Rename the old LevenbergMarquardt class to LevenbergMarquardtLegacy

Split the levenberg marquardt test and the hybrid nonlinear test

1 files changed, 9 insertions, 1525 deletions

diff --git a/unsupported/test/NonLinearOptimization.cpp b/unsupported/test/NonLinearOptimization.cpp
index d7376b0f5..6b4e88a95 100644
--- a/unsupported/test/NonLinearOptimization.cpp
+++ b/unsupported/test/NonLinearOptimization.cpp
@@ -2,7 +2,10 @@
 // for linear algebra.
 //
 // Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
-
+//
+// 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/.
 #include <stdio.h>
 
 #include "main.h"
@@ -127,118 +130,6 @@ struct Functor
 //  void operator() (const InputType& x, ValueType* v, JacobianType* _j=0) const;
 };
 
-struct lmder_functor : Functor<double>
-{
-    lmder_functor(void): Functor<double>(3,15) {}
-    int operator()(const VectorXd &x, VectorXd &fvec) const
-    {
-        double tmp1, tmp2, tmp3;
-        static const double y[15] = {1.4e-1, 1.8e-1, 2.2e-1, 2.5e-1, 2.9e-1, 3.2e-1, 3.5e-1,
-            3.9e-1, 3.7e-1, 5.8e-1, 7.3e-1, 9.6e-1, 1.34, 2.1, 4.39};
-
-        for (int i = 0; i < values(); i++)
-        {
-            tmp1 = i+1;
-            tmp2 = 16 - i - 1;
-            tmp3 = (i>=8)? tmp2 : tmp1;
-            fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3));
-        }
-        return 0;
-    }
-
-    int df(const VectorXd &x, MatrixXd &fjac) const
-    {
-        double tmp1, tmp2, tmp3, tmp4;
-        for (int i = 0; i < values(); i++)
-        {
-            tmp1 = i+1;
-            tmp2 = 16 - i - 1;
-            tmp3 = (i>=8)? tmp2 : tmp1;
-            tmp4 = (x[1]*tmp2 + x[2]*tmp3); tmp4 = tmp4*tmp4;
-            fjac(i,0) = -1;
-            fjac(i,1) = tmp1*tmp2/tmp4;
-            fjac(i,2) = tmp1*tmp3/tmp4;
-        }
-        return 0;
-    }
-};
-
-void testLmder1()
-{
-  int n=3, info;
-
-  VectorXd x;
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmder_functor functor;
-  LevenbergMarquardt<lmder_functor> lm(functor);
-  info = lm.lmder1(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 6);
-  VERIFY_IS_EQUAL(lm.njev, 5);
-
-  // check norm
-  VERIFY_IS_APPROX(lm.fvec.blueNorm(), 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.08241058, 1.133037, 2.343695;
-  VERIFY_IS_APPROX(x, x_ref);
-}
-
-void testLmder()
-{
-  const int m=15, n=3;
-  int info;
-  double fnorm, covfac;
-  VectorXd x;
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmder_functor functor;
-  LevenbergMarquardt<lmder_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return values
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 6);
-  VERIFY_IS_EQUAL(lm.njev, 5);
-
-  // check norm
-  fnorm = lm.fvec.blueNorm();
-  VERIFY_IS_APPROX(fnorm, 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.08241058, 1.133037, 2.343695;
-  VERIFY_IS_APPROX(x, x_ref);
-
-  // check covariance
-  covfac = fnorm*fnorm/(m-n);
-  internal::covar(lm.fjac, lm.permutation.indices()); // TODO : move this as a function of lm
-
-  MatrixXd cov_ref(n,n);
-  cov_ref <<
-      0.0001531202,   0.002869941,  -0.002656662,
-      0.002869941,    0.09480935,   -0.09098995,
-      -0.002656662,   -0.09098995,    0.08778727;
-
-//  std::cout << fjac*covfac << std::endl;
-
-  MatrixXd cov;
-  cov =  covfac*lm.fjac.topLeftCorner<n,n>();
-  VERIFY_IS_APPROX( cov, cov_ref);
-  // TODO: why isn't this allowed ? :
-  // VERIFY_IS_APPROX( covfac*fjac.topLeftCorner<n,n>() , cov_ref);
-}
-
 struct hybrj_functor : Functor<double>
 {
     hybrj_functor(void) : Functor<double>(9,9) {}
@@ -427,1423 +318,16 @@ void testHybrd()
   VERIFY_IS_APPROX(x, x_ref);
 }
 
-struct lmstr_functor : Functor<double>
-{
-    lmstr_functor(void) : Functor<double>(3,15) {}
-    int operator()(const VectorXd &x, VectorXd &fvec)
-    {
-        /*  subroutine fcn for lmstr1 example. */
-        double tmp1, tmp2, tmp3;
-        static const double y[15]={1.4e-1, 1.8e-1, 2.2e-1, 2.5e-1, 2.9e-1, 3.2e-1, 3.5e-1,
-            3.9e-1, 3.7e-1, 5.8e-1, 7.3e-1, 9.6e-1, 1.34, 2.1, 4.39};
-
-        assert(15==fvec.size());
-        assert(3==x.size());
-
-        for (int i=0; i<15; i++)
-        {
-            tmp1 = i+1;
-            tmp2 = 16 - i - 1;
-            tmp3 = (i>=8)? tmp2 : tmp1;
-            fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3));
-        }
-        return 0;
-    }
-    int df(const VectorXd &x, VectorXd &jac_row, VectorXd::Index rownb)
-    {
-        assert(x.size()==3);
-        assert(jac_row.size()==x.size());
-        double tmp1, tmp2, tmp3, tmp4;
-
-        int i = rownb-2;
-        tmp1 = i+1;
-        tmp2 = 16 - i - 1;
-        tmp3 = (i>=8)? tmp2 : tmp1;
-        tmp4 = (x[1]*tmp2 + x[2]*tmp3); tmp4 = tmp4*tmp4;
-        jac_row[0] = -1;
-        jac_row[1] = tmp1*tmp2/tmp4;
-        jac_row[2] = tmp1*tmp3/tmp4;
-        return 0;
-    }
-};
-
-void testLmstr1()
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmstr_functor functor;
-  LevenbergMarquardt<lmstr_functor> lm(functor);
-  info = lm.lmstr1(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 6);
-  VERIFY_IS_EQUAL(lm.njev, 5);
-
-  // check norm
-  VERIFY_IS_APPROX(lm.fvec.blueNorm(), 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.08241058, 1.133037, 2.343695 ;
-  VERIFY_IS_APPROX(x, x_ref);
-}
-
-void testLmstr()
-{
-  const int n=3;
-  int info;
-  double fnorm;
-  VectorXd x(n);
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmstr_functor functor;
-  LevenbergMarquardt<lmstr_functor> lm(functor);
-  info = lm.minimizeOptimumStorage(x);
-
-  // check return values
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 6);
-  VERIFY_IS_EQUAL(lm.njev, 5);
-
-  // check norm
-  fnorm = lm.fvec.blueNorm();
-  VERIFY_IS_APPROX(fnorm, 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.08241058, 1.133037, 2.343695;
-  VERIFY_IS_APPROX(x, x_ref);
-
-}
-
-struct lmdif_functor : Functor<double>
-{
-    lmdif_functor(void) : Functor<double>(3,15) {}
-    int operator()(const VectorXd &x, VectorXd &fvec) const
-    {
-        int i;
-        double tmp1,tmp2,tmp3;
-        static const double y[15]={1.4e-1,1.8e-1,2.2e-1,2.5e-1,2.9e-1,3.2e-1,3.5e-1,3.9e-1,
-            3.7e-1,5.8e-1,7.3e-1,9.6e-1,1.34e0,2.1e0,4.39e0};
-
-        assert(x.size()==3);
-        assert(fvec.size()==15);
-        for (i=0; i<15; i++)
-        {
-            tmp1 = i+1;
-            tmp2 = 15 - i;
-            tmp3 = tmp1;
-
-            if (i >= 8) tmp3 = tmp2;
-            fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3));
-        }
-        return 0;
-    }
-};
-
-void testLmdif1()
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n), fvec(15);
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmdif_functor functor;
-  DenseIndex nfev;
-  info = LevenbergMarquardt<lmdif_functor>::lmdif1(functor, x, &nfev);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(nfev, 26);
