cleaning, removing goto's, uniformization (try to reduce diff between

hybr[dj].h  or lm[der,dif,str].h as much as possible), for future merging.

5 files changed, 489 insertions, 636 deletions

diff --git a/unsupported/Eigen/src/NonLinear/hybrd.h b/unsupported/Eigen/src/NonLinear/hybrd.h
index 4d0416917..d6d0f02ea 100644
--- a/unsupported/Eigen/src/NonLinear/hybrd.h
+++ b/unsupported/Eigen/src/NonLinear/hybrd.h
@@ -89,7 +89,7 @@ int ei_hybrd(
     while (true) {
         jeval = true;
 
-        /*        calculate the jacobian matrix. */
+        /* calculate the jacobian matrix. */
 
         iflag = ei_fdjac1<Functor,Scalar>(x, fvec, fjac,
                 nb_of_subdiagonals, nb_of_superdiagonals, epsfcn, wa1, wa2);
@@ -97,12 +97,12 @@ int ei_hybrd(
         if (iflag < 0)
             break;
 
-        /*        compute the qr factorization of the jacobian. */
+        /* compute the qr factorization of the jacobian. */
 
         ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, 1, wa1.data(), wa2.data());
 
-        /*        on the first iteration and if mode is 1, scale according */
-        /*        to the norms of the columns of the initial jacobian. */
+        /* on the first iteration and if mode is 1, scale according */
+        /* to the norms of the columns of the initial jacobian. */
 
         if (iter == 1) {
             if (mode != 2)
@@ -112,8 +112,8 @@ int ei_hybrd(
                         diag[j] = 1.;
                 }
 
-            /*        on the first iteration, calculate the norm of the scaled x */
-            /*        and initialize the step bound delta. */
+            /* on the first iteration, calculate the norm of the scaled x */
+            /* and initialize the step bound delta. */
 
             wa3 = diag.cwise() * x;
             xnorm = wa3.stableNorm();
@@ -122,7 +122,7 @@ int ei_hybrd(
                 delta = factor;
         }
 
-        /*        form (q transpose)*fvec and store in qtf. */
+        /* form (q transpose)*fvec and store in qtf. */
 
         qtf = fvec;
         for (j = 0; j < n; ++j)
@@ -135,7 +135,7 @@ int ei_hybrd(
                     qtf[i] += fjac(i,j) * temp;
             }
 
-        /*        copy the triangular factor of the qr factorization into r. */
+        /* copy the triangular factor of the qr factorization into r. */
 
         sing = false;
         for (j = 0; j < n; ++j) {
@@ -150,20 +150,20 @@ int ei_hybrd(
                 sing = true;
         }
 
-        /*        accumulate the orthogonal factor in fjac. */
+        /* accumulate the orthogonal factor in fjac. */
 
         ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
 
-        /*        rescale if necessary. */
+        /* rescale if necessary. */
 
         /* Computing MAX */
         if (mode != 2)
             diag = diag.cwise().max(wa2);
 
-        /*        beginning of the inner loop. */
+        /* beginning of the inner loop. */
 
         while (true) {
-            /*           if requested, call Functor::f to enable printing of iterates. */
+            /* if requested, call Functor::f to enable printing of iterates. */
 
             if (nprint > 0) {
                 iflag = 0;
@@ -173,23 +173,23 @@ int ei_hybrd(
                     goto L300;
             }
 
-            /*           determine the direction p. */
+            /* determine the direction p. */
 
             ei_dogleg<Scalar>(R, diag, qtf, delta, wa1);
 
-            /*           store the direction p and x + p. calculate the norm of p. */
+            /* 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. */
+            /* 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. */
+            /* evaluate the function at x + p and calculate its norm. */
 
             iflag = Functor::f(wa2, wa4);
             ++nfev;
@@ -197,13 +197,13 @@ int ei_hybrd(
                 goto L300;
             fnorm1 = wa4.stableNorm();
 
-            /*           compute the scaled actual reduction. */
+            /* compute the scaled actual reduction. */
 
             actred = -1.;
             if (fnorm1 < fnorm) /* Computing 2nd power */
                 actred = 1. - ei_abs2(fnorm1 / fnorm);
 
-            /*           compute the scaled predicted reduction. */
+            /* compute the scaled predicted reduction. */
 
             l = 0;
             for (i = 0; i < n; ++i) {
@@ -219,14 +219,14 @@ int ei_hybrd(
             if (temp < fnorm) /* Computing 2nd power */
                 prered = 1. - ei_abs2(temp / fnorm);
 
