Fixed minsearch problem with non-varying parameters

minimize.cc

@@ -212,17 +212,18 @@ void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramsto
     }
   }
   
-
+  
   //Number of parameters to estimate
   int n=x.Nrows()-n_nonvary, maxiter=200*n,iter=0;
+  int ntot=x.Nrows();
   int func_evals=0;  
   // Some things we'll need.
   float rho=1,chi=2,psi=0.5,sigma=0.5;
   float tolx=1e-6,tolf=1e-6;
-  ColumnVector onesn(n);
+  ColumnVector onesn(ntot);
   onesn=1;
-  ColumnVector one2n(n),two2np1(n);
-  for(int i=1;i<=n;i++){
+  ColumnVector one2n(ntot),two2np1(ntot);
+  for(int i=1;i<=ntot;i++){
     one2n(i)=i;
     two2np1(i)=i+1;
   }
@@ -241,15 +242,14 @@ void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramsto
   
   float usual_delta=0.05,zero_term_delta=0.00025;
   //perturb each parameter by a bit, and store the cost.
-  ColumnVector y;
-
+  ColumnVector y=x;
 
   for(int i=1;i<=n;i++){
     // The values of nonvarying parameters should be the same in 
     // all of the optional param vectors and therefore in all
     // combinations of them in the remainder of the code.
+    
     if(paramstovary(i)==1){
-      y=x;
       if(y(i)!=0){y(i)=(1+usual_delta)*y(i);}
       else{y(i)=(1+zero_term_delta);}
       en=func.evaluate(y);
@@ -265,12 +265,10 @@ void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramsto
   
   sort(v.begin(),v.end(),pair_comparer()); //wasn't that easy...
   string how="";
-  ColumnVector xbar(n),xr(n),xe(n),xc(n),xcc(n),xtmp(n);
- 
+  ColumnVector xbar(ntot),xr(ntot),xe(ntot),xc(ntot),xcc(ntot),xtmp(ntot);
   //cerr<<"starting loop"<<endl;
   while(iter<=maxiter){
     iter++;
-    
     if(v[n].first-v[0].first< tolf){
       ColumnVector tmpvec1,tmpvec2;
       bool stopsearch=true;
@@ -283,7 +281,6 @@ void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramsto
       }
       if(stopsearch){break;}
     } 
-
     //compute reflection point
   
   // xbar is average of best n paramsets.
@@ -294,7 +291,7 @@ void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramsto
     xbar=xbar/n;
     xr=(1+rho)*xbar-rho*v[n].second; //reflection point
     float en_xr=func.evaluate(xr);func_evals++;
-     if(en_xr < v[0].first){ //en_xr is better than our current best
+    if(en_xr < v[0].first){ //en_xr is better than our current best
  
       //compute expansion point
       xe=(1+rho*chi)*xbar-rho*chi*v[n].second;