-
-  // check norm
-  functor(x, fvec);
-  VERIFY_IS_APPROX(fvec.blueNorm(), 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.0824106, 1.1330366, 2.3436947;
-  VERIFY_IS_APPROX(x, x_ref);
-
-}
-
-void testLmdif()
-{
-  const int m=15, n=3;
-  int info;
-  double fnorm, covfac;
-  VectorXd x(n);
-
-  /* the following starting values provide a rough fit. */
-  x.setConstant(n, 1.);
-
-  // do the computation
-  lmdif_functor functor;
-  NumericalDiff<lmdif_functor> numDiff(functor);
-  LevenbergMarquardt<NumericalDiff<lmdif_functor> > lm(numDiff);
-  info = lm.minimize(x);
-
-  // check return values
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 26);
-
-  // check norm
-  fnorm = lm.fvec.blueNorm();
-  VERIFY_IS_APPROX(fnorm, 0.09063596);
-
-  // check x
-  VectorXd x_ref(n);
-  x_ref << 0.08241058, 1.133037, 2.343695;
-  VERIFY_IS_APPROX(x, x_ref);
-
-  // check covariance
-  covfac = fnorm*fnorm/(m-n);
-  internal::covar(lm.fjac, lm.permutation.indices()); // TODO : move this as a function of lm
-
-  MatrixXd cov_ref(n,n);
-  cov_ref <<
-      0.0001531202,   0.002869942,  -0.002656662,
-      0.002869942,    0.09480937,   -0.09098997,
-      -0.002656662,   -0.09098997,    0.08778729;
-
-//  std::cout << fjac*covfac << std::endl;
-
-  MatrixXd cov;
-  cov =  covfac*lm.fjac.topLeftCorner<n,n>();
-  VERIFY_IS_APPROX( cov, cov_ref);
-  // TODO: why isn't this allowed ? :
-  // VERIFY_IS_APPROX( covfac*fjac.topLeftCorner<n,n>() , cov_ref);
-}
-
-struct chwirut2_functor : Functor<double>
-{
-    chwirut2_functor(void) : Functor<double>(3,54) {}
-    static const double m_x[54];
-    static const double m_y[54];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        int i;
-
-        assert(b.size()==3);
-        assert(fvec.size()==54);
-        for(i=0; i<54; i++) {
-            double x = m_x[i];
-            fvec[i] = exp(-b[0]*x)/(b[1]+b[2]*x) - m_y[i];
-        }
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==3);
-        assert(fjac.rows()==54);
-        assert(fjac.cols()==3);
-        for(int i=0; i<54; i++) {
-            double x = m_x[i];
-            double factor = 1./(b[1]+b[2]*x);
-            double e = exp(-b[0]*x);
-            fjac(i,0) = -x*e*factor;
-            fjac(i,1) = -e*factor*factor;
-            fjac(i,2) = -x*e*factor*factor;
-        }
-        return 0;
-    }
-};
-const double chwirut2_functor::m_x[54] = { 0.500E0, 1.000E0, 1.750E0, 3.750E0, 5.750E0, 0.875E0, 2.250E0, 3.250E0, 5.250E0, 0.750E0, 1.750E0, 2.750E0, 4.750E0, 0.625E0, 1.250E0, 2.250E0, 4.250E0, .500E0, 3.000E0, .750E0, 3.000E0, 1.500E0, 6.000E0, 3.000E0, 6.000E0, 1.500E0, 3.000E0, .500E0, 2.000E0, 4.000E0, .750E0, 2.000E0, 5.000E0, .750E0, 2.250E0, 3.750E0, 5.750E0, 3.000E0, .750E0, 2.500E0, 4.000E0, .750E0, 2.500E0, 4.000E0, .750E0, 2.500E0, 4.000E0, .500E0, 6.000E0, 3.000E0, .500E0, 2.750E0, .500E0, 1.750E0};
-const double chwirut2_functor::m_y[54] = { 92.9000E0 ,57.1000E0 ,31.0500E0 ,11.5875E0 ,8.0250E0 ,63.6000E0 ,21.4000E0 ,14.2500E0 ,8.4750E0 ,63.8000E0 ,26.8000E0 ,16.4625E0 ,7.1250E0 ,67.3000E0 ,41.0000E0 ,21.1500E0 ,8.1750E0 ,81.5000E0 ,13.1200E0 ,59.9000E0 ,14.6200E0 ,32.9000E0 ,5.4400E0 ,12.5600E0 ,5.4400E0 ,32.0000E0 ,13.9500E0 ,75.8000E0 ,20.0000E0 ,10.4200E0 ,59.5000E0 ,21.6700E0 ,8.5500E0 ,62.0000E0 ,20.2000E0 ,7.7600E0 ,3.7500E0 ,11.8100E0 ,54.7000E0 ,23.7000E0 ,11.5500E0 ,61.3000E0 ,17.7000E0 ,8.7400E0 ,59.2000E0 ,16.3000E0 ,8.6200E0 ,81.0000E0 ,4.8700E0 ,14.6200E0 ,81.7000E0 ,17.1700E0 ,81.3000E0 ,28.9000E0  };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/chwirut2.shtml
-void testNistChwirut2(void)
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 0.1, 0.01, 0.02;
-  // do the computation
-  chwirut2_functor functor;
-  LevenbergMarquardt<chwirut2_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 10);
-  VERIFY_IS_EQUAL(lm.njev, 8);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.6657666537E-01);
-  VERIFY_IS_APPROX(x[1], 5.1653291286E-03);
-  VERIFY_IS_APPROX(x[2], 1.2150007096E-02);
-
-  /*
-   * Second try
-   */
-  x<< 0.15, 0.008, 0.010;
-  // do the computation
-  lm.resetParameters();
-  lm.parameters.ftol = 1.E6*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 7);
-  VERIFY_IS_EQUAL(lm.njev, 6);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.6657666537E-01);
-  VERIFY_IS_APPROX(x[1], 5.1653291286E-03);
-  VERIFY_IS_APPROX(x[2], 1.2150007096E-02);
-}
-
-
-struct misra1a_functor : Functor<double>
-{
-    misra1a_functor(void) : Functor<double>(2,14) {}
-    static const double m_x[14];
-    static const double m_y[14];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==2);
-        assert(fvec.size()==14);
-        for(int i=0; i<14; i++) {
-            fvec[i] = b[0]*(1.-exp(-b[1]*m_x[i])) - m_y[i] ;
-        }
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==2);
-        assert(fjac.rows()==14);
-        assert(fjac.cols()==2);
-        for(int i=0; i<14; i++) {
-            fjac(i,0) = (1.-exp(-b[1]*m_x[i]));
-            fjac(i,1) = (b[0]*m_x[i]*exp(-b[1]*m_x[i]));
-        }
-        return 0;
-    }
-};
-const double misra1a_functor::m_x[14] = { 77.6E0, 114.9E0, 141.1E0, 190.8E0, 239.9E0, 289.0E0, 332.8E0, 378.4E0, 434.8E0, 477.3E0, 536.8E0, 593.1E0, 689.1E0, 760.0E0};
-const double misra1a_functor::m_y[14] = { 10.07E0, 14.73E0, 17.94E0, 23.93E0, 29.61E0, 35.18E0, 40.02E0, 44.82E0, 50.76E0, 55.05E0, 61.01E0, 66.40E0, 75.47E0, 81.78E0};
-
-// http://www.itl.nist.gov/div898/strd/nls/data/misra1a.shtml
-void testNistMisra1a(void)
-{
-  const int n=2;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 500., 0.0001;
-  // do the computation
-  misra1a_functor functor;
-  LevenbergMarquardt<misra1a_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 19);
-  VERIFY_IS_EQUAL(lm.njev, 15);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01);
-  // check x
-  VERIFY_IS_APPROX(x[0], 2.3894212918E+02);
-  VERIFY_IS_APPROX(x[1], 5.5015643181E-04);
-
-  /*
-   * Second try
-   */
-  x<< 250., 0.0005;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 5);
-  VERIFY_IS_EQUAL(lm.njev, 4);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01);
-  // check x
-  VERIFY_IS_APPROX(x[0], 2.3894212918E+02);
-  VERIFY_IS_APPROX(x[1], 5.5015643181E-04);
-}
-
-struct hahn1_functor : Functor<double>
-{
-    hahn1_functor(void) : Functor<double>(7,236) {}
