clean old stuff used to support precompilation inside a binary lib

11 files changed, 76 insertions, 206 deletions

diff --git a/Eigen/Cholesky b/Eigen/Cholesky
index a0e0d146b..7d209966f 100644
--- a/Eigen/Cholesky
+++ b/Eigen/Cholesky
@@ -5,15 +5,6 @@
 
 #include "src/Core/util/DisableMSVCWarnings.h"
 
-// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
-#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
-  #ifndef EIGEN_HIDE_HEAVY_CODE
-  #define EIGEN_HIDE_HEAVY_CODE
-  #endif
-#elif defined EIGEN_HIDE_HEAVY_CODE
-  #undef EIGEN_HIDE_HEAVY_CODE
-#endif
-
 namespace Eigen {
 
 /** \defgroup Cholesky_Module Cholesky module
@@ -37,29 +28,6 @@ namespace Eigen {
 
 } // namespace Eigen
 
-#define EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class LLT<MATRIXTYPE>; \
-  PREFIX template class LDLT<MATRIXTYPE>
-
-#define EIGEN_CHOLESKY_MODULE_INSTANTIATE(PREFIX) \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix2d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix3f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix3d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix4f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix4d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXf,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXd,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXcf,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXcd,PREFIX)
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-
-namespace Eigen {
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE(extern);
-} // namespace Eigen
-#endif
-
 #include "src/Core/util/EnableMSVCWarnings.h"
 
 #endif // EIGEN_CHOLESKY_MODULE_H
diff --git a/Eigen/Eigenvalues b/Eigen/Eigenvalues
index f22a3bc30..5a9757ad5 100644
--- a/Eigen/Eigenvalues
+++ b/Eigen/Eigenvalues
@@ -10,15 +10,6 @@
 #include "Householder"
 #include "LU"
 
-// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
-#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
-  #ifndef EIGEN_HIDE_HEAVY_CODE
-  #define EIGEN_HIDE_HEAVY_CODE
-  #endif
-#elif defined EIGEN_HIDE_HEAVY_CODE
-  #undef EIGEN_HIDE_HEAVY_CODE
-#endif
-
 namespace Eigen {
 
 /** \defgroup Eigenvalues_Module Eigenvalues module
@@ -44,32 +35,6 @@ namespace Eigen {
 #include "src/Eigenvalues/ComplexEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
 
-// declare all classes for a given matrix type
-#define EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class Tridiagonalization<MATRIXTYPE>; \
-  PREFIX template class HessenbergDecomposition<MATRIXTYPE>; \
-  PREFIX template class SelfAdjointEigenSolver<MATRIXTYPE>
-
-// removed because it does not support complex yet
-//  PREFIX template class EigenSolver<MATRIXTYPE>
-
-// declare all class for all types
-#define EIGEN_EIGENVALUES_MODULE_INSTANTIATE(PREFIX) \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix2d,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix3f,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix3d,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix4f,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(Matrix4d,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(MatrixXf,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(MatrixXd,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(MatrixXcf,PREFIX); \
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE_TYPE(MatrixXcd,PREFIX)
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-  EIGEN_EIGENVALUES_MODULE_INSTANTIATE(extern);
-#endif // EIGEN_EXTERN_INSTANTIATIONS
-
 } // namespace Eigen
 
 #include "src/Core/util/EnableMSVCWarnings.h"
diff --git a/Eigen/QR b/Eigen/QR
index 825cfb149..d64f96002 100644
--- a/Eigen/QR
+++ b/Eigen/QR
@@ -9,15 +9,6 @@
 #include "Jacobi"
 #include "Householder"
 
-// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
-#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
-  #ifndef EIGEN_HIDE_HEAVY_CODE
-  #define EIGEN_HIDE_HEAVY_CODE
-  #endif
-#elif defined EIGEN_HIDE_HEAVY_CODE
-  #undef EIGEN_HIDE_HEAVY_CODE
-#endif
-
 namespace Eigen {
 
