merge both c methods lmdif/lmdif1 into one class

LevenbergMarquardtNumericalDiff with two methods.

unsupported/Eigen/NonLinear

@@ -54,7 +54,6 @@ namespace Eigen {
 #include "src/NonLinear/lmdif.h"
 #include "src/NonLinear/hybrj.h"
 #include "src/NonLinear/lmstr1.h"
-#include "src/NonLinear/lmdif1.h"
 #include "src/NonLinear/chkder.h"
 
 //@}

unsupported/Eigen/src/NonLinear/lmdif.h

@@ -1,7 +1,19 @@
 
+
 template<typename FunctorType, typename Scalar>
-int ei_lmdif(
+class LevenbergMarquardtNumericalDiff 
-        const FunctorType &Functor,
+{
+public:
+    LevenbergMarquardtNumericalDiff(const FunctorType &_functor)
+        : functor(_functor) {}
+
+    int minimize(
+            Matrix< Scalar, Dynamic, 1 >  &x,
+            Matrix< Scalar, Dynamic, 1 >  &fvec,
+            const Scalar tol = ei_sqrt(epsilon<Scalar>())
+            );
+
+    int minimize(
             Matrix< Scalar, Dynamic, 1 >  &x,
             Matrix< Scalar, Dynamic, 1 >  &fvec,
             int &nfev,
@@ -17,6 +29,61 @@ int ei_lmdif(
             Scalar gtol = Scalar(0.),
             Scalar epsfcn = Scalar(0.),
             int nprint=0
+            );
+
+private:
+    const FunctorType &functor;
+};
+
+
+template<typename FunctorType, typename Scalar>
+int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
+        Matrix< Scalar, Dynamic, 1 >  &x,
+        Matrix< Scalar, Dynamic, 1 >  &fvec,
+        Scalar tol
+        )
+{
+    const int n = x.size(), m=fvec.size();
+    int info, nfev=0;
+    Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
+    Matrix< Scalar, Dynamic, 1> diag, qtf;
+    VectorXi ipvt;
+
+    /* check the input parameters for errors. */
+    if (n <= 0 || m < n || tol < 0.) {
+        printf("ei_lmder1 bad args : m,n,tol,...");
+        return 0;
+    }
+
+    info = minimize(
+        x, fvec,
+        nfev,
+        fjac, ipvt, qtf, diag,
+        1,
+        100.,
+        (n+1)*200,
+        tol, tol, Scalar(0.), Scalar(0.)
+    );
+    return (info==8)?4:info;
+}
+
+template<typename FunctorType, typename Scalar>
+int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
+        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,
+        Scalar factor,
+        int maxfev,
+        Scalar ftol,
+        Scalar xtol,
+        Scalar gtol,
+        Scalar epsfcn,
+        int nprint
         )
 {
     const int m = fvec.size(), n = x.size();
@@ -55,7 +122,7 @@ int ei_lmdif(
     /*     evaluate the function at the starting point */
     /*     and calculate its norm. */
 
-    iflag = Functor.f(x, fvec);
+    iflag = functor.f(x, fvec);
     nfev = 1;
     if (iflag < 0)
         goto algo_end;
@@ -72,17 +139,17 @@ int ei_lmdif(
 
         /* calculate the jacobian matrix. */
 
-        iflag = ei_fdjac2(Functor, x, fvec, fjac, epsfcn);
+        iflag = ei_fdjac2(functor, x, fvec, fjac, epsfcn);
         nfev += n;
         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;
             if ((iter - 1) % nprint == 0)
-                iflag = Functor.debug(x, fvec);
+                iflag = functor.debug(x, fvec);
             if (iflag < 0)
                 break;
         }
@@ -178,7 +245,7 @@ int ei_lmdif(
 
             /* evaluate the function at x + p and calculate its norm. */
 
-            iflag = Functor.f(wa2, wa4);
+            iflag = functor.f(wa2, wa4);
             ++nfev;
             if (iflag < 0)
                 goto algo_end;
@@ -275,7 +342,7 @@ algo_end:
     if (iflag < 0)
         info = iflag;
     if (nprint > 0)
-        iflag = Functor.debug(x, fvec);
+        iflag = functor.debug(x, fvec);
     return info;
 }
 

unsupported/Eigen/src/NonLinear/lmdif1.h

@@ -1,34 +0,0 @@
-
-template<typename FunctorType, typename Scalar>
-int ei_lmdif1(
-        const FunctorType &Functor,
-        Matrix< Scalar, Dynamic, 1 >  &x,
-        Matrix< Scalar, Dynamic, 1 >  &fvec,
-        Scalar tol = ei_sqrt(epsilon<Scalar>())
-        )
-{
-    const int n = x.size(), m=fvec.size();
-    int info, nfev=0;
-    Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
-    Matrix< Scalar, Dynamic, 1> diag, qtf;
-    VectorXi ipvt;
-
-    /* check the input parameters for errors. */
-    if (n <= 0 || m < n || tol < 0.) {
-        printf("ei_lmder1 bad args : m,n,tol,...");
-        return 0;
-    }
-
-    info = ei_lmdif(
-        Functor,
-        x, fvec,
-        nfev,
-        fjac, ipvt, qtf, diag,
-        1,
-        100.,
-        (n+1)*200,
-        tol, tol, Scalar(0.), Scalar(0.)
-    );
-    return (info==8)?4:info;
-}
-

unsupported/test/NonLinear.cpp

@@ -541,7 +541,9 @@ void testLmdif1()
   x.setConstant(n, 1.);
 
   // do the computation
-  info = ei_lmdif1(lmdif_functor(), x, fvec);
+  lmdif_functor functor;
+  LevenbergMarquardtNumericalDiff<lmdif_functor,double> lm(functor);
+  info = lm.minimize(x, fvec);
 
   // check return value
   VERIFY( 1 == info);
@@ -569,7 +571,9 @@ void testLmdif()
   x.setConstant(n, 1.);
 
   // do the computation
-  info = ei_lmdif(lmdif_functor(), x, fvec, nfev, fjac, ipvt, qtf, diag);
+  lmdif_functor functor;
+  LevenbergMarquardtNumericalDiff<lmdif_functor,double> lm(functor);
+  info = lm.minimize(x, fvec, nfev, fjac, ipvt, qtf, diag);
 
   // check return values
   VERIFY( 1 == info);