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Removed extra code that was needed for variant

release/4.3a0
Frank Dellaert 2023-02-05 15:02:12 -08:00
parent b9ccdf9b11
commit a193867214
5 changed files with 10 additions and 29 deletions
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7
gtsam/inference/BayesTree-inst.h
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@ -26,7 +26,6 @@
#include <gtsam/base/timing.h>
#include <fstream>
#include <functional>
namespace gtsam {
@ -278,9 +277,8 @@ namespace gtsam {
FactorGraphType cliqueMarginal = clique->marginal2(function);
// Now, marginalize out everything that is not variable j
auto ordering = Ordering{j};
BayesNetType marginalBN =
*cliqueMarginal.marginalMultifrontalBayesNet(std::cref(ordering), function);
*cliqueMarginal.marginalMultifrontalBayesNet(Ordering{j}, function);
// The Bayes net should contain only one conditional for variable j, so return it
return marginalBN.front();
@ -402,9 +400,8 @@ namespace gtsam {
gttoc(Disjoint_marginals);
}
auto ordering = Ordering{j1, j2};
// now, marginalize out everything that is not variable j1 or j2
return p_BC1C2.marginalMultifrontalBayesNet(std::cref(ordering), function);
return p_BC1C2.marginalMultifrontalBayesNet(Ordering{j1, j2}, function);
}
/* ************************************************************************* */

5
gtsam/inference/BayesTreeCliqueBase-inst.h
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@ -20,8 +20,6 @@
#include <gtsam/inference/FactorGraph-inst.h>
#include <gtsam/base/timing.h>
#include <functional>
namespace gtsam {
/* ************************************************************************* */
@ -178,9 +176,8 @@ namespace gtsam {
// The variables we want to keepSet are exactly the ones in S
KeyVector indicesS(this->conditional()->beginParents(),
this->conditional()->endParents());
auto ordering = Ordering(indicesS);
auto separatorMarginal =
p_Cp.marginalMultifrontalBayesNet(std::cref(ordering), function);
p_Cp.marginalMultifrontalBayesNet(Ordering(indicesS), function);
cachedSeparatorMarginal_ = *separatorMarginal;
}
}

9
gtsam/inference/EliminateableFactorGraph-inst.h
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@ -21,15 +21,6 @@
#include <gtsam/inference/EliminateableFactorGraph.h>
#include <gtsam/inference/inferenceExceptions.h>
// some helper functions
namespace {
// A function to take a reference_wrapper object and return the underlying pointer
template<typename T>
T* get_pointer(std::reference_wrapper<T> ref) {
return &ref.get();
}
}
namespace gtsam {
/* ************************************************************************* */

16
gtsam/inference/EliminateableFactorGraph.h
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@ -139,7 +139,7 @@ namespace gtsam {
OptionalVariableIndex variableIndex = {}) 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, dependeing on
* provided, the ordering will be computed using either COLAMD or METIS, depending on
* the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
*
* <b> Example - Full Cholesky elimination in COLAMD order: </b>
@ -160,7 +160,7 @@ namespace gtsam {
OptionalVariableIndex variableIndex = {}) 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, dependeing on
* provided, the ordering will be computed using either COLAMD or METIS, depending on
* the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
*
* <b> Example - Full QR elimination in specified order:
@ -273,8 +273,7 @@ namespace gtsam {
* COLAMD marginalization order by default
* @param variables Determines the *ordered* variables whose marginal to compute,
* will be ordered in the returned BayesNet.
* @param function Optional dense elimination function, if not provided the default will be
* used.
* @param function Optional dense elimination function..
* @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
* provided one will be computed. */
std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@ -286,8 +285,7 @@ namespace gtsam {
* COLAMD marginalization order by default
* @param variables Determines the variables whose marginal to compute,
* will be ordered using constrained COLAMD.
* @param function Optional dense elimination function, if not provided the default will be
* used.
* @param function Optional dense elimination function..
* @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
* provided one will be computed. */
std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@ -300,8 +298,7 @@ namespace gtsam {
* will be ordered in the returned BayesNet.
* @param marginalizedVariableOrdering Ordering for the variables being marginalized out,
* i.e. all variables not in \c variables.
* @param function Optional dense elimination function, if not provided the default will be
* used.
* @param function Optional dense elimination function..
* @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
* provided one will be computed. */
std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@ -315,8 +312,7 @@ namespace gtsam {
* will be ordered using constrained COLAMD.
* @param marginalizedVariableOrdering Ordering for the variables being marginalized out,
* i.e. all variables not in \c variables.
* @param function Optional dense elimination function, if not provided the default will be
* used.
* @param function Optional dense elimination function..
* @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
* provided one will be computed. */
std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(

2
gtsam/nonlinear/ExtendedKalmanFilter-inl.h
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@ -38,7 +38,7 @@ namespace gtsam {
Ordering lastKeyAsOrdering;
lastKeyAsOrdering += lastKey;
const GaussianConditional::shared_ptr marginal =
linearFactorGraph.marginalMultifrontalBayesNet(std::cref(lastKeyAsOrdering))->front();
linearFactorGraph.marginalMultifrontalBayesNet(lastKeyAsOrdering)->front();
// Extract the current estimate of x1,P1
VectorValues result = marginal->solve(VectorValues());