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diff --git a/eigen/bench/eig33.cpp b/eigen/bench/eig33.cpp
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-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// The computeRoots function included in this is based on materials
-// covered by the following copyright and license:
-// 
-// Geometric Tools, LLC
-// Copyright (c) 1998-2010
-// Distributed under the Boost Software License, Version 1.0.
-// 
-// Permission is hereby granted, free of charge, to any person or organization
-// obtaining a copy of the software and accompanying documentation covered by
-// this license (the "Software") to use, reproduce, display, distribute,
-// execute, and transmit the Software, and to prepare derivative works of the
-// Software, and to permit third-parties to whom the Software is furnished to
-// do so, all subject to the following:
-// 
-// The copyright notices in the Software and this entire statement, including
-// the above license grant, this restriction and the following disclaimer,
-// must be included in all copies of the Software, in whole or in part, and
-// all derivative works of the Software, unless such copies or derivative
-// works are solely in the form of machine-executable object code generated by
-// a source language processor.
-// 
-// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-// FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
-// SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
-// FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
-// ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-// DEALINGS IN THE SOFTWARE.
-
-#include <iostream>
-#include <Eigen/Core>
-#include <Eigen/Eigenvalues>
-#include <Eigen/Geometry>
-#include <bench/BenchTimer.h>
-
-using namespace Eigen;
-using namespace std;
-
-template<typename Matrix, typename Roots>
-inline void computeRoots(const Matrix& m, Roots& roots)
-{
-  typedef typename Matrix::Scalar Scalar;
-  const Scalar s_inv3 = 1.0/3.0;
-  const Scalar s_sqrt3 = std::sqrt(Scalar(3.0));
-
-  // The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0.  The
-  // eigenvalues are the roots to this equation, all guaranteed to be
-  // real-valued, because the matrix is symmetric.
-  Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(0,1)*m(0,2)*m(1,2) - m(0,0)*m(1,2)*m(1,2) - m(1,1)*m(0,2)*m(0,2) - m(2,2)*m(0,1)*m(0,1);
-  Scalar c1 = m(0,0)*m(1,1) - m(0,1)*m(0,1) + m(0,0)*m(2,2) - m(0,2)*m(0,2) + m(1,1)*m(2,2) - m(1,2)*m(1,2);
-  Scalar c2 = m(0,0) + m(1,1) + m(2,2);
-
-  // Construct the parameters used in classifying the roots of the equation
-  // and in solving the equation for the roots in closed form.
-  Scalar c2_over_3 = c2*s_inv3;
-  Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
-  if (a_over_3 > Scalar(0))
-    a_over_3 = Scalar(0);
-
-  Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
-
-  Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
-  if (q > Scalar(0))
-    q = Scalar(0);
-
-  // Compute the eigenvalues by solving for the roots of the polynomial.
-  Scalar rho = std::sqrt(-a_over_3);
-  Scalar theta = std::atan2(std::sqrt(-q),half_b)*s_inv3;
-  Scalar cos_theta = std::cos(theta);
-  Scalar sin_theta = std::sin(theta);
-  roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
-  roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
-  roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
-}
-
-template<typename Matrix, typename Vector>
-void eigen33(const Matrix& mat, Matrix& evecs, Vector& evals)
-{
-  typedef typename Matrix::Scalar Scalar;
-  // Scale the matrix so its entries are in [-1,1].  The scaling is applied
-  // only when at least one matrix entry has magnitude larger than 1.
-
-  Scalar shift = mat.trace()/3;
-  Matrix scaledMat = mat;
-  scaledMat.diagonal().array() -= shift;
-  Scalar scale = scaledMat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
-  scale = std::max(scale,Scalar(1));
-  scaledMat/=scale;
-
-  // Compute the eigenvalues
-//   scaledMat.setZero();
-  computeRoots(scaledMat,evals);
-
-  // compute the eigen vectors
-  // **here we assume 3 differents eigenvalues**
-
-  // "optimized version" which appears to be slower with gcc!
