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220 lines
8.5 KiB
220 lines
8.5 KiB
/* -*- c++ -*- (enables emacs c++ mode) */
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/*===========================================================================
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Copyright (C) 2003-2015 Yves Renard
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This file is a part of GETFEM++
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Getfem++ is free software; you can redistribute it and/or modify it
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under the terms of the GNU Lesser General Public License as published
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by the Free Software Foundation; either version 3 of the License, or
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(at your option) any later version along with the GCC Runtime Library
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Exception either version 3.1 or (at your option) any later version.
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This program is distributed in the hope that it will be useful, but
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WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
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or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public
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License and GCC Runtime Library Exception for more details.
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You should have received a copy of the GNU Lesser General Public License
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along with this program; if not, write to the Free Software Foundation,
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Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301, USA.
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As a special exception, you may use this file as it is a part of a free
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software library without restriction. Specifically, if other files
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instantiate templates or use macros or inline functions from this file,
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or you compile this file and link it with other files to produce an
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executable, this file does not by itself cause the resulting executable
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to be covered by the GNU Lesser General Public License. This exception
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does not however invalidate any other reasons why the executable file
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might be covered by the GNU Lesser General Public License.
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===========================================================================*/
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/**@file gmm_precond_ildltt.h
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@author Yves Renard <Yves.Renard@insa-lyon.fr>
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@date June 30, 2003.
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@brief incomplete LDL^t (cholesky) preconditioner with fill-in and threshold.
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*/
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#ifndef GMM_PRECOND_ILDLTT_H
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#define GMM_PRECOND_ILDLTT_H
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// Store U = LT and D in indiag. On each line, the fill-in is the number
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// of non-zero elements on the line of the original matrix plus K, except if
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// the matrix is dense. In this case the fill-in is K on each line.
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#include "gmm_precond_ilut.h"
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namespace gmm {
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/** incomplete LDL^t (cholesky) preconditioner with fill-in and
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threshold. */
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template <typename Matrix>
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class ildltt_precond {
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public :
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typedef typename linalg_traits<Matrix>::value_type value_type;
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typedef typename number_traits<value_type>::magnitude_type magnitude_type;
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typedef rsvector<value_type> svector;
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row_matrix<svector> U;
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std::vector<magnitude_type> indiag;
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protected:
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size_type K;
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double eps;
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template<typename M> void do_ildltt(const M&, row_major);
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void do_ildltt(const Matrix&, col_major);
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public:
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void build_with(const Matrix& A, int k_ = -1, double eps_ = double(-1)) {
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if (k_ >= 0) K = k_;
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if (eps_ >= double(0)) eps = eps_;
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gmm::resize(U, mat_nrows(A), mat_ncols(A));
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indiag.resize(std::min(mat_nrows(A), mat_ncols(A)));
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do_ildltt(A, typename principal_orientation_type<typename
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linalg_traits<Matrix>::sub_orientation>::potype());
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}
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ildltt_precond(const Matrix& A, int k_, double eps_)
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: U(mat_nrows(A),mat_ncols(A)), K(k_), eps(eps_) { build_with(A); }
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ildltt_precond(void) { K=10; eps = 1E-7; }
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ildltt_precond(size_type k_, double eps_) : K(k_), eps(eps_) {}
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size_type memsize() const {
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return sizeof(*this) + nnz(U)*sizeof(value_type) + indiag.size() * sizeof(magnitude_type);
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}
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};
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template<typename Matrix> template<typename M>
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void ildltt_precond<Matrix>::do_ildltt(const M& A,row_major) {
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typedef value_type T;
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typedef typename number_traits<T>::magnitude_type R;
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size_type n = mat_nrows(A);
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if (n == 0) return;
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svector w(n);
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T tmp;
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R prec = default_tol(R()), max_pivot = gmm::abs(A(0,0)) * prec;
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gmm::clear(U);
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for (size_type i = 0; i < n; ++i) {
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gmm::copy(mat_const_row(A, i), w);
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double norm_row = gmm::vect_norm2(w);
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for (size_type krow = 0, k; krow < w.nb_stored(); ++krow) {
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typename svector::iterator wk = w.begin() + krow;
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if ((k = wk->c) >= i) break;
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if (gmm::is_complex(wk->e)) {
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tmp = gmm::conj(U(k, i))/indiag[k]; // not completely satisfactory ..
