Changed tests for BiELL. (589d4c64) · Commits · TNL / tnl-dev

src/UnitTests/Matrices/SparseMatrixTest.hpp

+80 −26

Original line number	Diff line number	Diff line
		@@ -15,6 +15,7 @@

		// Temporary, until test_OperatorEquals doesn't work for all formats.
		#include <TNL/Matrices/ChunkedEllpack.h>
		#include <TNL/Matrices/BiEllpack.h>

		#ifdef HAVE_GTEST
		#include <gtest/gtest.h>
		@@ -200,7 +201,7 @@ void test_SetElement()
		/*
		* Sets up the following 10x10 sparse matrix:
		*
		* / 1 2 3 4 0 0 0 0 0 0 \
		* / 1 0 2 0 3 0 4 0 0 0 \
		* \| 5 6 7 0 0 0 0 0 0 0 \|
		* \| 8 9 10 11 12 13 14 15 0 0 \|
		* \| 16 17 0 0 0 0 0 0 0 0 \|
		@@ -222,12 +223,20 @@ void test_SetElement()

		typename Matrix::CompressedRowLengthsVector rowLengths;
		rowLengths.setSize( rows );
		rowLengths.setValue( 8 );
		// rowLengths.setValue( 8 );
		rowLengths.setElement( 0, 4 );
		rowLengths.setElement( 1, 3 );
		rowLengths.setElement( 2, 8 );
		rowLengths.setElement( 3, 2 );
		for( IndexType i = 4; i < 10; i++ )
		{
		rowLengths.setElement( i, 1 );
		}
		m.setCompressedRowLengths( rowLengths );

		RealType value = 1;
		for( IndexType i = 0; i < 4; i++ )
		m.setElement( 0, i, value++ );
		m.setElement( 0, 2 * i, value++ );

		for( IndexType i = 0; i < 3; i++ )
		m.setElement( 1, i, value++ );
		@@ -242,12 +251,12 @@ void test_SetElement()
		m.setElement( i, 0, value++ );

		EXPECT_EQ( m.getElement( 0, 0 ), 1 );
		EXPECT_EQ( m.getElement( 0, 1 ), 2 );
		EXPECT_EQ( m.getElement( 0, 2 ), 3 );
		EXPECT_EQ( m.getElement( 0, 3 ), 4 );
		EXPECT_EQ( m.getElement( 0, 4 ), 0 );
		EXPECT_EQ( m.getElement( 0, 1 ), 0 );
		EXPECT_EQ( m.getElement( 0, 2 ), 2 );
		EXPECT_EQ( m.getElement( 0, 3 ), 0 );
		EXPECT_EQ( m.getElement( 0, 4 ), 3 );
		EXPECT_EQ( m.getElement( 0, 5 ), 0 );
		EXPECT_EQ( m.getElement( 0, 6 ), 0 );
		EXPECT_EQ( m.getElement( 0, 6 ), 4 );
		EXPECT_EQ( m.getElement( 0, 7 ), 0 );
		EXPECT_EQ( m.getElement( 0, 8 ), 0 );
		EXPECT_EQ( m.getElement( 0, 9 ), 0 );
		@@ -746,43 +755,88 @@ void test_OperatorEquals()
		return;
		else
		{
		using CHELL_host = TNL::Matrices::ChunkedEllpack< RealType, TNL::Devices::Host, IndexType >;
		using CHELL_cuda = TNL::Matrices::ChunkedEllpack< RealType, TNL::Devices::Cuda, IndexType >;
		using BiELL_host = TNL::Matrices::BiEllpack< RealType, TNL::Devices::Host, IndexType >;
		using BiELL_cuda = TNL::Matrices::BiEllpack< RealType, TNL::Devices::Cuda, IndexType >;

