From 8573f541dd5dd163e2f47b824787fe9464764c27 Mon Sep 17 00:00:00 2001
From: Tomas Oberhuber <tomas.oberhuber@fjfi.cvut.cz>
Date: Wed, 11 Dec 2019 18:00:42 +0100
Subject: [PATCH] Implementing sparse matrcies assignment.
---
src/TNL/Containers/Segments/CSR.hpp | 11 +-
src/TNL/Containers/Segments/Ellpack.hpp | 18 +-
src/TNL/Containers/Segments/SlicedEllpack.hpp | 6 +-
src/TNL/Matrices/Matrix.h | 9 +-
src/TNL/Matrices/SparseMatrix.h | 19 +-
src/TNL/Matrices/SparseMatrix.hpp | 88 +++-
src/UnitTests/Matrices/SparseMatrixTest.hpp | 494 +++++++++---------
7 files changed, 374 insertions(+), 271 deletions(-)
diff --git a/src/TNL/Containers/Segments/CSR.hpp b/src/TNL/Containers/Segments/CSR.hpp
index ef7431038c..ccb483125d 100644
--- a/src/TNL/Containers/Segments/CSR.hpp
+++ b/src/TNL/Containers/Segments/CSR.hpp
@@ -154,11 +154,12 @@ CSR< Device, Index >::
forSegments( IndexType first, IndexType last, Function& f, Args... args ) const
{
const auto offsetsView = this->offsets.getConstView();
- auto l = [=] __cuda_callable__ ( const IndexType i, Args... args ) mutable {
- const IndexType begin = offsetsView[ i ];
- const IndexType end = offsetsView[ i + 1 ];
- for( IndexType j = begin; j < end; j++ )
- if( ! f( i, j, args... ) )
+ auto l = [=] __cuda_callable__ ( const IndexType segmentIdx, Args... args ) mutable {
+ const IndexType begin = offsetsView[ segmentIdx ];
+ const IndexType end = offsetsView[ segmentIdx + 1 ];
+ IndexType localIdx( 0 );
+ for( IndexType globalIdx = begin; globalIdx < end; globalIdx++ )
+ if( ! f( segmentIdx, localIdx++, globalIdx, args... ) )
break;
};
Algorithms::ParallelFor< Device >::exec( first, last, l, args... );
diff --git a/src/TNL/Containers/Segments/Ellpack.hpp b/src/TNL/Containers/Segments/Ellpack.hpp
index d3d90be5e0..337009e99a 100644
--- a/src/TNL/Containers/Segments/Ellpack.hpp
+++ b/src/TNL/Containers/Segments/Ellpack.hpp
@@ -192,11 +192,12 @@ forSegments( IndexType first, IndexType last, Function& f, Args... args ) const
if( RowMajorOrder )
{
const IndexType segmentSize = this->segmentSize;
- auto l = [=] __cuda_callable__ ( const IndexType i, Args... args ) mutable {
- const IndexType begin = i * segmentSize;
+ auto l = [=] __cuda_callable__ ( const IndexType segmentIdx, Args... args ) mutable {
+ const IndexType begin = segmentIdx * segmentSize;
const IndexType end = begin + segmentSize;
- for( IndexType j = begin; j < end; j++ )
- if( ! f( i, j, args... ) )
+ IndexType localIdx( 0 );
+ for( IndexType globalIdx = begin; globalIdx < end; globalIdx++ )
+ if( ! f( segmentIdx, localIdx++, globalIdx, args... ) )
break;
};
Algorithms::ParallelFor< Device >::exec( first, last, l, args... );
@@ -205,11 +206,12 @@ forSegments( IndexType first, IndexType last, Function& f, Args... args ) const
{
const IndexType storageSize = this->getStorageSize();
const IndexType alignedSize = this->alignedSize;
- auto l = [=] __cuda_callable__ ( const IndexType i, Args... args ) mutable {
- const IndexType begin = i;
+ auto l = [=] __cuda_callable__ ( const IndexType segmentIdx, Args... args ) mutable {
+ const IndexType begin = segmentIdx;
const IndexType end = storageSize;
- for( IndexType j = begin; j < end; j += alignedSize )
- if( ! f( i, j, args... ) )
+ IndexType localIdx( 0 );
+ for( IndexType globalIdx = begin; globalIdx < end; globalIdx += alignedSize )
+ if( ! f( segmentIdx, localIdx++, globalIdx, args... ) )
break;
};
Algorithms::ParallelFor< Device >::exec( first, last, l, args... );
diff --git a/src/TNL/Containers/Segments/SlicedEllpack.hpp b/src/TNL/Containers/Segments/SlicedEllpack.hpp
index c8e74ec591..d721edb00b 100644
--- a/src/TNL/Containers/Segments/SlicedEllpack.hpp
+++ b/src/TNL/Containers/Segments/SlicedEllpack.hpp
@@ -225,8 +225,9 @@ forSegments( IndexType first, IndexType last, Function& f, Args... args ) const
const IndexType segmentSize = sliceSegmentSizes_view[ sliceIdx ];
const IndexType begin = sliceOffsets_view[ sliceIdx ] + segmentInSliceIdx * segmentSize;
const IndexType end = begin + segmentSize;
+ IndexType localIdx( 0 );
for( IndexType globalIdx = begin; globalIdx < end; globalIdx++ )
- if( ! f( segmentIdx, globalIdx, args... ) )
+ if( ! f( segmentIdx, localIdx++, globalIdx, args... ) )
break;
};
Algorithms::ParallelFor< Device >::exec( first, last, l, args... );
@@ -239,8 +240,9 @@ forSegments( IndexType first, IndexType last, Function& f, Args... args ) const
const IndexType segmentSize = sliceSegmentSizes_view[ sliceIdx ];
const IndexType begin = sliceOffsets_view[ sliceIdx ] + segmentInSliceIdx;
const IndexType end = sliceOffsets_view[ sliceIdx + 1 ];
+ IndexType localIdx( 0 );
for( IndexType globalIdx = begin; globalIdx < end; globalIdx += SliceSize )
- if( ! f( segmentIdx, globalIdx, args... ) )
+ if( ! f( segmentIdx, localIdx++, globalIdx, args... ) )
break;
};
Algorithms::ParallelFor< Device >::exec( first, last, l, args... );
diff --git a/src/TNL/Matrices/Matrix.h b/src/TNL/Matrices/Matrix.h
index a877fd5c24..4a038eb2e8 100644
--- a/src/TNL/Matrices/Matrix.h
+++ b/src/TNL/Matrices/Matrix.h
@@ -39,7 +39,7 @@ public:
using RealAllocatorType = RealAllocator;
Matrix( const RealAllocatorType& allocator = RealAllocatorType() );
-
+
Matrix( const IndexType rows,
const IndexType columns,
const RealAllocatorType& allocator = RealAllocatorType() );
@@ -100,9 +100,9 @@ public:
virtual Real getElement( const IndexType row,
const IndexType column ) const = 0;
-
+
const ValuesVector& getValues() const;
