aboutsummaryrefslogtreecommitdiffhomepage
path: root/Eigen/src
diff options
context:
space:
mode:
Diffstat (limited to 'Eigen/src')
-rw-r--r--Eigen/src/Cholesky/LDLT.h2
-rw-r--r--Eigen/src/Core/MatrixBase.h9
-rw-r--r--Eigen/src/Core/ReturnByValue.h9
-rw-r--r--Eigen/src/Core/util/ForwardDeclarations.h8
-rw-r--r--Eigen/src/Core/util/Macros.h2
-rw-r--r--Eigen/src/Geometry/Transform.h20
-rw-r--r--Eigen/src/LU/Determinant.h2
-rw-r--r--Eigen/src/LU/FullPivLU.h (renamed from Eigen/src/LU/LU.h)62
-rw-r--r--Eigen/src/LU/Inverse.h47
-rw-r--r--Eigen/src/LU/PartialPivLU.h (renamed from Eigen/src/LU/PartialLU.h)75
-rw-r--r--Eigen/src/QR/ColPivHouseholderQR.h (renamed from Eigen/src/QR/ColPivotingHouseholderQR.h)62
-rw-r--r--Eigen/src/QR/FullPivHouseholderQR.h (renamed from Eigen/src/QR/FullPivotingHouseholderQR.h)64
-rw-r--r--Eigen/src/QR/HouseholderQR.h4
-rw-r--r--Eigen/src/SVD/JacobiSVD.h4
-rw-r--r--Eigen/src/Sparse/SparseLU.h2
15 files changed, 211 insertions, 161 deletions
diff --git a/Eigen/src/Cholesky/LDLT.h b/Eigen/src/Cholesky/LDLT.h
index c8d92f3c0..f95e10935 100644
--- a/Eigen/src/Cholesky/LDLT.h
+++ b/Eigen/src/Cholesky/LDLT.h
@@ -88,7 +88,7 @@ template<typename MatrixType> class LDLT
/** \returns a vector of integers, whose size is the number of rows of the matrix being decomposed,
* representing the P permutation i.e. the permutation of the rows. For its precise meaning,
- * see the examples given in the documentation of class LU.
+ * see the examples given in the documentation of class FullPivLU.
*/
inline const IntColVectorType& permutationP() const
{
diff --git a/Eigen/src/Core/MatrixBase.h b/Eigen/src/Core/MatrixBase.h
index a2b57f8ea..729349b6f 100644
--- a/Eigen/src/Core/MatrixBase.h
+++ b/Eigen/src/Core/MatrixBase.h
@@ -699,8 +699,9 @@ template<typename Derived> class MatrixBase
/////////// LU module ///////////
- const LU<PlainMatrixType> lu() const;
- const PartialLU<PlainMatrixType> partialLu() const;
+ const FullPivLU<PlainMatrixType> fullPivLu() const;
+ const PartialPivLU<PlainMatrixType> partialPivLu() const;
+ const PartialPivLU<PlainMatrixType> lu() const;
const ei_inverse_impl<Derived> inverse() const;
template<typename ResultType>
void computeInverseAndDetWithCheck(
@@ -725,8 +726,8 @@ template<typename Derived> class MatrixBase
/////////// QR module ///////////
const HouseholderQR<PlainMatrixType> householderQr() const;
- const ColPivotingHouseholderQR<PlainMatrixType> colPivotingHouseholderQr() const;
- const FullPivotingHouseholderQR<PlainMatrixType> fullPivotingHouseholderQr() const;
+ const ColPivHouseholderQR<PlainMatrixType> colPivHouseholderQr() const;
+ const FullPivHouseholderQR<PlainMatrixType> fullPivHouseholderQr() const;
EigenvaluesReturnType eigenvalues() const;
RealScalar operatorNorm() const;
diff --git a/Eigen/src/Core/ReturnByValue.h b/Eigen/src/Core/ReturnByValue.h
index 55652db48..87b057f86 100644
--- a/Eigen/src/Core/ReturnByValue.h
+++ b/Eigen/src/Core/ReturnByValue.h
@@ -34,7 +34,14 @@ struct ei_traits<ReturnByValue<Derived> >
: public ei_traits<typename ei_traits<Derived>::ReturnMatrixType>
{
enum {
- Flags = ei_traits<typename ei_traits<Derived>::ReturnMatrixType>::Flags | EvalBeforeNestingBit
+ // FIXME had to remove the DirectAccessBit for usage like
+ // matrix.inverse().block(...)
+ // because the Block ctor with direct access
+ // wants to call coeffRef() to get an address, and that fails (infinite recursion) as ReturnByValue
+ // doesnt implement coeffRef(). The better fix is probably rather to make Block work directly
+ // on the nested type, right?