		/*
		* Sets up the following 4x4 sparse matrix:
		* Sets up the following 8x8 sparse matrix:
		*
		* / 1 2 3 0 \
		* \| 0 4 0 5 \|
		* \| 6 7 8 0 \|
		* \ 0 9 10 11 /
		* / 1 2 3 0 4 5 0 0 \ 5
		* \| 0 6 0 7 0 0 0 0 \| 2
		* \| 0 8 9 0 10 0 0 0 \| 3
		* \| 0 11 12 13 14 0 0 0 \| 4
		* \| 0 15 0 0 0 0 0 0 \| 1
		* \| 0 16 17 18 19 20 21 0 \| 6
		* \| 22 23 24 25 26 27 28 0 \| 7
		* \ 29 30 31 32 33 34 35 36 / 8
		*/

		const IndexType m_rows = 4;
		const IndexType m_cols = 4;
		/* Sorted:
		*
		*
		* / 29 30 31 32 33 34 35 36 \
		* \| 22 23 24 25 26 27 28 \|
		* \| 16 17 18 19 20 21 \|
		* \| 1 2 3 4 5 \|
		* \| 11 12 13 14 \|
		* \| 8 9 10 \|
		* \| 6 7 \|
		* \ 15 /
		*/

		const IndexType m_rows = 8;
		const IndexType m_cols = 8;

		CHELL_host m_host;
		BiELL_host m_host;

		m_host.reset();
		m_host.setDimensions( m_rows, m_cols );
		typename CHELL_host::CompressedRowLengthsVector rowLengths;
		typename BiELL_host::CompressedRowLengthsVector rowLengths;
		rowLengths.setSize( m_rows );
		rowLengths.setValue( 3 );
		rowLengths.setElement(0, 5);
		rowLengths.setElement(1, 2);
		rowLengths.setElement(2, 3);
		rowLengths.setElement(3, 4);
		rowLengths.setElement(4, 1);
		rowLengths.setElement(5, 6);
		rowLengths.setElement(6, 7);
		rowLengths.setElement(7, 8);
		m_host.setCompressedRowLengths( rowLengths );

		RealType value = 1;
		for( IndexType i = 0; i < m_cols - 1; i++ ) // 0th row
		for( IndexType i = 0; i < 3; i++ ) // 0th row
		m_host.setElement( 0, i, value++ );

		m_host.setElement( 1, 1, value++ );
		m_host.setElement( 1, 3, value++ ); // 1st row
		m_host.setElement( 0, 4, value++ ); // 0th row
		m_host.setElement( 0, 5, value++ );

		for( IndexType i = 0; i < m_cols - 1; i++ ) // 2nd row
		m_host.setElement( 1, 1, value++ ); // 1st row
		m_host.setElement( 1, 3, value++ );

		for( IndexType i = 1; i < 3; i++ ) // 2nd row
		m_host.setElement( 2, i, value++ );

		for( IndexType i = 1; i < m_cols; i++ ) // 3rd row
		m_host.setElement( 2, 4, value++ ); // 2nd row


		for( IndexType i = 1; i < 5; i++ ) // 3rd row
		m_host.setElement( 3, i, value++ );

		m_host.setElement( 4, 1, value++ ); // 4th row

		for( IndexType i = 1; i < 7; i++ ) // 5th row
		m_host.setElement( 5, i, value++ );

		for( IndexType i = 0; i < 7; i++ ) // 6th row
		m_host.setElement( 6, i, value++ );

		for( IndexType i = 0; i < 8; i++ ) // 7th row
		m_host.setElement( 7, i, value++ );

		m_host.print( std::cout );

		m_host.printValues();

		EXPECT_EQ( m_host.getElement( 0, 0 ), 1 );
		EXPECT_EQ( m_host.getElement( 0, 1 ), 2 );
		EXPECT_EQ( m_host.getElement( 0, 2 ), 3 );
		@@ -803,7 +857,7 @@ void test_OperatorEquals()
		EXPECT_EQ( m_host.getElement( 3, 2 ), 10 );
		EXPECT_EQ( m_host.getElement( 3, 3 ), 11 );

		CHELL_cuda m_cuda;
		BiELL_cuda m_cuda;

		// Copy the host matrix into the cuda matrix
		m_cuda = m_host;