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eigenize lmder + some other small fixes

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This commit is contained in:
Thomas Capricelli 2009-08-09 05:07:59 +02:00
parent a6625f22d4
commit 50c192961c
2 changed files with 129 additions and 91 deletions
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52
unsupported/Eigen/src/NonLinear/MathFunctions.h
View File

@ -36,6 +36,7 @@ int ei_hybrd1(
{
int lwa = (x.size()*(3*x.size()+13))/2;
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
fvec.resize(x.size());
return hybrd1(Functor::f, 0, x.size(), x.data(), fvec.data(), tol, wa.data(), lwa);
}
@ -44,14 +45,16 @@ template<typename Functor, typename Scalar>
int ei_lmder1(
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
VectorXi &ipvt,
Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
)
{
int lwa = 5*x.size()+fvec.size();
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
VectorXi ipvt(x.size());
int ldfjac = fvec.size();
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > fjac(ldfjac, x.size());
ipvt.resize(x.size());
return lmder1 (
Functor::f, 0,
fvec.size(), x.size(), x.data(), fvec.data(),
@ -62,5 +65,50 @@ int ei_lmder1(
);
}
template<typename Functor, typename Scalar>
int ei_lmder(
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
int &nfev,
int &njev,
Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
VectorXi &ipvt,
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &wa1,
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &diag,
int mode=1,
double factor = 100.,
int maxfev = 400,
Scalar ftol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
Scalar xtol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
Scalar gtol = Scalar(0.),
int nprint=0
)
{
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >
qtf(x.size()),
wa2(x.size()), wa3(x.size()),
wa4(fvec.size());
int ldfjac = fvec.size();
ipvt.resize(x.size());
wa1.resize(x.size());
fjac.resize(ldfjac, x.size());
diag.resize(x.size());
return lmder (
Functor::f, 0,
fvec.size(), x.size(), x.data(), fvec.data(),
fjac.data() , ldfjac,
ftol, xtol, gtol,
maxfev,
diag.data(), mode,
factor,
nprint,
&nfev, &njev,
ipvt.data(),
qtf.data(),
wa1.data(), wa2.data(), wa3.data(), wa4.data()
);
}
#endif // EIGEN_NONLINEAR_MATHFUNCTIONS_H

96
unsupported/test/NonLinear.cpp
View File

@ -159,12 +159,13 @@ void testLmder1()
Eigen::VectorXd x(n), fvec(m);
Eigen::MatrixXd fjac(m, n);
VectorXi ipvt;
/* the following starting values provide a rough fit. */
x.setConstant(n, 1.);
// do the computation
info = ei_lmder1<lmder1_functor,double>(x, fvec);
info = ei_lmder1<lmder1_functor,double>(x, fvec, ipvt);
// check return value
VERIFY( 1 == info);
@ -178,9 +179,9 @@ void testLmder1()
VERIFY_IS_APPROX(x, x_ref);
}
int fcn_lmder(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac,
int ldfjac, int iflag)
{
struct lmder_functor {
static int f(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac, int ldfjac, int iflag)
{
/* subroutine fcn for lmder example. */
@ -221,69 +222,58 @@ int fcn_lmder(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec
};
}
return 0;
}
}
};
void testLmder()
{
int i, j, m, n, ldfjac, maxfev, mode, nprint, info, nfev, njev;
int ipvt[3];
double ftol, xtol, gtol, factor, fnorm;
double x[3], fvec[15], fjac[15*3], diag[3], qtf[3],
wa1[3], wa2[3], wa3[3], wa4[15];
double covfac;
const int m=15, n=3;
int info, nfev, njev;
double fnorm, covfac, covar_ftol;
Eigen::VectorXd x(n), fvec(m), diag(n), wa1;
Eigen::MatrixXd fjac(m, n);
VectorXi ipvt;
m = 15;
n = 3;
/* the following starting values provide a rough fit. */
x.setConstant(n, 1.);
/* the following starting values provide a rough fit. */
x[1-1] = 1.;
x[2-1] = 1.;
x[3-1] = 1.;
ldfjac = 15;
/* set ftol and xtol to the square root of the machine */
/* and gtol to zero. unless high solutions are */
/* required, these are the recommended settings. */
ftol = sqrt(dpmpar(1));
xtol = sqrt(dpmpar(1));
gtol = 0.;
maxfev = 400;
mode = 1;
factor = 1.e2;
nprint = 0;
info = lmder(fcn_lmder, 0, m, n, x, fvec, fjac, ldfjac, ftol, xtol, gtol,
maxfev, diag, mode, factor, nprint, &nfev, &njev,
ipvt, qtf, wa1, wa2, wa3, wa4);
fnorm = enorm(m, fvec);
VERIFY_IS_APPROX(fnorm, 0.09063596);
// do the computation
info = ei_lmder<lmder_functor, double>(x, fvec, nfev, njev, fjac, ipvt, wa1, diag);
// check return values
VERIFY( 1 == info);
VERIFY(nfev==6);
VERIFY(njev==5);
VERIFY(info==1);
double x_ref[] = {0.08241058, 1.133037, 2.343695 };
for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
ftol = dpmpar(1);
covfac = fnorm*fnorm/(m-n);
covar(n, fjac, ldfjac, ipvt, ftol, wa1);
double cov_ref[] = {
// check norm
fnorm = fvec.norm();
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
covar_ftol = dpmpar(1);
covfac = fnorm*fnorm/(m-n);
covar(n, fjac.data(), m, ipvt.data(), covar_ftol, wa1.data());
Eigen::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
};
-0.002656662, -0.09098995, 0.08778727;
for (i=1; i<=n; i++)
for (j=1; j<=n; j++)
VERIFY_IS_APPROX(fjac[(i-1)*ldfjac+j-1]*covfac, cov_ref[(i-1)*3+(j-1)]);
// std::cout << fjac*covfac << std::endl;
Eigen::MatrixXd cov;
cov = covfac*fjac.corner<n,n>(TopLeft);
VERIFY_IS_APPROX( cov, cov_ref);
// TODO: why isn't this allowed ? :
// VERIFY_IS_APPROX( covfac*fjac.corner<n,n>(TopLeft) , cov_ref);
}
int fcn_hybrj1(void * /*p*/, int n, const double *x, double *fvec, double *fjac, int ldfjac,
int iflag)
{