disable old subgraph preconditioners temporarily to remove name conflict
Yong-Dian Jian
parent
0a842cf0ec
commit
bc7293a0a7
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@ -1,150 +1,150 @@
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/* ----------------------------------------------------------------------------
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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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/**
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* @file SubgraphPreconditioner.cpp
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* @date Dec 31, 2009
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* @author: Frank Dellaert
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*/
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#include <boost/foreach.hpp>
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#include <gtsam/linear/SubgraphPreconditioner.h>
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#include <gtsam/linear/JacobianFactor.h>
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#include <gtsam/linear/GaussianFactorGraph.h>
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using namespace std;
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namespace gtsam {
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/* ************************************************************************* */
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SubgraphPreconditioner::SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2,
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const sharedBayesNet& Rc1, const sharedValues& xbar) :
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Ab1_(Ab1), Ab2_(Ab2), Rc1_(Rc1), xbar_(xbar), b2bar_(gaussianErrors_(*Ab2_,*xbar)) {
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}
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/* ************************************************************************* */
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// x = xbar + inv(R1)*y
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VectorValues SubgraphPreconditioner::x(const VectorValues& y) const {
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#ifdef VECTORBTREE
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if (!y.cloned(*xbar_)) throw
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invalid_argument("SubgraphPreconditioner::x: y needs to be cloned from xbar");
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#endif
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VectorValues x = y;
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backSubstituteInPlace(*Rc1_,x);
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x += *xbar_;
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return x;
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}
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// SubgraphPreconditioner SubgraphPreconditioner::add_priors(double sigma) const {
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// SubgraphPreconditioner result = *this ;
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// result.Ab2_ = sharedFG(new GaussianFactorGraph(Ab2_->add_priors(sigma))) ;
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// return result ;
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// }
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/* ************************************************************************* */
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double error(const SubgraphPreconditioner& sp, const VectorValues& y) {
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Errors e(y);
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VectorValues x = sp.x(y);
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Errors e2 = gaussianErrors(*sp.Ab2(),x);
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return 0.5 * (dot(e, e) + dot(e2,e2));
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}
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/* ************************************************************************* */
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// gradient is y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar),
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VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y) {
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VectorValues x = sp.x(y); // x = inv(R1)*y
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Errors e2 = gaussianErrors(*sp.Ab2(),x);
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VectorValues gx2 = VectorValues::Zero(y);
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gtsam::transposeMultiplyAdd(*sp.Ab2(),1.0,e2,gx2); // A2'*e2;
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VectorValues gy2 = gtsam::backSubstituteTranspose(*sp.Rc1(), gx2); // inv(R1')*gx2
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return y + gy2;
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}
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/* ************************************************************************* */
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// Apply operator A, A*y = [I;A2*inv(R1)]*y = [y; A2*inv(R1)*y]
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Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y) {
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Errors e(y);
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// Add A2 contribution
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VectorValues x = y; // TODO avoid ?
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gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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Errors e2 = *sp.Ab2() * x; // A2*x
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e.splice(e.end(), e2);
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return e;
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}
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/* ************************************************************************* */
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// In-place version that overwrites e
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void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e) {
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Errors::iterator ei = e.begin();
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for ( Index i = 0 ; i < y.size() ; ++i, ++ei ) {
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*ei = y[i];
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}
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// Add A2 contribution
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VectorValues x = y; // TODO avoid ?
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gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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gtsam::multiplyInPlace(*sp.Ab2(),x,ei); // use iterator version
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}
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/* ************************************************************************* */
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// Apply operator A', A'*e = [I inv(R1')*A2']*e = e1 + inv(R1')*A2'*e2
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VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e) {
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Errors::const_iterator it = e.begin();
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VectorValues y = sp.zero();
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for ( Index i = 0 ; i < y.size() ; ++i, ++it )
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y[i] = *it ;
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sp.transposeMultiplyAdd2(1.0,it,e.end(),y);
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return y;
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}
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/* ************************************************************************* */
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// y += alpha*A'*e
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void transposeMultiplyAdd
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(const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y) {
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Errors::const_iterator it = e.begin();
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for ( Index i = 0 ; i < y.size() ; ++i, ++it ) {
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const Vector& ei = *it;
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axpy(alpha,ei,y[i]);
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}
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sp.transposeMultiplyAdd2(alpha,it,e.end(),y);
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}
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/* ************************************************************************* */
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// y += alpha*inv(R1')*A2'*e2
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void SubgraphPreconditioner::transposeMultiplyAdd2 (double alpha,
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Errors::const_iterator it, Errors::const_iterator end, VectorValues& y) const {
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// create e2 with what's left of e
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// TODO can we avoid creating e2 by passing iterator to transposeMultiplyAdd ?
