Merge pull request #40 from borglab/feature/factor_graph_update
Factor graph update and add_factors methodrelease/4.3a0
Frank Dellaert
GitHub
commit
51fb1b6696
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@ -26,74 +26,105 @@
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#include <boost/bind.hpp>
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#include <stdio.h>
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#include <algorithm>
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#include <iostream> // for cout :-(
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#include <sstream>
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#include <iostream> // for cout :-(
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#include <string>
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namespace gtsam {
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/* ************************************************************************* */
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template<class FACTOR>
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void FactorGraph<FACTOR>::print(const std::string& s, const KeyFormatter& formatter) const {
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std::cout << s << std::endl;
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std::cout << "size: " << size() << std::endl;
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for (size_t i = 0; i < factors_.size(); i++) {
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std::stringstream ss;
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ss << "factor " << i << ": ";
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if (factors_[i])
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factors_[i]->print(ss.str(), formatter);
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/* ************************************************************************* */
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template <class FACTOR>
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void FactorGraph<FACTOR>::print(const std::string& s,
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const KeyFormatter& formatter) const {
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std::cout << s << std::endl;
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std::cout << "size: " << size() << std::endl;
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for (size_t i = 0; i < factors_.size(); i++) {
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std::stringstream ss;
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ss << "factor " << i << ": ";
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if (factors_[i]) factors_[i]->print(ss.str(), formatter);
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}
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}
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/* ************************************************************************* */
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template <class FACTOR>
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bool FactorGraph<FACTOR>::equals(const This& fg, double tol) const {
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// check whether the two factor graphs have the same number of factors.
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if (factors_.size() != fg.size()) return false;
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// check whether the factors are the same, in same order.
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for (size_t i = 0; i < factors_.size(); i++) {
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sharedFactor f1 = factors_[i], f2 = fg.factors_[i];
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if (f1 == NULL && f2 == NULL) continue;
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if (f1 == NULL || f2 == NULL) return false;
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if (!f1->equals(*f2, tol)) return false;
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}
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return true;
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}
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/* ************************************************************************* */
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template <class FACTOR>
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size_t FactorGraph<FACTOR>::nrFactors() const {
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size_t size_ = 0;
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for (const sharedFactor& factor : factors_)
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if (factor) size_++;
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return size_;
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}
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/* ************************************************************************* */
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template <class FACTOR>
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KeySet FactorGraph<FACTOR>::keys() const {
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KeySet keys;
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for (const sharedFactor& factor : this->factors_) {
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if (factor) keys.insert(factor->begin(), factor->end());
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}
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return keys;
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}
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/* ************************************************************************* */
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template <class FACTOR>
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KeyVector FactorGraph<FACTOR>::keyVector() const {
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KeyVector keys;
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keys.reserve(2 * size()); // guess at size
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for (const sharedFactor& factor : factors_)
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if (factor) keys.insert(keys.end(), factor->begin(), factor->end());
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std::sort(keys.begin(), keys.end());
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auto last = std::unique(keys.begin(), keys.end());
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keys.erase(last, keys.end());
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return keys;
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}
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/* ************************************************************************* */
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template <class FACTOR>
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template <typename CONTAINER, typename>
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FactorIndices FactorGraph<FACTOR>::add_factors(const CONTAINER& factors,
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bool useEmptySlots) {
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const size_t num_factors = factors.size();
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FactorIndices newFactorIndices(num_factors);
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if (useEmptySlots) {
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size_t i = 0;
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for (size_t j = 0; j < num_factors; ++j) {
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// Loop to find the next available factor slot
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do {
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if (i >= size())
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// Make room for remaining factors, happens only once.
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resize(size() + num_factors - j);
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else if (at(i))
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++i; // Move on to the next slot or past end.
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else
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break; // We found an empty slot, break to fill it.
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} while (true);
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// Use the current slot, updating graph and newFactorSlots.
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at(i) = factors[j];
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newFactorIndices[j] = i;
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}
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} else {
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// We're not looking for unused slots, so just add the factors at the end.
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for (size_t i = 0; i < num_factors; ++i) newFactorIndices[i] = i + size();
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push_back(factors);
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}
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return newFactorIndices;
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}
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/* ************************************************************************* */
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template<class FACTOR>
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bool FactorGraph<FACTOR>::equals(const This& fg, double tol) const {
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/** check whether the two factor graphs have the same number of factors_ */
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if (factors_.size() != fg.size()) return false;
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/** check whether the factors_ are the same */
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for (size_t i = 0; i < factors_.size(); i++) {
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// TODO: Doesn't this force order of factor insertion?
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sharedFactor f1 = factors_[i], f2 = fg.factors_[i];
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if (f1 == NULL && f2 == NULL) continue;
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if (f1 == NULL || f2 == NULL) return false;
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if (!f1->equals(*f2, tol)) return false;
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}
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return true;
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}
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/* ************************************************************************* */
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template<class FACTOR>
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size_t FactorGraph<FACTOR>::nrFactors() const {
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size_t size_ = 0;
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for(const sharedFactor& factor: factors_)
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if (factor) size_++;
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return size_;
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}
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/* ************************************************************************* */
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template<class FACTOR>
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KeySet FactorGraph<FACTOR>::keys() const {
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KeySet keys;
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for(const sharedFactor& factor: this->factors_) {
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if(factor)
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keys.insert(factor->begin(), factor->end());
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}
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return keys;
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}
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/* ************************************************************************* */
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template <class FACTOR>
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KeyVector FactorGraph<FACTOR>::keyVector() const {
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KeyVector keys;
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keys.reserve(2 * size()); // guess at size
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for (const sharedFactor& factor: factors_)
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if (factor)
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keys.insert(keys.end(), factor->begin(), factor->end());
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std::sort(keys.begin(), keys.end());
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auto last = std::unique(keys.begin(), keys.end());
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keys.erase(last, keys.end());
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return keys;
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}
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/* ************************************************************************* */
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} // namespace gtsam
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} // namespace gtsam
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@ -22,350 +22,382 @@
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#pragma once
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#include <gtsam/base/Testable.h>
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#include <gtsam/base/FastVector.h>
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#include <gtsam/base/Testable.h>
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#include <gtsam/inference/Key.h>
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#include <Eigen/Core> // for Eigen::aligned_allocator
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#include <boost/serialization/nvp.hpp>
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#include <boost/serialization/vector.hpp>
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#include <boost/assign/list_inserter.hpp>
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#include <boost/bind.hpp>
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#include <boost/make_shared.hpp>
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#include <boost/serialization/nvp.hpp>
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#include <boost/serialization/vector.hpp>
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#include <string>
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#include <type_traits>
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#include <utility>
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namespace gtsam {
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/// Define collection type:
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typedef FastVector<FactorIndex> FactorIndices;
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// Forward declarations
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template<class CLIQUE> class BayesTree;
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// Forward declarations
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template <class CLIQUE>
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class BayesTree;
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/** Helper */
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template<class C>
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class CRefCallPushBack
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{
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C& obj;
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public:
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CRefCallPushBack(C& obj) : obj(obj) {}
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template<typename A>
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void operator()(const A& a) { obj.push_back(a); }
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};
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/** Helper */
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template <class C>
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class CRefCallPushBack {
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C& obj;
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/** Helper */
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template<class C>
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class RefCallPushBack
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{
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C& obj;
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public:
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RefCallPushBack(C& obj) : obj(obj) {}
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template<typename A>
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void operator()(A& a) { obj.push_back(a); }
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};
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public:
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explicit CRefCallPushBack(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(const A& a) {
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obj.push_back(a);
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}
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};
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/** Helper */
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template<class C>
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class CRefCallAddCopy
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{
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C& obj;
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public:
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CRefCallAddCopy(C& obj) : obj(obj) {}
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template<typename A>
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void operator()(const A& a) { obj.addCopy(a); }
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};
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/** Helper */
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template <class C>
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class RefCallPushBack {
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C& obj;
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public:
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explicit RefCallPushBack(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(A& a) {
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obj.push_back(a);
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}
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};
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/** Helper */
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template <class C>
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class CRefCallAddCopy {
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C& obj;
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public:
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explicit CRefCallAddCopy(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(const A& a) {
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obj.addCopy(a);
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}
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};
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/**
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* A factor graph is a bipartite graph with factor nodes connected to variable
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* nodes. In this class, however, only factor nodes are kept around.
