/usr/share/octave/packages/nnet-0.1.13/trastd.m is in octave-nnet 0.1.13-2.
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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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | ## Copyright (C) 2005 Michel D. Schmid <michaelschmid@users.sourceforge.net>
##
##
## 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, 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; see the file COPYING. If not, see
## <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {}@var{pn} = trastd (@var{p},@var{meanp},@var{stdp})
## @code{trastd} preprocess additional data for neural network simulation.
##
## @example
## @code{p} : test input data
## @code{meanp}: vector with standardization parameters of prestd(...)
## @code{stdp} : vector with standardization parameters of prestd(...)
##
## meanp = [2.5; 6.5];
## stdp = [1.2910; 1.2910];
## p = [1 4; 2 5];
##
## pn = trastd(p,meanp,stdp);
## @end example
## @noindent
## @end deftypefn
## @seealso{prestd, poststd}
## Author: Michel D. Schmid
function [Pn] = trastd(Pp,meanp,stdp)
## check number of inputs
error(nargchk(3,3,nargin));
[nRows,nColumns]=size(Pp);
rowOnes = ones(1,nColumns);
## now set all standard deviations which are zero to 1
[nRowsII, nColumnsII] = size(stdp);
rowZeros = zeros(nRowsII,1);
findZeros = find(stdp==0);
rowZeros(findZeros)=1;
equal = rowZeros;
nequal = !equal;
if ( sum(equal) != 0 )
warning("Some standard deviations are zero. Those inputs won't be transformed.");
meanp = meanp.*nequal;
stdp = stdp.*nequal + 1*equal;
end
Pn = (Pp-meanp*rowOnes)./(stdp*rowOnes);
endfunction
##
## >> mInput = [1 2 3 4; 5 6 7 8]
##
## mInput =
##
## 1 2 3 4
## 5 6 7 8
##
## >> [pn,meanp,stdp] = prestd(mInput)
##
## pn =
##
## -1.1619 -0.3873 0.3873 1.1619
## -1.1619 -0.3873 0.3873 1.1619
##
##
## meanp =
##
## 2.5000
## 6.5000
##
##
## stdp =
##
## 1.2910
## 1.2910
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