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Renamed typedef name Conditional to ConditionalType

release/4.3a0
Richard Roberts 2011-03-01 17:16:43 +00:00
parent d99d047a77
commit 85ed6c306d
12 changed files with 20 additions and 20 deletions
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4
gtsam/inference/EliminationTree.h
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@ -40,13 +40,13 @@ public:
typedef typename FACTOR::shared_ptr sharedFactor;
typedef boost::shared_ptr<EliminationTree<FACTOR> > shared_ptr;
typedef gtsam::BayesNet<typename FACTOR::Conditional> BayesNet;
typedef gtsam::BayesNet<typename FACTOR::ConditionalType> BayesNet;
private:
typedef FastList<sharedFactor> Factors;
typedef FastList<shared_ptr> SubTrees;
typedef std::vector<typename FACTOR::Conditional::shared_ptr> Conditionals;
typedef std::vector<typename FACTOR::ConditionalType::shared_ptr> Conditionals;
Index key_; /** index associated with root */
Factors factors_; /** factors associated with root */

2
gtsam/inference/FactorBase-inl.h
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@ -35,7 +35,7 @@ FactorBase<KEY>::FactorBase(const FactorBase<KEY>& f) : keys_(f.keys_) {}
/* ************************************************************************* */
template<typename KEY>
FactorBase<KEY>::FactorBase(const Conditional& c) : keys_(c.keys()) {}
FactorBase<KEY>::FactorBase(const ConditionalType& c) : keys_(c.keys()) {}
/* ************************************************************************* */
template<typename KEY>

6
gtsam/inference/FactorBase.h
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@ -44,7 +44,7 @@ template<class KEY> class ConditionalBase;
* todo: Make NonlinearFactor derive from this too, which requires moving
* Combine, eliminate*, permute* and the sorted key invariant to IndexFactor.
*
* Note that derived classes *must* redefine the Conditional and shared_ptr
* Note that derived classes *must* redefine the ConditionalType and shared_ptr
* typedefs to refer to the associated conditional and shared_ptr types of the
* derived class. See IndexFactor, JacobianFactor, etc. for examples.
*/
@ -60,7 +60,7 @@ public:
* Typedef to the conditional type obtained by eliminating this factor.
* Derived classes must redefine this.
*/
typedef gtsam::ConditionalBase<Key> Conditional;
typedef gtsam::ConditionalBase<Key> ConditionalType;
/** A shared_ptr to this class. Derived classes must redefine this. */
typedef boost::shared_ptr<FactorBase> shared_ptr;
@ -86,7 +86,7 @@ public:
FactorBase(const This& f);
/** Construct from derived type */
FactorBase(const Conditional& c);
FactorBase(const ConditionalType& c);
/** Constructor from a collection of keys */
template<class KEYITERATOR> FactorBase(KEYITERATOR beginKey, KEYITERATOR endKey) :

6
gtsam/inference/GenericSequentialSolver-inl.h
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@ -52,7 +52,7 @@ void GenericSequentialSolver<FACTOR>::replaceFactors(const typename FactorGraph<
/* ************************************************************************* */
template<class FACTOR>
typename BayesNet<typename FACTOR::Conditional>::shared_ptr GenericSequentialSolver<FACTOR>::eliminate() const {
typename BayesNet<typename FACTOR::ConditionalType>::shared_ptr GenericSequentialSolver<FACTOR>::eliminate() const {
return eliminationTree_->eliminate();
}
@ -73,7 +73,7 @@ typename FactorGraph<FACTOR>::shared_ptr GenericSequentialSolver<FACTOR>::jointF
}
// Eliminate all variables
typename BayesNet<typename FACTOR::Conditional>::shared_ptr bayesNet(
typename BayesNet<typename FACTOR::ConditionalType>::shared_ptr bayesNet(
EliminationTree<FACTOR>::Create(*factors_)->eliminate());
// Undo the permuation on the original factors and on the structure.
@ -85,7 +85,7 @@ typename FactorGraph<FACTOR>::shared_ptr GenericSequentialSolver<FACTOR>::jointF
// Take the joint marginal from the Bayes net.
typename FactorGraph<FACTOR>::shared_ptr joint(new FactorGraph<FACTOR>);
joint->reserve(js.size());
typename BayesNet<typename FACTOR::Conditional>::const_reverse_iterator conditional = bayesNet->rbegin();
typename BayesNet<typename FACTOR::ConditionalType>::const_reverse_iterator conditional = bayesNet->rbegin();
for(size_t i = 0; i < js.size(); ++i) {
joint->push_back((*(conditional++))->toFactor()); }

2
gtsam/inference/GenericSequentialSolver.h
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@ -66,7 +66,7 @@ public:
* Eliminate the factor graph sequentially. Uses a column elimination tree
* to recursively eliminate.
*/
typename BayesNet<typename FACTOR::Conditional>::shared_ptr eliminate() const;
typename BayesNet<typename FACTOR::ConditionalType>::shared_ptr eliminate() const;
/**
* Compute the marginal joint over a set of variables, by integrating out