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* \nosubgrouping
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*/
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template <class FACTOR>
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class FactorGraph {
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public:
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typedef FACTOR FactorType; ///< factor type
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typedef boost::shared_ptr<FACTOR>
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sharedFactor; ///< Shared pointer to a factor
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typedef sharedFactor value_type;
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typedef typename FastVector<sharedFactor>::iterator iterator;
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typedef typename FastVector<sharedFactor>::const_iterator const_iterator;
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private:
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typedef FactorGraph<FACTOR> This; ///< Typedef for this class
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typedef boost::shared_ptr<This>
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shared_ptr; ///< Shared pointer for this class
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/// Check if a DERIVEDFACTOR is in fact derived from FactorType.
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template <typename DERIVEDFACTOR>
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using IsDerived = typename std::enable_if<
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std::is_base_of<FactorType, DERIVEDFACTOR>::value>::type;
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/// Check if T has a value_type derived from FactorType.
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template <typename T>
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using HasDerivedValueType = typename std::enable_if<
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std::is_base_of<FactorType, typename T::value_type>::value>::type;
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/// Check if T has a value_type derived from FactorType.
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template <typename T>
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using HasDerivedElementType = typename std::enable_if<std::is_base_of<
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FactorType, typename T::value_type::element_type>::value>::type;
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protected:
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/** concept check, makes sure FACTOR defines print and equals */
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GTSAM_CONCEPT_TESTABLE_TYPE(FACTOR)
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/** Collection of factors */
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FastVector<sharedFactor> factors_;
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/// @name Standard Constructors
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/// @{
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/** Default constructor */
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FactorGraph() {}
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/** Constructor from iterator over factors (shared_ptr or plain objects) */
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template <typename ITERATOR>
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FactorGraph(ITERATOR firstFactor, ITERATOR lastFactor) {
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push_back(firstFactor, lastFactor);
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}
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/** Construct from container of factors (shared_ptr or plain objects) */
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template <class CONTAINER>
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explicit FactorGraph(const CONTAINER& factors) {
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push_back(factors);
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}
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/// @}
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public:
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/// @name Adding Single Factors
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/// @{
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/**
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* A factor graph is a bipartite graph with factor nodes connected to variable nodes.
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* In this class, however, only factor nodes are kept around.
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* \nosubgrouping
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* Reserve space for the specified number of factors if you know in
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* advance how many there will be (works like FastVector::reserve).
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*/
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template<class FACTOR>
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class FactorGraph {
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void reserve(size_t size) { factors_.reserve(size); }
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public:
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typedef FACTOR FactorType; ///< factor type
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typedef boost::shared_ptr<FACTOR> sharedFactor; ///< Shared pointer to a factor
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typedef sharedFactor value_type;
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typedef typename FastVector<sharedFactor>::iterator iterator;
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typedef typename FastVector<sharedFactor>::const_iterator const_iterator;
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/// Add a factor directly using a shared_ptr.
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template <class DERIVEDFACTOR>
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IsDerived<DERIVEDFACTOR> push_back(boost::shared_ptr<DERIVEDFACTOR> factor) {
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factors_.push_back(boost::shared_ptr<FACTOR>(factor));
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}
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private:
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typedef FactorGraph<FACTOR> This; ///< Typedef for this class
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typedef boost::shared_ptr<This> shared_ptr; ///< Shared pointer for this class
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/// Emplace a shared pointer to factor of given type.
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template <class DERIVEDFACTOR, class... Args>
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IsDerived<DERIVEDFACTOR> emplace_shared(Args&&... args) {
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factors_.push_back(boost::allocate_shared<DERIVEDFACTOR>(
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Eigen::aligned_allocator<DERIVEDFACTOR>(),
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std::forward<Args>(args)...));
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}
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protected:
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/** concept check, makes sure FACTOR defines print and equals */
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GTSAM_CONCEPT_TESTABLE_TYPE(FACTOR)
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/**
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* Add a factor by value, will be copy-constructed (use push_back with a
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* shared_ptr to avoid the copy).
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*/
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template <class DERIVEDFACTOR>
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IsDerived<DERIVEDFACTOR> push_back(const DERIVEDFACTOR& factor) {
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factors_.push_back(boost::allocate_shared<DERIVEDFACTOR>(
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Eigen::aligned_allocator<DERIVEDFACTOR>(), factor));
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}
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/** Collection of factors */
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FastVector<sharedFactor> factors_;
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/// `add` is a synonym for push_back.
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template <class DERIVEDFACTOR>
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IsDerived<DERIVEDFACTOR> add(boost::shared_ptr<DERIVEDFACTOR> factor) {
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push_back(factor);
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}
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/// @name Standard Constructors
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/// @{
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/// `+=` works well with boost::assign list inserter.