+ Flags = (ei_traits<typename ei_traits<Derived>::ReturnMatrixType>::Flags
+ | EvalBeforeNestingBit) & ~DirectAccessBit
};
};
diff --git a/Eigen/src/Core/util/ForwardDeclarations.h b/Eigen/src/Core/util/ForwardDeclarations.h
index 01adca96d..86539a64e 100644
--- a/Eigen/src/Core/util/ForwardDeclarations.h
+++ b/Eigen/src/Core/util/ForwardDeclarations.h
@@ -114,12 +114,12 @@ template<typename ExpressionType, int Direction> class VectorwiseOp;
template<typename MatrixType,int RowFactor,int ColFactor> class Replicate;
template<typename MatrixType, int Direction = BothDirections> class Reverse;
-template<typename MatrixType> class LU;
-template<typename MatrixType> class PartialLU;
+template<typename MatrixType> class FullPivLU;
+template<typename MatrixType> class PartialPivLU;
template<typename MatrixType> struct ei_inverse_impl;
template<typename MatrixType> class HouseholderQR;
-template<typename MatrixType> class ColPivotingHouseholderQR;
-template<typename MatrixType> class FullPivotingHouseholderQR;
+template<typename MatrixType> class ColPivHouseholderQR;
+template<typename MatrixType> class FullPivHouseholderQR;
template<typename MatrixType> class SVD;
template<typename MatrixType, unsigned int Options = 0> class JacobiSVD;
template<typename MatrixType, int UpLo = LowerTriangular> class LLT;
diff --git a/Eigen/src/Core/util/Macros.h b/Eigen/src/Core/util/Macros.h
index 706b30174..66b9d52f4 100644
--- a/Eigen/src/Core/util/Macros.h
+++ b/Eigen/src/Core/util/Macros.h
@@ -30,7 +30,7 @@
#define EIGEN_WORLD_VERSION 2
#define EIGEN_MAJOR_VERSION 90
-#define EIGEN_MINOR_VERSION 0
+#define EIGEN_MINOR_VERSION 1
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
diff --git a/Eigen/src/Geometry/Transform.h b/Eigen/src/Geometry/Transform.h
index d03fd52fd..70204f72b 100644
--- a/Eigen/src/Geometry/Transform.h
+++ b/Eigen/src/Geometry/Transform.h
@@ -876,6 +876,24 @@ Transform<Scalar,Dim,Mode>::fromPositionOrientationScale(const MatrixBase<Positi
return *this;
}
+// selector needed to avoid taking the inverse of a 3x4 matrix
+template<typename TransformType, int Mode=TransformType::Mode>
+struct ei_projective_transform_inverse
+{
+ static inline void run(const TransformType&, TransformType&)
+ {}
+};
+
+template<typename TransformType>
+struct ei_projective_transform_inverse<TransformType, Projective>
+{
+ static inline void run(const TransformType& m, TransformType& res)
+ {
+ res.matrix() = m.matrix().inverse();
+ }
+};
+
+
/** \nonstableyet
*
* \returns the inverse transformation according to some given knowledge
@@ -902,7 +920,7 @@ Transform<Scalar,Dim,Mode>::inverse(TransformTraits hint) const
Transform res;
if (hint == Projective)
{
- res.matrix() = m_matrix.inverse();
+ ei_projective_transform_inverse<Transform>::run(*this, res);
}
else
{
diff --git a/Eigen/src/LU/Determinant.h b/Eigen/src/LU/Determinant.h
index b587065ed..8870d9f20 100644
--- a/Eigen/src/LU/Determinant.h
+++ b/Eigen/src/LU/Determinant.h
@@ -53,7 +53,7 @@ template<typename Derived,
{
static inline typename ei_traits<Derived>::Scalar run(const Derived& m)
{
- return m.partialLu().determinant();
+ return m.partialPivLu().determinant();
}
};
diff --git a/Eigen/src/LU/LU.h b/Eigen/src/LU/FullPivLU.h
index 4792aaf07..8743dac92 100644
--- a/Eigen/src/LU/LU.h
+++ b/Eigen/src/LU/FullPivLU.h
@@ -31,7 +31,7 @@ template<typename MatrixType> struct ei_lu_image_impl;
/** \ingroup LU_Module
*
- * \class LU
+ * \class FullPivLU
*
* \brief LU decomposition of a matrix with complete pivoting, and related features
*
@@ -54,12 +54,12 @@ template<typename MatrixType> struct ei_lu_image_impl;
* permutationP(), permutationQ().
*
* As an exemple, here is how the original matrix can be retrieved:
- * \include class_LU.cpp
- * Output: \verbinclude class_LU.out
+ * \include class_FullPivLU.cpp
+ * Output: \verbinclude class_FullPivLU.out
*
- * \sa MatrixBase::lu(), MatrixBase::determinant(), MatrixBase::inverse()
+ * \sa MatrixBase::fullPivLu(), MatrixBase::determinant(), MatrixBase::inverse()
*/
-template<typename MatrixType> class LU
+template<typename MatrixType> class FullPivLU
{
public:
@@ -81,14 +81,14 @@ template<typename MatrixType> class LU
* The default constructor is useful in cases in which the user intends to
* perform decompositions via LU::compute(const MatrixType&).
*/
- LU();
+ FullPivLU();
/** Constructor.
*
* \param matrix the matrix of which to compute the LU decomposition.
* It is required to be nonzero.
*/
- LU(const MatrixType& matrix);
+ FullPivLU(const MatrixType& matrix);
/** Computes the LU decomposition of the given matrix.
*
@@ -97,11 +97,11 @@ template<typename MatrixType> class LU
*
* \returns a reference to *this
*/
- LU& compute(const MatrixType& matrix);
+ FullPivLU& compute(const MatrixType& matrix);
/** \returns the LU decomposition matrix: the upper-triangular part is U, the
* unit-lower-triangular part is L (at least for square matrices; in the non-square
- * case, special care is needed, see the documentation of class LU).
+ * case, special care is needed, see the documentation of class FullPivLU).
*
* \sa matrixL(), matrixU()
*/
@@ -131,7 +131,7 @@ template<typename MatrixType> class LU
/** \returns a vector of integers, whose size is the number of rows of the matrix being decomposed,
* representing the P permutation i.e. the permutation of the rows. For its precise meaning,
- * see the examples given in the documentation of class LU.
+ * see the examples given in the documentation of class FullPivLU.
