Writting documentation on tridiagonal matrix.

                       OUTPUT MultidiagonalMatrixExample_setElement.out )

ADD_CUSTOM_TARGET( RunMatricesExamples ALL DEPENDS

ADD_CUSTOM_TARGET( RunMultidiagonalMatricesExamples ALL DEPENDS

   MultidiagonalMatrixExample_Constructor.out

   MultidiagonalMatrixExample_Constructor_init_list_1.out

   MultidiagonalMatrixExample_Constructor_init_list_2.out

#include <iostream>

#include <TNL/Matrices/SparseMatrix.h>

#include <TNL/Algorithms/ParallelFor.h>

#include <TNL/Matrices/TridiagonalMatrix.h>

#include <TNL/Devices/Host.h>

#include <TNL/Devices/Cuda.h>

template< typename Device >

void initializerListExample()

void createTridiagonalMatrix()

{

   TNL::Matrices::SparseMatrix< double, Device > matrix {

      {  1,  2,  3,  4,  5 }, // row capacities

      6 };                    // number of matrix columns

   const int matrixSize = 6;

   for( int row = 0; row < matrix.getRows(); row++ )

      for( int column = 0; column <= row; column++ )

         matrix.setElement( row, column, row - column + 1 );

   std::cout << "General sparse matrix: " << std::endl << matrix << std::endl;

   /***

    * Setup the following matrix (dots represent zeros):

    * 

    * /  2 -1 .   .  .  . \

    * | -1  2 -1  .  .  . |

    * |  . -1  2 -1  .  . |

    * |  .  . -1  2 -1  . |

    * |  .  .  . -1  2 -1 |

    * \  .  .  .  . -1  2 /

    * 

    */

   TNL::Matrices::TridiagonalMatrix< double, Device > matrix( 

      matrixSize, {

   /***

    * To set the matrix elements we first extend the diagonals to their full

    * lengths even outside the matrix (dots represent zeros and zeros are

    * artificial zeros used for memory alignment):

    * 

    * 0 /  2 -1 .   .  .  . \    -> {  0,  2, -1 }

    *   | -1  2 -1  .  .  . |    -> { -1,  2, -1 }

    *   |  . -1  2 -1  .  . |    -> { -1,  2, -1 }

    *   |  .  . -1  2 -1  . |    -> { -1,  2, -1 }

    *   |  .  .  . -1  2 -1 |    -> { -1,  2, -1 }

    *   \  .  .  .  . -1  2 / 0  -> { -1,  2,  0 }

    * 

    */

      {  0,  2, -1 },

      { -1,  2, -1 },

      { -1,  2, -1 },

      { -1,  2, -1 },

      { -1,  2, -1 },

      { -1,  2,  0 }

      } );

   std::cout << "The matrix reads as: " << std::endl << matrix << std::endl;

}

int main( int argc, char* argv[] )

{

   std::cout << "Creating matrices on CPU ... " << std::endl;

   initializerListExample< TNL::Devices::Host >();

   std::cout << "Creating tridiagonal matrix on CPU ... " << std::endl;

   createTridiagonalMatrix< TNL::Devices::Host >();

#ifdef HAVE_CUDA

   std::cout << "Creating matrices on CUDA GPU ... " << std::endl;

   initializerListExample< TNL::Devices::Cuda >();

   std::cout << "Creating tridiagonal matrix on CUDA GPU ... " << std::endl;

   createTridiagonalMatrix< TNL::Devices::Cuda >();

#endif

}

#include <iostream>

#include <TNL/Matrices/SparseMatrix.h>

#include <TNL/Devices/Host.h>

template< typename Device >

void initializerListExample()

{

   TNL::Matrices::SparseMatrix< double, Device > matrix (

      5, // number of matrix rows

      5, // number of matrix columns

      {  // matrix elements definition

         {  0,  0,  2.0 },

         {  1,  0, -1.0 }, {  1,  1,  2.0 }, {  1,  2, -1.0 },

         {  2,  1, -1.0 }, {  2,  2,  2.0 }, {  2,  3, -1.0 },

         {  3,  2, -1.0 }, {  3,  3,  2.0 }, {  3,  4, -1.0 },

         {  4,  4,  2.0 } } );

   std::cout << "General sparse matrix: " << std::endl << matrix << std::endl;

}

int main( int argc, char* argv[] )

{

   std::cout << "Creating matrices on CPU ... " << std::endl;

   initializerListExample< TNL::Devices::Host >();

#ifdef HAVE_CUDA

   std::cout << "Creating matrices on CUDA GPU ... " << std::endl;

   initializerListExample< TNL::Devices::Cuda >();

#endif

}

TridiagonalMatrixExample_Constructor_init_list_2.cpp

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