gtsam/gtsam/linear/SubgraphSolver.cpp

171 lines
6.2 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file SubgraphSolver.cpp
* @brief Subgraph Solver from IROS 2010
* @date 2010
* @author Frank Dellaert
* @author Yong Dian Jian
*/
#include <gtsam/linear/SubgraphSolver.h>
#include <gtsam/linear/GaussianBayesNet.h>
#include <gtsam/linear/iterative-inl.h>
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/linear/SubgraphPreconditioner.h>
#include <gtsam/base/DSFVector.h>
using namespace std;
namespace gtsam {
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &gfg,
const Parameters &parameters, const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
initialize(gfg);
}
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianFactorGraph::shared_ptr &jfg,
const Parameters &parameters, const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
initialize(*jfg);
}
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &Ab1,
const GaussianFactorGraph &Ab2, const Parameters &parameters,
const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
GaussianBayesNet::shared_ptr Rc1 = Ab1.eliminateSequential(ordering_,
EliminateQR);
initialize(Rc1, boost::make_shared<GaussianFactorGraph>(Ab2));
}
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianFactorGraph::shared_ptr &Ab1,
const GaussianFactorGraph::shared_ptr &Ab2, const Parameters &parameters,
const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
GaussianBayesNet::shared_ptr Rc1 = Ab1->eliminateSequential(ordering_,
EliminateQR);
initialize(Rc1, Ab2);
}
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1,
const GaussianFactorGraph &Ab2, const Parameters &parameters,
const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
initialize(Rc1, boost::make_shared<GaussianFactorGraph>(Ab2));
}
/**************************************************************************************************/
SubgraphSolver::SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1,
const GaussianFactorGraph::shared_ptr &Ab2, const Parameters &parameters,
const Ordering& ordering) :
parameters_(parameters), ordering_(ordering) {
initialize(Rc1, Ab2);
}
/**************************************************************************************************/
VectorValues SubgraphSolver::optimize() {
VectorValues ybar = conjugateGradients<SubgraphPreconditioner, VectorValues,
Errors>(*pc_, pc_->zero(), parameters_);
return pc_->x(ybar);
}
/**************************************************************************************************/
VectorValues SubgraphSolver::optimize(const VectorValues &initial) {
// the initial is ignored in this case ...
return optimize();
}
/**************************************************************************************************/
void SubgraphSolver::initialize(const GaussianFactorGraph &jfg) {
GaussianFactorGraph::shared_ptr Ab1 =
boost::make_shared<GaussianFactorGraph>(), Ab2 = boost::make_shared<
GaussianFactorGraph>();
boost::tie(Ab1, Ab2) = splitGraph(jfg);
if (parameters_.verbosity())
cout << "Split A into (A1) " << Ab1->size() << " and (A2) " << Ab2->size()
<< " factors" << endl;
GaussianBayesNet::shared_ptr Rc1 = Ab1->eliminateSequential(ordering_,
EliminateQR);
VectorValues::shared_ptr xbar = boost::make_shared<VectorValues>(
Rc1->optimize());
pc_ = boost::make_shared<SubgraphPreconditioner>(Ab2, Rc1, xbar);
}
/**************************************************************************************************/
void SubgraphSolver::initialize(const GaussianBayesNet::shared_ptr &Rc1,
const GaussianFactorGraph::shared_ptr &Ab2) {
VectorValues::shared_ptr xbar = boost::make_shared<VectorValues>(
Rc1->optimize());
pc_ = boost::make_shared<SubgraphPreconditioner>(Ab2, Rc1, xbar);
}
/**************************************************************************************************/
boost::tuple<GaussianFactorGraph::shared_ptr, GaussianFactorGraph::shared_ptr> //
SubgraphSolver::splitGraph(const GaussianFactorGraph &jfg) {
const VariableIndex index(jfg);
const size_t n = index.size();
DSFVector D(n);
GaussianFactorGraph::shared_ptr At(new GaussianFactorGraph());
GaussianFactorGraph::shared_ptr Ac(new GaussianFactorGraph());
size_t t = 0;
for ( const GaussianFactor::shared_ptr &gf: jfg ) {
if (gf->keys().size() > 2) {
throw runtime_error(
"SubgraphSolver::splitGraph the graph is not simple, sanity check failed ");
}
bool augment = false;
/* check whether this factor should be augmented to the "tree" graph */
if (gf->keys().size() == 1)
augment = true;
else {
const Key u = gf->keys()[0], v = gf->keys()[1], u_root = D.findSet(u),
v_root = D.findSet(v);
if (u_root != v_root) {
t++;
augment = true;
D.makeUnionInPlace(u_root, v_root);
}
}
if (augment)
At->push_back(gf);
else
Ac->push_back(gf);
}
return boost::tie(At, Ac);
}
/****************************************************************************/
VectorValues SubgraphSolver::optimize(const GaussianFactorGraph &gfg,
const KeyInfo &keyInfo, const std::map<Key, Vector> &lambda,
const VectorValues &initial) {
return VectorValues();
}
} // \namespace gtsam