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fix sparse vector assignment from a sparse matrix

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This commit is contained in:
Gael Guennebaud 2013-03-06 11:58:22 +01:00
parent 69bd334d2b
commit 98ce4455dd
4 changed files with 52 additions and 2 deletions
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3
Eigen/src/SparseCore/SparseVector.h
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@ -230,7 +230,8 @@ class SparseVector
template<typename OtherDerived> template<typename OtherDerived>
inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other) inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
{ {
if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime)) if ( (bool(OtherDerived::IsVectorAtCompileTime) && int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
|| ((!bool(OtherDerived::IsVectorAtCompileTime)) && ( bool(IsColVector) ? other.cols()>1 : other.rows()>1 )))
return assign(other.transpose()); return assign(other.transpose());
else else
return assign(other); return assign(other);

25
test/sparse.h
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@ -178,5 +178,30 @@ initSparse(double density,
} }
} }
template<typename Scalar> void
initSparse(double density,
Matrix<Scalar,1,Dynamic>& refVec,
SparseVector<Scalar,RowMajor>& sparseVec,
std::vector<int>* zeroCoords = 0,
std::vector<int>* nonzeroCoords = 0)
{
sparseVec.reserve(int(refVec.size()*density));
sparseVec.setZero();
for(int i=0; i<refVec.size(); i++)
{
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
if (v!=Scalar(0))
{
sparseVec.insertBack(i) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(i);
}
else if (zeroCoords)
zeroCoords->push_back(i);
refVec[i] = v;
}
}
#include <unsupported/Eigen/SparseExtra> #include <unsupported/Eigen/SparseExtra>
#endif // EIGEN_TESTSPARSE_H #endif // EIGEN_TESTSPARSE_H

20
test/sparse_product.cpp
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@ -46,6 +46,9 @@ template<typename SparseMatrixType> void sparse_product()
double density = (std::max)(8./(rows*cols), 0.1); double density = (std::max)(8./(rows*cols), 0.1);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector; typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
typedef SparseVector<Scalar,0,Index> ColSpVector;
typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
Scalar s1 = internal::random<Scalar>(); Scalar s1 = internal::random<Scalar>();
Scalar s2 = internal::random<Scalar>(); Scalar s2 = internal::random<Scalar>();
@ -117,8 +120,23 @@ template<typename SparseMatrixType> void sparse_product()
test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4); test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6); VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
// sparse matrix * sparse vector
ColSpVector cv0(cols), cv1;
DenseVector dcv0(cols), dcv1;
initSparse(2*density,dcv0, cv0);
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(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(rv1=m3*cv0, drv1=refMat3*dcv0);
} }
// test matrix - diagonal product // test matrix - diagonal product
{ {
DenseMatrix refM2 = DenseMatrix::Zero(rows, cols); DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);

6
test/sparse_vector.cpp
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@ -84,6 +84,12 @@ template<typename Scalar> void sparse_vector(int rows, int cols)
VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1)); VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval())); VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1)); VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
// sparse matrix to sparse vector
SparseMatrixType mv1;
VERIFY_IS_APPROX((mv1=v1),v1);
VERIFY_IS_APPROX(mv1,(v1=mv1));
VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
} }