-
+
ValuesVector& getValues();
// TODO: parallelize and optimize for sparse matrices
@@ -137,7 +137,8 @@ public:
__cuda_callable__
Index getValuesSize() const;
- protected:
+ // TODO: restore this
+ //protected:
IndexType rows, columns, numberOfColors;
diff --git a/src/TNL/Matrices/SparseMatrix.h b/src/TNL/Matrices/SparseMatrix.h
index 268fba6d39..b6a618e105 100644
--- a/src/TNL/Matrices/SparseMatrix.h
+++ b/src/TNL/Matrices/SparseMatrix.h
@@ -39,7 +39,7 @@ class SparseMatrix : public Matrix< Real, Device, Index, RealAllocator >
using ConstRowsCapacitiesView = typename RowsCapacitiesView::ConstViewType;
using ValuesVectorType = typename Matrix< Real, Device, Index, RealAllocator >::ValuesVector;
using ColumnsVectorType = Containers::Vector< IndexType, DeviceType, IndexType, IndexAllocatorType >;
-
+
// TODO: remove this - it is here only for compatibility with original matrix implementation
typedef Containers::Vector< IndexType, DeviceType, IndexType > CompressedRowLengthsVector;
typedef Containers::VectorView< IndexType, DeviceType, IndexType > CompressedRowLengthsVectorView;
@@ -64,6 +64,9 @@ class SparseMatrix : public Matrix< Real, Device, Index, RealAllocator >
void setCompressedRowLengths( ConstCompressedRowLengthsVectorView rowLengths );
+ template< typename Vector >
+ void getCompressedRowLengths( Vector& rowLengths ) const;
+
IndexType getRowLength( const IndexType row ) const;
__cuda_callable__
@@ -167,10 +170,16 @@ class SparseMatrix : public Matrix< Real, Device, Index, RealAllocator >
template< typename Fetch, typename Reduce, typename Keep, typename FetchReal >
void rowsReduction( IndexType first, IndexType last, Fetch& fetch, Reduce& reduce, Keep& keep, const FetchReal& zero ) const;
-
+
template< typename Fetch, typename Reduce, typename Keep, typename FetchReal >
void allRowsReduction( Fetch& fetch, Reduce& reduce, Keep& keep, const FetchReal& zero ) const;
+ template< typename Function >
+ void forRows( IndexType first, IndexType last, Function& function ) const;
+
+ template< typename Function >
+ void forAllRows( Function& function ) const;
+
template< typename Vector1, typename Vector2 >
bool performSORIteration( const Vector1& b,
const IndexType row,
@@ -201,7 +210,9 @@ class SparseMatrix : public Matrix< Real, Device, Index, RealAllocator >
__cuda_callable__
IndexType getPaddingIndex() const;
- protected:
+
+// TODO: restore it and also in Matrix
+// protected:
ColumnsVectorType columnIndexes;
@@ -210,6 +221,8 @@ class SparseMatrix : public Matrix< Real, Device, Index, RealAllocator >
IndexAllocator indexAlloctor;
RealAllocator realAllocator;
+
+
};
} // namespace Conatiners
diff --git a/src/TNL/Matrices/SparseMatrix.hpp b/src/TNL/Matrices/SparseMatrix.hpp
index e26693f6a1..3605daaef4 100644
--- a/src/TNL/Matrices/SparseMatrix.hpp
+++ b/src/TNL/Matrices/SparseMatrix.hpp
@@ -116,6 +116,32 @@ setCompressedRowLengths( ConstCompressedRowLengthsVectorView rowLengths )
this->columnIndexes = this->getPaddingIndex();
}
+template< typename Real,
+ template< typename, typename > class Segments,
+ typename Device,
+ typename Index,
+ typename RealAllocator,
+ typename IndexAllocator >
+ template< typename Vector >
+void
+SparseMatrix< Real, Segments, Device, Index, RealAllocator, IndexAllocator >::
+getCompressedRowLengths( Vector& rowLengths ) const
+{
+ rowLengths.setSize( this->getRows() );
+ rowLengths = 0;
+ auto rowLengths_view = rowLengths.getView();
+ auto fetch = [] __cuda_callable__ ( IndexType row, IndexType column, const RealType& value ) -> IndexType {
+ return ( value != 0.0 );
+ };
+ auto reduce = [] __cuda_callable__ ( IndexType& aux, const IndexType a ) {
+ aux += a;
+ };
+ auto keep = [=] __cuda_callable__ ( const IndexType rowIdx, const IndexType value ) mutable {
+ rowLengths_view[ rowIdx ] = value;
+ };
+ this->allRowsReduction( fetch, reduce, keep, 0 );
+}
+
template< typename Real,
template< typename, typename > class Segments,
typename Device,
@@ -554,6 +580,43 @@ allRowsReduction( Fetch& fetch, Reduce& reduce, Keep& keep, const FetchReal& zer
this->rowsReduction( 0, this->getRows(), fetch, reduce, keep, zero );
}
+template< typename Real,
+ template< typename, typename > class Segments,
+ typename Device,
+ typename Index,
+ typename RealAllocator,
+ typename IndexAllocator >
+ template< typename Function >
+void
+SparseMatrix< Real, Segments, Device, Index, RealAllocator, IndexAllocator >::
+forRows( IndexType first, IndexType last, Function& function ) const
+{
+ const auto columns_view = this->columnIndexes.getConstView();
+ const auto values_view = this->values.getConstView();
+ const IndexType paddingIndex_ = this->getPaddingIndex();
+ auto fetch_ = [=] __cuda_callable__ ( IndexType rowIdx, IndexType localIdx, IndexType globalIdx ) mutable -> decltype( fetch( IndexType(), IndexType(), RealType() ) ) {
+ IndexType columnIdx = columns_view[ globalIdx ];
+ if( columnIdx != paddingIndex_ )
+ return fetch( rowIdx, columnIdx, values_view[ globalIdx ] );
+ return zero;
+ };
+ this->segments.segmentsReduction( first, last, fetch_, reduce, keep, zero );
+
+}
+
+template< typename Real,
+ template< typename, typename > class Segments,
+ typename Device,
+ typename Index,
+ typename RealAllocator,
+ typename IndexAllocator >
+ template< typename Function >
+void
+SparseMatrix< Real, Segments, Device, Index, RealAllocator, IndexAllocator >::
+forAllRows( Function& function ) const
+{
