Boost.uBlas 1.49
Linear Algebra in C++: matrices, vectors and numeric algorithms

Level 2 BLAS

level 2 basic linear algebra subroutines More...

Functions

template<class V , class E1 , class E2 >
BOOST_UBLAS_INLINE V & boost::numeric::ublas::axpy_prod (const matrix_expression< E1 > &e1, const vector_expression< E2 > &e2, V &v, bool init=true)
 computes v += A x or v = A x in an optimized fashion.
template<class V , class E1 , class E2 >
BOOST_UBLAS_INLINE V & boost::numeric::ublas::axpy_prod (const vector_expression< E1 > &e1, const matrix_expression< E2 > &e2, V &v, bool init=true)
 computes v += AT x or v = AT x in an optimized fashion.

Detailed Description

level 2 basic linear algebra subroutines


Function Documentation

template<class V , class E1 , class E2 >
BOOST_UBLAS_INLINE V& boost::numeric::ublas::axpy_prod ( const matrix_expression< E1 > &  e1,
const vector_expression< E2 > &  e2,
V &  v,
bool  init = true 
)

computes v += A x or v = A x in an optimized fashion.

Parameters:
e1the matrix expression A
e2the vector expression x
vthe result vector v
inita boolean parameter

axpy_prod(A, x, v, init) implements the well known axpy-product. Setting init to true is equivalent to call v.clear() before axpy_prod. Currently init defaults to true, but this may change in the future.

Up to now there are some specialisation for compressed matrices that give a large speed up compared to prod.

Definition at line 244 of file operation.hpp.

template<class V , class E1 , class E2 >
BOOST_UBLAS_INLINE V& boost::numeric::ublas::axpy_prod ( const vector_expression< E1 > &  e1,
const matrix_expression< E2 > &  e2,
V &  v,
bool  init = true 
)

computes v += AT x or v = AT x in an optimized fashion.

Parameters:
e1the vector expression x
e2the matrix expression A
vthe result vector v
inita boolean parameter

axpy_prod(x, A, v, init) implements the well known axpy-product. Setting init to true is equivalent to call v.clear() before axpy_prod. Currently init defaults to true, but this may change in the future.

Up to now there are some specialisation for compressed matrices that give a large speed up compared to prod.

Definition at line 466 of file operation.hpp.