Public Member Functions | |
| GenericModel (GenericModel &&other) noexcept | |
| virtual const std::string & | getName () const =0 |
| virtual bool | isJacobianSparsityAvailable ()=0 |
| virtual std::vector< std::set< size_t > > | JacobianSparsitySet ()=0 |
| virtual std::vector< bool > | JacobianSparsityBool ()=0 |
| virtual void | JacobianSparsity (std::vector< size_t > &equations, std::vector< size_t > &variables)=0 |
| virtual bool | isHessianSparsityAvailable ()=0 |
| virtual std::vector< std::set< size_t > > | HessianSparsitySet ()=0 |
| virtual std::vector< bool > | HessianSparsityBool ()=0 |
| virtual void | HessianSparsity (std::vector< size_t > &rows, std::vector< size_t > &cols)=0 |
| virtual bool | isEquationHessianSparsityAvailable ()=0 |
| virtual std::vector< std::set< size_t > > | HessianSparsitySet (size_t i)=0 |
| virtual std::vector< bool > | HessianSparsityBool (size_t i)=0 |
| virtual void | HessianSparsity (size_t i, std::vector< size_t > &rows, std::vector< size_t > &cols)=0 |
| virtual size_t | Domain () const =0 |
| virtual size_t | Range () const =0 |
| virtual const std::vector< std::string > & | getAtomicFunctionNames ()=0 |
| virtual bool | addAtomicFunction (atomic_base< Base > &atomic)=0 |
| virtual bool | addExternalModel (GenericModel< Base > &atomic)=0 |
| void | setAtomicEvalForwardOne4CppAD (bool evalForwardOne4CppAD) |
| bool | isAtomicEvalForwardOne4CppAD () const |
| virtual bool | isForwardZeroAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | ForwardZero (const VectorBase &x) |
| virtual void | ForwardZero (const CppAD::vector< bool > &vx, CppAD::vector< bool > &vy, ArrayView< const Base > tx, ArrayView< Base > ty)=0 |
| template<typename VectorBase > | |
| void | ForwardZero (const VectorBase &x, VectorBase &dep) |
| virtual void | ForwardZero (ArrayView< const Base > x, ArrayView< Base > dep)=0 |
| virtual void | ForwardZero (const std::vector< const Base *> &x, ArrayView< Base > dep)=0 |
| virtual bool | isJacobianAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | Jacobian (const VectorBase &x) |
| template<typename VectorBase > | |
| void | Jacobian (const VectorBase &x, VectorBase &jac) |
| virtual void | Jacobian (ArrayView< const Base > x, ArrayView< Base > jac)=0 |
| virtual bool | isHessianAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | Hessian (const VectorBase &x, const VectorBase &w) |
| template<typename VectorBase > | |
| void | Hessian (const VectorBase &x, const VectorBase &w, VectorBase &hess) |
| template<typename VectorBase > | |
| VectorBase | Hessian (const VectorBase &x, size_t i) |
| virtual void | Hessian (ArrayView< const Base > x, ArrayView< const Base > w, ArrayView< Base > hess)=0 |
| virtual bool | isForwardOneAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | ForwardOne (const VectorBase &tx) |
| virtual void | ForwardOne (ArrayView< const Base > tx, ArrayView< Base > ty)=0 |
| virtual bool | isSparseForwardOneAvailable ()=0 |
| virtual void | ForwardOne (ArrayView< const Base > x, size_t tx1Nnz, const size_t idx[], const Base tx1[], ArrayView< Base > ty1)=0 |
| virtual bool | isReverseOneAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | ReverseOne (const VectorBase &tx, const VectorBase &ty, const VectorBase &py) |
| template<typename VectorBase > | |
| void | ReverseOne (const VectorBase &tx, const VectorBase &ty, VectorBase &px, const VectorBase &py) |
| virtual bool | isSparseReverseOneAvailable ()=0 |
| virtual void | ReverseOne (ArrayView< const Base > tx, ArrayView< const Base > ty, ArrayView< Base > px, ArrayView< const Base > py)=0 |
| virtual void | ReverseOne (ArrayView< const Base > x, ArrayView< Base > px, size_t pyNnz, const size_t idx[], const Base py[])=0 |
| virtual bool | isReverseTwoAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | ReverseTwo (const VectorBase &tx, const VectorBase &ty, const VectorBase &py) |
| template<typename VectorBase > | |
| void | ReverseTwo (const VectorBase &tx, const VectorBase &ty, VectorBase &px, const VectorBase &py) |
| virtual bool | isSparseReverseTwoAvailable ()=0 |