-            /*           compute the ratio of the actual to the predicted */
-            /*           reduction. */
+            /* compute the ratio of the actual to the predicted */
+            /* reduction. */
 
             ratio = 0.;
             if (prered > 0.)
                 ratio = actred / prered;
 
-            /*           update the step bound. */
+            /* update the step bound. */
 
             if (ratio < Scalar(.1)) {
                 ncsuc = 0;
@@ -242,10 +242,10 @@ int ei_hybrd(
                 }
             }
 
-            /*           test for successful iteration. */
+            /* test for successful iteration. */
 
             if (ratio >= Scalar(1e-4)) {
-                /*           successful iteration. update x, fvec, and their norms. */
+                /* successful iteration. update x, fvec, and their norms. */
                 x = wa2;
                 wa2 = diag.cwise() * x;
                 fvec = wa4;
@@ -254,7 +254,7 @@ int ei_hybrd(
                 ++iter;
             }
 
-            /*           determine the progress of the iteration. */
+            /* determine the progress of the iteration. */
 
             ++nslow1;
             if (actred >= Scalar(.001))
@@ -264,14 +264,14 @@ int ei_hybrd(
             if (actred >= Scalar(.1))
                 nslow2 = 0;
 
-            /*           test for convergence. */
+            /* test for convergence. */
 
             if (delta <= xtol * xnorm || fnorm == 0.)
                 info = 1;
             if (info != 0)
                 goto L300;
 
-            /*           tests for termination and stringent tolerances. */
+            /* tests for termination and stringent tolerances. */
 
             if (nfev >= maxfev)
                 info = 2;
@@ -285,14 +285,14 @@ int ei_hybrd(
             if (info != 0)
                 goto L300;
 
-            /*           criterion for recalculating jacobian approximation */
-            /*           by forward differences. */
+            /* criterion for recalculating jacobian approximation */
+            /* by forward differences. */
 
             if (ncfail == 2)
                 break;
 
-            /*           calculate the rank one modification to the jacobian */
-            /*           and update qtf if necessary. */
+            /* calculate the rank one modification to the jacobian */
+            /* and update qtf if necessary. */
 
             for (j = 0; j < n; ++j) {
                 sum = wa4.dot(fjac.col(j));
@@ -302,17 +302,17 @@ int ei_hybrd(
                     qtf[j] = sum;
             }
 
-            /*           compute the qr factorization of the updated jacobian. */
+            /* compute the qr factorization of the updated jacobian. */
 
             ei_r1updt<Scalar>(n, n, R.data(), R.size(), wa1.data(), wa2.data(), wa3.data(), &sing);
             ei_r1mpyq<Scalar>(n, n, fjac.data(), fjac.rows(), wa2.data(), wa3.data());
             ei_r1mpyq<Scalar>(1, n, qtf.data(), 1, wa2.data(), wa3.data());
 
-            /*           end of the inner loop. */
+            /* end of the inner loop. */
 
             jeval = false;
         }
-        /*        end of the outer loop. */
+        /* end of the outer loop. */
     }
 L300:
     /*     termination, either normal or user imposed. */
diff --git a/unsupported/Eigen/src/NonLinear/hybrj.h b/unsupported/Eigen/src/NonLinear/hybrj.h
index 4276d804b..ba4b8493a 100644
--- a/unsupported/Eigen/src/NonLinear/hybrj.h
+++ b/unsupported/Eigen/src/NonLinear/hybrj.h
@@ -78,19 +78,19 @@ int ei_hybrj(
     while (true) {
         jeval = true;
 
-        /*        calculate the jacobian matrix. */
+        /* calculate the jacobian matrix. */
 
         iflag = Functor::df(x, fjac);
         ++njev;
         if (iflag < 0)
             break;
 
-        /*        compute the qr factorization of the jacobian. */
+        /* compute the qr factorization of the jacobian. */
 
         ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, 1, wa1.data(), wa2.data());
 
-        /*        on the first iteration and if mode is 1, scale according */
-        /*        to the norms of the columns of the initial jacobian. */
+        /* on the first iteration and if mode is 1, scale according */
+        /* to the norms of the columns of the initial jacobian. */
 
         if (iter == 1) {
             if (mode != 2)
@@ -100,8 +100,8 @@ int ei_hybrj(
                         diag[j] = 1.;
                 }
 