-    static const double m_x[236];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        static const double m_y[236] = { .591E0 , 1.547E0 , 2.902E0 , 2.894E0 , 4.703E0 , 6.307E0 , 7.03E0  , 7.898E0 , 9.470E0 , 9.484E0 , 10.072E0 , 10.163E0 , 11.615E0 , 12.005E0 , 12.478E0 , 12.982E0 , 12.970E0 , 13.926E0 , 14.452E0 , 14.404E0 , 15.190E0 , 15.550E0 , 15.528E0 , 15.499E0 , 16.131E0 , 16.438E0 , 16.387E0 , 16.549E0 , 16.872E0 , 16.830E0 , 16.926E0 , 16.907E0 , 16.966E0 , 17.060E0 , 17.122E0 , 17.311E0 , 17.355E0 , 17.668E0 , 17.767E0 , 17.803E0 , 17.765E0 , 17.768E0 , 17.736E0 , 17.858E0 , 17.877E0 , 17.912E0 , 18.046E0 , 18.085E0 , 18.291E0 , 18.357E0 , 18.426E0 , 18.584E0 , 18.610E0 , 18.870E0 , 18.795E0 , 19.111E0 , .367E0 , .796E0 , 0.892E0 , 1.903E0 , 2.150E0 , 3.697E0 , 5.870E0 , 6.421E0 , 7.422E0 , 9.944E0 , 11.023E0 , 11.87E0  , 12.786E0 , 14.067E0 , 13.974E0 , 14.462E0 , 14.464E0 , 15.381E0 , 15.483E0 , 15.59E0  , 16.075E0 , 16.347E0 , 16.181E0 , 16.915E0 , 17.003E0 , 16.978E0 , 17.756E0 , 17.808E0 , 17.868E0 , 18.481E0 , 18.486E0 , 19.090E0 , 16.062E0 , 16.337E0 , 16.345E0 ,
-        16.388E0 , 17.159E0 , 17.116E0 , 17.164E0 , 17.123E0 , 17.979E0 , 17.974E0 , 18.007E0 , 17.993E0 , 18.523E0 , 18.669E0 , 18.617E0 , 19.371E0 , 19.330E0 , 0.080E0 , 0.248E0 , 1.089E0 , 1.418E0 , 2.278E0 , 3.624E0 , 4.574E0 , 5.556E0 , 7.267E0 , 7.695E0 , 9.136E0 , 9.959E0 , 9.957E0 , 11.600E0 , 13.138E0 , 13.564E0 , 13.871E0 , 13.994E0 , 14.947E0 , 15.473E0 , 15.379E0 , 15.455E0 , 15.908E0 , 16.114E0 , 17.071E0 , 17.135E0 , 17.282E0 , 17.368E0 , 17.483E0 , 17.764E0 , 18.185E0 , 18.271E0 , 18.236E0 , 18.237E0 , 18.523E0 , 18.627E0 , 18.665E0 , 19.086E0 , 0.214E0 , 0.943E0 , 1.429E0 , 2.241E0 , 2.951E0 , 3.782E0 , 4.757E0 , 5.602E0 , 7.169E0 , 8.920E0 , 10.055E0 , 12.035E0 , 12.861E0 , 13.436E0 , 14.167E0 , 14.755E0 , 15.168E0 , 15.651E0 , 15.746E0 , 16.216E0 , 16.445E0 , 16.965E0 , 17.121E0 , 17.206E0 , 17.250E0 , 17.339E0 , 17.793E0 , 18.123E0 , 18.49E0  , 18.566E0 , 18.645E0 , 18.706E0 , 18.924E0 , 19.1E0   , 0.375E0 , 0.471E0 , 1.504E0 , 2.204E0 , 2.813E0 , 4.765E0 , 9.835E0 , 10.040E0 , 11.946E0 , 12.596E0 , 
-13.303E0 , 13.922E0 , 14.440E0 , 14.951E0 , 15.627E0 , 15.639E0 , 15.814E0 , 16.315E0 , 16.334E0 , 16.430E0 , 16.423E0 , 17.024E0 , 17.009E0 , 17.165E0 , 17.134E0 , 17.349E0 , 17.576E0 , 17.848E0 , 18.090E0 , 18.276E0 , 18.404E0 , 18.519E0 , 19.133E0 , 19.074E0 , 19.239E0 , 19.280E0 , 19.101E0 , 19.398E0 , 19.252E0 , 19.89E0  , 20.007E0 , 19.929E0 , 19.268E0 , 19.324E0 , 20.049E0 , 20.107E0 , 20.062E0 , 20.065E0 , 19.286E0 , 19.972E0 , 20.088E0 , 20.743E0 , 20.83E0  , 20.935E0 , 21.035E0 , 20.93E0  , 21.074E0 , 21.085E0 , 20.935E0 };
-
-        //        int called=0; printf("call hahn1_functor with  iflag=%d, called=%d\n", iflag, called); if (iflag==1) called++;
-
-        assert(b.size()==7);
-        assert(fvec.size()==236);
-        for(int i=0; i<236; i++) {
-            double x=m_x[i], xx=x*x, xxx=xx*x;
-            fvec[i] = (b[0]+b[1]*x+b[2]*xx+b[3]*xxx) / (1.+b[4]*x+b[5]*xx+b[6]*xxx) - m_y[i];
-        }
-        return 0;
-    }
-
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==7);
-        assert(fjac.rows()==236);
-        assert(fjac.cols()==7);
-        for(int i=0; i<236; i++) {
-            double x=m_x[i], xx=x*x, xxx=xx*x;
-            double fact = 1./(1.+b[4]*x+b[5]*xx+b[6]*xxx);
-            fjac(i,0) = 1.*fact;
-            fjac(i,1) = x*fact;
-            fjac(i,2) = xx*fact;
-            fjac(i,3) = xxx*fact;
-            fact = - (b[0]+b[1]*x+b[2]*xx+b[3]*xxx) * fact * fact;
-            fjac(i,4) = x*fact;
-            fjac(i,5) = xx*fact;
-            fjac(i,6) = xxx*fact;
-        }
-        return 0;
-    }
-};
-const double hahn1_functor::m_x[236] = { 24.41E0 , 34.82E0 , 44.09E0 , 45.07E0 , 54.98E0 , 65.51E0 , 70.53E0 , 75.70E0 , 89.57E0 , 91.14E0 , 96.40E0 , 97.19E0 , 114.26E0 , 120.25E0 , 127.08E0 , 133.55E0 , 133.61E0 , 158.67E0 , 172.74E0 , 171.31E0 , 202.14E0 , 220.55E0 , 221.05E0 , 221.39E0 , 250.99E0 , 268.99E0 , 271.80E0 , 271.97E0 , 321.31E0 , 321.69E0 , 330.14E0 , 333.03E0 , 333.47E0 , 340.77E0 , 345.65E0 , 373.11E0 , 373.79E0 , 411.82E0 , 419.51E0 , 421.59E0 , 422.02E0 , 422.47E0 , 422.61E0 , 441.75E0 , 447.41E0 , 448.7E0  , 472.89E0 , 476.69E0 , 522.47E0 , 522.62E0 , 524.43E0 , 546.75E0 , 549.53E0 , 575.29E0 , 576.00E0 , 625.55E0 , 20.15E0 , 28.78E0 , 29.57E0 , 37.41E0 , 39.12E0 , 50.24E0 , 61.38E0 , 66.25E0 , 73.42E0 , 95.52E0 , 107.32E0 , 122.04E0 , 134.03E0 , 163.19E0 , 163.48E0 , 175.70E0 , 179.86E0 , 211.27E0 , 217.78E0 , 219.14E0 , 262.52E0 , 268.01E0 , 268.62E0 , 336.25E0 , 337.23E0 , 339.33E0 , 427.38E0 , 428.58E0 , 432.68E0 , 528.99E0 , 531.08E0 , 628.34E0 , 253.24E0 , 273.13E0 , 273.66E0 ,
-282.10E0 , 346.62E0 , 347.19E0 , 348.78E0 , 351.18E0 , 450.10E0 , 450.35E0 , 451.92E0 , 455.56E0 , 552.22E0 , 553.56E0 , 555.74E0 , 652.59E0 , 656.20E0 , 14.13E0 , 20.41E0 , 31.30E0 , 33.84E0 , 39.70E0 , 48.83E0 , 54.50E0 , 60.41E0 , 72.77E0 , 75.25E0 , 86.84E0 , 94.88E0 , 96.40E0 , 117.37E0 , 139.08E0 , 147.73E0 , 158.63E0 , 161.84E0 , 192.11E0 , 206.76E0 , 209.07E0 , 213.32E0 , 226.44E0 , 237.12E0 , 330.90E0 , 358.72E0 , 370.77E0 , 372.72E0 , 396.24E0 , 416.59E0 , 484.02E0 , 495.47E0 , 514.78E0 , 515.65E0 , 519.47E0 , 544.47E0 , 560.11E0 , 620.77E0 , 18.97E0 , 28.93E0 , 33.91E0 , 40.03E0 , 44.66E0 , 49.87E0 , 55.16E0 , 60.90E0 , 72.08E0 , 85.15E0 , 97.06E0 , 119.63E0 , 133.27E0 , 143.84E0 , 161.91E0 , 180.67E0 , 198.44E0 , 226.86E0 , 229.65E0 , 258.27E0 , 273.77E0 , 339.15E0 , 350.13E0 , 362.75E0 , 371.03E0 , 393.32E0 , 448.53E0 , 473.78E0 , 511.12E0 , 524.70E0 , 548.75E0 , 551.64E0 , 574.02E0 , 623.86E0 , 21.46E0 , 24.33E0 , 33.43E0 , 39.22E0 , 44.18E0 , 55.02E0 , 94.33E0 , 96.44E0 , 118.82E0 , 128.48E0 ,
-141.94E0 , 156.92E0 , 171.65E0 , 190.00E0 , 223.26E0 , 223.88E0 , 231.50E0 , 265.05E0 , 269.44E0 , 271.78E0 , 273.46E0 , 334.61E0 , 339.79E0 , 349.52E0 , 358.18E0 , 377.98E0 , 394.77E0 , 429.66E0 , 468.22E0 , 487.27E0 , 519.54E0 , 523.03E0 , 612.99E0 , 638.59E0 , 641.36E0 , 622.05E0 , 631.50E0 , 663.97E0 , 646.9E0  , 748.29E0 , 749.21E0 , 750.14E0 , 647.04E0 , 646.89E0 , 746.9E0  , 748.43E0 , 747.35E0 , 749.27E0 , 647.61E0 , 747.78E0 , 750.51E0 , 851.37E0 , 845.97E0 , 847.54E0 , 849.93E0 , 851.61E0 , 849.75E0 , 850.98E0 , 848.23E0};
-
-// http://www.itl.nist.gov/div898/strd/nls/data/hahn1.shtml
-void testNistHahn1(void)
-{
-  const int  n=7;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 10., -1., .05, -.00001, -.05, .001, -.000001;
-  // do the computation
-  hahn1_functor functor;
-  LevenbergMarquardt<hahn1_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 11);
-  VERIFY_IS_EQUAL(lm.njev, 10);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.0776351733E+00);
-  VERIFY_IS_APPROX(x[1],-1.2269296921E-01);
-  VERIFY_IS_APPROX(x[2], 4.0863750610E-03);
-  VERIFY_IS_APPROX(x[3],-1.426264e-06); // shoulde be : -1.4262662514E-06
-  VERIFY_IS_APPROX(x[4],-5.7609940901E-03);
-  VERIFY_IS_APPROX(x[5], 2.4053735503E-04);
-  VERIFY_IS_APPROX(x[6],-1.2314450199E-07);
-
-  /*
-   * Second try
-   */
-  x<< .1, -.1, .005, -.000001, -.005, .0001, -.0000001;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 11);
