useless cleaning

unsupported/Eigen/src/NonLinearOptimization/dogleg.h

@@ -118,7 +118,5 @@ algo_end:
 
     temp = (1.-alpha) * std::min(sgnorm,delta);
     x = temp * wa1 + alpha * x;
-    return;
-
 }
 

unsupported/Eigen/src/NonLinearOptimization/fdjac1.h

@@ -22,7 +22,7 @@ int ei_fdjac1(
     Matrix< Scalar, Dynamic, 1 >  wa1(n);
     Matrix< Scalar, Dynamic, 1 >  wa2(n);
 
-    eps = ei_sqrt((std::max(epsfcn,epsmch)));
+    eps = ei_sqrt(std::max(epsfcn,epsmch));
     msum = ml + mu + 1;
     if (msum >= n) {
         /* computation of dense approximate jacobian. */
@@ -49,18 +49,16 @@ int ei_fdjac1(
                 x[j] = wa2[j] + h;
             }
             iflag = Functor(x, wa1);
-            if (iflag < 0) {
+            if (iflag < 0)
                 return iflag;
-            }
             for (j = k; msum< 0 ? j > n: j < n; j += msum) {
                 x[j] = wa2[j];
                 h = eps * ei_abs(wa2[j]);
                 if (h == 0.) h = eps;
                 for (i = 0; i < n; ++i) {
                     fjac(i,j) = 0.;
-                    if (i >= j - mu && i <= j + ml) {
+                    if (i >= j - mu && i <= j + ml)
                         fjac(i,j) = (wa1[i] - fvec[i]) / h;
-                    }
                 }
             }
         }

unsupported/Eigen/src/NonLinearOptimization/qform.h

@@ -7,7 +7,7 @@ void ei_qform(int m, int n, Scalar *q, int
     int q_dim1, q_offset;
 
     /* Local variables */
-    int i, j, k, l, jm1, np1;
+    int i, j, k, l;
     Scalar sum, temp;
     int minmn;
 
@@ -22,34 +22,18 @@ void ei_qform(int m, int n, Scalar *q, int
     /*     zero out upper triangle of q in the first min(m,n) columns. */
 
     minmn = std::min(m,n);
-    if (minmn < 2) {
-        goto L30;
-    }
     for (j = 2; j <= minmn; ++j) {
-        jm1 = j - 1;
+        for (i = 1; i <= j-1; ++i)
-        for (i = 1; i <= jm1; ++i) {
             q[i + j * q_dim1] = 0.;
-            /* L10: */
-        }
-        /* L20: */
     }
-L30:
 
     /*     initialize remaining columns to those of the identity matrix. */
 
-    np1 = n + 1;
+    for (j = n+1; j <= m; ++j) {
-    if (m < np1) {
+        for (i = 1; i <= m; ++i)
-        goto L60;
-    }
-    for (j = np1; j <= m; ++j) {
-        for (i = 1; i <= m; ++i) {
             q[i + j * q_dim1] = 0.;
-            /* L40: */
-        }
         q[j + j * q_dim1] = 1.;
-        /* L50: */
     }
-L60:
 
     /*     accumulate q from its factored form. */
 
@@ -58,32 +42,19 @@ L60:
         for (i = k; i <= m; ++i) {
             wa[i] = q[i + k * q_dim1];
             q[i + k * q_dim1] = 0.;
-            /* L70: */
         }
         q[k + k * q_dim1] = 1.;
-        if (wa[k] == 0.) {
+        if (wa[k] == 0.)
-            goto L110;
+            continue;
-        }
         for (j = k; j <= m; ++j) {
             sum = 0.;
-            for (i = k; i <= m; ++i) {
+            for (i = k; i <= m; ++i)
                 sum += q[i + j * q_dim1] * wa[i];
-                /* L80: */
-            }
             temp = sum / wa[k];
-            for (i = k; i <= m; ++i) {
+            for (i = k; i <= m; ++i)
                 q[i + j * q_dim1] -= temp * wa[i];
-                /* L90: */
-            }
-            /* L100: */
         }
-L110:
-        /* L120: */
-        ;
     }
-    return;
 