-            /*        on the first iteration, calculate the norm of the scaled x */
-            /*        and initialize the step bound delta. */
+            /* on the first iteration, calculate the norm of the scaled x */
+            /* and initialize the step bound delta. */
 
             wa3 = diag.cwise() * x;
             xnorm = wa3.stableNorm();
@@ -110,7 +110,7 @@ int ei_hybrj(
                 delta = factor;
         }
 
-        /*        form (q transpose)*fvec and store in qtf. */
+        /* form (q transpose)*fvec and store in qtf. */
 
         qtf = fvec;
         for (j = 0; j < n; ++j)
@@ -123,7 +123,7 @@ int ei_hybrj(
                     qtf[i] += fjac(i,j) * temp;
             }
 
-        /*        copy the triangular factor of the qr factorization into r. */
+        /* copy the triangular factor of the qr factorization into r. */
 
         sing = false;
         for (j = 0; j < n; ++j) {
@@ -138,20 +138,20 @@ int ei_hybrj(
                 sing = true;
         }
 
-        /*        accumulate the orthogonal factor in fjac. */
+        /* accumulate the orthogonal factor in fjac. */
 
         ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
 
-        /*        rescale if necessary. */
+        /* rescale if necessary. */
 
         /* Computing MAX */
         if (mode != 2)
             diag = diag.cwise().max(wa2);
 
-        /*        beginning of the inner loop. */
+        /* beginning of the inner loop. */
 
         while (true) {
-            /*           if requested, call Functor::f to enable printing of iterates. */
+            /* if requested, call Functor::f to enable printing of iterates. */
 
             if (nprint > 0) {
                 iflag = 0;
@@ -161,23 +161,23 @@ int ei_hybrj(
                     goto L300;
             }
 
-            /*           determine the direction p. */
+            /* determine the direction p. */
 
             ei_dogleg<Scalar>(R, diag, qtf, delta, wa1);
 
-            /*           store the direction p and x + p. calculate the norm of p. */
+            /* 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. */
+            /* 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. */
+            /* evaluate the function at x + p and calculate its norm. */
 
             iflag = Functor::f(wa2, wa4);
             ++nfev;
@@ -185,13 +185,13 @@ int ei_hybrj(
                 goto L300;
             fnorm1 = wa4.stableNorm();
 
-            /*           compute the scaled actual reduction. */
+            /* compute the scaled actual reduction. */
 
             actred = -1.;
             if (fnorm1 < fnorm) /* Computing 2nd power */
                 actred = 1. - ei_abs2(fnorm1 / fnorm);
 
-            /*           compute the scaled predicted reduction. */
+            /* compute the scaled predicted reduction. */
 
             l = 0;
             for (i = 0; i < n; ++i) {
@@ -207,14 +207,14 @@ int ei_hybrj(
             if (temp < fnorm) /* Computing 2nd power */
                 prered = 1. - ei_abs2(temp / fnorm);
 
-            /*           compute the ratio of the actual to the predicted */
-            /*           reduction. */
+            /* compute the ratio of the actual to the predicted */
+            /* reduction. */
 
             ratio = 0.;
             if (prered > 0.)
                 ratio = actred / prered;
 
-            /*           update the step bound. */
+            /* update the step bound. */
 
             if (ratio < Scalar(.1)) {
                 ncsuc = 0;
@@ -230,10 +230,10 @@ int ei_hybrj(
                 }
             }
 
-            /*           test for successful iteration. */
+            /* test for successful iteration. */
 
             if (ratio >= Scalar(1e-4)) {
-                /*           successful iteration. update x, fvec, and their norms. */
+                /* successful iteration. update x, fvec, and their norms. */
                 x = wa2;
                 wa2 = diag.cwise() * x;
                 fvec = wa4;
@@ -242,7 +242,7 @@ int ei_hybrj(
                 ++iter;
             }
 
-            /*           determine the progress of the iteration. */
+            /* determine the progress of the iteration. */
 
             ++nslow1;
             if (actred >= Scalar(.001))
@@ -252,14 +252,14 @@ int ei_hybrj(
             if (actred >= Scalar(.1))
                 nslow2 = 0;
 
-            /*           test for convergence. */
+            /* test for convergence. */
 
             if (delta <= xtol * xnorm || fnorm == 0.)
                 info = 1;
             if (info != 0)
                 goto L300;
 
-            /*           tests for termination and stringent tolerances. */
+            /* tests for termination and stringent tolerances. */
 
             if (nfev >= maxfev)
                 info = 2;
@@ -273,13 +273,13 @@ int ei_hybrj(
             if (info != 0)
                 goto L300;
 
