Added BayesNet::popLeaf
Richard Roberts
parent
8fe0f6a501
commit
f19c9c2da4
|
|
@ -49,6 +49,24 @@ namespace gtsam {
|
|||
return equal(conditionals_.begin(),conditionals_.end(),cbn.conditionals_.begin(),equals_star<CONDITIONAL>(tol));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
template<class CONDITIONAL>
|
||||
typename BayesNet<CONDITIONAL>::const_iterator BayesNet<CONDITIONAL>::find(Index key) const {
|
||||
for(const_iterator it = begin(); it != end(); ++it)
|
||||
if(std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) != (*it)->endFrontals())
|
||||
return it;
|
||||
return end();
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
template<class CONDITIONAL>
|
||||
typename BayesNet<CONDITIONAL>::iterator BayesNet<CONDITIONAL>::find(Index key) {
|
||||
for(iterator it = begin(); it != end(); ++it)
|
||||
if(std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) != (*it)->endFrontals())
|
||||
return it;
|
||||
return end();
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
template<class CONDITIONAL>
|
||||
void BayesNet<CONDITIONAL>::permuteWithInverse(const Permutation& inversePermutation) {
|
||||
|
|
@ -82,6 +100,21 @@ namespace gtsam {
|
|||
push_front(conditional);
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
template<class CONDITIONAL>
|
||||
void BayesNet<CONDITIONAL>::popLeaf(iterator conditional) {
|
||||
#ifndef NDEBUG
|
||||
BOOST_FOREACH(typename CONDITIONAL::shared_ptr checkConditional, conditionals_) {
|
||||
BOOST_FOREACH(Index key, (*conditional)->frontals()) {
|
||||
if(std::find(checkConditional->beginParents(), checkConditional->endParents(), key) != checkConditional->endParents())
|
||||
throw std::invalid_argument(
|
||||
"Debug mode exception: in BayesNet::popLeaf, the requested conditional is not a leaf.");
|
||||
}
|
||||
}
|
||||
#endif
|
||||
conditionals_.erase(conditional);
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
template<class CONDITIONAL>
|
||||
FastList<Index> BayesNet<CONDITIONAL>::ordering() const {
|
||||
|
|
@ -118,7 +151,7 @@ namespace gtsam {
|
|||
}
|
||||
}
|
||||
throw(invalid_argument((boost::format(
|
||||
"BayesNet::operator['%1%']: not found") % key).str()));
|
||||
"BayesNet::operator['%1%']: not found") % key).str()));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
|
|
|
|||
|
|
@ -22,6 +22,7 @@
|
|||
#include <list>
|
||||
#include <boost/shared_ptr.hpp>
|
||||
#include <boost/serialization/nvp.hpp>
|
||||
#include <boost/assign/list_inserter.hpp>
|
||||
|
||||
#include <gtsam/base/types.h>
|
||||
#include <gtsam/base/FastList.h>
|
||||
|
|
@ -30,126 +31,181 @@
|
|||
|
||||
namespace gtsam {
|
||||
|
||||
/**
|
||||
* A BayesNet is a list of conditionals, stored in elimination order, i.e.
|
||||
* leaves first, parents last. GaussianBayesNet and SymbolicBayesNet are
|
||||
* defined as typedefs of this class, using GaussianConditional and
|
||||
* IndexConditional as the CONDITIONAL template argument.
|
||||
*
|
||||
* todo: Symbolic using Index is a misnomer.
|
||||
* todo: how to handle Bayes nets with an optimize function? Currently using global functions.
|
||||
*/
|
||||
template<class CONDITIONAL>
|
||||
class BayesNet: public Testable<BayesNet<CONDITIONAL> > {
|
||||
/**
|
||||
* A BayesNet is a list of conditionals, stored in elimination order, i.e.
|
||||
* leaves first, parents last. GaussianBayesNet and SymbolicBayesNet are
|
||||
* defined as typedefs of this class, using GaussianConditional and
|
||||
* IndexConditional as the CONDITIONAL template argument.
|
||||
*
|
||||
* todo: Symbolic using Index is a misnomer.
|
||||
* todo: how to handle Bayes nets with an optimize function? Currently using global functions.