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Errors e2;
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while (it != end)
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e2.push_back(*(it++));
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VectorValues x = VectorValues::Zero(y); // x = 0
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gtsam::transposeMultiplyAdd(*Ab2_,1.0,e2,x); // x += A2'*e2
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axpy(alpha, gtsam::backSubstituteTranspose(*Rc1_, x), y); // y += alpha*inv(R1')*x
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}
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/* ************************************************************************* */
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void SubgraphPreconditioner::print(const std::string& s) const {
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cout << s << endl;
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Ab2_->print();
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}
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} // nsamespace gtsam
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///* ----------------------------------------------------------------------------
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//
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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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//
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// * See LICENSE for the license information
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//
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// * -------------------------------------------------------------------------- */
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//
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///**
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// * @file SubgraphPreconditioner.cpp
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// * @date Dec 31, 2009
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// * @author: Frank Dellaert
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// */
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//
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//#include <boost/foreach.hpp>
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//#include <gtsam/linear/SubgraphPreconditioner.h>
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//#include <gtsam/linear/JacobianFactor.h>
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//#include <gtsam/linear/GaussianFactorGraph.h>
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//
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//using namespace std;
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//
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//namespace gtsam {
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//
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// /* ************************************************************************* */
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// SubgraphPreconditioner::SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2,
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// const sharedBayesNet& Rc1, const sharedValues& xbar) :
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// Ab1_(Ab1), Ab2_(Ab2), Rc1_(Rc1), xbar_(xbar), b2bar_(gaussianErrors_(*Ab2_,*xbar)) {
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// }
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//
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// /* ************************************************************************* */
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// // x = xbar + inv(R1)*y
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// VectorValues SubgraphPreconditioner::x(const VectorValues& y) const {
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//#ifdef VECTORBTREE
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// if (!y.cloned(*xbar_)) throw
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// invalid_argument("SubgraphPreconditioner::x: y needs to be cloned from xbar");
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//#endif
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// VectorValues x = y;
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// backSubstituteInPlace(*Rc1_,x);
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// x += *xbar_;
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// return x;
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// }
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//
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//// SubgraphPreconditioner SubgraphPreconditioner::add_priors(double sigma) const {
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//// SubgraphPreconditioner result = *this ;
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//// result.Ab2_ = sharedFG(new GaussianFactorGraph(Ab2_->add_priors(sigma))) ;
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//// return result ;
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//// }
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//
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// /* ************************************************************************* */
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// double error(const SubgraphPreconditioner& sp, const VectorValues& y) {
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//
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// Errors e(y);
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// VectorValues x = sp.x(y);
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// Errors e2 = gaussianErrors(*sp.Ab2(),x);
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// return 0.5 * (dot(e, e) + dot(e2,e2));
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// }
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//
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// /* ************************************************************************* */
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// // gradient is y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar),
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// VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y) {
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// VectorValues x = sp.x(y); // x = inv(R1)*y
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// Errors e2 = gaussianErrors(*sp.Ab2(),x);
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// VectorValues gx2 = VectorValues::Zero(y);
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// gtsam::transposeMultiplyAdd(*sp.Ab2(),1.0,e2,gx2); // A2'*e2;
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// VectorValues gy2 = gtsam::backSubstituteTranspose(*sp.Rc1(), gx2); // inv(R1')*gx2
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// return y + gy2;
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// }
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//
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// /* ************************************************************************* */
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// // Apply operator A, A*y = [I;A2*inv(R1)]*y = [y; A2*inv(R1)*y]
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// Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y) {
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//
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// Errors e(y);
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//
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// // Add A2 contribution
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// VectorValues x = y; // TODO avoid ?