-            /*           criterion for recalculating jacobian. */
+            /* criterion for recalculating jacobian. */
 
             if (ncfail == 2)
                 break;
 
-            /*           calculate the rank one modification to the jacobian */
-            /*           and update qtf if necessary. */
+            /* calculate the rank one modification to the jacobian */
+            /* and update qtf if necessary. */
 
             for (j = 0; j < n; ++j) {
                 sum = wa4.dot(fjac.col(j));
@@ -289,17 +289,17 @@ int ei_hybrj(
                     qtf[j] = sum;
             }
 
-            /*           compute the qr factorization of the updated jacobian. */
+            /* compute the qr factorization of the updated jacobian. */
 
             ei_r1updt<Scalar>(n, n, R.data(), R.size(), wa1.data(), wa2.data(), wa3.data(), &sing);
             ei_r1mpyq<Scalar>(n, n, fjac.data(), fjac.rows(), wa2.data(), wa3.data());
             ei_r1mpyq<Scalar>(1, n, qtf.data(), 1, wa2.data(), wa3.data());
 
-            /*           end of the inner loop. */
+            /* end of the inner loop. */
 
             jeval = false;
         }
-        /*        end of the outer loop. */
+        /* end of the outer loop. */
     }
 L300:
     /*     termination, either normal or user imposed. */
diff --git a/unsupported/Eigen/src/NonLinear/lmder.h b/unsupported/Eigen/src/NonLinear/lmder.h
index d651da7d5..1f0e5b20b 100644
--- a/unsupported/Eigen/src/NonLinear/lmder.h
+++ b/unsupported/Eigen/src/NonLinear/lmder.h
@@ -46,8 +46,7 @@ int ei_lmder(
 
     /*     check the input parameters for errors. */
 
-    if (n <= 0 || m < n || ftol < 0. || xtol < 0. || 
-            gtol < 0. || maxfev <= 0 || factor <= 0.)
+    if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.)
         goto L300;
 
     if (mode == 2)
@@ -70,16 +69,16 @@ int ei_lmder(
 
     /*     beginning of the outer loop. */
 
-    while(true) {
+    while (true) {
 
-        /*        calculate the jacobian matrix. */
+        /* calculate the jacobian matrix. */
 
         iflag = Functor::df(x, fjac);
         ++njev;
         if (iflag < 0)
             break;
 
-        /*        if requested, call Functor::f to enable printing of iterates. */
+        /* if requested, call Functor::f to enable printing of iterates. */
 
         if (nprint > 0) {
             iflag = 0;
@@ -89,13 +88,13 @@ int ei_lmder(
                 break;
         }
 
-        /*        compute the qr factorization of the jacobian. */
+        /* compute the qr factorization of the jacobian. */
 
         ei_qrfac<Scalar>(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. */
+        /* on the first iteration and if mode is 1, scale according */
+        /* to the norms of the columns of the initial jacobian. */
 
         if (iter == 1) {
             if (mode != 2)
@@ -104,8 +103,10 @@ int ei_lmder(
                     if (wa2[j] == 0.)
                         diag[j] = 1.;
                 }
-            /*        on the first iteration, calculate the norm of the scaled x */
-            /*        and initialize the step bound delta. */
+
+            /* 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;
@@ -113,8 +114,8 @@ int ei_lmder(
                 delta = factor;
         }
 
-        /*        form (q transpose)*fvec and store the first n components in */
-        /*        qtf. */
+        /* form (q transpose)*fvec and store the first n components in */
+        /* qtf. */
 
         wa4 = fvec;
         for (j = 0; j < n; ++j) {
@@ -130,7 +131,7 @@ int ei_lmder(
             qtf[j] = wa4[j];
         }
 
-        /*        compute the norm of the scaled gradient. */
+        /* compute the norm of the scaled gradient. */
 
         gnorm = 0.;
         if (fnorm != 0.)
@@ -145,21 +146,21 @@ int ei_lmder(
                 }
             }
 
-        /*        test for convergence of the gradient norm. */
+        /* test for convergence of the gradient norm. */
 
-        if (gnorm <= gtol) {
+        if (gnorm <= gtol)
             info = 4;
-        }
         if (info != 0)
             break;
 
-        /*        rescale if necessary. */
+        /* rescale if necessary. */
 
         if (mode != 2) /* Computing MAX */
             diag = diag.cwise().max(wa2);
 
