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34 template <
typename FUNCTOR,
int M,
int N1,
int N2>
57 double rowMajor1[
M * N1] = {}, rowMajor2[
M * N2] = {};
58 double* jacobians[] = {rowMajor1, rowMajor2};
59 success = AutoDiff<FUNCTOR, double, N1, N2>::Differentiate(
73 throw std::runtime_error(
74 "AdaptAutoDiff: function call resulted in failure");
Eigen::Matrix< double, N2, 1 > Vector2
Eigen::Matrix< double, M, N2, Eigen::RowMajor > RowMajor2
Eigen::Matrix< double, M, 1 > VectorT
static ConjugateGradientParameters parameters
VectorT operator()(const Vector1 &v1, const Vector2 &v2, OptionalJacobian< M, N1 > H1={}, OptionalJacobian< M, N2 > H2={})
Special class for optional Jacobian arguments.
A matrix or vector expression mapping an existing array of data.
The matrix class, also used for vectors and row-vectors.
Eigen::Matrix< double, M, N1, Eigen::RowMajor > RowMajor1
Eigen::Matrix< double, N1, 1 > Vector1
Matrix< RealScalar, Dynamic, Dynamic > M
gtsam
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autogenerated on Sun Dec 22 2024 04:11:05