*
* \sa permutationQ()
*/
@@ -143,7 +143,7 @@ template<typename MatrixType> class LU
/** \returns a vector of integers, whose size is the number of columns of the matrix being
* decomposed, representing the Q permutation i.e. the permutation of the columns.
- * For its precise meaning, see the examples given in the documentation of class LU.
+ * For its precise meaning, see the examples given in the documentation of class FullPivLU.
*
* \sa permutationP()
*/
@@ -162,8 +162,8 @@ template<typename MatrixType> class LU
* For that, it uses the threshold value that you can control by calling
* setThreshold(const RealScalar&).
*
- * Example: \include LU_kernel.cpp
- * Output: \verbinclude LU_kernel.out
+ * Example: \include FullPivLU_kernel.cpp
+ * Output: \verbinclude FullPivLU_kernel.out
*
* \sa image()
*/
@@ -187,8 +187,8 @@ template<typename MatrixType> class LU
* For that, it uses the threshold value that you can control by calling
* setThreshold(const RealScalar&).
*
- * Example: \include LU_image.cpp
- * Output: \verbinclude LU_image.out
+ * Example: \include FullPivLU_image.cpp
+ * Output: \verbinclude FullPivLU_image.out
*
* \sa kernel()
*/
@@ -214,8 +214,8 @@ template<typename MatrixType> class LU
* \note_about_arbitrary_choice_of_solution
* \note_about_using_kernel_to_study_multiple_solutions
*
- * Example: \include LU_solve.cpp
- * Output: \verbinclude LU_solve.out
+ * Example: \include FullPivLU_solve.cpp
+ * Output: \verbinclude FullPivLU_solve.out
*
* \sa TriangularView::solve(), kernel(), inverse()
*/
@@ -260,7 +260,7 @@ template<typename MatrixType> class LU
*
* If you want to come back to the default behavior, call setThreshold(Default_t)
*/
- LU& setThreshold(const RealScalar& threshold)
+ FullPivLU& setThreshold(const RealScalar& threshold)
{
m_usePrescribedThreshold = true;
m_prescribedThreshold = threshold;
@@ -274,7 +274,7 @@ template<typename MatrixType> class LU
*
* See the documentation of setThreshold(const RealScalar&).
*/
- LU& setThreshold(Default_t)
+ FullPivLU& setThreshold(Default_t)
{
m_usePrescribedThreshold = false;
}
@@ -383,20 +383,20 @@ template<typename MatrixType> class LU
};
template<typename MatrixType>
-LU<MatrixType>::LU()
+FullPivLU<MatrixType>::FullPivLU()
: m_isInitialized(false), m_usePrescribedThreshold(false)
{
}
template<typename MatrixType>
-LU<MatrixType>::LU(const MatrixType& matrix)
+FullPivLU<MatrixType>::FullPivLU(const MatrixType& matrix)
: m_isInitialized(false), m_usePrescribedThreshold(false)
{
compute(matrix);
}
template<typename MatrixType>
-LU<MatrixType>& LU<MatrixType>::compute(const MatrixType& matrix)
+FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
{
m_isInitialized = true;
m_lu = matrix;
@@ -483,7 +483,7 @@ LU<MatrixType>& LU<MatrixType>::compute(const MatrixType& matrix)
}
template<typename MatrixType>
-typename ei_traits<MatrixType>::Scalar LU<MatrixType>::determinant() const
+typename ei_traits<MatrixType>::Scalar FullPivLU<MatrixType>::determinant() const
{
ei_assert(m_isInitialized && "LU is not initialized.");
ei_assert(m_lu.rows() == m_lu.cols() && "You can't take the determinant of a non-square matrix!");
@@ -511,7 +511,7 @@ struct ei_traits<ei_lu_kernel_impl<MatrixType> >
template<typename MatrixType>
struct ei_lu_kernel_impl : public ReturnByValue<ei_lu_kernel_impl<MatrixType> >
{
- typedef LU<MatrixType> LUType;
+ typedef FullPivLU<MatrixType> LUType;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
const LUType& m_lu;
@@ -615,7 +615,7 @@ struct ei_traits<ei_lu_image_impl<MatrixType> >
template<typename MatrixType>
struct ei_lu_image_impl : public ReturnByValue<ei_lu_image_impl<MatrixType> >
{
- typedef LU<MatrixType> LUType;
+ typedef FullPivLU<MatrixType> LUType;
typedef typename MatrixType::RealScalar RealScalar;
const LUType& m_lu;
int m_rank, m_cols;
@@ -670,7 +670,7 @@ template<typename MatrixType, typename Rhs>
struct ei_lu_solve_impl : public ReturnByValue<ei_lu_solve_impl<MatrixType, Rhs> >
{
typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNested;
- typedef LU<MatrixType> LUType;
+ typedef FullPivLU<MatrixType> LUType;
const LUType& m_lu;
const typename Rhs::Nested m_rhs;
@@ -739,15 +739,15 @@ struct ei_lu_solve_impl : public ReturnByValue<ei_lu_solve_impl<MatrixType, Rhs>
/** \lu_module
*
- * \return the LU decomposition of \c *this.
+ * \return the full-pivoting LU decomposition of \c *this.
