命名空间
	implementation

	special_purpose

类
struct	Block
	Generic class Block which wraps a matrix class and contains block specific information, providing a uniform way to deal with matrix blocks for all supported backend matrices. 更多...

函数
template<class Matrix >
Block< Matrix >	block (Matrix matrix, index_t row_begin, index_t col_begin, index_t row_size, index_t col_size)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	matrix_product (Matrix A, Matrix B, Matrix C, bool transpose_A=false, bool transpose_B=false, bool overwrite=true)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	add (Matrix A, Matrix B, Matrix C, typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	subtract (Matrix A, Matrix B, Matrix C, typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	scale (Matrix A, Matrix B, typename Matrix::Scalar alpha)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	elementwise_product (Matrix A, Matrix B, Matrix C)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
implementation::elementwise_square< backend, Matrix >::ReturnType	elementwise_square (Matrix m)

template<Backend backend = linalg_traits<Core>::backend, class Matrix , class ResultMatrix >
void	elementwise_square (Matrix m, ResultMatrix result)

template<Backend backend = linalg_traits<Core>::backend, class Matrix >
void	convolve (Matrix X, Matrix W, Matrix Y, bool flip=false, bool overwrite=true, int32_t stride_x=1, int32_t stride_y=1)

template<Backend backend = linalg_traits<Redux>::backend, class Vector >
Vector::Scalar	dot (Vector a, Vector b)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
Matrix::Scalar	sum (Matrix m, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
Matrix::Scalar	sum_symmetric (Matrix m, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
Matrix::Scalar	sum_symmetric (Block< Matrix > b, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
implementation::colwise_sum< backend, Matrix >::ReturnType	colwise_sum (Matrix m, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix , class Vector >
void	colwise_sum (Matrix m, Vector result, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
implementation::rowwise_sum< backend, Matrix >::ReturnType	rowwise_sum (Matrix m, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix , class Vector >
void	rowwise_sum (Matrix m, Vector result, bool no_diag=false)

template<Backend backend = linalg_traits<Redux>::backend, class Vector >
Vector::Scalar	vector_sum (Vector a)

template<Backend backend = linalg_traits<Redux>::backend, class Matrix >
Matrix::Scalar	max (Matrix m)

template<Backend backend = linalg_traits<Core>::backend, class Matrix , class Vector >
void	set_rows_const (Matrix A, Vector v)

函数说明

void shogun::linalg::add	(	Matrix	A,
		Matrix	B,
		Matrix	C,
		typename Matrix::Scalar	alpha = `1.0`,
		typename Matrix::Scalar	beta = `1.0`
	)

Performs the operation C = alpha*A + beta*B. Works for both matrices and vectors

在文件 Core.h 第 67 行定义.

Block<Matrix> shogun::linalg::block	(	Matrix	matrix,
		index_t	row_begin,
		index_t	col_begin,
		index_t	row_size,
		index_t	col_size
	)

Method that returns a block object. Suited for Eigen3/SGMatrix

参数

matrix	the matrix on which the block is defined
row_begin	the row index at which the block starts
col_begin	the col index at which the block starts
row_size	the number of rows in the block
col_size	the number of cols in the block

返回: a block object on this matrix

在文件 Block.h 第 102 行定义.

implementation::colwise_sum<backend,Matrix>::ReturnType shogun::linalg::colwise_sum	(	Matrix	m,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of matrix colwise sum of values that works with generic dense matrices

参数

m	the matrix whose colwise sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)

返回: the colwise sum of co-efficients computed as \(s_j=\sum_{i}m_{i,j}\)

在文件 Redux.h 第 113 行定义.

void shogun::linalg::colwise_sum	(	Matrix	m,
		Vector	result,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of matrix colwise sum of values that works with generic dense matrices

参数

m	the matrix whose colwise sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)
result	Pre-allocated vector for the result of the computation

在文件 Redux.h 第 128 行定义.

void shogun::linalg::convolve	(	Matrix	X,
		Matrix	W,
		Matrix	Y,
		bool	flip = `false`,
		bool	overwrite = `true`,
		int32_t	stride_x = `1`,
		int32_t	stride_y = `1`
	)

Computes the 2D convolution of X with W

NOTE: For the ViennaCL backend, the size of W (number of bytes) must not exceed CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE.

参数

X	Input image
W	Filter coefficients. The dimensions of the matrix must be odd-numbered.
Y	Output image of the same size as the input image, as the borders of the input image are implicitly padded with zeros during the computation
flip	If true the filter coefficients are flipped, performing cross-correlation instead of convolution
overwrite	If true, the values in Y are overwritten with result of the computation. Otherwise, the result is added to the existing values in Y.
stride_x	Stride in the x (column) direction
stride_y	Stride in the y (row) direction

在文件 Core.h 第 139 行定义.

Vector::Scalar shogun::linalg::dot	(	Vector	a,
		Vector	b
	)

Wrapper method for internal implementation of vector dot-product that works with generic vectors.

