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[jabaws.git] / website / archive / binaries / mac / src / disembl / Tisean_3.0.1 / source_f / predict.f

diff --git a/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/predict.f b/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/predict.f
deleted file mode 100644 (file)
index 0e8d161..0000000
--- a/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/predict.f
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@@ -1,104 +0,0 @@
-c===========================================================================
-c
-c   This file is part of TISEAN
-c 
-c   Copyright (c) 1998-2007 Rainer Hegger, Holger Kantz, Thomas Schreiber
-c 
-c   TISEAN is free software; you can redistribute it and/or modify
-c   it under the terms of the GNU General Public License as published by
-c   the Free Software Foundation; either version 2 of the License, or
-c   (at your option) any later version.
-c
-c   TISEAN is distributed in the hope that it will be useful,
-c   but WITHOUT ANY WARRANTY; without even the implied warranty of
-c   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-c   GNU General Public License for more details.
-c
-c   You should have received a copy of the GNU General Public License
-c   along with TISEAN; if not, write to the Free Software
-c   Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
-c
-c===========================================================================
-c   simple nonlinear prediction, fast neighbour search
-c   see  H. Kantz, T. Schreiber, Nonlinear Time Series Analysis, Cambridge
-c      University Press (1997,2004)
-c   author T. Schreiber (1998)
-c===========================================================================
-      parameter(nx=1000000)
-      dimension x(nx), y(nx)
-      character*72 file, fout
-      data eps/0./, frac/0./, ifc/1/
-      data iverb/1/
-
-      call whatido("prediction with locally constant fits",iverb)
-      id=imust("d")
-      m=imust("m")
-      eps=fcan("r",eps)
-      frac=fcan("v",frac)
-      ifc=ican("s",ifc)
-      nmaxx=ican("l",nx)
-      nexcl=ican("x",0)
-      jcol=ican("c",0)
-      isout=igetout(fout,iverb)
-      if(eps.eq.0.and.frac.eq.0.) call usage()
-
-      do 10 ifi=1,nstrings()
-         call nthstring(ifi,file)
-         nmax=nmaxx
-         call readfile(nmax,x,nexcl,jcol,file,iverb)
-         if(file.eq."-") file="stdin"
-         if(isout.eq.1) call addsuff(fout,file,"_pred")
-         call rms(nmax,x,sc,sd)
-         if(frac.gt.0) eps=sd*frac
-         iun=istdout()
-         if(fout.eq." ") iun=istderr()
-         write(iun,*) "err: ", fcerror(nmax,x,y,m,id,ifc,eps), 
-     .      " "//file(1:index(file," ")-1)
- 10      call writefile(nmax,y,fout,iverb)
-      end
-
-      subroutine usage()
-c usage message
-
-      call whatineed(
-     .   "-d# -m# [-r# | -v#]"//
-     .   " [-s# -o outfile -l# -x# -c# -V# -h] file(s)")
-      call ptext("either -r or -v must be present")
-      call popt("d","delay")
-      call popt("m","embedding dimension")
-      call popt("r","absolute radius of neighbourhoods")
-      call popt("v","same as fraction of standard deviation")
-      call popt("s","time steps ahead forecast (one step)")
-      call popt("l","number of values to be read (all)")
-      call popt("x","number of values to be skipped (0)")
-      call popt("c","column to be read (1 or file,#)")
-      call pout("file_pred")
-      call pall()
-      stop
-      end
-
-      function fcerror(nmax,y,yp,m,id,ifc,eps)
-      parameter(im=100,ii=100000000,nx=1000000) 
-      dimension y(nmax),yp(nx),jh(0:im*im),jpntr(nx),nlist(nx)
-
-      if(nmax.gt.nx) stop "fcerror: make nx larger."
-      call base(nmax-ifc,y,id,m,jh,jpntr,eps)
-      fcerror=0
-
-      call rms(nmax,y,sx,sd)
-      do 10 n=1,(m-1)*id+ifc
- 10      yp(n)=sx
-      do 20 n=(m-1)*id+1,nmax-ifc           
-         call neigh(nmax,y,y,n,nmax,id,m,jh,jpntr,eps,nlist,nfound)
-         av=0
-         do 30 nn=1,nfound            
- 30         if(nlist(nn).ne.n) av=av+y(nlist(nn)+ifc) 
-         if(nfound.gt.1) then
-            yp(n+ifc)=av/(nfound-1)
-         else
-            yp(n+ifc)=sx
-         endif
- 20      fcerror=fcerror+(y(n+ifc)-yp(n+ifc))**2
-      fcerror=sqrt(fcerror/(nmax-ifc-(m-1)*id))
-      end
-