template int ei_lmdif( Matrix< Scalar, Dynamic, 1 > &x, Matrix< Scalar, Dynamic, 1 > &fvec, int &nfev, Matrix< Scalar, Dynamic, Dynamic > &fjac, VectorXi &ipvt, Matrix< Scalar, Dynamic, 1 > &qtf, Matrix< Scalar, Dynamic, 1 > &diag, int mode=1, Scalar factor = 100., int maxfev = 400, Scalar ftol = ei_sqrt(epsilon()), Scalar xtol = ei_sqrt(epsilon()), Scalar gtol = Scalar(0.), Scalar epsfcn = Scalar(0.), int nprint=0 ) { const int m = fvec.size(), n = x.size(); Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(m); ipvt.resize(n); fjac.resize(m, n); diag.resize(n); qtf.resize(n); /* Local variables */ int i, j, l; Scalar par, sum; int iter; Scalar temp, temp1, temp2; int iflag; Scalar delta; Scalar ratio; Scalar fnorm, gnorm; Scalar pnorm, xnorm, fnorm1, actred, dirder, prered; int info; /* Function Body */ info = 0; iflag = 0; nfev = 0; /* check the input parameters for errors. */ if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.) { goto L300; } if (mode == 2) for (j = 0; j < n; ++j) if (diag[j] <= 0.) goto L300; /* evaluate the function at the starting point */ /* and calculate its norm. */ iflag = Functor::f(x, fvec); nfev = 1; if (iflag < 0) { goto L300; } fnorm = fvec.stableNorm(); /* initialize levenberg-marquardt parameter and iteration counter. */ par = 0.; iter = 1; /* beginning of the outer loop. */ L30: /* calculate the jacobian matrix. */ iflag = ei_fdjac2(x, fvec, fjac, epsfcn, wa4); nfev += n; if (iflag < 0) { goto L300; } /* if requested, call Functor::f to enable printing of iterates. */ if (nprint <= 0) { goto L40; } iflag = 0; if ((iter - 1) % nprint == 0) { iflag = Functor::debug(x, fvec); } if (iflag < 0) { goto L300; } L40: /* compute the qr factorization of the jacobian. */ ei_qrfac(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data()); ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1) /* on the first iteration and if mode is 1, scale according */ /* to the norms of the columns of the initial jacobian. */ if (iter != 1) { goto L80; } if (mode == 2) { goto L60; } for (j = 0; j < n; ++j) { diag[j] = wa2[j]; if (wa2[j] == 0.) { diag[j] = 1.; } /* L50: */ } L60: /* on the first iteration, calculate the norm of the scaled x */ /* and initialize the step bound delta. */ wa3 = diag.cwise() * x; xnorm = wa3.stableNorm(); delta = factor * xnorm; if (delta == 0.) { delta = factor; } L80: /* form (q transpose)*fvec and store the first n components in */ /* qtf. */ wa4 = fvec; for (j = 0; j < n; ++j) { if (fjac(j,j) == 0.) { goto L120; } sum = 0.; for (i = j; i < m; ++i) { sum += fjac(i,j) * wa4[i]; /* L100: */ } temp = -sum / fjac(j,j); for (i = j; i < m; ++i) { wa4[i] += fjac(i,j) * temp; /* L110: */ } L120: fjac(j,j) = wa1[j]; qtf[j] = wa4[j]; /* L130: */ } /* compute the norm of the scaled gradient. */ gnorm = 0.; if (fnorm == 0.) { goto L170; } for (j = 0; j < n; ++j) { l = ipvt[j]; if (wa2[l] != 0.) { sum = 0.; for (i = 0; i <= j; ++i) sum += fjac(i,j) * (qtf[i] / fnorm); /* Computing MAX */ gnorm = std::max(gnorm, ei_abs(sum / wa2[l])); } } L170: /* test for convergence of the gradient norm. */ if (gnorm <= gtol) { info = 4; } if (info != 0) { goto L300; } /* rescale if necessary. */ if (mode == 2) { goto L190; } /* Computing MAX */ diag = diag.cwise().max(wa2); L190: /* beginning of the inner loop. */ L200: /* determine the levenberg-marquardt parameter. */ ei_lmpar(fjac, ipvt, diag, qtf, delta, par, wa1, wa2); /* store the direction p and x + p. calculate the norm of p. */ wa1 = -wa1; wa2 = x + wa1; wa3 = diag.cwise() * wa1; pnorm = wa3.stableNorm(); /* on the first iteration, adjust the initial step bound. */ if (iter == 1) { delta = std::min(delta,pnorm); } /* evaluate the function at x + p and calculate its norm. */ iflag = Functor::f(wa2, wa4); ++nfev; if (iflag < 0) { goto L300; } fnorm1 = wa4.stableNorm(); /* compute the scaled actual reduction. */ actred = -1.; if (Scalar(.1) * fnorm1 < fnorm) /* Computing 2nd power */ actred = 1. - ei_abs2(fnorm1 / fnorm); /* compute the scaled predicted reduction and */ /* the scaled directional derivative. */ wa3.fill(0.); for (j = 0; j < n; ++j) { l = ipvt[j]; temp = wa1[l]; for (i = 0; i <= j; ++i) { wa3[i] += fjac(i,j) * temp; /* L220: */ } /* L230: */ } temp1 = ei_abs2(wa3.stableNorm() / fnorm); temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm); /* Computing 2nd power */ prered = temp1 + temp2 / Scalar(.5); dirder = -(temp1 + temp2); /* compute the ratio of the actual to the predicted */ /* reduction. */ ratio = 0.; if (prered != 0.) { ratio = actred / prered; } /* update the step bound. */ if (ratio > Scalar(.25)) { goto L240; } if (actred >= 0.) { temp = Scalar(.5); } if (actred < 0.) { temp = Scalar(.5) * dirder / (dirder + Scalar(.5) * actred); } if (Scalar(.1) * fnorm1 >= fnorm || temp < Scalar(.1)) temp = Scalar(.1); /* Computing MIN */ delta = temp * std::min(delta, pnorm / Scalar(.1)); par /= temp; goto L260; L240: if (par != 0. && ratio < Scalar(.75)) { goto L250; } delta = pnorm / Scalar(.5); par = Scalar(.5) * par; L250: L260: /* test for successful iteration. */ if (ratio < Scalar(1e-4)) { goto L290; } /* successful iteration. update x, fvec, and their norms. */ x = wa2; wa2 = diag.cwise() * x; fvec = wa4; xnorm = wa2.stableNorm(); fnorm = fnorm1; ++iter; L290: /* tests for convergence. */ if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1.) { info = 1; } if (delta <= xtol * xnorm) { info = 2; } if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1. && info == 2) { info = 3; } if (info != 0) { goto L300; } /* tests for termination and stringent tolerances. */ if (nfev >= maxfev) { info = 5; } if (ei_abs(actred) <= epsilon() && prered <= epsilon() && Scalar(.5) * ratio <= 1.) { info = 6; } if (delta <= epsilon() * xnorm) { info = 7; } if (gnorm <= epsilon()) { info = 8; } if (info != 0) { goto L300; } /* end of the inner loop. repeat if iteration unsuccessful. */ if (ratio < Scalar(1e-4)) { goto L200; } /* end of the outer loop. */ goto L30; L300: /* termination, either normal or user imposed. */ if (iflag < 0) { info = iflag; } iflag = 0; if (nprint > 0) { iflag = Functor::debug(x, fvec); } return info; }