Special Products

Functions

template<class V, class E1, class E2> BOOST_UBLAS_INLINE V &	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 &	axpy_prod (const vector_expression< E1 > &e1, const matrix_expression< E2 > &e2, V &v, bool init=true)
	computes `v += A^T x` or `v = A^T x` in an optimized fashion.
template<class M, class E1, class E2> BOOST_UBLAS_INLINE M &	axpy_prod (const matrix_expression< E1 > &e1, const matrix_expression< E2 > &e2, M &m, bool init=true)
	computes `M += A X` or `M = A X` in an optimized fashion.
template<class M, class E1, class E2> BOOST_UBLAS_INLINE M &	opb_prod (const matrix_expression< E1 > &e1, const matrix_expression< E2 > &e2, M &m, bool init=true)
	computes `M += A X` or `M = A X` in an optimized fashion.

BOOST_UBLAS_INLINE V& 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:

	e1	the matrix expression `A`
	e2	the vector expression `x`
	v	the result vector `v`
	init	a 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.

BOOST_UBLAS_INLINE V& axpy_prod	(	const vector_expression< E1 > &	e1,
		const matrix_expression< E2 > &	e2,
		V &	v,
		bool	init = `true`
	)

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

Parameters:

	e1	the vector expression `x`
	e2	the matrix expression `A`
	v	the result vector `v`
	init	a 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.

BOOST_UBLAS_INLINE M& axpy_prod	(	const matrix_expression< E1 > &	e1,
		const matrix_expression< E2 > &	e2,
		M &	m,
		bool	init = `true`
	)

computes M += A X or M = A X in an optimized fashion.

Parameters:

	e1	the matrix expression `A`
	e2	the matrix expression `X`
	m	the result matrix `M`
	init	a boolean parameter

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

Up to now there are no specialisations.

BOOST_UBLAS_INLINE M& opb_prod	(	const matrix_expression< E1 > &	e1,
		const matrix_expression< E2 > &	e2,
		M &	m,
		bool	init = `true`
	)

computes M += A X or M = A X in an optimized fashion.

Parameters:

	e1	the matrix expression `A`
	e2	the matrix expression `X`
	m	the result matrix `M`
	init	a boolean parameter

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

This function may give a speedup if A has less columns than rows, because the product is computed as a sum of outer products.

Copyright (©) 2000-2004 Michael Stevens, Mathias Koch, Joerg Walter, Gunter Winkler
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