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// gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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// Errors e2 = *sp.Ab2() * x; // A2*x
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// e.splice(e.end(), e2);
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//
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// return e;
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// }
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//
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// /* ************************************************************************* */
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// // In-place version that overwrites e
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// void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e) {
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//
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//
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// Errors::iterator ei = e.begin();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++ei ) {
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// *ei = y[i];
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// }
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//
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// // Add A2 contribution
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// VectorValues x = y; // TODO avoid ?
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// gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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// gtsam::multiplyInPlace(*sp.Ab2(),x,ei); // use iterator version
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// }
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//
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// /* ************************************************************************* */
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// // Apply operator A', A'*e = [I inv(R1')*A2']*e = e1 + inv(R1')*A2'*e2
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// VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e) {
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//
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// Errors::const_iterator it = e.begin();
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// VectorValues y = sp.zero();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++it )
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// y[i] = *it ;
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// sp.transposeMultiplyAdd2(1.0,it,e.end(),y);
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// return y;
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// }
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//
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// /* ************************************************************************* */
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// // y += alpha*A'*e
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// void transposeMultiplyAdd
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// (const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y) {
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//
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//
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// Errors::const_iterator it = e.begin();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++it ) {
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// const Vector& ei = *it;
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// axpy(alpha,ei,y[i]);
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// }
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// sp.transposeMultiplyAdd2(alpha,it,e.end(),y);
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// }
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//
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// /* ************************************************************************* */
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// // y += alpha*inv(R1')*A2'*e2
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// void SubgraphPreconditioner::transposeMultiplyAdd2 (double alpha,
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// Errors::const_iterator it, Errors::const_iterator end, VectorValues& y) const {
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//
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// // create e2 with what's left of e
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// // TODO can we avoid creating e2 by passing iterator to transposeMultiplyAdd ?
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// Errors e2;
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// while (it != end)
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// e2.push_back(*(it++));
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//
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// VectorValues x = VectorValues::Zero(y); // x = 0
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// gtsam::transposeMultiplyAdd(*Ab2_,1.0,e2,x); // x += A2'*e2
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// axpy(alpha, gtsam::backSubstituteTranspose(*Rc1_, x), y); // y += alpha*inv(R1')*x
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// }
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//
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// /* ************************************************************************* */
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// void SubgraphPreconditioner::print(const std::string& s) const {
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// cout << s << endl;
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// Ab2_->print();
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// }
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//} // nsamespace gtsam
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@ -1,116 +1,116 @@
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/* ----------------------------------------------------------------------------
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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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/**
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* @file SubgraphPreconditioner.h
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* @date Dec 31, 2009
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* @author Frank Dellaert
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*/
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#pragma once
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#include <gtsam/linear/JacobianFactor.h>
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#include <gtsam/linear/GaussianBayesNet.h>
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#include <gtsam/nonlinear/Ordering.h> // FIXME shouldn't have nonlinear things in linear
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namespace gtsam {
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/**
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* Subgraph conditioner class, as explained in the RSS 2010 submission.
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* Starting with a graph A*x=b, we split it in two systems A1*x=b1 and A2*x=b2
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* We solve R1*x=c1, and make the substitution y=R1*x-c1.
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* To use the class, give the Bayes Net R1*x=c1 and Graph A2*x=b2.
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* Then solve for yhat using CG, and solve for xhat = system.x(yhat).
