Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / nan-2.5.5 / zscore.m

diff --git a/octave_packages/nan-2.5.5/zscore.m b/octave_packages/nan-2.5.5/zscore.m
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+function [i,v,m] = zscore(i,DIM)
+% ZSCORE removes the mean and normalizes the data 
+% to a variance of 1. Can be used for Pre-Whitening of the data, too. 
+%
+% [z,r,m] = zscore(x,DIM)
+%   z   z-score of x along dimension DIM
+%   r   is the inverse of the standard deviation
+%   m   is the mean of x
+%
+% The data x can be reconstrated with 
+%     x = z*diag(1./r) + repmat(m,size(z)./size(m))  
+%     z = x*diag(r) - repmat(m.*v,size(z)./size(m))  
+%
+% DIM  dimension
+%      1: STATS of columns
+%      2: STATS of rows
+%      default or []: first DIMENSION, with more than 1 element
+%
+% see also: SUMSKIPNAN, MEAN, STD, DETREND
+%
+% REFERENCE(S):
+% [1] http://mathworld.wolfram.com/z-Score.html
+
+%    This program is free software; you can redistribute it and/or modify
+%    it under the terms of the GNU General Public License as published by
+%    the Free Software Foundation; either version 2 of the License, or
+%    (at your option) any later version.
+%
+%    This program is distributed in the hope that it will be useful,
+%    but WITHOUT ANY WARRANTY; without even the implied warranty of
+%    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+%    GNU General Public License for more details.
+%
+%    You should have received a copy of the GNU General Public License
+%    along with this program; If not, see <http://www.gnu.org/licenses/>.
+
+
+%      $Id: zscore.m 8223 2011-04-20 09:16:06Z schloegl $
+%      Copyright (C) 2000-2003,2009 by Alois Schloegl <alois.schloegl@gmail.com>       
+%       This function is part of the NaN-toolbox
+%       http://pub.ist.ac.at/~schloegl/matlab/NaN/
+
+
+if any(size(i)==0); return; end;
+
+if nargin<2
+        DIM=[]; 
+end
+if nargin<3
+        W = []; 
+end
+if isempty(DIM), 
+        DIM=min(find(size(i)>1));
+        if isempty(DIM), DIM=1; end;
+end;
+
+
+% pre-whitening
+m = mean(i,DIM,W);
+i = i-repmat(m,size(i)./size(m));  % remove mean
+v = 1./sqrt(mean(i.^2,DIM,W));
+i = i.*repmat(v,size(i)./size(v)); % scale to var=1
+
+        
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