gtsam 4.1.1 gtsam
gtsam::DiscreteFactorGraph Class Reference

## Detailed Description

A Discrete Factor Graph is a factor graph where all factors are Discrete, i.e.

Inheritance diagram for gtsam::DiscreteFactorGraph:

## Public Member Functions

DiscreteFactorGraph ()
Default constructor.

template<typename ITERATOR >
DiscreteFactorGraph (ITERATOR firstFactor, ITERATOR lastFactor)
Construct from iterator over factors.

template<class CONTAINER >
DiscreteFactorGraph (const CONTAINER &factors)
Construct from container of factors (shared_ptr or plain objects)

template<class DERIVEDFACTOR >
DiscreteFactorGraph (const FactorGraph< DERIVEDFACTOR > &graph)
Implicit copy/downcast constructor to override explicit template container constructor.

virtual ~DiscreteFactorGraph ()
Destructor.

template<class SOURCE >
void add (const DiscreteKey &j, SOURCE table)

template<class SOURCE >
void add (const DiscreteKey &j1, const DiscreteKey &j2, SOURCE table)

template<class SOURCE >
void add (const DiscreteKeys &keys, SOURCE table)
add shared discreteFactor immediately from arguments

KeySet keys () const
Return the set of variables involved in the factors (set union)

DecisionTreeFactor product () const
return product of all factors as a single factor

double operator() (const DiscreteFactor::Values &values) const
Evaluates the factor graph given values, returns the joint probability of the factor graph given specific instantiation of values.

void print (const std::string &s="DiscreteFactorGraph", const KeyFormatter &formatter=DefaultKeyFormatter) const override
print More...

DiscreteFactor::sharedValues optimize () const
Solve the factor graph by performing variable elimination in COLAMD order using the dense elimination function specified in function, followed by back-substitution resulting from elimination. More...

Testable
bool equals (const This &fg, double tol=1e-9) const

Public Member Functions inherited from gtsam::FactorGraph< DiscreteFactor >
virtual ~FactorGraph ()=default
Default destructor.

void reserve (size_t size)
Reserve space for the specified number of factors if you know in advance how many there will be (works like FastVector::reserve).

IsDerived< DERIVEDFACTOR > push_back (boost::shared_ptr< DERIVEDFACTOR > factor)
Add a factor directly using a shared_ptr.

IsDerived< DERIVEDFACTOR > push_back (const DERIVEDFACTOR &factor)
Add a factor by value, will be copy-constructed (use push_back with a shared_ptr to avoid the copy).

IsDerived< DERIVEDFACTOR > emplace_shared (Args &&... args)
Emplace a shared pointer to factor of given type.

IsDerived< DERIVEDFACTOR > add (boost::shared_ptr< DERIVEDFACTOR > factor)
add is a synonym for push_back.

std::enable_if< std::is_base_of< FactorType, DERIVEDFACTOR >::value, boost::assign::list_inserter< RefCallPushBack< This > > >::type operator+= (boost::shared_ptr< DERIVEDFACTOR > factor)
+= works well with boost::assign list inserter.

HasDerivedElementType< ITERATOR > push_back (ITERATOR firstFactor, ITERATOR lastFactor)
Push back many factors with an iterator over shared_ptr (factors are not copied)

HasDerivedValueType< ITERATOR > push_back (ITERATOR firstFactor, ITERATOR lastFactor)
Push back many factors with an iterator (factors are copied)

HasDerivedElementType< CONTAINER > push_back (const CONTAINER &container)
Push back many factors as shared_ptr's in a container (factors are not copied)

HasDerivedValueType< CONTAINER > push_back (const CONTAINER &container)
Push back non-pointer objects in a container (factors are copied).

Add a factor or container of factors, including STL collections, BayesTrees, etc.

boost::assign::list_inserter< CRefCallPushBack< This > > operator+= (const FACTOR_OR_CONTAINER &factorOrContainer)
Add a factor or container of factors, including STL collections, BayesTrees, etc.

std::enable_if< std::is_base_of< This, typenameCLIQUE::FactorGraphType >::value >::type push_back (const BayesTree< CLIQUE > &bayesTree)
Push back a BayesTree as a collection of factors. More...