 /** \defgroup QR_Module QR module
@@ -38,26 +29,6 @@ namespace Eigen {
 #include "src/QR/FullPivHouseholderQR.h"
 #include "src/QR/ColPivHouseholderQR.h"
 
-// declare all classes for a given matrix type
-#define EIGEN_QR_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class HouseholderQR<MATRIXTYPE>; \
-
-// declare all class for all types
-#define EIGEN_QR_MODULE_INSTANTIATE(PREFIX) \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix2d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix3f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix3d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix4f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix4d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXf,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXd,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXcf,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXcd,PREFIX)
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-  EIGEN_QR_MODULE_INSTANTIATE(extern);
-#endif // EIGEN_EXTERN_INSTANTIATIONS
 
 } // namespace Eigen
 
diff --git a/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index d81715528..ca3e4eaf3 100644
--- a/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -25,8 +25,6 @@
 #ifndef EIGEN_GENERAL_BLOCK_PANEL_H
 #define EIGEN_GENERAL_BLOCK_PANEL_H
 
-#ifndef EIGEN_EXTERN_INSTANTIATIONS
-
 #ifdef EIGEN_HAS_FUSE_CJMADD
 #define CJMADD(A,B,C,T)  C = cj.pmadd(A,B,C);
 #else
@@ -762,6 +760,4 @@ struct ei_gemm_pack_rhs<Scalar, Index, nr, RowMajor, PanelMode>
   }
 };
 
-#endif // EIGEN_EXTERN_INSTANTIATIONS
-
 #endif // EIGEN_GENERAL_BLOCK_PANEL_H
diff --git a/Eigen/src/Core/products/GeneralMatrixMatrix.h b/Eigen/src/Core/products/GeneralMatrixMatrix.h
index 991977c1f..457173382 100644
--- a/Eigen/src/Core/products/GeneralMatrixMatrix.h
+++ b/Eigen/src/Core/products/GeneralMatrixMatrix.h
@@ -25,8 +25,6 @@
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_H
 
-#ifndef EIGEN_EXTERN_INSTANTIATIONS
-
 /* Specialization for a row-major destination matrix => simple transposition of the product */
 template<
   typename Scalar, typename Index,
@@ -203,8 +201,6 @@ static void run(Index rows, Index cols, Index depth,
 
 };
 
-#endif // EIGEN_EXTERN_INSTANTIATIONS
-
 /*********************************************************************************
 *  Specialization of GeneralProduct<> for "large" GEMM, i.e.,
 *  implementation of the high level wrapper to ei_general_matrix_matrix_product
diff --git a/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
index 4f3c357a8..783042782 100644
--- a/Eigen/src/Eigenvalues/HessenbergDecomposition.h
+++ b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
@@ -53,11 +53,11 @@ struct ei_traits<HessenbergDecompositionMatrixHReturnType<MatrixType> >
   * \f$ Q^{-1} = Q^* \f$).
   *
   * Call the function compute() to compute the Hessenberg decomposition of a
-  * given matrix. Alternatively, you can use the 
+  * given matrix. Alternatively, you can use the
   * HessenbergDecomposition(const MatrixType&) constructor which computes the
   * Hessenberg decomposition at construction time. Once the decomposition is
   * computed, you can use the matrixH() and matrixQ() functions to construct
-  * the matrices H and Q in the decomposition. 
+  * the matrices H and Q in the decomposition.
   *
   * The documentation for matrixH() contains an example of the typical use of
   * this class.
@@ -114,8 +114,8 @@ template<typename _MatrixType> class HessenbergDecomposition
         m_hCoeffs.resize(size-1);
     }
 
-    /** \brief Constructor; computes Hessenberg decomposition of given matrix. 
-      * 
+    /** \brief Constructor; computes Hessenberg decomposition of given matrix.
+      *
       * \param[in]  matrix  Square matrix whose Hessenberg decomposition is to be computed.
       *
       * This constructor calls compute() to compute the Hessenberg
@@ -138,8 +138,8 @@ template<typename _MatrixType> class HessenbergDecomposition
       m_isInitialized = true;
     }
 
