1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_JACOBI_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_JACOBI_H
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup Jacobi_Module
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \jacobi_module
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \class JacobiRotation
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Rotation given by a cosine-sine pair.
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This class represents a Jacobi or Givens rotation.
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This is a 2D rotation in the plane \c J of angle \f$ \theta \f$ defined by
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * its cosine \c c and sine \c s as follow:
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ J = \left ( \begin{array}{cc} c & \overline s \\ -s  & \overline c \end{array} \right ) \f$
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * You can apply the respective counter-clockwise rotation to a column vector \c v by
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * applying its adjoint on the left: \f$ v = J^* v \f$ that translates to the following Eigen code:
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \code
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * v.applyOnTheLeft(J.adjoint());
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \endcode
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> class JacobiRotation
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename NumTraits<Scalar>::Real RealScalar;
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Default constructor without any initialization. */
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    JacobiRotation() {}
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Construct a planar rotation from a cosine-sine pair (\a c, \c s). */
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    JacobiRotation(const Scalar& c, const Scalar& s) : m_c(c), m_s(s) {}
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar& c() { return m_c; }
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar c() const { return m_c; }
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar& s() { return m_s; }
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar s() const { return m_s; }
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Concatenates two planar rotation */
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    JacobiRotation operator*(const JacobiRotation& other)
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      using numext::conj;
547faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      return JacobiRotation(m_c * other.m_c - conj(m_s) * other.m_s,
557faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez                            conj(m_c * conj(other.m_s) + conj(m_s) * conj(other.m_c)));
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Returns the transposed transformation */
597faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    JacobiRotation transpose() const { using numext::conj; return JacobiRotation(m_c, -conj(m_s)); }
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Returns the adjoint transformation */
627faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    JacobiRotation adjoint() const { using numext::conj; return JacobiRotation(conj(m_c), -m_s); }
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename Derived>
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    bool makeJacobi(const MatrixBase<Derived>&, typename Derived::Index p, typename Derived::Index q);
667faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    bool makeJacobi(const RealScalar& x, const Scalar& y, const RealScalar& z);
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    void makeGivens(const Scalar& p, const Scalar& q, Scalar* z=0);
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    void makeGivens(const Scalar& p, const Scalar& q, Scalar* z, internal::true_type);
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    void makeGivens(const Scalar& p, const Scalar& q, Scalar* z, internal::false_type);
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar m_c, m_s;
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** Makes \c *this as a Jacobi rotation \a J such that applying \a J on both the right and left sides of the selfadjoint 2x2 matrix
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ B = \left ( \begin{array}{cc} x & y \\ \overline y & z \end{array} \right )\f$ yields a diagonal matrix \f$ A = J^* B J \f$
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa MatrixBase::makeJacobi(const MatrixBase<Derived>&, Index, Index), MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
837faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandezbool JacobiRotation<Scalar>::makeJacobi(const RealScalar& x, const Scalar& y, const RealScalar& z)
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
857faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::sqrt;
867faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real RealScalar;
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(y == Scalar(0))
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = Scalar(1);
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = Scalar(0);
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return false;
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
967faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    RealScalar tau = (x-z)/(RealScalar(2)*abs(y));
977faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    RealScalar w = sqrt(numext::abs2(tau) + RealScalar(1));
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RealScalar t;
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(tau>RealScalar(0))
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      t = RealScalar(1) / (tau + w);
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      t = RealScalar(1) / (tau - w);
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RealScalar sign_t = t > RealScalar(0) ? RealScalar(1) : RealScalar(-1);
1087faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    RealScalar n = RealScalar(1) / sqrt(numext::abs2(t)+RealScalar(1));
1097faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    m_s = - sign_t * (numext::conj(y) / abs(y)) * abs(t) * n;
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = n;
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return true;
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** Makes \c *this as a Jacobi rotation \c J such that applying \a J on both the right and left sides of the 2x2 selfadjoint matrix
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ B = \left ( \begin{array}{cc} \text{this}_{pp} & \text{this}_{pq} \\ (\text{this}_{pq})^* & \text{this}_{qq} \end{array} \right )\f$ yields
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * a diagonal matrix \f$ A = J^* B J \f$
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Example: \include Jacobi_makeJacobi.cpp
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Output: \verbinclude Jacobi_makeJacobi.out
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa JacobiRotation::makeJacobi(RealScalar, Scalar, RealScalar), MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline bool JacobiRotation<Scalar>::makeJacobi(const MatrixBase<Derived>& m, typename Derived::Index p, typename Derived::Index q)
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
1287faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  return makeJacobi(numext::real(m.coeff(p,p)), m.coeff(p,q), numext::real(m.coeff(q,q)));
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** Makes \c *this as a Givens rotation \c G such that applying \f$ G^* \f$ to the left of the vector
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ V = \left ( \begin{array}{c} p \\ q \end{array} \right )\f$ yields:
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ G^* V = \left ( \begin{array}{c} r \\ 0 \end{array} \right )\f$.