FactorIndices add_factors (const CONTAINER &factors, bool useEmptySlots=false)
Add new factors to a factor graph and returns a list of new factor indices, optionally finding and reusing empty factor slots.

bool equals (const This &fg, double tol=1e-9) const
Check equality.

size_t size () const
return the number of factors (including any null factors set by remove() ).

bool empty () const
Check if the graph is empty (null factors set by remove() will cause this to return false).

const sharedFactor at (size_t i) const
Get a specific factor by index (this checks array bounds and may throw an exception, as opposed to operator[] which does not).

sharedFactorat (size_t i)
Get a specific factor by index (this checks array bounds and may throw an exception, as opposed to operator[] which does not).

const sharedFactor operator[] (size_t i) const
Get a specific factor by index (this does not check array bounds, as opposed to at() which does).

sharedFactoroperator[] (size_t i)
Get a specific factor by index (this does not check array bounds, as opposed to at() which does).

const_iterator begin () const
Iterator to beginning of factors.

const_iterator end () const
Iterator to end of factors.

sharedFactor front () const
Get the first factor.

sharedFactor back () const
Get the last factor.

iterator begin ()
non-const STL-style begin()

iterator end ()
non-const STL-style end()

void resize (size_t size)
Directly resize the number of factors in the graph. More...

void remove (size_t i)
delete factor without re-arranging indexes by inserting a nullptr pointer

void replace (size_t index, sharedFactor factor)
replace a factor by index

iterator erase (iterator item)
Erase factor and rearrange other factors to take up the empty space.

iterator erase (iterator first, iterator last)
Erase factors and rearrange other factors to take up the empty space.

size_t nrFactors () const
return the number of non-null factors

KeySet keys () const
Potentially slow function to return all keys involved, sorted, as a set.

KeyVector keyVector () const
Potentially slow function to return all keys involved, sorted, as a vector.

bool exists (size_t idx) const
MATLAB interface utility: Checks whether a factor index idx exists in the graph and is a live pointer.

Public Member Functions inherited from gtsam::EliminateableFactorGraph< DiscreteFactorGraph >
boost::shared_ptr< BayesNetTypeeliminateSequential (OptionalOrderingType orderingType=boost::none, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do sequential elimination of all variables to produce a Bayes net. More...

boost::shared_ptr< BayesNetTypeeliminateSequential (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do sequential elimination of all variables to produce a Bayes net. More...

boost::shared_ptr< BayesTreeTypeeliminateMultifrontal (OptionalOrderingType orderingType=boost::none, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do multifrontal elimination of all variables to produce a Bayes tree. More...

boost::shared_ptr< BayesTreeTypeeliminateMultifrontal (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do multifrontal elimination of all variables to produce a Bayes tree. More...

std::pair< boost::shared_ptr< BayesNetType >, boost::shared_ptr< FactorGraphType > > eliminatePartialSequential (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do sequential elimination of some variables, in ordering provided, to produce a Bayes net and a remaining factor graph. More...

std::pair< boost::shared_ptr< BayesNetType >, boost::shared_ptr< FactorGraphType > > eliminatePartialSequential (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do sequential elimination of the given variables in an ordering computed by COLAMD to produce a Bayes net and a remaining factor graph. More...

std::pair< boost::shared_ptr< BayesTreeType >, boost::shared_ptr< FactorGraphType > > eliminatePartialMultifrontal (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do multifrontal elimination of some variables, in ordering provided, to produce a Bayes tree and a remaining factor graph. More...

std::pair< boost::shared_ptr< BayesTreeType >, boost::shared_ptr< FactorGraphType > > eliminatePartialMultifrontal (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Do multifrontal elimination of the given variables in an ordering computed by COLAMD to produce a Bayes net and a remaining factor graph. More...

boost::shared_ptr< BayesNetTypemarginalMultifrontalBayesNet (boost::variant< const Ordering &, const KeyVector & > variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Compute the marginal of the requested variables and return the result as a Bayes net. More...

boost::shared_ptr< BayesNetTypemarginalMultifrontalBayesNet (boost::variant< const Ordering &, const KeyVector & > variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Compute the marginal of the requested variables and return the result as a Bayes net. More...

boost::shared_ptr< BayesTreeTypemarginalMultifrontalBayesTree (boost::variant< const Ordering &, const KeyVector & > variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Compute the marginal of the requested variables and return the result as a Bayes tree. More...

boost::shared_ptr< BayesTreeTypemarginalMultifrontalBayesTree (boost::variant< const Ordering &, const KeyVector & > variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Compute the marginal of the requested variables and return the result as a Bayes tree. More...

boost::shared_ptr< FactorGraphTypemarginal (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex=boost::none) const
Compute the marginal factor graph of the requested variables.

