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Fixed shortcuts after adding several more problematic testcases

release/4.3a0
Frank Dellaert 2012-09-17 00:29:03 +00:00
parent 34a9000134
commit cdf45105c2
5 changed files with 519 additions and 294 deletions
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8
.cproject
View File

@ -863,6 +863,14 @@
<useDefaultCommand>true</useDefaultCommand>
<runAllBuilders>true</runAllBuilders>
</target>
<target name="testSymbolicBayesTree.run" path="build/gtsam/inference" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
<buildCommand>make</buildCommand>
<buildArguments>-j1</buildArguments>
<buildTarget>testSymbolicBayesTree.run</buildTarget>
<stopOnError>true</stopOnError>
<useDefaultCommand>false</useDefaultCommand>
<runAllBuilders>true</runAllBuilders>
</target>
<target name="vSFMexample.run" path="build/examples/vSLAMexample" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
<buildCommand>make</buildCommand>
<buildArguments>-j2</buildArguments>

118
gtsam/discrete/tests/testDiscreteBayesTree.cpp
View File

@ -36,40 +36,6 @@ class Clique: public BayesTreeCliqueBase<Clique, DiscreteConditional> {
protected:
/// Calculate set S\B
vector<Index> separatorShortcutVariables(derived_ptr B) const {
sharedConditional p_F_S = this->conditional();
vector<Index> &indicesB = B->conditional()->keys();
vector<Index> S_setminus_B;
set_difference(p_F_S->beginParents(), p_F_S->endParents(), //
indicesB.begin(), indicesB.end(), back_inserter(S_setminus_B));
return S_setminus_B;
}
/**
* Determine variable indices to keep in recursive separator shortcut calculation
* The factor graph p_Cp_B has keys from the parent clique Cp and from B.
* But we only keep the variables not in S union B.
*/
vector<Index> indices(derived_ptr B,
const FactorGraph<FactorType>& p_Cp_B) const {
// We do this by first merging S and B
sharedConditional p_F_S = this->conditional();
vector<Index> &indicesB = B->conditional()->keys();
vector<Index> S_union_B;
set_union(p_F_S->beginParents(), p_F_S->endParents(), //
indicesB.begin(), indicesB.end(), back_inserter(S_union_B));
// then intersecting S_union_B with all keys in p_Cp_B
set<Index> allKeys = p_Cp_B.keys();
vector<Index> keepers;
set_intersection(S_union_B.begin(), S_union_B.end(), //
allKeys.begin(), allKeys.end(), back_inserter(keepers));
return keepers;
}
public:
typedef BayesTreeCliqueBase<Clique, DiscreteConditional> Base;
@ -102,88 +68,6 @@ public:
return result;
}
/**
* Separator shortcut function P(S||B) = P(S\B|B)
* where S is a clique separator, and B any node (e.g., a brancing in the tree)
* We can compute it recursively from the parent shortcut
* P(Sp||B) as \int P(Fp|Sp) P(Sp||B), where Fp are the frontal nodes in p
*/
FactorGraph<FactorType>::shared_ptr separatorShortcut(derived_ptr B) const {
typedef FactorGraph<FactorType> FG;
FG::shared_ptr p_S_B; //shortcut P(S||B) This is empty now
// We only calculate the shortcut when this clique is not B
// and when the S\B is not empty
vector<Index> S_setminus_B = separatorShortcutVariables(B);
if (B.get() != this && !S_setminus_B.empty()) {
// Obtain P(Fp|Sp) as a factor
derived_ptr parent(parent_.lock());
boost::shared_ptr<FactorType> p_Fp_Sp = parent->conditional()->toFactor();
// Obtain the parent shortcut P(Sp|B) as factors
// TODO: really annoying that we eliminate more than we have to !
// TODO: we should only eliminate C_p\B, with S\B variables last
// TODO: and this index dance will be easier then, as well
FG p_Sp_B(parent->shortcut(B, &EliminateDiscrete));
// now combine P(Cp||B) = P(Fp|Sp) * P(Sp||B)
boost::shared_ptr<FG> p_Cp_B(new FG);
p_Cp_B->push_back(p_Fp_Sp);
p_Cp_B->push_back(p_Sp_B);
// Figure out how many variables there are in in the shortcut
// size_t nVariables = *max_element(S_setminus_B.begin(),S_setminus_B.end());
// cout << "nVariables: " << nVariables << endl;
// VariableIndex::shared_ptr structure(new VariableIndex(*p_Cp_B));
// GTSAM_PRINT(*p_Cp_B);
// GTSAM_PRINT(*structure);
// Create a generic solver that will marginalize for us
GenericSequentialSolver<FactorType> solver(*p_Cp_B);
// The factor graph above will have keys from the parent clique Cp and from B.
// But we only keep the variables not in S union B.
vector<Index> keepers = indices(B, *p_Cp_B);
p_S_B = solver.jointFactorGraph(keepers, &EliminateDiscrete);
}
// return the shortcut P(S||B)
return p_S_B;
}
/**
* The shortcut density is a conditional P(S||B) of the separator of this
* clique on the clique B.
*/
BayesNet<DiscreteConditional> shortcut(derived_ptr B,
Eliminate function) const {
//Check if the ShortCut already exists
if (cachedShortcut_) {
return *cachedShortcut_; // return the cached version
} else {
BayesNet<DiscreteConditional> bn;
FactorGraph<FactorType>::shared_ptr fg = separatorShortcut(B);
if (fg) {
// calculate set S\B of indices to keep in Bayes net
vector<Index> S_setminus_B = separatorShortcutVariables(B);
set<Index> keep(S_setminus_B.begin(), S_setminus_B.end());
BOOST_FOREACH (FactorType::shared_ptr factor,*fg) {
DecisionTreeFactor::shared_ptr df = boost::dynamic_pointer_cast<
DecisionTreeFactor>(factor);
if (keep.count(*factor->begin()))
bn.push_front(boost::make_shared<DiscreteConditional>(1, *df));
}
}
cachedShortcut_ = bn;
return bn;
}
}
};
typedef BayesTree<DiscreteConditional, Clique> DiscreteBayesTree;
@ -196,7 +80,7 @@ double evaluate(const DiscreteBayesTree& tree,
/* ************************************************************************* */
TEST_UNSAFE( DiscreteMarginals, thinTree ) {
TEST_UNSAFE( DiscreteBayesTree, thinTree ) {
const int nrNodes = 15;
const size_t nrStates = 2;

257
gtsam/inference/BayesTreeCliqueBase-inl.h
View File

@ -22,7 +22,7 @@ namespace gtsam {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED,CONDITIONAL>::assertInvariants() const {
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::assertInvariants() const {
#ifndef NDEBUG
// We rely on the keys being sorted
// FastVector<Index> sortedUniqueKeys(conditional_->begin(), conditional_->end());
@ -35,27 +35,71 @@ namespace gtsam {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
BayesTreeCliqueBase<DERIVED,CONDITIONAL>::BayesTreeCliqueBase(const sharedConditional& conditional) :
conditional_(conditional) {
std::vector<Index> BayesTreeCliqueBase<DERIVED, CONDITIONAL>::separator_setminus_B(
derived_ptr B) const {
sharedConditional p_F_S = this->conditional();
std::vector<Index> &indicesB = B->conditional()->keys();
std::vector<Index> S_setminus_B;
std::set_difference(p_F_S->beginParents(), p_F_S->endParents(), //
indicesB.begin(), indicesB.end(), back_inserter(S_setminus_B));
return S_setminus_B;
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
std::vector<Index> BayesTreeCliqueBase<DERIVED, CONDITIONAL>::shortcut_indices(
derived_ptr B, const FactorGraph<FactorType>& p_Cp_B) const {
std::set<Index> allKeys = p_Cp_B.keys();
std::vector<Index> &indicesB = B->conditional()->keys();
std::vector<Index> keep;
#ifdef OLD_INDICES
// We do this by first merging S and B
sharedConditional p_F_S = this->conditional();
std::vector<Index> S_union_B;
std::set_union(p_F_S->beginParents(), p_F_S->endParents(),//
indicesB.begin(), indicesB.end(), back_inserter(S_union_B));
// then intersecting S_union_B with all keys in p_Cp_B
std::set_intersection(S_union_B.begin(), S_union_B.end(),//
allKeys.begin(), allKeys.end(), back_inserter(keep));
#else
std::vector<Index> S_setminus_B = separator_setminus_B(B); // TODO, get as argument?
