gtsam 4.2.0
gtsam
gtsam::DiscreteFactorGraph Class Reference

Detailed Description

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

Factor == DiscreteFactor

+ Inheritance diagram for gtsam::DiscreteFactorGraph:

Public Member Functions

 DiscreteFactorGraph ()
 

‍map from keys to values

More...
 
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<typename... Args>
void add (Args &&... args)
 Add a decision-tree factor.
 
KeySet keys () const
 Return the set of variables involved in the factors (set union)
 
DiscreteKeys discreteKeys () const
 Return the DiscreteKeys in this factor graph.
 
DecisionTreeFactor product () const
 return product of all factors as a single factor
 
double operator() (const DiscreteValues &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...
 
DiscreteBayesNet sumProduct (OptionalOrderingType orderingType=boost::none) const
 Implement the sum-product algorithm. More...
 
DiscreteBayesNet sumProduct (const Ordering &ordering) const
 Implement the sum-product algorithm. More...
 
DiscreteLookupDAG maxProduct (OptionalOrderingType orderingType=boost::none) const
 Implement the max-product algorithm. More...
 
DiscreteLookupDAG maxProduct (const Ordering &ordering) const
 Implement the max-product algorithm. More...
 
DiscreteValues optimize (OptionalOrderingType orderingType=boost::none) const
 Find the maximum probable explanation (MPE) by doing max-product. More...
 
DiscreteValues optimize (const Ordering &ordering) const
 Find the maximum probable explanation (MPE) by doing max-product. More...
 
Testable
bool equals (const This &fg, double tol=1e-9) const
 
Wrapper support
std::string markdown (const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DiscreteFactor::Names &names={}) const
 Render as markdown tables. More...
 
std::string html (const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DiscreteFactor::Names &names={}) const
 Render as html tables. More...
 
- Public Member Functions inherited from gtsam::FactorGraph< DiscreteFactor >
 FactorGraph (std::initializer_list< boost::shared_ptr< DERIVEDFACTOR > > sharedFactors)
 Constructor that takes an initializer list of shared pointers. More...
 
virtual ~FactorGraph ()=default
 Default destructor Public and virtual so boost serialization can call it.
 
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).
 
void add (const FACTOR_OR_CONTAINER &factorOrContainer)
 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 up to tolerance.
 
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.
 
double error (const HybridValues &values) const
 Add error for all factors.
 
iterator begin ()
 non-const STL-style begin()
 
iterator end ()
 non-const STL-style end()
 
virtual 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.
 
void dot (std::ostream &os, const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DotWriter &writer=DotWriter()) const
 Output to graphviz format, stream version.
 
std::string dot (const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DotWriter &writer=DotWriter()) const
 Output to graphviz format string.
 
void saveGraph (const std::string &filename, const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DotWriter &writer=DotWriter()) const
 output to file with graphviz format.
 
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 tree 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

using This = DiscreteFactorGraph
 this class
 
using Base = FactorGraph< DiscreteFactor >
 base factor graph type
 
using BaseEliminateable = EliminateableFactorGraph< This >
 for elimination
 
using shared_ptr = boost::shared_ptr< This >
 shared_ptr to This
 
using Values = DiscreteValues
 backwards compatibility
 
using Indices = KeyVector
 
- 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.
 

Additional Inherited Members

- Protected Member Functions inherited from gtsam::FactorGraph< DiscreteFactor >
bool isEqual (const FactorGraph &other) const
 Check exact equality of the factor pointers. Useful for derived ==.
 
 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...
 

Constructor & Destructor Documentation

◆ DiscreteFactorGraph()

gtsam::DiscreteFactorGraph::DiscreteFactorGraph ( )
inline

‍map from keys to values

Default constructor

Member Function Documentation

◆ html()

string gtsam::DiscreteFactorGraph::html ( const KeyFormatter keyFormatter = DefaultKeyFormatter,
const DiscreteFactor::Names names = {} 
) const

Render as html tables.

Parameters
keyFormatterGTSAM-style Key formatter.
namesoptional, a map from Key to category names.
Returns
std::string a (potentially long) html string.

◆ markdown()

string gtsam::DiscreteFactorGraph::markdown ( const KeyFormatter keyFormatter = DefaultKeyFormatter,
const DiscreteFactor::Names names = {} 
) const

Render as markdown tables.

Parameters
keyFormatterGTSAM-style Key formatter.
namesoptional, a map from Key to category names.
Returns
std::string a (potentially long) markdown string.

◆ maxProduct() [1/2]

DiscreteLookupDAG gtsam::DiscreteFactorGraph::maxProduct ( const Ordering ordering) const

Implement the max-product algorithm.

Parameters
ordering
Returns
DiscreteLookupDAG `DAG with lookup tables

◆ maxProduct() [2/2]

DiscreteLookupDAG gtsam::DiscreteFactorGraph::maxProduct ( OptionalOrderingType  orderingType = boost::none) const

Implement the max-product algorithm.

Parameters
orderingType: one of COLAMD, METIS, NATURAL, CUSTOM
Returns
DiscreteLookupDAG DAG with lookup tables

◆ optimize() [1/2]

DiscreteValues gtsam::DiscreteFactorGraph::optimize ( const Ordering ordering) const

Find the maximum probable explanation (MPE) by doing max-product.

Parameters
ordering
Returns
DiscreteValues : MPE

◆ optimize() [2/2]

DiscreteValues gtsam::DiscreteFactorGraph::optimize ( OptionalOrderingType  orderingType = boost::none) const

Find the maximum probable explanation (MPE) by doing max-product.

Parameters
orderingType
Returns
DiscreteValues : MPE

◆ print()

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

print

Reimplemented from gtsam::FactorGraph< DiscreteFactor >.

◆ sumProduct() [1/2]

DiscreteBayesNet gtsam::DiscreteFactorGraph::sumProduct ( const Ordering ordering) const

Implement the sum-product algorithm.

Parameters
ordering
Returns
DiscreteBayesNet encoding posterior P(X|Z)

◆ sumProduct() [2/2]

DiscreteBayesNet gtsam::DiscreteFactorGraph::sumProduct ( OptionalOrderingType  orderingType = boost::none) const

Implement the sum-product algorithm.

Parameters
orderingType: one of COLAMD, METIS, NATURAL, CUSTOM
Returns
DiscreteBayesNet encoding posterior P(X|Z)

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