GTSAM
4.0.2
C++ library for smoothing and mapping (SAM)
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#include <EliminateableFactorGraph.h>
Public Types | |
typedef EliminationTraits< FactorGraphType > | EliminationTraitsType |
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< std::shared_ptr< ConditionalType >, std::shared_ptr< _FactorType > > | EliminationResult |
typedef std::function< EliminationResult(const FactorGraphType &, const Ordering &)> | Eliminate |
The function type that does a single dense elimination step on a subgraph. | |
typedef std::optional< std::reference_wrapper< const VariableIndex > > | OptionalVariableIndex |
typedef std::optional< Ordering::OrderingType > | OptionalOrderingType |
Typedef for an optional ordering type. | |
Public Member Functions | |
std::shared_ptr< BayesNetType > | eliminateSequential (OptionalOrderingType orderingType={}, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesNetType > | eliminateSequential (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | eliminateMultifrontal (OptionalOrderingType orderingType={}, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | eliminateMultifrontal (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::pair< std::shared_ptr< BayesNetType >, std::shared_ptr< FactorGraphType > > | eliminatePartialSequential (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::pair< std::shared_ptr< BayesNetType >, std::shared_ptr< FactorGraphType > > | eliminatePartialSequential (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::pair< std::shared_ptr< BayesTreeType >, std::shared_ptr< FactorGraphType > > | eliminatePartialMultifrontal (const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::pair< std::shared_ptr< BayesTreeType >, std::shared_ptr< FactorGraphType > > | eliminatePartialMultifrontal (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesNetType > | marginalMultifrontalBayesNet (const Ordering &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesNetType > | marginalMultifrontalBayesNet (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesNetType > | marginalMultifrontalBayesNet (const Ordering &variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesNetType > | marginalMultifrontalBayesNet (const KeyVector &variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | marginalMultifrontalBayesTree (const Ordering &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | marginalMultifrontalBayesTree (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | marginalMultifrontalBayesTree (const Ordering &variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< BayesTreeType > | marginalMultifrontalBayesTree (const KeyVector &variables, const Ordering &marginalizedVariableOrdering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
std::shared_ptr< FactorGraphType > | marginal (const KeyVector &variables, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const |
EliminateableFactorGraph is a base class for factor graphs that contains elimination algorithms. Any factor graph holding eliminateable factors can derive from this class to expose functions for computing marginals, conditional marginals, doing multifrontal and sequential elimination, etc.
typedef std::pair<std::shared_ptr<ConditionalType>, std::shared_ptr<_FactorType> > gtsam::EliminateableFactorGraph< FACTORGRAPH >::EliminationResult |
The pair of conditional and remaining factor produced by a single dense elimination step on a subgraph.
typedef std::optional<std::reference_wrapper<const VariableIndex> > gtsam::EliminateableFactorGraph< FACTORGRAPH >::OptionalVariableIndex |
Typedef for an optional variable index as an argument to elimination functions It is an optional to a constant reference
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminateMultifrontal | ( | OptionalOrderingType | orderingType = {} , |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do multifrontal elimination of all variables to produce a Bayes tree. If an ordering is not provided, the ordering will be computed using either COLAMD or METIS, depending on the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
Example - Full Cholesky elimination in COLAMD order:
Example - Reusing an existing VariableIndex to improve performance, and using COLAMD ordering:
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminateMultifrontal | ( | const Ordering & | ordering, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do multifrontal elimination of all variables to produce a Bayes tree. If an ordering is not provided, the ordering will be computed using either COLAMD or METIS, depending on the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
Example - Full QR elimination in specified order:
std::pair< std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType >, std::shared_ptr< FACTORGRAPH > > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminatePartialMultifrontal | ( | const Ordering & | ordering, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do multifrontal elimination of some variables, in ordering
provided, to produce a Bayes tree and a remaining factor graph. This computes the factorization \( p(X) = p(A|B) p(B) \), where \( A = \) variables
, \( X \) is all the variables in the factor graph, and \( B = X\backslash A \).
std::pair< std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType >, std::shared_ptr< FACTORGRAPH > > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminatePartialMultifrontal | ( | const KeyVector & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do multifrontal elimination of the given variables
in an ordering computed by COLAMD to produce a Bayes tree and a remaining factor graph. This computes the factorization \( p(X) = p(A|B) p(B) \), where \( A = \) variables
, \( X \) is all the variables in the factor graph, and \( B = X\backslash A \).