std::set_intersection(S_setminus_B.begin(), S_setminus_B.end(), //
allKeys.begin(), allKeys.end(), back_inserter(keep));
std::set_intersection(indicesB.begin(), indicesB.end(), //
allKeys.begin(), allKeys.end(), back_inserter(keep));
#endif
// BOOST_FOREACH(Index j, keep) std::cout << j << " "; std::cout << std::endl;
return keep;
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
BayesTreeCliqueBase<DERIVED, CONDITIONAL>::BayesTreeCliqueBase(
const sharedConditional& conditional) :
conditional_(conditional) {
assertInvariants();
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
BayesTreeCliqueBase<DERIVED,CONDITIONAL>::BayesTreeCliqueBase(const std::pair<sharedConditional, boost::shared_ptr<typename ConditionalType::FactorType> >& result) :
conditional_(result.first) {
BayesTreeCliqueBase<DERIVED, CONDITIONAL>::BayesTreeCliqueBase(
const std::pair<sharedConditional,
boost::shared_ptr<typename ConditionalType::FactorType> >& result) :
conditional_(result.first) {
assertInvariants();
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED,CONDITIONAL>::print(const std::string& s, const IndexFormatter& indexFormatter) const {
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::print(const std::string& s,
const IndexFormatter& indexFormatter) const {
conditional_->print(s, indexFormatter);
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
size_t BayesTreeCliqueBase<DERIVED,CONDITIONAL>::treeSize() const {
size_t BayesTreeCliqueBase<DERIVED, CONDITIONAL>::treeSize() const {
size_t size = 1;
BOOST_FOREACH(const derived_ptr& child, children_)
size += child->treeSize();
@ -64,15 +108,17 @@ namespace gtsam {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED,CONDITIONAL>::printTree(const std::string& indent, const IndexFormatter& indexFormatter) const {
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::printTree(
const std::string& indent, const IndexFormatter& indexFormatter) const {
asDerived(this)->print(indent, indexFormatter);
BOOST_FOREACH(const derived_ptr& child, children_)
child->printTree(indent+" ", indexFormatter);
child->printTree(indent + " ", indexFormatter);
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED,CONDITIONAL>::permuteWithInverse(const Permutation& inversePermutation) {
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::permuteWithInverse(
const Permutation& inversePermutation) {
conditional_->permuteWithInverse(inversePermutation);
BOOST_FOREACH(const derived_ptr& child, children_) {
child->permuteWithInverse(inversePermutation);
@ -82,19 +128,21 @@ namespace gtsam {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
bool BayesTreeCliqueBase<DERIVED,CONDITIONAL>::permuteSeparatorWithInverse(const Permutation& inversePermutation) {
bool changed = conditional_->permuteSeparatorWithInverse(inversePermutation);
bool BayesTreeCliqueBase<DERIVED, CONDITIONAL>::permuteSeparatorWithInverse(
const Permutation& inversePermutation) {
bool changed = conditional_->permuteSeparatorWithInverse(
inversePermutation);
#ifndef NDEBUG
if(!changed) {
BOOST_FOREACH(Index& separatorKey, conditional_->parents()) { assert(separatorKey == inversePermutation[separatorKey]); }
BOOST_FOREACH(Index& separatorKey, conditional_->parents()) {assert(separatorKey == inversePermutation[separatorKey]);}
BOOST_FOREACH(const derived_ptr& child, children_) {
assert(child->permuteSeparatorWithInverse(inversePermutation) == false);
}
}
#endif
if(changed) {
if (changed) {
BOOST_FOREACH(const derived_ptr& child, children_) {
(void)child->permuteSeparatorWithInverse(inversePermutation);
(void) child->permuteSeparatorWithInverse(inversePermutation);
}
}
assertInvariants();
@ -108,105 +156,47 @@ namespace gtsam {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
BayesNet<CONDITIONAL> BayesTreeCliqueBase<DERIVED, CONDITIONAL>::shortcut(
derived_ptr R, Eliminate function) const{
derived_ptr B, Eliminate function) const {
static const bool debug = false;
// Check if the ShortCut already exists
if (!cachedShortcut_) {
BayesNet<ConditionalType> p_S_R; //shortcut P(S|R) This is empty now
// We only calculate the shortcut when this clique is not B
// and when the S\B is not empty
std::vector<Index> S_setminus_B = separator_setminus_B(B);
if (B.get() != this && !S_setminus_B.empty()) {
//Check if the ShortCut already exists
if(!cachedShortcut_){
// Obtain P(Cp||B) = P(Fp|Sp) * P(Sp||B) as a factor graph
derived_ptr parent(parent_.lock());
FactorGraph<FactorType> p_Cp_B(parent->shortcut(B, function)); // P(Sp||B)
p_Cp_B.push_back(parent->conditional()->toFactor()); // P(Fp|Sp)
// A first base case is when this clique or its parent is the root,
// in which case we return an empty Bayes net.
// Add the root conditional
// TODO: this is needed because otherwise we will be solving singular
// systems and exceptions are thrown. However, we should be able to omit
// this if we can get ATTEMPT_AT_NOT_ELIMINATING_ALL in
// GenericSequentialSolver.* working...
p_Cp_B.push_back(B->conditional()->toFactor()); // P(B)
derived_ptr parent(parent_.lock());
if (R.get() != this && parent != R) {
// Create solver that will marginalize for us
GenericSequentialSolver<FactorType> solver(p_Cp_B);
// The root conditional
FactorGraph<FactorType> p_R(BayesNet<ConditionalType>(R->conditional()));
// Determine the variables we want to keep
std::vector<Index> keep = shortcut_indices(B, p_Cp_B);
// The parent clique has a ConditionalType for each frontal node in Fp
// so we can obtain P(Fp|Sp) in factor graph form
FactorGraph<FactorType> p_Fp_Sp(BayesNet<ConditionalType>(parent->conditional()));
// Finally, we only want to have S\B variables in the Bayes net, so
size_t nrFrontals = S_setminus_B.size();
cachedShortcut_ = //
*solver.conditionalBayesNet(keep, nrFrontals, function);
assertInvariants();
} else {
BayesNet<CONDITIONAL> empty;
cachedShortcut_ = empty;
}
}
// If not the base case, obtain the parent shortcut P(Sp|R) as factors
FactorGraph<FactorType> p_Sp_R(parent->shortcut(R, function));
// now combine P(Cp|R) = P(Fp|Sp) * P(Sp|R)
FactorGraph<FactorType> p_Cp_R;
p_Cp_R.push_back(p_R);
p_Cp_R.push_back(p_Fp_Sp);
p_Cp_R.push_back(p_Sp_R);
// Eliminate into a Bayes net with ordering designed to integrate out
// any variables not in *our* separator. Variables to integrate out must be
// eliminated first hence the desired ordering is [Cp\S S].
