big huge changes, so i dont remember everything.

* renaming, e.g. LU ---> FullPivLU * split tests framework: more robust, e.g. dont generate empty tests if a number is skipped * make all remaining tests use that splitting, as needed. * Fix 4x4 inversion (see stable branch) * Transform::inverse() and geo_transform test : adapt to new inverse() API, it was also trying to instantiate inverse() for 3x4 matrices. * CMakeLists: more robust regexp to parse the version number * misc fixes in unit tests
2026-04-10 11:34:33 +08:00 · 2009-10-28 18:19:29 -04:00
parent 1f1c04cac1
commit 2840ac7e94
99 changed files with 816 additions and 710 deletions
--- 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
    {
--- 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;
--- 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
  };
 };

--- 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;
--- 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 && \
--- 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
  {
--- 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();
  }
 };

--- a/Eigen/src/LU/FullPivLU.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
--- 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
--- a/Eigen/src/LU/PartialPivLU.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
--- a/Eigen/src/QR/ColPivotingHouseholderQR.h
+++ b/Eigen/src/QR/ColPivotingHouseholderQR.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());
 }


--- a/Eigen/src/QR/FullPivotingHouseholderQR.h
+++ b/Eigen/src/QR/FullPivotingHouseholderQR.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
--- 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()
  */
--- 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)
--- 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