-  VERIFY_IS_EQUAL(lm.njev, 10);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.077640); // should be :  1.0776351733E+00
-  VERIFY_IS_APPROX(x[1], -0.1226933); // should be : -1.2269296921E-01
-  VERIFY_IS_APPROX(x[2], 0.004086383); // should be : 4.0863750610E-03
-  VERIFY_IS_APPROX(x[3], -1.426277e-06); // shoulde be : -1.4262662514E-06
-  VERIFY_IS_APPROX(x[4],-5.7609940901E-03);
-  VERIFY_IS_APPROX(x[5], 0.00024053772); // should be : 2.4053735503E-04
-  VERIFY_IS_APPROX(x[6], -1.231450e-07); // should be : -1.2314450199E-07
-
-}
-
-struct misra1d_functor : Functor<double>
-{
-    misra1d_functor(void) : Functor<double>(2,14) {}
-    static const double x[14];
-    static const double y[14];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==2);
-        assert(fvec.size()==14);
-        for(int i=0; i<14; i++) {
-            fvec[i] = b[0]*b[1]*x[i]/(1.+b[1]*x[i]) - y[i];
-        }
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==2);
-        assert(fjac.rows()==14);
-        assert(fjac.cols()==2);
-        for(int i=0; i<14; i++) {
-            double den = 1.+b[1]*x[i];
-            fjac(i,0) = b[1]*x[i] / den;
-            fjac(i,1) = b[0]*x[i]*(den-b[1]*x[i])/den/den;
-        }
-        return 0;
-    }
-};
-const double misra1d_functor::x[14] = { 77.6E0, 114.9E0, 141.1E0, 190.8E0, 239.9E0, 289.0E0, 332.8E0, 378.4E0, 434.8E0, 477.3E0, 536.8E0, 593.1E0, 689.1E0, 760.0E0};
-const double misra1d_functor::y[14] = { 10.07E0, 14.73E0, 17.94E0, 23.93E0, 29.61E0, 35.18E0, 40.02E0, 44.82E0, 50.76E0, 55.05E0, 61.01E0, 66.40E0, 75.47E0, 81.78E0};
-
-// http://www.itl.nist.gov/div898/strd/nls/data/misra1d.shtml
-void testNistMisra1d(void)
-{
-  const int n=2;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 500., 0.0001;
-  // do the computation
-  misra1d_functor functor;
-  LevenbergMarquardt<misra1d_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 3);
-  VERIFY_IS_EQUAL(lm.nfev, 9);
-  VERIFY_IS_EQUAL(lm.njev, 7);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02);
-  // check x
-  VERIFY_IS_APPROX(x[0], 4.3736970754E+02);
-  VERIFY_IS_APPROX(x[1], 3.0227324449E-04);
-
-  /*
-   * Second try
-   */
-  x<< 450., 0.0003;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 4);
-  VERIFY_IS_EQUAL(lm.njev, 3);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02);
-  // check x
-  VERIFY_IS_APPROX(x[0], 4.3736970754E+02);
-  VERIFY_IS_APPROX(x[1], 3.0227324449E-04);
-}
-
 
-struct lanczos1_functor : Functor<double>
-{
-    lanczos1_functor(void) : Functor<double>(6,24) {}
-    static const double x[24];
-    static const double y[24];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==6);
-        assert(fvec.size()==24);
-        for(int i=0; i<24; i++)
-            fvec[i] = b[0]*exp(-b[1]*x[i]) + b[2]*exp(-b[3]*x[i]) + b[4]*exp(-b[5]*x[i])  - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==6);
-        assert(fjac.rows()==24);
-        assert(fjac.cols()==6);
-        for(int i=0; i<24; i++) {
-            fjac(i,0) = exp(-b[1]*x[i]);
-            fjac(i,1) = -b[0]*x[i]*exp(-b[1]*x[i]);
-            fjac(i,2) = exp(-b[3]*x[i]);
-            fjac(i,3) = -b[2]*x[i]*exp(-b[3]*x[i]);
-            fjac(i,4) = exp(-b[5]*x[i]);
-            fjac(i,5) = -b[4]*x[i]*exp(-b[5]*x[i]);
-        }
-        return 0;
-    }
-};
-const double lanczos1_functor::x[24] = { 0.000000000000E+00, 5.000000000000E-02, 1.000000000000E-01, 1.500000000000E-01, 2.000000000000E-01, 2.500000000000E-01, 3.000000000000E-01, 3.500000000000E-01, 4.000000000000E-01, 4.500000000000E-01, 5.000000000000E-01, 5.500000000000E-01, 6.000000000000E-01, 6.500000000000E-01, 7.000000000000E-01, 7.500000000000E-01, 8.000000000000E-01, 8.500000000000E-01, 9.000000000000E-01, 9.500000000000E-01, 1.000000000000E+00, 1.050000000000E+00, 1.100000000000E+00, 1.150000000000E+00 };
-const double lanczos1_functor::y[24] = { 2.513400000000E+00 ,2.044333373291E+00 ,1.668404436564E+00 ,1.366418021208E+00 ,1.123232487372E+00 ,9.268897180037E-01 ,7.679338563728E-01 ,6.388775523106E-01 ,5.337835317402E-01 ,4.479363617347E-01 ,3.775847884350E-01 ,3.197393199326E-01 ,2.720130773746E-01 ,2.324965529032E-01 ,1.996589546065E-01 ,1.722704126914E-01 ,1.493405660168E-01 ,1.300700206922E-01 ,1.138119324644E-01 ,1.000415587559E-01 ,8.833209084540E-02 ,7.833544019350E-02 ,6.976693743449E-02 ,6.239312536719E-02 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/lanczos1.shtml
-void testNistLanczos1(void)
-{
-  const int n=6;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 1.2, 0.3, 5.6, 5.5, 6.5, 7.6;
-  // do the computation
-  lanczos1_functor functor;
-  LevenbergMarquardt<lanczos1_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 2);
-  VERIFY_IS_EQUAL(lm.nfev, 79);
-  VERIFY_IS_EQUAL(lm.njev, 72);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.430899764097e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
-  // check x
-  VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
-  VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
-  VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
-  VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
-  VERIFY_IS_APPROX(x[4], 1.5575999998E+00);
-  VERIFY_IS_APPROX(x[5], 5.0000000001E+00);
-
-  /*
-   * Second try
-   */
-  x<< 0.5, 0.7, 3.6, 4.2, 4., 6.3;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 2);
-  VERIFY_IS_EQUAL(lm.nfev, 9);
-  VERIFY_IS_EQUAL(lm.njev, 8);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.428595533845e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
-  // check x
-  VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
-  VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
-  VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
-  VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
-  VERIFY_IS_APPROX(x[4], 1.5575999998E+00);
-  VERIFY_IS_APPROX(x[5], 5.0000000001E+00);
-
-}
-
-struct rat42_functor : Functor<double>
-{
-    rat42_functor(void) : Functor<double>(3,9) {}
-    static const double x[9];
-    static const double y[9];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==3);
-        assert(fvec.size()==9);
-        for(int i=0; i<9; i++) {
-            fvec[i] = b[0] / (1.+exp(b[1]-b[2]*x[i])) - y[i];
-        }
-        return 0;
-    }
-
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==3);
-        assert(fjac.rows()==9);
-        assert(fjac.cols()==3);
-        for(int i=0; i<9; i++) {
-            double e = exp(b[1]-b[2]*x[i]);
-            fjac(i,0) = 1./(1.+e);
-            fjac(i,1) = -b[0]*e/(1.+e)/(1.+e);
-            fjac(i,2) = +b[0]*e*x[i]/(1.+e)/(1.+e);
-        }
-        return 0;
-    }
-};
-const double rat42_functor::x[9] = { 9.000E0, 14.000E0, 21.000E0, 28.000E0, 42.000E0, 57.000E0, 63.000E0, 70.000E0, 79.000E0 };
-const double rat42_functor::y[9] = { 8.930E0 ,10.800E0 ,18.590E0 ,22.330E0 ,39.350E0 ,56.110E0 ,61.730E0 ,64.620E0 ,67.080E0 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/ratkowsky2.shtml
