LinearRegression.h

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// Copyright (c) 2002-present, OpenMS Inc. -- EKU Tuebingen, ETH Zurich, and FU Berlin
// SPDX-License-Identifier: BSD-3-Clause
//
// --------------------------------------------------------------------------
// $Maintainer: Timo Sachsenberg $
// $Authors: $
// --------------------------------------------------------------------------
 
#pragma once
 
#include <OpenMS/CONCEPT/Types.h>
#include <OpenMS/CONCEPT/Exception.h>
 
#include <cmath>
#include <vector>
 
 
namespace OpenMS
{
  namespace Math
  {
    class OPENMS_DLLAPI LinearRegression
    {
public:
 
      LinearRegression() :
        intercept_(0),
        slope_(0),
        x_intercept_(0),
        lower_(0),
        upper_(0),
        t_star_(0),
        r_squared_(0),
        stand_dev_residuals_(0),
        mean_residuals_(0),
        stand_error_slope_(0),
        chi_squared_(0),
        rsd_(0)
      {
      }
 
      virtual ~LinearRegression() = default;
 
      void computeRegression(double confidence_interval_P,
        std::vector<double>::const_iterator x_begin,
        std::vector<double>::const_iterator x_end,
        std::vector<double>::const_iterator y_begin,
        bool compute_goodness = true);
 
      void computeRegressionWeighted(double confidence_interval_P, 
        std::vector<double>::const_iterator x_begin, 
        std::vector<double>::const_iterator x_end, 
        std::vector<double>::const_iterator y_begin, 
        std::vector<double>::const_iterator w_begin, 
        bool compute_goodness = true);
 
      double getIntercept() const;
      double getSlope() const;
      double getXIntercept() const;
      double getLower() const;
      double getUpper() const;
      double getTValue() const;
      double getRSquared() const;
      double getStandDevRes() const;
      double getMeanRes() const;
      double getStandErrSlope() const;
      double getChiSquared() const;
      double getRSD() const;
 
      static inline double computePointY(double x, double slope, double intercept)
      {
        return slope * x + intercept;
      }
 
protected:
 
      double intercept_;
      double slope_;
      double x_intercept_;
      double lower_;
      double upper_;
      double t_star_;
      double r_squared_;
      double stand_dev_residuals_;
      double mean_residuals_;
      double stand_error_slope_;
      double chi_squared_;
      double rsd_;
 
      void computeGoodness_(const std::vector<double>& X, const std::vector<double>& Y, double confidence_interval_P);
 
      template <typename Iterator>
      double computeChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, double slope, double intercept);
 
      template <typename Iterator>
      double computeWeightedChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin, double slope, double intercept);
 
private:
 
      LinearRegression(const LinearRegression& arg);
      LinearRegression& operator=(const LinearRegression& arg);
 
    }; //class
 
    //x, y, w must be of same size
    template <typename Iterator>
    double LinearRegression::computeChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, double slope, double intercept)
    {
      double chi_squared = 0.0;
      Iterator xIter = x_begin;
      Iterator yIter = y_begin;
      for (; xIter != x_end; ++xIter, ++yIter)
      {
        chi_squared += std::pow(*yIter - computePointY(*xIter, slope, intercept), 2);
      }
 
      return chi_squared;
    }
 
    //x, y, w must be of same size
    template <typename Iterator>
    double LinearRegression::computeWeightedChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin, double slope, double intercept)
    {
      double chi_squared = 0.0;
      Iterator xIter = x_begin;
      Iterator yIter = y_begin;
      Iterator wIter = w_begin;
      for (; xIter != x_end; ++xIter, ++yIter, ++wIter)
      {
        chi_squared += *wIter * std::pow(*yIter - computePointY(*xIter, slope, intercept), 2);
      }
 
      return chi_squared;
    }
  } // namespace Math
} // namespace OpenMS