-        /*        beginning of the inner loop. */
+        /* beginning of the inner loop. */
         do {
+
             /* determine the levenberg-marquardt parameter. */
 
             ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
@@ -173,9 +174,8 @@ int ei_lmder(
 
             /* on the first iteration, adjust the initial step bound. */
 
-            if (iter == 1) {
+            if (iter == 1)
                 delta = std::min(delta,pnorm);
-            }
 
             /* evaluate the function at x + p and calculate its norm. */
 
@@ -198,9 +198,8 @@ int ei_lmder(
             for (j = 0; j < n; ++j) {
                 l = ipvt[j];
                 temp = wa1[l];
-                for (i = 0; i <= j; ++i) {
+                for (i = 0; i <= j; ++i)
                     wa3[i] += fjac(i,j) * temp;
-                }
             }
             temp1 = ei_abs2(wa3.stableNorm() / fnorm);
             temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
@@ -227,12 +226,9 @@ int ei_lmder(
                 /* Computing MIN */
                 delta = temp * std::min(delta, pnorm / Scalar(.1));
                 par /= temp;
-            }
-            else {
-                if (!(par != 0. && ratio < Scalar(.75))) {
-                    delta = pnorm / Scalar(.5);
-                    par = Scalar(.5) * par;
-                }
+            } else if (!(par != 0. && ratio < Scalar(.75))) {
+                delta = pnorm / Scalar(.5);
+                par = Scalar(.5) * par;
             }
 
             /* test for successful iteration. */
@@ -272,12 +268,11 @@ int ei_lmder(
                 goto L300;
             /* end of the inner loop. repeat if iteration unsuccessful. */
         } while (ratio < Scalar(1e-4));
-        /*        end of the outer loop. */
+        /* end of the outer loop. */
     }
 L300:
 
     /*     termination, either normal or user imposed. */
-
     if (iflag < 0)
         info = iflag;
     if (nprint > 0)
diff --git a/unsupported/Eigen/src/NonLinear/lmdif.h b/unsupported/Eigen/src/NonLinear/lmdif.h
index 42aefb32d..70d6b76bc 100644
--- a/unsupported/Eigen/src/NonLinear/lmdif.h
+++ b/unsupported/Eigen/src/NonLinear/lmdif.h
@@ -45,10 +45,8 @@ int ei_lmdif(
 
     /*     check the input parameters for errors. */
 
-    if (n <= 0 || m < n || ftol < 0. || xtol < 0. || 
-            gtol < 0. || maxfev <= 0 || factor <= 0.) {
+    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;
@@ -58,9 +56,8 @@ int ei_lmdif(
 
     iflag = Functor::f(x, fvec);
     nfev = 1;
-    if (iflag < 0) {
+    if (iflag < 0)
         goto L300;
-    }
     fnorm = fvec.stableNorm();
 
     /*     initialize levenberg-marquardt parameter and iteration counter. */
@@ -70,283 +67,214 @@ int ei_lmdif(
 
     /*     beginning of the outer loop. */
 
-L30:
-
-    /*        calculate the jacobian matrix. */
+    while (true) {
 
-    iflag = ei_fdjac2<Functor,Scalar>(x, fvec, fjac, epsfcn, wa4);
-    nfev += n;
-    if (iflag < 0) {
-        goto L300;
-    }
+        /* calculate the jacobian matrix. */
 
-    /*        if requested, call Functor::f to enable printing of iterates. */
+        iflag = ei_fdjac2<Functor,Scalar>(x, fvec, fjac, epsfcn, wa4);
+        nfev += n;
+        if (iflag < 0)
+            break;
 
-    if (nprint <= 0) {
-        goto L40;
-    }
-    iflag = 0;
-    if ((iter - 1) % nprint == 0) {
-        iflag = Functor::debug(x, fvec);
-    }
-    if (iflag < 0) {
-        goto L300;
-    }
-L40:
+        /* if requested, call Functor::f to enable printing of iterates. */
 
-    /*        compute the qr factorization of the jacobian. */
-
-    ei_qrfac<Scalar>(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.;
+        if (nprint > 0) {
+            iflag = 0;
+            if ((iter - 1) % nprint == 0)
+                iflag = Functor::debug(x, fvec);
+            if (iflag < 0)
+                break;
         }
-        /* L50: */
-    }
-L60:
 
-    /*        on the first iteration, calculate the norm of the scaled x */
-    /*        and initialize the step bound delta. */
+        /* compute the qr factorization of the jacobian. */
 