-void testNistRat42(void)
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 100., 1., 0.1;
-  // do the computation
-  rat42_functor functor;
-  LevenbergMarquardt<rat42_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 10);
-  VERIFY_IS_EQUAL(lm.njev, 8);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.0565229338E+00);
-  // check x
-  VERIFY_IS_APPROX(x[0], 7.2462237576E+01);
-  VERIFY_IS_APPROX(x[1], 2.6180768402E+00);
-  VERIFY_IS_APPROX(x[2], 6.7359200066E-02);
-
-  /*
-   * Second try
-   */
-  x<< 75., 2.5, 0.07;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 6);
-  VERIFY_IS_EQUAL(lm.njev, 5);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.0565229338E+00);
-  // check x
-  VERIFY_IS_APPROX(x[0], 7.2462237576E+01);
-  VERIFY_IS_APPROX(x[1], 2.6180768402E+00);
-  VERIFY_IS_APPROX(x[2], 6.7359200066E-02);
-}
-
-struct MGH10_functor : Functor<double>
-{
-    MGH10_functor(void) : Functor<double>(3,16) {}
-    static const double x[16];
-    static const double y[16];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==3);
-        assert(fvec.size()==16);
-        for(int i=0; i<16; i++)
-            fvec[i] =  b[0] * exp(b[1]/(x[i]+b[2])) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==3);
-        assert(fjac.rows()==16);
-        assert(fjac.cols()==3);
-        for(int i=0; i<16; i++) {
-            double factor = 1./(x[i]+b[2]);
-            double e = exp(b[1]*factor);
-            fjac(i,0) = e;
-            fjac(i,1) = b[0]*factor*e;
-            fjac(i,2) = -b[1]*b[0]*factor*factor*e;
-        }
-        return 0;
-    }
-};
-const double MGH10_functor::x[16] = { 5.000000E+01, 5.500000E+01, 6.000000E+01, 6.500000E+01, 7.000000E+01, 7.500000E+01, 8.000000E+01, 8.500000E+01, 9.000000E+01, 9.500000E+01, 1.000000E+02, 1.050000E+02, 1.100000E+02, 1.150000E+02, 1.200000E+02, 1.250000E+02 };
-const double MGH10_functor::y[16] = { 3.478000E+04, 2.861000E+04, 2.365000E+04, 1.963000E+04, 1.637000E+04, 1.372000E+04, 1.154000E+04, 9.744000E+03, 8.261000E+03, 7.030000E+03, 6.005000E+03, 5.147000E+03, 4.427000E+03, 3.820000E+03, 3.307000E+03, 2.872000E+03 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/mgh10.shtml
-void testNistMGH10(void)
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 2., 400000., 25000.;
-  // do the computation
-  MGH10_functor functor;
-  LevenbergMarquardt<MGH10_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 2); 
-  VERIFY_IS_EQUAL(lm.nfev, 284 ); 
-  VERIFY_IS_EQUAL(lm.njev, 249 ); 
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7945855171E+01);
-  // check x
-  VERIFY_IS_APPROX(x[0], 5.6096364710E-03);
-  VERIFY_IS_APPROX(x[1], 6.1813463463E+03);
-  VERIFY_IS_APPROX(x[2], 3.4522363462E+02);
-
-  /*
-   * Second try
-   */
-  x<< 0.02, 4000., 250.;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 3);
-  VERIFY_IS_EQUAL(lm.nfev, 126);
-  VERIFY_IS_EQUAL(lm.njev, 116);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7945855171E+01);
-  // check x
-  VERIFY_IS_APPROX(x[0], 5.6096364710E-03);
-  VERIFY_IS_APPROX(x[1], 6.1813463463E+03);
-  VERIFY_IS_APPROX(x[2], 3.4522363462E+02);
-}
-
-
-struct BoxBOD_functor : Functor<double>
-{
-    BoxBOD_functor(void) : Functor<double>(2,6) {}
-    static const double x[6];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        static const double y[6] = { 109., 149., 149., 191., 213., 224. };
-        assert(b.size()==2);
-        assert(fvec.size()==6);
-        for(int i=0; i<6; i++)
-            fvec[i] =  b[0]*(1.-exp(-b[1]*x[i])) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==2);
-        assert(fjac.rows()==6);
-        assert(fjac.cols()==2);
-        for(int i=0; i<6; i++) {
-            double e = exp(-b[1]*x[i]);
-            fjac(i,0) = 1.-e;
-            fjac(i,1) = b[0]*x[i]*e;
-        }
-        return 0;
-    }
-};
-const double BoxBOD_functor::x[6] = { 1., 2., 3., 5., 7., 10. };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/boxbod.shtml
-void testNistBoxBOD(void)
-{
-  const int n=2;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 1., 1.;
-  // do the computation
-  BoxBOD_functor functor;
-  LevenbergMarquardt<BoxBOD_functor> lm(functor);
-  lm.parameters.ftol = 1.E6*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
-  lm.parameters.factor = 10.;
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 31);
-  VERIFY_IS_EQUAL(lm.njev, 25);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.1680088766E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 2.1380940889E+02);
-  VERIFY_IS_APPROX(x[1], 5.4723748542E-01);
-
-  /*
-   * Second try
-   */
-  x<< 100., 0.75;
-  // do the computation
-  lm.resetParameters();
-  lm.parameters.ftol = NumTraits<double>::epsilon();
-  lm.parameters.xtol = NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1); 
-  VERIFY_IS_EQUAL(lm.nfev, 15 ); 
-  VERIFY_IS_EQUAL(lm.njev, 14 ); 
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.1680088766E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 2.1380940889E+02);
-  VERIFY_IS_APPROX(x[1], 5.4723748542E-01);
-}
-
-struct MGH17_functor : Functor<double>
-{
-    MGH17_functor(void) : Functor<double>(5,33) {}
-    static const double x[33];
-    static const double y[33];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==5);
-        assert(fvec.size()==33);
-        for(int i=0; i<33; i++)
-            fvec[i] =  b[0] + b[1]*exp(-b[3]*x[i]) +  b[2]*exp(-b[4]*x[i]) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==5);
-        assert(fjac.rows()==33);
-        assert(fjac.cols()==5);
-        for(int i=0; i<33; i++) {
-            fjac(i,0) = 1.;
-            fjac(i,1) = exp(-b[3]*x[i]);
-            fjac(i,2) = exp(-b[4]*x[i]);
-            fjac(i,3) = -x[i]*b[1]*exp(-b[3]*x[i]);
-            fjac(i,4) = -x[i]*b[2]*exp(-b[4]*x[i]);
-        }
-        return 0;
-    }
-};
-const double MGH17_functor::x[33] = { 0.000000E+00, 1.000000E+01, 2.000000E+01, 3.000000E+01, 4.000000E+01, 5.000000E+01, 6.000000E+01, 7.000000E+01, 8.000000E+01, 9.000000E+01, 1.000000E+02, 1.100000E+02, 1.200000E+02, 1.300000E+02, 1.400000E+02, 1.500000E+02, 1.600000E+02, 1.700000E+02, 1.800000E+02, 1.900000E+02, 2.000000E+02, 2.100000E+02, 2.200000E+02, 2.300000E+02, 2.400000E+02, 2.500000E+02, 2.600000E+02, 2.700000E+02, 2.800000E+02, 2.900000E+02, 3.000000E+02, 3.100000E+02, 3.200000E+02 };
-const double MGH17_functor::y[33] = { 8.440000E-01, 9.080000E-01, 9.320000E-01, 9.360000E-01, 9.250000E-01, 9.080000E-01, 8.810000E-01, 8.500000E-01, 8.180000E-01, 7.840000E-01, 7.510000E-01, 7.180000E-01, 6.850000E-01, 6.580000E-01, 6.280000E-01, 6.030000E-01, 5.800000E-01, 5.580000E-01, 5.380000E-01, 5.220000E-01, 5.060000E-01, 4.900000E-01, 4.780000E-01, 4.670000E-01, 4.570000E-01, 4.480000E-01, 4.380000E-01, 4.310000E-01, 4.240000E-01, 4.200000E-01, 4.140000E-01, 4.110000E-01, 4.060000E-01 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/mgh17.shtml