|
||||
*/
|
||||
template<class CONDITIONAL>
|
||||
class BayesNet: public Testable<BayesNet<CONDITIONAL> > {
|
||||
|
||||
public:
|
||||
public:
|
||||
|
||||
typedef typename boost::shared_ptr<BayesNet<CONDITIONAL> > shared_ptr;
|
||||
typedef typename boost::shared_ptr<BayesNet<CONDITIONAL> > shared_ptr;
|
||||
|
||||
/** We store shared pointers to Conditional densities */
|
||||
typedef typename boost::shared_ptr<CONDITIONAL> sharedConditional;
|
||||
typedef typename boost::shared_ptr<const CONDITIONAL> const_sharedConditional;
|
||||
typedef typename std::list<sharedConditional> Conditionals;
|
||||
/** We store shared pointers to Conditional densities */
|
||||
typedef typename boost::shared_ptr<CONDITIONAL> sharedConditional;
|
||||
typedef typename boost::shared_ptr<const CONDITIONAL> const_sharedConditional;
|
||||
typedef typename std::list<sharedConditional> Conditionals;
|
||||
|
||||
typedef typename Conditionals::const_iterator iterator;
|
||||
typedef typename Conditionals::const_reverse_iterator reverse_iterator;
|
||||
typedef typename Conditionals::const_iterator const_iterator;
|
||||
typedef typename Conditionals::const_reverse_iterator const_reverse_iterator;
|
||||
typedef typename Conditionals::iterator iterator;
|
||||
typedef typename Conditionals::reverse_iterator reverse_iterator;
|
||||
typedef typename Conditionals::const_iterator const_iterator;
|
||||
typedef typename Conditionals::const_reverse_iterator const_reverse_iterator;
|
||||
|
||||
protected:
|
||||
protected:
|
||||
|
||||
/**
|
||||
* Conditional densities are stored in reverse topological sort order (i.e., leaves first,
|
||||
* parents last), which corresponds to the elimination ordering if so obtained,
|
||||
* and is consistent with the column (block) ordering of an upper triangular matrix.
|
||||
*/
|
||||
Conditionals conditionals_;
|
||||
/**
|
||||
* Conditional densities are stored in reverse topological sort order (i.e., leaves first,
|
||||
* parents last), which corresponds to the elimination ordering if so obtained,
|
||||
* and is consistent with the column (block) ordering of an upper triangular matrix.
|
||||
*/
|
||||
Conditionals conditionals_;
|
||||
|
||||
public:
|
||||
public:
|
||||
|
||||
/** Default constructor as an empty BayesNet */
|
||||
BayesNet() {};
|
||||
/** Default constructor as an empty BayesNet */
|
||||
BayesNet() {};
|
||||
|
||||
/** BayesNet with 1 conditional */
|
||||
BayesNet(const sharedConditional& conditional) { push_back(conditional); }
|
||||
/** BayesNet with 1 conditional */
|
||||
BayesNet(const sharedConditional& conditional) { push_back(conditional); }
|
||||
|
||||
/** print */
|
||||
void print(const std::string& s = "") const;
|
||||
/** print */
|
||||
void print(const std::string& s = "") const;
|
||||
|
||||
/** check equality */
|
||||
bool equals(const BayesNet& other, double tol = 1e-9) const;
|
||||
/** check equality */
|
||||
bool equals(const BayesNet& other, double tol = 1e-9) const;
|
||||
|
||||
/** push_back: use reverse topological sort (i.e. parents last / elimination order) */
|
||||
inline void push_back(const sharedConditional& conditional) {
|
||||
conditionals_.push_back(conditional);
|
||||
}
|
||||
/** Find an iterator pointing to the conditional where the specified key
|
||||
* appears as a frontal variable, or end() if no conditional contains this
|
||||
* key. Running time is approximately \f$ O(n) \f$ in the number of
|
||||
* conditionals in the BayesNet.
|
||||
* @param key The index to find in the frontal variables of a conditional.
|
||||
*/
|
||||
const_iterator find(Index key) const;
|
||||
|
||||
/** push_front: use topological sort (i.e. parents first / reverse elimination order) */
|
||||
inline void push_front(const sharedConditional& conditional) {
|
||||
conditionals_.push_front(conditional);
|
||||
}
|
||||
/** Find an iterator pointing to the conditional where the specified key
|
||||
* appears as a frontal variable, or end() if no conditional contains this
|
||||
* key. Running time is approximately \f$ O(n) \f$ in the number of
|
||||
* conditionals in the BayesNet.
|
||||
* @param key The index to find in the frontal variables of a conditional.
