jiang */ -#include #include -#include +#include +#include #include #include @@ -27,19 +27,19 @@ namespace gtsam { // Instantiate base classes template class EliminatableClusterTree; -template class JunctionTree; + HybridGaussianFactorGraph>; +template class JunctionTree; struct HybridConstructorTraversalData { typedef - typename JunctionTree::Node + typename JunctionTree::Node Node; typedef typename JunctionTree::sharedNode sharedNode; + HybridGaussianFactorGraph>::sharedNode sharedNode; HybridConstructorTraversalData* const parentData; - sharedNode myJTNode; + sharedNode junctionTreeNode; FastVector childSymbolicConditionals; FastVector childSymbolicFactors; KeySet discreteKeys; @@ -57,24 +57,24 @@ struct HybridConstructorTraversalData { // On the pre-order pass, before children have been visited, we just set up // a traversal data structure with its own JT node, and create a child // pointer in its parent. - HybridConstructorTraversalData myData = + HybridConstructorTraversalData data = HybridConstructorTraversalData(&parentData); - myData.myJTNode = boost::make_shared(node->key, node->factors); - parentData.myJTNode->addChild(myData.myJTNode); + data.junctionTreeNode = boost::make_shared(node->key, node->factors); + parentData.junctionTreeNode->addChild(data.junctionTreeNode); for (HybridFactor::shared_ptr& f : node->factors) { for (auto& k : f->discreteKeys()) { - myData.discreteKeys.insert(k.first); + data.discreteKeys.insert(k.first); } } - return myData; + return data; } // Post-order visitor function static void ConstructorTraversalVisitorPostAlg2( const boost::shared_ptr& ETreeNode, - const HybridConstructorTraversalData& myData) { + const HybridConstructorTraversalData& data) { // In this post-order visitor, we combine the symbolic elimination results // from the elimination tree children and symbolically eliminate the current // elimination tree node. We then check whether each of our elimination @@ -87,50 +87,50 @@ struct HybridConstructorTraversalData { // Do symbolic elimination for this node SymbolicFactors symbolicFactors; symbolicFactors.reserve(ETreeNode->factors.size() + - myData.childSymbolicFactors.size()); + data.childSymbolicFactors.size()); // Add ETree node factors symbolicFactors += ETreeNode->factors; // Add symbolic factors passed up from children - symbolicFactors += myData.childSymbolicFactors; + symbolicFactors += data.childSymbolicFactors; Ordering keyAsOrdering; keyAsOrdering.push_back(ETreeNode->key); - SymbolicConditional::shared_ptr myConditional; - SymbolicFactor::shared_ptr mySeparatorFactor; - boost::tie(myConditional, mySeparatorFactor) = + SymbolicConditional::shared_ptr conditional; + SymbolicFactor::shared_ptr separatorFactor; + boost::tie(conditional, separatorFactor) = internal::EliminateSymbolic(symbolicFactors, keyAsOrdering); // Store symbolic elimination results in the parent - myData.parentData->childSymbolicConditionals.push_back(myConditional); - myData.parentData->childSymbolicFactors.push_back(mySeparatorFactor); - myData.parentData->discreteKeys.merge(myData.discreteKeys); + data.parentData->childSymbolicConditionals.push_back(conditional); + data.parentData->childSymbolicFactors.push_back(separatorFactor); + data.parentData->discreteKeys.merge(data.discreteKeys); - sharedNode node = myData.myJTNode; + sharedNode node = data.junctionTreeNode; const FastVector& childConditionals = - myData.childSymbolicConditionals; - node->problemSize_ = (int)(myConditional->size() * symbolicFactors.size()); + data.childSymbolicConditionals; + node->problemSize_ = (int)(conditional->size() * symbolicFactors.size()); // Merge our children if they are in our clique - if our conditional has // exactly one fewer parent than our child's conditional. - const size_t myNrParents = myConditional->nrParents(); + const size_t nrParents = conditional->nrParents(); const size_t nrChildren = node->nrChildren(); assert(childConditionals.size() == nrChildren); // decide which children to merge, as index into children - std::vector nrFrontals = node->nrFrontalsOfChildren(); + std::vector nrChildrenFrontals = node->nrFrontalsOfChildren(); std::vector merge(nrChildren, false); - size_t myNrFrontals = 1; + size_t nrFrontals = 1; for (size_t i = 0; i < nrChildren; i++) { // Check if we should merge the i^th child - if (myNrParents + myNrFrontals == childConditionals[i]->nrParents()) { + if (nrParents + nrFrontals == childConditionals[i]->nrParents()) { const bool myType = - myData.discreteKeys.exists(myConditional->frontals()[0]); + data.discreteKeys.exists(conditional->frontals()[0]); const bool theirType = - myData.discreteKeys.exists(childConditionals[i]->frontals()[0]); + data.discreteKeys.exists(childConditionals[i]->frontals()[0]); if (myType == theirType) { // Increment number of frontal variables - myNrFrontals += nrFrontals[i]; + nrFrontals += nrChildrenFrontals[i]; merge[i] = true; } } @@ -142,7 +142,7 @@ struct HybridConstructorTraversalData { }; /* ************************************************************************* */ -HybridJunctionTree::HybridJunctionTree( +HybridGaussianJunctionTree::HybridGaussianJunctionTree( const HybridEliminationTree& eliminationTree) { gttic(JunctionTree_FromEliminationTree); // Here we rely on the BayesNet having been produced by this elimination tree, @@ -156,7 +156,7 @@ HybridJunctionTree::HybridJunctionTree( // as we go. Gather the created junction tree roots in a dummy Node. typedef HybridConstructorTraversalData Data; Data rootData(0); - rootData.myJTNode = + rootData.junctionTreeNode = boost::make_shared(); // Make a dummy node to gather // the junction tree roots treeTraversal::DepthFirstForest(eliminationTree, rootData, @@ -164,7 +164,7 @@ HybridJunctionTree::HybridJunctionTree( Data::ConstructorTraversalVisitorPostAlg2); // Assign roots from the dummy node - this->addChildrenAsRoots(rootData.myJTNode); + this->addChildrenAsRoots(rootData.junctionTreeNode); // Transfer remaining factors from elimination tree Base::remainingFactors_ = eliminationTree.remainingFactors(); diff --git a/gtsam/hybrid/HybridJunctionTree.h b/gtsam/hybrid/HybridGaussianJunctionTree.h similarity index 84% rename from gtsam/hybrid/HybridJunctionTree.h rename to gtsam/hybrid/HybridGaussianJunctionTree.h index ce9b818e6..314e7daa6 100644 --- a/gtsam/hybrid/HybridJunctionTree.h +++ b/gtsam/hybrid/HybridGaussianJunctionTree.h @@ -10,15 +10,15 @@ * -------------------------------------------------------------------------- */ /** - * @file HybridJunctionTree.h + * @file HybridGaussianJunctionTree.h * @date Mar 11, 2022 * @author Fan Jiang */ #pragma once -#include #include +#include #include namespace gtsam { @@ -48,12 +48,12 @@ class HybridEliminationTree; * \addtogroup Multifrontal * \nosubgrouping */ -class GTSAM_EXPORT HybridJunctionTree - : public JunctionTree { +class GTSAM_EXPORT HybridGaussianJunctionTree + : public JunctionTree { public: - typedef JunctionTree + typedef JunctionTree Base; ///< Base class - typedef HybridJunctionTree This; ///< This class + typedef HybridGaussianJunctionTree This; ///< This class typedef boost::shared_ptr shared_ptr; ///< Shared pointer to this class /** @@ -65,7 +65,7 @@ class GTSAM_EXPORT HybridJunctionTree * named constructor instead. * @return The elimination tree */ - HybridJunctionTree(const HybridEliminationTree& eliminationTree); + HybridGaussianJunctionTree(const HybridEliminationTree& eliminationTree); }; } // namespace gtsam diff --git a/gtsam/hybrid/hybrid.i b/gtsam/hybrid/hybrid.i index 612f3abc5..94eaa88b2 100644 --- a/gtsam/hybrid/hybrid.i +++ b/gtsam/hybrid/hybrid.i @@ -98,15 +98,15 @@ class HybridBayesNet { const gtsam::DotWriter& writer = gtsam::DotWriter()) const; }; -#include -class GaussianHybridFactorGraph { - GaussianHybridFactorGraph(); - GaussianHybridFactorGraph(const gtsam::HybridBayesNet& bayesNet); +#include +class HybridGaussianFactorGraph { + HybridGaussianFactorGraph(); + HybridGaussianFactorGraph(const gtsam::HybridBayesNet& bayesNet); // Building the graph void push_back(const gtsam::HybridFactor* factor); void push_back(const gtsam::HybridConditional* conditional); - void push_back(const gtsam::GaussianHybridFactorGraph& graph); + void push_back(const gtsam::HybridGaussianFactorGraph& graph); void push_back(const gtsam::HybridBayesNet& bayesNet); void push_back(const gtsam::HybridBayesTree& bayesTree); void push_back(const gtsam::GaussianMixtureFactor* gmm); @@ -120,13 +120,13 @@ class GaussianHybridFactorGraph { const gtsam::HybridFactor* at(size_t i) const; void print(string s = "") const; - bool equals(const gtsam::GaussianHybridFactorGraph& fg, double tol = 1e-9) const; + bool equals(const gtsam::HybridGaussianFactorGraph& fg, double tol = 1e-9) const; gtsam::HybridBayesNet* eliminateSequential(); gtsam::HybridBayesNet* eliminateSequential( gtsam::Ordering::OrderingType type); gtsam::HybridBayesNet* eliminateSequential(const gtsam::Ordering& ordering); - pair + pair eliminatePartialSequential(const gtsam::Ordering& ordering); gtsam::HybridBayesTree* eliminateMultifrontal(); @@ -134,7 +134,7 @@ class GaussianHybridFactorGraph { gtsam::Ordering::OrderingType type); gtsam::HybridBayesTree* eliminateMultifrontal( const gtsam::Ordering& ordering); - pair + pair eliminatePartialMultifrontal(const gtsam::Ordering& ordering); string dot( diff --git a/gtsam/hybrid/tests/Switching.h b/gtsam/hybrid/tests/Switching.h index 77d8182c8..c081b8e87 100644 --- a/gtsam/hybrid/tests/Switching.h +++ b/gtsam/hybrid/tests/Switching.h @@ -18,8 +18,8 @@ #include #include -#include #include +#include #include #include @@ -29,10 +29,10 @@ using gtsam::symbol_shorthand::C; using gtsam::symbol_shorthand::X; namespace gtsam { -inline GaussianHybridFactorGraph::shared_ptr makeSwitchingChain( +inline HybridGaussianFactorGraph::shared_ptr makeSwitchingChain( size_t n, std::function keyFunc = X, std::function dKeyFunc = C) { - GaussianHybridFactorGraph hfg; + HybridGaussianFactorGraph hfg; hfg.add(JacobianFactor(keyFunc(1), I_3x3, Z_3x1)); @@ -51,7 +51,7 @@ inline GaussianHybridFactorGraph::shared_ptr makeSwitchingChain( } } - return boost::make_shared(std::move(hfg)); + return boost::make_shared(std::move(hfg)); } inline std::pair> makeBinaryOrdering( diff --git a/gtsam/hybrid/tests/testGaussianHybridFactorGraph.cpp b/gtsam/hybrid/tests/testGaussianHybridFactorGraph.cpp index 853353278..8ff959d74 100644 --- a/gtsam/hybrid/tests/testGaussianHybridFactorGraph.cpp +++ b/gtsam/hybrid/tests/testGaussianHybridFactorGraph.cpp @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /* - * @file testGaussianHybridFactorGraph.cpp + * @file testHybridGaussianFactorGraph.cpp * @date Mar 11, 2022 * @author Fan Jiang */ @@ -20,7 +20,6 @@ #include #include #include -#include #include #include #include @@ -29,7 +28,8 @@ #include #include #include -#include +#include +#include #include #include #include @@ -57,25 +57,11 @@ using gtsam::symbol_shorthand::D; using gtsam::symbol_shorthand::X; using gtsam::symbol_shorthand::Y; -#ifdef HYBRID_DEBUG -#define BOOST_STACKTRACE_GNU_SOURCE_NOT_REQUIRED - -#include // ::signal, ::raise - -#include - -void my_signal_handler(int signum) { - ::signal(signum, SIG_DFL); - std::cout << boost::stacktrace::stacktrace(); - ::raise(SIGABRT); -} -#endif - /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, creation) { +TEST(HybridGaussianFactorGraph, creation) { HybridConditional