| virtual void | ReverseTwo (ArrayView< const Base > tx, ArrayView< const Base > ty, ArrayView< Base > px, ArrayView< const Base > py)=0 |
| virtual void | ReverseTwo (ArrayView< const Base > x, size_t tx1Nnz, const size_t idx[], const Base tx1[], ArrayView< Base > px2, ArrayView< const Base > py2)=0 |
| virtual bool | isSparseJacobianAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | SparseJacobian (const VectorBase &x) |
| template<typename VectorBase > | |
| void | SparseJacobian (const VectorBase &x, VectorBase &jac) |
| virtual void | SparseJacobian (ArrayView< const Base > x, ArrayView< Base > jac)=0 |
| virtual void | SparseJacobian (const std::vector< Base > &x, std::vector< Base > &jac, std::vector< size_t > &row, std::vector< size_t > &col)=0 |
| virtual void | SparseJacobian (ArrayView< const Base > x, ArrayView< Base > jac, size_t const **row, size_t const **col)=0 |
| virtual void | SparseJacobian (const std::vector< const Base *> &x, ArrayView< Base > jac, size_t const **row, size_t const **col)=0 |
| virtual bool | isSparseHessianAvailable ()=0 |
| template<typename VectorBase > | |
| VectorBase | SparseHessian (const VectorBase &x, const VectorBase &w) |
| template<typename VectorBase > | |
| void | SparseHessian (const VectorBase &x, const VectorBase &w, VectorBase &hess) |
| virtual void | SparseHessian (ArrayView< const Base > x, ArrayView< const Base > w, ArrayView< Base > hess)=0 |
| virtual void | SparseHessian (const std::vector< Base > &x, const std::vector< Base > &w, std::vector< Base > &hess, std::vector< size_t > &row, std::vector< size_t > &col)=0 |
| virtual void | SparseHessian (ArrayView< const Base > x, ArrayView< const Base > w, ArrayView< Base > hess, size_t const **row, size_t const **col)=0 |
| virtual void | SparseHessian (const std::vector< const Base *> &x, ArrayView< const Base > w, ArrayView< Base > hess, size_t const **row, size_t const **col)=0 |
| virtual CGAtomicGenericModel< Base > & | asAtomic () |
Protected Attributes | |
| CGAtomicGenericModel< Base > * | _atomic |
| bool | _evalAtomicForwardOne4CppAD |
Detailed Description
template<class Base>
class CppAD::cg::GenericModel< Base >
Abstract class used to execute a generated model
Definition at line 141 of file declare_cg.hpp.
Member Function Documentation
◆ addAtomicFunction()
|
pure virtual |
Defines a CppAD atomic function to be used as an external function by the compiled code. It should match an external function name previously provided to create the source.
- Parameters
-
atomic The atomic function. This object must only be deleted after the model.
- Returns
- true if the atomic function is required by the model, false if it will never be used.
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ addExternalModel()
|
pure virtual |
Defines a generic model to be used as an external function by the compiled code. It should match an external function name previously provided to create the source. This form should be preferred over ::addAtomicFunction whenever possible.
- Parameters
-
atomic The generic model. This object must only be deleted after the model.
- Returns
- true if the external function is required by the model, false if it will never be used.
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ asAtomic()
|
inlinevirtual |
Provides a wrapper for this compiled model allowing it to be used as an atomic function. The model must not be deleted while the atomic function is in use.
- Returns
- an atomic function wrapper for this model
Definition at line 889 of file generic_model.hpp.
◆ Domain()
|
pure virtual |
Provides the number of independent variables.
- Returns
- The number of independent variables
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), CppAD::cg::GenericModel< Base >::Hessian(), CppAD::cg::GenericModel< Base >::Jacobian(), CppAD::cg::CGAtomicGenericModel< Base >::rev_sparse_hes(), CppAD::cg::GenericModel< Base >::ReverseOne(), CppAD::cg::GenericModel< Base >::ReverseTwo(), CppAD::cg::GenericModel< Base >::SparseHessian(), and CppAD::cg::GenericModel< Base >::SparseJacobian().
