remove the boring, old-school nprint option, we'll have a dedicated

method for 'one iteration' anyway.

unsupported/Eigen/src/NonLinear/hybrd.h

@@ -20,8 +20,7 @@ public:
             const int maxfev = 2000,
             const Scalar factor = Scalar(100.),
             const Scalar xtol = ei_sqrt(epsilon<Scalar>()),
-            const Scalar epsfcn = Scalar(0.),
+            const Scalar epsfcn = Scalar(0.)
-            const int nprint=0
             );
 
     Matrix< Scalar, Dynamic, 1 >  fvec;
@@ -76,8 +75,7 @@ int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
         const int maxfev,
         const Scalar factor,
         const Scalar xtol,
-        const Scalar epsfcn,
+        const Scalar epsfcn
-        const int nprint
         )
 {
     const int n = x.size();
@@ -225,15 +223,6 @@ int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
         /* beginning of the inner loop. */
 
         while (true) {
-            /* if requested, call functor.f to enable printing of iterates. */
-
-            if (nprint > 0) {
-                iflag = 0;
-                if ((iter - 1) % nprint == 0)
-                    iflag = functor.debug(x, fvec);
-                if (iflag < 0)
-                    goto algo_end;
-            }
 
             /* determine the direction p. */
 
@@ -380,8 +369,6 @@ algo_end:
     /*     termination, either normal or user imposed. */
     if (iflag < 0)
         info = iflag;
-    if (nprint > 0)
-        iflag = functor.debug(x, fvec);
     return info;
 }
 

unsupported/Eigen/src/NonLinear/hybrj.h

@@ -17,8 +17,7 @@ public:
             const int mode=1,
             const int maxfev = 1000,
             const Scalar factor = Scalar(100.),
-            const Scalar xtol = ei_sqrt(epsilon<Scalar>()),
+            const Scalar xtol = ei_sqrt(epsilon<Scalar>())
-            const int nprint=0
             );
 
     Matrix< Scalar, Dynamic, 1 >  fvec;
@@ -71,8 +70,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
         const int mode,
         const int maxfev,
         const Scalar factor,
-        const Scalar xtol,
+        const Scalar xtol
-        const int nprint
         )
 {
     const int n = x.size();
@@ -211,15 +209,6 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
         /* beginning of the inner loop. */
 
         while (true) {
-            /* if requested, call functor.f to enable printing of iterates. */
-
-            if (nprint > 0) {
-                iflag = 0;
-                if ((iter - 1) % nprint == 0)
-                    iflag = functor.debug(x, fvec, fjac);
-                if (iflag < 0)
-                    goto algo_end;
-            }
 
             /* determine the direction p. */
 
@@ -365,8 +354,6 @@ algo_end:
     /*     termination, either normal or user imposed. */
     if (iflag < 0)
         info = iflag;
-    if (nprint > 0)
-        iflag = functor.debug(x, fvec, fjac);
     return info;
 }
 

unsupported/Eigen/src/NonLinear/lmder.h

@@ -21,8 +21,7 @@ public:
             const int maxfev = 400,
             const Scalar ftol = ei_sqrt(epsilon<Scalar>()),
             const Scalar xtol = ei_sqrt(epsilon<Scalar>()),
-            const Scalar gtol = Scalar(0.),
+            const Scalar gtol = Scalar(0.)
-            const int nprint=0
             );
 
     Matrix< Scalar, Dynamic, 1 >  fvec;
@@ -77,8 +76,7 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
         const int maxfev,
         const Scalar ftol,
         const Scalar xtol,
-        const Scalar gtol,
+        const Scalar gtol
-        const int nprint
         )
 {
     const int n = x.size();
@@ -143,16 +141,6 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
         if (iflag < 0)
             break;
 
-        /* if requested, call functor.f to enable printing of iterates. */
-
-        if (nprint > 0) {
-            iflag = 0;
-            if ((iter - 1) % nprint == 0)
-                iflag = functor.debug(x, fvec, fjac);
-            if (iflag < 0)
-                break;
-        }
-
         /* compute the qr factorization of the jacobian. */
 
         ei_qrfac<Scalar>(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
@@ -340,7 +328,5 @@ algo_end:
     /*     termination, either normal or user imposed. */
     if (iflag < 0)
         info = iflag;
-    if (nprint > 0)
-        iflag = functor.debug(x, fvec, fjac);
     return info;
 }

unsupported/Eigen/src/NonLinear/lmdif.h

@@ -21,8 +21,7 @@ public:
             const Scalar ftol = ei_sqrt(epsilon<Scalar>()),
             const Scalar xtol = ei_sqrt(epsilon<Scalar>()),
             const Scalar gtol = Scalar(0.),
-            const Scalar epsfcn = Scalar(0.),
+            const Scalar epsfcn = Scalar(0.)
-            const int nprint=0
             );
 
     Matrix< Scalar, Dynamic, 1 >  fvec;
@@ -76,8 +75,7 @@ int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
         const Scalar ftol,
         const Scalar xtol,
         const Scalar gtol,
-        const Scalar epsfcn,
+        const Scalar epsfcn
-        const int nprint
         )
 {
     const int n = x.size();
@@ -140,16 +138,6 @@ int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
         if (iflag < 0)
             break;
 
-        /* if requested, call functor.f to enable printing of iterates. */
-
-        if (nprint > 0) {
-            iflag = 0;
-            if ((iter - 1) % nprint == 0)
-                iflag = functor.debug(x, fvec);
-            if (iflag < 0)
-                break;
-        }
-
         /* compute the qr factorization of the jacobian. */
 
         ei_qrfac<Scalar>(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
@@ -337,8 +325,6 @@ algo_end:
     /*     termination, either normal or user imposed. */
     if (iflag < 0)
         info = iflag;
-    if (nprint > 0)
-        iflag = functor.debug(x, fvec);
     return info;
 }
 

unsupported/Eigen/src/NonLinear/lmstr.h

@@ -21,8 +21,7 @@ public:
             const int maxfev = 400,
             const Scalar ftol = ei_sqrt(epsilon<Scalar>()),
             const Scalar xtol = ei_sqrt(epsilon<Scalar>()),
-            const Scalar gtol = Scalar(0.),
+            const Scalar gtol = Scalar(0.)
-            const int nprint=0
             );
 
     Matrix< Scalar, Dynamic, 1 >  fvec;
@@ -76,8 +75,7 @@ int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
         const int maxfev,
         const Scalar ftol,
         const Scalar xtol,
-        const Scalar gtol,
+        const Scalar gtol
-        const int nprint
         )
 {
     const int n = x.size();
@@ -135,16 +133,6 @@ int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
 
     while (true) {
 
-        /* if requested, call functor.f to enable printing of iterates. */
-
-        if (nprint > 0) {
-            iflag = 0;
-            if ((iter - 1) % nprint == 0)
-                iflag = functor.debug(x, fvec, wa3);
-            if (iflag < 0)
-                break;
-        }
-
         /* compute the qr factorization of the jacobian matrix */
         /* calculated one row at a time, while simultaneously */
         /* forming (q transpose)*fvec and storing the first */
@@ -355,8 +343,6 @@ algo_end:
     /*     termination, either normal or user imposed. */
     if (iflag < 0)
         info = iflag;
-    if (nprint > 0)
-        iflag = functor.debug(x, fvec, wa3);
     return info;
 }