-//     Vector base;
-//     Scalar alpha, beta;
-//     base <<   scaledMat(1,0) * scaledMat(2,1),
-//               scaledMat(1,0) * scaledMat(2,0),
-//              -scaledMat(1,0) * scaledMat(1,0);
-//     for(int k=0; k<2; ++k)
-//     {
-//       alpha = scaledMat(0,0) - evals(k);
-//       beta  = scaledMat(1,1) - evals(k);
-//       evecs.col(k) = (base + Vector(-beta*scaledMat(2,0), -alpha*scaledMat(2,1), alpha*beta)).normalized();
-//     }
-//     evecs.col(2) = evecs.col(0).cross(evecs.col(1)).normalized();
-
-//   // naive version
-//   Matrix tmp;
-//   tmp = scaledMat;
-//   tmp.diagonal().array() -= evals(0);
-//   evecs.col(0) = tmp.row(0).cross(tmp.row(1)).normalized();
-// 
-//   tmp = scaledMat;
-//   tmp.diagonal().array() -= evals(1);
-//   evecs.col(1) = tmp.row(0).cross(tmp.row(1)).normalized();
-// 
-//   tmp = scaledMat;
-//   tmp.diagonal().array() -= evals(2);
-//   evecs.col(2) = tmp.row(0).cross(tmp.row(1)).normalized();
-  
-  // a more stable version:
-  if((evals(2)-evals(0))<=Eigen::NumTraits<Scalar>::epsilon())
-  {
-    evecs.setIdentity();
-  }
-  else
-  {
-    Matrix tmp;
-    tmp = scaledMat;
-    tmp.diagonal ().array () -= evals (2);
-    evecs.col (2) = tmp.row (0).cross (tmp.row (1)).normalized ();
-    
-    tmp = scaledMat;
-    tmp.diagonal ().array () -= evals (1);
-    evecs.col(1) = tmp.row (0).cross(tmp.row (1));
-    Scalar n1 = evecs.col(1).norm();
-    if(n1<=Eigen::NumTraits<Scalar>::epsilon())
-      evecs.col(1) = evecs.col(2).unitOrthogonal();
-    else
-      evecs.col(1) /= n1;
-    
-    // make sure that evecs[1] is orthogonal to evecs[2]
-    evecs.col(1) = evecs.col(2).cross(evecs.col(1).cross(evecs.col(2))).normalized();
-    evecs.col(0) = evecs.col(2).cross(evecs.col(1));
-  }
-  
-  // Rescale back to the original size.
-  evals *= scale;
-  evals.array()+=shift;
-}
-
-int main()
-{
-  BenchTimer t;
-  int tries = 10;
-  int rep = 400000;
-  typedef Matrix3d Mat;
-  typedef Vector3d Vec;
-  Mat A = Mat::Random(3,3);
-  A = A.adjoint() * A;
-//   Mat Q = A.householderQr().householderQ();
-//   A = Q * Vec(2.2424567,2.2424566,7.454353).asDiagonal() * Q.transpose();
-
-  SelfAdjointEigenSolver<Mat> eig(A);
-  BENCH(t, tries, rep, eig.compute(A));
-  std::cout << "Eigen iterative:  " << t.best() << "s\n";
-  
-  BENCH(t, tries, rep, eig.computeDirect(A));
-  std::cout << "Eigen direct   :  " << t.best() << "s\n";
-
-  Mat evecs;
-  Vec evals;
-  BENCH(t, tries, rep, eigen33(A,evecs,evals));
-  std::cout << "Direct: " << t.best() << "s\n\n";
-
-//   std::cerr << "Eigenvalue/eigenvector diffs:\n";
-//   std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
-//   for(int k=0;k<3;++k)
-//     if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
-//       evecs.col(k) = -evecs.col(k);
-//   std::cerr << evecs - eig.eigenvectors() << "\n\n";
-}