Author: Gunter Winkler

# 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 += AT x` or `v = AT 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 += AT x` or `v = AT 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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