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template <class DERIVEDFACTOR>
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typename std::enable_if<
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std::is_base_of<FactorType, DERIVEDFACTOR>::value,
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boost::assign::list_inserter<RefCallPushBack<This>>>::type
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operator+=(boost::shared_ptr<DERIVEDFACTOR> factor) {
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return boost::assign::make_list_inserter(RefCallPushBack<This>(*this))(
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factor);
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}
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/** Default constructor */
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FactorGraph() {}
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/// @}
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/// @name Adding via iterators
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/// @{
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/** Constructor from iterator over factors (shared_ptr or plain objects) */
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template<typename ITERATOR>
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FactorGraph(ITERATOR firstFactor, ITERATOR lastFactor) { push_back(firstFactor, lastFactor); }
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/**
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* Push back many factors with an iterator over shared_ptr (factors are not
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* copied)
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*/
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template <typename ITERATOR>
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HasDerivedElementType<ITERATOR> push_back(ITERATOR firstFactor,
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ITERATOR lastFactor) {
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factors_.insert(end(), firstFactor, lastFactor);
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}
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/** Construct from container of factors (shared_ptr or plain objects) */
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template<class CONTAINER>
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explicit FactorGraph(const CONTAINER& factors) { push_back(factors); }
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/// Push back many factors with an iterator (factors are copied)
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template <typename ITERATOR>
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HasDerivedValueType<ITERATOR> push_back(ITERATOR firstFactor,
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ITERATOR lastFactor) {
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for (ITERATOR f = firstFactor; f != lastFactor; ++f) push_back(*f);
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}
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/// @}
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/// @name Advanced Constructors
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/// @{
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/// @}
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/// @name Adding via container
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/// @{
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// TODO: are these needed?
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/**
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* Push back many factors as shared_ptr's in a container (factors are not
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* copied)
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*/
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template <typename CONTAINER>
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HasDerivedElementType<CONTAINER> push_back(const CONTAINER& container) {
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push_back(container.begin(), container.end());
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}
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///**
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// * @brief Constructor from a Bayes net
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// * @param bayesNet the Bayes net to convert, type CONDITIONAL must yield compatible factor
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// * @return a factor graph with all the conditionals, as factors
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// */
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//template<class CONDITIONAL>
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//FactorGraph(const BayesNet<CONDITIONAL>& bayesNet);
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/// Push back non-pointer objects in a container (factors are copied).
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template <typename CONTAINER>
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HasDerivedValueType<CONTAINER> push_back(const CONTAINER& container) {
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push_back(container.begin(), container.end());
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}
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///** convert from Bayes tree */
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//template<class CONDITIONAL, class CLIQUE>
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//FactorGraph(const BayesTree<CONDITIONAL, CLIQUE>& bayesTree);
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/**
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* Add a factor or container of factors, including STL collections,
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* BayesTrees, etc.
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*/
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template <class FACTOR_OR_CONTAINER>
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void add(const FACTOR_OR_CONTAINER& factorOrContainer) {
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push_back(factorOrContainer);
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}
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///** convert from a derived type */
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//template<class DERIVEDFACTOR>
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//FactorGraph(const FactorGraph<DERIVEDFACTOR>& factors) {
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// factors_.assign(factors.begin(), factors.end());
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//}
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/**
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* Add a factor or container of factors, including STL collections,
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* BayesTrees, etc.
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*/
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template <class FACTOR_OR_CONTAINER>
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||||
boost::assign::list_inserter<CRefCallPushBack<This>> operator+=(
|
||||
const FACTOR_OR_CONTAINER& factorOrContainer) {
|
||||
return boost::assign::make_list_inserter(CRefCallPushBack<This>(*this))(
|
||||
factorOrContainer);
|
||||
}
|
||||
|
||||
/// @}
|
||||
/// @}
|
||||
/// @name Specialized versions
|
||||
/// @{
|
||||
|
||||
public:
|
||||
/// @name Adding Factors
|
||||
/// @{
|
||||
/**
|
||||
* Push back a BayesTree as a collection of factors.
|
||||
* NOTE: This should be hidden in derived classes in favor of a
|
||||
* type-specialized version that calls this templated function.
|
||||
*/
|
||||
template <class CLIQUE>
|
||||
typename std::enable_if<
|
||||
std::is_base_of<This, typename CLIQUE::FactorGraphType>::value>::type
|
||||
push_back(const BayesTree<CLIQUE>& bayesTree) {
|
||||
bayesTree.addFactorsToGraph(*this);
|
||||
}
|
||||
|
||||
/**
|
||||
* Reserve space for the specified number of factors if you know in
|
||||
* advance how many there will be (works like FastVector::reserve).
|
||||
*/
|
||||
void reserve(size_t size) { factors_.reserve(size); }
|
||||
/**
|
||||
* Add new factors to a factor graph and returns a list of new factor indices,
|
||||
* optionally finding and reusing empty factor slots.
|
||||
*/
|
||||
template <typename CONTAINER, typename = HasDerivedElementType<CONTAINER>>
|
||||
FactorIndices add_factors(const CONTAINER& factors,
|
||||
bool useEmptySlots = false);
|
||||
|
||||
// TODO: are these needed?
|
||||
/// @}
|
||||
/// @name Testable
|
||||
/// @{
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
template<class DERIVEDFACTOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value>::type
|
||||
push_back(boost::shared_ptr<DERIVEDFACTOR> factor) {
|
||||
factors_.push_back(boost::shared_ptr<FACTOR>(factor)); }
|
||||
/** print out graph */
|
||||
void print(const std::string& s = "FactorGraph",
|
||||
const KeyFormatter& formatter = DefaultKeyFormatter) const;
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
void push_back(const sharedFactor& factor) {
|
||||
factors_.push_back(factor); }
|
||||
/** Check equality */
|
||||
bool equals(const This& fg, double tol = 1e-9) const;
|
||||
/// @}
|
||||
|
||||
/** Emplace a factor */
|
||||
template<class DERIVEDFACTOR, class... Args>
|
||||
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value>::type
|
||||
emplace_shared(Args&&... args) {
|
||||
factors_.push_back(boost::allocate_shared<DERIVEDFACTOR>(Eigen::aligned_allocator<DERIVEDFACTOR>(), std::forward<Args>(args)...));
|
||||
}
|
||||
public:
|
||||
/// @name Standard Interface
|
||||
/// @{
|
||||
|
||||
/** push back many factors with an iterator over shared_ptr (factors are not copied) */
|
||||
template<typename ITERATOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, typename ITERATOR::value_type::element_type>::value>::type
|
||||
push_back(ITERATOR firstFactor, ITERATOR lastFactor) {
|
||||
factors_.insert(end(), firstFactor, lastFactor); }
|
||||
/** return the number of factors (including any null factors set by remove()
|
||||
* ). */
|
||||
size_t size() const { return factors_.size(); }
|
||||
|
||||
/** push back many factors as shared_ptr's in a container (factors are not copied) */
|
||||
template<typename CONTAINER>
|
||||
typename std::enable_if<std::is_base_of<FactorType, typename CONTAINER::value_type::element_type>::value>::type
|
||||
push_back(const CONTAINER& container) {
|
||||
push_back(container.begin(), container.end());
|
||||
}
|
||||
/** Check if the graph is empty (null factors set by remove() will cause
|
||||
* this to return false). */
|
||||
bool empty() const { return factors_.empty(); }
|
||||
|
||||
/** push back a BayesTree as a collection of factors. NOTE: This should be hidden in derived
|
||||
* classes in favor of a type-specialized version that calls this templated function. */
|
||||
template<class CLIQUE>
|
||||
typename std::enable_if<std::is_base_of<This, typename CLIQUE::FactorGraphType>::value>::type
|
||||
push_back(const BayesTree<CLIQUE>& bayesTree) {
|
||||
bayesTree.addFactorsToGraph(*this);
|
||||
}
|
||||
/** Get a specific factor by index (this checks array bounds and may throw
|
||||
* an exception, as opposed to operator[] which does not).
|
||||
*/
|
||||
const sharedFactor at(size_t i) const { return factors_.at(i); }
|
||||
|
||||
//#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V4
|
||||
/** Add a factor by value, will be copy-constructed (use push_back with a shared_ptr to avoid
|
||||
* the copy). */
|
||||
template<class DERIVEDFACTOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value>::type
|
||||
push_back(const DERIVEDFACTOR& factor) {
|
||||
factors_.push_back(boost::allocate_shared<DERIVEDFACTOR>(Eigen::aligned_allocator<DERIVEDFACTOR>(), factor));
|
||||
}
|
||||
//#endif
|
||||
/** Get a specific factor by index (this checks array bounds and may throw
|
||||
* an exception, as opposed to operator[] which does not).
|
||||
*/
|
||||
sharedFactor& at(size_t i) { return factors_.at(i); }
|
||||
|
||||
/** push back many factors with an iterator over plain factors (factors are copied) */
|
||||
template<typename ITERATOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, typename ITERATOR::value_type>::value>::type
|
||||
push_back(ITERATOR firstFactor, ITERATOR lastFactor) {
|
||||
for (ITERATOR f = firstFactor; f != lastFactor; ++f)
|
||||
push_back(*f);
|
||||
}
|
||||
/** Get a specific factor by index (this does not check array bounds, as
|
||||
* opposed to at() which does).
|
||||
*/
|
||||
const sharedFactor operator[](size_t i) const { return at(i); }
|
||||
|
||||
/** push back many factors as non-pointer objects in a container (factors are copied) */
|
||||
template<typename CONTAINER>
|
||||
typename std::enable_if<std::is_base_of<FactorType, typename CONTAINER::value_type>::value>::type
|
||||
push_back(const CONTAINER& container) {
|
||||
push_back(container.begin(), container.end());
|
||||
}
|
||||
/** Get a specific factor by index (this does not check array bounds, as
|
||||
* opposed to at() which does).
|
||||
*/
|
||||
sharedFactor& operator[](size_t i) { return at(i); }
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
template<class DERIVEDFACTOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value,
|
||||
boost::assign::list_inserter<RefCallPushBack<This> > >::type
|
||||
operator+=(boost::shared_ptr<DERIVEDFACTOR> factor) {
|
||||
return boost::assign::make_list_inserter(RefCallPushBack<This>(*this))(factor);
|
||||
}
|
||||
/** Iterator to beginning of factors. */
|
||||
const_iterator begin() const { return factors_.begin(); }
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
boost::assign::list_inserter<CRefCallPushBack<This> >
|
||||
operator+=(const sharedFactor& factor) {
|
||||
return boost::assign::make_list_inserter(CRefCallPushBack<This>(*this))(factor);
|
||||
}
|
||||
/** Iterator to end of factors. */
|
||||
const_iterator end() const { return factors_.end(); }
|
||||
|
||||
/** Add a factor or container of factors, including STL collections, BayesTrees, etc. */
|
||||
template<class FACTOR_OR_CONTAINER>
|
||||
boost::assign::list_inserter<CRefCallPushBack<This> >
|
||||
operator+=(const FACTOR_OR_CONTAINER& factorOrContainer) {
|
||||
return boost::assign::make_list_inserter(CRefCallPushBack<This>(*this))(factorOrContainer);
|
||||
}
|
||||
/** Get the first factor */
|
||||
sharedFactor front() const { return factors_.front(); }
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
template<class DERIVEDFACTOR>
|
||||
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value>::type
|
||||
add(boost::shared_ptr<DERIVEDFACTOR> factor) {
|
||||
push_back(factor);
|
||||
}
|
||||
/** Get the last factor */
|
||||
sharedFactor back() const { return factors_.back(); }
|
||||
|
||||
/** Add a factor directly using a shared_ptr */
|
||||
void add(const sharedFactor& factor) {
|
||||
push_back(factor);
|
||||
}
|
||||
/// @}
|
||||
/// @name Modifying Factor Graphs (imperative, discouraged)
|
||||
/// @{
|
||||
|
||||
/** Add a factor or container of factors, including STL collections, BayesTrees, etc. */
|
||||
template<class FACTOR_OR_CONTAINER>
|
||||
void add(const FACTOR_OR_CONTAINER& factorOrContainer) {
|
||||
push_back(factorOrContainer);
|
||||
}
|
||||
/** non-const STL-style begin() */
|
||||
iterator begin() { return factors_.begin(); }
|
||||
|
||||
/// @}
|
||||
/// @name Testable
|
||||
/// @{
|
||||
/** non-const STL-style end() */
|
||||
iterator end() { return factors_.end(); }
|
||||
|
||||
/** print out graph */
|
||||
void print(const std::string& s = "FactorGraph",
|
||||
const KeyFormatter& formatter = DefaultKeyFormatter) const;
|
||||
/** Directly resize the number of factors in the graph. If the new size is
|
||||
* less than the original, factors at the end will be removed. If the new
|
||||
* size is larger than the original, null factors will be appended.
|
||||
*/
|
||||
void resize(size_t size) { factors_.resize(size); }
|
||||
|
||||
/** Check equality */
|
||||
bool equals(const This& fg, double tol = 1e-9) const;
|
||||
/// @}
|
||||
/** delete factor without re-arranging indexes by inserting a NULL pointer
|
||||
*/
|
||||
void remove(size_t i) { factors_[i].reset(); }
|
||||
|
||||
public:
|
||||
/// @name Standard Interface
|
||||
/// @{
|
||||
/** replace a factor by index */
|
||||
void replace(size_t index, sharedFactor factor) { at(index) = factor; }
|
||||
|
||||
/** return the number of factors (including any null factors set by remove() ). */
|
||||
size_t size() const { return factors_.size(); }
|
||||
/** Erase factor and rearrange other factors to take up the empty space */
|
||||
iterator erase(iterator item) { return factors_.erase(item); }
|
||||
|
||||
/** Check if the graph is empty (null factors set by remove() will cause this to return false). */
|
||||
bool empty() const { return factors_.empty(); }
|
||||
/** Erase factors and rearrange other factors to take up the empty space */
|
||||
iterator erase(iterator first, iterator last) {
|
||||
return factors_.erase(first, last);
|
||||
}
|
||||
|
||||
/** Get a specific factor by index (this checks array bounds and may throw an exception, as
|
||||
* opposed to operator[] which does not).
