Jacobian using Auto-Diff Codegeneration. More...

#include <DerivativesCppadJIT.h>

Inheritance diagram for ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >:

Public Types
using	CG_SCALAR = ADCGScalar
	CG_SCALAR type. More...

using	CG_VALUE_TYPE = ADCGValueType
	autodiff scalar type More...

using	IN_TYPE_CG = Eigen::Matrix< CG_SCALAR, IN_DIM, 1 >
	function input vector type More...

using	OUT_TYPE_CG = Eigen::Matrix< CG_SCALAR, OUT_DIM, 1 >
	function output vector type More...

using	IN_TYPE_D = Eigen::Matrix< double, IN_DIM, 1 >
	function input vector type double More...

using	OUT_TYPE_D = Eigen::Matrix< double, OUT_DIM, 1 >
	function output vector type More...

using	JAC_TYPE_D = Eigen::Matrix< double, OUT_DIM, IN_DIM >
	Jacobian type. More...

using	JAC_TYPE_ROW_MAJOR = Eigen::Matrix< double, OUT_DIM, IN_DIM, Eigen::RowMajor >
	Jac. type in row-major. More...

using	HES_TYPE_D = Eigen::Matrix< double, IN_DIM, IN_DIM >

using	HES_TYPE_ROW_MAJOR = Eigen::Matrix< double, IN_DIM, IN_DIM, Eigen::RowMajor >

using	FUN_TYPE_CG = std::function< OUT_TYPE_CG(const IN_TYPE_CG &)>
	function type More...

using	DerivativesBase = Derivatives< IN_DIM, OUT_DIM >

Public Types inherited from ct::core::Derivatives< IN_DIM, OUT_DIM, double >
typedef Eigen::Matrix< double, IN_DIM, 1 >	IN_TYPE
	function input vector type More...

typedef Eigen::Matrix< double, OUT_DIM, 1 >	OUT_TYPE
	function output vector type More...

typedef Eigen::Matrix< double, OUT_DIM, IN_DIM >	JAC_TYPE

typedef Eigen::Matrix< double, IN_DIM, IN_DIM >	HES_TYPE

Public Member Functions
	DerivativesCppadJIT (FUN_TYPE_CG &f, int inputDim=IN_DIM, int outputDim=OUT_DIM)
	Contructs the derivatives for codegeneration using a FUN_TYPE_CG function. More...

	DerivativesCppadJIT (const DerivativesCppadJIT &arg)
	copy constructor More...

void	update (FUN_TYPE_CG &f, const size_t inputDim=IN_DIM, const size_t outputDim=OUT_DIM)
	update the Jacobian with a new function More...

virtual	~DerivativesCppadJIT ()=default
	destructor More...

DerivativesCppadJIT *	clone () const
	deep cloning of Jacobian More...

virtual OUT_TYPE_D	forwardZero (const Eigen::VectorXd &x)
	Evaluates the method itself. More...

virtual JAC_TYPE_D	jacobian (const Eigen::VectorXd &x)
	Evaluates the jacobian with respect to the input. More...

virtual void	sparseJacobian (const Eigen::VectorXd &x, Eigen::VectorXd &jac, Eigen::VectorXi &iRow, Eigen::VectorXi &jCol)
	Returns the evaluated jacobian in sparse format. More...

virtual Eigen::VectorXd	sparseJacobianValues (const Eigen::VectorXd &x)
	Returns the non zero values of the jacobian. More...

virtual HES_TYPE_D	hessian (const Eigen::VectorXd &x, const Eigen::VectorXd &lambda)
	Evaluates the hessian (2nd order derivatives with respect to input) of the method. In case of a vector valued function, the method returns the weighted sum of the hessians with weights w. More...

virtual void	sparseHessian (const Eigen::VectorXd &x, const Eigen::VectorXd &lambda, Eigen::VectorXd &hes, Eigen::VectorXi &iRow, Eigen::VectorXi &jCol)
	Returns the weighted sum of hessian of the problem in sparse format. More...

virtual Eigen::VectorXd	sparseHessianValues (const Eigen::VectorXd &x, const Eigen::VectorXd &lambda)
	Returns the non zero elements of the hessian of the problem. More...

Eigen::Matrix< bool, Eigen::Dynamic, Eigen::Dynamic >	getSparsityPatternJacobian ()
	get Jacobian sparsity pattern More...

Eigen::Matrix< bool, Eigen::Dynamic, Eigen::Dynamic >	getSparsityPatternHessian ()
	get Hessian sparsity pattern More...

void	getSparsityPatternJacobian (Eigen::VectorXi &rows, Eigen::VectorXi &columns)
	get Jacobian sparsity pattern More...

size_t	getNumNonZerosJacobian ()
	Returns the number of nonzeros in the sparse jacobian. More...

size_t	getNumNonZerosHessian ()
	Returns the number of nonzeros in the sparse hessian. More...

void	getSparsityPatternHessian (Eigen::VectorXi &rows, Eigen::VectorXi &columns)
	get Hessian sparsity pattern More...

void	compileJIT (const DerivativesCppadSettings &settings, const std::string &libName="unnamedLib", bool verbose=false)
	Uses just-in-time compilation to compile the Jacobian and other derivatives. More...

const std::shared_ptr< CppAD::cg::DynamicLib< double > >	getDynamicLib ()
	retrieve the dynamic library, e.g. for testing purposes More...

Public Member Functions inherited from ct::core::Derivatives< IN_DIM, OUT_DIM, double >
	Derivatives ()

virtual	~Derivatives ()
	default destructor More...

Protected Member Functions
void	recordCg ()
	record the Auto-Diff terms for code generation More...

Protected Attributes
std::function< OUT_TYPE_CG(const IN_TYPE_CG &)>	cgStdFun_

int	inputDim_
	the function More...

int	outputDim_
	function input dimension More...

CppAD::ADFun< CG_VALUE_TYPE >	cgCppadFun_
	function output dimension More...

bool	compiled_
	auto-diff function More...

std::string	libName_
	flag if Jacobian is compiled More...

std::vector< size_t >	sparsityRowsJacobian_
	a unique name for this library More...

std::vector< size_t >	sparsityColsJacobian_

std::vector< size_t >	sparsityRowsHessian_

std::vector< size_t >	sparsityColsHessian_

Eigen::VectorXi	sparsityRowsJacobianEigen_

Eigen::VectorXi	sparsityColsJacobianEigen_

Eigen::VectorXi	sparsityRowsHessianEigen_

Eigen::VectorXi	sparsityColsHessianEigen_

CppAD::cg::GccCompiler< double >	compiler_

CppAD::cg::ClangCompiler< double >	compilerClang_
	compile for codegeneration More...

std::shared_ptr< CppAD::cg::DynamicLib< double > >	dynamicLib_

std::shared_ptr< CppAD::cg::GenericModel< double > >	model_
	dynamic library to load after compilation More...

Detailed Description

template<int IN_DIM, int OUT_DIM>
class ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >

Jacobian using Auto-Diff Codegeneration.

Uses Auto-Diff code generation to compute the Jacobian $J(x_s) = \frac{df}{dx} |_{x=x_s}$ of a regular vector-valued mathematical function $ y = f(x) $ .

x has IN_DIM dimension and y has OUT_DIM dimension. Thus, they can be scalar functions (IN_DIM = 1, OUT_DIM = 1), fixed or variable size (IN_DIM = -1, OUT_DIM = -1) functions.

Note: In fact, this class is called Jacobian but computes also zero order derivatives

Template Parameters

IN_DIM	Input dimensionality of the function (use Eigen::Dynamic (-1) for dynamic size)
OUT_DIM	Output dimensionailty of the function (use Eigen::Dynamic (-1) for dynamic size)

Member Typedef Documentation

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::CG_SCALAR = ADCGScalar

CG_SCALAR type.

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::CG_VALUE_TYPE = ADCGValueType

autodiff scalar type

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::IN_TYPE_CG = Eigen::Matrix<CG_SCALAR, IN_DIM, 1>

function input vector type

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::OUT_TYPE_CG = Eigen::Matrix<CG_SCALAR, OUT_DIM, 1>

function output vector type

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::IN_TYPE_D = Eigen::Matrix<double, IN_DIM, 1>

function input vector type double

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::OUT_TYPE_D = Eigen::Matrix<double, OUT_DIM, 1>

function output vector type

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::JAC_TYPE_D = Eigen::Matrix<double, OUT_DIM, IN_DIM>

Jacobian type.

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::JAC_TYPE_ROW_MAJOR = Eigen::Matrix<double, OUT_DIM, IN_DIM, Eigen::RowMajor>

Jac. type in row-major.

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::HES_TYPE_D = Eigen::Matrix<double, IN_DIM, IN_DIM>

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::HES_TYPE_ROW_MAJOR = Eigen::Matrix<double, IN_DIM, IN_DIM, Eigen::RowMajor>

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::FUN_TYPE_CG = std::function<OUT_TYPE_CG(const IN_TYPE_CG&)>

function type

template<int IN_DIM, int OUT_DIM>

using ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::DerivativesBase = Derivatives<IN_DIM, OUT_DIM>

Constructor & Destructor Documentation

template<int IN_DIM, int OUT_DIM>

ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::DerivativesCppadJIT	(	FUN_TYPE_CG &	f,
		int	inputDim = `IN_DIM`,
		int	outputDim = `OUT_DIM`
	)

inline

Contructs the derivatives for codegeneration using a FUN_TYPE_CG function.

Warning: If IN_DIM and/our OUT_DIM are set to dynamic (-1), then the actual dimensions of x and y have to be passed here.

Parameters

	f	The function to be autodiffed
[in]	inputDim	inputDim input dimension, must be specified if template parameter IN_DIM is -1 (dynamic)
[in]	outputDim	outputDim output dimension, must be specified if template parameter IN_DIM is -1 (dynamic)

template<int IN_DIM, int OUT_DIM>

ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::DerivativesCppadJIT ( const DerivativesCppadJIT< IN_DIM, OUT_DIM > & arg )

inline

copy constructor

Parameters

arg	instance to copy

Note: It is important to not only copy the pointer to the dynamic library, but to load the library properly instead.

template<int IN_DIM, int OUT_DIM>

virtual ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::~DerivativesCppadJIT ( )

virtualdefault

destructor

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

Member Function Documentation

template<int IN_DIM, int OUT_DIM>

void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::update	(	FUN_TYPE_CG &	f,
		const size_t	inputDim = `IN_DIM`,
		const size_t	outputDim = `OUT_DIM`
	)

inline

update the Jacobian with a new function

Warning: If IN_DIM and/our OUT_DIM are set to dynamic (-1), then the actual dimensions of x and y have to be passed here.

Parameters

f	new function to compute Jacobian of
inputDim	input dimension, must be specified if template parameter IN_DIM is -1 (dynamic)
outputDim	output dimension, must be specified if template parameter IN_DIM is -1 (dynamic)

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::DerivativesCppadJIT().

template<int IN_DIM, int OUT_DIM>

DerivativesCppadJIT* ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::clone ( ) const

inlinevirtual

deep cloning of Jacobian

Implements ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual OUT_TYPE_D ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::forwardZero ( const Eigen::VectorXd & x )

inlinevirtual

Evaluates the method itself.

Parameters

[in] x The point of evaluation

Returns: The evalution of the method

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual JAC_TYPE_D ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::jacobian ( const Eigen::VectorXd & x )

inlinevirtual

Evaluates the jacobian with respect to the input.

Parameters

[in] x The point of evaluation

Returns: The evaluated jacobian

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparseJacobian	(	const Eigen::VectorXd &	x,
		Eigen::VectorXd &	jac,
		Eigen::VectorXi &	iRow,
		Eigen::VectorXi &	jCol
	)

inlinevirtual

Returns the evaluated jacobian in sparse format.

