//                                               -*- C++ -*-
/**
 *  @file  t_ExpertMixture_std.cxx
 *  @brief The test file of class ExpertMixture for standard methods
 *
 *  Copyright (C) 2005-2013 EDF-EADS-Phimeca
 *
 *  This library is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Lesser General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This library 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 Lesser General Public License for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public
 *  along with this library.  If not, see <http://www.gnu.org/licenses/>.
 *
 *  @author schueller
 *  @date   2012-07-16 12:24:33 +0200 (Mon, 16 Jul 2012)
 */
#include "OT.hxx"
#include "OTtestcode.hxx"

using namespace OT;
using namespace OT::Test;

int main(int argc, char *argv[])
{
  TESTPREAMBLE;
  OStream fullprint(std::cout);
  setRandomGenerator();

  try
    {

      // Create a collection of distribution
      Mixture::DistributionCollection aCollection;
      CorrelationMatrix R(2);
      R(0, 1) = -0.99;
      NumericalPoint mean(2);
      mean[0] = -1.0;
      mean[1] = 1.0;
      aCollection.add( Normal(mean, NumericalPoint(2, 1.0), R) );
      R(0, 1) = 0.99;
      mean[0] = 1.0;
      aCollection.add( Normal(mean, NumericalPoint(2, 1.0), R) );

      // Instanciate one distribution object
      Mixture distribution(aCollection, NumericalPoint(aCollection.getSize(), 1.0));

      // Create a mixture classifier
      MixtureClassifier classifier(distribution);
      fullprint << "classifier dimension=" << classifier.getDimension() << std::endl;

      // Create local experts
      Basis experts(0);
      experts.add(NumericalMathFunction("x", "-x"));
      experts.add(NumericalMathFunction("x", "x"));

      // Create a mixture of experts
      ExpertMixture moe(experts, classifier);

      fullprint << "Mixture of experts=" << moe << std::endl;

      // Evaluate the mixture of experts on some points
      for (UnsignedLong i = 0; i < 5; ++i)
        {
          NumericalPoint p(1, -0.3 + 0.8 * i / 4.0);
          fullprint << "moe(" << p[0] << ")=" << moe(p) << std::endl;
        }

    }
  catch (TestFailed & ex)
    {
      std::cerr << ex << std::endl;
      return ExitCode::Error;
    }


  return ExitCode::Success;
}
