mirror of https://github.com/AxioDL/metaforce.git
97 lines
3.4 KiB
C++
97 lines
3.4 KiB
C++
/* -*- c++ -*- (enables emacs c++ mode) */
|
|
/*===========================================================================
|
|
|
|
Copyright (C) 2002-2017 Yves Renard, Benjamin Schleimer
|
|
|
|
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.
|
|
|
|
===========================================================================*/
|
|
|
|
/**@file gmm_leastsquares_cg.h
|
|
@author Benjamin Schleimer <bensch128 (at) yahoo (dot) com>
|
|
@date January 23, 2007.
|
|
@brief Conjugate gradient least squares algorithm.
|
|
Algorithm taken from http://www.stat.washington.edu/wxs/Stat538-w05/Notes/conjugate-gradients.pdf page 6
|
|
*/
|
|
#ifndef GMM_LEAST_SQUARES_CG_H__
|
|
#define GMM_LEAST_SQUARES_CG_H__
|
|
|
|
#include "gmm_kernel.h"
|
|
#include "gmm_iter.h"
|
|
#include "gmm_conjugated.h"
|
|
|
|
namespace gmm {
|
|
|
|
template <typename Matrix, typename Vector1, typename Vector2>
|
|
void least_squares_cg(const Matrix& C, Vector1& x, const Vector2& y,
|
|
iteration &iter) {
|
|
|
|
typedef typename temporary_dense_vector<Vector1>::vector_type temp_vector;
|
|
typedef typename linalg_traits<Vector1>::value_type T;
|
|
|
|
T rho, rho_1(0), a;
|
|
temp_vector p(vect_size(x)), q(vect_size(y)), g(vect_size(x));
|
|
temp_vector r(vect_size(y));
|
|
iter.set_rhsnorm(gmm::sqrt(gmm::abs(vect_hp(y, y))));
|
|
|
|
if (iter.get_rhsnorm() == 0.0)
|
|
clear(x);
|
|
else {
|
|
mult(C, scaled(x, T(-1)), y, r);
|
|
mult(conjugated(C), r, g);
|
|
rho = vect_hp(g, g);
|
|
copy(g, p);
|
|
|
|
while (!iter.finished_vect(g)) {
|
|
|
|
if (!iter.first()) {
|
|
rho = vect_hp(g, g);
|
|
add(g, scaled(p, rho / rho_1), p);
|
|
}
|
|
|
|
mult(C, p, q);
|
|
|
|
a = rho / vect_hp(q, q);
|
|
add(scaled(p, a), x);
|
|
add(scaled(q, -a), r);
|
|
// NOTE: how do we minimize the impact to the transpose?
|
|
mult(conjugated(C), r, g);
|
|
rho_1 = rho;
|
|
|
|
++iter;
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename Matrix, typename Precond,
|
|
typename Vector1, typename Vector2> inline
|
|
void least_squares_cg(const Matrix& C, const Vector1& x, const Vector2& y,
|
|
iteration &iter)
|
|
{ least_squares_cg(C, linalg_const_cast(x), y, iter); }
|
|
}
|
|
|
|
|
|
#endif // GMM_SOLVER_CG_H__
|