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*/
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class SubgraphPreconditioner {
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public:
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typedef boost::shared_ptr<const GaussianBayesNet> sharedBayesNet;
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typedef boost::shared_ptr<const FactorGraph<JacobianFactor> > sharedFG;
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typedef boost::shared_ptr<const VectorValues> sharedValues;
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typedef boost::shared_ptr<const Errors> sharedErrors;
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private:
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sharedFG Ab1_, Ab2_;
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sharedBayesNet Rc1_;
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sharedValues xbar_;
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sharedErrors b2bar_; /** b2 - A2*xbar */
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public:
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SubgraphPreconditioner();
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/**
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* Constructor
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* @param Ab1: the Graph A1*x=b1
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* @param Ab2: the Graph A2*x=b2
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* @param Rc1: the Bayes Net R1*x=c1
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* @param xbar: the solution to R1*x=c1
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*/
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SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2, const sharedBayesNet& Rc1, const sharedValues& xbar);
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/** Access Ab1 */
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const sharedFG& Ab1() const { return Ab1_; }
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/** Access Ab2 */
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const sharedFG& Ab2() const { return Ab2_; }
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/** Access Rc1 */
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const sharedBayesNet& Rc1() const { return Rc1_; }
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/**
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* Add zero-mean i.i.d. Gaussian prior terms to each variable
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* @param sigma Standard deviation of Gaussian
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*/
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// SubgraphPreconditioner add_priors(double sigma) const;
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/* x = xbar + inv(R1)*y */
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VectorValues x(const VectorValues& y) const;
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/* A zero VectorValues with the structure of xbar */
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VectorValues zero() const {
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VectorValues V(VectorValues::Zero(*xbar_)) ;
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return V ;
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}
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/**
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* Add constraint part of the error only, used in both calls above
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* y += alpha*inv(R1')*A2'*e2
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* Takes a range indicating e2 !!!!
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*/
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void transposeMultiplyAdd2(double alpha, Errors::const_iterator begin,
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Errors::const_iterator end, VectorValues& y) const;
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/** print the object */
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void print(const std::string& s = "SubgraphPreconditioner") const;
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};
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/* error, given y */
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double error(const SubgraphPreconditioner& sp, const VectorValues& y);
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/** gradient = y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar) */
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VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y);
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/** Apply operator A */
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Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y);
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/** Apply operator A in place: needs e allocated already */
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void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e);
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/** Apply operator A' */
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VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e);
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/**
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* Add A'*e to y
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* y += alpha*A'*[e1;e2] = [alpha*e1; alpha*inv(R1')*A2'*e2]
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*/
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void transposeMultiplyAdd(const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y);
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} // namespace gtsam
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///* ----------------------------------------------------------------------------
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//
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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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//
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// * See LICENSE for the license information
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//
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// * -------------------------------------------------------------------------- */
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//
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///**
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// * @file SubgraphPreconditioner.h
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// * @date Dec 31, 2009
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// * @author Frank Dellaert
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// */
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//
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//#pragma once
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//
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//#include <gtsam/linear/JacobianFactor.h>
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//#include <gtsam/linear/GaussianBayesNet.h>
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//#include <gtsam/nonlinear/Ordering.h> // FIXME shouldn't have nonlinear things in linear
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//
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//namespace gtsam {
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//
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// /**
|
||||
// * Subgraph conditioner class, as explained in the RSS 2010 submission.
|
||||
// * Starting with a graph A*x=b, we split it in two systems A1*x=b1 and A2*x=b2
|
||||
// * We solve R1*x=c1, and make the substitution y=R1*x-c1.
|
||||
// * To use the class, give the Bayes Net R1*x=c1 and Graph A2*x=b2.
|
||||
// * Then solve for yhat using CG, and solve for xhat = system.x(yhat).