+ this->forRows( 0, this->getRows(), function );
+}
/*template< typename Real,
template< typename, typename > class Segments,
@@ -638,12 +701,31 @@ SparseMatrix< Real, Segments, Device, Index, RealAllocator, IndexAllocator >&
SparseMatrix< Real, Segments, Device, Index, RealAllocator, IndexAllocator >::
operator=( const SparseMatrix< Real2, Segments2, Device2, Index2, RealAllocator2, IndexAllocator2 >& matrix )
{
+ using RHSMatrixType = SparseMatrix< Real2, Segments2, Device2, Index2, RealAllocator2, IndexAllocator2 >;
if( std::is_same< Device, Device2 >::value )
{
-
+ RowsCapacitiesType rowLengths;
+ matrix.getCompressedRowLengths( rowLengths );
+ this->setCompressedRowLengths( rowLengths );
+ // TODO: Replace this with SparseMatrixView
+ const auto matrix_columns_view = matrix.columnIndexes.getConstView();
+ const auto matrix_values_view = matrix.values.getConstView();
+ const auto segments_view = this->segments.getConstView();
+ auto this_columns_view = this->columnIndexes.getView();
+ auto this_values_view = this->values.getView();
+ const IndexType paddingIndex = this->getPaddingIndex();
+ auto f = [=] __cuda_callable__ ( IndexType rowIdx, IndexType localIdx, IndexType globalIdx ) {
+ const IndexType column = matrix_columns_view[ globalIdx ];
+ if( column != paddingIndex )
+ {
+ const RealType value = matrix_values_view[ globalIdx ];
+ IndexType thisGlobalIdx = segments_view.getGlobalIdx( rowIdx, localIdx );
+ this_columns_view[ thisGlobalIdx ] = column;
+ this_values_view[ thisGlobalIdx ] = value;
+ }
+ };
+ matrix.forAllRows( f );
}
-
-
}
template< typename Real,
diff --git a/src/UnitTests/Matrices/SparseMatrixTest.hpp b/src/UnitTests/Matrices/SparseMatrixTest.hpp
index b366f4e2fe..07a60178f1 100644
--- a/src/UnitTests/Matrices/SparseMatrixTest.hpp
+++ b/src/UnitTests/Matrices/SparseMatrixTest.hpp
@@ -18,7 +18,7 @@
#include <TNL/Matrices/AdEllpack.h>
#include <TNL/Matrices/BiEllpack.h>
-#ifdef HAVE_GTEST
+#ifdef HAVE_GTEST
#include <gtest/gtest.h>
template< typename MatrixHostFloat, typename MatrixHostInt >
@@ -36,7 +36,7 @@ void cuda_test_GetType()
bool testRan = false;
EXPECT_TRUE( testRan );
std::cout << "\nTEST DID NOT RUN. NOT WORKING.\n\n";
- std::cerr << "This test has not been implemented properly yet.\n" << std::endl;
+ std::cerr << "This test has not been implemented properly yet.\n" << std::endl;
}
template< typename Matrix >
@@ -45,13 +45,13 @@ void test_SetDimensions()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
const IndexType rows = 9;
const IndexType cols = 8;
-
+
Matrix m;
m.setDimensions( rows, cols );
-
+
EXPECT_EQ( m.getRows(), 9 );
EXPECT_EQ( m.getColumns(), 8 );
}
@@ -62,41 +62,41 @@ void test_SetCompressedRowLengths()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
const IndexType rows = 10;
const IndexType cols = 11;
-
+
Matrix m;
m.reset();
m.setDimensions( rows, cols );
typename Matrix::CompressedRowLengthsVector rowLengths;
rowLengths.setSize( rows );
rowLengths.setValue( 3 );
-
+
IndexType rowLength = 1;
for( IndexType i = 2; i < rows; i++ )
rowLengths.setElement( i, rowLength++ );
-
+
m.setCompressedRowLengths( rowLengths );
-
+
// Insert values into the rows.
RealType value = 1;
-
+
for( IndexType i = 0; i < 3; i++ ) // 0th row
m.setElement( 0, i, value++ );
-
+
for( IndexType i = 0; i < 3; i++ ) // 1st row
m.setElement( 1, i, value++ );
-
+
for( IndexType i = 0; i < 1; i++ ) // 2nd row
m.setElement( 2, i, value++ );
-
+
for( IndexType i = 0; i < 2; i++ ) // 3rd row
m.setElement( 3, i, value++ );
-
+
for( IndexType i = 0; i < 3; i++ ) // 4th row
m.setElement( 4, i, value++ );
-
+
for( IndexType i = 0; i < 4; i++ ) // 5th row
m.setElement( 5, i, value++ );
@@ -111,8 +111,8 @@ void test_SetCompressedRowLengths()
for( IndexType i = 0; i < 8; i++ ) // 9th row
m.setElement( 9, i, value++ );
-
-
+
+
EXPECT_EQ( m.getNonZeroRowLength( 0 ), 3 );
EXPECT_EQ( m.getNonZeroRowLength( 1 ), 3 );
EXPECT_EQ( m.getNonZeroRowLength( 2 ), 1 );
@@ -131,21 +131,21 @@ void test_SetLike()
using RealType = typename Matrix1::RealType;
using DeviceType = typename Matrix1::DeviceType;
using IndexType = typename Matrix1::IndexType;
-
+
const IndexType rows = 8;
const IndexType cols = 7;
-
+
Matrix1 m1;
m1.reset();
m1.setDimensions( rows + 1, cols + 2 );
-
+
Matrix2 m2;
m2.reset();
m2.setDimensions( rows, cols );
-
+
m1.setLike( m2 );
-
-
+
+
EXPECT_EQ( m1.getRows(), m2.getRows() );
EXPECT_EQ( m1.getColumns(), m2.getColumns() );
}
@@ -174,7 +174,7 @@ void test_GetNumberOfNonzeroMatrixElements()
const IndexType rows = 10;
const IndexType cols = 10;
-
+
Matrix m;
m.reset();
@@ -225,7 +225,7 @@ void test_Reset()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 5x4 sparse matrix:
*
@@ -235,16 +235,16 @@ void test_Reset()
* | 0 0 0 0 |
* \ 0 0 0 0 /
*/
-
+
const IndexType rows = 5;
const IndexType cols = 4;
-
+
Matrix m;
m.setDimensions( rows, cols );
-
+
m.reset();
-
-
+
+
EXPECT_EQ( m.getRows(), 0 );
EXPECT_EQ( m.getColumns(), 0 );
}
@@ -255,7 +255,7 @@ void test_SetElement()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 10x10 sparse matrix:
*
@@ -270,15 +270,15 @@ void test_SetElement()
* | 22 23 24 25 26 27 28 29 30 31 |
* \ 32 33 34 35 36 37 38 39 40 41 /
*/
-
+
const IndexType rows = 10;
const IndexType cols = 10;
-
+
Matrix m;
m.reset();
-
+
m.setDimensions( rows, cols );
-
+
typename Matrix::CompressedRowLengthsVector rowLengths;
rowLengths.setSize( rows );
rowLengths.setElement( 0, 4 );
@@ -292,29 +292,29 @@ void test_SetElement()
