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wrapper for lmdif1 + eigenization of calling test

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This commit is contained in:
Thomas Capricelli 2009-08-10 17:16:43 +02:00
parent 80372c18ee
commit bb1204a145
2 changed files with 59 additions and 40 deletions
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25
unsupported/Eigen/src/NonLinear/MathFunctions.h
View File

@ -266,5 +266,30 @@ int ei_lmdif(
);
}
template<typename Functor, typename Scalar>
int ei_lmdif1(
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
VectorXi &iwa,
Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
)
{
int n = x.size();
int ldfjac = fvec.size();
int lwa = ldfjac*n+5*n+ldfjac;
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > fjac(ldfjac, n);
iwa.resize(n);
wa.resize(lwa);
return lmdif1 (
Functor::f, 0,
fvec.size(), n, x.data(), fvec.data(),
tol,
iwa.data(),
wa.data(), lwa
);
}
#endif // EIGEN_NONLINEAR_MATHFUNCTIONS_H

74
unsupported/test/NonLinear.cpp
View File

@ -684,58 +684,52 @@ void testLmstr()
for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
}
int fcn_lmdif1(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, int /*iflag*/)
{
/* function fcn for lmdif1 example */
int i;
double tmp1,tmp2,tmp3;
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};
for (i=0; i<15; i++)
struct lmdif1_functor {
static int f(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, int /*iflag*/)
{
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));
/* function fcn for lmdif1 example */
int i;
double tmp1,tmp2,tmp3;
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};
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;
}
return 0;
}
};
void testLmdif1()
{
int m, n, info, lwa, iwa[3];
double tol, fnorm, x[3], fvec[15], wa[75];
int m=15, n=3, info;
m = 15;
n = 3;
Eigen::VectorXd x(n), fvec(m);
VectorXi iwa;
/* the following starting values provide a rough fit. */
x.setConstant(n, 1.);
x[0] = 1.e0;
x[1] = 1.e0;
x[2] = 1.e0;
// do the computation
info = ei_lmdif1<lmdif1_functor,double>(x, fvec, iwa);
lwa = 75;
// check return value
VERIFY( 1 == info);
/* set tol to the square root of the machine precision. unless high
precision solutions are required, this is the recommended
setting. */
// check norm
VERIFY_IS_APPROX(fvec.norm(), 0.09063596);
tol = sqrt(dpmpar(1));
info = lmdif1(fcn_lmdif1, 0, m, n, x, fvec, tol, iwa, wa, lwa);
fnorm = enorm(m, fvec);
VERIFY_IS_APPROX(fnorm, 0.09063596);
VERIFY(info==1);
double x_ref[] = {0.0824106, 1.1330366, 2.3436947 };
int j;
for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
// check x
VectorXd x_ref(n);
x_ref << 0.0824106, 1.1330366, 2.3436947;
VERIFY_IS_APPROX(x, x_ref);
}