◆ ForwardOne() [1/3]
|
inline |
Computes results during a forward mode sweep. Computes the first-order Taylor coefficients for dependent variables relative to a single independent variable. This method can be used during the evaluation of the jacobian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic forward mode function!
- Parameters
-
tx The Taylor coefficients of the independent variables
- Returns
- The Taylor coefficients of the dependent variables
Definition at line 429 of file generic_model.hpp.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), and CppAD::cg::GenericModelExternalFunctionWrapper< Base >::forward().
◆ ForwardOne() [2/3]
|
pure virtual |
Computes results during a forward mode sweep. Computes the first-order Taylor coefficients for dependent variables relative to a single independent variable. This method can be used during the evaluation of the jacobian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic forward mode function!
- Parameters
-
tx The Taylor coefficients of the independent variables ty The Taylor coefficients of the dependent variables
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ForwardOne() [3/3]
|
pure virtual |
Computes results during a first-order forward mode sweep, the first-order Taylor coefficients for dependent variables relative to a single independent variable. This method can be used during the evaluation of the jacobian when the model is used through a user defined external/atomic AD function. This method version avoids some data copies and can be more efficient.
- Warning
- do not used it as a generic forward mode function!
- Parameters
-
x independent variable vector tx1Nnz the number of non-zeros of the directional derivatives of the independent variables (seed directions) idx the locations of the non-zero values the partial derivatives of the dependent variables (seeds) tx1 the non-zero values of the partial derivatives of the dependent variables (seeds) ty1
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ForwardZero() [1/5]
|
inline |
Evaluates the dependent model variables (zero-order). This method considers that the generic model was prepared with a single array for the independent variables (the default behavior).
- Parameters
-
x The independent variable vector
- Returns
- The dependent variable vector
Definition at line 212 of file generic_model.hpp.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), CppAD::cg::GenericModelExternalFunctionWrapper< Base >::forward(), and CppAD::cg::GenericModel< Base >::ForwardZero().
◆ ForwardZero() [2/5]
|
pure virtual |
Evaluates the dependent model variables (zero-order). This method considers that the generic model was prepared with a single array for the independent variables (the default behavior).
- Parameters
-
vx If it is not empty then it provides which independent variables are considered as variables (not parameters) vy If vx and vy are not empty, it identifies which elements of ty are variables tx The independent variable vector ty The dependent variable vector
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ForwardZero() [3/5]
|
inline |
Evaluates the dependent model variables (zero-order). This method considers that the generic model was prepared using a single array for the independent variables (the default behavior).
- Parameters
-
x The independent variable vector dep The dependent variable vector
Definition at line 245 of file generic_model.hpp.
◆ ForwardZero() [4/5]
|
pure virtual |
Evaluates the dependent model variables (zero-order). This method considers that the generic model was prepared using a single array for the independent variables (the default behavior).
- Parameters
-
x The independent variable vector dep The dependent variable vector
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ForwardZero() [5/5]
|
pure virtual |
Determines the dependent variable values using a variable number of independent variable arrays. This method can be useful if the generic model was prepared considering that the independent variables are provided by several arrays.
- Parameters
-
x Contains the several independent variable vectors dep The values of the dependent variables
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ getAtomicFunctionNames()
|
pure virtual |
The names of the atomic functions required by this model. All external/atomic functions must be provided before using this model to compute numerical values.
- Returns
- the names of the atomic functions used by this model
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ getName()
|
pure virtual |
Provides the name for this model.
- Returns
- The model name
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::FunctorGenericModel< Base >::addExternalModel().
◆ Hessian() [1/4]
|
inline |
Determines the dense weighted sum of the Hessians using dense methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers
- Returns
- The values of the dense hessian
Definition at line 347 of file generic_model.hpp.
Referenced by CppAD::cg::GenericModel< Base >::Hessian().
◆ Hessian() [2/4]
|
inline |
Determines the dense weighted sum of the Hessians using dense methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the dense hessian
Definition at line 366 of file generic_model.hpp.
◆ Hessian() [3/4]
|
inline |
Determines the dense Hessian for a given dependent variable using dense methods.
\[ hess = \frac{{\rm d^2} F_i }{{\rm d} x^2 } (x) \]
- Parameters
-
x The independent variables i The index of the function/dependent variable
- Returns
- The values of the dense hessian for the function/dependent variable i
Definition at line 384 of file generic_model.hpp.