|
||||
*/
|
||||
iterator find(Index key);
|
||||
|
||||
// push_back an entire Bayes net */
|
||||
void push_back(const BayesNet<CONDITIONAL> bn);
|
||||
/** push_back: use reverse topological sort (i.e. parents last / elimination order) */
|
||||
inline void push_back(const sharedConditional& conditional) {
|
||||
conditionals_.push_back(conditional);
|
||||
}
|
||||
|
||||
// push_front an entire Bayes net */
|
||||
void push_front(const BayesNet<CONDITIONAL> bn);
|
||||
/** push_front: use topological sort (i.e. parents first / reverse elimination order) */
|
||||
inline void push_front(const sharedConditional& conditional) {
|
||||
conditionals_.push_front(conditional);
|
||||
}
|
||||
|
||||
/**
|
||||
* pop_front: remove node at the bottom, used in marginalization
|
||||
* For example P(ABC)=P(A|BC)P(B|C)P(C) becomes P(BC)=P(B|C)P(C)
|
||||
*/
|
||||
inline void pop_front() {conditionals_.pop_front();}
|
||||
/// push_back an entire Bayes net
|
||||
void push_back(const BayesNet<CONDITIONAL> bn);
|
||||
|
||||
/** Permute the variables in the BayesNet */
|
||||
void permuteWithInverse(const Permutation& inversePermutation);
|
||||
/// push_front an entire Bayes net
|
||||
void push_front(const BayesNet<CONDITIONAL> bn);
|
||||
|
||||
/**
|
||||
* Permute the variables when only separator variables need to be permuted.
|
||||
* Returns true if any reordered variables appeared in the separator and
|
||||
* false if not.
|
||||
*/
|
||||
bool permuteSeparatorWithInverse(const Permutation& inversePermutation);
|
||||
/** += syntax for push_back, e.g. bayesNet += c1, c2, c3
|
||||
* @param conditional The conditional to add to the back of the BayesNet
|
||||
*/
|
||||
boost::assign::list_inserter<boost::assign_detail::call_push_back<BayesNet<CONDITIONAL> >, sharedConditional>
|
||||
operator+=(const sharedConditional& conditional) {
|
||||
return boost::assign::make_list_inserter(boost::assign_detail::call_push_back<BayesNet<CONDITIONAL> >(*this))(conditional); }
|
||||
|
||||
/** size is the number of nodes */
|
||||
inline size_t size() const {
|
||||
return conditionals_.size();
|
||||
}
|
||||
/**
|
||||
* pop_front: remove node at the bottom, used in marginalization
|
||||
* For example P(ABC)=P(A|BC)P(B|C)P(C) becomes P(BC)=P(B|C)P(C)
|
||||
*/
|
||||
void pop_front() {conditionals_.pop_front();}
|
||||
|
||||
/** return keys in reverse topological sort order, i.e., elimination order */
|
||||
FastList<Index> ordering() const;
|
||||
/**
|
||||
* Remove any leaf conditional. The conditional to remove is specified by
|
||||
* iterator. To find the iterator pointing to the conditional containing a
|
||||
* particular key, use find(), which has \f$ O(n) \f$ complexity. The
|
||||
* popLeaf function by itself has \f$ O(1) \f$ complexity.
|
||||
*
|
||||
* If the program calling this function is
|
||||
* compiled without NDEBUG defined, this function will check that the node
|
||||
* is indeed a leaf, but otherwise will not check, because the check has
|
||||
* \f$ O(n^2) \f$ complexity.
|
||||
*
|
||||
* Example 1:
|
||||
\code
|
||||
// Remove a leaf node with a known conditional
|
||||
GaussianBayesNet gbn = ...
|
||||
GaussianBayesNet::iterator leafConditional = ...
|
||||
gbn.popLeaf(leafConditional);
|
||||
\endcode
|
||||
* Example 2:
|
||||
\code
|
||||
// Remove the leaf node containing variable index 14
|
||||
GaussianBayesNet gbn = ...
|
||||
gbn.popLeaf(gbn.find(14));
|
||||
\endcode
|
||||
* @param conditional The iterator pointing to the leaf conditional to remove
|
||||
*/
|
||||
void popLeaf(iterator conditional);
|
||||
|
||||
/** SLOW O(n) random access to Conditional by key */
|
||||
sharedConditional operator[](Index key) const;
|
||||
/** Permute the variables in the BayesNet */
|
||||
void permuteWithInverse(const Permutation& inversePermutation);
|
||||
|
||||
/** return last node in ordering */
|
||||
sharedConditional& front() { return conditionals_.front(); }
|
||||
/**
|
||||
* Permute the variables when only separator variables need to be permuted.
