gtsam::Basis< DERIVED >::VectorDerivativeFunctor< M > Class Template Reference

Detailed Description

template<typename DERIVED>
template<int M>
class gtsam::Basis< DERIVED >::VectorDerivativeFunctor< M >

VectorDerivativeFunctor at a given x, applied to ParameterMatrix<M>.

This functor is used to evaluate the derivatives of a parameterized function at a given scalar value x. When given a specific M*N parameters, returns an M-vector the M corresponding function derivatives at x, possibly with Jacobians wrpt the parameters.

Inheritance diagram for gtsam::Basis< DERIVED >::VectorDerivativeFunctor< M >:

Public Member Functions
EIGEN_MAKE_ALIGNED_OPERATOR_NEW	VectorDerivativeFunctor ()
	For serialization.
	VectorDerivativeFunctor (size_t N, double x)
	Default Constructor.
	VectorDerivativeFunctor (size_t N, double x, double a, double b)
	Constructor, with optional interval [a,b].
VectorM	apply (const ParameterMatrix< M > &P, OptionalJacobian< -1, -1 > H=boost::none) const
VectorM	operator() (const ParameterMatrix< M > &P, OptionalJacobian< -1, -1 > H=boost::none) const
	c++ sugar

Protected Types
using	VectorM = Eigen::Matrix< double, M, 1 >
using	Jacobian = Eigen::Matrix< double, M, -1 >

Protected Member Functions
void	calculateJacobian ()
	Calculate the M*(M*N) Jacobian of this functor with respect to the M*N parameter matrix P. More...
Protected Member Functions inherited from gtsam::Basis< DERIVED >::DerivativeFunctorBase
	DerivativeFunctorBase ()
	For serialization.
	DerivativeFunctorBase (size_t N, double x)
	DerivativeFunctorBase (size_t N, double x, double a, double b)
void	print (const std::string &s="") const

Protected Attributes
Jacobian	H_
Protected Attributes inherited from gtsam::Basis< DERIVED >::DerivativeFunctorBase
Weights	weights_

Member Function Documentation

calculateJacobian()

template<typename DERIVED >

template<int M>

void gtsam::Basis< DERIVED >::VectorDerivativeFunctor< M >::calculateJacobian ( )

inlineprotected

Calculate the M*(M*N) Jacobian of this functor with respect to the M*N parameter matrix P.

We flatten assuming column-major order, e.g., if N=3 and M=2, we have H =[ w(0) 0 w(1) 0 w(2) 0 0 w(0) 0 w(1) 0 w(2) ] i.e., the Kronecker product of weights_ with the MxM identity matrix.

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The documentation for this class was generated from the following file:

• /Users/dellaert/git/github/gtsam/basis/Basis.h