X-Git-Url: http://mmka.chem.univ.gda.pl/gitweb/?p=unres.git;a=blobdiff_plain;f=source%2Fmaxlik%2Fsrc_CSA%2Fminsumsl.f;fp=source%2Fmaxlik%2Fsrc_CSA%2Fminsumsl.f;h=0000000000000000000000000000000000000000;hp=53105e502254f1b8c0197b4b4ee0d45ce28959ec;hb=af72f8e89a5d33f0d86ba898d6c5bbbda4b25b84;hpb=f9e536df1fd1627429123fe8990edfcdc2cc1a9a

diff --git a/source/maxlik/src_CSA/minsumsl.f b/source/maxlik/src_CSA/minsumsl.f
deleted file mode 100644
index 53105e5..0000000
--- a/source/maxlik/src_CSA/minsumsl.f
+++ /dev/null
@@ -1,86 +0,0 @@
-      subroutine minsumsl(nvar,x,minval)
-      implicit real*8 (a-h,o-z)
-      include 'DIMENSIONS'
-      parameter (maxvar=maxene+3*nnbase)
-      parameter (liv=60,lv=(77+maxvar*(maxvar+17)/2)) 
-*********************************************************************
-* OPTIMIZE sets up SUMSL or DFP and provides a simple interface for *
-* the calling subprogram.                                           *     
-* when d(i)=1.0, then v(35) is the length of the initial step,      *     
-* calculated in the usual pythagorean way.                          *     
-* absolute convergence occurs when the function is within v(31) of  *     
-* zero. unless you know the minimum value in advance, abs convg     *     
-* is probably not useful.                                           *     
-* relative convergence is when the model predicts that the function *   
-* will decrease by less than v(32)*abs(fun).                        *   
-*********************************************************************
-      dimension iv(liv)                                               
-      real*8 minval,x(nvar),d(maxvar),v(1:lv)                     
-      external funclik,grad,fdum
-      integer idum(1)
-      double precision rdum(1)
-      double precision urparm(maxT)
-      double precision g(maxvar)
-      call deflt(2,iv,liv,lv,v)                                         
-* 12 means fresh start, dont call deflt                                 
-      iv(1)=12                                                          
-* max num of fun calls                                                  
-      maxfun=1000
-      iv(17)=maxfun
-* max num of iterations                                                 
-      maxit=50
-      iv(18)=maxit
-* controls output                                                       
-      iv(19)=1                                                          
-* selects output unit                                                   
-      iv(21)=2
-* 1 means to print out result                                           
-      iv(22)=1                                                          
-* 1 means to print out summary stats                                    
-      iv(23)=1                                                          
-* 1 means to print initial x and d                                      
-      iv(24)=1                                                          
-* min val for v(radfac) default is 0.1                                  
-      v(24)=0.01D0                                                       
-* max val for v(radfac) default is 4.0                                  
-      v(25)=2.0D0                                                       
-c     v(25)=4.0D0                                                       
-* check false conv if (act fnctn decrease) .lt. v(26)*(exp decrease)    
-* the sumsl default is 0.1                                              
-      v(26)=0.001D0
-* false conv if (act fnctn decrease) .lt. v(34)                         
-* the sumsl default is 100*machep                                       
-      v(34)=v(34)/100.0D0                                               
-* absolute convergence                                                  
-      tolf=1.0D-4
-      v(31)=tolf
-* relative convergence                                                  
-      rtolf=1.0D-12
-      v(32)=rtolf
-* controls initial step size                                            
-       v(35)=1.0D-6                                                    
-* large vals of d correspond to small components of step                
-      do 20 i=1,nvar
-         d(i)=1.0D0                                                     
-20    continue
-
-      nf=0
-      call funclik(nvar,x,nf,f,idum,urparm,fdum)  
-      write (2,'(a,1pe17.10)') 'Initial function value:',f
-      call grad(nvar,x,nf,g,idum,urparm,fdum)
-      write (2,*) "Initial gradient"
-      do i=1,nvar
-        write (2,'(i5,e15.5)') i,g(i)
-      enddo
-c minimize the log-likelihood function
-      print *,"iv1",iv(1)
-      call sumsl(nvar,d,x,funclik,grad,iv,liv,lv,v,idum,urparm,fdum)
-      minval=v(10)                                                      
-      write (2,*)
-      write (2,'(a,i4)') 'SUMSL return code:',iv(1)
-      write (2,'(a,1pe17.10)') 'Final function value:',minval
-c      print *,"exiting minsumsl"
-      return  
-      end  
-c---------------------------------------------------------------------
-