LCOV - code coverage report
Current view: top level - ugbase/lib_algebra/small_algebra - additional_math.h (source / functions) Coverage Total Hit
Test: coverage.info Lines: 0.0 % 13 0
Test Date: 2025-09-21 23:31:46 Functions: 0.0 % 5 0

            Line data    Source code
       1              : /*
       2              :  * Copyright (c) 2013-2015:  G-CSC, Goethe University Frankfurt
       3              :  * Author: Martin Rupp
       4              :  * 
       5              :  * This file is part of UG4.
       6              :  * 
       7              :  * UG4 is free software: you can redistribute it and/or modify it under the
       8              :  * terms of the GNU Lesser General Public License version 3 (as published by the
       9              :  * Free Software Foundation) with the following additional attribution
      10              :  * requirements (according to LGPL/GPL v3 §7):
      11              :  * 
      12              :  * (1) The following notice must be displayed in the Appropriate Legal Notices
      13              :  * of covered and combined works: "Based on UG4 (www.ug4.org/license)".
      14              :  * 
      15              :  * (2) The following notice must be displayed at a prominent place in the
      16              :  * terminal output of covered works: "Based on UG4 (www.ug4.org/license)".
      17              :  * 
      18              :  * (3) The following bibliography is recommended for citation and must be
      19              :  * preserved in all covered files:
      20              :  * "Reiter, S., Vogel, A., Heppner, I., Rupp, M., and Wittum, G. A massively
      21              :  *   parallel geometric multigrid solver on hierarchically distributed grids.
      22              :  *   Computing and visualization in science 16, 4 (2013), 151-164"
      23              :  * "Vogel, A., Reiter, S., Rupp, M., Nägel, A., and Wittum, G. UG4 -- a novel
      24              :  *   flexible software system for simulating pde based models on high performance
      25              :  *   computers. Computing and visualization in science 16, 4 (2013), 165-179"
      26              :  * 
      27              :  * This program is distributed in the hope that it will be useful,
      28              :  * but WITHOUT ANY WARRANTY; without even the implied warranty of
      29              :  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
      30              :  * GNU Lesser General Public License for more details.
      31              :  */
      32              : 
      33              : #ifndef FAMG_ADDITIONAL_MATH_H_
      34              : #define FAMG_ADDITIONAL_MATH_H_
      35              : #include "lib_algebra/small_algebra/small_matrix/densematrix.h"
      36              : namespace ug{
      37              : 
      38              : inline void vecSum(double &erg, double alpha, double vec)
      39              : {
      40              :         erg = alpha * vec;
      41              : }
      42              : 
      43              : template<typename T>
      44              : inline void vecSum(typename T::value_type &erg, double alpha, const T &vec)
      45              : {
      46              :         erg = alpha * vec[0];
      47              :         for (size_t i = 1; i < vec.size(); i++)
      48              :                 erg += vec[i];
      49              :         erg *= alpha;
      50              : }
      51              : 
      52              : inline double vecSum(double alpha, double vec)
      53              : {
      54              :         return alpha * vec;
      55              : }
      56              : template<typename T>
      57              : inline typename T::value_type vecSum(double alpha, const T &vec)
      58              : {
      59              :         typename T::value_type erg;
      60              :         vecSum(erg, alpha, vec);
      61              :         return erg;
      62              : }
      63              : 
      64              : inline void matSum(double &erg, double alpha, double vec)
      65              : {
      66              :         erg = alpha * vec;
      67              : }
      68              : 
      69              : template<typename T1, typename T2>
      70              : inline void matSum(T1 &erg, double alpha, T2 &mat)
      71              : {
      72              :         for (size_t r = 0; mat.num_rows(); r++)
      73              :         {
      74              :                 erg[r] = mat(r, 0);
      75              :                 for (size_t c = 1; c < mat.num_cols(); c++)
      76              :                         erg[r] += mat(r, c);
      77              :                 erg[r] *= alpha;
      78              :         }
      79              : }
      80              : 
      81              : template<typename T1, typename T2>
      82              : inline T1 matSum(double alpha, T2 &mat)
      83              : {
      84              :         T1 erg;
      85              :         matSum(erg, alpha, mat);
      86              :         return erg;
      87              : }
      88              : 
      89              : template<typename T1>
      90              : inline typename DenseMatrix<T1>::value_type Sum1Mat1(const DenseMatrix<T1> &mat)
      91              : {
      92              :         typename DenseMatrix<T1>::value_type ret = 0.0;
      93              :         for (size_t r = 0; mat.num_rows(); r++)
      94              :                 for (size_t c = 1; c < mat.num_cols(); c++)