-    wa3 = diag.cwise() * x;
-    xnorm = wa3.stableNorm();
-    delta = factor * xnorm;
-    if (delta == 0.) {
-        delta = factor;
-    }
-L80:
+        ei_qrfac<Scalar>(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)
 
-    /*        form (q transpose)*fvec and store the first n components in */
-    /*        qtf. */
+        /* on the first iteration and if mode is 1, scale according */
+        /* to the norms of the columns of the initial jacobian. */
 
-    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: */
-    }
+        if (iter == 1) {
+            if (mode != 2)
+                for (j = 0; j < n; ++j) {
+                    diag[j] = wa2[j];
+                    if (wa2[j] == 0.)
+                        diag[j] = 1.;
+                }
 
-    /*        compute the norm of the scaled gradient. */
+            /* on the first iteration, calculate the norm of the scaled x */
+            /* and initialize the step bound delta. */
 
-    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]));
+            wa3 = diag.cwise() * x;
+            xnorm = wa3.stableNorm();
+            delta = factor * xnorm;
+            if (delta == 0.)
+                delta = factor;
         }
-    }
-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<Scalar>(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: */
+        /* 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.) {
+                sum = 0.;
+                for (i = j; i < m; ++i)
+                    sum += fjac(i,j) * wa4[i];
+                temp = -sum / fjac(j,j);
+                for (i = j; i < m; ++i)
+                    wa4[i] += fjac(i,j) * temp;
+            }
+            fjac(j,j) = wa1[j];
+            qtf[j] = wa4[j];
         }
-        /* 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. */
+        /* compute the norm of the scaled gradient. */
 
-    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;
+        gnorm = 0.;
+        if (fnorm != 0.)
+            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]));
+                }
+            }
+
+        /* test for convergence of the gradient norm. */
+
+        if (gnorm <= gtol)
+            info = 4;
+        if (info != 0)
+            break;
+
+        /* rescale if necessary. */
+
+        if (mode != 2) /* Computing MAX */
+            diag = diag.cwise().max(wa2);
+
+        /* beginning of the inner loop. */
+        do {
+
+            /* determine the levenberg-marquardt parameter. */
+
+            ei_lmpar<Scalar>(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;
+            }
+            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)) {
+                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;
+            } else if (!(par != 0. && ratio < Scalar(.75))) {
+                delta = pnorm / Scalar(.5);
+                par = Scalar(.5) * par;
+            }
+
+            /* test for successful iteration. */
+
+            if (ratio >= Scalar(1e-4)) {
+                /* successful iteration. update x, fvec, and their norms. */
+                x = wa2;
+                wa2 = diag.cwise() * x;
+                fvec = wa4;
+                xnorm = wa2.stableNorm();
+                fnorm = fnorm1;
+                ++iter;
+            }
+
+            /* 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<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.)
+                info = 6;
+            if (delta <= epsilon<Scalar>() * xnorm)
+                info = 7;
+            if (gnorm <= epsilon<Scalar>())
+                info = 8;
+            if (info != 0)
+                goto L300;
+            /* end of the inner loop. repeat if iteration unsuccessful. */
+        } while (ratio < Scalar(1e-4));
+        /* end of the outer loop. */
     }
-    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<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.) {
-        info = 6;
-    }
-    if (delta <= epsilon<Scalar>() * xnorm) {
-        info = 7;
-    }
-    if (gnorm <= epsilon<Scalar>()) {
-        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) {
+    if (iflag < 0)
         info = iflag;
-    }
-    iflag = 0;
-    if (nprint > 0) {
+    if (nprint > 0)
         iflag = Functor::debug(x, fvec);
-    }
     return info;
 }
 
diff --git a/unsupported/Eigen/src/NonLinear/lmstr.h b/unsupported/Eigen/src/NonLinear/lmstr.h
index dab5f8c4d..ed516e5aa 100644
--- a/unsupported/Eigen/src/NonLinear/lmstr.h
+++ b/unsupported/Eigen/src/NonLinear/lmstr.h
@@ -46,22 +46,19 @@ int ei_lmstr(
 
     /*     check the input parameters for errors. */
 
-    if (n <= 0 || m < n || ftol < 0. || xtol < 0. || 
-            gtol < 0. || maxfev <= 0 || factor <= 0.) {
+    if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.)
         goto L340;
-    }
     if (mode == 2)
         for (j = 0; j < n; ++j)
-            if (diag[j] <= 0.) goto L300;
+            if (diag[j] <= 0.) goto L340;
 
