text: // --------------------------------------------------------------------------
  //                   OpenMS -- Open-Source Mass Spectrometry
  // --------------------------------------------------------------------------
  // Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
  // ETH Zurich, and Freie Universitaet Berlin 2002-2020.
  //
  // 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: Timo Sachsenberg $
  // $Authors: $
  // --------------------------------------------------------------------------
  
  #pragma once
  
  #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
      ~MaxLikeliFitter1D() override
      {
      }
  
      /// 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<float> real_data;
        real_data.reserve(set.size());
        std::vector<float> 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_() override
      {
        Fitter1D::updateMembers_();
      }
  
    };
  }
  
  