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📄 lmstr.c

📁 该程序实现了非线性最小二乘问题和非线性方程组的解法
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/* L70: */    }    ++(*njev);/*        if the jacobian is rank deficient, call qrfac to *//*        reorder its columns and update the components of qtf. */    sing = FALSE_;    i__1 = n;    for (j = 1; j <= i__1; ++j) {	if (fjac[j + j * fjac_dim1] == 0.) {	    sing = TRUE_;	}	ipvt[j] = j;	wa2[j] = enorm(j, &fjac[j * fjac_dim1 + 1]);/* L80: */    }    if (! sing) {	goto L130;    }    qrfac(n, n, &fjac[fjac_offset], ldfjac, TRUE_, &ipvt[1], n, &wa1[1], &	    wa2[1], &wa3[1]);    i__1 = n;    for (j = 1; j <= i__1; ++j) {	if (fjac[j + j * fjac_dim1] == 0.) {	    goto L110;	}	sum = 0.;	i__2 = n;	for (i__ = j; i__ <= i__2; ++i__) {	    sum += fjac[i__ + j * fjac_dim1] * qtf[i__];/* L90: */	}	temp = -sum / fjac[j + j * fjac_dim1];	i__2 = n;	for (i__ = j; i__ <= i__2; ++i__) {	    qtf[i__] += fjac[i__ + j * fjac_dim1] * temp;/* L100: */	}L110:	fjac[j + j * fjac_dim1] = wa1[j];/* L120: */    }L130:/*        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 L170;    }    if (mode == 2) {	goto L150;    }    i__1 = n;    for (j = 1; j <= i__1; ++j) {	diag[j] = wa2[j];	if (wa2[j] == 0.) {	    diag[j] = 1.;	}/* L140: */    }L150:/*        on the first iteration, calculate the norm of the scaled x *//*        and initialize the step bound delta. */    i__1 = n;    for (j = 1; j <= i__1; ++j) {	wa3[j] = diag[j] * x[j];/* L160: */    }    xnorm = enorm(n, &wa3[1]);    delta = factor * xnorm;    if (delta == 0.) {	delta = factor;    }L170:/*        compute the norm of the scaled gradient. */    gnorm = 0.;    if (fnorm == 0.) {	goto L210;    }    i__1 = n;    for (j = 1; j <= i__1; ++j) {	l = ipvt[j];	if (wa2[l] == 0.) {	    goto L190;	}	sum = 0.;	i__2 = j;	for (i__ = 1; i__ <= i__2; ++i__) {	    sum += fjac[i__ + j * fjac_dim1] * (qtf[i__] / fnorm);/* L180: */	}/* Computing MAX */	d__2 = gnorm, d__3 = (d__1 = sum / wa2[l], abs(d__1));	gnorm = max(d__2,d__3);L190:/* L200: */	;    }L210:/*        test for convergence of the gradient norm. */    if (gnorm <= gtol) {	info = 4;    }    if (info != 0) {	goto L340;    }/*        rescale if necessary. */    if (mode == 2) {	goto L230;    }    i__1 = n;    for (j = 1; j <= i__1; ++j) {/* Computing MAX */	d__1 = diag[j], d__2 = wa2[j];	diag[j] = max(d__1,d__2);/* L220: */    }L230:/*        beginning of the inner loop. */L240:/*           determine the levenberg-marquardt parameter. */    lmpar(n, &fjac[fjac_offset], ldfjac, &ipvt[1], &diag[1], &qtf[1], delta,	     &par, &wa1[1], &wa2[1], &wa3[1], &wa4[1]);/*           store the direction p and x + p. calculate the norm of p. */    i__1 = n;    for (j = 1; j <= i__1; ++j) {	wa1[j] = -wa1[j];	wa2[j] = x[j] + wa1[j];	wa3[j] = diag[j] * wa1[j];/* L250: */    }    pnorm = enorm(n, &wa3[1]);/*           on the first iteration, adjust the initial step bound. */    if (iter == 1) {	delta = min(delta,pnorm);    }/*           evaluate the function at x + p and calculate its norm. */    iflag = (*fcn)(p, m, n, &wa2[1], &wa4[1], &wa3[1], 1);    ++(*nfev);    if (iflag < 0) {	goto L340;    }    fnorm1 = enorm(m, &wa4[1]);/*           compute the scaled actual reduction. */    actred = -1.;    if (p1 * fnorm1 < fnorm) {/* Computing 2nd power */	d__1 = fnorm1 / fnorm;	actred = 1. - d__1 * d__1;    }/*           compute the scaled predicted reduction and *//*           the scaled directional derivative. */    i__1 = n;    for (j = 1; j <= i__1; ++j) {	wa3[j] = 0.;	l = ipvt[j];	temp = wa1[l];	i__2 = j;	for (i__ = 1; i__ <= i__2; ++i__) {	    wa3[i__] += fjac[i__ + j * fjac_dim1] * temp;/* L260: */	}/* L270: */    }    temp1 = enorm(n, &wa3[1]) / fnorm;    temp2 = sqrt(par) * pnorm / fnorm;/* Computing 2nd power */    d__1 = temp1;/* Computing 2nd power */    d__2 = temp2;    prered = d__1 * d__1 + d__2 * d__2 / p5;/* Computing 2nd power */    d__1 = temp1;/* Computing 2nd power */    d__2 = temp2;    dirder = -(d__1 * d__1 + d__2 * d__2);/*           compute the ratio of the actual to the predicted *//*           reduction. */    ratio = 0.;    if (prered != 0.) {	ratio = actred / prered;    }/*           update the step bound. */    if (ratio > p25) {	goto L280;    }    if (actred >= 0.) {	temp = p5;    }    if (actred < 0.) {	temp = p5 * dirder / (dirder + p5 * actred);    }    if (p1 * fnorm1 >= fnorm || temp < p1) {	temp = p1;    }/* Computing MIN */    d__1 = delta, d__2 = pnorm / p1;    delta = temp * min(d__1,d__2);    par /= temp;    goto L300;L280:    if (par != 0. && ratio < p75) {	goto L290;    }    delta = pnorm / p5;    par = p5 * par;L290:L300:/*           test for successful iteration. */    if (ratio < p0001) {	goto L330;    }/*           successful iteration. update x, fvec, and their norms. */    i__1 = n;    for (j = 1; j <= i__1; ++j) {	x[j] = wa2[j];	wa2[j] = diag[j] * x[j];/* L310: */    }    i__1 = m;    for (i__ = 1; i__ <= i__1; ++i__) {	fvec[i__] = wa4[i__];/* L320: */    }    xnorm = enorm(n, &wa2[1]);    fnorm = fnorm1;    ++iter;L330:/*           tests for convergence. */    if (abs(actred) <= ftol && prered <= ftol && p5 * ratio <= 1.) {	info = 1;    }    if (delta <= xtol * xnorm) {	info = 2;    }    if (abs(actred) <= ftol && prered <= ftol && p5 * ratio <= 1. && info 	    == 2) {	info = 3;    }    if (info != 0) {	goto L340;    }/*           tests for termination and stringent tolerances. */    if (*nfev >= maxfev) {	info = 5;    }    if (abs(actred) <= epsmch && prered <= epsmch && p5 * ratio <= 1.) {	info = 6;    }    if (delta <= epsmch * xnorm) {	info = 7;    }    if (gnorm <= epsmch) {	info = 8;    }    if (info != 0) {	goto L340;    }/*           end of the inner loop. repeat if iteration unsuccessful. */    if (ratio < p0001) {	goto L240;    }/*        end of the outer loop. */    goto L30;L340:/*     termination, either normal or user imposed. */    if (iflag < 0) {	info = iflag;    }    iflag = 0;    if (nprint > 0) {	iflag = (*fcn)(p, m, n, &x[1], &fvec[1], &wa3[1], 0);    }    return info;/*     last card of subroutine lmstr. */} /* lmstr_ */

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