#include <Basis.h>
Public Member Functions | |
T | apply (const Matrix &P, OptionalJacobian< -1, -1 > H={}) const |
Manifold evaluation. More... | |
ManifoldEvaluationFunctor () | |
For serialization. More... | |
ManifoldEvaluationFunctor (size_t N, double x) | |
Default Constructor. More... | |
ManifoldEvaluationFunctor (size_t N, double x, double a, double b) | |
Constructor, with interval [a,b]. More... | |
T | operator() (const Matrix &P, OptionalJacobian< -1, -1 > H={}) const |
c++ sugar More... | |
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Vector | apply (const Matrix &P, OptionalJacobian< -1, -1 > H={}) const |
M-dimensional evaluation. More... | |
Vector | operator() (const Matrix &P, OptionalJacobian< -1, -1 > H={}) const |
c++ sugar More... | |
EIGEN_MAKE_ALIGNED_OPERATOR_NEW | VectorEvaluationFunctor () |
For serialization. More... | |
VectorEvaluationFunctor (size_t M, size_t N, double x) | |
Default Constructor. More... | |
VectorEvaluationFunctor (size_t M, size_t N, double x, double a, double b) | |
Constructor, with interval [a,b]. More... | |
Private Types | |
using | Base = VectorEvaluationFunctor |
Static Private Attributes | |
constexpr static auto | M = traits<T>::dimension |
Additional Inherited Members | |
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using | Jacobian = Eigen::Matrix< double, -1, -1 > |
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void | calculateJacobian () |
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double | apply (const typename DERIVED::Parameters &p, OptionalJacobian<-1, -1 > H={}) const |
Regular 1D evaluation. More... | |
EvaluationFunctor () | |
For serialization. More... | |
EvaluationFunctor (size_t N, double x) | |
Constructor with interval [a,b]. More... | |
EvaluationFunctor (size_t N, double x, double a, double b) | |
Constructor with interval [a,b]. More... | |
double | operator() (const typename DERIVED::Parameters &p, OptionalJacobian<-1, -1 > H={}) const |
c++ sugar More... | |
void | print (const std::string &s="") const |
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Jacobian | H_ |
size_t | M_ |
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Weights | weights_ |
Manifold EvaluationFunctor at a given x, applied to a parameter Matrix. This functor is used to evaluate a parameterized function at a given scalar value x. When given a specific M*N parameters, returns an M-vector the M corresponding functions at x, possibly with Jacobians wrpt the parameters.
The difference with the VectorEvaluationFunctor is that after computing the M*1 vector xi=F(x;P), with x a scalar and P the M*N parameter vector, we also retract xi back to the T manifold. For example, if T==Rot3, then we first compute a 3-vector xi using x and P, and then map that 3-vector xi back to the Rot3 manifold, yielding a valid 3D rotation.
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