-    /** \brief Computes Hessenberg decomposition of given matrix. 
-      * 
+    /** \brief Computes Hessenberg decomposition of given matrix.
+      *
       * \param[in]  matrix  Square matrix whose Hessenberg decomposition is to be computed.
       * \returns    Reference to \c *this
       *
@@ -177,18 +177,18 @@ template<typename _MatrixType> class HessenbergDecomposition
       * or the member function compute(const MatrixType&) has been called
       * before to compute the Hessenberg decomposition of a matrix.
       *
-      * The Householder coefficients allow the reconstruction of the matrix 
+      * The Householder coefficients allow the reconstruction of the matrix
       * \f$ Q \f$ in the Hessenberg decomposition from the packed data.
       *
       * \sa packedMatrix(), \ref Householder_Module "Householder module"
       */
-    const CoeffVectorType& householderCoefficients() const 
-    { 
+    const CoeffVectorType& householderCoefficients() const
+    {
       ei_assert(m_isInitialized && "HessenbergDecomposition is not initialized.");
-      return m_hCoeffs; 
+      return m_hCoeffs;
     }
 
-    /** \brief Returns the internal representation of the decomposition 
+    /** \brief Returns the internal representation of the decomposition
       *
       *	\returns a const reference to a matrix with the internal representation
       *	         of the decomposition.
@@ -201,11 +201,11 @@ template<typename _MatrixType> class HessenbergDecomposition
       *  - the upper part and lower sub-diagonal represent the Hessenberg matrix H
       *  - the rest of the lower part contains the Householder vectors that, combined with
       *    Householder coefficients returned by householderCoefficients(),
-      *    allows to reconstruct the matrix Q as 
+      *    allows to reconstruct the matrix Q as
       *       \f$ Q = H_{N-1} \ldots H_1 H_0 \f$.
-      *    Here, the matrices \f$ H_i \f$ are the Householder transformations 
+      *    Here, the matrices \f$ H_i \f$ are the Householder transformations
       *       \f$ H_i = (I - h_i v_i v_i^T) \f$
-      *    where \f$ h_i \f$ is the \f$ i \f$th Householder coefficient and 
+      *    where \f$ h_i \f$ is the \f$ i \f$th Householder coefficient and
       *    \f$ v_i \f$ is the Householder vector defined by
       *       \f$ v_i = [ 0, \ldots, 0, 1, M(i+2,i), \ldots, M(N-1,i) ]^T \f$
       *    with M the matrix returned by this function.
@@ -217,13 +217,13 @@ template<typename _MatrixType> class HessenbergDecomposition
       *
       * \sa householderCoefficients()
       */
-    const MatrixType& packedMatrix() const 
-    { 
+    const MatrixType& packedMatrix() const
+    {
       ei_assert(m_isInitialized && "HessenbergDecomposition is not initialized.");
-      return m_matrix; 
+      return m_matrix;
     }
 