// However, an added wrinkle is that Cp might overlap with the root.
// Keys corresponding to the root should not be added to the ordering at all.
if(debug) {
p_R.print("p_R: ");
p_Fp_Sp.print("p_Fp_Sp: ");
p_Sp_R.print("p_Sp_R: ");
}
// We want to factor into a conditional of the clique variables given the
// root and the marginal on the root, integrating out all other variables.
// The integrands include any parents of this clique and the variables of
// the parent clique.
FastSet<Index> variablesAtBack;
FastSet<Index> separator;
size_t uniqueRootVariables = 0;
BOOST_FOREACH(const Index separatorIndex, this->conditional()->parents()) {
variablesAtBack.insert(separatorIndex);
separator.insert(separatorIndex);
if(debug) std::cout << "At back (this): " << separatorIndex << std::endl;
}
BOOST_FOREACH(const Index key, R->conditional()->keys()) {
if(variablesAtBack.insert(key).second)
++ uniqueRootVariables;
if(debug) std::cout << "At back (root): " << key << std::endl;
}
Permutation toBack = Permutation::PushToBack(
std::vector<Index>(variablesAtBack.begin(), variablesAtBack.end()),
R->conditional()->lastFrontalKey() + 1);
Permutation::shared_ptr toBackInverse(toBack.inverse());
BOOST_FOREACH(const typename FactorType::shared_ptr& factor, p_Cp_R) {
factor->permuteWithInverse(*toBackInverse); }
typename BayesNet<ConditionalType>::shared_ptr eliminated(EliminationTree<
FactorType>::Create(p_Cp_R)->eliminate(function));
// Take only the conditionals for p(S|R). We check for each variable being
// in the separator set because if some separator variables overlap with
// root variables, we cannot rely on the number of root variables, and also
// want to include those variables in the conditional.
BOOST_REVERSE_FOREACH(typename ConditionalType::shared_ptr conditional, *eliminated) {
assert(conditional->nrFrontals() == 1);
if(separator.find(toBack[conditional->firstFrontalKey()]) != separator.end()) {
if(debug)
conditional->print("Taking C|R conditional: ");
p_S_R.push_front(conditional);
}
if(p_S_R.size() == separator.size())
break;
}
// Undo the permutation
if(debug) toBack.print("toBack: ");
p_S_R.permuteWithInverse(toBack);
}
cachedShortcut_ = p_S_R;
}
else
p_S_R = *cachedShortcut_; // return the cached version
assertInvariants();
// return the shortcut P(S|R)
return p_S_R;
// return the shortcut P(S||B)
return *cachedShortcut_; // return the cached version
}
/* ************************************************************************* */
@ -216,12 +206,13 @@ namespace gtsam {
// Because the root clique could be very big.
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
FactorGraph<typename BayesTreeCliqueBase<DERIVED,CONDITIONAL>::FactorType> BayesTreeCliqueBase<DERIVED,CONDITIONAL>::marginal(
derived_ptr R, Eliminate function) const{
FactorGraph<typename BayesTreeCliqueBase<DERIVED, CONDITIONAL>::FactorType> BayesTreeCliqueBase<
DERIVED, CONDITIONAL>::marginal(derived_ptr R, Eliminate function) const {
// If we are the root, just return this root
// NOTE: immediately cast to a factor graph
BayesNet<ConditionalType> bn(R->conditional());
if (R.get()==this) return bn;
if (R.get() == this)
return bn;
// Combine P(F|S), P(S|R), and P(R)
BayesNet<ConditionalType> p_FSR = this->shortcut(R, function);
@ -237,16 +228,21 @@ namespace gtsam {
// P(C1,C2) = \int_R P(F1|S1) P(S1|R) P(F2|S1) P(S2|R) P(R)
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
FactorGraph<typename BayesTreeCliqueBase<DERIVED,CONDITIONAL>::FactorType> BayesTreeCliqueBase<DERIVED,CONDITIONAL>::joint(
derived_ptr C2, derived_ptr R, Eliminate function) const {
FactorGraph<typename BayesTreeCliqueBase<DERIVED, CONDITIONAL>::FactorType> BayesTreeCliqueBase<
DERIVED, CONDITIONAL>::joint(derived_ptr C2, derived_ptr R,
Eliminate function) const {
// For now, assume neither is the root
// Combine P(F1|S1), P(S1|R), P(F2|S2), P(S2|R), and P(R)
FactorGraph<FactorType> joint;
if (!isRoot()) joint.push_back(this->conditional()->toFactor()); // P(F1|S1)
if (!isRoot()) joint.push_back(shortcut(R, function)); // P(S1|R)
if (!C2->isRoot()) joint.push_back(C2->conditional()->toFactor()); // P(F2|S2)
if (!C2->isRoot()) joint.push_back(C2->shortcut(R, function)); // P(S2|R)
if (!isRoot())
joint.push_back(this->conditional()->toFactor()); // P(F1|S1)
if (!isRoot())
joint.push_back(shortcut(R, function)); // P(S1|R)
if (!C2->isRoot())
joint.push_back(C2->conditional()->toFactor()); // P(F2|S2)
if (!C2->isRoot())
joint.push_back(C2->shortcut(R, function)); // P(S2|R)
