111 lines
3.3 KiB
C++
111 lines
3.3 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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/**
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* @file NonlinearISAM-inl.h
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* @date Jan 19, 2010
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* @author Viorela Ila and Richard Roberts
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*/
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#include <gtsam/nonlinear/NonlinearISAM.h>
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#include <gtsam/linear/GaussianFactorGraph.h>
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#include <gtsam/inference/Ordering.h>
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#include <boost/foreach.hpp>
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#include <iostream>
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using namespace std;
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namespace gtsam {
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/* ************************************************************************* */
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void NonlinearISAM::saveGraph(const string& s, const KeyFormatter& keyFormatter) const {
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isam_.saveGraph(s, keyFormatter);
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}
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/* ************************************************************************* */
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void NonlinearISAM::update(const NonlinearFactorGraph& newFactors, const Values& initialValues) {
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if(newFactors.size() > 0) {
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// Reorder and relinearize every reorderInterval updates
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if(reorderInterval_ > 0 && ++reorderCounter_ >= reorderInterval_) {
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reorder_relinearize();
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reorderCounter_ = 0;
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}
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factors_.push_back(newFactors);
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// Linearize new factors and insert them
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// TODO: optimize for whole config?
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linPoint_.insert(initialValues);
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boost::shared_ptr<GaussianFactorGraph> linearizedNewFactors = newFactors.linearize(linPoint_);
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// Update ISAM
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isam_.update(*linearizedNewFactors, eliminationFunction_);
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}
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}
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/* ************************************************************************* */
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void NonlinearISAM::reorder_relinearize() {
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// cout << "Reordering, relinearizing..." << endl;
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if(factors_.size() > 0) {
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// Obtain the new linearization point
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const Values newLinPoint = estimate();
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isam_.clear();
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// Just recreate the whole BayesTree
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// TODO: allow for constrained ordering here
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// TODO: decouple relinearization and reordering to avoid
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isam_.update(*factors_.linearize(newLinPoint), eliminationFunction_);
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// Update linearization point
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linPoint_ = newLinPoint;
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}
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}
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/* ************************************************************************* */
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Values NonlinearISAM::estimate() const {
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if(isam_.size() > 0)
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return linPoint_.retract(isam_.optimize());
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else
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return linPoint_;
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}
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/* ************************************************************************* */
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Matrix NonlinearISAM::marginalCovariance(Key key) const {
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return isam_.marginalCovariance(key);
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}
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/* ************************************************************************* */
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void NonlinearISAM::print(const string& s, const KeyFormatter& keyFormatter) const {
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cout << s << "ReorderInterval: " << reorderInterval_ << " Current Count: " << reorderCounter_ << endl;
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isam_.print("GaussianISAM:\n");
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linPoint_.print("Linearization Point:\n", keyFormatter);
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factors_.print("Nonlinear Graph:\n", keyFormatter);
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}
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/* ************************************************************************* */
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void NonlinearISAM::printStats() const {
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isam_.getCliqueData().getStats().print();
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}
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/* ************************************************************************* */
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}///\ namespace gtsam
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