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Run sparse_basic unit tests also for rectangular matrices.

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TriangularView with UnitDiag does not work properly yet (bug #901)
This commit is contained in:
Christoph Hertzberg 2014-10-31 17:12:13 +01:00
parent 4ec2f07a5b
commit 0833b82efd
2 changed files with 93 additions and 76 deletions
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4
Eigen/src/SparseCore/SparseTriangularView.h
View File

@ -213,7 +213,7 @@ public:
{
if((!SkipFirst) && Base::operator bool())
Base::operator++();
m_returnOne = true;
m_returnOne = true; // FIXME check innerSize()>outer();
}
}
@ -228,7 +228,7 @@ public:
{
if((!SkipFirst) && Base::operator bool())
Base::operator++();
m_returnOne = true;
m_returnOne = true; // FIXME check innerSize()>outer();
}
}
return *this;

165
test/sparse_basic.cpp
View File

@ -18,6 +18,9 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
const Index rows = ref.rows();
const Index cols = ref.cols();
const Index inner = ref.innerSize();
const Index outer = ref.outerSize();
typedef typename SparseMatrixType::Scalar Scalar;
enum { Flags = SparseMatrixType::Flags };
@ -36,23 +39,22 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
std::vector<Vector2> nonzeroCoords;
initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
return;
// test coeff and coeffRef
for (int i=0; i<(int)zeroCoords.size(); ++i)
for (std::size_t i=0; i<zeroCoords.size(); ++i)
{
VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[i].x(),zeroCoords[i].y()) = 5 );
}
VERIFY_IS_APPROX(m, refMat);
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
if(!nonzeroCoords.empty()) {
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
}
VERIFY_IS_APPROX(m, refMat);
/*
// test InnerIterators and Block expressions
for (int t=0; t<10; ++t)
{
@ -61,23 +63,25 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
int w = internal::random<int>(1,cols-j-1);
int h = internal::random<int>(1,rows-i-1);
// VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
for(int c=0; c<w; c++)
{
VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
for(int r=0; r<h; r++)
{
// VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
// FIXME col().coeff() not implemented yet
// VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
}
}
// for(int r=0; r<h; r++)
// {
// VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
// for(int c=0; c<w; c++)
// {
// VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
// }
// }
for(int r=0; r<h; r++)
{
VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
for(int c=0; c<w; c++)
{
// FIXME row().coeff() not implemented yet
// VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
}
}
}
for(int c=0; c<cols; c++)
@ -91,8 +95,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
}
*/
// test assertion
VERIFY_RAISES_ASSERT( m.coeffRef(-1,1) = 0 );
VERIFY_RAISES_ASSERT( m.coeffRef(0,m.cols()) = 0 );
@ -165,11 +169,11 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test innerVector()
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
Index j0 = internal::random<Index>(0,rows-1);
Index j1 = internal::random<Index>(0,rows-1);
Index j0 = internal::random<Index>(0,outer-1);
Index j1 = internal::random<Index>(0,outer-1);
if(SparseMatrixType::IsRowMajor)
VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0));
else
@ -180,25 +184,25 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
else
VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
SparseMatrixType m3(rows,rows);
m3.reserve(VectorXi::Constant(rows,int(rows/2)));
for(Index j=0; j<rows; ++j)
for(Index k=0; k<j; ++k)
SparseMatrixType m3(rows,cols);
m3.reserve(VectorXi::Constant(outer,int(inner/2)));
for(Index j=0; j<outer; ++j)
for(Index k=0; k<(std::min)(j,inner); ++k)
m3.insertByOuterInner(j,k) = k+1;
for(Index j=0; j<rows; ++j)
for(Index j=0; j<(std::min)(outer, inner); ++j)
{
VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
if(j>0)
VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
}
m3.makeCompressed();
for(Index j=0; j<rows; ++j)
for(Index j=0; j<(std::min)(outer, inner); ++j)
{
VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
if(j>0)
VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
}
VERIFY(m3.innerVector(j0).nonZeros() == m3.transpose().innerVector(j0).nonZeros());
// m2.innerVector(j0) = 2*m2.innerVector(j1);
@ -208,14 +212,13 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test innerVectors()
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
Index j0 = internal::random<Index>(0,rows-2);
Index j1 = internal::random<Index>(0,rows-2);
Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
Index j0 = internal::random<Index>(0,outer-2);
Index j1 = internal::random<Index>(0,outer-2);
Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
if(SparseMatrixType::IsRowMajor)
VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
else
@ -242,14 +245,14 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test basic computations
{
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m1(rows, rows);
SparseMatrixType m2(rows, rows);
SparseMatrixType m3(rows, rows);
SparseMatrixType m4(rows, rows);
DenseMatrix refM1 = DenseMatrix::Zero(rows, cols);
DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
