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-rw-r--r--test/sparse_basic.cpp214
1 files changed, 136 insertions, 78 deletions
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index 4c9b9111e..097959c84 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -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
@@ -180,42 +184,41 @@ 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);
- //refMat2.col(j0) = 2*refMat2.col(j1);
- //VERIFY_IS_APPROX(m2, refMat2);
+// m2.innerVector(j0) = 2*m2.innerVector(j1);
+// refMat2.col(j0) = 2*refMat2.col(j1);
+// VERIFY_IS_APPROX(m2, refMat2);
}
// 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
@@ -239,22 +242,23 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
VERIFY_IS_APPROX(m2, refMat2);
}
-
+
// 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);
initSparse<Scalar>(density, refM4, m4);
+ VERIFY_IS_APPROX(m1*s1, refM1*s1);
VERIFY_IS_APPROX(m1+m2, refM1+refM2);
VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
VERIFY_IS_APPROX(m3.cwiseProduct(m1+m2), refM3.cwiseProduct(refM1+refM2));
@@ -269,7 +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());
@@ -296,25 +300,29 @@ 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());
VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
+
+ // check isApprox handles opposite storage order
+ typename Transpose<SparseMatrixType>::PlainObject m3(m2);
+ VERIFY(m2.isApprox(m3));
}
// 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
@@ -341,8 +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;
@@ -403,8 +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>();
@@ -414,13 +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>();
@@ -440,6 +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
@@ -452,16 +468,23 @@ 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());
+ VERIFY_IS_APPROX(const_cast<const SparseMatrixType&>(m2).diagonal(), refMat2.diagonal().eval());
+
+ initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag);
+ m2.diagonal() += refMat2.diagonal();
+ refMat2.diagonal() += refMat2.diagonal();
+ VERIFY_IS_APPROX(m2, refMat2);
}
// 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));
@@ -502,19 +525,54 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
}
}
+
+template<typename SparseMatrixType>
+void big_sparse_triplet(typename SparseMatrixType::Index rows, typename SparseMatrixType::Index cols, double density) {
+typedef typename SparseMatrixType::Index Index;
+typedef typename SparseMatrixType::Scalar Scalar;
+typedef Triplet<Scalar,Index> TripletType;
+std::vector<TripletType> triplets;
+double nelements = density * rows*cols;
+VERIFY(nelements>=0 && nelements < NumTraits<Index>::highest());
+Index ntriplets = Index(nelements);
+triplets.reserve(ntriplets);
+Scalar sum = Scalar(0);
+for(Index i=0;i<ntriplets;++i)
+{
+ Index r = internal::random<Index>(0,rows-1);
+ Index c = internal::random<Index>(0,cols-1);
+ Scalar v = internal::random<Scalar>();
+ triplets.push_back(TripletType(r,c,v));
+ sum += v;
+}
+SparseMatrixType m(rows,cols);
+m.setFromTriplets(triplets.begin(), triplets.end());
+VERIFY(m.nonZeros() <= ntriplets);
+VERIFY_IS_APPROX(sum, m.sum());
+}
+
+
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))) ));
}
+
+ // Regression test for bug 900: (manually insert higher values here, if you have enough RAM):
+ CALL_SUBTEST_3((big_sparse_triplet<SparseMatrix<float, RowMajor, int> >(10000, 10000, 0.125)));
+ CALL_SUBTEST_4((big_sparse_triplet<SparseMatrix<double, ColMajor, long int> >(10000, 10000, 0.125)));
}
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