gtsam/slam/GaussianISAM2.cpp

135 lines
4.4 KiB
C++

/**
* @file GaussianISAM2
* @brief Full non-linear ISAM
* @author Michael Kaess
*/
#include <gtsam/slam/GaussianISAM2.h>
using namespace std;
using namespace gtsam;
// Explicitly instantiate so we don't have to include everywhere
#include <gtsam/inference/ISAM2-inl.h>
template class ISAM2<GaussianConditional, simulated2D::Config>;
template class ISAM2<GaussianConditional, planarSLAM::Config>;
namespace gtsam {
/* ************************************************************************* */
void optimize2(const GaussianISAM2::sharedClique& clique, double threshold, set<Symbol>& changed, VectorConfig& result) {
// if none of the variables in this clique (frontal and separator!) changed
// significantly, then by the running intersection property, none of the
// cliques in the children need to be processed
bool process_children = false;
// parents are assumed to already be solved and available in result
GaussianISAM2::Clique::const_reverse_iterator it;
for (it = clique->rbegin(); it!=clique->rend(); it++) {
GaussianConditional::shared_ptr cg = *it;
// only solve if at least one of the separator variables changed
// significantly, ie. is in the set "changed"
bool found = true;
if (cg->nrParents()>0) {
found = false;
BOOST_FOREACH(const Symbol& key, cg->parents()) {
if (changed.find(key)!=changed.end()) {
found = true;
}
}
}
if (found) {
// Solve for that variable
Vector x = cg->solve(result);
process_children = true;
// store result in partial solution
result.insert(cg->key(), x);
// if change is above threshold, add to set of changed variables
if (max(abs(x)) >= threshold) {
changed.insert(cg->key());
process_children = true;
}
}
}
if (process_children) {
BOOST_FOREACH(const GaussianISAM2::sharedClique& child, clique->children_) {
optimize2(child, threshold, changed, result);
}
}
}
/* ************************************************************************* */
// fast version without threshold
void optimize2(const GaussianISAM2::sharedClique& clique, VectorConfig& result) {
// parents are assumed to already be solved and available in result
GaussianISAM2::Clique::const_reverse_iterator it;
for (it = clique->rbegin(); it!=clique->rend(); it++) {
GaussianConditional::shared_ptr cg = *it;
Vector x = cg->solve(result);
// store result in partial solution
result.insert(cg->key(), x);
}
BOOST_FOREACH(const GaussianISAM2::sharedClique& child, clique->children_) {
optimize2(child, result);
}
}
/* ************************************************************************* */
VectorConfig optimize2(const GaussianISAM2& bayesTree, double threshold) {
VectorConfig result;
set<Symbol> changed;
// starting from the root, call optimize on each conditional
if (threshold<=0.) {
optimize2(bayesTree.root(), result);
} else {
optimize2(bayesTree.root(), threshold, changed, result);
}
return result;
}
/* ************************************************************************* */
VectorConfig optimize2(const GaussianISAM2_P& bayesTree, double threshold) {
VectorConfig result;
set<Symbol> changed;
// starting from the root, call optimize on each conditional
if (threshold<=0.) {
optimize2(bayesTree.root(), result);
} else {
optimize2(bayesTree.root(), threshold, changed, result);
}
return result;
}
/* ************************************************************************* */
void nnz_internal(const GaussianISAM2::sharedClique& clique, int& result) {
// go through the conditionals of this clique
GaussianISAM2::Clique::const_reverse_iterator it;
for (it = clique->rbegin(); it!=clique->rend(); it++) {
GaussianConditional::shared_ptr cg = *it;
int dimSep = 0;
for (GaussianConditional::const_iterator matrix_it = cg->parentsBegin(); matrix_it != cg->parentsEnd(); matrix_it++) {
dimSep += matrix_it->second.size2();
}
int dimR = cg->dim();
result += ((dimR+1)*dimR)/2 + dimSep*dimR;
}
// traverse the children
BOOST_FOREACH(const GaussianISAM2::sharedClique& child, clique->children_) {
nnz_internal(child, result);
}
}
/* ************************************************************************* */
int calculate_nnz(const GaussianISAM2::sharedClique& clique) {
int result = 0;
// starting from the root, add up entries of frontal and conditional matrices of each conditional
nnz_internal(clique, result);
return result;
}
} /// namespace gtsam