rowLengths.setElement( 8, 10 );
rowLengths.setElement( 9, 10 );
m.setCompressedRowLengths( rowLengths );
-
+
RealType value = 1;
for( IndexType i = 0; i < 4; i++ )
m.setElement( 0, 2 * i, value++ );
-
+
for( IndexType i = 0; i < 3; i++ )
m.setElement( 1, i, value++ );
-
+
for( IndexType i = 0; i < 8; i++ )
m.setElement( 2, i, value++ );
-
+
for( IndexType i = 0; i < 2; i++ )
m.setElement( 3, i, value++ );
-
+
for( IndexType i = 4; i < 8; i++ )
m.setElement( i, 0, value++ );
-
+
for( IndexType j = 8; j < rows; j++)
{
for( IndexType i = 0; i < cols; i++ )
m.setElement( j, i, value++ );
}
-
+
EXPECT_EQ( m.getElement( 0, 0 ), 1 );
EXPECT_EQ( m.getElement( 0, 1 ), 0 );
EXPECT_EQ( m.getElement( 0, 2 ), 2 );
@@ -325,7 +325,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 0, 7 ), 0 );
EXPECT_EQ( m.getElement( 0, 8 ), 0 );
EXPECT_EQ( m.getElement( 0, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 1, 0 ), 5 );
EXPECT_EQ( m.getElement( 1, 1 ), 6 );
EXPECT_EQ( m.getElement( 1, 2 ), 7 );
@@ -336,7 +336,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 1, 7 ), 0 );
EXPECT_EQ( m.getElement( 1, 8 ), 0 );
EXPECT_EQ( m.getElement( 1, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 2, 0 ), 8 );
EXPECT_EQ( m.getElement( 2, 1 ), 9 );
EXPECT_EQ( m.getElement( 2, 2 ), 10 );
@@ -347,7 +347,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 2, 7 ), 15 );
EXPECT_EQ( m.getElement( 2, 8 ), 0 );
EXPECT_EQ( m.getElement( 2, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 3, 0 ), 16 );
EXPECT_EQ( m.getElement( 3, 1 ), 17 );
EXPECT_EQ( m.getElement( 3, 2 ), 0 );
@@ -358,7 +358,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 3, 7 ), 0 );
EXPECT_EQ( m.getElement( 3, 8 ), 0 );
EXPECT_EQ( m.getElement( 3, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 4, 0 ), 18 );
EXPECT_EQ( m.getElement( 4, 1 ), 0 );
EXPECT_EQ( m.getElement( 4, 2 ), 0 );
@@ -369,7 +369,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 4, 7 ), 0 );
EXPECT_EQ( m.getElement( 4, 8 ), 0 );
EXPECT_EQ( m.getElement( 4, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 5, 0 ), 19 );
EXPECT_EQ( m.getElement( 5, 1 ), 0 );
EXPECT_EQ( m.getElement( 5, 2 ), 0 );
@@ -380,7 +380,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 5, 7 ), 0 );
EXPECT_EQ( m.getElement( 5, 8 ), 0 );
EXPECT_EQ( m.getElement( 5, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 6, 0 ), 20 );
EXPECT_EQ( m.getElement( 6, 1 ), 0 );
EXPECT_EQ( m.getElement( 6, 2 ), 0 );
@@ -391,7 +391,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 6, 7 ), 0 );
EXPECT_EQ( m.getElement( 6, 8 ), 0 );
EXPECT_EQ( m.getElement( 6, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 7, 0 ), 21 );
EXPECT_EQ( m.getElement( 7, 1 ), 0 );
EXPECT_EQ( m.getElement( 7, 2 ), 0 );
@@ -402,7 +402,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 7, 7 ), 0 );
EXPECT_EQ( m.getElement( 7, 8 ), 0 );
EXPECT_EQ( m.getElement( 7, 9 ), 0 );
-
+
EXPECT_EQ( m.getElement( 8, 0 ), 22 );
EXPECT_EQ( m.getElement( 8, 1 ), 23 );
EXPECT_EQ( m.getElement( 8, 2 ), 24 );
@@ -413,7 +413,7 @@ void test_SetElement()
EXPECT_EQ( m.getElement( 8, 7 ), 29 );
EXPECT_EQ( m.getElement( 8, 8 ), 30 );
EXPECT_EQ( m.getElement( 8, 9 ), 31 );
-
+
EXPECT_EQ( m.getElement( 9, 0 ), 32 );
EXPECT_EQ( m.getElement( 9, 1 ), 33 );
EXPECT_EQ( m.getElement( 9, 2 ), 34 );
@@ -432,7 +432,7 @@ void test_AddElement()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 6x5 sparse matrix:
*
@@ -443,10 +443,10 @@ void test_AddElement()
* | 0 11 0 0 0 |
* \ 0 0 0 12 0 /
*/
-
+
const IndexType rows = 6;
const IndexType cols = 5;
-
+
Matrix m;
m.reset();
m.setDimensions( rows, cols );
@@ -454,61 +454,61 @@ void test_AddElement()
rowLengths.setSize( rows );
rowLengths.setValue( 3 );
m.setCompressedRowLengths( rowLengths );
-
+
RealType value = 1;
for( IndexType i = 0; i < cols - 2; i++ ) // 0th row
m.setElement( 0, i, value++ );
-
+
for( IndexType i = 1; i < cols - 1; i++ ) // 1st row
m.setElement( 1, i, value++ );
-
+
for( IndexType i = 2; i < cols; i++ ) // 2nd row
m.setElement( 2, i, value++ );
-
+
m.setElement( 3, 0, value++ ); // 3rd row
-
+
m.setElement( 4, 1, value++ ); // 4th row
-
+
m.setElement( 5, 3, value++ ); // 5th row
-
-
+
+
// Check the set elements
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 ), 0 );
EXPECT_EQ( m.getElement( 0, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 1, 0 ), 0 );
EXPECT_EQ( m.getElement( 1, 1 ), 4 );
EXPECT_EQ( m.getElement( 1, 2 ), 5 );
EXPECT_EQ( m.getElement( 1, 3 ), 6 );
EXPECT_EQ( m.getElement( 1, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 2, 0 ), 0 );
EXPECT_EQ( m.getElement( 2, 1 ), 0 );
EXPECT_EQ( m.getElement( 2, 2 ), 7 );
EXPECT_EQ( m.getElement( 2, 3 ), 8 );
EXPECT_EQ( m.getElement( 2, 4 ), 9 );
-
+
EXPECT_EQ( m.getElement( 3, 0 ), 10 );
EXPECT_EQ( m.getElement( 3, 1 ), 0 );
EXPECT_EQ( m.getElement( 3, 2 ), 0 );
EXPECT_EQ( m.getElement( 3, 3 ), 0 );
EXPECT_EQ( m.getElement( 3, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 4, 0 ), 0 );
EXPECT_EQ( m.getElement( 4, 1 ), 11 );
EXPECT_EQ( m.getElement( 4, 2 ), 0 );
EXPECT_EQ( m.getElement( 4, 3 ), 0 );
EXPECT_EQ( m.getElement( 4, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 5, 0 ), 0 );
EXPECT_EQ( m.getElement( 5, 1 ), 0 );
EXPECT_EQ( m.getElement( 5, 2 ), 0 );
EXPECT_EQ( m.getElement( 5, 3 ), 12 );
EXPECT_EQ( m.getElement( 5, 4 ), 0 );
-
+
// Add new elements to the old elements with a multiplying factor applied to the old elements.