-void testNistMGH17(void)
-{
-  const int n=5;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 50., 150., -100., 1., 2.;
-  // do the computation
-  MGH17_functor functor;
-  LevenbergMarquardt<MGH17_functor> lm(functor);
-  lm.parameters.ftol = NumTraits<double>::epsilon();
-  lm.parameters.xtol = NumTraits<double>::epsilon();
-  lm.parameters.maxfev = 1000;
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 2); 
-  VERIFY_IS_EQUAL(lm.nfev, 602 ); 
-  VERIFY_IS_EQUAL(lm.njev, 545 ); 
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.4648946975E-05);
-  // check x
-  VERIFY_IS_APPROX(x[0], 3.7541005211E-01);
-  VERIFY_IS_APPROX(x[1], 1.9358469127E+00);
-  VERIFY_IS_APPROX(x[2], -1.4646871366E+00);
-  VERIFY_IS_APPROX(x[3], 1.2867534640E-02);
-  VERIFY_IS_APPROX(x[4], 2.2122699662E-02);
-
-  /*
-   * Second try
-   */
-  x<< 0.5  ,1.5  ,-1   ,0.01 ,0.02;
-  // do the computation
-  lm.resetParameters();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 18);
-  VERIFY_IS_EQUAL(lm.njev, 15);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.4648946975E-05);
-  // check x
-  VERIFY_IS_APPROX(x[0], 3.7541005211E-01);
-  VERIFY_IS_APPROX(x[1], 1.9358469127E+00);
-  VERIFY_IS_APPROX(x[2], -1.4646871366E+00);
-  VERIFY_IS_APPROX(x[3], 1.2867534640E-02);
-  VERIFY_IS_APPROX(x[4], 2.2122699662E-02);
-}
-
-struct MGH09_functor : Functor<double>
-{
-    MGH09_functor(void) : Functor<double>(4,11) {}
-    static const double _x[11];
-    static const double y[11];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==4);
-        assert(fvec.size()==11);
-        for(int i=0; i<11; i++) {
-            double x = _x[i], xx=x*x;
-            fvec[i] = b[0]*(xx+x*b[1])/(xx+x*b[2]+b[3]) - y[i];
-        }
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==4);
-        assert(fjac.rows()==11);
-        assert(fjac.cols()==4);
-        for(int i=0; i<11; i++) {
-            double x = _x[i], xx=x*x;
-            double factor = 1./(xx+x*b[2]+b[3]);
-            fjac(i,0) = (xx+x*b[1]) * factor;
-            fjac(i,1) = b[0]*x* factor;
-            fjac(i,2) = - b[0]*(xx+x*b[1]) * x * factor * factor;
-            fjac(i,3) = - b[0]*(xx+x*b[1]) * factor * factor;
-        }
-        return 0;
-    }
-};
-const double MGH09_functor::_x[11] = { 4., 2., 1., 5.E-1 , 2.5E-01, 1.670000E-01, 1.250000E-01,  1.E-01, 8.330000E-02, 7.140000E-02, 6.250000E-02 };
-const double MGH09_functor::y[11] = { 1.957000E-01, 1.947000E-01, 1.735000E-01, 1.600000E-01, 8.440000E-02, 6.270000E-02, 4.560000E-02, 3.420000E-02, 3.230000E-02, 2.350000E-02, 2.460000E-02 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/mgh09.shtml
-void testNistMGH09(void)
-{
-  const int n=4;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 25., 39, 41.5, 39.;
-  // do the computation
-  MGH09_functor functor;
-  LevenbergMarquardt<MGH09_functor> lm(functor);
-  lm.parameters.maxfev = 1000;
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1); 
-  VERIFY_IS_EQUAL(lm.nfev, 490 ); 
-  VERIFY_IS_EQUAL(lm.njev, 376 ); 
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 3.0750560385E-04);
-  // check x
-  VERIFY_IS_APPROX(x[0], 0.1928077089); // should be 1.9280693458E-01
-  VERIFY_IS_APPROX(x[1], 0.19126423573); // should be 1.9128232873E-01
-  VERIFY_IS_APPROX(x[2], 0.12305309914); // should be 1.2305650693E-01
-  VERIFY_IS_APPROX(x[3], 0.13605395375); // should be 1.3606233068E-01
-
-  /*
-   * Second try
-   */
-  x<< 0.25, 0.39, 0.415, 0.39;
-  // do the computation
-  lm.resetParameters();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 18);
-  VERIFY_IS_EQUAL(lm.njev, 16);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 3.0750560385E-04);
-  // check x
-  VERIFY_IS_APPROX(x[0], 0.19280781); // should be 1.9280693458E-01
-  VERIFY_IS_APPROX(x[1], 0.19126265); // should be 1.9128232873E-01
-  VERIFY_IS_APPROX(x[2], 0.12305280); // should be 1.2305650693E-01
-  VERIFY_IS_APPROX(x[3], 0.13605322); // should be 1.3606233068E-01
-}
-
-
-
-struct Bennett5_functor : Functor<double>
-{
-    Bennett5_functor(void) : Functor<double>(3,154) {}
-    static const double x[154];
-    static const double y[154];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==3);
-        assert(fvec.size()==154);
-        for(int i=0; i<154; i++)
-            fvec[i] = b[0]* pow(b[1]+x[i],-1./b[2]) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==3);
-        assert(fjac.rows()==154);
-        assert(fjac.cols()==3);
-        for(int i=0; i<154; i++) {
-            double e = pow(b[1]+x[i],-1./b[2]);
-            fjac(i,0) = e;
-            fjac(i,1) = - b[0]*e/b[2]/(b[1]+x[i]);
-            fjac(i,2) = b[0]*e*log(b[1]+x[i])/b[2]/b[2];
-        }
-        return 0;
-    }
-};
-const double Bennett5_functor::x[154] = { 7.447168E0, 8.102586E0, 8.452547E0, 8.711278E0, 8.916774E0, 9.087155E0, 9.232590E0, 9.359535E0, 9.472166E0, 9.573384E0, 9.665293E0, 9.749461E0, 9.827092E0, 9.899128E0, 9.966321E0, 10.029280E0, 10.088510E0, 10.144430E0, 10.197380E0, 10.247670E0, 10.295560E0, 10.341250E0, 10.384950E0, 10.426820E0, 10.467000E0, 10.505640E0, 10.542830E0, 10.578690E0, 10.613310E0, 10.646780E0, 10.679150E0, 10.710520E0, 10.740920E0, 10.770440E0, 10.799100E0, 10.826970E0, 10.854080E0, 10.880470E0, 10.906190E0, 10.931260E0, 10.955720E0, 10.979590E0, 11.002910E0, 11.025700E0, 11.047980E0, 11.069770E0, 11.091100E0, 11.111980E0, 11.132440E0, 11.152480E0, 11.172130E0, 11.191410E0, 11.210310E0, 11.228870E0, 11.247090E0, 11.264980E0, 11.282560E0, 11.299840E0, 11.316820E0, 11.333520E0, 11.349940E0, 11.366100E0, 11.382000E0, 11.397660E0, 11.413070E0, 11.428240E0, 11.443200E0, 11.457930E0, 11.472440E0, 11.486750E0, 11.500860E0, 11.514770E0, 11.528490E0, 11.542020E0, 11.555380E0, 11.568550E0,
-11.581560E0, 11.594420E0, 11.607121E0, 11.619640E0, 11.632000E0, 11.644210E0, 11.656280E0, 11.668200E0, 11.679980E0, 11.691620E0, 11.703130E0, 11.714510E0, 11.725760E0, 11.736880E0, 11.747890E0, 11.758780E0, 11.769550E0, 11.780200E0, 11.790730E0, 11.801160E0, 11.811480E0, 11.821700E0, 11.831810E0, 11.841820E0, 11.851730E0, 11.861550E0, 11.871270E0, 11.880890E0, 11.890420E0, 11.899870E0, 11.909220E0, 11.918490E0, 11.927680E0, 11.936780E0, 11.945790E0, 11.954730E0, 11.963590E0, 11.972370E0, 11.981070E0, 11.989700E0, 11.998260E0, 12.006740E0, 12.015150E0, 12.023490E0, 12.031760E0, 12.039970E0, 12.048100E0, 12.056170E0, 12.064180E0, 12.072120E0, 12.080010E0, 12.087820E0, 12.095580E0, 12.103280E0, 12.110920E0, 12.118500E0, 12.126030E0, 12.133500E0, 12.140910E0, 12.148270E0, 12.155570E0, 12.162830E0, 12.170030E0, 12.177170E0, 12.184270E0, 12.191320E0, 12.198320E0, 12.205270E0, 12.212170E0, 12.219030E0, 12.225840E0, 12.232600E0, 12.239320E0, 12.245990E0, 12.252620E0, 12.259200E0, 12.265750E0, 12.272240E0 };