Parameters

[in]	x	The point of evaluation
[out]	jac	The non zero values of the jacobian
[out]	iRow	The row indices of the non zero values
[out]	jCol	The column indices of the non zero values

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual Eigen::VectorXd ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparseJacobianValues ( const Eigen::VectorXd & x )

inlinevirtual

Returns the non zero values of the jacobian.

Parameters

[in] x The point of evaluation

Returns: The non zeros values of the jacobian

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual HES_TYPE_D ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::hessian	(	const Eigen::VectorXd &	x,
		const Eigen::VectorXd &	lambda
	)

inlinevirtual

Evaluates the hessian (2nd order derivatives with respect to input) of the method. In case of a vector valued function, the method returns the weighted sum of the hessians with weights w.

Parameters

[in]	x	The point of evaluation
[in]	lambda	The weights of the sum

Returns: The evaluated hessian

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::hessian().

template<int IN_DIM, int OUT_DIM>

virtual void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparseHessian	(	const Eigen::VectorXd &	x,
		const Eigen::VectorXd &	lambda,
		Eigen::VectorXd &	hes,
		Eigen::VectorXi &	iRow,
		Eigen::VectorXi &	jCol
	)

inlinevirtual

Returns the weighted sum of hessian of the problem in sparse format.

Parameters

[in]	x	The point of evaluation
[in]	lambda	The weights of the sum of the hessian
	hes	The non zero values of the hessian
	iRow	The row indices of the non zero values
	jCol	The column indices of the non zero values

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

virtual Eigen::VectorXd ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparseHessianValues	(	const Eigen::VectorXd &	x,
		const Eigen::VectorXd &	lambda
	)

inlinevirtual

Returns the non zero elements of the hessian of the problem.

Parameters

[in]	x	The point of evaluation
[in]	lambda	The weights of the sum of the hessian

Returns: { description_of_the_return_value }

Reimplemented from ct::core::Derivatives< IN_DIM, OUT_DIM, double >.

template<int IN_DIM, int OUT_DIM>

Eigen::Matrix<bool, Eigen::Dynamic, Eigen::Dynamic> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getSparsityPatternJacobian ( )

inline

get Jacobian sparsity pattern

Auto-Diff automatically detects the sparsity pattern of the Jacobian. This method returns the pattern.

Returns: Sparsity pattern of the Jacobian

template<int IN_DIM, int OUT_DIM>

Eigen::Matrix<bool, Eigen::Dynamic, Eigen::Dynamic> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getSparsityPatternHessian ( )

inline

get Hessian sparsity pattern

Returns: Auto-diff automatically detects the sparsity pattern of the Hessian

template<int IN_DIM, int OUT_DIM>

void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getSparsityPatternJacobian	(	Eigen::VectorXi &	rows,
		Eigen::VectorXi &	columns
	)

inline

get Jacobian sparsity pattern

Auto-Diff automatically detects the sparsity pattern of the Jacobian. This method returns the pattern in row-column format. Row and columns contain the indeces of all non-zero entries.

Parameters

rows	row indeces of non-zero entries
columns	column indeces of non-zero entries

template<int IN_DIM, int OUT_DIM>

size_t ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getNumNonZerosJacobian ( )

inline

Returns the number of nonzeros in the sparse jacobian.

Returns: The number of nonzeros in the sparse jacobian

template<int IN_DIM, int OUT_DIM>

size_t ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getNumNonZerosHessian ( )

inline

Returns the number of nonzeros in the sparse hessian.

Returns: The number of non zeros in the sparse hessian

template<int IN_DIM, int OUT_DIM>

void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getSparsityPatternHessian	(	Eigen::VectorXi &	rows,
		Eigen::VectorXi &	columns
	)

inline

get Hessian sparsity pattern

Auto-Diff automatically detects the sparsity pattern of the Jacobian. This method returns the pattern in row-column format. Row and columns contain the indeces of all non-zero entries.

