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//===========================================================================
//
// Copyright (C) 2004-2008 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 2.1 of the License, 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 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_precond_ilutp.h
@author Yves Renard <Yves.Renard@insa-lyon.fr>
@date October 14, 2004.
@brief ILUTP: Incomplete LU with threshold and K fill-in Preconditioner and
column pivoting.
*/
#ifndef GMM_PRECOND_ILUTP_H
#define GMM_PRECOND_ILUTP_H
#include "gmm_precond_ilut.h"
namespace gmm {
/**
ILUTP: Incomplete LU with threshold and K fill-in Preconditioner and
column pivoting.
See Yousef Saad, Iterative Methods for
sparse linear systems, PWS Publishing Company, section 10.4.4
TODO : store the permutation by cycles to avoid the temporary vector
*/
template <typename Matrix>
class ilutp_precond {
public :
typedef typename linalg_traits<Matrix>::value_type value_type;
typedef wsvector<value_type> _wsvector;
typedef rsvector<value_type> _rsvector;
typedef row_matrix<_rsvector> LU_Matrix;
typedef col_matrix<_wsvector> CLU_Matrix;
bool invert;
LU_Matrix L, U;
gmm::unsorted_sub_index indperm;
gmm::unsorted_sub_index indperminv;
mutable std::vector<value_type> temporary;
protected:
size_type K;
double eps;
template<typename M> void do_ilutp(const M&, row_major);
void do_ilutp(const Matrix&, col_major);
public:
void build_with(const Matrix& A) {
invert = false;
gmm::resize(L, mat_nrows(A), mat_ncols(A));
gmm::resize(U, mat_nrows(A), mat_ncols(A));
do_ilutp(A, typename principal_orientation_type<typename
linalg_traits<Matrix>::sub_orientation>::potype());
}
ilutp_precond(const Matrix& A, size_type k_, double eps_)
: L(mat_nrows(A), mat_ncols(A)), U(mat_nrows(A), mat_ncols(A)),
K(k_), eps(eps_) { build_with(A); }
ilutp_precond(int k_, double eps_) : K(k_), eps(eps_) {}
ilutp_precond(void) { K = 10; eps = 1E-7; }
size_type memsize() const {
return sizeof(*this) + (nnz(U)+nnz(L))*sizeof(value_type);
}
};
template<typename Matrix> template<typename M>
void ilutp_precond<Matrix>::do_ilutp(const M& A, row_major) {
typedef value_type T;
typedef typename number_traits<T>::magnitude_type R;
size_type n = mat_nrows(A);
CLU_Matrix CU(n,n);
if (n == 0) return;
std::vector<T> indiag(n);
temporary.resize(n);
std::vector<size_type> ipvt(n), ipvtinv(n);
for (size_type i = 0; i < n; ++i) ipvt[i] = ipvtinv[i] = i;
indperm = unsorted_sub_index(ipvt);
indperminv = unsorted_sub_index(ipvtinv);
_wsvector w(mat_ncols(A));
_rsvector ww(mat_ncols(A));
T tmp = T(0);
gmm::clear(L); gmm::clear(U);
R prec = default_tol(R());
R max_pivot = gmm::abs(A(0,0)) * prec;
for (size_type i = 0; i < n; ++i) {
copy(sub_vector(mat_const_row(A, i), indperm), w);
double norm_row = gmm::vect_norm2(mat_const_row(A, i));
typename _wsvector::iterator wkold = w.end();
for (typename _wsvector::iterator wk = w.begin();
wk != w.end() && wk->first < i; ) {
size_type k = wk->first;
tmp = (wk->second) * indiag[k];
if (gmm::abs(tmp) < eps * norm_row) w.erase(k);
else { wk->second += tmp; gmm::add(scaled(mat_row(U, k), -tmp), w); }
if (wkold == w.end()) wk = w.begin(); else { wk = wkold; ++wk; }
if (wk != w.end() && wk->first == k)
{ if (wkold == w.end()) wkold = w.begin(); else ++wkold; ++wk; }
}
gmm::clean(w, eps * norm_row);
gmm::copy(w, ww);
std::sort(ww.begin(), ww.end(), elt_rsvector_value_less_<T>());
typename _rsvector::const_iterator wit = ww.begin(), wite = ww.end();
size_type ip = size_type(-1);
for (; wit != wite; ++wit)
if (wit->c >= i) { ip = wit->c; tmp = wit->e; break; }
if (ip == size_type(-1) || gmm::abs(tmp) <= max_pivot)
{ GMM_WARNING2("pivot " << i << " too small"); ip=i; ww[i]=tmp=T(1); }
max_pivot = std::max(max_pivot, std::min(gmm::abs(tmp) * prec, R(1)));
indiag[i] = T(1) / tmp;
