X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?p=CreaPhase.git;a=blobdiff_plain;f=octave_packages%2Fnnet-0.1.13%2Ftrastd.m;fp=octave_packages%2Fnnet-0.1.13%2Ftrastd.m;h=d4e0a2e31397ef97a5142fc06cd654691431b393;hp=0000000000000000000000000000000000000000;hb=c880e8788dfc484bf23ce13fa2787f2c6bca4863;hpb=1705066eceaaea976f010f669ce8e972f3734b05

diff --git a/octave_packages/nnet-0.1.13/trastd.m b/octave_packages/nnet-0.1.13/trastd.m
new file mode 100644
index 0000000..d4e0a2e
--- /dev/null
+++ b/octave_packages/nnet-0.1.13/trastd.m
@@ -0,0 +1,91 @@
+## 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
\ No newline at end of file