|
||||
// */
|
||||
// class SubgraphPreconditioner {
|
||||
//
|
||||
// public:
|
||||
// typedef boost::shared_ptr<const GaussianBayesNet> sharedBayesNet;
|
||||
// typedef boost::shared_ptr<const FactorGraph<JacobianFactor> > sharedFG;
|
||||
// typedef boost::shared_ptr<const VectorValues> sharedValues;
|
||||
// typedef boost::shared_ptr<const Errors> sharedErrors;
|
||||
//
|
||||
// private:
|
||||
// sharedFG Ab1_, Ab2_;
|
||||
// sharedBayesNet Rc1_;
|
||||
// sharedValues xbar_;
|
||||
// sharedErrors b2bar_; /** b2 - A2*xbar */
|
||||
//
|
||||
// public:
|
||||
//
|
||||
// SubgraphPreconditioner();
|
||||
// /**
|
||||
// * Constructor
|
||||
// * @param Ab1: the Graph A1*x=b1
|
||||
// * @param Ab2: the Graph A2*x=b2
|
||||
// * @param Rc1: the Bayes Net R1*x=c1
|
||||
// * @param xbar: the solution to R1*x=c1
|
||||
// */
|
||||
// SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2, const sharedBayesNet& Rc1, const sharedValues& xbar);
|
||||
//
|
||||
// /** Access Ab1 */
|
||||
// const sharedFG& Ab1() const { return Ab1_; }
|
||||
//
|
||||
// /** Access Ab2 */
|
||||
// const sharedFG& Ab2() const { return Ab2_; }
|
||||
//
|
||||
// /** Access Rc1 */
|
||||
// const sharedBayesNet& Rc1() const { return Rc1_; }
|
||||
//
|
||||
// /**
|
||||
// * Add zero-mean i.i.d. Gaussian prior terms to each variable
|
||||
// * @param sigma Standard deviation of Gaussian
|
||||
// */
|
||||
//// SubgraphPreconditioner add_priors(double sigma) const;
|
||||
//
|
||||
// /* x = xbar + inv(R1)*y */
|
||||
// VectorValues x(const VectorValues& y) const;
|
||||
//
|
||||
// /* A zero VectorValues with the structure of xbar */
|
||||
// VectorValues zero() const {
|
||||
// VectorValues V(VectorValues::Zero(*xbar_)) ;
|
||||
// return V ;
|
||||
// }
|
||||
//
|
||||
// /**
|
||||
// * Add constraint part of the error only, used in both calls above
|
||||
// * y += alpha*inv(R1')*A2'*e2
|
||||
// * Takes a range indicating e2 !!!!
|
||||
// */
|
||||
// void transposeMultiplyAdd2(double alpha, Errors::const_iterator begin,
|
||||
// Errors::const_iterator end, VectorValues& y) const;
|
||||
//
|
||||
// /** print the object */
|
||||
// void print(const std::string& s = "SubgraphPreconditioner") const;
|
||||
// };
|
||||
//
|
||||
// /* error, given y */
|
||||
// double error(const SubgraphPreconditioner& sp, const VectorValues& y);
|
||||
//
|
||||
// /** gradient = y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar) */
|
||||
// VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y);
|
||||
//
|
||||
// /** Apply operator A */
|
||||
// Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y);
|
||||
//
|
||||
// /** Apply operator A in place: needs e allocated already */
|
||||
// void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e);
|
||||
//
|
||||
// /** Apply operator A' */
|
||||
// VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e);
|
||||
//
|
||||
// /**
|
||||
// * Add A'*e to y
|
||||
// * y += alpha*A'*[e1;e2] = [alpha*e1; alpha*inv(R1')*A2'*e2]
|
||||
// */
|
||||
// void transposeMultiplyAdd(const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y);
|
||||
//
|
||||
//} // namespace gtsam
|
||||
|
|
|
|||
|
|
@ -1,50 +1,50 @@
|
|||
/* ----------------------------------------------------------------------------
|
||||
|
||||
* 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
|
||||
|
||||
* -------------------------------------------------------------------------- */
|
||||
|
||||