joint.push_back(R->conditional()->toFactor()); // P(R)
// Find the keys of both C1 and C2
@ -257,29 +253,30 @@ namespace gtsam {
keys12.insert(keys2.begin(), keys2.end());
// Calculate the marginal
std::vector<Index> keys12vector; keys12vector.reserve(keys12.size());
std::vector<Index> keys12vector;
keys12vector.reserve(keys12.size());
keys12vector.insert(keys12vector.begin(), keys12.begin(), keys12.end());
assertInvariants();
GenericSequentialSolver<FactorType> solver(joint);
return *solver.jointFactorGraph(keys12vector, function);
}
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::deleteCachedShorcuts() {
/* ************************************************************************* */
template<class DERIVED, class CONDITIONAL>
void BayesTreeCliqueBase<DERIVED, CONDITIONAL>::deleteCachedShorcuts() {
// When a shortcut is requested, all of the shortcuts between it and the
// root are also generated. So, if this clique's cached shortcut is set,
// recursively call over all child cliques. Otherwise, it is unnecessary.
if(cachedShortcut_) {
BOOST_FOREACH(derived_ptr& child, children_) {
child->deleteCachedShorcuts();
}
// When a shortcut is requested, all of the shortcuts between it and the
// root are also generated. So, if this clique's cached shortcut is set,
// recursively call over all child cliques. Otherwise, it is unnecessary.
if (cachedShortcut_) {
BOOST_FOREACH(derived_ptr& child, children_) {
child->deleteCachedShorcuts();
}
//Delete CachedShortcut for this clique
this->resetCachedShortcut();
}
//Delete CachedShortcut for this clique
this->resetCachedShortcut();
}
}
}
}

152
gtsam/inference/BayesTreeCliqueBase.h
View File

@ -25,7 +25,9 @@
#include <gtsam/inference/FactorGraph.h>
#include <gtsam/inference/BayesNet.h>
namespace gtsam { template<class CONDITIONAL, class CLIQUE> class BayesTree; }
namespace gtsam {
template<class CONDITIONAL, class CLIQUE> class BayesTree;
}
namespace gtsam {
@ -48,7 +50,7 @@ namespace gtsam {
struct BayesTreeCliqueBase {
public:
typedef BayesTreeCliqueBase<DERIVED,CONDITIONAL> This;
typedef BayesTreeCliqueBase<DERIVED, CONDITIONAL> This;
typedef DERIVED DerivedType;
typedef CONDITIONAL ConditionalType;
typedef boost::shared_ptr<ConditionalType> sharedConditional;
@ -61,19 +63,22 @@ namespace gtsam {
protected:
/// @name Standard Constructors
/// @{
/// @name Standard Constructors
/// @{
/** Default constructor */
BayesTreeCliqueBase() {}
BayesTreeCliqueBase() {
}
/** Construct from a conditional, leaving parent and child pointers uninitialized */
BayesTreeCliqueBase(const sharedConditional& conditional);
/** Construct from an elimination result, which is a pair<CONDITIONAL,FACTOR> */
BayesTreeCliqueBase(const std::pair<sharedConditional, boost::shared_ptr<typename ConditionalType::FactorType> >& result);
BayesTreeCliqueBase(
const std::pair<sharedConditional,
boost::shared_ptr<typename ConditionalType::FactorType> >& result);
/// @}
/// @}
/// This stores the Cached Shortcut value
mutable boost::optional<BayesNet<ConditionalType> > cachedShortcut_;
@ -83,67 +88,91 @@ namespace gtsam {
derived_weak_ptr parent_;
std::list<derived_ptr> children_;
/// @name Testable
/// @{
/// @name Testable
/// @{
/** check equality */
bool equals(const This& other, double tol=1e-9) const {
return (!conditional_ && !other.conditional()) ||
conditional_->equals(*other.conditional(), tol);
bool equals(const This& other, double tol = 1e-9) const {
return (!conditional_ && !other.conditional())
|| conditional_->equals(*other.conditional(), tol);
}
/** print this node */
void print(const std::string& s = "", const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const;
void print(const std::string& s = "", const IndexFormatter& indexFormatter =
DefaultIndexFormatter) const;
/** print this node and entire subtree below it */
void printTree(const std::string& indent="", const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const;
void printTree(const std::string& indent = "",
const IndexFormatter& indexFormatter = DefaultIndexFormatter) const;
/// @}
/// @name Standard Interface
/// @{
/// @}
/// @name Standard Interface
/// @{
/** Access the conditional */
const sharedConditional& conditional() const { return conditional_; }
const sharedConditional& conditional() const {
return conditional_;
}
/** is this the root of a Bayes tree ? */
inline bool isRoot() const { return parent_.expired(); }
inline bool isRoot() const {
return parent_.expired();
}
/** The size of subtree rooted at this clique, i.e., nr of Cliques */
