Marsyas  0.6.0-alpha
/usr/src/RPM/BUILD/marsyas-0.6.0/src/marsyas/marsystems/Norm.cpp
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00001 /*
00002 ** Copyright (C) 1998-2006 George Tzanetakis <gtzan@cs.uvic.ca>
00003 **
00004 ** This program is free software; you can redistribute it and/or modify
00005 ** it under the terms of the GNU General Public License as published by
00006 ** the Free Software Foundation; either version 2 of the License, or
00007 ** (at your option) any later version.
00008 **
00009 ** This program is distributed in the hope that it will be useful,
00010 ** but WITHOUT ANY WARRANTY; without even the implied warranty of
00011 ** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
00012 ** GNU General Public License for more details.
00013 **
00014 ** You should have received a copy of the GNU General Public License
00015 ** along with this program; if not, write to the Free Software
00016 ** Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
00017 */
00018 
00019 #include "Norm.h"
00020 
00021 using std::ostringstream;
00022 using namespace Marsyas;
00023 
00024 Norm::Norm(mrs_string name):MarSystem("Norm",name)
00025 {
00026 }
00027 
00028 Norm::~Norm()
00029 {
00030 }
00031 
00032 MarSystem*
00033 Norm::clone() const
00034 {
00035   return new Norm(*this);
00036 }
00037 
00038 void
00039 Norm::myProcess(realvec& in, realvec& out)
00040 {
00041   realvec row(inSamples_);
00042   mrs_real mean;
00043   mrs_real std;
00044   mrs_natural t,o;
00045 
00046   for (o=0; o < inObservations_; o++)
00047   {
00048     // Calculate the mean and standard deviation of each row aka observation.
00049     for (t = 0; t < inSamples_; t++)
00050     {
00051       row(t) = in(o,t);
00052     }
00053     mean = row.mean();
00054     std =  row.std();
00055     // If standard deviation is zero, the input is constant, so
00056     // subtracting the mean will give zero output and we can just
00057     // set the standard deviation to 1.0 to avoid zero division woes.
00058     if (std == 0.0)
00059     {
00060       std = 1.0;
00061     }
00062 
00063     for (t = 0; t < inSamples_; t++)
00064     {
00065       out(o, t) = (in(o, t) - mean) / std;
00066     }
00067   }
00068 }