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a couple of fixes after thye merge

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This commit is contained in:
Gael Guennebaud 2009-12-23 09:07:01 +01:00
parent eaaba30cac
commit fcc3be5dce
7 changed files with 24 additions and 9 deletions
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7
Eigen/src/Core/ProductBase.h
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@ -29,8 +29,9 @@
*
*/
template<typename Derived, typename _Lhs, typename _Rhs>
struct ei_traits<ProductBase<Derived,_Lhs,_Rhs> > : ei_traits<typename ei_cleantype<_Lhs>::type>
struct ei_traits<ProductBase<Derived,_Lhs,_Rhs> > //: ei_traits<typename ei_cleantype<_Lhs>::type>
{
typedef DenseStorageMatrix DenseStorageType;
typedef typename ei_cleantype<_Lhs>::type Lhs;
typedef typename ei_cleantype<_Rhs>::type Rhs;
typedef typename ei_scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
@ -172,7 +173,9 @@ struct ei_traits<ScaledProduct<NestedProduct> >
: ei_traits<ProductBase<ScaledProduct<NestedProduct>,
typename NestedProduct::_LhsNested,
typename NestedProduct::_RhsNested> >
{};
{
typedef typename ei_traits<NestedProduct>::StorageType StorageType;
};
template<typename NestedProduct>
class ScaledProduct

4
Eigen/src/Core/TriangularMatrix.h
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@ -465,7 +465,7 @@ TriangularView<MatrixType, Mode>::operator=(const MatrixBase<OtherDerived>& othe
{
if(OtherDerived::Flags & EvalBeforeAssigningBit)
{
typename OtherDerived::PlainMatrixType other_evaluated(other.rows(), other.cols());
typename ei_plain_matrix_type<OtherDerived>::type other_evaluated(other.rows(), other.cols());
other_evaluated.template triangularView<Mode>().lazyAssign(other.derived());
lazyAssign(other_evaluated);
}
@ -536,7 +536,7 @@ void TriangularBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
{
if(ei_traits<Derived>::Flags & EvalBeforeAssigningBit)
{
typename Derived::PlainMatrixType other_evaluated(rows(), cols());
typename ei_plain_matrix_type<Derived>::type other_evaluated(rows(), cols());
evalToLazy(other_evaluated);
other.derived().swap(other_evaluated);
}

2
Eigen/src/Geometry/Homogeneous.h
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@ -194,7 +194,7 @@ VectorwiseOp<ExpressionType,Direction>::hnormalized() const
return HNormalized_Block(_expression(),0,0,
Direction==Vertical ? _expression().rows()-1 : _expression().rows(),
Direction==Horizontal ? _expression().cols()-1 : _expression().cols()).cwiseQuotient(
Replicate<NestByValue<HNormalized_Factors>,
Replicate<HNormalized_Factors,
Direction==Vertical ? HNormalized_SizeMinusOne : 1,
Direction==Horizontal ? HNormalized_SizeMinusOne : 1>
(HNormalized_Factors(_expression(),

3
Eigen/src/LU/Inverse.h
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@ -203,7 +203,7 @@ struct ei_compute_inverse_size4
result.coeffRef(1,3) = matrix.minor(3,1).determinant();
result.coeffRef(2,3) = -matrix.minor(3,2).determinant();
result.coeffRef(3,3) = matrix.minor(3,3).determinant();
result /= (matrix.col(0).cwise()*result.row(0).transpose()).sum();
result /= (matrix.col(0).cwiseProduct(result.row(0).transpose())).sum();
}
};
@ -212,7 +212,6 @@ struct ei_compute_inverse<MatrixType, ResultType, 4>
: ei_compute_inverse_size4<Architecture::Target, typename MatrixType::Scalar,
MatrixType, ResultType>
{
// FIXME empty?
};
template<typename MatrixType, typename ResultType>

4
Eigen/src/Sparse/SparseSelfAdjointView.h
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@ -144,7 +144,9 @@ SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const MatrixBase<DerivedU>& u
template<typename Lhs, typename Rhs, int UpLo>
struct ei_traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
: ei_traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
{};
{
typedef Dense StorageType;
};
template<typename Lhs, typename Rhs, int UpLo>
class SparseSelfAdjointTimeDenseProduct

11
Eigen/src/Sparse/SparseUtil.h
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@ -155,4 +155,15 @@ template<typename T> class ei_eval<T,Sparse>
typedef SparseMatrix<_Scalar, _Flags> type;
};
template<typename T> struct ei_plain_matrix_type<T,Sparse>
{
typedef typename ei_traits<T>::Scalar _Scalar;
enum {
_Flags = ei_traits<T>::Flags
};
public:
typedef SparseMatrix<_Scalar, _Flags> type;
};
#endif // EIGEN_SPARSEUTIL_H

2
test/sparse_product.cpp
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@ -61,7 +61,7 @@ template<typename SparseMatrixType> void sparse_product(const SparseMatrixType&
VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
VERIFY_IS_APPROX(dm4=m2.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2.transpose()*(refMat3+refMat5)*0.5);
// dense * sparse
VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
VERIFY_IS_APPROX(dm4=refMat2*m3.transpose(), refMat4=refMat2*refMat3.transpose());