|
||||
*/
|
||||
const sharedFactor at(size_t i) const { return factors_.at(i); }
|
||||
/// @}
|
||||
/// @name Advanced Interface
|
||||
/// @{
|
||||
|
||||
/** Get a specific factor by index (this checks array bounds and may throw an exception, as
|
||||
* opposed to operator[] which does not).
|
||||
*/
|
||||
sharedFactor& at(size_t i) { return factors_.at(i); }
|
||||
/** return the number of non-null factors */
|
||||
size_t nrFactors() const;
|
||||
|
||||
/** Get a specific factor by index (this does not check array bounds, as opposed to at() which
|
||||
* does).
|
||||
*/
|
||||
const sharedFactor operator[](size_t i) const { return at(i); }
|
||||
/** Potentially slow function to return all keys involved, sorted, as a set
|
||||
*/
|
||||
KeySet keys() const;
|
||||
|
||||
/** Get a specific factor by index (this does not check array bounds, as opposed to at() which
|
||||
* does).
|
||||
*/
|
||||
sharedFactor& operator[](size_t i) { return at(i); }
|
||||
/** Potentially slow function to return all keys involved, sorted, as a
|
||||
* vector
|
||||
*/
|
||||
KeyVector keyVector() const;
|
||||
|
||||
/** Iterator to beginning of factors. */
|
||||
const_iterator begin() const { return factors_.begin();}
|
||||
/** MATLAB interface utility: Checks whether a factor index idx exists in
|
||||
* the graph and is a live pointer */
|
||||
inline bool exists(size_t idx) const { return idx < size() && at(idx); }
|
||||
|
||||
/** Iterator to end of factors. */
|
||||
const_iterator end() const { return factors_.end(); }
|
||||
private:
|
||||
/** Serialization function */
|
||||
friend class boost::serialization::access;
|
||||
template <class ARCHIVE>
|
||||
void serialize(ARCHIVE& ar, const unsigned int /*version*/) {
|
||||
ar& BOOST_SERIALIZATION_NVP(factors_);
|
||||
}
|
||||
|
||||
/** Get the first factor */
|
||||
sharedFactor front() const { return factors_.front(); }
|
||||
|
||||
/** Get the last factor */
|
||||
sharedFactor back() const { return factors_.back(); }
|
||||
|
||||
/// @}
|
||||
/// @name Modifying Factor Graphs (imperative, discouraged)
|
||||
/// @{
|
||||
|
||||
/** non-const STL-style begin() */
|
||||
iterator begin() { return factors_.begin();}
|
||||
|
||||
/** non-const STL-style end() */
|
||||
iterator end() { return factors_.end(); }
|
||||
|
||||
/** Directly resize the number of factors in the graph. If the new size is less than the
|
||||
* original, factors at the end will be removed. If the new size is larger than the original,
|
||||
* null factors will be appended.
|
||||
*/
|
||||
void resize(size_t size) { factors_.resize(size); }
|
||||
|
||||
/** delete factor without re-arranging indexes by inserting a NULL pointer */
|
||||
void remove(size_t i) { factors_[i].reset();}
|
||||
|
||||
/** replace a factor by index */
|
||||
void replace(size_t index, sharedFactor factor) { at(index) = factor; }
|
||||
|
||||
/** Erase factor and rearrange other factors to take up the empty space */
|
||||
iterator erase(iterator item) { return factors_.erase(item); }
|
||||
|
||||
/** Erase factors and rearrange other factors to take up the empty space */
|
||||
iterator erase(iterator first, iterator last) { return factors_.erase(first, last); }
|
||||
|
||||
/// @}
|
||||
/// @name Advanced Interface
|
||||
/// @{
|
||||
|
||||
/** return the number of non-null factors */
|
||||
size_t nrFactors() const;
|
||||
|
||||
/** Potentially slow function to return all keys involved, sorted, as a set */
|
||||
KeySet keys() const;
|
||||
|
||||
/** Potentially slow function to return all keys involved, sorted, as a vector */
|
||||
KeyVector keyVector() const;
|
||||
|
||||
/** MATLAB interface utility: Checks whether a factor index idx exists in the graph and is a live pointer */
|
||||
inline bool exists(size_t idx) const { return idx < size() && at(idx); }
|
||||
|
||||
private:
|
||||
|
||||
/** Serialization function */
|
||||
friend class boost::serialization::access;
|
||||
template<class ARCHIVE>
|
||||
void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
|
||||
ar & BOOST_SERIALIZATION_NVP(factors_);
|
||||
}
|
||||
|
||||
/// @}
|
||||
|
||||
}; // FactorGraph
|
||||
|
||||
} // namespace gtsam
|
||||
/// @}
|
||||
}; // FactorGraph
|
||||
} // namespace gtsam
|
||||
|
||||
#include <gtsam/inference/FactorGraph-inst.h>
|
||||
|
|
|
|||
|
|
@ -35,12 +35,15 @@ namespace gtsam {
|
|||
namespace internal
|
||||
{
|
||||
/* ************************************************************************* */
|
||||
double logDeterminant(const GaussianBayesTreeClique::shared_ptr& clique, double& parentSum)
|
||||
{
|
||||
parentSum += clique->conditional()->R().diagonal().unaryExpr(std::ptr_fun<double,double>(log)).sum();
|
||||
assert(false);
|
||||
return 0;
|
||||
}
|
||||
double logDeterminant(const GaussianBayesTreeClique::shared_ptr& clique,
|
||||
double& parentSum) {
|
||||
parentSum += clique->conditional()
|
||||
->R()
|
||||
.diagonal()
|
||||
.unaryExpr(std::ptr_fun<double, double>(log))
|
||||
.sum();
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
|
|
|
|||
|
|
@ -15,14 +15,16 @@
|
|||
* @author Christian Potthast
|
||||
**/
|
||||
|
||||
#include <CppUnitLite/TestHarness.h>
|
||||
|
||||
#include <gtsam/symbolic/SymbolicFactorGraph.h>
|
||||
|
||||
