gtsam/gtsam/hybrid/HybridGaussianFactor.cpp

203 lines
7.9 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 HybridGaussianFactor.cpp
* @brief A set of Gaussian factors indexed by a set of discrete keys.
* @author Fan Jiang
* @author Varun Agrawal
* @author Frank Dellaert
* @date Mar 12, 2022
*/
#include <gtsam/base/types.h>
#include <gtsam/base/utilities.h>
#include <gtsam/discrete/DecisionTree-inl.h>
#include <gtsam/discrete/DecisionTree.h>
#include <gtsam/hybrid/HybridFactor.h>
#include <gtsam/hybrid/HybridGaussianFactor.h>
#include <gtsam/hybrid/HybridGaussianProductFactor.h>
#include <gtsam/hybrid/HybridValues.h>
#include <gtsam/linear/GaussianFactor.h>
#include <gtsam/linear/GaussianFactorGraph.h>
namespace gtsam {
/* *******************************************************************************/
struct HybridGaussianFactor::ConstructorHelper {
KeyVector continuousKeys; // Continuous keys extracted from factors
DiscreteKeys discreteKeys; // Discrete keys provided to the constructors
FactorValuePairs pairs; // The decision tree with factors and scalars
/// Constructor for a single discrete key and a vector of Gaussian factors
ConstructorHelper(const DiscreteKey& discreteKey,
const std::vector<GaussianFactor::shared_ptr>& factors)
: discreteKeys({discreteKey}) {
// Extract continuous keys from the first non-null factor
for (const auto& factor : factors) {
if (factor && continuousKeys.empty()) {
continuousKeys = factor->keys();
break;
}
}
// Build the FactorValuePairs DecisionTree
pairs = FactorValuePairs(
DecisionTree<Key, GaussianFactor::shared_ptr>(discreteKeys, factors),
[](const sharedFactor& f) {
return std::pair{f,
f ? 0.0 : std::numeric_limits<double>::infinity()};
});
}
/// Constructor for a single discrete key and a vector of
/// GaussianFactorValuePairs
ConstructorHelper(const DiscreteKey& discreteKey,
const std::vector<GaussianFactorValuePair>& factorPairs)
: discreteKeys({discreteKey}) {
// Extract continuous keys from the first non-null factor
for (const GaussianFactorValuePair& pair : factorPairs) {
if (pair.first && continuousKeys.empty()) {
continuousKeys = pair.first->keys();
break;
}
}
// Build the FactorValuePairs DecisionTree
pairs = FactorValuePairs(discreteKeys, factorPairs);
}
/// Constructor for a vector of discrete keys and a vector of
/// GaussianFactorValuePairs
ConstructorHelper(const DiscreteKeys& discreteKeys,
const FactorValuePairs& factorPairs)
: discreteKeys(discreteKeys) {
// Extract continuous keys from the first non-null factor
// TODO: just stop after first non-null factor
factorPairs.visit([&](const GaussianFactorValuePair& pair) {
if (pair.first && continuousKeys.empty()) {
continuousKeys = pair.first->keys();
}
});
// Build the FactorValuePairs DecisionTree
pairs = factorPairs;
}
};
/* *******************************************************************************/
HybridGaussianFactor::HybridGaussianFactor(const ConstructorHelper& helper)
: Base(helper.continuousKeys, helper.discreteKeys),
factors_(helper.pairs) {}
HybridGaussianFactor::HybridGaussianFactor(
const DiscreteKey& discreteKey,
const std::vector<GaussianFactor::shared_ptr>& factors)
: HybridGaussianFactor(ConstructorHelper(discreteKey, factors)) {}
HybridGaussianFactor::HybridGaussianFactor(
const DiscreteKey& discreteKey,
const std::vector<GaussianFactorValuePair>& factorPairs)
: HybridGaussianFactor(ConstructorHelper(discreteKey, factorPairs)) {}
HybridGaussianFactor::HybridGaussianFactor(const DiscreteKeys& discreteKeys,
const FactorValuePairs& factors)
: HybridGaussianFactor(ConstructorHelper(discreteKeys, factors)) {}
/* *******************************************************************************/
bool HybridGaussianFactor::equals(const HybridFactor& lf, double tol) const {
const This* e = dynamic_cast<const This*>(&lf);
if (e == nullptr) return false;
// This will return false if either factors_ is empty or e->factors_ is
// empty, but not if both are empty or both are not empty:
if (factors_.empty() ^ e->factors_.empty()) return false;
// Check the base and the factors:
auto compareFunc = [tol](const GaussianFactorValuePair& pair1,
const GaussianFactorValuePair& pair2) {
auto f1 = pair1.first, f2 = pair2.first;
bool match = (!f1 && !f2) || (f1 && f2 && f1->equals(*f2, tol));
return match && gtsam::equal(pair1.second, pair2.second, tol);
};
return Base::equals(*e, tol) && factors_.equals(e->factors_, compareFunc);
}
/* *******************************************************************************/
void HybridGaussianFactor::print(const std::string& s,
const KeyFormatter& formatter) const {
std::cout << (s.empty() ? "" : s + "\n");
HybridFactor::print("", formatter);
std::cout << "{\n";
if (factors_.empty()) {
std::cout << " empty" << std::endl;
} else {
factors_.print(
"", [&](Key k) { return formatter(k); },
[&](const GaussianFactorValuePair& pair) -> std::string {
RedirectCout rd;
std::cout << ":\n";
if (pair.first) {
pair.first->print("", formatter);
std::cout << "scalar: " << pair.second << "\n";
return rd.str();
} else {
return "nullptr";
}
});
}
std::cout << "}" << std::endl;
}
/* *******************************************************************************/
GaussianFactorValuePair HybridGaussianFactor::operator()(
const DiscreteValues& assignment) const {
return factors_(assignment);
}
/* *******************************************************************************/
HybridGaussianProductFactor HybridGaussianFactor::asProductFactor() const {
// Implemented by creating a new DecisionTree where:
// - The structure (keys and assignments) is preserved from factors_
// - Each leaf converted to a GaussianFactorGraph with just the factor and its
// scalar.
return {{factors_,
[](const GaussianFactorValuePair& pair)
-> std::pair<GaussianFactorGraph, double> {
return {GaussianFactorGraph{pair.first}, pair.second};
}}};
}
/* *******************************************************************************/
inline static double PotentiallyPrunedComponentError(
const GaussianFactorValuePair& pair, const VectorValues& continuousValues) {
return pair.first ? pair.first->error(continuousValues) + pair.second
: std::numeric_limits<double>::infinity();
}
/* *******************************************************************************/
AlgebraicDecisionTree<Key> HybridGaussianFactor::errorTree(
const VectorValues& continuousValues) const {
// functor to convert from sharedFactor to double error value.
auto errorFunc = [&continuousValues](const GaussianFactorValuePair& pair) {
return PotentiallyPrunedComponentError(pair, continuousValues);
};
return {factors_, errorFunc};
}
/* *******************************************************************************/
double HybridGaussianFactor::error(const HybridValues& values) const {
// Directly index to get the component, no need to build the whole tree.
const GaussianFactorValuePair pair = factors_(values.discrete());
return PotentiallyPrunedComponentError(pair, values.continuous());
}
} // namespace gtsam