|
||||
* Returns true if any reordered variables appeared in the separator and
|
||||
* false if not.
|
||||
*/
|
||||
bool permuteSeparatorWithInverse(const Permutation& inversePermutation);
|
||||
|
||||
/** return last node in ordering */
|
||||
boost::shared_ptr<const CONDITIONAL> front() const { return conditionals_.front(); }
|
||||
/** size is the number of nodes */
|
||||
size_t size() const {
|
||||
return conditionals_.size();
|
||||
}
|
||||
|
||||
/** return last node in ordering */
|
||||
sharedConditional& back() { return conditionals_.back(); }
|
||||
/** return keys in reverse topological sort order, i.e., elimination order */
|
||||
FastList<Index> ordering() const;
|
||||
|
||||
/** return last node in ordering */
|
||||
boost::shared_ptr<const CONDITIONAL> back() const { return conditionals_.back(); }
|
||||
/** SLOW O(n) random access to Conditional by key */
|
||||
sharedConditional operator[](Index key) const;
|
||||
|
||||
/** return iterators. FD: breaks encapsulation? */
|
||||
inline const_iterator const begin() const {return conditionals_.begin();}
|
||||
inline const_iterator const end() const {return conditionals_.end();}
|
||||
inline const_reverse_iterator const rbegin() const {return conditionals_.rbegin();}
|
||||
inline const_reverse_iterator const rend() const {return conditionals_.rend();}
|
||||
/** return last node in ordering */
|
||||
sharedConditional& front() { return conditionals_.front(); }
|
||||
|
||||
/** saves the bayes to a text file in GraphViz format */
|
||||
// void saveGraph(const std::string& s) const;
|
||||
/** return last node in ordering */
|
||||
boost::shared_ptr<const CONDITIONAL> front() const { return conditionals_.front(); }
|
||||
|
||||
private:
|
||||
/** Serialization function */
|
||||
friend class boost::serialization::access;
|
||||
template<class ARCHIVE>
|
||||
void serialize(ARCHIVE & ar, const unsigned int version) {
|
||||
ar & BOOST_SERIALIZATION_NVP(conditionals_);
|
||||
}
|
||||
}; // BayesNet
|
||||
/** return last node in ordering */
|
||||
sharedConditional& back() { return conditionals_.back(); }
|
||||
|
||||
/** return last node in ordering */
|
||||
boost::shared_ptr<const CONDITIONAL> back() const { return conditionals_.back(); }
|
||||
|
||||
/** return iterators. FD: breaks encapsulation? */
|
||||
const_iterator begin() const {return conditionals_.begin();}
|
||||
const_iterator end() const {return conditionals_.end();}
|
||||
const_reverse_iterator rbegin() const {return conditionals_.rbegin();}
|
||||
const_reverse_iterator rend() const {return conditionals_.rend();}
|
||||
iterator begin() {return conditionals_.begin();}
|
||||
iterator end() {return conditionals_.end();}
|
||||
reverse_iterator rbegin() {return conditionals_.rbegin();}
|
||||
reverse_iterator rend() {return conditionals_.rend();}
|
||||
|
||||
/** saves the bayes to a text file in GraphViz format */
|
||||
// void saveGraph(const std::string& s) const;
|
||||
|
||||
private:
|
||||
/** Serialization function */
|
||||
friend class boost::serialization::access;
|
||||
template<class ARCHIVE>
|
||||
void serialize(ARCHIVE & ar, const unsigned int version) {
|
||||
ar & BOOST_SERIALIZATION_NVP(conditionals_);
|
||||
}
|
||||
}; // BayesNet
|
||||
|
||||
} /// namespace gtsam
|
||||
|
|
|
|||
|
|
@ -22,7 +22,6 @@ using namespace boost::assign;
|
|||
#include <CppUnitLite/TestHarness.h>
|
||||
|