*
- * \sa class LU
+ * \sa class FullPivLU
*/
template<typename Derived>
-inline const LU<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::lu() const
+inline const FullPivLU<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::fullPivLu() const
{
- return LU<PlainMatrixType>(eval());
+ return FullPivLU<PlainMatrixType>(eval());
}
#endif // EIGEN_LU_H
diff --git a/Eigen/src/LU/Inverse.h b/Eigen/src/LU/Inverse.h
index a168d58cd..306b5f60a 100644
--- a/Eigen/src/LU/Inverse.h
+++ b/Eigen/src/LU/Inverse.h
@@ -34,7 +34,7 @@ struct ei_compute_inverse
{
static inline void run(const MatrixType& matrix, ResultType& result)
{
- result = matrix.partialLu().inverse();
+ result = matrix.partialPivLu().inverse();
}
};
@@ -232,22 +232,31 @@ struct ei_compute_inverse<MatrixType, ResultType, 4>
typename MatrixType::PlainMatrixType matrix(_matrix);
// let's extract from the 2 first colums a 2x2 block whose determinant is as big as possible.
- int good_row0=0, good_row1=1;
- RealScalar good_absdet(-1);
- // this double for loop shouldn't be too costly: only 6 iterations
- for(int row0=0; row0<4; ++row0) {
- for(int row1=row0+1; row1<4; ++row1)
- {
- RealScalar absdet = ei_abs(matrix.coeff(row0,0)*matrix.coeff(row1,1)
- - matrix.coeff(row0,1)*matrix.coeff(row1,0));
- if(absdet > good_absdet)
- {
- good_absdet = absdet;
- good_row0 = row0;
- good_row1 = row1;
- }
- }
- }
+ int good_row0, good_row1, good_i;
+ Matrix<RealScalar,6,1> absdet;
+
+ // any 2x2 block with determinant above this threshold will be considered good enough
+ RealScalar d = (matrix.col(0).squaredNorm()+matrix.col(1).squaredNorm()) * RealScalar(1e-2);
+ #define ei_inv_size4_helper_macro(i,row0,row1) \
+ absdet[i] = ei_abs(matrix.coeff(row0,0)*matrix.coeff(row1,1) \
+ - matrix.coeff(row0,1)*matrix.coeff(row1,0)); \
+ if(absdet[i] > d) { good_row0=row0; good_row1=row1; goto good; }
+ ei_inv_size4_helper_macro(0,0,1)
+ ei_inv_size4_helper_macro(1,0,2)
+ ei_inv_size4_helper_macro(2,0,3)
+ ei_inv_size4_helper_macro(3,1,2)
+ ei_inv_size4_helper_macro(4,1,3)
+ ei_inv_size4_helper_macro(5,2,3)
+
+ // no 2x2 block has determinant bigger than the threshold. So just take the one that
+ // has the biggest determinant
+ absdet.maxCoeff(&good_i);
+ good_row0 = good_i <= 2 ? 0 : good_i <= 4 ? 1 : 2;
+ good_row1 = good_i <= 2 ? good_i+1 : good_i <= 4 ? good_i-1 : 3;
+
+ // now good_row0 and good_row1 are correctly set
+ good:
+
// do row permutations to move this 2x2 block to the top
matrix.row(0).swap(matrix.row(good_row0));
matrix.row(1).swap(matrix.row(good_row1));
@@ -318,12 +327,12 @@ struct ei_inverse_impl : public ReturnByValue<ei_inverse_impl<MatrixType> >
* \returns the matrix inverse of this matrix.
*
* For small fixed sizes up to 4x4, this method uses ad-hoc methods (cofactors up to 3x3, Euler's trick for 4x4).
- * In the general case, this method uses class PartialLU.
+ * In the general case, this method uses class PartialPivLU.
*
* \note This matrix must be invertible, otherwise the result is undefined. If you need an
* invertibility check, do the following:
* \li for fixed sizes up to 4x4, use computeInverseAndDetWithCheck().
- * \li for the general case, use class LU.
+ * \li for the general case, use class FullPivLU.
*
* Example: \include MatrixBase_inverse.cpp
* Output: \verbinclude MatrixBase_inverse.out
diff --git a/Eigen/src/LU/PartialLU.h b/Eigen/src/LU/PartialPivLU.h
index e8d21e5ad..647ada38f 100644
--- a/Eigen/src/LU/PartialLU.h
+++ b/Eigen/src/LU/PartialPivLU.h
@@ -30,7 +30,7 @@ template<typename MatrixType, typename Rhs> struct ei_partiallu_solve_impl;
/** \ingroup LU_Module
*
- * \class PartialLU
+ * \class PartialPivLU
*
* \brief LU decomposition of a matrix with partial pivoting, and related features
*
@@ -46,10 +46,10 @@ template<typename MatrixType, typename Rhs> struct ei_partiallu_solve_impl;
* matrix is invertible: it is your task to check that you only use this decomposition on invertible matrices.
*
* The guaranteed safe alternative, working for all matrices, is the full pivoting LU decomposition, provided
- * by class LU.
+ * by class FullPivLU.
*
* This is \b not a rank-revealing LU decomposition. Many features are intentionally absent from this class,
- * such as rank computation. If you need these features, use class LU.
+ * such as rank computation. If you need these features, use class FullPivLU.
*
* This LU decomposition is suitable to invert invertible matrices. It is what MatrixBase::inverse() uses
* in the general case.
@@ -57,9 +57,9 @@ template<typename MatrixType, typename Rhs> struct ei_partiallu_solve_impl;
*
* The data of the LU decomposition can be directly accessed through the methods matrixLU(), permutationP().
*
- * \sa MatrixBase::partialLu(), MatrixBase::determinant(), MatrixBase::inverse(), MatrixBase::computeInverse(), class LU
+ * \sa MatrixBase::partialPivLu(), MatrixBase::determinant(), MatrixBase::inverse(), MatrixBase::computeInverse(), class FullPivLU
*/
-template<typename MatrixType> class PartialLU
+template<typename MatrixType> class PartialPivLU
{
public:
@@ -79,40 +79,40 @@ template<typename MatrixType> class PartialLU
* \brief Default Constructor.
