11 #include <gtsam/inference/Symbol.h> 15 class GaussianBayesNet;
20 template<
size_t D,
size_t ZDim>
24 typedef Eigen::Matrix<double, ZDim, D> MatrixZD;
32 const std::vector<MatrixZD, Eigen::aligned_allocator<MatrixZD> >& FBlocks,
const Matrix& E,
const Matrix3& P,
34 const SharedDiagonal& model = SharedDiagonal()) :
39 for (
size_t k = 0; k < FBlocks.size(); ++k) {
41 gfg.
add(pointKey, E.block<ZDim, 3>(ZDim * k, 0), key, FBlocks[k],
42 b.segment < ZDim > (ZDim * k), model);
48 variables.push_back(pointKey);
friend GTSAM_EXPORT std::pair< std::shared_ptr< GaussianConditional >, shared_ptr > EliminateQR(const GaussianFactorGraph &factors, const Ordering &keys)
std::pair< std::shared_ptr< BayesNetType >, std::shared_ptr< FactorGraphType > > eliminatePartialSequential(const Ordering &ordering, const Eliminate &function=EliminationTraitsType::DefaultEliminate, OptionalVariableIndex variableIndex={}) const
Definition: EliminateableFactorGraph-inst.h:149
JacobianFactorQR(const KeyVector &keys, const std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > > &FBlocks, const Matrix &E, const Matrix3 &P, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
Definition: JacobianFactorQR.h:31
void add(const GaussianFactor &factor)
Definition: GaussianFactorGraph.h:125
JacobianFactor class with fixed sized blcoks.
Linear Factor Graph where all factors are Gaussians.
Definition: chartTesting.h:28
Definition: RegularJacobianFactor.h:32
FastVector< Key > KeyVector
Define collection type once and for all - also used in wrappers.
Definition: Key.h:86
Definition: JacobianFactorQR.h:21
const KeyVector & keys() const
Access the factor's involved variable keys.
Definition: Factor.h:142
std::uint64_t Key
Integer nonlinear key type.
Definition: types.h:102
Definition: GaussianFactorGraph.h:73