参数

a	first vector
b	second vector

返回: the dot product of \(\mathbf{a}\) and \(\mathbf{b}\), represented as \(\sum_i a_i b_i\)

在文件 Redux.h 第 56 行定义.

void shogun::linalg::elementwise_product	(	Matrix	A,
		Matrix	B,
		Matrix	C
	)

Performs the operation C = A .* B where ".*" denotes elementwise multiplication

在文件 Core.h 第 90 行定义.

implementation::elementwise_square<backend,Matrix>::ReturnType shogun::linalg::elementwise_square ( Matrix m )

Wrapper method for internal implementation of square of co-efficients that works with generic dense matrices.

参数

m	the matrix whose squared co-efficients matrix has to be computed

返回: another matrix whose co-efficients are \(m'_{i,j}=m_(i,j}^2\) for all \(i,j\)

在文件 Core.h 第 104 行定义.

void shogun::linalg::elementwise_square	(	Matrix	m,
		ResultMatrix	result
	)

Wrapper method for internal implementation of square of co-efficients that works with generic dense matrices.

参数

m	the matrix whose squared co-efficients matrix has to be computed
result	Pre-allocated matrix for the result of the computation

在文件 Core.h 第 117 行定义.

void shogun::linalg::matrix_product	(	Matrix	A,
		Matrix	B,
		Matrix	C,
		bool	transpose_A = `false`,
		bool	transpose_B = `false`,
		bool	overwrite = `true`
	)

Performs matrix multiplication

参数

A	First matrix
B	Second matrix
C	Result of the operation
transpose_A	Whether to the transpose of A should be used instead of A
transpose_B	Whether to the transpose of B should be used instead of B
overwrite	If true, the values in C are overwritten with the result, otherwise, the result is added to the existing values

在文件 Core.h 第 59 行定义.

Matrix::Scalar shogun::linalg::max ( Matrix m )

Returns the largest element in a matrix or vector

在文件 Redux.h 第 177 行定义.

implementation::rowwise_sum<backend,Matrix>::ReturnType shogun::linalg::rowwise_sum	(	Matrix	m,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of matrix rowwise sum of values that works with generic dense matrices

参数

m	the matrix whose rowwise sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)

返回: the rowwise sum of co-efficients computed as \(s_i=\sum_{j}m_{i,j}\)

在文件 Redux.h 第 142 行定义.

void shogun::linalg::rowwise_sum	(	Matrix	m,
		Vector	result,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of matrix rowwise sum of values that works with generic dense matrices

参数

m	the matrix whose rowwise sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)
result	Pre-allocated vector for the result of the computation

在文件 Redux.h 第 157 行定义.

void shogun::linalg::scale	(	Matrix	A,
		Matrix	B,
		typename Matrix::Scalar	alpha
	)

Performs the operation B = alpha*A. Works for both matrices and vectors

在文件 Core.h 第 83 行定义.

void shogun::linalg::set_rows_const	(	Matrix	A,
		Vector	v
	)

Sets each row of a matrix to some constant value. That is, perfoms the operation A[i,j] = v[i], for all i and j

在文件 Util.h 第 49 行定义.

void shogun::linalg::subtract	(	Matrix	A,
		Matrix	B,
		Matrix	C,
		typename Matrix::Scalar	alpha = `1.0`,
		typename Matrix::Scalar	beta = `1.0`
	)

Performs the operation C = alpha*A - beta*B. Works for both matrices and vectors

在文件 Core.h 第 75 行定义.

Matrix::Scalar shogun::linalg::sum	(	Matrix	m,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of matrix sum of values that works with generic dense matrices

参数

m	the matrix whose sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)

返回: the sum of co-efficients computed as \(\sum_{i,j}m_{i,j}\)

在文件 Redux.h 第 70 行定义.

Matrix::Scalar shogun::linalg::sum_symmetric	(	Matrix	m,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of symmetric matrix sum of values that works with generic dense matrices

参数

m	the matrix whose sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)

返回: the sum of co-efficients computed as \(\sum_{i,j}m_{i,j}\)

在文件 Redux.h 第 84 行定义.

Matrix::Scalar shogun::linalg::sum_symmetric	(	Block< Matrix >	b,
		bool	no_diag = `false`
	)

Wrapper method for internal implementation of symmetric matrix-block sum of values that works with generic dense matrix blocks

参数

b	the matrix-block whose sum of co-efficients has to be computed
no_diag	if true, diagonal entries are excluded from the sum (default - false)

返回: the sum of co-efficients computed as \(\sum_{i,j}b_{i,j}\)

在文件 Redux.h 第 98 行定义.

Vector::Scalar shogun::linalg::vector_sum ( Vector a )

Wrapper method for internal implementation of vector sum of values that works with generic dense vectors

参数

a	vector whose sum has to be computed

返回: the vector sum \(\sum_i a_i\)

在文件 Redux.h 第 170 行定义.

命名空间

类

函数

函数说明