-    /** \brief Reconstructs the orthogonal matrix Q in the decomposition 
+    /** \brief Reconstructs the orthogonal matrix Q in the decomposition
       *
       * \returns object representing the matrix Q
       *
@@ -274,7 +274,7 @@ template<typename _MatrixType> class HessenbergDecomposition
     typedef Matrix<Scalar, 1, Size, Options | RowMajor, 1, MaxSize> VectorType;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     static void _compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp);
-    
+
   protected:
     MatrixType m_matrix;
     CoeffVectorType m_hCoeffs;
@@ -282,8 +282,6 @@ template<typename _MatrixType> class HessenbergDecomposition
     bool m_isInitialized;
 };
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 /** \internal
   * Performs a tridiagonal decomposition of \a matA in place.
   *
@@ -325,8 +323,6 @@ void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVector
   }
 }
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   * \nonstableyet
   *
diff --git a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index 6a7d46b39..04402f844 100644
--- a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -43,7 +43,7 @@
   * A matrix \f$ A \f$ is selfadjoint if it equals its adjoint. For real
   * matrices, this means that the matrix is symmetric: it equals its
   * transpose. This class computes the eigenvalues and eigenvectors of a
-  * selfadjoint matrix. These are the scalars \f$ \lambda \f$ and vectors 
+  * selfadjoint matrix. These are the scalars \f$ \lambda \f$ and vectors
   * \f$ v \f$ such that \f$ Av = \lambda v \f$.  The eigenvalues of a
   * selfadjoint matrix are always real. If \f$ D \f$ is a diagonal matrix with
   * the eigenvalues on the diagonal, and \f$ V \f$ is a matrix with the
@@ -68,7 +68,7 @@
   *
   * The documentation for SelfAdjointEigenSolver(const MatrixType&, bool)
   * contains an example of the typical use of this class.
-  *  
+  *
   * \sa MatrixBase::eigenvalues(), class EigenSolver, class ComplexEigenSolver
   */
 template<typename _MatrixType> class SelfAdjointEigenSolver
@@ -87,15 +87,15 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::Index Index;
 
-    /** \brief Real scalar type for \p _MatrixType. 
+    /** \brief Real scalar type for \p _MatrixType.
       *
-      * This is just \c Scalar if #Scalar is real (e.g., \c float or 
+      * This is just \c Scalar if #Scalar is real (e.g., \c float or
       * \c double), and the type of the real part of \c Scalar if #Scalar is
       * complex.
       */
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
-    /** \brief Type for vector of eigenvalues as returned by eigenvalues(). 
+    /** \brief Type for vector of eigenvalues as returned by eigenvalues().
       *
       * This is a column vector with entries of type #RealScalar.
       * The length of the vector is the size of \p _MatrixType.
@@ -130,7 +130,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * This constructor is useful for dynamic-size matrices, when the user
       * intends to perform decompositions via compute(const MatrixType&, bool)
       * or compute(const MatrixType&, const MatrixType&, bool). The \p size
-      * parameter is only used as a hint. It is not an error to give a wrong 
+      * parameter is only used as a hint. It is not an error to give a wrong
       * \p size, but it may impair performance.
       *
       * \sa compute(const MatrixType&, bool) for an example
@@ -143,13 +143,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
           m_isInitialized(false)
     {}
 
-    /** \brief Constructor; computes eigendecomposition of given matrix. 
-      * 
+    /** \brief Constructor; computes eigendecomposition of given matrix.
+      *
       * \param[in]  matrix  Selfadjoint matrix whose eigendecomposition is to
-      *    be computed. 
+      *    be computed.
       * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
       *    eigenvalues are computed; if false, only the eigenvalues are
-      *    computed. 
+      *    computed.
       *
       * This constructor calls compute(const MatrixType&, bool) to compute the
       * eigenvalues of the matrix \p matrix. The eigenvectors are computed if
@@ -158,7 +158,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.out
       *
-      * \sa compute(const MatrixType&, bool), 
+      * \sa compute(const MatrixType&, bool),
       *     SelfAdjointEigenSolver(const MatrixType&, const MatrixType&, bool)
       */
     SelfAdjointEigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
@@ -172,14 +172,14 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     }
 