-const double Bennett5_functor::y[154] = { -34.834702E0 ,-34.393200E0 ,-34.152901E0 ,-33.979099E0 ,-33.845901E0 ,-33.732899E0 ,-33.640301E0 ,-33.559200E0 ,-33.486801E0 ,-33.423100E0 ,-33.365101E0 ,-33.313000E0 ,-33.260899E0 ,-33.217400E0 ,-33.176899E0 ,-33.139198E0 ,-33.101601E0 ,-33.066799E0 ,-33.035000E0 ,-33.003101E0 ,-32.971298E0 ,-32.942299E0 ,-32.916302E0 ,-32.890202E0 ,-32.864101E0 ,-32.841000E0 ,-32.817799E0 ,-32.797501E0 ,-32.774300E0 ,-32.757000E0 ,-32.733799E0 ,-32.716400E0 ,-32.699100E0 ,-32.678799E0 ,-32.661400E0 ,-32.644001E0 ,-32.626701E0 ,-32.612202E0 ,-32.597698E0 ,-32.583199E0 ,-32.568699E0 ,-32.554298E0 ,-32.539799E0 ,-32.525299E0 ,-32.510799E0 ,-32.499199E0 ,-32.487598E0 ,-32.473202E0 ,-32.461601E0 ,-32.435501E0 ,-32.435501E0 ,-32.426800E0 ,-32.412300E0 ,-32.400799E0 ,-32.392101E0 ,-32.380501E0 ,-32.366001E0 ,-32.357300E0 ,-32.348598E0 ,-32.339901E0 ,-32.328400E0 ,-32.319698E0 ,-32.311001E0 ,-32.299400E0 ,-32.290699E0 ,-32.282001E0 ,-32.273300E0 ,-32.264599E0 ,-32.256001E0 ,-32.247299E0
-,-32.238602E0 ,-32.229900E0 ,-32.224098E0 ,-32.215401E0 ,-32.203800E0 ,-32.198002E0 ,-32.189400E0 ,-32.183601E0 ,-32.174900E0 ,-32.169102E0 ,-32.163300E0 ,-32.154598E0 ,-32.145901E0 ,-32.140099E0 ,-32.131401E0 ,-32.125599E0 ,-32.119801E0 ,-32.111198E0 ,-32.105400E0 ,-32.096699E0 ,-32.090900E0 ,-32.088001E0 ,-32.079300E0 ,-32.073502E0 ,-32.067699E0 ,-32.061901E0 ,-32.056099E0 ,-32.050301E0 ,-32.044498E0 ,-32.038799E0 ,-32.033001E0 ,-32.027199E0 ,-32.024300E0 ,-32.018501E0 ,-32.012699E0 ,-32.004002E0 ,-32.001099E0 ,-31.995300E0 ,-31.989500E0 ,-31.983700E0 ,-31.977900E0 ,-31.972099E0 ,-31.969299E0 ,-31.963501E0 ,-31.957701E0 ,-31.951900E0 ,-31.946100E0 ,-31.940300E0 ,-31.937401E0 ,-31.931601E0 ,-31.925800E0 ,-31.922899E0 ,-31.917101E0 ,-31.911301E0 ,-31.908400E0 ,-31.902599E0 ,-31.896900E0 ,-31.893999E0 ,-31.888201E0 ,-31.885300E0 ,-31.882401E0 ,-31.876600E0 ,-31.873699E0 ,-31.867901E0 ,-31.862101E0 ,-31.859200E0 ,-31.856300E0 ,-31.850500E0 ,-31.844700E0 ,-31.841801E0 ,-31.838900E0 ,-31.833099E0 ,-31.830200E0 ,
--31.827299E0 ,-31.821600E0 ,-31.818701E0 ,-31.812901E0 ,-31.809999E0 ,-31.807100E0 ,-31.801300E0 ,-31.798401E0 ,-31.795500E0 ,-31.789700E0 ,-31.786800E0 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/bennett5.shtml
-void testNistBennett5(void)
-{
-  const int  n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< -2000., 50., 0.8;
-  // do the computation
-  Bennett5_functor functor;
-  LevenbergMarquardt<Bennett5_functor> lm(functor);
-  lm.parameters.maxfev = 1000;
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 758);
-  VERIFY_IS_EQUAL(lm.njev, 744);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.2404744073E-04);
-  // check x
-  VERIFY_IS_APPROX(x[0], -2.5235058043E+03);
-  VERIFY_IS_APPROX(x[1], 4.6736564644E+01);
-  VERIFY_IS_APPROX(x[2], 9.3218483193E-01);
-  /*
-   * Second try
-   */
-  x<< -1500., 45., 0.85;
-  // do the computation
-  lm.resetParameters();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 203);
-  VERIFY_IS_EQUAL(lm.njev, 192);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.2404744073E-04);
-  // check x
-  VERIFY_IS_APPROX(x[0], -2523.3007865); // should be -2.5235058043E+03
-  VERIFY_IS_APPROX(x[1], 46.735705771); // should be 4.6736564644E+01);
-  VERIFY_IS_APPROX(x[2], 0.93219881891); // should be 9.3218483193E-01);
-}
-
-struct thurber_functor : Functor<double>
-{
-    thurber_functor(void) : Functor<double>(7,37) {}
-    static const double _x[37];
-    static const double _y[37];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        //        int called=0; printf("call hahn1_functor with  iflag=%d, called=%d\n", iflag, called); if (iflag==1) called++;
-        assert(b.size()==7);
-        assert(fvec.size()==37);
-        for(int i=0; i<37; i++) {
-            double x=_x[i], xx=x*x, xxx=xx*x;
-            fvec[i] = (b[0]+b[1]*x+b[2]*xx+b[3]*xxx) / (1.+b[4]*x+b[5]*xx+b[6]*xxx) - _y[i];
-        }
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==7);
-        assert(fjac.rows()==37);
-        assert(fjac.cols()==7);
-        for(int i=0; i<37; i++) {
-            double x=_x[i], xx=x*x, xxx=xx*x;
-            double fact = 1./(1.+b[4]*x+b[5]*xx+b[6]*xxx);
-            fjac(i,0) = 1.*fact;
-            fjac(i,1) = x*fact;
-            fjac(i,2) = xx*fact;
-            fjac(i,3) = xxx*fact;
-            fact = - (b[0]+b[1]*x+b[2]*xx+b[3]*xxx) * fact * fact;
-            fjac(i,4) = x*fact;
-            fjac(i,5) = xx*fact;
-            fjac(i,6) = xxx*fact;
-        }
-        return 0;
-    }
-};
-const double thurber_functor::_x[37] = { -3.067E0, -2.981E0, -2.921E0, -2.912E0, -2.840E0, -2.797E0, -2.702E0, -2.699E0, -2.633E0, -2.481E0, -2.363E0, -2.322E0, -1.501E0, -1.460E0, -1.274E0, -1.212E0, -1.100E0, -1.046E0, -0.915E0, -0.714E0, -0.566E0, -0.545E0, -0.400E0, -0.309E0, -0.109E0, -0.103E0, 0.010E0, 0.119E0, 0.377E0, 0.790E0, 0.963E0, 1.006E0, 1.115E0, 1.572E0, 1.841E0, 2.047E0, 2.200E0 };
-const double thurber_functor::_y[37] = { 80.574E0, 84.248E0, 87.264E0, 87.195E0, 89.076E0, 89.608E0, 89.868E0, 90.101E0, 92.405E0, 95.854E0, 100.696E0, 101.060E0, 401.672E0, 390.724E0, 567.534E0, 635.316E0, 733.054E0, 759.087E0, 894.206E0, 990.785E0, 1090.109E0, 1080.914E0, 1122.643E0, 1178.351E0, 1260.531E0, 1273.514E0, 1288.339E0, 1327.543E0, 1353.863E0, 1414.509E0, 1425.208E0, 1421.384E0, 1442.962E0, 1464.350E0, 1468.705E0, 1447.894E0, 1457.628E0};
-
-// http://www.itl.nist.gov/div898/strd/nls/data/thurber.shtml
-void testNistThurber(void)
-{
-  const int n=7;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 1000 ,1000 ,400 ,40 ,0.7,0.3,0.0 ;
-  // do the computation
-  thurber_functor functor;
-  LevenbergMarquardt<thurber_functor> lm(functor);
-  lm.parameters.ftol = 1.E4*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E4*NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 39);
-  VERIFY_IS_EQUAL(lm.njev, 36);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6427082397E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.2881396800E+03);
-  VERIFY_IS_APPROX(x[1], 1.4910792535E+03);
-  VERIFY_IS_APPROX(x[2], 5.8323836877E+02);
-  VERIFY_IS_APPROX(x[3], 7.5416644291E+01);
-  VERIFY_IS_APPROX(x[4], 9.6629502864E-01);
-  VERIFY_IS_APPROX(x[5], 3.9797285797E-01);
-  VERIFY_IS_APPROX(x[6], 4.9727297349E-02);
-
-  /*
-   * Second try
-   */
-  x<< 1300 ,1500 ,500  ,75   ,1    ,0.4  ,0.05  ;
-  // do the computation
-  lm.resetParameters();
-  lm.parameters.ftol = 1.E4*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E4*NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 29);
-  VERIFY_IS_EQUAL(lm.njev, 28);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6427082397E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.2881396800E+03);