/*
@@ -521,7 +521,7 @@ void test_AddElement()
* | 0 11 0 0 0 |
* \ 0 0 0 12 0 /
*/
-
+
/*
* The following setup results in the following 6x5 sparse matrix:
*
@@ -532,57 +532,57 @@ void test_AddElement()
* | 0 35 14 15 0 |
* \ 0 0 16 41 18 /
*/
-
+
RealType newValue = 1;
for( IndexType i = 0; i < cols - 2; i++ ) // 0th row
m.addElement( 0, i, newValue++, 2.0 );
-
+
for( IndexType i = 1; i < cols - 1; i++ ) // 1st row
m.addElement( 1, i, newValue++, 2.0 );
-
+
for( IndexType i = 2; i < cols; i++ ) // 2nd row
m.addElement( 2, i, newValue++, 2.0 );
-
+
for( IndexType i = 0; i < cols - 2; i++ ) // 3rd row
m.addElement( 3, i, newValue++, 2.0 );
-
+
for( IndexType i = 1; i < cols - 1; i++ ) // 4th row
m.addElement( 4, i, newValue++, 2.0 );
-
+
for( IndexType i = 2; i < cols; i++ ) // 5th row
m.addElement( 5, i, newValue++, 2.0 );
-
-
+
+
EXPECT_EQ( m.getElement( 0, 0 ), 3 );
EXPECT_EQ( m.getElement( 0, 1 ), 6 );
EXPECT_EQ( m.getElement( 0, 2 ), 9 );
EXPECT_EQ( m.getElement( 0, 3 ), 0 );
EXPECT_EQ( m.getElement( 0, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 1, 0 ), 0 );
EXPECT_EQ( m.getElement( 1, 1 ), 12 );
EXPECT_EQ( m.getElement( 1, 2 ), 15 );
EXPECT_EQ( m.getElement( 1, 3 ), 18 );
EXPECT_EQ( m.getElement( 1, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 2, 0 ), 0 );
EXPECT_EQ( m.getElement( 2, 1 ), 0 );
EXPECT_EQ( m.getElement( 2, 2 ), 21 );
EXPECT_EQ( m.getElement( 2, 3 ), 24 );
EXPECT_EQ( m.getElement( 2, 4 ), 27 );
-
+
EXPECT_EQ( m.getElement( 3, 0 ), 30 );
EXPECT_EQ( m.getElement( 3, 1 ), 11 );
EXPECT_EQ( m.getElement( 3, 2 ), 12 );
EXPECT_EQ( m.getElement( 3, 3 ), 0 );
EXPECT_EQ( m.getElement( 3, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 4, 0 ), 0 );
EXPECT_EQ( m.getElement( 4, 1 ), 35 );
EXPECT_EQ( m.getElement( 4, 2 ), 14 );
EXPECT_EQ( m.getElement( 4, 3 ), 15 );
EXPECT_EQ( m.getElement( 4, 4 ), 0 );
-
+
EXPECT_EQ( m.getElement( 5, 0 ), 0 );
EXPECT_EQ( m.getElement( 5, 1 ), 0 );
EXPECT_EQ( m.getElement( 5, 2 ), 16 );
@@ -596,7 +596,7 @@ void test_SetRow()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 3x7 sparse matrix:
*
@@ -604,10 +604,10 @@ void test_SetRow()
* | 2 2 2 0 0 0 0 |
* \ 3 3 3 0 0 0 0 /
*/
-
+
const IndexType rows = 3;
const IndexType cols = 7;
-
+
Matrix m;
m.reset();
m.setDimensions( rows, cols );
@@ -616,7 +616,7 @@ void test_SetRow()
rowLengths.setValue( 6 );
rowLengths.setElement( 1, 3 );
m.setCompressedRowLengths( rowLengths );
-
+
RealType value = 1;
for( IndexType i = 0; i < 3; i++ )
{
@@ -624,19 +624,19 @@ void test_SetRow()
m.setElement( 1, i, value + 1 );
m.setElement( 2, i, value + 2 );
}
-
+
RealType row1 [ 3 ] = { 11, 11, 11 }; IndexType colIndexes1 [ 3 ] = { 0, 1, 2 };
RealType row2 [ 3 ] = { 22, 22, 22 }; IndexType colIndexes2 [ 3 ] = { 0, 1, 2 };
RealType row3 [ 3 ] = { 33, 33, 33 }; IndexType colIndexes3 [ 3 ] = { 3, 4, 5 };
-
+
RealType row = 0;
IndexType elements = 3;
-
+
m.setRow( row++, colIndexes1, row1, elements );
m.setRow( row++, colIndexes2, row2, elements );
m.setRow( row++, colIndexes3, row3, elements );
-
-
+
+
EXPECT_EQ( m.getElement( 0, 0 ), 11 );
EXPECT_EQ( m.getElement( 0, 1 ), 11 );
EXPECT_EQ( m.getElement( 0, 2 ), 11 );
@@ -644,7 +644,7 @@ void test_SetRow()
EXPECT_EQ( m.getElement( 0, 4 ), 0 );
EXPECT_EQ( m.getElement( 0, 5 ), 0 );
EXPECT_EQ( m.getElement( 0, 6 ), 0 );
-
+
EXPECT_EQ( m.getElement( 1, 0 ), 22 );
EXPECT_EQ( m.getElement( 1, 1 ), 22 );
EXPECT_EQ( m.getElement( 1, 2 ), 22 );
@@ -652,7 +652,7 @@ void test_SetRow()
EXPECT_EQ( m.getElement( 1, 4 ), 0 );
EXPECT_EQ( m.getElement( 1, 5 ), 0 );
EXPECT_EQ( m.getElement( 1, 6 ), 0 );
-
+
EXPECT_EQ( m.getElement( 2, 0 ), 0 );
EXPECT_EQ( m.getElement( 2, 1 ), 0 );
EXPECT_EQ( m.getElement( 2, 2 ), 0 );
@@ -669,7 +669,7 @@ void test_VectorProduct()
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;
-
+
/*
* Sets up the following 4x4 sparse matrix:
*
@@ -678,10 +678,10 @@ void test_VectorProduct()
* | 0 4 0 0 |
* \ 0 0 5 0 /
*/
-
+
const IndexType m_rows_1 = 4;
const IndexType m_cols_1 = 4;
-
+
Matrix m_1;
m_1.reset();
m_1.setDimensions( m_rows_1, m_cols_1 );
@@ -692,37 +692,37 @@ void test_VectorProduct()
rowLengths_1.setElement( 2, 1 );
rowLengths_1.setElement( 3, 1 );
m_1.setCompressedRowLengths( rowLengths_1 );
-
+
RealType value_1 = 1;
m_1.setElement( 0, 0, value_1++ ); // 0th row
-
+
m_1.setElement( 1, 1, value_1++ ); // 1st row
m_1.setElement( 1, 3, value_1++ );
-
+
m_1.setElement( 2, 1, value_1++ ); // 2nd row
-
+
m_1.setElement( 3, 2, value_1++ ); // 3rd row
-
+
VectorType inVector_1;
inVector_1.setSize( m_cols_1 );
- for( IndexType i = 0; i < inVector_1.getSize(); i++ )
+ for( IndexType i = 0; i < inVector_1.getSize(); i++ )
inVector_1.setElement( i, 2 );
- VectorType outVector_1;
+ VectorType outVector_1;
outVector_1.setSize( m_rows_1 );
for( IndexType j = 0; j < outVector_1.getSize(); j++ )
outVector_1.setElement( j, 0 );
-
-
+
+
m_1.vectorProduct( inVector_1, outVector_1 );
-
-
+
+
EXPECT_EQ( outVector_1.getElement( 0 ), 2 );
EXPECT_EQ( outVector_1.getElement( 1 ), 10 );
EXPECT_EQ( outVector_1.getElement( 2 ), 8 );
EXPECT_EQ( outVector_1.getElement( 3 ), 10 );
-
-
+
+
/*
* Sets up the following 4x4 sparse matrix:
*
@@ -731,10 +731,10 @@ void test_VectorProduct()
* | 5 6 7 0 |
* \ 0 8 0 0 /
*/
-
+
const IndexType m_rows_2 = 4;
const IndexType m_cols_2 = 4;
-
+
Matrix m_2;
m_2.reset();
m_2.setDimensions( m_rows_2, m_cols_2 );
@@ -744,39 +744,39 @@ void test_VectorProduct()
rowLengths_2.setElement( 1, 1 );
rowLengths_2.setElement( 3, 1 );
m_2.setCompressedRowLengths( rowLengths_2 );
-
+
RealType value_2 = 1;
for( IndexType i = 0; i < 3; i++ ) // 0th row
m_2.setElement( 0, i, value_2++ );
-
+
m_2.setElement( 1, 3, value_2++ ); // 1st row
-
+
for( IndexType i = 0; i < 3; i++ ) // 2nd row