#include <gtsam/linear/SubgraphSolver.h>
|
||||
|
||||
using namespace std;
|
||||
|
||||
namespace gtsam {
|
||||
|
||||
/* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||
bool split(const std::map<Index, Index> &M,
|
||||
const GaussianFactorGraph &Ab,
|
||||
GaussianFactorGraph &Ab1,
|
||||
GaussianFactorGraph &Ab2) {
|
||||
|
||||
Ab1 = GaussianFactorGraph();
|
||||
Ab2 = GaussianFactorGraph();
|
||||
|
||||
for ( size_t i = 0 ; i < Ab.size() ; ++i ) {
|
||||
|
||||
boost::shared_ptr<GaussianFactor> factor = Ab[i] ;
|
||||
|
||||
if (factor->keys().size() > 2)
|
||||
throw(invalid_argument("split: only support factors with at most two keys"));
|
||||
if (factor->keys().size() == 1) {
|
||||
Ab1.push_back(factor);
|
||||
Ab2.push_back(factor);
|
||||
continue;
|
||||
}
|
||||
Index key1 = factor->keys()[0];
|
||||
Index key2 = factor->keys()[1];
|
||||
|
||||
if ((M.find(key1) != M.end() && M.find(key1)->second == key2) ||
|
||||
(M.find(key2) != M.end() && M.find(key2)->second == key1))
|
||||
Ab1.push_back(factor);
|
||||
else
|
||||
Ab2.push_back(factor);
|
||||
}
|
||||
return true ;
|
||||
}
|
||||
|
||||
} // \namespace gtsam
|
||||
///* ----------------------------------------------------------------------------
|
||||
//
|
||||
// * 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
|
||||
//
|
||||
// * -------------------------------------------------------------------------- */
|
||||
//
|
||||
//#include <gtsam/linear/SubgraphSolver.h>
|
||||
//
|
||||
//using namespace std;
|
||||
//
|
||||
//namespace gtsam {
|
||||
//
|
||||
///* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||
//bool split(const std::map<Index, Index> &M,
|
||||
// const GaussianFactorGraph &Ab,
|
||||
// GaussianFactorGraph &Ab1,
|
||||
// GaussianFactorGraph &Ab2) {
|
||||
//
|
||||
// Ab1 = GaussianFactorGraph();
|
||||
// Ab2 = GaussianFactorGraph();
|
||||
//
|
||||
// for ( size_t i = 0 ; i < Ab.size() ; ++i ) {
|
||||
//
|
||||
// boost::shared_ptr<GaussianFactor> factor = Ab[i] ;
|
||||
//
|
||||
// if (factor->keys().size() > 2)
|
||||
// throw(invalid_argument("split: only support factors with at most two keys"));
|
||||
// if (factor->keys().size() == 1) {
|
||||
// Ab1.push_back(factor);
|
||||
// Ab2.push_back(factor);
|
||||
// continue;
|
||||
// }
|
||||
// Index key1 = factor->keys()[0];
|
||||
// Index key2 = factor->keys()[1];
|
||||
//
|
||||
// if ((M.find(key1) != M.end() && M.find(key1)->second == key2) ||
|
||||
// (M.find(key2) != M.end() && M.find(key2)->second == key1))
|
||||
// Ab1.push_back(factor);
|
||||
// else
|
||||
// Ab2.push_back(factor);
|
||||
// }
|
||||
// return true ;
|
||||
//}
|
||||
//
|
||||
//} // \namespace gtsam
|
||||
|
|
|
|||
|
|
@ -1,100 +1,100 @@
|
|||
/* ----------------------------------------------------------------------------
|
||||
|
||||
* 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
|
||||
|
||||
* -------------------------------------------------------------------------- */
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <boost/make_shared.hpp>
|
||||
|
||||
#include <gtsam/linear/GaussianFactorGraph.h>
|
||||
#include <gtsam/linear/IterativeSolver.h>
|
||||
#include <gtsam/linear/SubgraphPreconditioner.h>
|
||||
|
||||
namespace gtsam {
|
||||
|
||||
/* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||
bool split(const std::map<Index, Index> &M,
|
||||
const GaussianFactorGraph &Ab,
|
||||
GaussianFactorGraph &Ab1,
|
||||
GaussianFactorGraph &Ab2);
|
||||
|
||||
/**
|
||||
