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-rw-r--r--eigen/test/sparse_product.cpp203
1 files changed, 166 insertions, 37 deletions
diff --git a/eigen/test/sparse_product.cpp b/eigen/test/sparse_product.cpp
index a2ea9d5..c1edd26 100644
--- a/eigen/test/sparse_product.cpp
+++ b/eigen/test/sparse_product.cpp
@@ -7,37 +7,29 @@
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-#include "sparse.h"
+static long int nb_temporaries;
-template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
+inline void on_temporary_creation() {
+ // here's a great place to set a breakpoint when debugging failures in this test!
+ nb_temporaries++;
+}
-template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
- static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
- typedef typename SparseMatrixType::Index Index;
- Index c = internal::random<Index>(0,m2.cols()-1);
- Index c1 = internal::random<Index>(0,m2.cols()-1);
- VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
- VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
- }
-};
-
-template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
- static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
- typedef typename SparseMatrixType::Index Index;
- Index r = internal::random<Index>(0,m2.rows()-1);
- Index c1 = internal::random<Index>(0,m2.cols()-1);
- VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
- VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
+#define EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN { on_temporary_creation(); }
+
+#include "sparse.h"
+
+#define VERIFY_EVALUATION_COUNT(XPR,N) {\
+ nb_temporaries = 0; \
+ CALL_SUBTEST( XPR ); \
+ if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
+ VERIFY( (#XPR) && nb_temporaries==N ); \
}
-};
-// (m2,m4,refMat2,refMat4,dv1);
-// VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
-// VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
+
template<typename SparseMatrixType> void sparse_product()
{
- typedef typename SparseMatrixType::Index Index;
+ typedef typename SparseMatrixType::StorageIndex StorageIndex;
Index n = 100;
const Index rows = internal::random<Index>(1,n);
const Index cols = internal::random<Index>(1,n);
@@ -45,12 +37,12 @@ template<typename SparseMatrixType> void sparse_product()
typedef typename SparseMatrixType::Scalar Scalar;
enum { Flags = SparseMatrixType::Flags };
- double density = (std::max)(8./(rows*cols), 0.1);
+ double density = (std::max)(8./(rows*cols), 0.2);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
- typedef SparseVector<Scalar,0,Index> ColSpVector;
- typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
+ typedef SparseVector<Scalar,0,StorageIndex> ColSpVector;
+ typedef SparseVector<Scalar,RowMajor,StorageIndex> RowSpVector;
Scalar s1 = internal::random<Scalar>();
Scalar s2 = internal::random<Scalar>();
@@ -93,33 +85,124 @@ template<typename SparseMatrixType> void sparse_product()
VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
+ VERIFY_IS_APPROX(m4 = (m2+m2)*m3, refMat4 = (refMat2+refMat2)*refMat3);
+ VERIFY_IS_APPROX(m4 = m2*m3.leftCols(cols/2), refMat4 = refMat2*refMat3.leftCols(cols/2));
+ VERIFY_IS_APPROX(m4 = m2*(m3+m3).leftCols(cols/2), refMat4 = refMat2*(refMat3+refMat3).leftCols(cols/2));
VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
+ // make sure the right product implementation is called:
+ if((!SparseMatrixType::IsRowMajor) && m2.rows()<=m3.cols())
+ {
+ VERIFY_EVALUATION_COUNT(m4 = m2*m3, 3); // 1 temp for the result + 2 for transposing and get a sorted result.
