merge both c methods lmstr/lmstr1 into one class

LevenbergMarquardtOptimumStorage with two methods.

unsupported/Eigen/NonLinear

@@ -48,13 +48,13 @@ namespace Eigen {
 #include "src/NonLinear/dogleg.h"
 #include "src/NonLinear/covar.h"
 
+#include "src/NonLinear/chkder.h"
+
 #include "src/NonLinear/lmder.h"
 #include "src/NonLinear/hybrd.h"
 #include "src/NonLinear/lmstr.h"
 #include "src/NonLinear/lmdif.h"
 #include "src/NonLinear/hybrj.h"
-#include "src/NonLinear/lmstr1.h"
-#include "src/NonLinear/chkder.h"
 
 //@}
 

unsupported/Eigen/src/NonLinear/lmder.h

@@ -50,7 +50,7 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
 
     /* check the input parameters for errors. */
     if (n <= 0 || m < n || tol < 0.) {
-        printf("ei_lmder1 bad args : m,n,tol,...");
+        printf("LevenbergMarquardt::minimize() bad args : m,n,tol,...");
         return 0;
     }
 

unsupported/Eigen/src/NonLinear/lmstr.h

@@ -1,7 +1,73 @@
 
 template<typename FunctorType, typename Scalar>
-int ei_lmstr(
+class LevenbergMarquardtOptimumStorage 
-        const FunctorType &Functor,
+{
+public:
+    LevenbergMarquardtOptimumStorage(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,
+            int &njev,
+            Matrix< Scalar, Dynamic, Dynamic > &fjac,
+            VectorXi &ipvt,
+            Matrix< Scalar, Dynamic, 1 >  &qtf,
+            Matrix< Scalar, Dynamic, 1 >  &diag,
+            int mode=1,
+            Scalar factor = 100.,
+            int maxfev = 400,
+            Scalar ftol = ei_sqrt(epsilon<Scalar>()),
+            Scalar xtol = ei_sqrt(epsilon<Scalar>()),
+            Scalar gtol = Scalar(0.),
+            int nprint=0
+            );
+
+private:
+    const FunctorType &functor;
+};
+
+
+template<typename FunctorType, typename Scalar>
+int LevenbergMarquardtOptimumStorage<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, njev=0;
+    Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
+    Matrix< Scalar, Dynamic, 1> diag, qtf;
+    VectorXi ipvt(n);
+
+    /* check the input parameters for errors. */
+    if (n <= 0 || m < n || tol < 0.) {
+        printf("LevenbergMarquardtOptimumStorage::minimize() bad args : m,n,tol,...");
+        return 0;
+    }
+
+    info = minimize(
+        x, fvec,
+        nfev, njev,
+        fjac, ipvt, qtf, diag,
+        1,
+        100.,
+        (n+1)*100,
+        tol, tol, Scalar(0.)
+    );
+    return (info==8)?4:info;
+}
+
+template<typename FunctorType, typename Scalar>
+int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
         Matrix< Scalar, Dynamic, 1 >  &x,
         Matrix< Scalar, Dynamic, 1 >  &fvec,
         int &nfev,
@@ -10,13 +76,13 @@ int ei_lmstr(
         VectorXi &ipvt,
         Matrix< Scalar, Dynamic, 1 >  &qtf,
         Matrix< Scalar, Dynamic, 1 >  &diag,
-        int mode=1,
+        int mode,
-        Scalar factor = 100.,
+        Scalar factor,
-        int maxfev = 400,
+        int maxfev,
-        Scalar ftol = ei_sqrt(epsilon<Scalar>()),
+        Scalar ftol,
-        Scalar xtol = ei_sqrt(epsilon<Scalar>()),
+        Scalar xtol,
-        Scalar gtol = Scalar(0.),
+        Scalar gtol,
-        int nprint=0
+        int nprint
         )
 {
     const int m = fvec.size(), n = x.size();
@@ -56,7 +122,7 @@ int ei_lmstr(
     /*     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;
@@ -71,12 +137,12 @@ int ei_lmstr(
 
     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;
             if ((iter - 1) % nprint == 0)
-                iflag = Functor.debug(x, fvec, wa3);
+                iflag = functor.debug(x, fvec, wa3);
             if (iflag < 0)
                 break;
         }
@@ -90,7 +156,7 @@ int ei_lmstr(
         fjac.fill(0.);
         iflag = 2;
         for (i = 0; i < m; ++i) {
-            if (Functor.df(x, wa3, iflag) < 0)
+            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());
@@ -195,7 +261,7 @@ int ei_lmstr(
 
             /* 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;
@@ -292,7 +358,7 @@ algo_end:
     if (iflag < 0)
         info = iflag;
     if (nprint > 0)
-        iflag = Functor.debug(x, fvec, wa3);
+        iflag = functor.debug(x, fvec, wa3);
     return info;
 }
 

unsupported/Eigen/src/NonLinear/lmstr1.h

@@ -1,35 +0,0 @@
-
-template<typename FunctorType, typename Scalar>
-int ei_lmstr1(
-        const FunctorType &Functor,
-        Matrix< Scalar, Dynamic, 1 >  &x,
-        Matrix< Scalar, Dynamic, 1 >  &fvec,
-        VectorXi &ipvt,
-        Scalar tol = ei_sqrt(epsilon<Scalar>())
-        )
-{
-    const int n = x.size(), m=fvec.size();
-    int info, nfev=0, njev=0;
-    Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
-    Matrix< Scalar, Dynamic, 1> diag, qtf;
-
-    /* check the input parameters for errors. */
-    if (n <= 0 || m < n || tol < 0.) {
-        printf("ei_lmstr1 bad args : m,n,tol,...");
-        return 0;
-    }
-
-    ipvt.resize(n);
-    info = ei_lmstr(
-        Functor,
-        x, fvec,
-        nfev, njev,
-        fjac, ipvt, qtf, diag,
-        1,
-        100.,
-        (n+1)*100,
-        tol, tol, Scalar(0.)
-    );
-    return (info==8)?4:info;
-}
-

unsupported/test/NonLinear.cpp

@@ -453,13 +453,14 @@ void testLmstr1()
   int m=15, n=3, info;
 
   VectorXd x(n), fvec(m);
-  VectorXi ipvt;
 
   /* the following starting values provide a rough fit. */
   x.setConstant(n, 1.);
 
   // do the computation
-  info = ei_lmstr1(lmstr_functor(), x, fvec, ipvt);
+  lmstr_functor functor;
+  LevenbergMarquardtOptimumStorage<lmstr_functor,double> lm(functor);
+  info = lm.minimize(x, fvec);
 
   // check return value
   VERIFY( 1 == info);
@@ -486,8 +487,9 @@ void testLmstr()
   x.setConstant(n, 1.);
 
   // do the computation
-  info = ei_lmstr(lmstr_functor(), x, fvec, nfev, njev, fjac, ipvt, qtf, diag);
+  lmstr_functor functor;
-  VectorXd wa(n);
+  LevenbergMarquardtOptimumStorage<lmstr_functor,double> lm(functor);
+  info = lm.minimize(x, fvec, nfev, njev, fjac, ipvt, qtf, diag);
 
   // check return values
   VERIFY( 1 == info);