test; - GaussianHybridFactorGraph hfg; + HybridGaussianFactorGraph hfg; hfg.add(HybridGaussianFactor(JacobianFactor(0, I_3x3, Z_3x1))); @@ -91,8 +77,8 @@ TEST(GaussianHybridFactorGraph, creation) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminate) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminate) { + HybridGaussianFactorGraph hfg; hfg.add(HybridGaussianFactor(JacobianFactor(0, I_3x3, Z_3x1))); @@ -102,8 +88,8 @@ TEST(GaussianHybridFactorGraph, eliminate) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminateMultifrontal) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateMultifrontal) { + HybridGaussianFactorGraph hfg; DiscreteKey c(C(1), 2); @@ -119,8 +105,8 @@ TEST(GaussianHybridFactorGraph, eliminateMultifrontal) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminateFullSequentialEqualChance) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateFullSequentialEqualChance) { + HybridGaussianFactorGraph hfg; DiscreteKey c1(C(1), 2); @@ -143,8 +129,8 @@ TEST(GaussianHybridFactorGraph, eliminateFullSequentialEqualChance) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminateFullSequentialSimple) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateFullSequentialSimple) { + HybridGaussianFactorGraph hfg; DiscreteKey c1(C(1), 2); @@ -171,8 +157,8 @@ TEST(GaussianHybridFactorGraph, eliminateFullSequentialSimple) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalSimple) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalSimple) { + HybridGaussianFactorGraph hfg; DiscreteKey c1(C(1), 2); @@ -204,8 +190,8 @@ TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalSimple) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalCLG) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalCLG) { + HybridGaussianFactorGraph hfg; DiscreteKey c(C(1), 2); @@ -240,8 +226,8 @@ TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalCLG) { * This test is about how to assemble the Bayes Tree roots after we do partial * elimination */ -TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalTwoClique) { - GaussianHybridFactorGraph hfg; +TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalTwoClique) { + HybridGaussianFactorGraph hfg; hfg.add(JacobianFactor(X(0), I_3x3, X(1), -I_3x3, Z_3x1)); hfg.add(JacobianFactor(X(1), I_3x3, X(2), -I_3x3, Z_3x1)); @@ -290,7 +276,7 @@ TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalTwoClique) { GTSAM_PRINT(ordering_full); HybridBayesTree::shared_ptr hbt; - GaussianHybridFactorGraph::shared_ptr remaining; + HybridGaussianFactorGraph::shared_ptr remaining; std::tie(hbt, remaining) = hfg.eliminatePartialMultifrontal(ordering_full); GTSAM_PRINT(*hbt); @@ -309,7 +295,7 @@ TEST(GaussianHybridFactorGraph, eliminateFullMultifrontalTwoClique) { /* ************************************************************************* */ // TODO(fan): make a graph like Varun's paper one -TEST(GaussianHybridFactorGraph, Switching) { +TEST(HybridGaussianFactorGraph, Switching) { auto N = 12; auto hfg = makeSwitchingChain(N); @@ -381,7 +367,7 @@ TEST(GaussianHybridFactorGraph, Switching) { GTSAM_PRINT(ordering_full); HybridBayesTree::shared_ptr hbt; - GaussianHybridFactorGraph::shared_ptr remaining; + HybridGaussianFactorGraph::shared_ptr remaining; std::tie(hbt, remaining) = hfg->eliminatePartialMultifrontal(ordering_full); // GTSAM_PRINT(*hbt); @@ -417,7 +403,7 @@ TEST(GaussianHybridFactorGraph, Switching) { /* ************************************************************************* */ // TODO(fan): make a graph like Varun's paper one -TEST(GaussianHybridFactorGraph, SwitchingISAM) { +TEST(HybridGaussianFactorGraph, SwitchingISAM) { auto N = 11; auto hfg = makeSwitchingChain(N); @@ -473,7 +459,7 @@ TEST(GaussianHybridFactorGraph, SwitchingISAM) { GTSAM_PRINT(ordering_full); HybridBayesTree::shared_ptr hbt; - GaussianHybridFactorGraph::shared_ptr remaining; + HybridGaussianFactorGraph::shared_ptr remaining; std::tie(hbt, remaining) = hfg->eliminatePartialMultifrontal(ordering_full); // GTSAM_PRINT(*hbt); @@ -499,10 +485,10 @@ TEST(GaussianHybridFactorGraph, SwitchingISAM) { } auto new_fg = makeSwitchingChain(12); - auto isam = HybridISAM(*hbt); + auto isam = HybridGaussianISAM(*hbt); { - GaussianHybridFactorGraph factorGraph; + HybridGaussianFactorGraph factorGraph; factorGraph.push_back(new_fg->at(new_fg->size() - 2)); factorGraph.push_back(new_fg->at(new_fg->size() - 1)); isam.update(factorGraph); @@ -512,7 +498,7 @@ TEST(GaussianHybridFactorGraph, SwitchingISAM) { } /* ************************************************************************* */ -TEST(GaussianHybridFactorGraph, SwitchingTwoVar) { +TEST(HybridGaussianFactorGraph, SwitchingTwoVar) { const int N = 7; auto hfg = makeSwitchingChain(N, X); hfg->push_back(*makeSwitchingChain(N, Y, D)); @@ -582,7 +568,7 @@ TEST(GaussianHybridFactorGraph, SwitchingTwoVar) { } { HybridBayesNet::shared_ptr hbn; - GaussianHybridFactorGraph::shared_ptr remaining; + HybridGaussianFactorGraph::shared_ptr remaining; std::tie(hbn, remaining) = hfg->eliminatePartialSequential(ordering_partial); diff --git a/gtsam/inference/inference.i b/gtsam/inference/inference.i index e8d918a1d..fbdd70fdf 100644 --- a/gtsam/inference/inference.i +++ b/gtsam/inference/inference.i @@ -9,7 +9,7 @@ namespace gtsam { #include #include #include -#include +#include #include @@ -107,36 +107,36 @@ class Ordering { template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering Colamd(const FACTOR_GRAPH& graph); template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering ColamdConstrainedLast( const FACTOR_GRAPH& graph, const gtsam::KeyVector& constrainLast, bool forceOrder = false); template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering ColamdConstrainedFirst( const FACTOR_GRAPH& graph, const gtsam::KeyVector& constrainFirst, bool forceOrder = false); template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering Natural(const FACTOR_GRAPH& graph); template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering Metis(const FACTOR_GRAPH& graph); template < FACTOR_GRAPH = {gtsam::NonlinearFactorGraph, gtsam::DiscreteFactorGraph, - gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::GaussianHybridFactorGraph}> + gtsam::SymbolicFactorGraph, gtsam::GaussianFactorGraph, gtsam::HybridGaussianFactorGraph}> static gtsam::Ordering Create(gtsam::Ordering::OrderingType orderingType, const FACTOR_GRAPH& graph); diff --git a/python/gtsam/tests/test_HybridFactorGraph.py b/python/gtsam/tests/test_HybridFactorGraph.py index 895c9e14e..07a8178e6 100644 --- a/python/gtsam/tests/test_HybridFactorGraph.py +++ b/python/gtsam/tests/test_HybridFactorGraph.py @@ -20,8 +20,8 @@ from gtsam.symbol_shorthand import C, X from gtsam.utils.test_case import GtsamTestCase -class TestGaussianHybridFactorGraph(GtsamTestCase): - """Unit tests for GaussianHybridFactorGraph.""" +class TestHybridGaussianFactorGraph(GtsamTestCase): + """Unit tests for HybridGaussianFactorGraph.""" def test_create(self): """Test contruction of hybrid factor graph.""" @@ -36,13 +36,13 @@ class TestGaussianHybridFactorGraph(GtsamTestCase): gmf = gtsam.GaussianMixtureFactor.FromFactors([X(0)], dk, [jf1, jf2]) - hfg = gtsam.GaussianHybridFactorGraph() + hfg = gtsam.HybridGaussianFactorGraph() hfg.add(jf1) hfg.add(jf2) hfg.push_back(gmf) hbn = hfg.eliminateSequential( - gtsam.Ordering.ColamdConstrainedLastGaussianHybridFactorGraph( + gtsam.Ordering.ColamdConstrainedLastHybridGaussianFactorGraph( hfg, [C(0)])) # print("hbn = ", hbn)