     /** \brief Constructor; computes eigendecomposition of given matrix pencil.
-      * 
+      *
       * \param[in]  matA  Selfadjoint matrix in matrix pencil.
       * \param[in]  matB  Positive-definite matrix in matrix pencil.
       * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
       *    eigenvalues are computed; if false, only the eigenvalues are
-      *    computed. 
+      *    computed.
       *
-      * This constructor calls compute(const MatrixType&, const MatrixType&, bool) 
+      * This constructor calls compute(const MatrixType&, const MatrixType&, bool)
       * to compute the eigenvalues and (if requested) the eigenvectors of the
       * generalized eigenproblem \f$ Ax = \lambda B x \f$ with \a matA the
       * selfadjoint matrix \f$ A \f$ and \a matB the positive definite matrix
@@ -189,7 +189,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.out
       *
-      * \sa compute(const MatrixType&, const MatrixType&, bool), 
+      * \sa compute(const MatrixType&, const MatrixType&, bool),
       *     SelfAdjointEigenSolver(const MatrixType&, bool)
       */
     SelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true)
@@ -202,13 +202,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       compute(matA, matB, computeEigenvectors);
     }
 
-    /** \brief Computes eigendecomposition of given matrix. 
-      * 
+    /** \brief Computes eigendecomposition of given matrix.
+      *
       * \param[in]  matrix  Selfadjoint matrix whose eigendecomposition is to
-      *    be computed. 
+      *    be computed.
       * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
       *    eigenvalues are computed; if false, only the eigenvalues are
-      *    computed. 
+      *    computed.
       * \returns    Reference to \c *this
       *
       * This function computes the eigenvalues of \p matrix.  The eigenvalues()
@@ -236,13 +236,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       */
     SelfAdjointEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
 
-    /** \brief Computes eigendecomposition of given matrix pencil. 
-      * 
+    /** \brief Computes eigendecomposition of given matrix pencil.
+      *
       * \param[in]  matA  Selfadjoint matrix in matrix pencil.
       * \param[in]  matB  Positive-definite matrix in matrix pencil.
       * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
       *    eigenvalues are computed; if false, only the eigenvalues are
-      *    computed. 
+      *    computed.
       * \returns    Reference to \c *this
       *
       * This function computes eigenvalues and (if requested) the eigenvectors
@@ -253,11 +253,11 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * eigenvectors are also computed and can be retrieved by calling
       * eigenvectors().
       *
-      * The implementation uses LLT to compute the Cholesky decomposition 
+      * The implementation uses LLT to compute the Cholesky decomposition
       * \f$ B = LL^* \f$ and calls compute(const MatrixType&, bool) to compute
       * the eigendecomposition \f$ L^{-1} A (L^*)^{-1} \f$. This solves the
       * generalized eigenproblem, because any solution of the generalized
-      * eigenproblem \f$ Ax = \lambda B x \f$ corresponds to a solution 
+      * eigenproblem \f$ Ax = \lambda B x \f$ corresponds to a solution
       * \f$ L^{-1} A (L^*)^{-1} (L^* x) = \lambda (L^* x) \f$ of the
       * eigenproblem for \f$ L^{-1} A (L^*)^{-1} \f$.
       *
@@ -268,7 +268,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       */
     SelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true);
 
-    /** \brief Returns the eigenvectors of given matrix (pencil). 
+    /** \brief Returns the eigenvectors of given matrix (pencil).
       *
       * \returns  A const reference to the matrix whose columns are the eigenvectors.
       *
@@ -293,7 +293,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       return m_eivec;
     }
 
-    /** \brief Returns the eigenvalues of given matrix (pencil). 
+    /** \brief Returns the eigenvalues of given matrix (pencil).
       *
       * \returns A const reference to the column vector containing the eigenvalues.
       *
@@ -307,13 +307,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       *
       * \sa eigenvectors(), MatrixBase::eigenvalues()
       */
-    const RealVectorType& eigenvalues() const 
-    { 
+    const RealVectorType& eigenvalues() const
+    {
       ei_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
-      return m_eivalues; 
+      return m_eivalues;
     }
 
-    /** \brief Computes the positive-definite square root of the matrix. 
+    /** \brief Computes the positive-definite square root of the matrix.
       *
       * \returns the positive-definite square root of the matrix
       *
@@ -328,7 +328,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * Example: \include SelfAdjointEigenSolver_operatorSqrt.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_operatorSqrt.out
       *
-      * \sa operatorInverseSqrt(), 
+      * \sa operatorInverseSqrt(),
       *     \ref MatrixFunctions_Module "MatrixFunctions Module"
       */
     MatrixType operatorSqrt() const
@@ -338,7 +338,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       return m_eivec * m_eivalues.cwiseSqrt().asDiagonal() * m_eivec.adjoint();
     }
 