     /*     evaluate the function at the starting point */
     /*     and calculate its norm. */
 
     iflag = Functor::f(x, fvec);
     nfev = 1;
-    if (iflag < 0) {
+    if (iflag < 0)
         goto L340;
-    }
     fnorm = fvec.stableNorm();
 
     /*     initialize levenberg-marquardt parameter and iteration counter. */
@@ -71,297 +68,230 @@ int ei_lmstr(
 
     /*     beginning of the outer loop. */
 
-L30:
-
-    /*        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, wa3);
-    }
-    if (iflag < 0) {
-        goto L340;
-    }
-L40:
-
-    /*        compute the qr factorization of the jacobian matrix */
-    /*        calculated one row at a time, while simultaneously */
-    /*        forming (q transpose)*fvec and storing the first */
-    /*        n components in qtf. */
-
-    qtf.fill(0.);
-    fjac.fill(0.);
-    iflag = 2;
-    for (i = 0; i < m; ++i) {
-        if (Functor::df(x, wa3, iflag) < 0)
-            goto L340;
-        temp = fvec[i];
-        ei_rwupdt<Scalar>(n, fjac.data(), fjac.rows(), wa3.data(), qtf.data(), &temp, wa1.data(), wa2.data());
-        ++iflag;
-    }
-    ++njev;
+    while (true) {
 
-    /*        if the jacobian is rank deficient, call qrfac to */
-    /*        reorder its columns and update the components of qtf. */
+        /* if requested, call Functor::f to enable printing of iterates. */
 
-    sing = false;
-    for (j = 0; j < n; ++j) {
-        if (fjac(j,j) == 0.) {
-            sing = true;
+        if (nprint > 0) {
+            iflag = 0;
+            if ((iter - 1) % nprint == 0)
+                iflag = Functor::debug(x, fvec, wa3);
+            if (iflag < 0)
+                break;
         }
-        ipvt[j] = j;
-        wa2[j] = fjac.col(j).start(j).stableNorm();
-    }
-    if (! sing)
-        goto L130;
-    ipvt.cwise()+=1;
-    ei_qrfac<Scalar>(n, 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)
-    for (j = 0; j < n; ++j) {
-        if (fjac(j,j) == 0.)
-            goto L110;
-        sum = 0.;
-        for (i = j; i < n; ++i) {
-            sum += fjac(i,j) * qtf[i];
-        }
-        temp = -sum / fjac(j,j);
-        for (i = j; i < n; ++i) {
-            qtf[i] += fjac(i,j) * temp;
-        }
-L110:
-        fjac(j,j) = 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;
-    }
-    for (j = 0; j < n; ++j) {
-        diag[j] = wa2[j];
-        if (wa2[j] == 0.) {
-            diag[j] = 1.;
+        /* compute the qr factorization of the jacobian matrix */
+        /* calculated one row at a time, while simultaneously */
+        /* forming (q transpose)*fvec and storing the first */
+        /* n components in qtf. */
+
+        qtf.fill(0.);
+        fjac.fill(0.);
+        iflag = 2;
+        for (i = 0; i < m; ++i) {
+            if (Functor::df(x, wa3, iflag) < 0)
+                break;
+            temp = fvec[i];
+            ei_rwupdt<Scalar>(n, fjac.data(), fjac.rows(), wa3.data(), qtf.data(), &temp, wa1.data(), wa2.data());
+            ++iflag;
         }
-        /* L140: */
-    }
-L150:
-
-    /*        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;
-    }
-L170:
-
-    /*        compute the norm of the scaled gradient. */
-
-    gnorm = 0.;
-    if (fnorm == 0.) {
-        goto L210;
-    }
-    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]));
+        ++njev;
+
+        /* if the jacobian is rank deficient, call qrfac to */
+        /* reorder its columns and update the components of qtf. */
+
+        sing = false;
+        for (j = 0; j < n; ++j) {
+            if (fjac(j,j) == 0.) {
+                sing = true;
+            }
+            ipvt[j] = j;
+            wa2[j] = fjac.col(j).start(j).stableNorm();
         }
-    }
-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;
-    }
-    /* Computing MAX */
-    diag = diag.cwise().max(wa2);
-L230:
-
-    /*        beginning of the inner loop. */
-
-L240:
-
-    /*           determine the levenberg-marquardt parameter. */
-
-    ei_lmpar<Scalar>(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 L340;
-    }
-    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;
-            /* L260: */
+        if (sing) {
+            ipvt.cwise()+=1;
+            ei_qrfac<Scalar>(n, 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)
+            for (j = 0; j < n; ++j) {
+                if (fjac(j,j) != 0.) {
+                    sum = 0.;
+                    for (i = j; i < n; ++i)
+                        sum += fjac(i,j) * qtf[i];
+                    temp = -sum / fjac(j,j);
+                    for (i = j; i < n; ++i)
+                        qtf[i] += fjac(i,j) * temp;
+                }
+                fjac(j,j) = wa1[j];
+            }
         }
-        /* L270: */
-    }
-    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 L280;
-    }
-    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 L300;
-L280:
-    if (par != 0. && ratio < Scalar(.75)) {
-        goto L290;
-    }
-    delta = pnorm / Scalar(.5);
-    par = Scalar(.5) * par;
-L290:
-L300:
-
-    /*           test for successful iteration. */
-
-    if (ratio < Scalar(1e-4)) {
-        goto L330;
-    }
-
-    /*           successful iteration. update x, fvec, and their norms. */
-
-    x = wa2;
-    wa2 = diag.cwise() * x;
-    fvec = wa4;
-    xnorm = wa2.stableNorm();
-    fnorm = fnorm1;
-    ++iter;
-L330:
 