-    /*     last card of subroutine qform. */
+}
-
-} /* qform_ */
 

unsupported/Eigen/src/NonLinearOptimization/qrfac.h

@@ -39,22 +39,17 @@ void ei_qrfac(int m, int n, Scalar *a, int
 
     minmn = std::min(m,n);
     for (j = 1; j <= minmn; ++j) {
-        if (! (pivot)) {
+        if (! (pivot))
             goto L40;
-        }
 
         /*        bring the column of largest norm into the pivot position. */
 
         kmax = j;
-        for (k = j; k <= n; ++k) {
+        for (k = j; k <= n; ++k)
-            if (rdiag[k] > rdiag[kmax]) {
+            if (rdiag[k] > rdiag[kmax])
                 kmax = k;
-            }
+        if (kmax == j)
-            /* L20: */
-        }
-        if (kmax == j) {
             goto L40;
-        }
         for (i = 1; i <= m; ++i) {
             temp = a[i + j * a_dim1];
             a[i + j * a_dim1] = a[i + kmax * a_dim1];
@@ -72,60 +67,39 @@ L40:
         /*        j-th column of a to a multiple of the j-th unit vector. */
 
         ajnorm = Map< Matrix< Scalar, Dynamic, 1 > >(&a[j + j * a_dim1],m-j+1).blueNorm();
-        if (ajnorm == 0.) {
+        if (ajnorm == 0.)
             goto L100;
-        }
+        if (a[j + j * a_dim1] < 0.)
-        if (a[j + j * a_dim1] < 0.) {
             ajnorm = -ajnorm;
-        }
+        for (i = j; i <= m; ++i)
-        for (i = j; i <= m; ++i) {
             a[i + j * a_dim1] /= ajnorm;
-            /* L50: */
-        }
         a[j + j * a_dim1] += 1.;
 
         /*        apply the transformation to the remaining columns */
         /*        and update the norms. */
 
         jp1 = j + 1;
-        if (n < jp1) {
-            goto L100;
-        }
         for (k = jp1; k <= n; ++k) {
             sum = 0.;
-            for (i = j; i <= m; ++i) {
+            for (i = j; i <= m; ++i)
                 sum += a[i + j * a_dim1] * a[i + k * a_dim1];
-                /* L60: */
-            }
             temp = sum / a[j + j * a_dim1];
-            for (i = j; i <= m; ++i) {
+            for (i = j; i <= m; ++i)
                 a[i + k * a_dim1] -= temp * a[i + j * a_dim1];
-                /* L70: */
+            if (! (pivot) || rdiag[k] == 0.)
-            }
+                continue;
-            if (! (pivot) || rdiag[k] == 0.) {
-                goto L80;
-            }
             temp = a[j + k * a_dim1] / rdiag[k];
             /* Computing MAX */
             /* Computing 2nd power */
             rdiag[k] *= ei_sqrt((std::max(Scalar(0.), Scalar(1.)-ei_abs2(temp))));
             /* Computing 2nd power */
-            if (Scalar(.05) * ei_abs2(rdiag[k] / wa[k]) > epsmch) {
+            if (Scalar(.05) * ei_abs2(rdiag[k] / wa[k]) > epsmch)
-                goto L80;
+                continue;
-            }
             rdiag[k] = Map< Matrix< Scalar, Dynamic, 1 > >(&a[jp1 + k * a_dim1],m-j).blueNorm();
             wa[k] = rdiag[k];
-L80:
-            /* L90: */
-            ;
         }
 L100:
         rdiag[j] = -ajnorm;
-        /* L110: */
     }
-    return;
+}
-
-    /*     last card of subroutine qrfac. */
-
-} /* qrfac_ */