* A nonlinear system solver using subgraph preconditioning conjugate gradient
|
||||
* Concept NonLinearSolver<G,T,L> implements
|
||||
* linearize: G * T -> L
|
||||
* solve : L -> VectorValues
|
||||
*/
|
||||
template<class GRAPH, class LINEAR, class VALUES>
|
||||
class SubgraphSolver : public IterativeSolver {
|
||||
|
||||
private:
|
||||
typedef typename VALUES::Key Key;
|
||||
typedef typename GRAPH::Pose Pose;
|
||||
typedef typename GRAPH::Constraint Constraint;
|
||||
|
||||
typedef boost::shared_ptr<const SubgraphSolver> shared_ptr ;
|
||||
typedef boost::shared_ptr<Ordering> shared_ordering ;
|
||||
typedef boost::shared_ptr<GRAPH> shared_graph ;
|
||||
typedef boost::shared_ptr<LINEAR> shared_linear ;
|
||||
typedef boost::shared_ptr<VALUES> shared_values ;
|
||||
typedef boost::shared_ptr<SubgraphPreconditioner> shared_preconditioner ;
|
||||
typedef std::map<Index,Index> mapPairIndex ;
|
||||
|
||||
/* the ordering derived from the spanning tree */
|
||||
shared_ordering ordering_;
|
||||
|
||||
/* the indice of two vertices in the gaussian factor graph */
|
||||
mapPairIndex pairs_;
|
||||
|
||||
/* preconditioner */
|
||||
shared_preconditioner pc_;
|
||||
|
||||
/* flag for direct solver - either QR or LDL */
|
||||
bool useQR_;
|
||||
|
||||
public:
|
||||
|
||||
SubgraphSolver(const GRAPH& G, const VALUES& theta0, const Parameters ¶meters = Parameters(), bool useQR = false):
|
||||
IterativeSolver(parameters), useQR_(useQR) { initialize(G,theta0); }
|
||||
|
||||
SubgraphSolver(const LINEAR& GFG) {
|
||||
std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||
throw std::runtime_error("SubgraphSolver: gaussian factor graph initialization not supported");
|
||||
}
|
||||
|
||||
SubgraphSolver(const shared_linear& GFG, const boost::shared_ptr<VariableIndex>& structure, bool useQR = false) {
|
||||
std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||
throw std::runtime_error("SubgraphSolver: gaussian factor graph and variable index initialization not supported");
|
||||
}
|
||||
|
||||
SubgraphSolver(const SubgraphSolver& solver) :
|
||||
IterativeSolver(solver), ordering_(solver.ordering_), pairs_(solver.pairs_), pc_(solver.pc_), useQR_(solver.useQR_) {}
|
||||
|
||||
SubgraphSolver(shared_ordering ordering,
|
||||
mapPairIndex pairs,
|
||||
shared_preconditioner pc,
|
||||
sharedParameters parameters = boost::make_shared<Parameters>(),
|
||||
bool useQR = true) :
|
||||
IterativeSolver(parameters), ordering_(ordering), pairs_(pairs), pc_(pc), useQR_(useQR) {}
|
||||
|
||||
void replaceFactors(const typename LINEAR::shared_ptr &graph);
|
||||
VectorValues::shared_ptr optimize() ;
|
||||
shared_ordering ordering() const { return ordering_; }
|
||||
|
||||
protected:
|
||||
void initialize(const GRAPH& G, const VALUES& theta0);
|
||||
|
||||
private:
|
||||
SubgraphSolver():IterativeSolver(){}
|
||||
};
|
||||
|
||||
} // namespace gtsam
|
||||
|
||||
#include <gtsam/linear/SubgraphSolver-inl.h>
|
||||
///* ----------------------------------------------------------------------------
|
||||
//
|
||||
// * 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
|
||||
//
|
||||
// * -------------------------------------------------------------------------- */
|
||||
//
|
||||
//#pragma once
|
||||
//
|
||||
//#include <boost/make_shared.hpp>
|
||||
//
|
||||
//#include <gtsam/linear/GaussianFactorGraph.h>
|
||||
//#include <gtsam/linear/IterativeSolver.h>
|
||||
//#include <gtsam/linear/SubgraphPreconditioner.h>
|
||||
//
|
||||