## Public Types

typedef DiscreteFactorGraph This
Typedef to this class.

typedef FactorGraph< DiscreteFactorBase
Typedef to base factor graph type.

typedef EliminateableFactorGraph< ThisBaseEliminateable
Typedef to base elimination class.

typedef boost::shared_ptr< Thisshared_ptr
shared_ptr to this class

typedef KeyVector Indices
A map from keys to values.

typedef Assignment< KeyValues

typedef boost::shared_ptr< ValuessharedValues

Public Types inherited from gtsam::FactorGraph< DiscreteFactor >
typedef DiscreteFactor FactorType
factor type

typedef boost::shared_ptr< DiscreteFactorsharedFactor
Shared pointer to a factor.

typedef sharedFactor value_type

typedef FastVector< sharedFactor >::iterator iterator

typedef FastVector< sharedFactor >::const_iterator const_iterator

Public Types inherited from gtsam::EliminateableFactorGraph< DiscreteFactorGraph >
typedef EliminationTraits< FactorGraphTypeEliminationTraitsType
Typedef to the specific EliminationTraits for this graph.

typedef EliminationTraitsType::ConditionalType ConditionalType
Conditional type stored in the Bayes net produced by elimination.

typedef EliminationTraitsType::BayesNetType BayesNetType
Bayes net type produced by sequential elimination.

typedef EliminationTraitsType::EliminationTreeType EliminationTreeType
Elimination tree type that can do sequential elimination of this graph.

typedef EliminationTraitsType::BayesTreeType BayesTreeType
Bayes tree type produced by multifrontal elimination.

typedef EliminationTraitsType::JunctionTreeType JunctionTreeType
Junction tree type that can do multifrontal elimination of this graph.

typedef std::pair< boost::shared_ptr< ConditionalType >, boost::shared_ptr< _FactorType > > EliminationResult
The pair of conditional and remaining factor produced by a single dense elimination step on a subgraph.

typedef std::function< EliminationResult(const FactorGraphType &, const Ordering &)> Eliminate
The function type that does a single dense elimination step on a subgraph.

typedef boost::optional< const VariableIndex & > OptionalVariableIndex
Typedef for an optional variable index as an argument to elimination functions.

typedef boost::optional< Ordering::OrderingTypeOptionalOrderingType
Typedef for an optional ordering type.

Protected Member Functions inherited from gtsam::FactorGraph< DiscreteFactor >
FactorGraph ()
Default constructor.

FactorGraph (ITERATOR firstFactor, ITERATOR lastFactor)
Constructor from iterator over factors (shared_ptr or plain objects)

FactorGraph (const CONTAINER &factors)
Construct from container of factors (shared_ptr or plain objects)

Protected Attributes inherited from gtsam::FactorGraph< DiscreteFactor >
FastVector< sharedFactorfactors_
concept check, makes sure FACTOR defines print and equals More...

## ◆ optimize()

 DiscreteFactor::sharedValues gtsam::DiscreteFactorGraph::optimize ( ) const

Solve the factor graph by performing variable elimination in COLAMD order using the dense elimination function specified in function, followed by back-substitution resulting from elimination.

Is equivalent to calling graph.eliminateSequential()->optimize().

## ◆ print()

 void gtsam::DiscreteFactorGraph::print ( const std::string & s = "DiscreteFactorGraph", const KeyFormatter & formatter = DefaultKeyFormatter ) const
overridevirtual

print

Reimplemented from gtsam::FactorGraph< DiscreteFactor >.

Reimplemented in gtsam::Scheduler.

The documentation for this class was generated from the following files: