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eigenize the test for lmder1, clean functor stuff.
(and check the tests still pass, of course, that's the whole point..)
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@ -28,7 +28,6 @@
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#include <cminpack.h>
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#include <cminpack.h>
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template<typename Functor, typename Scalar>
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template<typename Functor, typename Scalar>
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// TODO : fixe Scalar here
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int ei_hybrd1(
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int ei_hybrd1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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@ -41,5 +40,27 @@ int ei_hybrd1(
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return hybrd1(Functor::f, 0, x.size(), x.data(), fvec.data(), tol, wa.data(), lwa);
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return hybrd1(Functor::f, 0, x.size(), x.data(), fvec.data(), tol, wa.data(), lwa);
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}
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}
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template<typename Functor, typename Scalar>
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int ei_lmder1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
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)
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{
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int lwa = 5*x.size()+fvec.size();
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
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VectorXi ipvt(x.size());
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int ldfjac = fvec.size();
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > fjac(ldfjac, x.size());
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return lmder1 (
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Functor::f, 0,
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fvec.size(), x.size(), x.data(), fvec.data(),
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fjac.data() , ldfjac,
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tol,
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ipvt.data(),
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wa.data(), lwa
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);
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}
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#endif // EIGEN_NONLINEAR_MATHFUNCTIONS_H
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#endif // EIGEN_NONLINEAR_MATHFUNCTIONS_H
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@ -112,81 +112,72 @@ void testChkder()
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}
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}
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int fcn_lmder1(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac,
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struct lmder1_functor {
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int ldfjac, int iflag)
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static int f(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac, int ldfjac, int iflag)
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{
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/* subroutine fcn for lmder1 example. */
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int i;
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double tmp1, tmp2, tmp3, tmp4;
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double y[15] = {1.4e-1, 1.8e-1, 2.2e-1, 2.5e-1, 2.9e-1, 3.2e-1, 3.5e-1,
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3.9e-1, 3.7e-1, 5.8e-1, 7.3e-1, 9.6e-1, 1.34, 2.1, 4.39};
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if (iflag != 2)
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{
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{
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for (i = 1; i <= 15; i++)
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{
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/* subroutine fcn for lmder1 example. */
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tmp1 = i;
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tmp2 = 16 - i;
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int i;
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tmp3 = tmp1;
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double tmp1, tmp2, tmp3, tmp4;
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if (i > 8) tmp3 = tmp2;
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double y[15] = {1.4e-1, 1.8e-1, 2.2e-1, 2.5e-1, 2.9e-1, 3.2e-1, 3.5e-1,
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fvec[i-1] = y[i-1] - (x[1-1] + tmp1/(x[2-1]*tmp2 + x[3-1]*tmp3));
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3.9e-1, 3.7e-1, 5.8e-1, 7.3e-1, 9.6e-1, 1.34, 2.1, 4.39};
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}
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if (iflag != 2)
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{
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for (i = 1; i <= 15; i++)
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{
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tmp1 = i;
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tmp2 = 16 - i;
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tmp3 = tmp1;
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if (i > 8) tmp3 = tmp2;
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fvec[i-1] = y[i-1] - (x[1-1] + tmp1/(x[2-1]*tmp2 + x[3-1]*tmp3));
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}
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}
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else
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{
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for ( i = 1; i <= 15; i++)
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{
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tmp1 = i;
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tmp2 = 16 - i;
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tmp3 = tmp1;
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if (i > 8) tmp3 = tmp2;
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tmp4 = (x[2-1]*tmp2 + x[3-1]*tmp3); tmp4 = tmp4*tmp4;
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fjac[i-1 + ldfjac*(1-1)] = -1.;
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fjac[i-1 + ldfjac*(2-1)] = tmp1*tmp2/tmp4;
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fjac[i-1 + ldfjac*(3-1)] = tmp1*tmp3/tmp4;
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}
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}
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return 0;
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}
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}
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else
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};
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{
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for ( i = 1; i <= 15; i++)
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{
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tmp1 = i;
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tmp2 = 16 - i;
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tmp3 = tmp1;
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if (i > 8) tmp3 = tmp2;
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tmp4 = (x[2-1]*tmp2 + x[3-1]*tmp3); tmp4 = tmp4*tmp4;
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fjac[i-1 + ldfjac*(1-1)] = -1.;
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fjac[i-1 + ldfjac*(2-1)] = tmp1*tmp2/tmp4;
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fjac[i-1 + ldfjac*(3-1)] = tmp1*tmp3/tmp4;
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}
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}
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return 0;
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}
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void testLmder1()
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void testLmder1()
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{
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{