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gmm::add(scaled(mat_row(U, k), -tmp), w);
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}
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else {
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tmp = wk->e;
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if (gmm::abs(tmp) < eps * norm_row) { w.sup(k); --krow; }
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else { wk->e += tmp; gmm::add(scaled(mat_row(U, k), -tmp), w); }
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}
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}
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tmp = w[i];
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if (gmm::abs(gmm::real(tmp)) <= max_pivot)
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{ GMM_WARNING2("pivot " << i << " is too small"); tmp = T(1); }
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max_pivot = std::max(max_pivot, std::min(gmm::abs(tmp) * prec, R(1)));
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indiag[i] = R(1) / gmm::real(tmp);
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gmm::clean(w, eps * norm_row);
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gmm::scale(w, T(indiag[i]));
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std::sort(w.begin(), w.end(), elt_rsvector_value_less_<T>());
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typename svector::const_iterator wit = w.begin(), wite = w.end();
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for (size_type nnu = 0; wit != wite; ++wit) // copy to be optimized ...
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if (wit->c > i) { if (nnu < K) { U(i, wit->c) = wit->e; ++nnu; } }
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}
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}
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template<typename Matrix>
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void ildltt_precond<Matrix>::do_ildltt(const Matrix& A, col_major)
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{ do_ildltt(gmm::conjugated(A), row_major()); }
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template <typename Matrix, typename V1, typename V2> inline
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void mult(const ildltt_precond<Matrix>& P, const V1 &v1, V2 &v2) {
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gmm::copy(v1, v2);
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gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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gmm::upper_tri_solve(P.U, v2, true);
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}
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_mult(const ildltt_precond<Matrix>& P,const V1 &v1, V2 &v2)
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{ mult(P, v1, v2); }
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template <typename Matrix, typename V1, typename V2> inline
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void left_mult(const ildltt_precond<Matrix>& P, const V1 &v1, V2 &v2) {
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copy(v1, v2);
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gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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}
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template <typename Matrix, typename V1, typename V2> inline
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void right_mult(const ildltt_precond<Matrix>& P, const V1 &v1, V2 &v2)
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{ copy(v1, v2); gmm::upper_tri_solve(P.U, v2, true); }
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_left_mult(const ildltt_precond<Matrix>& P, const V1 &v1,
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V2 &v2) {
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copy(v1, v2);
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gmm::upper_tri_solve(P.U, v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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}
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_right_mult(const ildltt_precond<Matrix>& P, const V1 &v1,
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V2 &v2)
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{ copy(v1, v2); gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true); }
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// for compatibility with old versions
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template <typename Matrix>
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struct choleskyt_precond : public ildltt_precond<Matrix>{
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choleskyt_precond(const Matrix& A, int k_, double eps_)
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: ildltt_precond<Matrix>(A, k_, eps_) {}
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choleskyt_precond(void) {}
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} IS_DEPRECATED;
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template <typename Matrix, typename V1, typename V2> inline
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void mult(const choleskyt_precond<Matrix>& P, const V1 &v1, V2 &v2) {
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gmm::copy(v1, v2);
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gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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gmm::upper_tri_solve(P.U, v2, true);
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}
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_mult(const choleskyt_precond<Matrix>& P,const V1 &v1, V2 &v2)
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{ mult(P, v1, v2); }
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template <typename Matrix, typename V1, typename V2> inline
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void left_mult(const choleskyt_precond<Matrix>& P, const V1 &v1, V2 &v2) {
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copy(v1, v2);
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gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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}
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template <typename Matrix, typename V1, typename V2> inline
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void right_mult(const choleskyt_precond<Matrix>& P, const V1 &v1, V2 &v2)
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{ copy(v1, v2); gmm::upper_tri_solve(P.U, v2, true); }
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_left_mult(const choleskyt_precond<Matrix>& P, const V1 &v1,
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V2 &v2) {
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copy(v1, v2);
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gmm::upper_tri_solve(P.U, v2, true);
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for (size_type i = 0; i < P.indiag.size(); ++i) v2[i] *= P.indiag[i];
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}
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template <typename Matrix, typename V1, typename V2> inline
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void transposed_right_mult(const choleskyt_precond<Matrix>& P, const V1 &v1,
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V2 &v2)
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{ copy(v1, v2); gmm::lower_tri_solve(gmm::conjugated(P.U), v2, true); }
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}
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#endif
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