-  VERIFY_IS_APPROX(x[1], 1.4910792535E+03);
-  VERIFY_IS_APPROX(x[2], 5.8323836877E+02);
-  VERIFY_IS_APPROX(x[3], 7.5416644291E+01);
-  VERIFY_IS_APPROX(x[4], 9.6629502864E-01);
-  VERIFY_IS_APPROX(x[5], 3.9797285797E-01);
-  VERIFY_IS_APPROX(x[6], 4.9727297349E-02);
-}
-
-struct rat43_functor : Functor<double>
-{
-    rat43_functor(void) : Functor<double>(4,15) {}
-    static const double x[15];
-    static const double y[15];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==4);
-        assert(fvec.size()==15);
-        for(int i=0; i<15; i++)
-            fvec[i] = b[0] * pow(1.+exp(b[1]-b[2]*x[i]),-1./b[3]) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==4);
-        assert(fjac.rows()==15);
-        assert(fjac.cols()==4);
-        for(int i=0; i<15; i++) {
-            double e = exp(b[1]-b[2]*x[i]);
-            double power = -1./b[3];
-            fjac(i,0) = pow(1.+e, power);
-            fjac(i,1) = power*b[0]*e*pow(1.+e, power-1.);
-            fjac(i,2) = -power*b[0]*e*x[i]*pow(1.+e, power-1.);
-            fjac(i,3) = b[0]*power*power*log(1.+e)*pow(1.+e, power);
-        }
-        return 0;
-    }
-};
-const double rat43_functor::x[15] = { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15. };
-const double rat43_functor::y[15] = { 16.08, 33.83, 65.80, 97.20, 191.55, 326.20, 386.87, 520.53, 590.03, 651.92, 724.93, 699.56, 689.96, 637.56, 717.41 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/ratkowsky3.shtml
-void testNistRat43(void)
-{
-  const int n=4;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 100., 10., 1., 1.;
-  // do the computation
-  rat43_functor functor;
-  LevenbergMarquardt<rat43_functor> lm(functor);
-  lm.parameters.ftol = 1.E6*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 27);
-  VERIFY_IS_EQUAL(lm.njev, 20);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7864049080E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 6.9964151270E+02);
-  VERIFY_IS_APPROX(x[1], 5.2771253025E+00);
-  VERIFY_IS_APPROX(x[2], 7.5962938329E-01);
-  VERIFY_IS_APPROX(x[3], 1.2792483859E+00);
-
-  /*
-   * Second try
-   */
-  x<< 700., 5., 0.75, 1.3;
-  // do the computation
-  lm.resetParameters();
-  lm.parameters.ftol = 1.E5*NumTraits<double>::epsilon();
-  lm.parameters.xtol = 1.E5*NumTraits<double>::epsilon();
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 9);
-  VERIFY_IS_EQUAL(lm.njev, 8);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7864049080E+03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 6.9964151270E+02);
-  VERIFY_IS_APPROX(x[1], 5.2771253025E+00);
-  VERIFY_IS_APPROX(x[2], 7.5962938329E-01);
-  VERIFY_IS_APPROX(x[3], 1.2792483859E+00);
-}
-
-
-
-struct eckerle4_functor : Functor<double>
-{
-    eckerle4_functor(void) : Functor<double>(3,35) {}
-    static const double x[35];
-    static const double y[35];
-    int operator()(const VectorXd &b, VectorXd &fvec)
-    {
-        assert(b.size()==3);
-        assert(fvec.size()==35);
-        for(int i=0; i<35; i++)
-            fvec[i] = b[0]/b[1] * exp(-0.5*(x[i]-b[2])*(x[i]-b[2])/(b[1]*b[1])) - y[i];
-        return 0;
-    }
-    int df(const VectorXd &b, MatrixXd &fjac)
-    {
-        assert(b.size()==3);
-        assert(fjac.rows()==35);
-        assert(fjac.cols()==3);
-        for(int i=0; i<35; i++) {
-            double b12 = b[1]*b[1];
-            double e = exp(-0.5*(x[i]-b[2])*(x[i]-b[2])/b12);
-            fjac(i,0) = e / b[1];
-            fjac(i,1) = ((x[i]-b[2])*(x[i]-b[2])/b12-1.) * b[0]*e/b12;
-            fjac(i,2) = (x[i]-b[2])*e*b[0]/b[1]/b12;
-        }
-        return 0;
-    }
-};
-const double eckerle4_functor::x[35] = { 400.0, 405.0, 410.0, 415.0, 420.0, 425.0, 430.0, 435.0, 436.5, 438.0, 439.5, 441.0, 442.5, 444.0, 445.5, 447.0, 448.5, 450.0, 451.5, 453.0, 454.5, 456.0, 457.5, 459.0, 460.5, 462.0, 463.5, 465.0, 470.0, 475.0, 480.0, 485.0, 490.0, 495.0, 500.0};
-const double eckerle4_functor::y[35] = { 0.0001575, 0.0001699, 0.0002350, 0.0003102, 0.0004917, 0.0008710, 0.0017418, 0.0046400, 0.0065895, 0.0097302, 0.0149002, 0.0237310, 0.0401683, 0.0712559, 0.1264458, 0.2073413, 0.2902366, 0.3445623, 0.3698049, 0.3668534, 0.3106727, 0.2078154, 0.1164354, 0.0616764, 0.0337200, 0.0194023, 0.0117831, 0.0074357, 0.0022732, 0.0008800, 0.0004579, 0.0002345, 0.0001586, 0.0001143, 0.0000710 };
-
-// http://www.itl.nist.gov/div898/strd/nls/data/eckerle4.shtml
-void testNistEckerle4(void)
-{
-  const int n=3;
-  int info;
-
-  VectorXd x(n);
-
-  /*
-   * First try
-   */
-  x<< 1., 10., 500.;
-  // do the computation
-  eckerle4_functor functor;
-  LevenbergMarquardt<eckerle4_functor> lm(functor);
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 18);
-  VERIFY_IS_EQUAL(lm.njev, 15);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.4635887487E-03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.5543827178);
-  VERIFY_IS_APPROX(x[1], 4.0888321754);
-  VERIFY_IS_APPROX(x[2], 4.5154121844E+02);
-
-  /*
-   * Second try
-   */
-  x<< 1.5, 5., 450.;
-  // do the computation
-  info = lm.minimize(x);
-
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 7);
-  VERIFY_IS_EQUAL(lm.njev, 6);
-  // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.4635887487E-03);
-  // check x
-  VERIFY_IS_APPROX(x[0], 1.5543827178);
-  VERIFY_IS_APPROX(x[1], 4.0888321754);
-  VERIFY_IS_APPROX(x[2], 4.5154121844E+02);
-}
 
 void test_NonLinearOptimization()
 {
     // Tests using the examples provided by (c)minpack
-    CALL_SUBTEST/*_1*/(testChkder());
-    CALL_SUBTEST/*_1*/(testLmder1());
-    CALL_SUBTEST/*_1*/(testLmder());
-    CALL_SUBTEST/*_2*/(testHybrj1());
-    CALL_SUBTEST/*_2*/(testHybrj());
-    CALL_SUBTEST/*_2*/(testHybrd1());
-    CALL_SUBTEST/*_2*/(testHybrd());
-    CALL_SUBTEST/*_3*/(testLmstr1());
-    CALL_SUBTEST/*_3*/(testLmstr());
-    CALL_SUBTEST/*_3*/(testLmdif1());
-    CALL_SUBTEST/*_3*/(testLmdif());
-
-    // NIST tests, level of difficulty = "Lower"
-    CALL_SUBTEST/*_4*/(testNistMisra1a());
-    CALL_SUBTEST/*_4*/(testNistChwirut2());
-
-    // NIST tests, level of difficulty = "Average"
-    CALL_SUBTEST/*_5*/(testNistHahn1());
-    CALL_SUBTEST/*_6*/(testNistMisra1d());
-//     CALL_SUBTEST/*_7*/(testNistMGH17());
-//     CALL_SUBTEST/*_8*/(testNistLanczos1());
-
-//     // NIST tests, level of difficulty = "Higher"
-    CALL_SUBTEST/*_9*/(testNistRat42());
-//     CALL_SUBTEST/*_10*/(testNistMGH10());
-    CALL_SUBTEST/*_11*/(testNistBoxBOD());
-//     CALL_SUBTEST/*_12*/(testNistMGH09());
-    CALL_SUBTEST/*_13*/(testNistBennett5());
-    CALL_SUBTEST/*_14*/(testNistThurber());
-    CALL_SUBTEST/*_15*/(testNistRat43());
-    CALL_SUBTEST/*_16*/(testNistEckerle4());
+    CALL_SUBTEST(testChkder());
+    CALL_SUBTEST(testHybrj1());
+    CALL_SUBTEST(testHybrj());
+    CALL_SUBTEST(testHybrd1());
+    CALL_SUBTEST(testHybrd());
 }
 
 /*