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int j, m, n, ldfjac, info, lwa;
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int m=15, n=3, info;
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int ipvt[3];
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double tol, fnorm;
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double x[3], fvec[15], fjac[15*3], wa[30];
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m = 15;
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Eigen::VectorXd x(n), fvec(m);
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n = 3;
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Eigen::MatrixXd fjac(m, n);
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/* the following starting values provide a rough fit. */
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/* the following starting values provide a rough fit. */
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x.setConstant(n, 1.);
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x[1-1] = 1.;
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// do the computation
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x[2-1] = 1.;
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info = ei_lmder1<lmder1_functor,double>(x, fvec);
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x[3-1] = 1.;
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ldfjac = 15;
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// check return value
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lwa = 30;
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VERIFY( 1 == info);
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/* set tol to the square root of the machine precision. */
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// check norm
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/* unless high solutions are required, */
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VERIFY_IS_APPROX(fvec.norm(), 0.09063596);
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/* this is the recommended setting. */
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tol = sqrt(dpmpar(1));
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// check x
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VectorXd x_ref(n);
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info = lmder1(fcn_lmder1, 0, m, n, x, fvec, fjac, ldfjac, tol,
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x_ref << 0.08241058, 1.133037, 2.343695;
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ipvt, wa, lwa);
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VERIFY_IS_APPROX(x, x_ref);
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fnorm = enorm(m, fvec);
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VERIFY_IS_APPROX(fnorm, 0.09063596);
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VERIFY(info == 1);
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double x_ref[] = {0.08241058, 1.133037, 2.343695 };
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for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
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}
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}
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int fcn_lmder(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac,
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int fcn_lmder(void * /*p*/, int /*m*/, int /*n*/, const double *x, double *fvec, double *fjac,
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int ldfjac, int iflag)
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int ldfjac, int iflag)
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{
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{
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@ -464,29 +455,25 @@ void testHybrj()
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for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
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for (j=1; j<=n; j++) VERIFY_IS_APPROX(x[j-1], x_ref[j-1]);
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}
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}
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int fcn_hybrd1(void * /*p*/, int n, const double *x, double *fvec, int /*iflag*/)
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struct hybrd1_functor {
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{
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static int f(void * /*p*/, int n, const double *x, double *fvec, int /*iflag*/)
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/* subroutine fcn for hybrd1 example. */
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int k;
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double one=1, temp, temp1, temp2, three=3, two=2, zero=0;
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for (k=1; k <= n; k++)
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{
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{
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temp = (three - two*x[k-1])*x[k-1];
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/* subroutine fcn for hybrd1 example. */
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temp1 = zero;
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if (k != 1) temp1 = x[k-1-1];
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int k;
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temp2 = zero;
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double one=1, temp, temp1, temp2, three=3, two=2, zero=0;
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if (k != n) temp2 = x[k+1-1];
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fvec[k-1] = temp - temp1 - two*temp2 + one;
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for (k=1; k <= n; k++)
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{
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temp = (three - two*x[k-1])*x[k-1];
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temp1 = zero;
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if (k != 1) temp1 = x[k-1-1];
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temp2 = zero;
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if (k != n) temp2 = x[k+1-1];
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fvec[k-1] = temp - temp1 - two*temp2 + one;
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}
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return 0;
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}
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}
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return 0;
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}
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struct myfunctor {
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static int f(void *p, int n, const double *x, double *fvec, int iflag )
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{ return fcn_hybrd1(p,n,x,fvec,iflag) ; }
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};
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};
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void testHybrd1()
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void testHybrd1()
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@ -497,11 +484,8 @@ void testHybrd1()
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/* the following starting values provide a rough solution. */
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/* the following starting values provide a rough solution. */
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x.setConstant(n, -1.);
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x.setConstant(n, -1.);
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/* set tol to the square root of the machine precision. */
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// do the computation
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/* unless high solutions are required, */
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info = ei_hybrd1<hybrd1_functor,double>(x, fvec);
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/* this is the recommended setting. */
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info = ei_hybrd1<myfunctor,double>(x, fvec);
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// check return value
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// check return value
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VERIFY( 1 == info);
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VERIFY( 1 == info);
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