Parameters

rows	row indeces of non-zero entries
columns	column indeces of non-zero entries

template<int IN_DIM, int OUT_DIM>

void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::compileJIT	(	const DerivativesCppadSettings &	settings,
		const std::string &	libName = `"unnamedLib"`,
		bool	verbose = `false`
	)

inline

Uses just-in-time compilation to compile the Jacobian and other derivatives.

This method generates source code for the Jacobian and zero order derivative. It then compiles the source code to a dynamically loadable library that then gets loaded.

template<int IN_DIM, int OUT_DIM>

const std::shared_ptr<CppAD::cg::DynamicLib<double> > ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::getDynamicLib ( )

inline

retrieve the dynamic library, e.g. for testing purposes

template<int IN_DIM, int OUT_DIM>

void ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::recordCg ( )

inlineprotected

record the Auto-Diff terms for code generation

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

Member Data Documentation

template<int IN_DIM, int OUT_DIM>

std::function<OUT_TYPE_CG(const IN_TYPE_CG&)> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::cgStdFun_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::recordCg(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

template<int IN_DIM, int OUT_DIM>

int ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::inputDim_

protected

the function

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternHessian(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternJacobian(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::recordCg(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

template<int IN_DIM, int OUT_DIM>

int ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::outputDim_

protected

function input dimension

template<int IN_DIM, int OUT_DIM>

CppAD::ADFun<CG_VALUE_TYPE> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::cgCppadFun_

protected

function output dimension

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::DerivativesCppadJIT(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::recordCg().

template<int IN_DIM, int OUT_DIM>

bool ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::compiled_

protected

auto-diff function

template<int IN_DIM, int OUT_DIM>

std::string ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::libName_

protected

flag if Jacobian is compiled

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::DerivativesCppadJIT(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

template<int IN_DIM, int OUT_DIM>

std::vector<size_t> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityRowsJacobian_

protected

a unique name for this library

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getNumNonZerosJacobian(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobianValues().

template<int IN_DIM, int OUT_DIM>

std::vector<size_t> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityColsJacobian_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobianValues().

template<int IN_DIM, int OUT_DIM>

std::vector<size_t> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityRowsHessian_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getNumNonZerosHessian(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessianValues().

template<int IN_DIM, int OUT_DIM>

std::vector<size_t> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityColsHessian_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessianValues().

template<int IN_DIM, int OUT_DIM>

Eigen::VectorXi ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityRowsJacobianEigen_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternJacobian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobian().

template<int IN_DIM, int OUT_DIM>

Eigen::VectorXi ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityColsJacobianEigen_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternJacobian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseJacobian().

template<int IN_DIM, int OUT_DIM>

Eigen::VectorXi ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityRowsHessianEigen_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternHessian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessian().

template<int IN_DIM, int OUT_DIM>

Eigen::VectorXi ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::sparsityColsHessianEigen_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getSparsityPatternHessian(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::sparseHessian().

template<int IN_DIM, int OUT_DIM>

CppAD::cg::GccCompiler<double> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::compiler_

protected

template<int IN_DIM, int OUT_DIM>

CppAD::cg::ClangCompiler<double> ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::compilerClang_

protected

compile for codegeneration

template<int IN_DIM, int OUT_DIM>

std::shared_ptr<CppAD::cg::DynamicLib<double> > ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::dynamicLib_

protected

Referenced by ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::compileJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::DerivativesCppadJIT(), ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::getDynamicLib(), and ct::core::DerivativesCppadJIT< STATE_DIM+CONTROL_DIM+1, 1 >::update().

template<int IN_DIM, int OUT_DIM>

std::shared_ptr<CppAD::cg::GenericModel<double> > ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >::model_

protected

dynamic library to load after compilation

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

/home/adrl/code/src/control-toolbox/ct_core/include/ct/core/math/DerivativesCppadJIT.h

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<int IN_DIM, int OUT_DIM> class ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<int IN_DIM, int OUT_DIM>
class ct::core::DerivativesCppadJIT< IN_DIM, OUT_DIM >