size_t treeSize() const;
/** The arrow operator accesses the conditional */
const ConditionalType* operator->() const { return conditional_.get(); }
const ConditionalType* operator->() const {
return conditional_.get();
}
/** return the const reference of children */
const std::list<derived_ptr>& children() const { return children_; }
const std::list<derived_ptr>& children() const {
return children_;
}
/** return a shared_ptr to the parent clique */
derived_ptr parent() const { return parent_.lock(); }
derived_ptr parent() const {
return parent_.lock();
}
/// @}
/// @name Advanced Interface
/// @{
/// @}
/// @name Advanced Interface
/// @{
/** The arrow operator accesses the conditional */
ConditionalType* operator->() { return conditional_.get(); }
ConditionalType* operator->() {
return conditional_.get();
}
/** return the reference of children non-const version*/
std::list<derived_ptr>& children() { return children_; }
std::list<derived_ptr>& children() {
return children_;
}
/** Construct shared_ptr from a conditional, leaving parent and child pointers uninitialized */
static derived_ptr Create(const sharedConditional& conditional) { return boost::make_shared<DerivedType>(conditional); }
static derived_ptr Create(const sharedConditional& conditional) {
return boost::make_shared<DerivedType>(conditional);
}
/** Construct shared_ptr from a FactorGraph<FACTOR>::EliminationResult. In this class
* the conditional part is kept and the factor part is ignored, but in derived clique
* types, such as ISAM2Clique, the factor part is kept as a cached factor.
* @param result An elimination result, which is a pair<CONDITIONAL,FACTOR>
*/
static derived_ptr Create(const std::pair<sharedConditional, boost::shared_ptr<typename ConditionalType::FactorType> >& result) { return boost::make_shared<DerivedType>(result); }
static derived_ptr Create(
const std::pair<sharedConditional,
boost::shared_ptr<typename ConditionalType::FactorType> >& result) {
return boost::make_shared<DerivedType>(result);
}
/** Returns a new clique containing a copy of the conditional but without
* the parent and child clique pointers.
*/
derived_ptr clone() const { return Create(sharedConditional(new ConditionalType(*conditional_))); }
/** Returns a new clique containing a copy of the conditional but without
* the parent and child clique pointers.
*/
derived_ptr clone() const {
return Create(sharedConditional(new ConditionalType(*conditional_)));
}
/** Permute the variables in the whole subtree rooted at this clique */
void permuteWithInverse(const Permutation& inversePermutation);
@ -156,13 +185,16 @@ namespace gtsam {
bool permuteSeparatorWithInverse(const Permutation& inversePermutation);
/** return the conditional P(S|Root) on the separator given the root */
BayesNet<ConditionalType> shortcut(derived_ptr root, Eliminate function) const;
BayesNet<ConditionalType> shortcut(derived_ptr root,
Eliminate function) const;
/** return the marginal P(C) of the clique */
FactorGraph<FactorType> marginal(derived_ptr root, Eliminate function) const;
FactorGraph<FactorType> marginal(derived_ptr root,
Eliminate function) const;
/** return the joint P(C1,C2), where C1==this. TODO: not a method? */
FactorGraph<FactorType> joint(derived_ptr C2, derived_ptr root, Eliminate function) const;
FactorGraph<FactorType> joint(derived_ptr C2, derived_ptr root,
Eliminate function) const;
/**
* This deletes the cached shortcuts of all cliques (subtree) below this clique.
@ -171,29 +203,53 @@ namespace gtsam {
void deleteCachedShorcuts();
/** return cached shortcut of the clique */
const boost::optional<BayesNet<ConditionalType> > cachedShortcut() const { return cachedShortcut_; }
const boost::optional<BayesNet<ConditionalType> > cachedShortcut() const {
return cachedShortcut_;
}
friend class BayesTree<ConditionalType, DerivedType>;
friend class BayesTree<ConditionalType, DerivedType> ;
protected:
///TODO: comment
/// assert invariants that have to hold in a clique
void assertInvariants() const;
/// Calculate set \f$ S \setminus B \f$ for shortcut calculations
std::vector<Index> separator_setminus_B(derived_ptr B) const;
/// Calculate set \f$ S_p \cap B \f$ for shortcut calculations
std::vector<Index> parent_separator_intersection_B(derived_ptr B) const;
/**
* Determine variable indices to keep in recursive separator shortcut calculation
* The factor graph p_Cp_B has keys from the parent clique Cp and from B.
* But we only keep the variables not in S union B.
