Advanced mock operation for DelayedUnaryIsometricOperation. More...

#include <mock_helpers.hpp>

Public Member Functions
template<typename Index_ , typename InputValue_ , typename OutputValue_ >
void	dense (bool row, Index_ i, Index_ start, Index_ length, const InputValue_ input, OutputValue_ output) const

template<typename Index_ , typename InputValue_ , typename OutputValue_ >
void	dense (bool row, Index_ i, const std::vector< Index_ > &indices, const InputValue_ input, OutputValue_ output) const

template<typename Index_ , typename InputValue_ , typename OutputValue_ >
void	sparse (bool row, Index_ i, Index_ num, const InputValue_ input_value, const Index_ index, OutputValue_ *output_value) const

template<typename OutputValue_ , typename InputValue_ , typename Index_ >
OutputValue_	fill (bool row, Index_ i) const

bool	zero_depends_on_row () const

bool	zero_depends_on_column () const

bool	non_zero_depends_on_row () const

bool	non_zero_depends_on_column () const

bool	is_sparse () const

Static Public Attributes
static constexpr bool	is_basic = false

Detailed Description

Advanced mock operation for DelayedUnaryIsometricOperation.

This class defines the advanced expectations for an operation in DelayedUnaryIsometricOperation, which improves efficiency by taking advantage of any sparsity in the underlying matrix. Either the operation itself preserves sparsity, or any loss of sparsity is predictable, i.e., zeros are transformed into a constant non-zero value that does not depend on its position in the Matrix.

Actual operations aren't expected to inherit from this class; this is only provided for documentation purposes. Operations only need to implement methods with the same signatures for compile-time polymorphism.

Member Function Documentation

◆ dense() [1/2]

template<typename Index_ , typename InputValue_ , typename OutputValue_ >

void tatami::DelayedUnaryIsometricMockAdvanced::dense	(	bool	row,
		Index_	i,
		Index_	start,
		Index_	length,
		const InputValue_ *	input,
		OutputValue_ *	output
	)		const

inline

This method accepts a contiguous block of an element of the target dimension from the underlying matrix (input), applies the operation to each value, and stores the result in another array of different type (output).

Implementions of this method do not necessarily need to have the same template arguments as shown here. It will be called without any explicit template arguments so anything can be used as long as type deduction works.

Template Parameters

Index_	Type of index value.
InputValue_	Type of matrix value to use in the operation.
OutputValue_	Type of matrix value returned by the operation.

Parameters

	row	Whether the rows are the target dimension. If true, `buffer` contains row `i`, otherwise it contains column `i`.
	i	Index of the extracted row (if `row = true`) or column (otherwise). This argument should be ignored if the operation does not depend on the row/column (i.e., when all of `zero_depends_on_row()` and friends return false), in which case an arbitrary placeholder may be supplied.
	start	Start of the contiguous block of columns (if `row = true`) or rows (otherwise) extracted from `i`.
	length	Length of the contiguous block.
[in]	input	Pointer to an array containing a contiguous block of a row/column extracted from the matrix. This has `length` addressable elements.
[out]	output	Pointer to an array to store the results of the operation applied to elements of `input`. This has `length` addressable elements. If `InputValue_ == OutputValue_`, this is guaranteed to be the same as `input`.

◆ dense() [2/2]

template<typename Index_ , typename InputValue_ , typename OutputValue_ >

void tatami::DelayedUnaryIsometricMockAdvanced::dense	(	bool	row,
		Index_	i,
		const std::vector< Index_ > &	indices,
		const InputValue_ *	input,
		OutputValue_ *	output
	)		const

inline

This method accepts an indexed subset of an element of the target dimension from the underlying matrix (input), applies the operation to each value, and stores the result in another array of different type (output).

Implementions of this method do not necessarily need to have the same template arguments as shown here. It will be called without any explicit template arguments so anything can be used as long as type deduction works.

Template Parameters

InputValue_	Type of matrix value to use in the operation.
Index_	Type of index value.
OutputValue_	Type of matrix value returned by the operation.

Parameters

	row	Whether the rows are the target dimension. If true, `buffer` contains row `i`, otherwise it contains column `i`.
	i	Index of the extracted row (if `row = true`) or column (otherwise). This argument should be ignored if the operation does not depend on the row/column (i.e., when all of `zero_depends_on_row()` and friends return false), in which case an arbitrary placeholder may be supplied.
	indices	Sorted and unique indices of columns (if `row = true`) or rows (otherwise) extracted from `i`.
[in]	input	Pointer to an array containing an indexed subset of a row/column extracted from the matrix. This has `length` addressable elements.
[out]	output	Pointer to an array to store the results of the operation applied to elements of `input`. This has `length` addressable elements. If `InputValue_ == OutputValue_`, this is guaranteed to be the same as `input`.

◆ sparse()

template<typename Index_ , typename InputValue_ , typename OutputValue_ >

void tatami::DelayedUnaryIsometricMockAdvanced::sparse	(	bool	row,
		Index_	i,
		Index_	num,
		const InputValue_ *	input_value,
		const Index_ *	index,
		OutputValue_ *	output_value
	)		const

inline

This method is expected to iterate over input_value, apply the operation to each value, and store the result in output_value. We assume that the operation only needs to be applied to the structural non-zeros; structural zeros are either ignored for sparsity-preserving operations, or the result of the operation on zeros will be populated by fill().