m_2.setElement( 2, i, value_2++ );
-
+
for( IndexType i = 1; i < 2; i++ ) // 3rd row
m_2.setElement( 3, i, value_2++ );
-
+
VectorType inVector_2;
inVector_2.setSize( m_cols_2 );
- for( IndexType i = 0; i < inVector_2.getSize(); i++ )
+ for( IndexType i = 0; i < inVector_2.getSize(); i++ )
inVector_2.setElement( i, 2 );
- VectorType outVector_2;
+ VectorType outVector_2;
outVector_2.setSize( m_rows_2 );
for( IndexType j = 0; j < outVector_2.getSize(); j++ )
outVector_2.setElement( j, 0 );
-
-
+
+
m_2.vectorProduct( inVector_2, outVector_2 );
-
-
+
+
EXPECT_EQ( outVector_2.getElement( 0 ), 12 );
EXPECT_EQ( outVector_2.getElement( 1 ), 8 );
EXPECT_EQ( outVector_2.getElement( 2 ), 36 );
EXPECT_EQ( outVector_2.getElement( 3 ), 16 );
-
-
+
+
/*
* Sets up the following 4x4 sparse matrix:
*
@@ -785,10 +785,10 @@ void test_VectorProduct()
* | 7 8 9 0 |
* \ 0 10 11 12 /
*/
-
+
const IndexType m_rows_3 = 4;
const IndexType m_cols_3 = 4;
-
+
Matrix m_3;
m_3.reset();
m_3.setDimensions( m_rows_3, m_cols_3 );
@@ -796,40 +796,40 @@ void test_VectorProduct()
rowLengths_3.setSize( m_rows_3 );
rowLengths_3.setValue( 3 );
m_3.setCompressedRowLengths( rowLengths_3 );
-
+
RealType value_3 = 1;
for( IndexType i = 0; i < 3; i++ ) // 0th row
m_3.setElement( 0, i, value_3++ );
-
+
for( IndexType i = 1; i < 4; i++ )
m_3.setElement( 1, i, value_3++ ); // 1st row
-
+
for( IndexType i = 0; i < 3; i++ ) // 2nd row
m_3.setElement( 2, i, value_3++ );
-
+
for( IndexType i = 1; i < 4; i++ ) // 3rd row
m_3.setElement( 3, i, value_3++ );
-
+
VectorType inVector_3;
inVector_3.setSize( m_cols_3 );
- for( IndexType i = 0; i < inVector_3.getSize(); i++ )
+ for( IndexType i = 0; i < inVector_3.getSize(); i++ )
inVector_3.setElement( i, 2 );
- VectorType outVector_3;
+ VectorType outVector_3;
outVector_3.setSize( m_rows_3 );
for( IndexType j = 0; j < outVector_3.getSize(); j++ )
outVector_3.setElement( j, 0 );
-
-
+
+
m_3.vectorProduct( inVector_3, outVector_3 );
-
-
+
+
EXPECT_EQ( outVector_3.getElement( 0 ), 12 );
EXPECT_EQ( outVector_3.getElement( 1 ), 30 );
EXPECT_EQ( outVector_3.getElement( 2 ), 48 );
EXPECT_EQ( outVector_3.getElement( 3 ), 66 );
-
-
+
+
/*
* Sets up the following 8x8 sparse matrix:
*
@@ -842,10 +842,10 @@ void test_VectorProduct()
* | 26 27 28 29 30 0 0 0 |
* \ 31 32 33 34 35 0 0 0 /
*/
-
+
const IndexType m_rows_4 = 8;
const IndexType m_cols_4 = 8;
-
+
Matrix m_4;
m_4.reset();
m_4.setDimensions( m_rows_4, m_cols_4 );
@@ -856,48 +856,48 @@ void test_VectorProduct()
rowLengths_4.setElement( 6, 5 );
rowLengths_4.setElement( 7, 5 );
m_4.setCompressedRowLengths( rowLengths_4 );
-
+
RealType value_4 = 1;
for( IndexType i = 0; i < 3; i++ ) // 0th row
m_4.setElement( 0, i, value_4++ );
-
+
m_4.setElement( 0, 5, value_4++ );
-
+
for( IndexType i = 1; i < 5; i++ ) // 1st row
m_4.setElement( 1, i, value_4++ );
-
+
for( IndexType i = 0; i < 5; i++ ) // 2nd row
m_4.setElement( 2, i, value_4++ );
-
+
for( IndexType i = 1; i < 5; i++ ) // 3rd row
m_4.setElement( 3, i, value_4++ );
-
+
for( IndexType i = 2; i < 6; i++ ) // 4th row
m_4.setElement( 4, i, value_4++ );
-
+
for( IndexType i = 3; i < 7; i++ ) // 5th row
m_4.setElement( 5, i, value_4++ );
-
+
for( IndexType i = 0; i < 5; i++ ) // 6th row
m_4.setElement( 6, i, value_4++ );
-
+
for( IndexType i = 0; i < 5; i++ ) // 7th row
m_4.setElement( 7, i, value_4++ );
-
+
VectorType inVector_4;
inVector_4.setSize( m_cols_4 );
- for( IndexType i = 0; i < inVector_4.getSize(); i++ )
+ for( IndexType i = 0; i < inVector_4.getSize(); i++ )
inVector_4.setElement( i, 2 );
- VectorType outVector_4;
+ VectorType outVector_4;
outVector_4.setSize( m_rows_4 );
for( IndexType j = 0; j < outVector_4.getSize(); j++ )
outVector_4.setElement( j, 0 );
-
-
+
+
m_4.vectorProduct( inVector_4, outVector_4 );
-
-
+
+
EXPECT_EQ( outVector_4.getElement( 0 ), 20 );
EXPECT_EQ( outVector_4.getElement( 1 ), 52 );
EXPECT_EQ( outVector_4.getElement( 2 ), 110 );
@@ -906,8 +906,8 @@ void test_VectorProduct()
EXPECT_EQ( outVector_4.getElement( 5 ), 188 );
EXPECT_EQ( outVector_4.getElement( 6 ), 280 );
EXPECT_EQ( outVector_4.getElement( 7 ), 330 );
-
-
+
+
/*
* Sets up the following 8x8 sparse matrix:
*
@@ -976,7 +976,7 @@ void test_VectorProduct()
for( IndexType i = 0; i < inVector_5.getSize(); i++ )
inVector_5.setElement( i, 2 );
- VectorType outVector_5;
+ VectorType outVector_5;
outVector_5.setSize( m_rows_5 );
for( IndexType j = 0; j < outVector_5.getSize(); j++ )
outVector_5.setElement( j, 0 );
@@ -1077,6 +1077,8 @@ void test_RowsReduction()
};
m.allRowsReduction( fetch, reduce, keep, 0 );
EXPECT_EQ( rowsCapacities, rowLengths );
+ m.getCompressedRowLengths( rowLengths );
+ EXPECT_EQ( rowsCapacities, rowLengths );
////
// Compute max norm
@@ -1102,7 +1104,7 @@ void test_PerformSORIteration()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 4x4 sparse matrix:
*
@@ -1111,10 +1113,10 @@ void test_PerformSORIteration()
* | 0 1 4 1 |
* \ 0 0 1 4 /
*/
-
+
const IndexType m_rows = 4;
const IndexType m_cols = 4;
-
+
Matrix m;
m.reset();
m.setDimensions( m_rows, m_cols );
@@ -1122,54 +1124,54 @@ void test_PerformSORIteration()
rowLengths.setSize( m_rows );
rowLengths.setValue( 3 );
m.setCompressedRowLengths( rowLengths );
-
+
m.setElement( 0, 0, 4.0 ); // 0th row
m.setElement( 0, 1, 1.0);
-
+
m.setElement( 1, 0, 1.0 ); // 1st row
m.setElement( 1, 1, 4.0 );
m.setElement( 1, 2, 1.0 );
-
+
m.setElement( 2, 1, 1.0 ); // 2nd row
m.setElement( 2, 2, 4.0 );
m.setElement( 2, 3, 1.0 );
-
+
m.setElement( 3, 2, 1.0 ); // 3rd row
m.setElement( 3, 3, 4.0 );
-
+
RealType bVector [ 4 ] = { 1, 1, 1, 1 };
RealType xVector [ 4 ] = { 1, 1, 1, 1 };
-
+
IndexType row = 0;
RealType omega = 1;
-
-
+
+
m.performSORIteration( bVector, row++, xVector, omega);
