gtsam/gtsam/nonlinear/NonlinearConjugateGradientO...

79 lines
2.4 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 NonlinearConjugateGradientOptimizer.cpp
* @brief Simple non-linear optimizer that solves using *non-preconditioned* CG
* @author Yong-Dian Jian
* @date Jun 11, 2012
*/
#include <gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/linear/VectorValues.h>
#include <cmath>
using namespace std;
namespace gtsam {
/**
* @brief Return the gradient vector of a nonlinear factor graph
* @param nfg the graph
* @param values a linearization point
* Can be moved to NonlinearFactorGraph.h if desired
*/
static VectorValues gradientInPlace(const NonlinearFactorGraph &nfg,
const Values &values) {
// Linearize graph
GaussianFactorGraph::shared_ptr linear = nfg.linearize(values);
return linear->gradientAtZero();
}
double NonlinearConjugateGradientOptimizer::System::error(
const State &state) const {
return graph_.error(state);
}
NonlinearConjugateGradientOptimizer::System::Gradient NonlinearConjugateGradientOptimizer::System::gradient(
const State &state) const {
return gradientInPlace(graph_, state);
}
NonlinearConjugateGradientOptimizer::System::State NonlinearConjugateGradientOptimizer::System::advance(
const State &current, const double alpha, const Gradient &g) const {
Gradient step = g;
step *= alpha;
return current.retract(step);
}
void NonlinearConjugateGradientOptimizer::iterate() {
int dummy;
boost::tie(state_.values, dummy) = nonlinearConjugateGradient<System, Values>(
System(graph_), state_.values, params_, true /* single iterations */);
++state_.iterations;
state_.error = graph_.error(state_.values);
}
const Values& NonlinearConjugateGradientOptimizer::optimize() {
// Optimize until convergence
System system(graph_);
boost::tie(state_.values, state_.iterations) = //
nonlinearConjugateGradient(system, state_.values, params_, false);
state_.error = graph_.error(state_.values);
return state_.values;
}
} /* namespace gtsam */