If non_zero_depends_on_row() && !row or non_zero_depends_on_column() && row, index is guaranteed to be non-NULL. Otherwise, it may be NULL and should be ignored. Even if non-NULL, indices are not guaranteed to be sorted.

Implementations of this method do not necessarily need to have the same template arguments as shown here. It will be called without any explicit template arguments so anything can be used as long as type deduction works.

Template Parameters

Index_	Type of index value.
InputValue_	Type of matrix value to use in the operation.
OutputValue_	Type of matrix value returned by the operation.

Parameters

	row	Whether the rows are the target dimension. If true, `buffer` contains row `i`, otherwise it contains column `i`.
	i	Index of the extracted row (if `row = true`) or column (otherwise). This argument should be ignored if the operation does not depend on the row/column (i.e., when all of `zero_depends_on_row()` and friends return false), in which case an arbitrary placeholder may be supplied.
	num	Number of non-zero elements for row/column `i`.
[in]	input_value	Pointer to an array of values of the structural non-zero elements from the row/column of the matrix. This is guaranteed to have `num` addressable elements.
[in]	index	Pointer to an array of column (if `row = true`) or row indices (otherwise) of the non-zero elements. Alternatively NULL.
[out]	output_value	Pointer to an array in which to store the result of the operation on each element of `input_value`. This is guaranteed to have `num` addressable elements. If `InputValue_ == OutputValue_`, this is guaranteed to be the same as `input`.

◆ fill()

template<typename OutputValue_ , typename InputValue_ , typename Index_ >

OutputValue_ tatami::DelayedUnaryIsometricMockAdvanced::fill	(	bool	row,
		Index_	i
	)		const

inline

Template Parameters

OutputValue_	Type of the result of the operation.
InputValue_	Type of the matrix value used in the operation.
Index_	Type of index value.

Parameters

row	Whether `i` refers to the row or column index.
i	The index of the row (if `row = true`) or column (otherwise) containing the zeros. This argument should be ignored if the operation does not depend on the row/column (i.e., when all of `zero_depends_on_row()` and friends return false), in which case an arbitrary placeholder may be supplied.

Returns: The result of the operation being applied on zeros from the i-th row/column of the matrix.

This method will be called with the explicit OutputValue_ and InputValue_ template parameters. Implementations of this method should either ensure that Index_ is deducible or use a fixed integer type in the method signature.

◆ zero_depends_on_row()

bool tatami::DelayedUnaryIsometricMockAdvanced::zero_depends_on_row ( ) const

inline

Returns: Whether the operation will convert a structural zero to a non-zero value, in a manner that depends on the identity of the column in which the structural zero occurs.

This method is only called when is_sparse() returns false. It is not necessary to explicitly return false here for sparsity-preserving operations, as DelayedUnaryIsometricOperation will automatically recognize such operations as being row-independent.

This method may be omitted from the class definition, in which case it is assumed to always return false.

◆ zero_depends_on_column()

bool tatami::DelayedUnaryIsometricMockAdvanced::zero_depends_on_column ( ) const

inline

Returns: Whether the operation will convert a structural zero to a non-zero value, in a manner that depends on the identity of the column in which the structural zero occurs.

This method is only called when is_sparse() returns false. It is not necessary to explicitly return false here for sparsity-preserving operations, as DelayedUnaryIsometricOperation will automatically recognize such operations as being row-independent.

This method may be omitted from the class definition, in which case it is assumed to always return false.

◆ non_zero_depends_on_row()

bool tatami::DelayedUnaryIsometricMockAdvanced::non_zero_depends_on_row ( ) const

inline

Returns: Whether the result of the operation on a non-zero operand depends on the identity of the row containing the operand.

This method may be omitted from the class definition, in which case it is assumed to always return false.

◆ non_zero_depends_on_column()

bool tatami::DelayedUnaryIsometricMockAdvanced::non_zero_depends_on_column ( ) const

inline

Returns: Whether the result of the operation on a non-zero operand depends on the identity of the column containing the operand.

This method may also omitted from the class definition, in which case it is assumed to always return false.

◆ is_sparse()

bool tatami::DelayedUnaryIsometricMockAdvanced::is_sparse ( ) const

inline

Returns: Does this operation preserve sparsity? This may return false.

Member Data Documentation

◆ is_basic

constexpr bool tatami::DelayedUnaryIsometricMockAdvanced::is_basic = false

staticconstexpr

Whether this is a basic operation. This should be false, otherwise a basic operation interface is expected (see DelayedUnaryIsometricMockBasic).

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

tatami/isometric/unary/mock_helpers.hpp

Public Member Functions

Static Public Attributes

Detailed Description

Member Function Documentation

◆ dense() [1/2]

◆ dense() [2/2]

◆ sparse()

◆ fill()

◆ zero_depends_on_row()

◆ zero_depends_on_column()

◆ non_zero_depends_on_row()

◆ non_zero_depends_on_column()

◆ is_sparse()

Member Data Documentation

◆ is_basic