*/
std::vector<Index> shortcut_indices(derived_ptr B,
const FactorGraph<FactorType>& p_Cp_B) const;
/// Reset the computed shortcut of this clique. Used by friend BayesTree
void resetCachedShortcut() { cachedShortcut_ = boost::none; }
void resetCachedShortcut() {
cachedShortcut_ = boost::none;
}
private:
/** Cliques cannot be copied except by the clone() method, which does not
/**
* Cliques cannot be copied except by the clone() method, which does not
* copy the parent and child pointers.
*/
BayesTreeCliqueBase(const This& other) { assert(false); }
BayesTreeCliqueBase(const This& other) {
assert(false);
}
/** Cliques cannot be copied except by the clone() method, which does not
* copy the parent and child pointers.
*/
This& operator=(const This& other) { assert(false); return *this; }
This& operator=(const This& other) {
assert(false);
return *this;
}
/** Serialization function */
friend class boost::serialization::access;
@ -204,17 +260,19 @@ namespace gtsam {
ar & BOOST_SERIALIZATION_NVP(children_);
}
/// @}
/// @}
}; // \struct Clique
};
// \struct Clique
template<class DERIVED, class CONDITIONAL>
const DERIVED* asDerived(const BayesTreeCliqueBase<DERIVED,CONDITIONAL>* base) {
const DERIVED* asDerived(
const BayesTreeCliqueBase<DERIVED, CONDITIONAL>* base) {
return static_cast<const DERIVED*>(base);
}
template<class DERIVED, class CONDITIONAL>
DERIVED* asDerived(BayesTreeCliqueBase<DERIVED,CONDITIONAL>* base) {
DERIVED* asDerived(BayesTreeCliqueBase<DERIVED, CONDITIONAL>* base) {
return static_cast<DERIVED*>(base);
}

278
gtsam/inference/tests/testSymbolicBayesTree.cpp Normal file
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@ -0,0 +1,278 @@
/* ----------------------------------------------------------------------------
* 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 testSymbolicBayesTree.cpp
* @date sept 15, 2012
* @author Frank Dellaert
*/
#include <gtsam/inference/SymbolicSequentialSolver.h>
#include <gtsam/inference/SymbolicFactorGraph.h>
#include <gtsam/inference/BayesTree.h>
#include <boost/assign/list_of.hpp>
#include <boost/assign/std/vector.hpp>
using namespace boost::assign;
#include <CppUnitLite/TestHarness.h>
using namespace std;
using namespace gtsam;
static bool debug = false;
typedef BayesNet<IndexConditional> SymbolicBayesNet;
typedef BayesTree<IndexConditional> SymbolicBayesTree;
/* ************************************************************************* */
TEST_UNSAFE( SymbolicBayesTree, thinTree ) {
// create a thin-tree Bayesnet, a la Jean-Guillaume
SymbolicBayesNet bayesNet;
bayesNet.push_front(boost::make_shared<IndexConditional>(14));
bayesNet.push_front(boost::make_shared<IndexConditional>(13, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(12, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(11, 13, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(10, 13, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(9, 12, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(8, 12, 14));
bayesNet.push_front(boost::make_shared<IndexConditional>(7, 11, 13));
bayesNet.push_front(boost::make_shared<IndexConditional>(6, 11, 13));
bayesNet.push_front(boost::make_shared<IndexConditional>(5, 10, 13));
bayesNet.push_front(boost::make_shared<IndexConditional>(4, 10, 13));
bayesNet.push_front(boost::make_shared<IndexConditional>(3, 9, 12));
bayesNet.push_front(boost::make_shared<IndexConditional>(2, 9, 12));
bayesNet.push_front(boost::make_shared<IndexConditional>(1, 8, 12));
bayesNet.push_front(boost::make_shared<IndexConditional>(0, 8, 12));
if (debug) {
GTSAM_PRINT(bayesNet);
bayesNet.saveGraph("/tmp/symbolicBayesNet.dot");
}
// create a BayesTree out of a Bayes net
SymbolicBayesTree bayesTree(bayesNet);
if (debug) {
GTSAM_PRINT(bayesTree);
bayesTree.saveGraph("/tmp/symbolicBayesTree.dot");
}
SymbolicBayesTree::Clique::shared_ptr R = bayesTree.root();
{
// check shortcut P(S9||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[9];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
EXPECT(assert_equal(expected, shortcut));
}
{
// check shortcut P(S8||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[8];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(12, 14));
EXPECT(assert_equal(expected, shortcut));
}
{
// check shortcut P(S4||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[4];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(10, 13, 14));
EXPECT(assert_equal(expected, shortcut));
}
{
// check shortcut P(S0||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[0];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(12, 14));