-
+
EXPECT_EQ( xVector[ 0 ], 0.0 );
EXPECT_EQ( xVector[ 1 ], 1.0 );
EXPECT_EQ( xVector[ 2 ], 1.0 );
EXPECT_EQ( xVector[ 3 ], 1.0 );
-
-
+
+
m.performSORIteration( bVector, row++, xVector, omega);
-
+
EXPECT_EQ( xVector[ 0 ], 0.0 );
EXPECT_EQ( xVector[ 1 ], 0.0 );
EXPECT_EQ( xVector[ 2 ], 1.0 );
EXPECT_EQ( xVector[ 3 ], 1.0 );
-
-
+
+
m.performSORIteration( bVector, row++, xVector, omega);
-
+
EXPECT_EQ( xVector[ 0 ], 0.0 );
EXPECT_EQ( xVector[ 1 ], 0.0 );
EXPECT_EQ( xVector[ 2 ], 0.0 );
EXPECT_EQ( xVector[ 3 ], 1.0 );
-
-
+
+
m.performSORIteration( bVector, row++, xVector, omega);
-
+
EXPECT_EQ( xVector[ 0 ], 0.0 );
EXPECT_EQ( xVector[ 1 ], 0.0 );
EXPECT_EQ( xVector[ 2 ], 0.0 );
@@ -1183,7 +1185,7 @@ void test_OperatorEquals()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
if( std::is_same< DeviceType, TNL::Devices::Cuda >::value )
return;
else
@@ -1229,33 +1231,33 @@ void test_OperatorEquals()
m_host.setElement( 0, 4, value++ ); // 0th row
m_host.setElement( 0, 5, value++ );
-
+
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++ );
-
+
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++ );
-
+
for( IndexType i = 0; i < 7; i++ ) // 1s at the end or rows: 5, 6
m_host.setElement( i, 7, 1);
-
+
EXPECT_EQ( m_host.getElement( 0, 0 ), 1 );
EXPECT_EQ( m_host.getElement( 0, 1 ), 2 );
EXPECT_EQ( m_host.getElement( 0, 2 ), 3 );
@@ -1264,7 +1266,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 0, 5 ), 5 );
EXPECT_EQ( m_host.getElement( 0, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 0, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 1, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 1 ), 6 );
EXPECT_EQ( m_host.getElement( 1, 2 ), 0 );
@@ -1273,7 +1275,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 1, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 2, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 1 ), 8 );
EXPECT_EQ( m_host.getElement( 2, 2 ), 9 );
@@ -1282,7 +1284,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 2, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 3, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 1 ), 11 );
EXPECT_EQ( m_host.getElement( 3, 2 ), 12 );
@@ -1291,7 +1293,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 3, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 4, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 1 ), 15 );
EXPECT_EQ( m_host.getElement( 4, 2 ), 0 );
@@ -1300,7 +1302,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 4, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 5, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 5, 1 ), 16 );
EXPECT_EQ( m_host.getElement( 5, 2 ), 17 );
@@ -1309,7 +1311,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 5, 5 ), 20 );
EXPECT_EQ( m_host.getElement( 5, 6 ), 21 );
EXPECT_EQ( m_host.getElement( 5, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 6, 0 ), 22 );
EXPECT_EQ( m_host.getElement( 6, 1 ), 23 );
EXPECT_EQ( m_host.getElement( 6, 2 ), 24 );
@@ -1318,7 +1320,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 6, 5 ), 27 );
EXPECT_EQ( m_host.getElement( 6, 6 ), 28 );
EXPECT_EQ( m_host.getElement( 6, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 7, 0 ), 29 );
EXPECT_EQ( m_host.getElement( 7, 1 ), 30 );
EXPECT_EQ( m_host.getElement( 7, 2 ), 31 );
@@ -1348,7 +1350,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 0, 5 ), 5 );
EXPECT_EQ( m_host.getElement( 0, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 0, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 1, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 1 ), 6 );
EXPECT_EQ( m_host.getElement( 1, 2 ), 0 );
@@ -1357,7 +1359,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 1, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 1, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 2, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 1 ), 8 );
EXPECT_EQ( m_host.getElement( 2, 2 ), 9 );
@@ -1366,7 +1368,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 2, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 2, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 3, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 1 ), 11 );
EXPECT_EQ( m_host.getElement( 3, 2 ), 12 );
@@ -1375,7 +1377,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 3, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 3, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 4, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 1 ), 15 );
EXPECT_EQ( m_host.getElement( 4, 2 ), 0 );
@@ -1384,7 +1386,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 4, 5 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 6 ), 0 );
EXPECT_EQ( m_host.getElement( 4, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 5, 0 ), 0 );
EXPECT_EQ( m_host.getElement( 5, 1 ), 16 );
EXPECT_EQ( m_host.getElement( 5, 2 ), 17 );
@@ -1393,7 +1395,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 5, 5 ), 20 );
EXPECT_EQ( m_host.getElement( 5, 6 ), 21 );
EXPECT_EQ( m_host.getElement( 5, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 6, 0 ), 22 );
EXPECT_EQ( m_host.getElement( 6, 1 ), 23 );
EXPECT_EQ( m_host.getElement( 6, 2 ), 24 );
@@ -1402,7 +1404,7 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 6, 5 ), 27 );
EXPECT_EQ( m_host.getElement( 6, 6 ), 28 );
EXPECT_EQ( m_host.getElement( 6, 7 ), 1 );
-
+
EXPECT_EQ( m_host.getElement( 7, 0 ), 29 );
EXPECT_EQ( m_host.getElement( 7, 1 ), 30 );
EXPECT_EQ( m_host.getElement( 7, 2 ), 31 );
@@ -1411,22 +1413,22 @@ void test_OperatorEquals()
EXPECT_EQ( m_host.getElement( 7, 5 ), 34 );
EXPECT_EQ( m_host.getElement( 7, 6 ), 35 );
EXPECT_EQ( m_host.getElement( 7, 7 ), 36 );
-
+
// Try vectorProduct with copied cuda matrix to see if it works correctly.
