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

diff --git a/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/normal.f b/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/normal.f
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--- a/website/archive/binaries/mac/src/disembl/Tisean_3.0.1/source_f/normal.f
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-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   utilities for normalisation of time series
-c   author T. Schreiber (1998)
-c===========================================================================
-      subroutine rms(nmax,x,sc,sd)
-c  return mean sc and rms amplitude sd
-      dimension x(nmax)
-
-      sc=0.
-      do 10 n=1,nmax
- 10      sc=sc+x(n)
-      sc=sc/nmax
-      sd=0.
-      do 20 n=1,nmax
- 20      sd=sd+(x(n)-sc)**2
-      sd=sqrt(sd/nmax)
-      end
-
-      subroutine normal(nmax,x,sc,sd)
-c  subtract mean, return mean sc and rms amplitude sd
-      dimension x(nmax)
-
-      call rms(nmax,x,sc,sd)
-      do 10 n=1,nmax
- 10      x(n)=x(n)-sc
-      end
-
-      subroutine normal1(nmax,x,sc,sd)
-c  subtract mean, rescale to unit variance, 
-c  return mean sc and rms amplitude sd
-      dimension x(nmax)
-
-      call rms(nmax,x,sc,sd)
-      if(sd.eq.0.) stop 
-     .   "normal1: zero variance, cannot normalise"
-      do 10 n=1,nmax
- 10      x(n)=(x(n)-sc)/sd
-      end
-
-      subroutine minmax(nmax,x,xmin,xmax)
-c  obtain smallest and  largest value in x
-      dimension x(nmax)
-
-      xmin=x(1)
-      xmax=x(1)
-      do 10 n=2,nmax
-         xmin=min(x(n),xmin)
- 10      xmax=max(x(n),xmax)
-      end
-