-    /** \brief Computes the inverse square root of the matrix. 
+    /** \brief Computes the inverse square root of the matrix.
       *
       * \returns the inverse positive-definite square root of the matrix
       *
@@ -375,7 +375,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
 
     /** \brief Maximum number of iterations.
       *
-      * Maximum number of iterations allowed for an eigenvalue to converge. 
+      * Maximum number of iterations allowed for an eigenvalue to converge.
       */
     static const int m_maxIterations = 30;
 
@@ -389,8 +389,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     bool m_eigenvectorsOk;
 };
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 /** \internal
   *
   * \eigenvalues_module \ingroup Eigenvalues_Module
@@ -467,7 +465,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>::compute(
     ei_tridiagonal_qr_step(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
   }
 
-  if (iter <= m_maxIterations) 
+  if (iter <= m_maxIterations)
     m_info = Success;
   else
     m_info = NoConvergence;
@@ -531,9 +529,6 @@ compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors
   return *this;
 }
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
-#ifndef EIGEN_EXTERN_INSTANTIATIONS
 template<typename RealScalar, typename Scalar, typename Index>
 static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
@@ -575,6 +570,5 @@ static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index
     }
   }
 }
-#endif
 
 #endif // EIGEN_SELFADJOINTEIGENSOLVER_H
diff --git a/Eigen/src/Eigenvalues/Tridiagonalization.h b/Eigen/src/Eigenvalues/Tridiagonalization.h
index acf21e2da..62a607176 100644
--- a/Eigen/src/Eigenvalues/Tridiagonalization.h
+++ b/Eigen/src/Eigenvalues/Tridiagonalization.h
@@ -80,7 +80,7 @@ template<typename _MatrixType> class Tridiagonalization
     typedef Matrix<Scalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> CoeffVectorType;
     typedef typename ei_plain_col_type<MatrixType, RealScalar>::type DiagonalType;
     typedef Matrix<RealScalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> SubDiagonalType;
-    
+
     typedef typename ei_meta_if<NumTraits<Scalar>::IsComplex,
               typename Diagonal<MatrixType,0>::RealReturnType,
               Diagonal<MatrixType,0>
@@ -109,13 +109,13 @@ template<typename _MatrixType> class Tridiagonalization
       * \sa compute() for an example.
       */
     Tridiagonalization(Index size = Size==Dynamic ? 2 : Size)
-      : m_matrix(size,size), 
+      : m_matrix(size,size),
         m_hCoeffs(size > 1 ? size-1 : 1),
         m_isInitialized(false)
     {}
 
-    /** \brief Constructor; computes tridiagonal decomposition of given matrix. 
-      * 
+    /** \brief Constructor; computes tridiagonal decomposition of given matrix.
+      *
       * \param[in]  matrix  Selfadjoint matrix whose tridiagonal decomposition
       * is to be computed.
       *
@@ -125,7 +125,7 @@ template<typename _MatrixType> class Tridiagonalization
       * Output: \verbinclude Tridiagonalization_Tridiagonalization_MatrixType.out
       */
     Tridiagonalization(const MatrixType& matrix)
-      : m_matrix(matrix), 
+      : m_matrix(matrix),
         m_hCoeffs(matrix.cols() > 1 ? matrix.cols()-1 : 1),
         m_isInitialized(false)
     {
@@ -133,8 +133,8 @@ template<typename _MatrixType> class Tridiagonalization
       m_isInitialized = true;
     }
 