      95              :                         ret += mat(r, c);
      96              :         return ret;
      97              : }
      98              : 
      99              : inline double matTrace(const double d)
     100              : {
     101              :         return d;
     102              : }
     103              : 
     104              : template<typename T1>
     105              : inline double matTrace(const DenseMatrix<T1> &mat)
     106              : {
     107              :         double tr=0.0;
     108              :         const size_t rk = (mat.num_rows() < mat.num_cols()) ? mat.num_rows() : mat.num_cols();
     109              :         for (size_t k = 0; k<rk; k++)
     110              :         {
     111              :                 tr += mat(k, k);
     112              :         }
     113              :         return tr;
     114              : }
     115              : 
     116              : inline double matDiagMax(const double d)
     117              : {
     118              :         return d;
     119              : }
     120              : 
     121              : template<typename T1>
     122              : inline double matDiagMax(const DenseMatrix<T1> &mat)
     123              : {
     124              :         double val=0.0;
     125              :         double max=0.0;
     126              :         const size_t rk = (mat.num_rows() < mat.num_cols()) ? mat.num_rows() : mat.num_cols();
     127              :         for (size_t k = 0; k<rk; k++)
     128              :         {
     129              :                 double abs=fabs(mat(k, k));
     130              :                 if (abs>max) {
     131              :                         val = mat(k, k);
     132              :                         max = abs;
     133              :                 }
     134              :         }
     135              :         return val;
     136              : }
     137              : 
     138              : 
     139              : inline double Sum1Mat1(double d)
     140              : {
     141              :         return d;
     142              : }
     143              : 
     144              : inline void GetDiag(double &a, double b)
     145              : {
     146              :         a = b;
     147            0 : }
     148              : 
     149              : template<typename T1, typename T2>
     150            0 : inline void GetDiag(T1 &m1, const T2 &m)
     151              : {
     152              :         UG_ASSERT(m.num_rows()==m.num_cols(), "");
     153              :         m1.resize(m.num_rows(), m.num_rows());
     154              :         m1=0.0;
     155            0 :         for (size_t i = 0; i < m.num_rows(); i++)
     156            0 :                 m1(i, i) = m(i, i);
     157            0 : }
     158              : 
     159              : template<typename T1, typename T2>
     160              : inline void GetDiagSqrt(T1 &v, const T2 &m)
     161              : {
     162              :         UG_ASSERT(m.num_rows()==m.num_cols(), "");
     163              :         v.resize(m.num_rows());
     164              :         for (size_t i = 0; i < m.num_rows(); i++)
     165              :                 v[i] = sqrt(m(i, i));
     166              : }
     167              : 
     168              : inline void GetDiagSqrt(double &a, double b)
     169              : {
     170              :         a = sqrt(b);
     171              : }
     172              : 
     173              : inline double EnergyProd(double v1, double M, double v2)
     174              : {
     175              :         return v1 * M * v2;
     176              : }
     177              : 
     178              : template<typename T1, typename T2>
     179              : inline double EnergyProd(const T1 &v1, const DenseMatrix<T2> &M, const T1 &v2)
     180              : {
     181              :         double sum = 0;
     182              :         for (size_t r = 0; r < M.num_rows(); r++)
     183              :         {
     184              :                 double t = 0;
     185              :                 for (size_t c = 0; c < M.num_cols(); c++)
     186              :                         t += M(r, c) * v2[c];
     187              :                 sum += t * v1[r];
     188              :         }
     189              :         return sum;
     190              : }
     191              : 
     192              : template<typename TMatrix>
     193            0 : void BlockMatrixToDoubleMatrix(DenseMatrix<VariableArray2<double> > &Ad, TMatrix &Ab)
     194              : {
     195              :         const size_t blockSize = block_traits<typename TMatrix::value_type>::static_num_rows;
     196            0 :         Ad.resize(blockSize*Ab.num_rows(), blockSize*Ab.num_cols());
     197              : 
     198            0 :         for(size_t i=0; i<Ab.num_rows(); i++)
     199              :         {
     200            0 :                 for(size_t j=0; j<Ab.num_cols(); j++)
     201            0 :                         for(size_t r=0; r<blockSize; r++)
     202            0 :                                 for(size_t c=0; c<blockSize; c++)
     203            0 :                                         Ad(i*blockSize+r, j*blockSize+c) = BlockRef(Ab(i, j), r, c);
     204              :         }
     205            0 : }
     206              : 
     207              : }
     208              : #endif /* ADDITIONAL_MATH_H_ */
        

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