using VectorType = TNL::Containers::Vector< RealType, TNL::Devices::Cuda, IndexType >;
-
+
VectorType inVector;
inVector.setSize( m_cols );
- for( IndexType i = 0; i < inVector.getSize(); i++ )
+ for( IndexType i = 0; i < inVector.getSize(); i++ )
inVector.setElement( i, 2 );
- VectorType outVector;
+ VectorType outVector;
outVector.setSize( m_rows );
for( IndexType j = 0; j < outVector.getSize(); j++ )
outVector.setElement( j, 0 );
-
+
m_cuda.vectorProduct( inVector, outVector );
-
+
EXPECT_EQ( outVector.getElement( 0 ), 32 );
EXPECT_EQ( outVector.getElement( 1 ), 28 );
EXPECT_EQ( outVector.getElement( 2 ), 56 );
@@ -1444,7 +1446,7 @@ void test_SaveAndLoad( const char* filename )
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 4x4 sparse matrix:
*
@@ -1453,10 +1455,10 @@ void test_SaveAndLoad( const char* filename )
* | 6 7 8 0 |
* \ 0 9 10 11 /
*/
-
+
const IndexType m_rows = 4;
const IndexType m_cols = 4;
-
+
Matrix savedMatrix;
savedMatrix.reset();
savedMatrix.setDimensions( m_rows, m_cols );
@@ -1464,22 +1466,22 @@ void test_SaveAndLoad( const char* filename )
rowLengths.setSize( m_rows );
rowLengths.setValue( 3 );
savedMatrix.setCompressedRowLengths( rowLengths );
-
+
RealType value = 1;
for( IndexType i = 0; i < m_cols - 1; i++ ) // 0th row
savedMatrix.setElement( 0, i, value++ );
-
+
savedMatrix.setElement( 1, 1, value++ );
savedMatrix.setElement( 1, 3, value++ ); // 1st row
-
+
for( IndexType i = 0; i < m_cols - 1; i++ ) // 2nd row
savedMatrix.setElement( 2, i, value++ );
-
+
for( IndexType i = 1; i < m_cols; i++ ) // 3rd row
savedMatrix.setElement( 3, i, value++ );
-
+
ASSERT_NO_THROW( savedMatrix.save( filename ) );
-
+
Matrix loadedMatrix;
loadedMatrix.reset();
loadedMatrix.setDimensions( m_rows, m_cols );
@@ -1487,51 +1489,51 @@ void test_SaveAndLoad( const char* filename )
rowLengths2.setSize( m_rows );
rowLengths2.setValue( 3 );
loadedMatrix.setCompressedRowLengths( rowLengths2 );
-
-
+
+
ASSERT_NO_THROW( loadedMatrix.load( filename ) );
-
-
+
+
EXPECT_EQ( savedMatrix.getElement( 0, 0 ), loadedMatrix.getElement( 0, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 1 ), loadedMatrix.getElement( 0, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 2 ), loadedMatrix.getElement( 0, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 3 ), loadedMatrix.getElement( 0, 3 ) );
-
+
EXPECT_EQ( savedMatrix.getElement( 1, 0 ), loadedMatrix.getElement( 1, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 1 ), loadedMatrix.getElement( 1, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 2 ), loadedMatrix.getElement( 1, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 3 ), loadedMatrix.getElement( 1, 3 ) );
-
+
EXPECT_EQ( savedMatrix.getElement( 2, 0 ), loadedMatrix.getElement( 2, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 1 ), loadedMatrix.getElement( 2, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 2 ), loadedMatrix.getElement( 2, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 3 ), loadedMatrix.getElement( 2, 3 ) );
-
+
EXPECT_EQ( savedMatrix.getElement( 3, 0 ), loadedMatrix.getElement( 3, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 1 ), loadedMatrix.getElement( 3, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 2 ), loadedMatrix.getElement( 3, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 3 ), loadedMatrix.getElement( 3, 3 ) );
-
+
EXPECT_EQ( savedMatrix.getElement( 0, 0 ), 1 );
EXPECT_EQ( savedMatrix.getElement( 0, 1 ), 2 );
EXPECT_EQ( savedMatrix.getElement( 0, 2 ), 3 );
EXPECT_EQ( savedMatrix.getElement( 0, 3 ), 0 );
-
+
EXPECT_EQ( savedMatrix.getElement( 1, 0 ), 0 );
EXPECT_EQ( savedMatrix.getElement( 1, 1 ), 4 );
EXPECT_EQ( savedMatrix.getElement( 1, 2 ), 0 );
EXPECT_EQ( savedMatrix.getElement( 1, 3 ), 5 );
-
+
EXPECT_EQ( savedMatrix.getElement( 2, 0 ), 6 );
EXPECT_EQ( savedMatrix.getElement( 2, 1 ), 7 );
EXPECT_EQ( savedMatrix.getElement( 2, 2 ), 8 );
EXPECT_EQ( savedMatrix.getElement( 2, 3 ), 0 );
-
+
EXPECT_EQ( savedMatrix.getElement( 3, 0 ), 0 );
EXPECT_EQ( savedMatrix.getElement( 3, 1 ), 9 );
EXPECT_EQ( savedMatrix.getElement( 3, 2 ), 10 );
EXPECT_EQ( savedMatrix.getElement( 3, 3 ), 11 );
-
+
EXPECT_EQ( std::remove( filename ), 0 );
}
@@ -1541,7 +1543,7 @@ void test_Print()
using RealType = typename Matrix::RealType;
using DeviceType = typename Matrix::DeviceType;
using IndexType = typename Matrix::IndexType;
-
+
/*
* Sets up the following 5x4 sparse matrix:
*
@@ -1551,10 +1553,10 @@ void test_Print()
* | 0 8 9 10 |
* \ 0 0 11 12 /
*/
-
+
const IndexType m_rows = 5;
const IndexType m_cols = 4;
-
+
Matrix m;
m.reset();
m.setDimensions( m_rows, m_cols );
@@ -1562,40 +1564,40 @@ void test_Print()
rowLengths.setSize( m_rows );
rowLengths.setValue( 3 );
m.setCompressedRowLengths( rowLengths );
-
+
RealType value = 1;
for( IndexType i = 0; i < m_cols - 1; i++ ) // 0th row
m.setElement( 0, i, value++ );
-
+
m.setElement( 1, 3, value++ ); // 1st row
-
+
for( IndexType i = 0; i < m_cols - 1; i++ ) // 2nd row
m.setElement( 2, i, value++ );
-
+
for( IndexType i = 1; i < m_cols; i++ ) // 3rd row
m.setElement( 3, i, value++ );
-
+
for( IndexType i = 2; i < m_cols; i++ ) // 4th row
m.setElement( 4, i, value++ );
-
+
#include <sstream>
std::stringstream printed;
std::stringstream couted;
-
+
//change the underlying buffer and save the old buffer
- auto old_buf = std::cout.rdbuf(printed.rdbuf());
+ auto old_buf = std::cout.rdbuf(printed.rdbuf());
m.print( std::cout ); //all the std::cout goes to ss
std::cout.rdbuf(old_buf); //reset
-
+
couted << "Row: 0 -> Col:0->1 Col:1->2 Col:2->3\t\n"
"Row: 1 -> Col:3->4\t\n"
"Row: 2 -> Col:0->5 Col:1->6 Col:2->7\t\n"
"Row: 3 -> Col:1->8 Col:2->9 Col:3->10\t\n"
"Row: 4 -> Col:2->11 Col:3->12\t\n";
-
-
+
+
EXPECT_EQ( printed.str(), couted.str() );
}
--
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