*
* The default constructor is useful in cases in which the user intends to
- * perform decompositions via PartialLU::compute(const MatrixType&).
+ * perform decompositions via PartialPivLU::compute(const MatrixType&).
*/
- PartialLU();
+ PartialPivLU();
/** Constructor.
*
* \param matrix the matrix of which to compute the LU decomposition.
*
* \warning The matrix should have full rank (e.g. if it's square, it should be invertible).
- * If you need to deal with non-full rank, use class LU instead.
+ * If you need to deal with non-full rank, use class FullPivLU instead.
*/
- PartialLU(const MatrixType& matrix);
+ PartialPivLU(const MatrixType& matrix);
- PartialLU& compute(const MatrixType& matrix);
+ PartialPivLU& compute(const MatrixType& matrix);
/** \returns the LU decomposition matrix: the upper-triangular part is U, the
* unit-lower-triangular part is L (at least for square matrices; in the non-square
- * case, special care is needed, see the documentation of class LU).
+ * case, special care is needed, see the documentation of class FullPivLU).
*
* \sa matrixL(), matrixU()
*/
inline const MatrixType& matrixLU() const
{
- ei_assert(m_isInitialized && "PartialLU is not initialized.");
+ ei_assert(m_isInitialized && "PartialPivLU is not initialized.");
return m_lu;
}
/** \returns a vector of integers, whose size is the number of rows of the matrix being decomposed,
* representing the P permutation i.e. the permutation of the rows. For its precise meaning,
- * see the examples given in the documentation of class LU.
+ * see the examples given in the documentation of class FullPivLU.
*/
inline const IntColVectorType& permutationP() const
{
- ei_assert(m_isInitialized && "PartialLU is not initialized.");
+ ei_assert(m_isInitialized && "PartialPivLU is not initialized.");
return m_p;
}
@@ -125,10 +125,10 @@ template<typename MatrixType> class PartialLU
*
* \returns the solution.
*
- * Example: \include PartialLU_solve.cpp
- * Output: \verbinclude PartialLU_solve.out
+ * Example: \include PartialPivLU_solve.cpp
+ * Output: \verbinclude PartialPivLU_solve.out
*
- * Since this PartialLU class assumes anyway that the matrix A is invertible, the solution
+ * Since this PartialPivLU class assumes anyway that the matrix A is invertible, the solution
* theoretically exists and is unique regardless of b.
*
* \note_about_checking_solutions
@@ -146,7 +146,7 @@ template<typename MatrixType> class PartialLU
/** \returns the inverse of the matrix of which *this is the LU decomposition.
*
* \warning The matrix being decomposed here is assumed to be invertible. If you need to check for
- * invertibility, use class LU instead.
+ * invertibility, use class FullPivLU instead.
*
* \sa MatrixBase::inverse(), LU::inverse()
*/
@@ -180,7 +180,7 @@ template<typename MatrixType> class PartialLU
};
template<typename MatrixType>
-PartialLU<MatrixType>::PartialLU()
+PartialPivLU<MatrixType>::PartialPivLU()
: m_lu(),
m_p(),
m_det_p(0),
@@ -189,7 +189,7 @@ PartialLU<MatrixType>::PartialLU()
}
template<typename MatrixType>
-PartialLU<MatrixType>::PartialLU(const MatrixType& matrix)
+PartialPivLU<MatrixType>::PartialPivLU(const MatrixType& matrix)
: m_lu(),
m_p(),
m_det_p(0),
@@ -378,12 +378,12 @@ void ei_partial_lu_inplace(MatrixType& lu, IntVector& row_transpositions, int& n
}
template<typename MatrixType>
-PartialLU<MatrixType>& PartialLU<MatrixType>::compute(const MatrixType& matrix)
+PartialPivLU<MatrixType>& PartialPivLU<MatrixType>::compute(const MatrixType& matrix)
{
m_lu = matrix;
m_p.resize(matrix.rows());
- ei_assert(matrix.rows() == matrix.cols() && "PartialLU is only for square (and moreover invertible) matrices");
+ ei_assert(matrix.rows() == matrix.cols() && "PartialPivLU is only for square (and moreover invertible) matrices");
const int size = matrix.rows();
IntColVectorType rows_transpositions(size);
@@ -401,9 +401,9 @@ PartialLU<MatrixType>& PartialLU<MatrixType>::compute(const MatrixType& matrix)
}
template<typename MatrixType>
-typename ei_traits<MatrixType>::Scalar PartialLU<MatrixType>::determinant() const
+typename ei_traits<MatrixType>::Scalar PartialPivLU<MatrixType>::determinant() const
{
- ei_assert(m_isInitialized && "PartialLU is not initialized.");
+ ei_assert(m_isInitialized && "PartialPivLU is not initialized.");
return Scalar(m_det_p) * m_lu.diagonal().prod();
}
@@ -424,7 +424,7 @@ template<typename MatrixType, typename Rhs>
struct ei_partiallu_solve_impl : public ReturnByValue<ei_partiallu_solve_impl<MatrixType, Rhs> >
{
typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNested;
- typedef PartialLU<MatrixType> LUType;
+ typedef PartialPivLU<MatrixType> LUType;
const LUType& m_lu;
const typename Rhs::Nested m_rhs;
@@ -464,15 +464,30 @@ struct ei_partiallu_solve_impl : public ReturnByValue<ei_partiallu_solve_impl<Ma
/** \lu_module
*
- * \return the LU decomposition of \c *this.
