131 lines
3.9 KiB
C++
131 lines
3.9 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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#pragma once
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#include <map>
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#include <boost/foreach.hpp>
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#include <boost/make_shared.hpp>
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#include <gtsam/linear/SubgraphSolver.h>
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#include <gtsam/linear/GaussianFactor.h>
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#include <gtsam/linear/GaussianFactorGraph.h>
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#include <gtsam/linear/GaussianBayesNet.h>
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#include <gtsam/nonlinear/Key.h>
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#include <gtsam/linear/iterative-inl.h>
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#include <gtsam/inference/EliminationTree-inl.h>
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using namespace std;
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namespace gtsam {
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/* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
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bool split(const std::map<Index, Index> &M,
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const GaussianFactorGraph &Ab,
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GaussianFactorGraph &Ab1,
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GaussianFactorGraph &Ab2) {
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Ab1 = GaussianFactorGraph();
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Ab2 = GaussianFactorGraph();
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for ( size_t i = 0 ; i < Ab.size() ; ++i ) {
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boost::shared_ptr<GaussianFactor> factor = Ab[i] ;
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if (factor->keys().size() > 2)
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throw(invalid_argument("split: only support factors with at most two keys"));
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if (factor->keys().size() == 1) {
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Ab1.push_back(factor);
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Ab2.push_back(factor);
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continue;
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}
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Index key1 = factor->keys()[0];
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Index key2 = factor->keys()[1];
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if ((M.find(key1) != M.end() && M.find(key1)->second == key2) ||
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(M.find(key2) != M.end() && M.find(key2)->second == key1))
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Ab1.push_back(factor);
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else
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Ab2.push_back(factor);
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}
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return true ;
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}
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template<class GRAPH, class LINEAR, class VALUES>
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void SubgraphSolver<GRAPH,LINEAR,VALUES>::replaceFactors(const typename LINEAR::shared_ptr &graph) {
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shared_linear Ab1 = boost::make_shared<LINEAR>(),
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Ab2 = boost::make_shared<LINEAR>();
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if (parameters_->verbosity()) cout << "split the graph ...";
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split(pairs_, *graph, *Ab1, *Ab2) ;
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if (parameters_->verbosity()) cout << ",with " << Ab1->size() << " and " << Ab2->size() << " factors" << endl;
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// // Add a HardConstraint to the root, otherwise the root will be singular
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// Key root = keys.back();
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// T_.addHardConstraint(root, theta0[root]);
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//
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// // compose the approximate solution
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// theta_bar_ = composePoses<GRAPH, Constraint, Pose, Values> (T_, tree, theta0[root]);
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LINEAR sacrificialAb1 = *Ab1; // duplicate !!!!!
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SubgraphPreconditioner::sharedBayesNet Rc1 = EliminationTree<GaussianFactor>::Create(sacrificialAb1)->eliminate();
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SubgraphPreconditioner::sharedValues xbar = gtsam::optimize_(*Rc1);
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pc_ = boost::make_shared<SubgraphPreconditioner>(Ab1,Ab2,Rc1,xbar);
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}
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template<class GRAPH, class LINEAR, class VALUES>
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VectorValues::shared_ptr SubgraphSolver<GRAPH,LINEAR,VALUES>::optimize() const {
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// preconditioned conjugate gradient
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VectorValues zeros = pc_->zero();
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VectorValues ybar = conjugateGradients<SubgraphPreconditioner, VectorValues, Errors>
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(*pc_, zeros, *parameters_);
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boost::shared_ptr<VectorValues> xbar = boost::make_shared<VectorValues>() ;
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*xbar = pc_->x(ybar);
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return xbar;
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}
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template<class GRAPH, class LINEAR, class VALUES>
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void SubgraphSolver<GRAPH,LINEAR,VALUES>::initialize(const GRAPH& G, const VALUES& theta0) {
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// generate spanning tree
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PredecessorMap<Key> tree_ = gtsam::findMinimumSpanningTree<GRAPH, Key, Constraint>(G);
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// make the ordering
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list<Key> keys = predecessorMap2Keys(tree_);
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ordering_ = boost::make_shared<Ordering>(list<Symbol>(keys.begin(), keys.end()));
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// build factor pairs
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pairs_.clear();
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typedef pair<Key,Key> EG ;
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BOOST_FOREACH( const EG &eg, tree_ ) {
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Symbol key1 = Symbol(eg.first),
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key2 = Symbol(eg.second) ;
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pairs_.insert(pair<Index, Index>((*ordering_)[key1], (*ordering_)[key2])) ;
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}
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}
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}
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