DenseMatrix refM4 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m1(rows, cols);
SparseMatrixType m2(rows, cols);
SparseMatrixType m3(rows, cols);
SparseMatrixType m4(rows, cols);
initSparse<Scalar>(density, refM1, m1);
initSparse<Scalar>(density, refM2, m2);
initSparse<Scalar>(density, refM3, m3);
@ -270,7 +273,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
if(SparseMatrixType::IsRowMajor)
VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.row(0).dot(refM2.row(0)));
else
VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0)));
VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.col(0)), refM1.col(0).dot(refM2.col(0)));
DenseVector rv = DenseVector::Random(m1.cols());
DenseVector cv = DenseVector::Random(m1.rows());
@ -297,8 +300,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test transpose
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
@ -314,12 +317,12 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test generic blocks
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
Index j0 = internal::random<Index>(0,rows-2);
Index j1 = internal::random<Index>(0,rows-2);
Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
Index j0 = internal::random<Index>(0,outer-2);
Index j1 = internal::random<Index>(0,outer-2);
Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
if(SparseMatrixType::IsRowMajor)
VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols));
else
@ -346,8 +349,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test prune
{
SparseMatrixType m2(rows, rows);
DenseMatrix refM2(rows, rows);
SparseMatrixType m2(rows, cols);
DenseMatrix refM2(rows, cols);
refM2.setZero();
int countFalseNonZero = 0;
int countTrueNonZero = 0;
@ -408,8 +411,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test triangularView
{
DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
SparseMatrixType m2(rows, rows), m3(rows, rows);
DenseMatrix refMat2(rows, cols), refMat3(rows, cols);
SparseMatrixType m2(rows, cols), m3(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
refMat3 = refMat2.template triangularView<Lower>();
m3 = m2.template triangularView<Lower>();
@ -419,13 +422,16 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
m3 = m2.template triangularView<Upper>();
VERIFY_IS_APPROX(m3, refMat3);
refMat3 = refMat2.template triangularView<UnitUpper>();
m3 = m2.template triangularView<UnitUpper>();
VERIFY_IS_APPROX(m3, refMat3);
if(inner>=outer) // FIXME this should be implemented for outer>inner as well
{
refMat3 = refMat2.template triangularView<UnitUpper>();
m3 = m2.template triangularView<UnitUpper>();
VERIFY_IS_APPROX(m3, refMat3);
refMat3 = refMat2.template triangularView<UnitLower>();
m3 = m2.template triangularView<UnitLower>();
VERIFY_IS_APPROX(m3, refMat3);
refMat3 = refMat2.template triangularView<UnitLower>();
m3 = m2.template triangularView<UnitLower>();
VERIFY_IS_APPROX(m3, refMat3);
}
refMat3 = refMat2.template triangularView<StrictlyUpper>();
m3 = m2.template triangularView<StrictlyUpper>();
@ -445,6 +451,11 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
refMat3 = refMat2.template selfadjointView<Lower>();
m3 = m2.template selfadjointView<Lower>();
VERIFY_IS_APPROX(m3, refMat3);
// selfadjointView only works for square matrices:
SparseMatrixType m4(rows, rows+1);
VERIFY_RAISES_ASSERT(m4.template selfadjointView<Lower>());
VERIFY_RAISES_ASSERT(m4.template selfadjointView<Upper>());
}
// test sparseView
@ -457,8 +468,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test diagonal
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
}
@ -466,7 +477,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test conservative resize
{
std::vector< std::pair<Index,Index> > inc;
inc.push_back(std::pair<Index,Index>(-3,-2));
if(rows > 3 && cols > 2)
inc.push_back(std::pair<Index,Index>(-3,-2));
inc.push_back(std::pair<Index,Index>(0,0));
inc.push_back(std::pair<Index,Index>(3,2));
inc.push_back(std::pair<Index,Index>(3,0));
@ -507,19 +519,24 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
}
}
void test_sparse_basic()
{
for(int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1,50);
EIGEN_UNUSED_VARIABLE(s);
int r = Eigen::internal::random<int>(1,100), c = Eigen::internal::random<int>(1,100);
if(Eigen::internal::random<int>(0,4) == 0) {
r = c; // check square matrices in 25% of tries
}
EIGEN_UNUSED_VARIABLE(r+c);
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(1, 1)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(8, 8)) ));
CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(s, s)) ));
CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(s, s)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(s, s)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(s, s)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(s, s)) ));
CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(r, c)) ));
CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(r, c)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(r, c)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(r, c)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(r, c)) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(s), short(s))) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(s), short(s))) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) ));
}
}