+ * \return the partial-pivoting LU decomposition of \c *this.
*
- * \sa class LU
+ * \sa class PartialPivLU
*/
template<typename Derived>
-inline const PartialLU<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::partialLu() const
+inline const PartialPivLU<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::partialPivLu() const
{
- return PartialLU<PlainMatrixType>(eval());
+ return PartialPivLU<PlainMatrixType>(eval());
+}
+
+/** \lu_module
+ *
+ * Synonym of partialPivLu().
+ *
+ * \return the partial-pivoting LU decomposition of \c *this.
+ *
+ * \sa class PartialPivLU
+ */
+template<typename Derived>
+inline const PartialPivLU<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::lu() const
+{
+ return PartialPivLU<PlainMatrixType>(eval());
}
#endif // EIGEN_PARTIALLU_H
diff --git a/Eigen/src/QR/ColPivotingHouseholderQR.h b/Eigen/src/QR/ColPivHouseholderQR.h
index b141da0aa..05287ff3c 100644
--- a/Eigen/src/QR/ColPivotingHouseholderQR.h
+++ b/Eigen/src/QR/ColPivHouseholderQR.h
@@ -29,7 +29,7 @@
/** \ingroup QR_Module
* \nonstableyet
*
- * \class ColPivotingHouseholderQR
+ * \class ColPivHouseholderQR
*
* \brief Householder rank-revealing QR decomposition of a matrix with column-pivoting
*
@@ -38,11 +38,11 @@
* This class performs a rank-revealing QR decomposition using Householder transformations.
*
* This decomposition performs column pivoting in order to be rank-revealing and improve
- * numerical stability. It is slower than HouseholderQR, and faster than FullPivotingHouseholderQR.
+ * numerical stability. It is slower than HouseholderQR, and faster than FullPivHouseholderQR.
*
- * \sa MatrixBase::colPivotingHouseholderQr()
+ * \sa MatrixBase::colPivHouseholderQr()
*/
-template<typename MatrixType> class ColPivotingHouseholderQR
+template<typename MatrixType> class ColPivHouseholderQR
{
public:
@@ -68,11 +68,11 @@ template<typename MatrixType> class ColPivotingHouseholderQR
* \brief Default Constructor.
*
* The default constructor is useful in cases in which the user intends to
- * perform decompositions via ColPivotingHouseholderQR::compute(const MatrixType&).
+ * perform decompositions via ColPivHouseholderQR::compute(const MatrixType&).
*/
- ColPivotingHouseholderQR() : m_qr(), m_hCoeffs(), m_isInitialized(false) {}
+ ColPivHouseholderQR() : m_qr(), m_hCoeffs(), m_isInitialized(false) {}
- ColPivotingHouseholderQR(const MatrixType& matrix)
+ ColPivHouseholderQR(const MatrixType& matrix)
: m_qr(matrix.rows(), matrix.cols()),
m_hCoeffs(std::min(matrix.rows(),matrix.cols())),
m_isInitialized(false)
@@ -94,8 +94,8 @@ template<typename MatrixType> class ColPivotingHouseholderQR
* \note The case where b is a matrix is not yet implemented. Also, this
* code is space inefficient.
*
- * Example: \include ColPivotingHouseholderQR_solve.cpp
- * Output: \verbinclude ColPivotingHouseholderQR_solve.out
+ * Example: \include ColPivHouseholderQR_solve.cpp
+ * Output: \verbinclude ColPivHouseholderQR_solve.out
*/
template<typename OtherDerived, typename ResultType>
bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const;
@@ -106,15 +106,15 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
const MatrixType& matrixQR() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_qr;
}
- ColPivotingHouseholderQR& compute(const MatrixType& matrix);
+ ColPivHouseholderQR& compute(const MatrixType& matrix);
const IntRowVectorType& colsPermutation() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_cols_permutation;
}
@@ -154,7 +154,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline int rank() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_rank;
}
@@ -165,7 +165,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline int dimensionOfKernel() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_qr.cols() - m_rank;
}
@@ -177,7 +177,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline bool isInjective() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_rank == m_qr.cols();
}
@@ -189,7 +189,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline bool isSurjective() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return m_rank == m_qr.rows();
}
@@ -200,7 +200,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline bool isInvertible() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return isInjective() && isSurjective();
}
@@ -215,7 +215,7 @@ template<typename MatrixType> class ColPivotingHouseholderQR
*/
inline void computeInverse(MatrixType *result) const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the inverse of a non-square matrix!");
solve(MatrixType::Identity(m_qr.rows(), m_qr.cols()), result);
}
@@ -247,23 +247,23 @@ template<typename MatrixType> class ColPivotingHouseholderQR
#ifndef EIGEN_HIDE_HEAVY_CODE
template<typename MatrixType>
-typename MatrixType::RealScalar ColPivotingHouseholderQR<MatrixType>::absDeterminant() const
+typename MatrixType::RealScalar ColPivHouseholderQR<MatrixType>::absDeterminant() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
return ei_abs(m_qr.diagonal().prod());
}
template<typename MatrixType>
-typename MatrixType::RealScalar ColPivotingHouseholderQR<MatrixType>::logAbsDeterminant() const
+typename MatrixType::RealScalar ColPivHouseholderQR<MatrixType>::logAbsDeterminant() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
return m_qr.diagonal().cwise().abs().cwise().log().sum();
}
template<typename MatrixType>
-ColPivotingHouseholderQR<MatrixType>& ColPivotingHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
+ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
{
int rows = matrix.rows();
int cols = matrix.cols();
@@ -333,12 +333,12 @@ ColPivotingHouseholderQR<MatrixType>& ColPivotingHouseholderQR<MatrixType>::comp
template<typename MatrixType>
template<typename OtherDerived, typename ResultType>
-bool ColPivotingHouseholderQR<MatrixType>::solve(
+bool ColPivHouseholderQR<MatrixType>::solve(
const MatrixBase<OtherDerived>& b,
ResultType *result
) const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
result->resize(m_qr.cols(), b.cols());
if(m_rank==0)
{
@@ -378,9 +378,9 @@ bool ColPivotingHouseholderQR<MatrixType>::solve(
/** \returns the matrix Q as a sequence of householder transformations */
template<typename MatrixType>
-typename ColPivotingHouseholderQR<MatrixType>::HouseholderSequenceType ColPivotingHouseholderQR<MatrixType>::matrixQ() const
+typename ColPivHouseholderQR<MatrixType>::HouseholderSequenceType ColPivHouseholderQR<MatrixType>::matrixQ() const
{
- ei_assert(m_isInitialized && "ColPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate());
}
@@ -388,13 +388,13 @@ typename ColPivotingHouseholderQR<MatrixType>::HouseholderSequenceType ColPivoti
/** \return the column-pivoting Householder QR decomposition of \c *this.