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * The value of \a z is returned if \a z is not null (the default is null).
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Also note that G is built such that the cosine is always real.
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Example: \include Jacobi_makeGivens.cpp
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Output: \verbinclude Jacobi_makeGivens.out
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This function implements the continuous Givens rotation generation algorithm
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * found in Anderson (2000), Discontinuous Plane Rotations and the Symmetric Eigenvalue Problem.
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * LAPACK Working Note 150, University of Tennessee, UT-CS-00-454, December 4, 2000.
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar* z)
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  makeGivens(p, q, z, typename internal::conditional<NumTraits<Scalar>::IsComplex, internal::true_type, internal::false_type>::type());
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// specialization for complexes
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar* r, internal::true_type)
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
1587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::sqrt;
1597faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
1607faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using numext::conj;
1617faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(q==Scalar(0))
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
1647faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    m_c = numext::real(p)<0 ? Scalar(-1) : Scalar(1);
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = 0;
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(r) *r = m_c * p;
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else if(p==Scalar(0))
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = 0;
1717faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    m_s = -q/abs(q);
1727faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    if(r) *r = abs(q);
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
1767faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    RealScalar p1 = numext::norm1(p);
1777faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    RealScalar q1 = numext::norm1(q);
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(p1>=q1)
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar ps = p / p1;
1817faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar p2 = numext::abs2(ps);
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar qs = q / p1;
1837faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar q2 = numext::abs2(qs);
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
1857faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar u = sqrt(RealScalar(1) + q2/p2);
1867faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      if(numext::real(p)<RealScalar(0))
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        u = -u;
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_c = Scalar(1)/u;
1907faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_s = -qs*conj(ps)*(m_c/p2);
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(r) *r = p * u;
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar ps = p / q1;
1967faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar p2 = numext::abs2(ps);
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar qs = q / q1;
1987faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar q2 = numext::abs2(qs);
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2007faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      RealScalar u = q1 * sqrt(p2 + q2);
2017faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      if(numext::real(p)<RealScalar(0))
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        u = -u;
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2047faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      p1 = abs(p);
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ps = p/p1;
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_c = p1/u;
2077faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_s = -conj(ps) * (q/u);
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(r) *r = ps * u;
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// specialization for reals
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar* r, internal::false_type)
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
2177faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::sqrt;
2187faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(q==Scalar(0))
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = p<Scalar(0) ? Scalar(-1) : Scalar(1);
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = Scalar(0);
2237faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    if(r) *r = abs(p);
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else if(p==Scalar(0))
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = Scalar(0);
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = q<Scalar(0) ? Scalar(1) : Scalar(-1);
2297faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    if(r) *r = abs(q);
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
2317faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  else if(abs(p) > abs(q))
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar t = q/p;
2347faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    Scalar u = sqrt(Scalar(1) + numext::abs2(t));
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(p<Scalar(0))
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      u = -u;
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = Scalar(1)/u;
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = -t * m_c;
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(r) *r = p * u;
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar t = p/q;
2447faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    Scalar u = sqrt(Scalar(1) + numext::abs2(t));
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(q<Scalar(0))
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      u = -u;
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_s = -Scalar(1)/u;
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_c = -t * m_s;
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(r) *r = q * u;
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/****************************************************************************************
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath*   Implementation of MatrixBase methods
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath****************************************************************************************/
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \jacobi_module
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Applies the clock wise 2D rotation \a j to the set of 2D vectors of cordinates \a x and \a y:
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \f$ \left ( \begin{array}{cc} x \\ y \end{array} \right )  =  J \left ( \begin{array}{cc} x \\ y \end{array} \right ) \f$
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename VectorX, typename VectorY, typename OtherScalar>
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const JacobiRotation<OtherScalar>& j);
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \jacobi_module
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Applies the rotation in the plane \a j to the rows \a p and \a q of \c *this, i.e., it computes B = J * B,
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * with \f$ B = \left ( \begin{array}{cc} \text{*this.row}(p) \\ \text{*this.row}(q) \end{array} \right ) \f$.
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class JacobiRotation, MatrixBase::applyOnTheRight(), internal::apply_rotation_in_the_plane()
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherScalar>
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void MatrixBase<Derived>::applyOnTheLeft(Index p, Index q, const JacobiRotation<OtherScalar>& j)
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  RowXpr x(this->row(p));
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  RowXpr y(this->row(q));
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::apply_rotation_in_the_plane(x, y, j);
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup Jacobi_Module
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Applies the rotation in the plane \a j to the columns \a p and \a q of \c *this, i.e., it computes B = B * J
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * with \f$ B = \left ( \begin{array}{cc} \text{*this.col}(p) & \text{*this.col}(q) \end{array} \right ) \f$.