||||
#include <gtsam/inference/IndexConditional.h>
|
||||
#ifdef ALL
|
||||
#include <gtsam/inference/SymbolicFactorGraph.h>
|
||||
|
||||
using namespace std;
|
||||
|
|
@ -32,6 +31,8 @@ static const Index _L_ = 0;
|
|||
static const Index _A_ = 1;
|
||||
static const Index _B_ = 2;
|
||||
static const Index _C_ = 3;
|
||||
static const Index _D_ = 4;
|
||||
static const Index _E_ = 5;
|
||||
|
||||
IndexConditional::shared_ptr
|
||||
B(new IndexConditional(_B_)),
|
||||
|
|
@ -100,8 +101,92 @@ TEST( SymbolicBayesNet, combine )
|
|||
|
||||
CHECK(assert_equal(expected,p_ABC));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(SymbolicBayesNet, find) {
|
||||
SymbolicBayesNet bn;
|
||||
bn += IndexConditional::shared_ptr(new IndexConditional(_A_, _B_));
|
||||
std::vector<Index> keys;
|
||||
keys.push_back(_B_);
|
||||
keys.push_back(_C_);
|
||||
keys.push_back(_D_);
|
||||
bn += IndexConditional::shared_ptr(new IndexConditional(keys,2));
|
||||
bn += IndexConditional::shared_ptr(new IndexConditional(_D_));
|
||||
|
||||
SymbolicBayesNet::iterator expected = bn.begin(); ++ expected;
|
||||
SymbolicBayesNet::iterator actual = bn.find(_C_);
|
||||
EXPECT(assert_equal(**expected, **actual));
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST_UNSAFE(SymbolicBayesNet, popLeaf) {
|
||||
IndexConditional::shared_ptr
|
||||
A(new IndexConditional(_A_,_E_)),
|
||||
B(new IndexConditional(_B_,_E_)),
|
||||
C(new IndexConditional(_C_,_D_)),
|
||||
D(new IndexConditional(_D_,_E_)),
|
||||
E(new IndexConditional(_E_));
|
||||
|
||||
// BayesNet after popping A
|
||||
SymbolicBayesNet expected1;
|
||||
expected1 += B, C, D, E;
|
||||
|
||||
// BayesNet after popping C
|
||||
SymbolicBayesNet expected2;
|
||||
expected2 += A, B, D, E;
|
||||
|
||||
// BayesNet after popping C and D
|
||||
SymbolicBayesNet expected3;
|
||||
expected3 += A, B, E;
|
||||
|
||||
// BayesNet after popping C and A
|
||||
SymbolicBayesNet expected4;
|
||||
expected4 += B, D, E;
|
||||
|
||||
|
||||
// BayesNet after popping A
|
||||
SymbolicBayesNet actual1;
|
||||
actual1 += A, B, C, D, E;
|
||||
actual1.popLeaf(actual1.find(_A_));
|
||||
|
||||
// BayesNet after popping C
|
||||
SymbolicBayesNet actual2;
|
||||
actual2 += A, B, C, D, E;
|
||||
actual2.popLeaf(actual2.find(_C_));
|
||||
|
||||
// BayesNet after popping C and D
|
||||
SymbolicBayesNet actual3;
|
||||
actual3 += A, B, C, D, E;
|
||||
actual3.popLeaf(actual3.find(_C_));
|
||||
actual3.popLeaf(actual3.find(_D_));
|
||||
|
||||
// BayesNet after popping C and A
|
||||
SymbolicBayesNet actual4;
|
||||
actual4 += A, B, C, D, E;
|
||||
actual4.popLeaf(actual4.find(_C_));
|
||||
actual4.popLeaf(actual4.find(_A_));
|
||||
|
||||
EXPECT(assert_equal(expected1, actual1));
|
||||
EXPECT(assert_equal(expected2, actual2));
|
||||
EXPECT(assert_equal(expected3, actual3));
|
||||
EXPECT(assert_equal(expected4, actual4));
|
||||
|
||||
// Try to remove a non-leaf node
|
||||
#undef NDEBUG_SAVED
|
||||
#ifdef NDEBUG
|
||||
#define NDEBUG_SAVED
|
||||
#endif
|
||||
|
||||
#undef NDEBUG
|
||||
SymbolicBayesNet actual5;
|
||||
actual5 += A, B, C, D, E;
|
||||
CHECK_EXCEPTION(actual5.popLeaf(actual5.find(_D_)), std::invalid_argument);
|
||||
|
||||
#ifdef NDEBUG_SAVED
|
||||
#define NDEBUG
|
||||
#endif
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
int main() {
|
||||
TestResult tr;
|
||||
|
|
|
|||
Loading…
Reference in New Issue