#include <deal.II/matrix_free/tensor_product_kernels.h>

Public Member Functions
	EvaluatorTensorProduct ()

	EvaluatorTensorProduct (const AlignedVector< Number2 > &shape_values, const AlignedVector< Number2 > &shape_gradients, const AlignedVector< Number2 > &shape_hessians, const unsigned int=0, const unsigned int=0)

	EvaluatorTensorProduct (const Number2 shape_values, const Number2 shape_gradients, const Number2 *shape_hessians, const unsigned int dummy1=0, const unsigned int dummy2=0)

template<int direction, bool contract_over_rows, bool add, int stride = 1>
void	values (const Number in[], Number out[]) const

template<int direction, bool contract_over_rows, bool add, int stride = 1>
void	gradients (const Number in[], Number out[]) const

template<int direction, bool contract_over_rows, bool add>
void	hessians (const Number in[], Number out[]) const

template<int direction, bool contract_over_rows, bool add>
void	values_one_line (const Number in[], Number out[]) const

template<int direction, bool contract_over_rows, bool add>
void	gradients_one_line (const Number in[], Number out[]) const

template<int direction, bool contract_over_rows, bool add>
void	hessians_one_line (const Number in[], Number out[]) const

Static Public Member Functions
template<int direction, bool contract_over_rows, bool add, bool one_line = false, EvaluatorQuantity quantity = EvaluatorQuantity::value, int stride = 1>
static void	apply (const Number2 DEAL_II_RESTRICT shape_data, const Number in, Number *out)

Static Public Attributes
static constexpr unsigned int	n_rows_of_product

static constexpr unsigned int	n_columns_of_product

Private Attributes
const Number2 *	shape_values

const Number2 *	shape_gradients

const Number2 *	shape_hessians

Detailed Description

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number, typename Number2 = Number>
struct internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >

Generic evaluator framework that valuates the given shape data in general dimensions using the tensor product form. Depending on the particular layout in the matrix entries, this corresponds to a usual matrix-matrix product or a matrix-matrix product including some symmetries. The actual work is implemented by functions of type apply_matrix_vector_product working on a single dimension, controlled by suitable strides, using the kernel specified via variant.

Template Parameters

dim	Space dimension in which this class is applied
n_rows	Number of rows in the transformation matrix, which corresponds to the number of 1d shape functions in the usual tensor contraction setting
n_columns	Number of columns in the transformation matrix, which corresponds to the number of 1d shape functions in the usual tensor contraction setting
Number	Abstract number type for input and output arrays
Number2	Abstract number type for coefficient arrays (defaults to same type as the input/output arrays); must implement operator* with Number and produce Number as an output to be a valid type

Definition at line 1573 of file tensor_product_kernels.h.

Constructor & Destructor Documentation

◆ EvaluatorTensorProduct() [1/3]

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::EvaluatorTensorProduct ( )

inline

Empty constructor. Does nothing. Be careful when using 'values' and related methods because they need to be filled with the other pointer

Definition at line 1584 of file tensor_product_kernels.h.

◆ EvaluatorTensorProduct() [2/3]

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::EvaluatorTensorProduct	(	const AlignedVector< Number2 > &	shape_values,
		const AlignedVector< Number2 > &	shape_gradients,
		const AlignedVector< Number2 > &	shape_hessians,
		const unsigned int	= `0`,
		const unsigned int	= `0`
	)

inline

Constructor, taking the data from ShapeInfo

Definition at line 1593 of file tensor_product_kernels.h.

◆ EvaluatorTensorProduct() [3/3]

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::EvaluatorTensorProduct	(	const Number2 *	shape_values,
		const Number2 *	shape_gradients,
		const Number2 *	shape_hessians,
		const unsigned int	dummy1 = `0`,
		const unsigned int	dummy2 = `0`
	)

inline

Constructor, taking the data from ShapeInfo via raw pointers

Definition at line 1633 of file tensor_product_kernels.h.

Member Function Documentation

◆ values()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add, int stride = 1>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::values	(	const Number	in[],
		Number	out[]
	)		const

inline

This interpolates values with sum factorization, according to the following parameters:

Template Parameters

direction	The direction along which the one-dimensional operations should be performed, using 0 as the fastest running direction x, 1 for y, and so on.
contract_over_rows	Describes whether the interpolation is over the rows or the columns in the underlying interpolation matrix. With the chosen convention in the data fields, `contract_over_rows==true` means interpolation from DoF values to quadrature points, whereas using the argument `false` will perform summation over quadrature points to produce integrals for each test function.
add	Specify whether to add into the output array or overwrite the previous content.
stride	This parameter can specify an additional stride in the array associated with quadrature points (`in` for `dof_to_quad==false`, otherwise `out`) from consecutive points in the x-direction. This is used to place results from different interpolation steps next to each other in memory.

Parameters

in	Input array for the operation, needs to be backed up by a sufficiently large memory region.
out	Array holding the result of the sum factorization operation.

Definition at line 1673 of file tensor_product_kernels.h.

◆ gradients()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add, int stride = 1>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::gradients	(	const Number	in[],
		Number	out[]
	)		const

inline

This interpolates gradients with sum factorization, based on the second argument given to the constructor of this class. For the documentation of the template and function parameters, see the values function.