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class JacobiRotation, MatrixBase::applyOnTheLeft(), internal::apply_rotation_in_the_plane()
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherScalar>
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void MatrixBase<Derived>::applyOnTheRight(Index p, Index q, const JacobiRotation<OtherScalar>& j)
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ColXpr x(this->col(p));
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ColXpr y(this->col(q));
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::apply_rotation_in_the_plane(x, y, j.transpose());
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename VectorX, typename VectorY, typename OtherScalar>
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const JacobiRotation<OtherScalar>& j)
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename VectorX::Index Index;
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename VectorX::Scalar Scalar;
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum { PacketSize = packet_traits<Scalar>::size };
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert(_x.size() == _y.size());
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index size = _x.size();
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index incrx = _x.innerStride();
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index incry = _y.innerStride();
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar* EIGEN_RESTRICT x = &_x.coeffRef(0);
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar* EIGEN_RESTRICT y = &_y.coeffRef(0);
3147faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
3157faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  OtherScalar c = j.c();
3167faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  OtherScalar s = j.s();
3177faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  if (c==OtherScalar(1) && s==OtherScalar(0))
3187faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    return;
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  /*** dynamic-size vectorized paths ***/
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(VectorX::SizeAtCompileTime == Dynamic &&
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    (VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ((incrx==1 && incry==1) || PacketSize == 1))
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // both vectors are sequentially stored in memory => vectorization
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Peeling = 2 };
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index alignedStart = internal::first_aligned(y, size);
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
3327faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    const Packet pc = pset1<Packet>(c);
3337faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    const Packet ps = pset1<Packet>(s);
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index i=0; i<alignedStart; ++i)
337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar xi = x[i];
339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar yi = y[i];
3407faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      x[i] =  c * xi + numext::conj(s) * yi;
3417faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      y[i] = -s * xi + numext::conj(c) * yi;
342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar* EIGEN_RESTRICT px = x + alignedStart;
345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar* EIGEN_RESTRICT py = y + alignedStart;
346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(internal::first_aligned(x, size)==alignedStart)
348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(Index i=alignedStart; i<alignedEnd; i+=PacketSize)
350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet xi = pload<Packet>(px);
352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet yi = pload<Packet>(py);
353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstore(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstore(py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        px += PacketSize;
356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        py += PacketSize;
357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index peelingEnd = alignedStart + ((size-alignedStart)/(Peeling*PacketSize))*(Peeling*PacketSize);
362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(Index i=alignedStart; i<peelingEnd; i+=Peeling*PacketSize)
363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet xi   = ploadu<Packet>(px);
365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet xi1  = ploadu<Packet>(px+PacketSize);
366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet yi   = pload <Packet>(py);
367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet yi1  = pload <Packet>(py+PacketSize);
368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstoreu(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstoreu(px+PacketSize, padd(pmul(pc,xi1),pcj.pmul(ps,yi1)));
370c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstore (py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
371c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstore (py+PacketSize, psub(pcj.pmul(pc,yi1),pmul(ps,xi1)));
372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        px += Peeling*PacketSize;
373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        py += Peeling*PacketSize;
374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(alignedEnd!=peelingEnd)
376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet xi = ploadu<Packet>(x+peelingEnd);
378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Packet yi = pload <Packet>(y+peelingEnd);
379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstoreu(x+peelingEnd, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        pstore (y+peelingEnd, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index i=alignedEnd; i<size; ++i)
385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar xi = x[i];
387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar yi = y[i];
3887faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      x[i] =  c * xi + numext::conj(s) * yi;
3897faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      y[i] = -s * xi + numext::conj(c) * yi;
390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
391c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
393c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  /*** fixed-size vectorized path ***/
394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else if(VectorX::SizeAtCompileTime != Dynamic &&
395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          (VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          (VectorX::Flags & VectorY::Flags & AlignedBit))
397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
3987faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    const Packet pc = pset1<Packet>(c);
3997faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    const Packet ps = pset1<Packet>(s);
400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar* EIGEN_RESTRICT px = x;
402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar* EIGEN_RESTRICT py = y;
403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index i=0; i<size; i+=PacketSize)
404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Packet xi = pload<Packet>(px);
406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Packet yi = pload<Packet>(py);
407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      pstore(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      pstore(py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      px += PacketSize;
410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      py += PacketSize;
411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  /*** non-vectorized path ***/
415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else
416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index i=0; i<size; ++i)
418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar xi = *x;
420c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar yi = *y;
4217faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      *x =  c * xi + numext::conj(s) * yi;
4227faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      *y = -s * xi + numext::conj(c) * yi;
423c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      x += incrx;
424c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      y += incry;
425c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
426c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
427c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
428c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
429c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
430c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
431c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
432c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
433c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_JACOBI_H
434