Commit be56f6db authored by Tomáš Oberhuber's avatar Tomáš Oberhuber
Browse files

Renaming rowLengths to compressedRowLengths in LambdaMatrix.

parent d6916fe6

Documentation/Examples/Matrices/LambdaMatrix/LambdaMatrixExample_Constructor.cpp

+4 −4
Original line number Diff line number Diff line
@@ -6,7 +6,7 @@ int main( int argc, char* argv[] ) 
   /***

    * Lambda functions defining the matrix.

    */

   auto rowLengths = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx ) -> int { return 1; };

   auto compressedRowLengths = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx ) -> int { return 1; };

   auto matrixElements1 = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx, const int localIdx, int& columnIdx, double& value ) {

         columnIdx = rowIdx;

         value =  1.0;
@@ -21,13 +21,13 @@ int main( int argc, char* argv[] ) 
   /***

    * Matrix construction with explicit type definition.

    */

   using MatrixType = decltype( TNL::Matrices::LambdaMatrixFactory< double, TNL::Devices::Host, int >::create( matrixElements1, rowLengths ) );

   MatrixType m1( size, size, matrixElements1, rowLengths );

   using MatrixType = decltype( TNL::Matrices::LambdaMatrixFactory< double, TNL::Devices::Host, int >::create( matrixElements1, compressedRowLengths ) );

   MatrixType m1( size, size, matrixElements1, compressedRowLengths );



   /***

    * Matrix construction using 'auto'.

    */

   auto m2 = TNL::Matrices::LambdaMatrixFactory< double, TNL::Devices::Host, int >::create( matrixElements2, rowLengths );

   auto m2 = TNL::Matrices::LambdaMatrixFactory< double, TNL::Devices::Host, int >::create( matrixElements2, compressedRowLengths );

   m2.setDimensions( size, size );



   std::cout << "The first lambda matrix: " << std::endl << m1 << std::endl;

Documentation/Examples/Matrices/LambdaMatrix/LambdaMatrixExample_forAllRows.cpp

+2 −2
Original line number Diff line number Diff line
@@ -10,14 +10,14 @@ void forRowsExample() 
   /***

    * Lambda functions defining the matrix.

    */

   auto rowLengths = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx ) -> int { return columns; };

   auto compressedRowLengths = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx ) -> int { return columns; };

   auto matrixElements = [=] __cuda_callable__ ( const int rows, const int columns, const int rowIdx, const int localIdx, int& columnIdx, double& value ) {

         columnIdx = localIdx;

         value = TNL::max( rowIdx - columnIdx + 1, 0 );

   };



   using MatrixFactory = TNL::Matrices::LambdaMatrixFactory< double, Device, int >;

   auto matrix = MatrixFactory::create( 5, 5, matrixElements, rowLengths );

   auto matrix = MatrixFactory::create( 5, 5, matrixElements, compressedRowLengths );



   TNL::Matrices::DenseMatrix< double, Device > denseMatrix( 5, 5 );

   auto denseView = denseMatrix.getView();