+ VERIFY_EVALUATION_COUNT(m4 = (m2*m3).pruned(0), 1);
+ VERIFY_EVALUATION_COUNT(m4 = (m2*m3).eval().pruned(0), 4);
+ }
+
+ // and that pruning is effective:
+ {
+ DenseMatrix Ad(2,2);
+ Ad << -1, 1, 1, 1;
+ SparseMatrixType As(Ad.sparseView()), B(2,2);
+ VERIFY_IS_EQUAL( (As*As.transpose()).eval().nonZeros(), 4);
+ VERIFY_IS_EQUAL( (Ad*Ad.transpose()).eval().sparseView().eval().nonZeros(), 2);
+ VERIFY_IS_EQUAL( (As*As.transpose()).pruned(1e-6).eval().nonZeros(), 2);
+ }
+
+ // dense ?= sparse * sparse
+ VERIFY_IS_APPROX(dm4 =m2*m3, refMat4 =refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4+=m2*m3, refMat4+=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4-=m2*m3, refMat4-=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3, refMat4 =refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3, refMat4+=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3, refMat4-=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3t.transpose(), refMat4 =refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3t.transpose(), refMat4+=refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3t.transpose(), refMat4-=refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4 =m2*m3t.transpose(), refMat4 =refMat2*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4+=m2*m3t.transpose(), refMat4+=refMat2*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4-=m2*m3t.transpose(), refMat4-=refMat2*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
+
// test aliasing
m4 = m2; refMat4 = refMat2;
VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
- // sparse * dense
+ // sparse * dense matrix
VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4=dm4+m2*refMat3, refMat4=refMat4+refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4+=m2*refMat3, refMat4+=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4-=m2*refMat3, refMat4-=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4.noalias()+=m2*refMat3, refMat4+=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4.noalias()-=m2*refMat3, refMat4-=refMat2*refMat3);
VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
+
+ // sparse * dense vector
+ VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3.col(0), refMat4.col(0)=refMat2*refMat3.col(0));
+ VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3t.transpose().col(0), refMat4.col(0)=refMat2*refMat3t.transpose().col(0));
+ VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3.col(0), refMat4.col(0)=refMat2t.transpose()*refMat3.col(0));
+ VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3t.transpose().col(0), refMat4.col(0)=refMat2t.transpose()*refMat3t.transpose().col(0));
// dense * sparse
VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4=dm4+refMat2*m3, refMat4=refMat4+refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4+=refMat2*m3, refMat4+=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4-=refMat2*m3, refMat4-=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4.noalias()+=refMat2*m3, refMat4+=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4.noalias()-=refMat2*m3, refMat4-=refMat2*refMat3);
VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
// sparse * dense and dense * sparse outer product
- test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
+ {
+ Index c = internal::random<Index>(0,depth-1);
+ Index r = internal::random<Index>(0,rows-1);
+ Index c1 = internal::random<Index>(0,cols-1);
+ Index r1 = internal::random<Index>(0,depth-1);
+ DenseMatrix dm5 = DenseMatrix::Random(depth, cols);
+
+ VERIFY_IS_APPROX( m4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX( m4=m2.middleCols(c,1)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+
+ VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.middleCols(c,1).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+
+ VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose());
+
+ VERIFY_IS_APPROX( m4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX( m4=m2.middleRows(r,1).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+
+ VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r));
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.middleRows(r,1), refMat4=dm5.col(c1)*refMat2.row(r));
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r));
+
+ VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r));
+ VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+ VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r));
+ }
VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
@@ -131,11 +214,11 @@ template<typename SparseMatrixType> void sparse_product()
RowSpVector rv0(depth), rv1;
RowDenseVector drv0(depth), drv1(rv1);
initSparse(2*density,drv0, rv0);
-
- VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
+
+ VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
- VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
+ VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
}
@@ -158,12 +241,16 @@ template<typename SparseMatrixType> void sparse_product()
// also check with a SparseWrapper:
DenseVector v1 = DenseVector::Random(cols);
DenseVector v2 = DenseVector::Random(rows);
+ DenseVector v3 = DenseVector::Random(rows);
VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
+
+ VERIFY_IS_APPROX(v2=m2*v1.asDiagonal()*v1, refM2*v1.asDiagonal()*v1);
+ VERIFY_IS_APPROX(v3=v2.asDiagonal()*m2*v1, v2.asDiagonal()*refM2*v1);
// evaluate to a dense matrix to check the .row() and .col() iterator functions
VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
@@ -172,7 +259,7 @@ template<typename SparseMatrixType> void sparse_product()
VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
}
- // test self adjoint products
+ // test self-adjoint and triangular-view products
{
DenseMatrix b = DenseMatrix::Random(rows, rows);
DenseMatrix x = DenseMatrix::Random(rows, rows);
@@ -180,9 +267,12 @@ template<typename SparseMatrixType> void sparse_product()
DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
DenseMatrix refS = DenseMatrix::Zero(rows, rows);
+ DenseMatrix refA = DenseMatrix::Zero(rows, rows);
SparseMatrixType mUp(rows, rows);
SparseMatrixType mLo(rows, rows);
SparseMatrixType mS(rows, rows);
+ SparseMatrixType mA(rows, rows);
+ initSparse<Scalar>(density, refA, mA);
do {
initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
} while (refUp.isZero());
@@ -195,26 +285,41 @@ template<typename SparseMatrixType> void sparse_product()
for (int k=0; k<mS.outerSize(); ++k)
for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
if (it.index() == k)
- it.valueRef() *= 0.5;
+ it.valueRef() *= Scalar(0.5);
VERIFY_IS_APPROX(refS.adjoint(), refS);
VERIFY_IS_APPROX(mS.adjoint(), mS);
VERIFY_IS_APPROX(mS, refS);
VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
+ // sparse selfadjointView with dense matrices
VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
+
+ VERIFY_IS_APPROX(x.noalias()+=mUp.template selfadjointView<Upper>()*b, refX+=refS*b);
+ VERIFY_IS_APPROX(x.noalias()-=mLo.template selfadjointView<Lower>()*b, refX-=refS*b);
+ VERIFY_IS_APPROX(x.noalias()+=mS.template selfadjointView<Upper|Lower>()*b, refX+=refS*b);
- // sparse selfadjointView * sparse
+ // sparse selfadjointView with sparse matrices
SparseMatrixType mSres(rows,rows);
VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
refX = refLo.template selfadjointView<Lower>()*refS);
- // sparse * sparse selfadjointview
VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
refX = refS * refLo.template selfadjointView<Lower>());
+
+ // sparse triangularView with dense matrices
+ VERIFY_IS_APPROX(x=mA.template triangularView<Upper>()*b, refX=refA.template triangularView<Upper>()*b);
+ VERIFY_IS_APPROX(x=mA.template triangularView<Lower>()*b, refX=refA.template triangularView<Lower>()*b);
+ VERIFY_IS_APPROX(x=b*mA.template triangularView<Upper>(), refX=b*refA.template triangularView<Upper>());
+ VERIFY_IS_APPROX(x=b*mA.template triangularView<Lower>(), refX=b*refA.template triangularView<Lower>());
+
+ // sparse triangularView with sparse matrices
+ VERIFY_IS_APPROX(mSres = mA.template triangularView<Lower>()*mS, refX = refA.template triangularView<Lower>()*refS);
+ VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Lower>(), refX = refS * refA.template triangularView<Lower>());
+ VERIFY_IS_APPROX(mSres = mA.template triangularView<Upper>()*mS, refX = refA.template triangularView<Upper>()*refS);
+ VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Upper>(), refX = refS * refA.template triangularView<Upper>());
}
-
}
// New test for Bug in SparseTimeDenseProduct
@@ -239,11 +344,35 @@ template<typename SparseMatrixType, typename DenseMatrixType> void sparse_produc
VERIFY_IS_APPROX( m4(0,0), 0.0 );
}
+template<typename Scalar>
+void bug_942()
+{
+ typedef Matrix<Scalar, Dynamic, 1> Vector;
+ typedef SparseMatrix<Scalar, ColMajor> ColSpMat;
+ typedef SparseMatrix<Scalar, RowMajor> RowSpMat;
+ ColSpMat cmA(1,1);
+ cmA.insert(0,0) = 1;
+
+ RowSpMat rmA(1,1);
+ rmA.insert(0,0) = 1;
+
+ Vector d(1);
+ d[0] = 2;
+
+ double res = 2;
+
+ VERIFY_IS_APPROX( ( cmA*d.asDiagonal() ).eval().coeff(0,0), res );
+ VERIFY_IS_APPROX( ( d.asDiagonal()*rmA ).eval().coeff(0,0), res );
+ VERIFY_IS_APPROX( ( rmA*d.asDiagonal() ).eval().coeff(0,0), res );
+ VERIFY_IS_APPROX( ( d.asDiagonal()*cmA ).eval().coeff(0,0), res );
+}
+
void test_sparse_product()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
+ CALL_SUBTEST_1( (bug_942<double>()) );
CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
generated by cgit v1.2.3 (git 2.39.1) at 2025-02-23 11:35:26 +0000