expected.push_front(boost::make_shared<IndexConditional>(8, 12, 14));
EXPECT(assert_equal(expected, shortcut));
}
}
/* ************************************************************************* *
Bayes tree for smoother with "natural" ordering:
C1 5 6
C2 4 : 5
C3 3 : 4
C4 2 : 3
C5 1 : 2
C6 0 : 1
**************************************************************************** */
TEST_UNSAFE( SymbolicBayesTree, linear_smoother_shortcuts ) {
// Create smoother with 7 nodes
SymbolicFactorGraph smoother;
smoother.push_factor(0);
smoother.push_factor(0, 1);
smoother.push_factor(1, 2);
smoother.push_factor(2, 3);
smoother.push_factor(3, 4);
smoother.push_factor(4, 5);
smoother.push_factor(5, 6);
BayesNet<IndexConditional> bayesNet =
*SymbolicSequentialSolver(smoother).eliminate();
if (debug) {
GTSAM_PRINT(bayesNet);
bayesNet.saveGraph("/tmp/symbolicBayesNet.dot");
}
// create a BayesTree out of a Bayes net
SymbolicBayesTree bayesTree(bayesNet);
if (debug) {
GTSAM_PRINT(bayesTree);
bayesTree.saveGraph("/tmp/symbolicBayesTree.dot");
}
SymbolicBayesTree::Clique::shared_ptr R = bayesTree.root();
{
// check shortcut P(S2||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[4]; // 4 is frontal in C2
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
EXPECT(assert_equal(expected, shortcut));
}
{
// check shortcut P(S3||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[3]; // 3 is frontal in C3
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(4, 5));
EXPECT(assert_equal(expected, shortcut));
}
{
// check shortcut P(S4||R) to root
SymbolicBayesTree::Clique::shared_ptr c = bayesTree[2]; // 2 is frontal in C4
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(3, 5));
EXPECT(assert_equal(expected, shortcut));
}
}
/* ************************************************************************* */
// from testSymbolicJunctionTree, which failed at one point
TEST(SymbolicBayesTree, complicatedMarginal) {
// Create the conditionals to go in the BayesTree
list<Index> L;
L = list_of(1)(2)(5);
IndexConditional::shared_ptr R_1_2(new IndexConditional(L, 2));
L = list_of(3)(4)(6);
IndexConditional::shared_ptr R_3_4(new IndexConditional(L, 2));
L = list_of(5)(6)(7)(8);
IndexConditional::shared_ptr R_5_6(new IndexConditional(L, 2));
L = list_of(7)(8)(11);
IndexConditional::shared_ptr R_7_8(new IndexConditional(L, 2));
L = list_of(9)(10)(11)(12);
IndexConditional::shared_ptr R_9_10(new IndexConditional(L, 2));
L = list_of(11)(12);
IndexConditional::shared_ptr R_11_12(new IndexConditional(L, 2));
// Symbolic Bayes Tree
typedef SymbolicBayesTree::Clique Clique;
typedef SymbolicBayesTree::sharedClique sharedClique;
// Create Bayes Tree
SymbolicBayesTree bt;
bt.insert(sharedClique(new Clique(R_11_12)));
bt.insert(sharedClique(new Clique(R_9_10)));
bt.insert(sharedClique(new Clique(R_7_8)));
bt.insert(sharedClique(new Clique(R_5_6)));
bt.insert(sharedClique(new Clique(R_3_4)));
bt.insert(sharedClique(new Clique(R_1_2)));
if (debug) {
GTSAM_PRINT(bt);
bt.saveGraph("/tmp/symbolicBayesTree.dot");
}
SymbolicBayesTree::Clique::shared_ptr R = bt.root();
SymbolicBayesNet empty;
// Shortcut on 9
{
SymbolicBayesTree::Clique::shared_ptr c = bt[9];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
EXPECT(assert_equal(empty, shortcut));
}
// Shortcut on 7
{
SymbolicBayesTree::Clique::shared_ptr c = bt[7];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
EXPECT(assert_equal(empty, shortcut));
}
// Shortcut on 5
{
SymbolicBayesTree::Clique::shared_ptr c = bt[5];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(8, 11));
expected.push_front(boost::make_shared<IndexConditional>(7, 8, 11));
EXPECT(assert_equal(expected, shortcut));
}
// Shortcut on 3
{
SymbolicBayesTree::Clique::shared_ptr c = bt[3];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(6, 11));
EXPECT(assert_equal(expected, shortcut));
}
// Shortcut on 1
{
SymbolicBayesTree::Clique::shared_ptr c = bt[1];
SymbolicBayesNet shortcut = c->shortcut(R, EliminateSymbolic);
SymbolicBayesNet expected;
expected.push_front(boost::make_shared<IndexConditional>(5, 11));
EXPECT(assert_equal(expected, shortcut));
}
// Marginal on 5
{
IndexFactor::shared_ptr actual = bt.marginalFactor(5, EliminateSymbolic);
EXPECT(assert_equal(IndexFactor(5), *actual, 1e-1));
}
// Shortcut on 6
{
IndexFactor::shared_ptr actual = bt.marginalFactor(6, EliminateSymbolic);
EXPECT(assert_equal(IndexFactor(6), *actual, 1e-1));
}
}
/* ************************************************************************* */
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */