/* * SubgraphPreconditioner.cpp * Created on: Dec 31, 2009 * @author: Frank Dellaert */ #include #include "SubgraphPreconditioner.h" using namespace std; namespace gtsam { /* ************************************************************************* */ SubgraphPreconditioner::SubgraphPreconditioner(sharedFG& Ab1, sharedFG& Ab2, sharedBayesNet& Rc1, sharedConfig& xbar) : Ab1_(Ab1), Ab2_(Ab2), Rc1_(Rc1), xbar_(xbar), b2bar_(Ab2_->errors_(*xbar)) { } /* ************************************************************************* */ // x = xbar + inv(R1)*y VectorConfig SubgraphPreconditioner::x(const VectorConfig& y) const { return *xbar_ + gtsam::backSubstitute(*Rc1_, y); } /* ************************************************************************* */ double SubgraphPreconditioner::error(const VectorConfig& y) const { Errors e; // Use BayesNet order to add y contributions in order BOOST_FOREACH(GaussianConditional::shared_ptr cg, *Rc1_) { const Symbol& j = cg->key(); e.push_back(y[j]); // append y } // Add A2 contribution VectorConfig x = this->x(y); Errors e2 = Ab2_->errors(x); e.splice(e.end(), e2); return 0.5 * dot(e, e); } /* ************************************************************************* */ // gradient is y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar), VectorConfig SubgraphPreconditioner::gradient(const VectorConfig& y) const { VectorConfig x = this->x(y); // x = inv(R1)*y VectorConfig gx2 = *Ab2_ ^ Ab2_->errors(x); VectorConfig gy2 = gtsam::backSubstituteTranspose(*Rc1_, gx2); // inv(R1')*gx2 return y + gy2; } /* ************************************************************************* */ // Apply operator A, A*y = [I;A2*inv(R1)]*y = [y; A2*inv(R1)*y] Errors SubgraphPreconditioner::operator*(const VectorConfig& y) const { Errors e; // Use BayesNet order to add y contributions in order BOOST_FOREACH(GaussianConditional::shared_ptr cg, *Rc1_) { const Symbol& j = cg->key(); e.push_back(y[j]); // append y } // Add A2 contribution VectorConfig x = gtsam::backSubstitute(*Rc1_, y); // x=inv(R1)*y Errors e2 = *Ab2_ * x; // A2*x e.splice(e.end(), e2); return e; } /* ************************************************************************* */ // Apply operator A', A'*e = [I inv(R1')*A2']*e = e1 + inv(R1')*A2'*e2 VectorConfig SubgraphPreconditioner::operator^(const Errors& e) const { VectorConfig y1; // Use BayesNet order to remove y contributions in order Errors::const_iterator it = e.begin(); BOOST_FOREACH(GaussianConditional::shared_ptr cg, *Rc1_) { const Symbol& j = cg->key(); const Vector& ej = *(it++); y1.insert(j,ej); } // create e2 with what's left of e Errors e2; while (it != e.end()) e2.push_back(*(it++)); // get A2 part, VectorConfig x = *Ab2_ ^ e2; // x = A2'*e2 VectorConfig y2 = gtsam::backSubstituteTranspose(*Rc1_, x); // inv(R1')*x; return y1 + y2; } /* ************************************************************************* */ void SubgraphPreconditioner::print(const std::string& s) const { cout << s << endl; Ab2_->print(); } } // nsamespace gtsam