LogOfGaussianDensityKernel.cc

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// -*- C++ -*-

// PLearn (A C++ Machine Learning Library)
// Copyright (C) 1998 Pascal Vincent
// Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
// Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
// Copyright (C) 2002 Xiangdong Wang, Christian Dorion

// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
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//  1. Redistributions of source code must retain the above copyright
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/* *******************************************************      
   * $Id: LogOfGaussianDensityKernel.cc,v 1.4 2004/04/07 23:17:52 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "LogOfGaussianDensityKernel.h"

namespace PLearn {
using namespace std;


PLEARN_IMPLEMENT_OBJECT(LogOfGaussianDensityKernel, "ONE LINE DESCR", "NO HELP");

real LogOfGaussianDensityKernel::evaluate(const Vec& x1, const Vec& x2) const
{ 
  // cerr << "LogOfGaussKernel mu: " << x1 << endl; 
  double sigmasq = sigma*sigma;
  // cerr << "sqnorm_xmu " << powdistance(x1, x2, real(2.0)) << endl;
  // cerr << "sigmasq " << sigmasq << endl;
  double q = powdistance(x1, x2, real(2.0))/sigmasq;
  // cerr << "log of gauss kernel q = " << q << endl; 
  //double logp = -0.5 * ( q + x1.length()*( log(2*M_PI) + log(sigmasq)) ); 
  double logp = -0.5 * ( q + x1.length()*( log(2*Pi) + log(sigmasq)) ); 
  // cerr << "logp = " << logp << endl;
  // exit(0);
  return real(logp);
}


void LogOfGaussianDensityKernel::declareOptions(OptionList& ol)
{
  declareOption(ol, "sigma", &LogOfGaussianDensityKernel::sigma, OptionBase::buildoption,
                "The width of the Gaussian");
  inherited::declareOptions(ol);
}



} // end of namespace PLearn

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