-    /** \brief Computes tridiagonal decomposition of given matrix. 
-      * 
+    /** \brief Computes tridiagonal decomposition of given matrix.
+      *
       * \param[in]  matrix  Selfadjoint matrix whose tridiagonal decomposition
       * is to be computed.
       * \returns    Reference to \c *this
@@ -167,7 +167,7 @@ template<typename _MatrixType> class Tridiagonalization
       * the member function compute(const MatrixType&) has been called before
       * to compute the tridiagonal decomposition of a matrix.
       *
-      * The Householder coefficients allow the reconstruction of the matrix 
+      * The Householder coefficients allow the reconstruction of the matrix
       * \f$ Q \f$ in the tridiagonal decomposition from the packed data.
       *
       * Example: \include Tridiagonalization_householderCoefficients.cpp
@@ -175,13 +175,13 @@ template<typename _MatrixType> class Tridiagonalization
       *
       * \sa packedMatrix(), \ref Householder_Module "Householder module"
       */
-    inline CoeffVectorType householderCoefficients() const 
-    { 
+    inline CoeffVectorType householderCoefficients() const
+    {
       ei_assert(m_isInitialized && "Tridiagonalization is not initialized.");
-      return m_hCoeffs; 
+      return m_hCoeffs;
     }
 
-    /** \brief Returns the internal representation of the decomposition 
+    /** \brief Returns the internal representation of the decomposition
       *
       *	\returns a const reference to a matrix with the internal representation
       *	         of the decomposition.
@@ -193,14 +193,14 @@ template<typename _MatrixType> class Tridiagonalization
       * The returned matrix contains the following information:
       *  - the strict upper triangular part is equal to the input matrix A.
       *  - the diagonal and lower sub-diagonal represent the real tridiagonal
-      *    symmetric matrix T. 
+      *    symmetric matrix T.
       *  - the rest of the lower part contains the Householder vectors that,
       *    combined with Householder coefficients returned by
       *    householderCoefficients(), allows to reconstruct the matrix Q as
       *       \f$ Q = H_{N-1} \ldots H_1 H_0 \f$.
-      *    Here, the matrices \f$ H_i \f$ are the Householder transformations 
+      *    Here, the matrices \f$ H_i \f$ are the Householder transformations
       *       \f$ H_i = (I - h_i v_i v_i^T) \f$
-      *    where \f$ h_i \f$ is the \f$ i \f$th Householder coefficient and 
+      *    where \f$ h_i \f$ is the \f$ i \f$th Householder coefficient and
       *    \f$ v_i \f$ is the Householder vector defined by
       *       \f$ v_i = [ 0, \ldots, 0, 1, M(i+2,i), \ldots, M(N-1,i) ]^T \f$
       *    with M the matrix returned by this function.
@@ -212,13 +212,13 @@ template<typename _MatrixType> class Tridiagonalization
       *
       * \sa householderCoefficients()
       */
-    inline const MatrixType& packedMatrix() const 
-    { 
+    inline const MatrixType& packedMatrix() const
+    {
       ei_assert(m_isInitialized && "Tridiagonalization is not initialized.");
-      return m_matrix; 
+      return m_matrix;
     }
 
-    /** \brief Returns the unitary matrix Q in the decomposition 
+    /** \brief Returns the unitary matrix Q in the decomposition
       *
       * \returns object representing the matrix Q
       *
@@ -285,7 +285,7 @@ template<typename _MatrixType> class Tridiagonalization
       */
     const SubDiagonalReturnType subDiagonal() const;
 