std::pair< std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType >, std::shared_ptr< FACTORGRAPH > > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminatePartialSequential | ( | const Ordering & | ordering, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do sequential elimination of some variables, in ordering
provided, to produce a Bayes net and a remaining factor graph. This computes the factorization \( p(X) = p(A|B) p(B) \), where \( A = \) variables
, \( X \) is all the variables in the factor graph, and \( B = X\backslash A \).
std::pair< std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType >, std::shared_ptr< FACTORGRAPH > > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminatePartialSequential | ( | const KeyVector & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do sequential elimination of the given variables
in an ordering computed by COLAMD to produce a Bayes net and a remaining factor graph. This computes the factorization \( p(X) = p(A|B) p(B) \), where \( A = \) variables
, \( X \) is all the variables in the factor graph, and \( B = X\backslash A \).
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminateSequential | ( | OptionalOrderingType | orderingType = {} , |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do sequential elimination of all variables to produce a Bayes net. If an ordering is not provided, the ordering provided by COLAMD will be used.
Example - Full Cholesky elimination in COLAMD order:
Example - METIS ordering for elimination
Example - Reusing an existing VariableIndex to improve performance, and using COLAMD ordering:
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::eliminateSequential | ( | const Ordering & | ordering, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Do sequential elimination of all variables to produce a Bayes net.
Example - Full QR elimination in specified order:
Example - Reusing an existing VariableIndex to improve performance:
std::shared_ptr< FACTORGRAPH > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginal | ( | const KeyVector & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal factor graph of the requested variables.
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesNet | ( | const Ordering & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes net. Uses COLAMD marginalization ordering by default
variables | Determines the ordered variables whose marginal to compute, will be ordered in the returned BayesNet as specified. |
function | Optional dense elimination function. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesNet | ( | const KeyVector & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes net. Uses COLAMD marginalization ordering by default
variables | Determines the variables whose marginal to compute, will be ordered using COLAMD; use Ordering(variables) to specify the variable ordering. |
function | Optional dense elimination function. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesNet | ( | const Ordering & | variables, |
const Ordering & | marginalizedVariableOrdering, | ||
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes net.
variables | Determines the ordered variables whose marginal to compute, will be ordered in the returned BayesNet as specified. |
marginalizedVariableOrdering | Ordering for the variables being marginalized out, i.e. all variables not in variables . |
function | Optional dense elimination function. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesNetType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesNet | ( | const KeyVector & | variables, |
const Ordering & | marginalizedVariableOrdering, | ||
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes net.
variables | Determines the variables whose marginal to compute, will be ordered using COLAMD; use Ordering(variables) to specify the variable ordering. |
marginalizedVariableOrdering | Ordering for the variables being marginalized out, i.e. all variables not in variables . |
function | Optional dense elimination function. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesTree | ( | const Ordering & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes tree. Uses COLAMD marginalization order by default
variables | Determines the ordered variables whose marginal to compute, will be ordered in the returned BayesNet as specified. |
function | Optional dense elimination function.. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesTree | ( | const KeyVector & | variables, |
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes tree. Uses COLAMD marginalization order by default
variables | Determines the variables whose marginal to compute, will be ordered using COLAMD; use Ordering(variables) to specify the variable ordering. |
function | Optional dense elimination function.. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesTree | ( | const Ordering & | variables, |
const Ordering & | marginalizedVariableOrdering, | ||
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes tree.
variables | Determines the ordered variables whose marginal to compute, will be ordered in the returned BayesNet as specified. |
marginalizedVariableOrdering | Ordering for the variables being marginalized out, i.e. all variables not in variables . |
function | Optional dense elimination function.. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |
std::shared_ptr< typename EliminateableFactorGraph< FACTORGRAPH >::BayesTreeType > gtsam::EliminateableFactorGraph< FACTORGRAPH >::marginalMultifrontalBayesTree | ( | const KeyVector & | variables, |
const Ordering & | marginalizedVariableOrdering, | ||
const Eliminate & | function = EliminationTraitsType::DefaultEliminate , |
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OptionalVariableIndex | variableIndex = {} |
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) | const |
Compute the marginal of the requested variables and return the result as a Bayes tree.
variables | Determines the variables whose marginal to compute, will be ordered using COLAMD; use Ordering(variables) to specify the variable ordering. |
marginalizedVariableOrdering | Ordering for the variables being marginalized out, i.e. all variables not in variables . |
function | Optional dense elimination function.. |
variableIndex | Optional pre-computed VariableIndex for the factor graph, if not provided one will be computed. |