#include <gtsam/base/TestableAssertions.h>
|
||||
#include <gtsam/symbolic/SymbolicBayesNet.h>
|
||||
#include <gtsam/symbolic/SymbolicBayesTree.h>
|
||||
#include <gtsam/symbolic/SymbolicConditional.h>
|
||||
#include <gtsam/symbolic/tests/symbolicExampleGraphs.h>
|
||||
|
||||
#include <CppUnitLite/TestHarness.h>
|
||||
|
||||
#include <boost/assign/std/set.hpp>
|
||||
|
||||
using namespace std;
|
||||
|
|
@ -46,11 +48,10 @@ TEST(SymbolicFactorGraph, keys2) {
|
|||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicFactorGraph, eliminateFullSequential)
|
||||
{
|
||||
TEST(SymbolicFactorGraph, eliminateFullSequential) {
|
||||
// Test with simpleTestGraph1
|
||||
Ordering order;
|
||||
order += 0,1,2,3,4;
|
||||
order += 0, 1, 2, 3, 4;
|
||||
SymbolicBayesNet actual1 = *simpleTestGraph1.eliminateSequential(order);
|
||||
EXPECT(assert_equal(simpleTestGraph1BayesNet, actual1));
|
||||
|
||||
|
|
@ -60,24 +61,20 @@ TEST(SymbolicFactorGraph, eliminateFullSequential)
|
|||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicFactorGraph, eliminatePartialSequential)
|
||||
{
|
||||
TEST(SymbolicFactorGraph, eliminatePartialSequential) {
|
||||
// Eliminate 0 and 1
|
||||
const Ordering order = list_of(0)(1);
|
||||
|
||||
const SymbolicBayesNet expectedBayesNet = list_of
|
||||
(SymbolicConditional(0,1,2))
|
||||
(SymbolicConditional(1,2,3,4));
|
||||
const SymbolicBayesNet expectedBayesNet =
|
||||
list_of(SymbolicConditional(0, 1, 2))(SymbolicConditional(1, 2, 3, 4));
|
||||
|
||||
const SymbolicFactorGraph expectedSfg = list_of
|
||||
(SymbolicFactor(2,3))
|
||||
(SymbolicFactor(4,5))
|
||||
(SymbolicFactor(2,3,4));
|
||||
const SymbolicFactorGraph expectedSfg = list_of(SymbolicFactor(2, 3))(
|
||||
SymbolicFactor(4, 5))(SymbolicFactor(2, 3, 4));
|
||||
|
||||
SymbolicBayesNet::shared_ptr actualBayesNet;
|
||||
SymbolicFactorGraph::shared_ptr actualSfg;
|
||||
boost::tie(actualBayesNet, actualSfg) =
|
||||
simpleTestGraph2.eliminatePartialSequential(Ordering(list_of(0)(1)));
|
||||
simpleTestGraph2.eliminatePartialSequential(Ordering(list_of(0)(1)));
|
||||
|
||||
EXPECT(assert_equal(expectedSfg, *actualSfg));
|
||||
EXPECT(assert_equal(expectedBayesNet, *actualBayesNet));
|
||||
|
|
@ -85,75 +82,71 @@ TEST(SymbolicFactorGraph, eliminatePartialSequential)
|
|||
SymbolicBayesNet::shared_ptr actualBayesNet2;
|
||||
SymbolicFactorGraph::shared_ptr actualSfg2;
|
||||
boost::tie(actualBayesNet2, actualSfg2) =
|
||||
simpleTestGraph2.eliminatePartialSequential(list_of(0)(1).convert_to_container<KeyVector >());
|
||||
simpleTestGraph2.eliminatePartialSequential(
|
||||
list_of(0)(1).convert_to_container<KeyVector>());
|
||||
|
||||
EXPECT(assert_equal(expectedSfg, *actualSfg2));
|
||||
EXPECT(assert_equal(expectedBayesNet, *actualBayesNet2));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicFactorGraph, eliminateFullMultifrontal)
|
||||
{
|
||||
Ordering ordering; ordering += 0,1,2,3;
|
||||
SymbolicBayesTree actual1 =
|
||||
*simpleChain.eliminateMultifrontal(ordering);
|
||||
TEST(SymbolicFactorGraph, eliminateFullMultifrontal) {
|
||||
Ordering ordering;
|
||||
ordering += 0, 1, 2, 3;
|
||||
SymbolicBayesTree actual1 = *simpleChain.eliminateMultifrontal(ordering);
|
||||
EXPECT(assert_equal(simpleChainBayesTree, actual1));
|
||||
|
||||
SymbolicBayesTree actual2 =
|
||||
*asiaGraph.eliminateMultifrontal(asiaOrdering);
|
||||
SymbolicBayesTree actual2 = *asiaGraph.eliminateMultifrontal(asiaOrdering);
|
||||
EXPECT(assert_equal(asiaBayesTree, actual2));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicFactorGraph, eliminatePartialMultifrontal)
|
||||
{
|
||||
TEST(SymbolicFactorGraph, eliminatePartialMultifrontal) {
|
||||
SymbolicBayesTree expectedBayesTree;
|
||||
SymbolicConditional::shared_ptr root = boost::make_shared<SymbolicConditional>(
|
||||
SymbolicConditional::FromKeys(list_of(4)(5)(1), 2));
|
||||
expectedBayesTree.insertRoot(boost::make_shared<SymbolicBayesTreeClique>(root));
|
||||
SymbolicConditional::shared_ptr root =
|
||||
boost::make_shared<SymbolicConditional>(
|
||||
SymbolicConditional::FromKeys(list_of(4)(5)(1), 2));
|
||||
expectedBayesTree.insertRoot(
|
||||
boost::make_shared<SymbolicBayesTreeClique>(root));
|
||||
|
||||
SymbolicFactorGraph expectedFactorGraph = list_of
|
||||
(SymbolicFactor(0,1))
|
||||
(SymbolicFactor(0,2))
|
||||
(SymbolicFactor(1,3))
|
||||
(SymbolicFactor(2,3))
|
||||
(SymbolicFactor(1));
|
||||
SymbolicFactorGraph expectedFactorGraph =
|
||||
list_of(SymbolicFactor(0, 1))(SymbolicFactor(0, 2))(SymbolicFactor(1, 3))(
|
||||
SymbolicFactor(2, 3))(SymbolicFactor(1));
|
||||
|
||||
SymbolicBayesTree::shared_ptr actualBayesTree;
|
||||
SymbolicFactorGraph::shared_ptr actualFactorGraph;
|
||||
boost::tie(actualBayesTree, actualFactorGraph) =
|
||||
simpleTestGraph2.eliminatePartialMultifrontal(Ordering(list_of(4)(5)));
|
||||
simpleTestGraph2.eliminatePartialMultifrontal(Ordering(list_of(4)(5)));
|
||||
|
||||
EXPECT(assert_equal(expectedFactorGraph, *actualFactorGraph));
|
||||
EXPECT(assert_equal(expectedBayesTree, *actualBayesTree));
|
||||
|
||||
SymbolicBayesTree expectedBayesTree2;
|
||||
SymbolicBayesTreeClique::shared_ptr root2 = boost::make_shared<SymbolicBayesTreeClique>(
|
||||
boost::make_shared<SymbolicConditional>(4,1));
|
||||
SymbolicBayesTreeClique::shared_ptr root2 =
|
||||
boost::make_shared<SymbolicBayesTreeClique>(
|
||||
boost::make_shared<SymbolicConditional>(4, 1));
|
||||
root2->children.push_back(boost::make_shared<SymbolicBayesTreeClique>(
|
||||
boost::make_shared<SymbolicConditional>(5,4)));
|
||||
boost::make_shared<SymbolicConditional>(5, 4)));
|
||||
expectedBayesTree2.insertRoot(root2);
|
||||
|
||||
SymbolicBayesTree::shared_ptr actualBayesTree2;
|
||||
SymbolicFactorGraph::shared_ptr actualFactorGraph2;
|
||||
boost::tie(actualBayesTree2, actualFactorGraph2) =
|
||||
simpleTestGraph2.eliminatePartialMultifrontal(list_of<Key>(4)(5).convert_to_container<KeyVector >());
|
||||
simpleTestGraph2.eliminatePartialMultifrontal(
|
||||
list_of<Key>(4)(5).convert_to_container<KeyVector>());
|
||||
|
||||
EXPECT(assert_equal(expectedFactorGraph, *actualFactorGraph2));
|
||||
EXPECT(assert_equal(expectedBayesTree2, *actualBayesTree2));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicFactorGraph, marginalMultifrontalBayesNet)
|
||||
{
|
||||
SymbolicBayesNet expectedBayesNet = list_of
|
||||
(SymbolicConditional(0, 1, 2))
|
||||
(SymbolicConditional(1, 2, 3))
|
||||
(SymbolicConditional(2, 3))
|
||||
(SymbolicConditional(3));
|
||||
TEST(SymbolicFactorGraph, marginalMultifrontalBayesNet) {
|
||||
SymbolicBayesNet expectedBayesNet =
|
||||
list_of(SymbolicConditional(0, 1, 2))(SymbolicConditional(1, 2, 3))(
|
||||
SymbolicConditional(2, 3))(SymbolicConditional(3));
|
||||
|
||||
SymbolicBayesNet actual1 = *simpleTestGraph2.marginalMultifrontalBayesNet(
|
||||
Ordering(list_of(0)(1)(2)(3)));
|
||||
Ordering(list_of(0)(1)(2)(3)));
|
||||
EXPECT(assert_equal(expectedBayesNet, actual1));
|
||||
}
|
||||
|
||||
|
|
@ -167,104 +160,75 @@ TEST(SymbolicFactorGraph, eliminate_disconnected_graph) {
|
|||
|
||||
// create expected Chordal bayes Net
|
||||
SymbolicBayesNet expected;
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(0,1,2));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(1,2));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(0, 1, 2));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(1, 2));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(2));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(3,4));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(3, 4));
|
||||
expected.push_back(boost::make_shared<SymbolicConditional>(4));
|
||||
|
||||
Ordering order;
|
||||
order += 0,1,2,3,4;
|
||||
order += 0, 1, 2, 3, 4;
|
||||
SymbolicBayesNet actual = *fg.eliminateSequential(order);
|
||||
|
||||
EXPECT(assert_equal(expected,actual));
|
||||
EXPECT(assert_equal(expected, actual));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
//TEST(SymbolicFactorGraph, marginals)
|
||||
//{
|
||||
// // Create factor graph
|
||||
// SymbolicFactorGraph fg;
|
||||
// fg.push_factor(0, 1);
|
||||
// fg.push_factor(0, 2);
|
||||
// fg.push_factor(1, 4);
|
||||
// fg.push_factor(2, 4);
|
||||
// fg.push_factor(3, 4);
|
||||
//
|
||||
// // eliminate
|
||||
// SymbolicSequentialSolver solver(fg);
|
||||
// SymbolicBayesNet::shared_ptr actual = solver.eliminate();
|
||||
// SymbolicBayesNet expected;
|
||||
// expected.push_front(boost::make_shared<IndexConditional>(4));
|
||||
// expected.push_front(boost::make_shared<IndexConditional>(3, 4));
|
||||
// expected.push_front(boost::make_shared<IndexConditional>(2, 4));
|
||||
// expected.push_front(boost::make_shared<IndexConditional>(1, 2, 4));
|
||||
// expected.push_front(boost::make_shared<IndexConditional>(0, 1, 2));
|
||||
// EXPECT(assert_equal(expected,*actual));
|
||||
//
|
||||
// {
|
||||
// // jointBayesNet
|
||||
// vector<Index> js;
|
||||
// js.push_back(0);
|
||||
// js.push_back(4);
|
||||
// js.push_back(3);
|
||||
// SymbolicBayesNet::shared_ptr actualBN = solver.jointBayesNet(js);
|
||||
// SymbolicBayesNet expectedBN;
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(3));
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(4, 3));
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(0, 4));
|
||||
// EXPECT( assert_equal(expectedBN,*actualBN));
|
||||
//
|
||||
// // jointFactorGraph
|
||||
// SymbolicFactorGraph::shared_ptr actualFG = solver.jointFactorGraph(js);
|
||||
// SymbolicFactorGraph expectedFG;
|
||||
// expectedFG.push_factor(0, 4);
|
||||
// expectedFG.push_factor(4, 3);
|
||||
// expectedFG.push_factor(3);
|
||||
// EXPECT( assert_equal(expectedFG,(SymbolicFactorGraph)(*actualFG)));
|
||||
// }
|
||||
//
|
||||
// {
|
||||
// // jointBayesNet
|
||||
// vector<Index> js;
|
||||
// js.push_back(0);
|
||||
// js.push_back(2);
|
||||
// js.push_back(3);
|
||||
// SymbolicBayesNet::shared_ptr actualBN = solver.jointBayesNet(js);
|
||||
// SymbolicBayesNet expectedBN;
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(2));
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(3, 2));
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(0, 3, 2));
|
||||
// EXPECT( assert_equal(expectedBN,*actualBN));
|
||||
//
|
||||
// // jointFactorGraph
|
||||
// SymbolicFactorGraph::shared_ptr actualFG = solver.jointFactorGraph(js);
|
||||
// SymbolicFactorGraph expectedFG;
|
||||
// expectedFG.push_factor(0, 3, 2);
|
||||
// expectedFG.push_factor(3, 2);
|
||||
// expectedFG.push_factor(2);
|
||||
// EXPECT( assert_equal(expectedFG,(SymbolicFactorGraph)(*actualFG)));