◆ Hessian() [4/4]
|
pure virtual |
Determines the dense weighted sum of the Hessians using dense methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the dense hessian
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ HessianSparsity()
|
pure virtual |
Provides the sparsity of the hessian for a dependent variable.
- Parameters
-
i The index of the dependent variable rows The sparsity pattern row indices. cols The sparsity pattern column indices.
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ HessianSparsityBool()
|
pure virtual |
Provides the sparsity of the hessian for a dependent variable.
- Parameters
-
i The index of the dependent variable
- Returns
- The sparsity
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ HessianSparsitySet() [1/2]
|
pure virtual |
Provides the sparsity of the sum of the hessian for each dependent variable.
- Returns
- The sparsity
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::rev_sparse_hes().
◆ HessianSparsitySet() [2/2]
|
pure virtual |
Provides the sparsity of the hessian for a dependent variable.
- Parameters
-
i The index of the dependent variable
- Returns
- The sparsity
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ isEquationHessianSparsityAvailable()
|
pure virtual |
Determines whether or not the sparsity pattern for the Hessian associated with a dependent variable can be requested.
- Returns
- true if it is possible to request the parsity pattern for the Hessians
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ isForwardOneAvailable()
|
pure virtual |
Determines whether or not the first-order forward mode dense methods can be called.
- Returns
- true if it is possible to evaluate the first-order forward mode using the dense vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::Hessian().
◆ isForwardZeroAvailable()
|
pure virtual |
Determines whether or not the model evaluation (zero-order forward mode) can be requested.
- Returns
- true if it is possible to evaluate the model
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::setAtomicEvalForwardOne4CppAD().
◆ isHessianAvailable()
|
pure virtual |
Determines whether or not the dense evaluation of the weighted sum of the Hessians can be requested.
- Returns
- true if it is possible to evaluate the dense weighted sum of the Hessians
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::Jacobian().
◆ isHessianSparsityAvailable()
|
pure virtual |
Determines whether or not the sparsity pattern for the weighted sum of the Hessians can be requested.
- Returns
- true if it is possible to request the parsity pattern for the weighted sum of the Hessians
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ isJacobianAvailable()
|
pure virtual |
Determines whether or not the dense Jacobian evaluation can be requested.
- Returns
- true if it is possible to evaluate the dense Jacobian
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ForwardZero().
◆ isJacobianSparsityAvailable()
|
pure virtual |
Determines whether or not the Jacobian sparsity pattern can be requested.
- Returns
- true if it is possible to request the Jacobian sparsity pattern
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ isReverseOneAvailable()
|
pure virtual |
Determines whether or not the first-order reverse mode dense methods can be called.
- Returns
- true if it is possible to evaluate the first-order reverse mode using the dense vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ForwardOne().
◆ isReverseTwoAvailable()
|
pure virtual |
Determines whether or not the second-order reverse mode dense methods can be called.
- Returns
- true if it is possible to evaluate the second-order reverse mode using the dense vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ReverseOne().
◆ isSparseForwardOneAvailable()
|
pure virtual |
Determines whether or not the first-order forward mode sparse method can be called.
- Returns
- true if it is possible to evaluate the first-order forward mode using the sparse vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ForwardOne().
◆ isSparseHessianAvailable()
|
pure virtual |
Determines whether or not the sparse evaluation of the weighted sum of the Hessians methods can be called.
- Returns
- true if it is possible to evaluate the sparse weighted sum of the Hessians
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::SparseJacobian().
◆ isSparseJacobianAvailable()
|
pure virtual |
Determines whether or not the sparse Jacobian evaluation methods can be called.
- Returns
- true if it is possible to evaluate the sparse Jacobian
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ReverseTwo().
◆ isSparseReverseOneAvailable()
|
pure virtual |
Determines whether or not the first-order reverse mode sparse method can be called.
- Returns
- true if it is possible to evaluate the first-order reverse mode using the sparse vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ReverseOne().
◆ isSparseReverseTwoAvailable()
|
pure virtual |
Determines whether or not the second-order reverse mode sparse methods can be called.
- Returns
- true if it is possible to evaluate the second-order reverse mode using the sparse vector format
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::GenericModel< Base >::ReverseTwo().
◆ Jacobian() [1/3]
|
inline |
Calculates a Jacobian using dense methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable vector
- Returns
- jac a dense Jacobian
Definition at line 293 of file generic_model.hpp.
Referenced by CppAD::cg::GenericModel< Base >::Jacobian().