-    /** \brief Performs a full decomposition in place 
+    /** \brief Performs a full decomposition in place
       *
       * \param[in,out]  mat  On input, the selfadjoint matrix whose tridiagonal
       *    decomposition is to be computed. On output, the orthogonal matrix Q
@@ -293,7 +293,7 @@ template<typename _MatrixType> class Tridiagonalization
       * \param[out]  diag  The diagonal of the tridiagonal matrix T in the
       *    decomposition.
       * \param[out]  subdiag  The subdiagonal of the tridiagonal matrix T in
-      *    the decomposition. 
+      *    the decomposition.
       * \param[in]  extractQ  If true, the orthogonal matrix Q in the
       *    decomposition is computed and stored in \p mat.
       *
@@ -311,10 +311,10 @@ template<typename _MatrixType> class Tridiagonalization
       *
       * \note Notwithstanding the name, the current implementation copies
       * \p mat to a temporary matrix and uses that matrix to compute the
-      * decomposition. 
+      * decomposition.
       *
       * Example (this uses the same matrix as the example in
-      *    Tridiagonalization(const MatrixType&)): 
+      *    Tridiagonalization(const MatrixType&)):
       *    \include Tridiagonalization_decomposeInPlace.cpp
       * Output: \verbinclude Tridiagonalization_decomposeInPlace.out
       *
@@ -367,8 +367,6 @@ Tridiagonalization<MatrixType>::matrixT() const
   return matT;
 }
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 /** \internal
   * Performs a tridiagonal decomposition of \a matA in place.
   *
@@ -473,6 +471,4 @@ void Tridiagonalization<MatrixType>::_decomposeInPlace3x3(MatrixType& mat, Diago
   }
 }
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
 #endif // EIGEN_TRIDIAGONALIZATION_H
diff --git a/Eigen/src/QR/ColPivHouseholderQR.h b/Eigen/src/QR/ColPivHouseholderQR.h
index e0eaf32a9..6914d6873 100644
--- a/Eigen/src/QR/ColPivHouseholderQR.h
+++ b/Eigen/src/QR/ColPivHouseholderQR.h
@@ -347,8 +347,6 @@ template<typename _MatrixType> class ColPivHouseholderQR
     Index m_det_pq;
 };
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 template<typename MatrixType>
 typename MatrixType::RealScalar ColPivHouseholderQR<MatrixType>::absDeterminant() const
 {
@@ -513,8 +511,6 @@ typename ColPivHouseholderQR<MatrixType>::HouseholderSequenceType ColPivHousehol
   return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate(), false, m_nonzero_pivots, 0);
 }
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
 /** \return the column-pivoting Householder QR decomposition of \c *this.
   *
   * \sa class ColPivHouseholderQR
diff --git a/Eigen/src/QR/FullPivHouseholderQR.h b/Eigen/src/QR/FullPivHouseholderQR.h
index 3b4d02d67..cfb0b30a9 100644
--- a/Eigen/src/QR/FullPivHouseholderQR.h
+++ b/Eigen/src/QR/FullPivHouseholderQR.h
@@ -271,8 +271,6 @@ template<typename _MatrixType> class FullPivHouseholderQR
     Index m_det_pq;
 };
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 template<typename MatrixType>
 typename MatrixType::RealScalar FullPivHouseholderQR<MatrixType>::absDeterminant() const
 {
@@ -437,8 +435,6 @@ typename FullPivHouseholderQR<MatrixType>::MatrixQType FullPivHouseholderQR<Matr
   return res;
 }
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
 /** \return the full-pivoting Householder QR decomposition of \c *this.
   *
   * \sa class FullPivHouseholderQR
diff --git a/Eigen/src/QR/HouseholderQR.h b/Eigen/src/QR/HouseholderQR.h
index a8caaccea..0eea47676 100644
--- a/Eigen/src/QR/HouseholderQR.h
+++ b/Eigen/src/QR/HouseholderQR.h
@@ -177,8 +177,6 @@ template<typename _MatrixType> class HouseholderQR
     bool m_isInitialized;
 };
 
-#ifndef EIGEN_HIDE_HEAVY_CODE
-
 template<typename MatrixType>
 typename MatrixType::RealScalar HouseholderQR<MatrixType>::absDeterminant() const
 {
@@ -254,8 +252,6 @@ struct ei_solve_retval<HouseholderQR<_MatrixType>, Rhs>
   }
 };
 
-#endif // EIGEN_HIDE_HEAVY_CODE
-
 /** \return the Householder QR decomposition of \c *this.
   *
   * \sa class HouseholderQR