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Define and use move constructor

release/4.3a0
Frank Dellaert 2025-01-25 15:31:55 -05:00
parent d3cd876cf9
commit 85b457f1e3
3 changed files with 36 additions and 9 deletions
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6
gtsam/linear/GaussianConditional-inl.h
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@ -33,4 +33,10 @@ namespace gtsam {
const KEYS& keys, size_t nrFrontals, const VerticalBlockMatrix& augmentedMatrix, const SharedDiagonal& sigmas) : const KEYS& keys, size_t nrFrontals, const VerticalBlockMatrix& augmentedMatrix, const SharedDiagonal& sigmas) :
BaseFactor(keys, augmentedMatrix, sigmas), BaseConditional(nrFrontals) {} BaseFactor(keys, augmentedMatrix, sigmas), BaseConditional(nrFrontals) {}
/* ************************************************************************* */
template<typename KEYS>
GaussianConditional::GaussianConditional(
const KEYS& keys, size_t nrFrontals, VerticalBlockMatrix&& augmentedMatrix, const SharedDiagonal& sigmas) :
BaseFactor(keys, std::move(augmentedMatrix), sigmas), BaseConditional(nrFrontals) {}
} // gtsam } // gtsam

33
gtsam/linear/GaussianConditional.h
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@ -75,13 +75,34 @@ namespace gtsam {
size_t nrFrontals, const Vector& d, size_t nrFrontals, const Vector& d,
const SharedDiagonal& sigmas = SharedDiagonal()); const SharedDiagonal& sigmas = SharedDiagonal());
/** Constructor with arbitrary number keys, and where the augmented matrix is given all together /**
* instead of in block terms. Note that only the active view of the provided augmented matrix * @brief Constructor with an arbitrary number of keys, where the augmented matrix
* is used, and that the matrix data is copied into a newly-allocated matrix in the constructed * is given all together instead of in block terms.
* factor. */ *
* @tparam KEYS Type of the keys container.
* @param keys Container of keys.
* @param nrFrontals Number of frontal variables.
* @param augmentedMatrix The augmented matrix containing the coefficients.
* @param sigmas Optional noise model (default is an empty SharedDiagonal).
*/
template <typename KEYS> template <typename KEYS>
GaussianConditional( GaussianConditional(const KEYS& keys, size_t nrFrontals,
const KEYS& keys, size_t nrFrontals, const VerticalBlockMatrix& augmentedMatrix, const VerticalBlockMatrix& augmentedMatrix,
const SharedDiagonal& sigmas = SharedDiagonal());
/**
* @brief Constructor with an arbitrary number of keys, where the augmented matrix
* is given all together instead of in block terms, using move semantics for efficiency.
*
* @tparam KEYS Type of the keys container.
* @param keys Container of keys.
* @param nrFrontals Number of frontal variables.
* @param augmentedMatrix The augmented matrix containing the coefficients (moved).
* @param sigmas Optional noise model (default is an empty SharedDiagonal).
*/
template <typename KEYS>
GaussianConditional(const KEYS& keys, size_t nrFrontals,
VerticalBlockMatrix&& augmentedMatrix,
const SharedDiagonal& sigmas = SharedDiagonal()); const SharedDiagonal& sigmas = SharedDiagonal());
/// Construct from mean `mu` and standard deviation `sigma`. /// Construct from mean `mu` and standard deviation `sigma`.

2
gtsam/linear/HessianFactor.cpp
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@ -470,7 +470,7 @@ std::shared_ptr<GaussianConditional> HessianFactor::eliminateCholesky(const Orde
// TODO(frank): pre-allocate GaussianConditional and write into it // TODO(frank): pre-allocate GaussianConditional and write into it
const VerticalBlockMatrix Ab = info_.split(nFrontals); const VerticalBlockMatrix Ab = info_.split(nFrontals);
conditional = std::make_shared<GaussianConditional>(keys_, nFrontals, Ab); conditional = std::make_shared<GaussianConditional>(keys_, nFrontals, std::move(Ab));
// Erase the eliminated keys in this factor // Erase the eliminated keys in this factor
keys_.erase(begin(), begin() + nFrontals); keys_.erase(begin(), begin() + nFrontals);