*
- * \sa class ColPivotingHouseholderQR
+ * \sa class ColPivHouseholderQR
*/
template<typename Derived>
-const ColPivotingHouseholderQR<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::colPivotingHouseholderQr() const
+const ColPivHouseholderQR<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::colPivHouseholderQr() const
{
- return ColPivotingHouseholderQR<PlainMatrixType>(eval());
+ return ColPivHouseholderQR<PlainMatrixType>(eval());
}
diff --git a/Eigen/src/QR/FullPivotingHouseholderQR.h b/Eigen/src/QR/FullPivHouseholderQR.h
index 9fee77803..07ec343a5 100644
--- a/Eigen/src/QR/FullPivotingHouseholderQR.h
+++ b/Eigen/src/QR/FullPivHouseholderQR.h
@@ -29,7 +29,7 @@
/** \ingroup QR_Module
* \nonstableyet
*
- * \class FullPivotingHouseholderQR
+ * \class FullPivHouseholderQR
*
* \brief Householder rank-revealing QR decomposition of a matrix with full pivoting
*
@@ -38,11 +38,11 @@
* This class performs a rank-revealing QR decomposition using Householder transformations.
*
* This decomposition performs a very prudent full pivoting in order to be rank-revealing and achieve optimal
- * numerical stability. The trade-off is that it is slower than HouseholderQR and ColPivotingHouseholderQR.
+ * numerical stability. The trade-off is that it is slower than HouseholderQR and ColPivHouseholderQR.
*
- * \sa MatrixBase::fullPivotingHouseholderQr()
+ * \sa MatrixBase::fullPivHouseholderQr()
*/
-template<typename MatrixType> class FullPivotingHouseholderQR
+template<typename MatrixType> class FullPivHouseholderQR
{
public:
@@ -65,11 +65,11 @@ template<typename MatrixType> class FullPivotingHouseholderQR
/** \brief Default Constructor.
*
* The default constructor is useful in cases in which the user intends to
- * perform decompositions via FullPivotingHouseholderQR::compute(const MatrixType&).
+ * perform decompositions via FullPivHouseholderQR::compute(const MatrixType&).
*/
- FullPivotingHouseholderQR() : m_isInitialized(false) {}
+ FullPivHouseholderQR() : m_isInitialized(false) {}
- FullPivotingHouseholderQR(const MatrixType& matrix)
+ FullPivHouseholderQR(const MatrixType& matrix)
: m_isInitialized(false)
{
compute(matrix);
@@ -89,8 +89,8 @@ template<typename MatrixType> class FullPivotingHouseholderQR
* \note The case where b is a matrix is not yet implemented. Also, this
* code is space inefficient.
