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AbstractLinAlgPack: C++ Interfaces For Vectors, Matrices And Related Linear Algebra Objects Version of the Day
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00001 // @HEADER 00002 // *********************************************************************** 00003 // 00004 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization 00005 // Copyright (2003) Sandia Corporation 00006 // 00007 // Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive 00008 // license for use of this work by or on behalf of the U.S. Government. 00009 // 00010 // This library is free software; you can redistribute it and/or modify 00011 // it under the terms of the GNU Lesser General Public License as 00012 // published by the Free Software Foundation; either version 2.1 of the 00013 // License, or (at your option) any later version. 00014 // 00015 // This library is distributed in the hope that it will be useful, but 00016 // WITHOUT ANY WARRANTY; without even the implied warranty of 00017 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 00018 // Lesser General Public License for more details. 00019 // 00020 // You should have received a copy of the GNU Lesser General Public 00021 // License along with this library; if not, write to the Free Software 00022 // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 00023 // USA 00024 // Questions? Contact Roscoe A. Bartlett (rabartl@sandia.gov) 00025 // 00026 // *********************************************************************** 00027 // @HEADER 00028 00029 #ifndef DENSE_V_P_S_T_P_T_M_T_V_H 00030 #define DENSE_V_P_S_T_P_T_M_T_V_H 00031 00032 #include "AbstractLinAlgPack/src/AbstractLinAlgPack_SpVectorClass.hpp" 00033 #include "AbstractLinAlgPack_SpVectorOp.hpp" 00034 #include "AbstractLinAlgPack/src/AbstractLinAlgPack_EtaVector.hpp" 00035 #include "AbstractLinAlgPack/src/AbstractLinAlgPack_GenPermMatrixSlice.hpp" 00036 #include "AbstractLinAlgPack_GenPermMatrixSliceOp.hpp" 00037 #include "AbstractLinAlgPack_LinAlgOpPackHack.hpp" 00038 #include "DenseLinAlgPack_DMatrixClass.hpp" 00039 #include "DenseLinAlgPack_DMatrixOut.hpp" 00040 #include "DenseLinAlgPack_AssertOp.hpp" 00041 #include "MiWorkspacePack.h" 00042 00043 namespace AbstractLinAlgPack { 00044 00051 template<class M_t, class V_t> 00052 void dense_Vp_StPtMtV( 00053 DVectorSlice *y 00054 ,value_type a 00055 ,const GenPermMatrixSlice &P 00056 ,BLAS_Cpp::Transp P_trans 00057 ,const M_t &M 00058 ,BLAS_Cpp::Transp M_trans 00059 ,const V_t &x 00060 ,value_type b 00061 ) 00062 { 00063 using BLAS_Cpp::no_trans; 00064 using BLAS_Cpp::trans; 00065 using BLAS_Cpp::trans_not; 00066 using BLAS_Cpp::rows; 00067 using BLAS_Cpp::cols; 00068 using DenseLinAlgPack::dot; 00069 using DenseLinAlgPack::DVector; 00070 using DenseLinAlgPack::Vt_S; 00071 using AbstractLinAlgPack::dot; 00072 using AbstractLinAlgPack::Vp_StMtV; 00073 using AbstractLinAlgPack::GenPermMatrixSlice; 00074 typedef AbstractLinAlgPack::EtaVector eta; 00075 using Teuchos::Workspace; 00076 Teuchos::WorkspaceStore* wss = Teuchos::get_default_workspace_store().get(); 00077 00078 // Validate the sizes 00079 // 00080 // y += op(P)*op(M)*x 00081 // 00082 const DenseLinAlgPack::size_type 00083 ny = y->size(), 00084 nx = x.size(), 00085 opM_rows = rows( M.rows(), M.cols(), M_trans ), 00086 opM_cols = cols( M.rows(), M.cols(), M_trans ); 00087 if( ny != rows( P.rows(), P.cols(), P_trans ) 00088 || nx != opM_cols 00089 || cols( P.rows(), P.cols(), P_trans ) != opM_rows ) 00090 throw std::length_error( "MatrixOp::Vp_StPtMtV(...) : Error, " 00091 "sizes of arguments does not match up" ); 00092 // 00093 // Compute y = b*y + a*op(P)*op(M)*x in a resonably efficient manner. This 00094 // implementation will assume that M is stored as a dense matrix. Either 00095 // t = op(M)*x is computed first (O(opM_rows*nx) flops) then y = b*y + a*op(P)*t 00096 // (O(ny) + O(P_nz) flops) or each row of t' = e(j)' * op(M) (O(nx) flops) 00097 // is computed one at a time and then y(i) = b*y(i) + a*t'*x (O(nx) flops) 00098 // where op(P)(i,j) = 1.0. In the latter case, there are P_nz rows 00099 // of op(M) that have to be generated so the total cost is O(P_nz*nx). 00100 // Therefore, we will do the former if opM_rows < P_nz and the latter otherwise. 00101 // 00102 if( !P.nz() ) { 00103 // y = b*y 00104 if(b==0.0) *y = 0.0; 00105 else if(b!=1.0) Vt_S(y,b); 00106 } 00107 else if( opM_rows > P.nz() || P.is_identity() ) { 00108 // t = op(M)*x 00109 Workspace<value_type> t_ws(wss,opM_rows); 00110 DVectorSlice t(&t_ws[0],t_ws.size()); 00111 LinAlgOpPack::V_MtV( &t, M, M_trans, x ); 00112 // y = b*y + a*op(P)*t 00113 Vp_StMtV( y, a, P, P_trans, t(), b ); 00114 } 00115 else { 00116 // y = b*y 00117 if(b==0.0) *y = 0.0; 00118 else if(b!=1.0) Vt_S(y,b); 00119 // Compute t' = e(j)' * op(M) then y(i) += a*t'*x where op(P)(i,j) = 1.0 00120 Workspace<value_type> t_ws(wss,opM_cols); 00121 DVectorSlice t(&t_ws[0],t_ws.size()); 00122 if( P.is_identity() ) { 00123 for( size_type k = 1; k <= P.nz(); ++k ) { 00124 const size_type 00125 i = k, 00126 j = k; 00127 // t = op(M') * e(j) 00128 LinAlgOpPack::V_MtV( &t, M, trans_not(M_trans), eta(j,opM_rows)() ); 00129 // y(i) += a*t'*x 00130 (*y)(i) += a * dot( t(), x ); 00131 } 00132 } 00133 else { 00134 for( GenPermMatrixSlice::const_iterator itr = P.begin(); itr != P.end(); ++itr ) { 00135 const DenseLinAlgPack::size_type 00136 i = P_trans == no_trans ? itr->row_i() : itr->col_j(), 00137 j = P_trans == no_trans ? itr->col_j() : itr->row_i(); 00138 // t = op(M') * e(j) 00139 LinAlgOpPack::V_MtV( &t, M, trans_not(M_trans), eta(j,opM_rows)() ); 00140 // y(i) += a*t'*x 00141 (*y)(i) += a * dot( t(), x ); 00142 } 00143 } 00144 } 00145 } 00146 00147 } // end namespace AbstractLinAlgPack 00148 00149 #endif // DENSE_V_P_S_T_P_T_M_T_V_H
1.7.4