◆ Jacobian() [2/3]
|
inline |
Calculates a Jacobian using dense methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable vector jac a dense Jacobian
Definition at line 310 of file generic_model.hpp.
◆ Jacobian() [3/3]
|
pure virtual |
Calculates a Jacobian using dense methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable vector jac a dense Jacobian
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ Range()
|
pure virtual |
Provides the number of dependent variables.
- Returns
- The number of dependent variables.
Implemented in CppAD::cg::FunctorGenericModel< Base >.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), CppAD::cg::GenericModel< Base >::ForwardOne(), CppAD::cg::GenericModel< Base >::ForwardZero(), CppAD::cg::GenericModel< Base >::Hessian(), CppAD::cg::GenericModel< Base >::Jacobian(), CppAD::cg::CGAtomicGenericModel< Base >::rev_sparse_hes(), and CppAD::cg::GenericModel< Base >::SparseJacobian().
◆ ReverseOne() [1/4]
|
inline |
Computes results during a reverse mode sweep (adjoints or partial derivatives of independent variables) for the evaluation of the jacobian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
Definition at line 511 of file generic_model.hpp.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), CppAD::cg::GenericModelExternalFunctionWrapper< Base >::reverse(), and CppAD::cg::GenericModel< Base >::ReverseOne().
◆ ReverseOne() [2/4]
|
inline |
Computes results during a reverse mode sweep (adjoints or partial derivatives of independent variables) for the evaluation of the jacobian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
Definition at line 528 of file generic_model.hpp.
◆ ReverseOne() [3/4]
|
pure virtual |
Computes results during a reverse mode sweep (adjoints or partial derivatives of independent variables) for the evaluation of the jacobian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ReverseOne() [4/4]
|
pure virtual |
Computes results during a reverse mode sweep (adjoints or partial derivatives of independent variables) for the evaluation of the jacobian when the model is used through a user defined external/atomic AD function. This method version avoids some data copies and can be more efficient.
- Warning
- do not used it as a generic reverse mode function!
- Parameters
-
x independent variable vector px partial derivatives of the independent variables (same size as x) pyNnz the number of non-zeros of the partial derivatives of the dependent variables (weight functionals) idx the locations of the non-zero values the partial derivatives of the dependent variables (weight functionals) py the non-zero values of the partial derivatives of the dependent variables (weight functionals)
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ReverseTwo() [1/4]
|
inline |
Computes second-order results during a reverse mode sweep (p = 2). This method can be used during the evaluation of the hessian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
- only the values for px[j * (k+1)] are defined, since px[j * (k+1) + 1] is not used during the hessian evaluation.
Definition at line 602 of file generic_model.hpp.
Referenced by CppAD::cg::CGAtomicGenericModel< Base >::CGAtomicGenericModel(), CppAD::cg::GenericModelExternalFunctionWrapper< Base >::reverse(), and CppAD::cg::GenericModel< Base >::ReverseTwo().
◆ ReverseTwo() [2/4]
|
inline |
Computes second-order results during a reverse mode sweep (p = 2). This method can be used during the evaluation of the hessian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
- only the values for px[j * (k+1)] are defined, since px[j * (k+1) + 1] is not used during the hessian evaluation.
Definition at line 620 of file generic_model.hpp.
◆ ReverseTwo() [3/4]
|
pure virtual |
Computes second-order results during a reverse mode sweep (p = 2). This method can be used during the evaluation of the hessian when the model is used through a user defined external/atomic AD function.
- Warning
- do not used it as a generic reverse mode function!
- only the values for px[j * (k+1)] are defined, since px[j * (k+1) + 1] is not used during the hessian evaluation.
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ ReverseTwo() [4/4]
|
pure virtual |
Computes second-order results during a reverse mode sweep (p = 2). This method can be used during the evaluation of the hessian when the model is used through a user defined external AD function. This method version avoids some data copies and can be more efficient.
- Warning
- do not used it as a generic reverse mode function!
- Parameters
-
x independent variable vector tx1Nnz the number of non-zeros of the first-order Taylor coefficients of the independents idx the locations of the non-zero values of the first-order Taylor coefficients of the independents tx1 the values of the non-zero first-order Taylor coefficients of the independents px2 second-order partials of the independents (should have the same size of x) py2 second-order partials of the dependents (should have the size of the dependent variables)
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ setAtomicEvalForwardOne4CppAD()
|
inline |
Defines whether or not to evaluate a forward mode of an atomic functions during a reverse sweep so that CppAD checks validate OK. If this model is not used within CppAD then it should be set to false.