|
||||
// }
|
||||
//
|
||||
// {
|
||||
// // conditionalBayesNet
|
||||
// vector<Index> js;
|
||||
// js.push_back(0);
|
||||
// js.push_back(2);
|
||||
// js.push_back(3);
|
||||
// size_t nrFrontals = 2;
|
||||
// SymbolicBayesNet::shared_ptr actualBN = //
|
||||
// solver.conditionalBayesNet(js, nrFrontals);
|
||||
// SymbolicBayesNet expectedBN;
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(2, 3));
|
||||
// expectedBN.push_front(boost::make_shared<IndexConditional>(0, 2, 3));
|
||||
// EXPECT( assert_equal(expectedBN,*actualBN));
|
||||
// }
|
||||
//}
|
||||
TEST(SymbolicFactorGraph, marginals) {
|
||||
// Create factor graph
|
||||
SymbolicFactorGraph fg;
|
||||
fg.push_factor(0, 1);
|
||||
fg.push_factor(0, 2);
|
||||
fg.push_factor(1, 4);
|
||||
fg.push_factor(2, 4);
|
||||
fg.push_factor(3, 4);
|
||||
|
||||
// eliminate
|
||||
Ordering ord(list_of(3)(4)(2)(1)(0));
|
||||
auto actual = fg.eliminateSequential(ord);
|
||||
SymbolicBayesNet expected;
|
||||
expected.emplace_shared<SymbolicConditional>(3, 4);
|
||||
expected.emplace_shared<SymbolicConditional>(4, 1, 2);
|
||||
expected.emplace_shared<SymbolicConditional>(2, 0, 1);
|
||||
expected.emplace_shared<SymbolicConditional>(1, 0);
|
||||
expected.emplace_shared<SymbolicConditional>(0);
|
||||
EXPECT(assert_equal(expected, *actual));
|
||||
|
||||
{
|
||||
// jointBayesNet
|
||||
Ordering ord(list_of(0)(4)(3));
|
||||
auto actual = fg.eliminatePartialSequential(ord);
|
||||
SymbolicBayesNet expectedBN;
|
||||
expectedBN.emplace_shared<SymbolicConditional>(0, 1, 2);
|
||||
expectedBN.emplace_shared<SymbolicConditional>(4, 1, 2, 3);
|
||||
expectedBN.emplace_shared<SymbolicConditional>(3, 1, 2);
|
||||
EXPECT(assert_equal(expectedBN, *(actual.first)));
|
||||
}
|
||||
|
||||
{
|
||||
// jointBayesNet
|
||||
Ordering ord(list_of(0)(2)(3));
|
||||
auto actual = fg.eliminatePartialSequential(ord);
|
||||
SymbolicBayesNet expectedBN;
|
||||
expectedBN.emplace_shared<SymbolicConditional>(0, 1, 2);
|
||||
expectedBN.emplace_shared<SymbolicConditional>(2, 1, 4);
|
||||
expectedBN.emplace_shared<SymbolicConditional>(3, 4);
|
||||
EXPECT(assert_equal(expectedBN, *(actual.first)));
|
||||
}
|
||||
|
||||
{
|
||||
// conditionalBayesNet
|
||||
Ordering ord(list_of(0)(2));
|
||||
auto actual = fg.eliminatePartialSequential(ord);
|
||||
SymbolicBayesNet expectedBN;
|
||||
expectedBN.emplace_shared<SymbolicConditional>(0, 1, 2);
|
||||
expectedBN.emplace_shared<SymbolicConditional>(2, 1, 4);
|
||||
EXPECT(assert_equal(expectedBN, *(actual.first)));
|
||||
}
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST( SymbolicFactorGraph, constructFromBayesNet )
|
||||
{
|
||||
TEST(SymbolicFactorGraph, constructFromBayesNet) {
|
||||
// create expected factor graph
|
||||
SymbolicFactorGraph expected;
|
||||
expected.push_factor(0, 1, 2);
|
||||
|
|
@ -284,8 +248,7 @@ TEST( SymbolicFactorGraph, constructFromBayesNet )
|
|||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST( SymbolicFactorGraph, constructFromBayesTree )
|
||||
{
|
||||
TEST(SymbolicFactorGraph, constructFromBayesTree) {
|
||||
// create expected factor graph
|
||||
SymbolicFactorGraph expected;
|
||||
expected.push_factor(_E_, _L_, _B_);
|
||||
|
|
@ -300,8 +263,7 @@ TEST( SymbolicFactorGraph, constructFromBayesTree )
|
|||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST( SymbolicFactorGraph, push_back )
|
||||
{
|
||||
TEST(SymbolicFactorGraph, push_back) {
|
||||
// Create two factor graphs and expected combined graph
|
||||
SymbolicFactorGraph fg1, fg2, expected;
|
||||
|
||||
|
|
@ -321,8 +283,47 @@ TEST( SymbolicFactorGraph, push_back )
|
|||
actual.push_back(fg1);
|
||||
actual.push_back(fg2);
|
||||
CHECK(assert_equal(expected, actual));
|
||||
|
||||
// combine in second way
|
||||
SymbolicFactorGraph actual2 = fg1;
|
||||
actual2.push_back(fg2);
|
||||
CHECK(assert_equal(expected, actual2));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
|
||||
TEST(SymbolicFactorGraph, add_factors) {
|
||||
SymbolicFactorGraph fg1;
|
||||
fg1.push_factor(10);
|
||||
fg1 += SymbolicFactor::shared_ptr(); // empty slot!
|
||||
fg1.push_factor(11);
|
||||
|
||||
SymbolicFactorGraph fg2;
|
||||
fg2.push_factor(1);
|
||||
fg2.push_factor(2);
|
||||
|
||||
SymbolicFactorGraph expected;
|
||||
expected.push_factor(10);
|
||||
expected.push_factor(1);
|
||||
expected.push_factor(11);
|
||||
expected.push_factor(2);
|
||||
const FactorIndices expectedIndices = list_of(1)(3);
|
||||
const FactorIndices actualIndices = fg1.add_factors(fg2, true);
|
||||
|
||||
EXPECT(assert_equal(expected, fg1));
|
||||
EXPECT(assert_container_equality(expectedIndices, actualIndices));
|
||||
|
||||
expected.push_factor(1);
|
||||
expected.push_factor(2);
|
||||
const FactorIndices expectedIndices2 = list_of(4)(5);
|
||||
const FactorIndices actualIndices2 = fg1.add_factors(fg2, false);
|
||||
|
||||
EXPECT(assert_equal(expected, fg1));
|
||||
EXPECT(assert_container_equality(expectedIndices2, actualIndices2));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
int main() {
|
||||
TestResult tr;
|
||||
return TestRegistry::runAllTests(tr);
|
||||
}
|
||||
/* ************************************************************************* */
|
||||
|
|
|
|||
Loading…
Reference in New Issue