mirror of https://github.com/AxioDL/metaforce.git
150 lines
6.4 KiB
C++
150 lines
6.4 KiB
C++
/* -*- c++ -*- (enables emacs c++ mode) */
|
|
/*===========================================================================
|
|
|
|
Copyright (C) 2002-2017 Yves Renard
|
|
|
|
This file is a part of GetFEM++
|
|
|
|
GetFEM++ is free software; you can redistribute it and/or modify it
|
|
under the terms of the GNU Lesser General Public License as published
|
|
by the Free Software Foundation; either version 3 of the License, or
|
|
(at your option) any later version along with the GCC Runtime Library
|
|
Exception either version 3.1 or (at your option) any later version.
|
|
This program is distributed in the hope that it will be useful, but
|
|
WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
|
|
or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public
|
|
License and GCC Runtime Library Exception for more details.
|
|
You should have received a copy of the GNU Lesser General Public License
|
|
along with this program; if not, write to the Free Software Foundation,
|
|
Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301, USA.
|
|
|
|
As a special exception, you may use this file as it is a part of a free
|
|
software library without restriction. Specifically, if other files
|
|
instantiate templates or use macros or inline functions from this file,
|
|
or you compile this file and link it with other files to produce an
|
|
executable, this file does not by itself cause the resulting executable
|
|
to be covered by the GNU Lesser General Public License. This exception
|
|
does not however invalidate any other reasons why the executable file
|
|
might be covered by the GNU Lesser General Public License.
|
|
|
|
===========================================================================*/
|
|
|
|
|
|
// This file is a modified version of approximate_inverse.h from ITL.
|
|
// See http://osl.iu.edu/research/itl/
|
|
// Following the corresponding Copyright notice.
|
|
//===========================================================================
|
|
//
|
|
// Copyright (c) 1998-2001, University of Notre Dame. All rights reserved.
|
|
// Redistribution and use in source and binary forms, with or without
|
|
// modification, are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistributions of source code must retain the above copyright
|
|
// notice, this list of conditions and the following disclaimer.
|
|
// * Redistributions in binary form must reproduce the above copyright
|
|
// notice, this list of conditions and the following disclaimer in the
|
|
// documentation and/or other materials provided with the distribution.
|
|
// * Neither the name of the University of Notre Dame nor the
|
|
// names of its contributors may be used to endorse or promote products
|
|
// derived from this software without specific prior written permission.
|
|
//
|
|
// THIS SOFTWARE IS PROVIDED BY THE TRUSTEES OF INDIANA UNIVERSITY AND
|
|
// CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
|
|
// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
|
|
// FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE TRUSTEES
|
|
// OF INDIANA UNIVERSITY AND CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
|
|
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
|
|
// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
|
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
|
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
|
|
// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
//
|
|
//===========================================================================
|
|
|
|
/**@file gmm_precond_mr_approx_inverse.h
|
|
@author Andrew Lumsdaine <lums@osl.iu.edu>
|
|
@author Lie-Quan Lee <llee@osl.iu.edu>
|
|
@author Yves Renard <Yves.Renard@insa-lyon.fr>
|
|
@date June 5, 2003.
|
|
@brief Approximate inverse via MR iteration.
|
|
*/
|
|
|
|
#ifndef GMM_PRECOND_MR_APPROX_INVERSE_H
|
|
#define GMM_PRECOND_MR_APPROX_INVERSE_H
|
|
|
|
|
|
#include "gmm_precond.h"
|
|
|
|
namespace gmm {
|
|
|
|
/** Approximate inverse via MR iteration (see P301 of Saad book).
|
|
*/
|
|
template <typename Matrix>
|
|
struct mr_approx_inverse_precond {
|
|
|
|
typedef typename linalg_traits<Matrix>::value_type value_type;
|
|
typedef typename number_traits<value_type>::magnitude_type magnitude_type;
|
|
typedef typename principal_orientation_type<typename
|
|
linalg_traits<Matrix>::sub_orientation>::potype sub_orientation;
|
|
typedef wsvector<value_type> VVector;
|
|
typedef col_matrix<VVector> MMatrix;
|
|
|
|
MMatrix M;
|
|
size_type nb_it;
|
|
magnitude_type threshold;
|
|
|
|
void build_with(const Matrix& A);
|
|
mr_approx_inverse_precond(const Matrix& A, size_type nb_it_,
|
|
magnitude_type threshold_)
|
|
: M(mat_nrows(A), mat_ncols(A))
|
|
{ threshold = threshold_; nb_it = nb_it_; build_with(A); }
|
|
mr_approx_inverse_precond(void)
|
|
{ threshold = magnitude_type(1E-7); nb_it = 5; }
|
|
mr_approx_inverse_precond(size_type nb_it_, magnitude_type threshold_)
|
|
{ threshold = threshold_; nb_it = nb_it_; }
|
|
const MMatrix &approx_inverse(void) const { return M; }
|
|
};
|
|
|
|
template <typename Matrix, typename V1, typename V2> inline
|
|
void mult(const mr_approx_inverse_precond<Matrix>& P, const V1 &v1, V2 &v2)
|
|
{ mult(P.M, v1, v2); }
|
|
|
|
template <typename Matrix, typename V1, typename V2> inline
|
|
void transposed_mult(const mr_approx_inverse_precond<Matrix>& P,
|
|
const V1 &v1,V2 &v2)
|
|
{ mult(gmm::conjugated(P.M), v1, v2); }
|
|
|
|
template <typename Matrix>
|
|
void mr_approx_inverse_precond<Matrix>::build_with(const Matrix& A) {
|
|
gmm::resize(M, mat_nrows(A), mat_ncols(A));
|
|
typedef value_type T;
|
|
typedef magnitude_type R;
|
|
VVector m(mat_ncols(A)),r(mat_ncols(A)),ei(mat_ncols(A)),Ar(mat_ncols(A));
|
|
T alpha = mat_trace(A)/ mat_euclidean_norm_sqr(A);
|
|
if (alpha == T(0)) alpha = T(1);
|
|
|
|
for (size_type i = 0; i < mat_nrows(A); ++i) {
|
|
gmm::clear(m); gmm::clear(ei);
|
|
m[i] = alpha;
|
|
ei[i] = T(1);
|
|
|
|
for (size_type j = 0; j < nb_it; ++j) {
|
|
gmm::mult(A, gmm::scaled(m, T(-1)), r);
|
|
gmm::add(ei, r);
|
|
gmm::mult(A, r, Ar);
|
|
T nAr = vect_sp(Ar,Ar);
|
|
if (gmm::abs(nAr) > R(0)) {
|
|
gmm::add(gmm::scaled(r, gmm::safe_divide(vect_sp(r, Ar), vect_sp(Ar, Ar))), m);
|
|
gmm::clean(m, threshold * gmm::vect_norm2(m));
|
|
} else gmm::clear(m);
|
|
}
|
|
if (gmm::vect_norm2(m) == R(0)) m[i] = alpha;
|
|
gmm::copy(m, M.col(i));
|
|
}
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|