gtsam/gtsam/hybrid/HybridNonlinearFactorGraph.cpp

101 lines
3.4 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 HybridNonlinearFactorGraph.cpp
* @brief Nonlinear hybrid factor graph that uses type erasure
* @author Varun Agrawal
* @date May 28, 2022
*/
#include <gtsam/hybrid/HybridNonlinearFactorGraph.h>
namespace gtsam {
/* ************************************************************************* */
void HybridNonlinearFactorGraph::add(
boost::shared_ptr<NonlinearFactor> factor) {
FactorGraph::add(boost::make_shared<HybridNonlinearFactor>(factor));
}
/* ************************************************************************* */
void HybridNonlinearFactorGraph::add(
boost::shared_ptr<DiscreteFactor> factor) {
FactorGraph::add(boost::make_shared<HybridDiscreteFactor>(factor));
}
/* ************************************************************************* */
void HybridNonlinearFactorGraph::print(const std::string& s,
const KeyFormatter& keyFormatter) const {
// Base::print(str, keyFormatter);
std::cout << (s.empty() ? "" : s + " ") << std::endl;
std::cout << "size: " << size() << std::endl;
for (size_t i = 0; i < factors_.size(); i++) {
std::stringstream ss;
ss << "factor " << i << ": ";
if (factors_[i]) {
factors_[i]->print(ss.str(), keyFormatter);
std::cout << std::endl;
}
}
}
/* ************************************************************************* */
HybridGaussianFactorGraph HybridNonlinearFactorGraph::linearize(
const Values& continuousValues) const {
// create an empty linear FG
HybridGaussianFactorGraph linearFG;
linearFG.reserve(size());
// linearize all hybrid factors
for (auto&& factor : factors_) {
// First check if it is a valid factor
if (factor) {
// Check if the factor is a hybrid factor.
// It can be either a nonlinear MixtureFactor or a linear
// GaussianMixtureFactor.
if (factor->isHybrid()) {
// Check if it is a nonlinear mixture factor
if (auto nlmf = boost::dynamic_pointer_cast<MixtureFactor>(factor)) {
linearFG.push_back(nlmf->linearize(continuousValues));
} else {
linearFG.push_back(factor);
}
// Now check if the factor is a continuous only factor.
} else if (factor->isContinuous()) {
// In this case, we check if factor->inner() is nonlinear since
// HybridFactors wrap over continuous factors.
auto nlhf = boost::dynamic_pointer_cast<HybridNonlinearFactor>(factor);
if (auto nlf =
boost::dynamic_pointer_cast<NonlinearFactor>(nlhf->inner())) {
auto hgf = boost::make_shared<HybridGaussianFactor>(
nlf->linearize(continuousValues));
linearFG.push_back(hgf);
} else {
linearFG.push_back(factor);
}
// Finally if nothing else, we are discrete-only which doesn't need
// lineariztion.
} else {
linearFG.push_back(factor);
}
} else {
linearFG.push_back(GaussianFactor::shared_ptr());
}
}
return linearFG;
}
} // namespace gtsam