- Parameters
-
evalForwardOne4CppAD true to perform the forward mode, false to ignore it
Definition at line 182 of file generic_model.hpp.
◆ SparseHessian() [1/6]
|
inline |
Determines the dense weighted sum of the Hessians using sparse methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers
- Returns
- The values of the dense Hessian
Definition at line 795 of file generic_model.hpp.
Referenced by CppAD::cg::GenericModel< Base >::SparseHessian().
◆ SparseHessian() [2/6]
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inline |
Determines the dense weighted sum of the Hessians using sparse methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the dense Hessian
Definition at line 814 of file generic_model.hpp.
◆ SparseHessian() [3/6]
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pure virtual |
Determines the dense weighted sum of the Hessians using sparse methods.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the dense Hessian
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseHessian() [4/6]
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pure virtual |
Determines the sparse weighted sum of the Hessians using a variable number of independent variable arrays.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the sparse hessian in the order provided by row and col row The row indices of the hessian values col The column indices of the hessian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseHessian() [5/6]
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pure virtual |
Determines the sparse weighted sum of the Hessians using a variable number of independent variable arrays.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
- Parameters
-
x The independent variables w The equation multipliers hess The values of the sparse hessian in the order provided by row and col row The row indices of the hessian values col The column indices of the hessian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseHessian() [6/6]
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pure virtual |
Determines the sparse weighted sum of the Hessians using a variable number of independent variable arrays.
\[ hess = \frac{\rm d^2 }{{\rm d} x^2 } \sum_{i} w_i F_i (x) \]
\[ i = 0 , \ldots , m - 1 \]
This method can be useful if the generic model was prepared considering that the independent variables are provided by several arrays.
- Parameters
-
x Contains the several independent variable vectors w The equation multipliers w_size The number of equations hess The values of the sparse hessian in the order provided by row and col row The row indices of the hessian values col The column indices of the hessian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseJacobian() [1/6]
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inline |
Calculates a Jacobian using sparse methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable vector
- Returns
- a dense Jacobian
Definition at line 697 of file generic_model.hpp.
Referenced by CppAD::cg::GenericModel< Base >::SparseJacobian().
◆ SparseJacobian() [2/6]
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inline |
Calculates a Jacobian using sparse methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable vector jac a vector where the dense Jacobian will be placed
Definition at line 714 of file generic_model.hpp.
◆ SparseJacobian() [3/6]
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pure virtual |
Calculates a Jacobian using sparse methods and saves it into a dense format:
\[ jac[ i n + j ] = \frac{\partial F_i( x ) }{\partial x_j } \]
\( i = 0 , \ldots , m - 1 \) and \(j = 0 , \ldots , n - 1 \).
- Parameters
-
x independent variable array (must have n elements) jac an array where the dense Jacobian will be placed (must be allocated with at least m * n elements)
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseJacobian() [4/6]
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pure virtual |
Calculates a Jacobian using sparse methods and saves it into a sparse format.
- Parameters
-
x independent variable array (must have n elements) jac The values of the sparse Jacobian in the order provided by row and col (must be allocated with at least the same number of non-zero elements as the Jacobian) row The row indices of the Jacobian values col The column indices of the Jacobian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseJacobian() [5/6]
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pure virtual |
Calculates a Jacobian using sparse methods and saves it into a sparse format.
- Parameters
-
x independent variable array (must have n elements) jac The values of the sparse Jacobian in the order provided by row and col (must be allocated with at least the same number of non-zero elements as the Jacobian) row The row indices of the Jacobian values col The column indices of the Jacobian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
◆ SparseJacobian() [6/6]
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pure virtual |
Determines the sparse Jacobian using a variable number of independent variable arrays. This method can be useful if the generic model was prepared considering that the independent variables are provided by several arrays.
- Parameters
-
x Contains the several independent variable vectors jac The values of the sparse Jacobian in the order provided by row and col row The row indices of the Jacobian values col The column indices of the Jacobian values
Implemented in CppAD::cg::FunctorGenericModel< Base >.
The documentation for this class was generated from the following files:
- include/cppad/cg/declare_cg.hpp
- include/cppad/cg/model/generic_model.hpp