2
gtsam/inference/IndexFactor.cpp
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@ -41,7 +41,7 @@ pair<BayesNet<IndexConditional>::shared_ptr, IndexFactor::shared_ptr> IndexFacto
if(variables.size() < 1)
throw invalid_argument("IndexFactor::CombineAndEliminate called on factors with zero total variables.");
pair<BayesNet<Conditional>::shared_ptr, shared_ptr> result;
pair<BayesNet<ConditionalType>::shared_ptr, shared_ptr> result;
result.first.reset(new BayesNet<IndexConditional>());
FastSet<Index>::const_iterator var;
for(var = variables.begin(); result.first->size() < nrFrontals; ++var)

8
gtsam/inference/IndexFactor.h
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@ -47,7 +47,7 @@ namespace gtsam {
typedef FactorBase<Index> Base;
/** Elimination produces an IndexConditional */
typedef IndexConditional Conditional;
typedef IndexConditional ConditionalType;
/** Overriding the shared_ptr typedef */
typedef boost::shared_ptr<IndexFactor> shared_ptr;
@ -83,7 +83,7 @@ namespace gtsam {
/**
* Combine and eliminate several factors.
*/
static std::pair<BayesNet<Conditional>::shared_ptr, shared_ptr> CombineAndEliminate(
static std::pair<BayesNet<ConditionalType>::shared_ptr, shared_ptr> CombineAndEliminate(
const FactorGraph<This>& factors, size_t nrFrontals=1);
/** Create a combined joint factor (new style for EliminationTree). */
@ -94,12 +94,12 @@ namespace gtsam {
* eliminate the first variable involved in this factor
* @return a conditional on the eliminated variable
*/
boost::shared_ptr<Conditional> eliminateFirst();
boost::shared_ptr<ConditionalType> eliminateFirst();
/**
* eliminate the first nrFrontals frontal variables.
*/
boost::shared_ptr<BayesNet<Conditional> > eliminate(size_t nrFrontals = 1);
boost::shared_ptr<BayesNet<ConditionalType> > eliminate(size_t nrFrontals = 1);
};

2
gtsam/inference/JunctionTree-inl.h
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@ -171,7 +171,7 @@ namespace gtsam {
// Now that we know which factors and variables, and where variables
// come from and go to, create and eliminate the new joint factor.
tic(2, "CombineAndEliminate");
pair<typename BayesNet<typename FG::FactorType::Conditional>::shared_ptr, typename FG::sharedFactor> eliminated(
pair<typename BayesNet<typename FG::FactorType::ConditionalType>::shared_ptr, typename FG::sharedFactor> eliminated(
FG::FactorType::CombineAndEliminate(fg, current->frontal.size()));
toc(2, "CombineAndEliminate");

2
gtsam/inference/JunctionTree.h
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@ -46,7 +46,7 @@ namespace gtsam {
typedef typename ClusterTree<FG>::Cluster Clique;
typedef typename Clique::shared_ptr sharedClique;
typedef class BayesTree<typename FG::FactorType::Conditional> BayesTree;
typedef class BayesTree<typename FG::FactorType::ConditionalType> BayesTree;
typedef boost::shared_ptr<JunctionTree<FG> > shared_ptr;

2
gtsam/linear/GaussianFactor.h
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@ -74,7 +74,7 @@ namespace gtsam {
enum SolveMethod { SOLVE_QR, SOLVE_PREFER_CHOLESKY };
typedef GaussianConditional Conditional;
typedef GaussianConditional ConditionalType;
typedef boost::shared_ptr<GaussianFactor> shared_ptr;
// Implementing Testable interface

2
gtsam/linear/HessianFactor.cpp
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@ -462,7 +462,7 @@ GaussianBayesNet::shared_ptr HessianFactor::splitEliminatedFactor(size_t nrFront
tic(2, "construct cond");
const ublas::scalar_vector<double> sigmas(varDim, 1.0);
conditionals->push_back(boost::make_shared<Conditional>(keys.begin()+j, keys.end(), 1, Ab, sigmas));
conditionals->push_back(boost::make_shared<ConditionalType>(keys.begin()+j, keys.end(), 1, Ab, sigmas));
toc(2, "construct cond");
if(debug) conditionals->back()->print("Extracted conditional: ");
Ab.rowStart() += varDim;

2
gtsam/linear/JacobianFactor.cpp
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@ -449,7 +449,7 @@ namespace gtsam {
size_t varDim = Ab_(0).size2();
Ab_.rowEnd() = Ab_.rowStart() + varDim;
const ublas::vector_range<const Vector> sigmas(noiseModel->sigmas(), ublas::range(Ab_.rowStart(), Ab_.rowEnd()));
conditionals->push_back(boost::make_shared<Conditional>(keys_.begin()+j, keys_.end(), 1, Ab_, sigmas));
conditionals->push_back(boost::make_shared<ConditionalType>(keys_.begin()+j, keys_.end(), 1, Ab_, sigmas));
if(debug) conditionals->back()->print("Extracted conditional: ");
Ab_.rowStart() += varDim;
Ab_.firstBlock() += 1;