*
- * Example: \include FullPivotingHouseholderQR_solve.cpp
- * Output: \verbinclude FullPivotingHouseholderQR_solve.out
+ * Example: \include FullPivHouseholderQR_solve.cpp
+ * Output: \verbinclude FullPivHouseholderQR_solve.out
*/
template<typename OtherDerived, typename ResultType>
bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const;
@@ -101,21 +101,21 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
const MatrixType& matrixQR() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_qr;
}
- FullPivotingHouseholderQR& compute(const MatrixType& matrix);
+ FullPivHouseholderQR& compute(const MatrixType& matrix);
const IntRowVectorType& colsPermutation() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_cols_permutation;
}
const IntColVectorType& rowsTranspositions() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_rows_transpositions;
}
@@ -155,7 +155,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline int rank() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_rank;
}
@@ -166,7 +166,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline int dimensionOfKernel() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_qr.cols() - m_rank;
}
@@ -178,7 +178,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline bool isInjective() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_rank == m_qr.cols();
}
@@ -190,7 +190,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline bool isSurjective() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return m_rank == m_qr.rows();
}
@@ -201,7 +201,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline bool isInvertible() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
return isInjective() && isSurjective();
}
@@ -216,7 +216,7 @@ template<typename MatrixType> class FullPivotingHouseholderQR
*/
inline void computeInverse(MatrixType *result) const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the inverse of a non-square matrix!");
solve(MatrixType::Identity(m_qr.rows(), m_qr.cols()), result);
}
@@ -249,23 +249,23 @@ template<typename MatrixType> class FullPivotingHouseholderQR
#ifndef EIGEN_HIDE_HEAVY_CODE
template<typename MatrixType>
-typename MatrixType::RealScalar FullPivotingHouseholderQR<MatrixType>::absDeterminant() const
+typename MatrixType::RealScalar FullPivHouseholderQR<MatrixType>::absDeterminant() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
return ei_abs(m_qr.diagonal().prod());
}
template<typename MatrixType>
-typename MatrixType::RealScalar FullPivotingHouseholderQR<MatrixType>::logAbsDeterminant() const
+typename MatrixType::RealScalar FullPivHouseholderQR<MatrixType>::logAbsDeterminant() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
ei_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
return m_qr.diagonal().cwise().abs().cwise().log().sum();
}
template<typename MatrixType>
-FullPivotingHouseholderQR<MatrixType>& FullPivotingHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
+FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
{
int rows = matrix.rows();
int cols = matrix.cols();
@@ -342,12 +342,12 @@ FullPivotingHouseholderQR<MatrixType>& FullPivotingHouseholderQR<MatrixType>::co
template<typename MatrixType>
template<typename OtherDerived, typename ResultType>
-bool FullPivotingHouseholderQR<MatrixType>::solve(
+bool FullPivHouseholderQR<MatrixType>::solve(
const MatrixBase<OtherDerived>& b,
ResultType *result
) const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
result->resize(m_qr.cols(), b.cols());
if(m_rank==0)
{
@@ -393,9 +393,9 @@ bool FullPivotingHouseholderQR<MatrixType>::solve(
/** \returns the matrix Q */
template<typename MatrixType>
-typename FullPivotingHouseholderQR<MatrixType>::MatrixQType FullPivotingHouseholderQR<MatrixType>::matrixQ() const
+typename FullPivHouseholderQR<MatrixType>::MatrixQType FullPivHouseholderQR<MatrixType>::matrixQ() const
{
- ei_assert(m_isInitialized && "FullPivotingHouseholderQR is not initialized.");
+ ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
// compute the product H'_0 H'_1 ... H'_n-1,
// where H_k is the k-th Householder transformation I - h_k v_k v_k'
// and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...]
@@ -417,13 +417,13 @@ typename FullPivotingHouseholderQR<MatrixType>::MatrixQType FullPivotingHousehol
/** \return the full-pivoting Householder QR decomposition of \c *this.
*
- * \sa class FullPivotingHouseholderQR
+ * \sa class FullPivHouseholderQR
*/
template<typename Derived>
-const FullPivotingHouseholderQR<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::fullPivotingHouseholderQr() const
+const FullPivHouseholderQR<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::fullPivHouseholderQr() const
{
- return FullPivotingHouseholderQR<PlainMatrixType>(eval());
+ return FullPivHouseholderQR<PlainMatrixType>(eval());
}
#endif // EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H
diff --git a/Eigen/src/QR/HouseholderQR.h b/Eigen/src/QR/HouseholderQR.h
index 01cd2adb5..a32aa4eaf 100644
--- a/Eigen/src/QR/HouseholderQR.h
+++ b/Eigen/src/QR/HouseholderQR.h
@@ -39,10 +39,10 @@
* stored in a compact way compatible with LAPACK.
*
* Note that no pivoting is performed. This is \b not a rank-revealing decomposition.
- * If you want that feature, use FullPivotingHouseholderQR or ColPivotingHouseholderQR instead.
+ * If you want that feature, use FullPivHouseholderQR or ColPivHouseholderQR instead.
*
* This Householder QR decomposition is faster, but less numerically stable and less feature-full than
- * FullPivotingHouseholderQR or ColPivotingHouseholderQR.
+ * FullPivHouseholderQR or ColPivHouseholderQR.
*
* \sa MatrixBase::householderQr()
*/
diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h
index 6a0597893..927ef6591 100644
--- a/Eigen/src/SVD/JacobiSVD.h
+++ b/Eigen/src/SVD/JacobiSVD.h
@@ -233,7 +233,7 @@ struct ei_svd_precondition_if_more_rows_than_cols<MatrixType, Options, true>
int diagSize = cols;
if(rows > cols)
{
- FullPivotingHouseholderQR<MatrixType> qr(matrix);
+ FullPivHouseholderQR<MatrixType> qr(matrix);
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<UpperTriangular>();
if(ComputeU) svd.m_matrixU = qr.matrixQ();
if(ComputeV)
@@ -278,7 +278,7 @@ struct ei_svd_precondition_if_more_cols_than_rows<MatrixType, Options, true>
typedef Matrix<Scalar,ColsAtCompileTime,RowsAtCompileTime,
MatrixOptions,MaxColsAtCompileTime,MaxRowsAtCompileTime>
TransposeTypeWithSameStorageOrder;
- FullPivotingHouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
+ FullPivHouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<UpperTriangular>().adjoint();
if(ComputeV) svd.m_matrixV = qr.matrixQ();
if(ComputeU)
diff --git a/Eigen/src/Sparse/SparseLU.h b/Eigen/src/Sparse/SparseLU.h
index e7191b7ab..3f8d0f8db 100644
--- a/Eigen/src/Sparse/SparseLU.h
+++ b/Eigen/src/Sparse/SparseLU.h
@@ -39,7 +39,7 @@ enum {
*
* \param MatrixType the type of the matrix of which we are computing the LU factorization
*
- * \sa class LU, class SparseLLT
+ * \sa class FullPivLU, class SparseLLT
*/
template<typename MatrixType, int Backend = DefaultBackend>
class SparseLU
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-04 22:43:48 +0000