/usr/share/octave/packages/nan-3.1.4/zscore.m is in octave-nan 3.1.4-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | function [i,m,s] = zscore(i,OPT, DIM, W)
% ZSCORE removes the mean and normalizes data
% to a variance of 1. Can be used for pre-whitening of data, too.
%
% [z,mu, sigma] = zscore(x [,OPT [, DIM])
% z z-score of x along dimension DIM
% sigma is the inverse of the standard deviation
% mu is the mean of x
%
% The data x can be reconstucted with
% x = z*diag(sigma) + repmat(m, size(z)./size(m))
% z = x*diag(1./sigma) - 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 3 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/>.
% $Id$
% Copyright (C) 2000-2003,2009,2014 by Alois Schloegl <alois.schloegl@ist.ac.at>
% 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
OPT=[];
end
if nargin<3
DIM=[];
end
if nargin<4
W = [];
end
if ~isempty(OPT) && ~any(OPT==[0,1])
error('OPT must be 0, 1 or empty.')
end
if isempty(DIM),
DIM=min(find(size(i)>1));
if isempty(DIM), DIM=1; end;
end;
% pre-whitening
[S,N,SSQ] = sumskipnan(i, DIM, W);
m = S./N;
i = i-repmat(m, size(i)./size(m)); % remove mean
s = std (i, OPT, DIM, W);
s(s==0)=1;
i = i ./ repmat(s,size(i)./size(s)); % scale to var=1
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