//namespace gtsam {
|
||||
//
|
||||
///* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||
//bool split(const std::map<Index, Index> &M,
|
||||
// const GaussianFactorGraph &Ab,
|
||||
// GaussianFactorGraph &Ab1,
|
||||
// GaussianFactorGraph &Ab2);
|
||||
//
|
||||
///**
|
||||
// * A nonlinear system solver using subgraph preconditioning conjugate gradient
|
||||
// * Concept NonLinearSolver<G,T,L> implements
|
||||
// * linearize: G * T -> L
|
||||
// * solve : L -> VectorValues
|
||||
// */
|
||||
//template<class GRAPH, class LINEAR, class VALUES>
|
||||
//class SubgraphSolver : public IterativeSolver {
|
||||
//
|
||||
//private:
|
||||
// typedef typename VALUES::Key Key;
|
||||
// typedef typename GRAPH::Pose Pose;
|
||||
// typedef typename GRAPH::Constraint Constraint;
|
||||
//
|
||||
// typedef boost::shared_ptr<const SubgraphSolver> shared_ptr ;
|
||||
// typedef boost::shared_ptr<Ordering> shared_ordering ;
|
||||
// typedef boost::shared_ptr<GRAPH> shared_graph ;
|
||||
// typedef boost::shared_ptr<LINEAR> shared_linear ;
|
||||
// typedef boost::shared_ptr<VALUES> shared_values ;
|
||||
// typedef boost::shared_ptr<SubgraphPreconditioner> shared_preconditioner ;
|
||||
// typedef std::map<Index,Index> mapPairIndex ;
|
||||
//
|
||||
// /* the ordering derived from the spanning tree */
|
||||
// shared_ordering ordering_;
|
||||
//
|
||||
// /* the indice of two vertices in the gaussian factor graph */
|
||||
// mapPairIndex pairs_;
|
||||
//
|
||||
// /* preconditioner */
|
||||
// shared_preconditioner pc_;
|
||||
//
|
||||
// /* flag for direct solver - either QR or LDL */
|
||||
// bool useQR_;
|
||||
//
|
||||
//public:
|
||||
//
|
||||
// SubgraphSolver(const GRAPH& G, const VALUES& theta0, const Parameters ¶meters = Parameters(), bool useQR = false):
|
||||
// IterativeSolver(parameters), useQR_(useQR) { initialize(G,theta0); }
|
||||
//
|
||||
// SubgraphSolver(const LINEAR& GFG) {
|
||||
// std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||
// throw std::runtime_error("SubgraphSolver: gaussian factor graph initialization not supported");
|
||||
// }
|
||||
//
|
||||
// SubgraphSolver(const shared_linear& GFG, const boost::shared_ptr<VariableIndex>& structure, bool useQR = false) {
|
||||
// std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||
// throw std::runtime_error("SubgraphSolver: gaussian factor graph and variable index initialization not supported");
|
||||
// }
|
||||
//
|
||||
// SubgraphSolver(const SubgraphSolver& solver) :
|
||||
// IterativeSolver(solver), ordering_(solver.ordering_), pairs_(solver.pairs_), pc_(solver.pc_), useQR_(solver.useQR_) {}
|
||||
//
|
||||
// SubgraphSolver(shared_ordering ordering,
|
||||
// mapPairIndex pairs,
|
||||
// shared_preconditioner pc,
|
||||
// sharedParameters parameters = boost::make_shared<Parameters>(),
|
||||
// bool useQR = true) :
|
||||
// IterativeSolver(parameters), ordering_(ordering), pairs_(pairs), pc_(pc), useQR_(useQR) {}
|
||||
//
|
||||
// void replaceFactors(const typename LINEAR::shared_ptr &graph);
|
||||
// VectorValues::shared_ptr optimize() ;
|
||||
// shared_ordering ordering() const { return ordering_; }
|
||||
//
|
||||
//protected:
|
||||
// void initialize(const GRAPH& G, const VALUES& theta0);
|
||||
//
|
||||
//private:
|
||||
// SubgraphSolver():IterativeSolver(){}
|
||||
//};
|
||||
//
|
||||
//} // namespace gtsam
|
||||
//
|
||||
//#include <gtsam/linear/SubgraphSolver-inl.h>
|
||||
|
|
|
|||
Loading…
Reference in New Issue