wit = ww.begin();
size_type nnl = 0, nnu = 0;
L[i].base_resize(K); U[i].base_resize(K+1);
typename _rsvector::iterator witL = L[i].begin(), witU = U[i].begin();
for (; wit != wite; ++wit) {
if (wit->c < i) { if (nnl < K) { *witL++ = *wit; ++nnl; } }
else if (nnu < K || wit->c == i)
{ CU(i, wit->c) = wit->e; *witU++ = *wit; ++nnu; }
}
L[i].base_resize(nnl); U[i].base_resize(nnu);
std::sort(L[i].begin(), L[i].end());
std::sort(U[i].begin(), U[i].end());
if (ip != i) {
typename _wsvector::const_iterator iti = CU.col(i).begin();
typename _wsvector::const_iterator itie = CU.col(i).end();
typename _wsvector::const_iterator itp = CU.col(ip).begin();
typename _wsvector::const_iterator itpe = CU.col(ip).end();
while (iti != itie && itp != itpe) {
if (iti->first < itp->first)
{ U.row(iti->first).swap_indices(i, ip); ++iti; }
else if (iti->first > itp->first)
{ U.row(itp->first).swap_indices(i,ip);++itp; }
else
{ U.row(iti->first).swap_indices(i, ip); ++iti; ++itp; }
}
for( ; iti != itie; ++iti) U.row(iti->first).swap_indices(i, ip);
for( ; itp != itpe; ++itp) U.row(itp->first).swap_indices(i, ip);
CU.swap_col(i, ip);
indperm.swap(i, ip);
indperminv.swap(ipvt[i], ipvt[ip]);
std::swap(ipvtinv[ipvt[i]], ipvtinv[ipvt[ip]]);
std::swap(ipvt[i], ipvt[ip]);
}
}
}
template<typename Matrix>
void ilutp_precond<Matrix>::do_ilutp(const Matrix& A, col_major) {
do_ilutp(gmm::transposed(A), row_major());
invert = true;
}
template <typename Matrix, typename V1, typename V2> inline
void mult(const ilutp_precond<Matrix>& P, const V1 &v1, V2 &v2) {
if (P.invert) {
gmm::copy(gmm::sub_vector(v1, P.indperm), v2);
gmm::lower_tri_solve(gmm::transposed(P.U), v2, false);
gmm::upper_tri_solve(gmm::transposed(P.L), v2, true);
}
else {
gmm::copy(v1, P.temporary);
gmm::lower_tri_solve(P.L, P.temporary, true);
gmm::upper_tri_solve(P.U, P.temporary, false);
gmm::copy(gmm::sub_vector(P.temporary, P.indperminv), v2);
}
}
template <typename Matrix, typename V1, typename V2> inline
void transposed_mult(const ilutp_precond<Matrix>& P,const V1 &v1,V2 &v2) {
if (P.invert) {
gmm::copy(v1, P.temporary);
gmm::lower_tri_solve(P.L, P.temporary, true);
gmm::upper_tri_solve(P.U, P.temporary, false);
gmm::copy(gmm::sub_vector(P.temporary, P.indperminv), v2);
}
else {
gmm::copy(gmm::sub_vector(v1, P.indperm), v2);
gmm::lower_tri_solve(gmm::transposed(P.U), v2, false);
gmm::upper_tri_solve(gmm::transposed(P.L), v2, true);
}
}
template <typename Matrix, typename V1, typename V2> inline
void left_mult(const ilutp_precond<Matrix>& P, const V1 &v1, V2 &v2) {
if (P.invert) {
gmm::copy(gmm::sub_vector(v1, P.indperm), v2);
gmm::lower_tri_solve(gmm::transposed(P.U), v2, false);
}
else {
copy(v1, v2);
gmm::lower_tri_solve(P.L, v2, true);
}
}
template <typename Matrix, typename V1, typename V2> inline
void right_mult(const ilutp_precond<Matrix>& P, const V1 &v1, V2 &v2) {
if (P.invert) {
copy(v1, v2);
gmm::upper_tri_solve(gmm::transposed(P.L), v2, true);
}
else {
copy(v1, P.temporary);
gmm::upper_tri_solve(P.U, P.temporary, false);
gmm::copy(gmm::sub_vector(P.temporary, P.indperminv), v2);
}
}
template <typename Matrix, typename V1, typename V2> inline
void transposed_left_mult(const ilutp_precond<Matrix>& P, const V1 &v1,
V2 &v2) {
if (P.invert) {
copy(v1, P.temporary);
gmm::upper_tri_solve(P.U, P.temporary, false);
gmm::copy(gmm::sub_vector(P.temporary, P.indperminv), v2);
}
else {
copy(v1, v2);
gmm::upper_tri_solve(gmm::transposed(P.L), v2, true);
}
}
template <typename Matrix, typename V1, typename V2> inline
void transposed_right_mult(const ilutp_precond<Matrix>& P, const V1 &v1,
V2 &v2) {
if (P.invert) {
copy(v1, v2);
gmm::lower_tri_solve(P.L, v2, true);
}
else {
gmm::copy(gmm::sub_vector(v1, P.indperm), v2);
gmm::lower_tri_solve(gmm::transposed(P.U), v2, false);
}
}
}
#endif
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