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// --------------------------------------------------------------------------
//                   OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2013.
//
// This software is released under a three-clause BSD license:
//  * Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
//  * Redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in the
//    documentation and/or other materials provided with the distribution.
//  * Neither the name of any author or any participating institution
//    may be used to endorse or promote products derived from this software
//    without specific prior written permission.
// For a full list of authors, refer to the file AUTHORS.
// --------------------------------------------------------------------------
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL ANY OF THE AUTHORS OR THE CONTRIBUTING
// INSTITUTIONS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
// OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
// OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
// ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// --------------------------------------------------------------------------
// $Maintainer: Clemens Groepl $
// $Authors: $
// --------------------------------------------------------------------------

#ifndef OPENMS_TRANSFORMATIONS_FEATUREFINDER_MAXLIKELIFITTER1D_H
#define OPENMS_TRANSFORMATIONS_FEATUREFINDER_MAXLIKELIFITTER1D_H

#include <OpenMS/TRANSFORMATIONS/FEATUREFINDER/Fitter1D.h>
#include <OpenMS/MATH/STATISTICS/StatisticFunctions.h>
#include <OpenMS/TRANSFORMATIONS/FEATUREFINDER/InterpolationModel.h>

namespace OpenMS
{

  /**
  @brief Abstract base class for all 1D-model fitters using maximum likelihood optimization.
  */
  class OPENMS_DLLAPI MaxLikeliFitter1D :
    public Fitter1D
  {

public:

    /// default constructor
    MaxLikeliFitter1D() :
      Fitter1D()
    {
    }

    /// copy constructor
    MaxLikeliFitter1D(const MaxLikeliFitter1D & source) :
      Fitter1D(source)
    {
    }

    /// destructor
    virtual ~MaxLikeliFitter1D()
    {
    }

    /// assignment operator
    virtual MaxLikeliFitter1D & operator=(const MaxLikeliFitter1D & source)
    {
      if (&source == this) return *this;

      Fitter1D::operator=(source);

      return *this;
    }

protected:

    /// fit an offset on the basis of the pearson correlation coefficient
    QualityType fitOffset_(InterpolationModel * model, const RawDataArrayType & set, const CoordinateType stdev1, const CoordinateType stdev2, const CoordinateType offset_step)
    {
      const CoordinateType offset_min = model->getInterpolation().supportMin() - stdev1;
      const CoordinateType offset_max = model->getInterpolation().supportMin() + stdev2;

      CoordinateType offset;
      QualityType correlation;

      //test model with default offset
      std::vector<Real> real_data;
      real_data.reserve(set.size());
      std::vector<Real> model_data;
      model_data.reserve(set.size());

      for (Size i = 0; i < set.size(); ++i)
      {
        real_data.push_back(set[i].getIntensity());
        model_data.push_back(model->getIntensity(DPosition<1>(set[i].getPosition())));
      }

      CoordinateType max_offset = model->getInterpolation().getOffset();
      QualityType max_correlation = Math::pearsonCorrelationCoefficient(real_data.begin(), real_data.end(), model_data.begin(), model_data.end());

      //test different offsets
      for (offset = offset_min; offset <= offset_max; offset += offset_step)
      {
        // set offset
        model->setOffset(offset);

        // get samples
        model_data.clear();
        for (Size i = 0; i < set.size(); ++i)
        {
          model_data.push_back(model->getIntensity(DPosition<1>(set[i].getPosition())));
        }

        correlation = Math::pearsonCorrelationCoefficient(real_data.begin(), real_data.end(), model_data.begin(), model_data.end());

        if (correlation > max_correlation)
        {
          max_correlation = correlation;
          max_offset = offset;
        }
      }

      model->setOffset(max_offset);

      return max_correlation;
    }

    void updateMembers_()
    {
      Fitter1D::updateMembers_();
    }

  };
}

#endif // OPENMS_TRANSFORMATIONS_FEATUREFINDER_MAXLIKELIFITTER1D_H