Definition at line 1687 of file tensor_product_kernels.h.

◆ hessians()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::hessians	(	const Number	in[],
		Number	out[]
	)		const

inline

This interpolates hessians with sum factorization, based on the third argument given to the constructor of this class. For the documentation of the template and function parameters, see the values function.

Definition at line 1703 of file tensor_product_kernels.h.

◆ values_one_line()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::values_one_line	(	const Number	in[],
		Number	out[]
	)		const

inline

A variant of interpolation with sum factorization that only applies the operation to a single 1d line, leaving all other entries untouched, rather than expanding the loop over all other directions of a tensor product mesh. For the documentation of the template and function parameters, see the other values function.

Definition at line 1723 of file tensor_product_kernels.h.

◆ gradients_one_line()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::gradients_one_line	(	const Number	in[],
		Number	out[]
	)		const

inline

A variant of interpolation with sum factorization that only applies the gradient operation to a single 1d line, leaving all other entries untouched, rather than expanding the loop over all other directions of a tensor product mesh. For the documentation of the template and function parameters, see the values function.

Definition at line 1739 of file tensor_product_kernels.h.

◆ hessians_one_line()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

template<int direction, bool contract_over_rows, bool add>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::hessians_one_line	(	const Number	in[],
		Number	out[]
	)		const

inline

A variant of interpolation with sum factorization that only applies the Hessian operation to a single 1d line, leaving all other entries untouched, rather than expanding the loop over all other directions of a tensor product mesh. For the documentation of the template and function parameters, see the values function.

Definition at line 1758 of file tensor_product_kernels.h.

◆ apply()

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 >

template<int direction, bool contract_over_rows, bool add, bool one_line, EvaluatorQuantity quantity, int stride>

void internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::apply	(	const Number2 *DEAL_II_RESTRICT	shape_data,
		const Number *	in,
		Number *	out
	)

inlinestatic

This function applies the tensor product kernel with sum factorization, corresponding to a matrix-vector multiplication of 1d stripes, along the given direction of the tensor data in the input array. This function allows the in and out arrays to alias for the case n_rows == n_columns, i.e., it is safe to perform the contraction in place where in and out point to the same address. For the case n_rows != n_columns, the output is in general not correct.

Template Parameters

direction	Direction that is evaluated
contract_over_rows	If true, the tensor contraction sums over the rows in the given `shape_data` array, otherwise it sums over the columns
add	If true, the result is added to the output vector, else the computed values overwrite the content in the output
one_line	If true, the kernel is only applied along a single 1d stripe within a dim-dimensional tensor, not the full n_rows^dim points as in the `false` case.
quantity	Specify whether values, gradients or Hessians should be interpolated, allowing specialized algorithms for some class template parameters of `variant` to find the right path.
stride	This parameter enables to place the result of the tensor product evaluation in the output array (if `contract_over_rows == true`) or input array (if `contract_over_rows == false`) with additional strides between adjacent points in x direction, which is used to group all components of a gradient adjacent in memory. If the stride is one, the data will form a contiguous range in memory.

Parameters

shape_data	Transformation matrix with `n_rows` rows and `n_columns` columns, stored in row-major format.
in	Pointer to the start of the input data vector.
out	Pointer to the start of the output data vector.

Definition at line 1838 of file tensor_product_kernels.h.

Member Data Documentation

◆ n_rows_of_product

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

constexpr unsigned int internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::n_rows_of_product

staticconstexpr

Initial value:

=

Utilities::pow(n_rows, dim)

Utilities::pow

constexpr T pow(const T base, const int iexp)

Definition utilities.h:966

Definition at line 1575 of file tensor_product_kernels.h.

◆ n_columns_of_product

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

constexpr unsigned int internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::n_columns_of_product

staticconstexpr

Initial value:

=

Utilities::pow(n_columns, dim)

Definition at line 1577 of file tensor_product_kernels.h.

◆ shape_values

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

const Number2* internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::shape_values

private

Definition at line 1818 of file tensor_product_kernels.h.

◆ shape_gradients

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

const Number2* internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::shape_gradients

private

Definition at line 1819 of file tensor_product_kernels.h.

◆ shape_hessians

template<EvaluatorVariant variant, int dim, int n_rows, int n_columns, typename Number , typename Number2 = Number>

const Number2* internal::EvaluatorTensorProduct< variant, dim, n_rows, n_columns, Number, Number2 >::shape_hessians

private

Definition at line 1820 of file tensor_product_kernels.h.

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

include/deal.II/matrix_free/tensor_product_kernels.h

Public Member Functions

Static Public Member Functions

Static Public Attributes

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ EvaluatorTensorProduct() [1/3]

◆ EvaluatorTensorProduct() [2/3]

◆ EvaluatorTensorProduct() [3/3]

Member Function Documentation

◆ values()

◆ gradients()

◆ hessians()

◆ values_one_line()

◆ gradients_one_line()

◆ hessians_one_line()

◆ apply()

Member Data Documentation

◆ n_rows_of_product

◆ n_columns_of_product

◆ shape_values

◆ shape_gradients

◆ shape_hessians