-    /*           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 L340;
-    }
-
-    /*           tests for termination and stringent tolerances. */
-
-    if (nfev >= maxfev) {
-        info = 5;
-    }
-    if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.) {
-        info = 6;
-    }
-    if (delta <= epsilon<Scalar>() * xnorm) {
-        info = 7;
-    }
-    if (gnorm <= epsilon<Scalar>()) {
-        info = 8;
-    }
-    if (info != 0) {
-        goto L340;
-    }
+        /* on the first iteration and if mode is 1, scale according */
+        /* to the norms of the columns of the initial jacobian. */
+
+        if (iter == 1) {
+            if (mode != 2)
+                for (j = 0; j < n; ++j) {
+                    diag[j] = wa2[j];
+                    if (wa2[j] == 0.)
+                        diag[j] = 1.;
+                }
+
+            /* 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;
+        }
 
-    /*           end of the inner loop. repeat if iteration unsuccessful. */
+        /* compute the norm of the scaled gradient. */
 
-    if (ratio < Scalar(1e-4)) {
-        goto L240;
+        gnorm = 0.;
+        if (fnorm != 0.)
+            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]));
+                }
+            }
+
+        /* test for convergence of the gradient norm. */
+
+        if (gnorm <= gtol)
+            info = 4;
+        if (info != 0)
+            break;
+
+        /* rescale if necessary. */
+
+        if (mode != 2) /* Computing MAX */
+            diag = diag.cwise().max(wa2);
+
+        /* beginning of the inner loop. */
+        do {
+
+            /* determine the levenberg-marquardt parameter. */
+
+            ei_lmpar<Scalar>(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 L340;
+            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;
+            }
+            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)) {
+                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;
+            } else if (!(par != 0. && ratio < Scalar(.75))) {
+                delta = pnorm / Scalar(.5);
+                par = Scalar(.5) * par;
+            }
+
+            /* test for successful iteration. */
+
+            if (ratio >= Scalar(1e-4)) {
+                /* successful iteration. update x, fvec, and their norms. */
+                x = wa2;
+                wa2 = diag.cwise() * x;
+                fvec = wa4;
+                xnorm = wa2.stableNorm();
+                fnorm = fnorm1;
+                ++iter;
+            }
+
+            /* 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 L340;
+
+            /* tests for termination and stringent tolerances. */
+
+            if (nfev >= maxfev)
+                info = 5;
+            if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.)
+                info = 6;
+            if (delta <= epsilon<Scalar>() * xnorm)
+                info = 7;
+            if (gnorm <= epsilon<Scalar>())
+                info = 8;
+            if (info != 0)
+                goto L340;
+            /* end of the inner loop. repeat if iteration unsuccessful. */
+        } while (ratio < Scalar(1e-4));
+        /* end of the outer loop. */
     }
-
-    /*        end of the outer loop. */
-
-    goto L30;
 L340:
 
     /*     termination, either normal or user imposed. */
-
-    if (iflag < 0) {
+    if (iflag < 0)
         info = iflag;
-    }
-    iflag = 0;
-    if (nprint > 0) {
+    if (nprint > 0)
         iflag = Functor::debug(x, fvec, wa3);
-    }
     return info;
 }