OB-Xd/Modules/gin/utilities/leastsquaresregression.cpp

/*==============================================================================

 Copyright 2018 by Roland Rabien, 2010 by 2010 by Alex Etchells
 For more information visit www.rabiensoftware.com

 ==============================================================================*/

void LeastSquaresRegression::addPoint (double x, double y)
{
    pointArray.add ({x, y});
}

void LeastSquaresRegression::addPoint (juce::Point<double> point)
{
    pointArray.add (point);
}

void LeastSquaresRegression::addPoints (Array<juce::Point<double>> points)
{
    pointArray.addArray (points);
}

void LeastSquaresRegression::clear()
{
    pointArray.clear();
}

bool LeastSquaresRegression::enoughPoints()
{
    return pointArray.size() >= 3;
}

Array<double> LeastSquaresRegression::getTerms()
{
    //notation sjk to mean the sum of x_i^j*y_i^k.
    double s40 = getSx4(); //sum of x^4
    double s30 = getSx3(); //sum of x^3
    double s20 = getSx2(); //sum of x^2
    double s10 = getSx();  //sum of x
    double s00 = pointArray.size();
    //sum of x^0 * y^0  ie 1 * number of entries

    double s21 = getSx2y(); //sum of x^2*y
    double s11 = getSxy();  //sum of x*y
    double s01 = getSy();   //sum of y

    double a = (s21*(s20 * s00 - s10 * s10) -
            s11*(s30 * s00 - s10 * s20) +
            s01*(s30 * s10 - s20 * s20))
            /
            (s40*(s20 * s00 - s10 * s10) -
             s30*(s30 * s00 - s10 * s20) +
             s20*(s30 * s10 - s20 * s20));

    double b = (s40*(s11 * s00 - s01 * s10) -
            s30*(s21 * s00 - s01 * s20) +
            s20*(s21 * s10 - s11 * s20))
            /
            (s40 * (s20 * s00 - s10 * s10) -
             s30 * (s30 * s00 - s10 * s20) +
             s20 * (s30 * s10 - s20 * s20));

    double c = (s40*(s20 * s01 - s10 * s11) -
            s30*(s30 * s01 - s10 * s21) +
            s20*(s30 * s11 - s20 * s21))
            /
            (s40 * (s20 * s00 - s10 * s10) -
             s30 * (s30 * s00 - s10 * s20) +
             s20 * (s30 * s10 - s20 * s20));

    Array<double> terms;
    terms.add (a);
    terms.add (b);
    terms.add (c);
    return terms;
}

double LeastSquaresRegression::aTerm()
{
    //notation sjk to mean the sum of x_i^j*y_i^k.
    double s40 = getSx4(); //sum of x^4
    double s30 = getSx3(); //sum of x^3
    double s20 = getSx2(); //sum of x^2
    double s10 = getSx();  //sum of x
    double s00 = pointArray.size();
    //sum of x^0 * y^0  ie 1 * number of entries

    double s21 = getSx2y(); //sum of x^2*y
    double s11 = getSxy();  //sum of x*y
    double s01 = getSy();   //sum of y

    //a = Da/D
    return (s21*(s20 * s00 - s10 * s10) -
            s11*(s30 * s00 - s10 * s20) +
            s01*(s30 * s10 - s20 * s20))
            /
            (s40*(s20 * s00 - s10 * s10) -
             s30*(s30 * s00 - s10 * s20) +
             s20*(s30 * s10 - s20 * s20));
}

double LeastSquaresRegression::bTerm()
{
    //notation sjk to mean the sum of x_i^j*y_i^k.
    double s40 = getSx4(); //sum of x^4
    double s30 = getSx3(); //sum of x^3
    double s20 = getSx2(); //sum of x^2
    double s10 = getSx();  //sum of x
    double s00 = pointArray.size();
    //sum of x^0 * y^0  ie 1 * number of entries

    double s21 = getSx2y(); //sum of x^2*y
    double s11 = getSxy();  //sum of x*y
    double s01 = getSy();   //sum of y

    //b = Db/D
    return (s40*(s11 * s00 - s01 * s10) -
            s30*(s21 * s00 - s01 * s20) +
            s20*(s21 * s10 - s11 * s20))
            /
            (s40 * (s20 * s00 - s10 * s10) -
             s30 * (s30 * s00 - s10 * s20) +
             s20 * (s30 * s10 - s20 * s20));
}

double LeastSquaresRegression::cTerm()
{
    //notation sjk to mean the sum of x_i^j*y_i^k.
    double s40 = getSx4(); //sum of x^4
    double s30 = getSx3(); //sum of x^3
    double s20 = getSx2(); //sum of x^2
    double s10 = getSx();  //sum of x
    double s00 = pointArray.size();
    //sum of x^0 * y^0  ie 1 * number of entries

    double s21 = getSx2y(); //sum of x^2*y
    double s11 = getSxy();  //sum of x*y
    double s01 = getSy();   //sum of y

    //c = Dc/D
    return (s40*(s20 * s01 - s10 * s11) -
            s30*(s30 * s01 - s10 * s21) +
            s20*(s30 * s11 - s20 * s21))
            /
            (s40 * (s20 * s00 - s10 * s10) -
             s30 * (s30 * s00 - s10 * s20) +
             s20 * (s30 * s10 - s20 * s20));
}

double LeastSquaresRegression::rSquare() // get r-squared
{
    // 1 - (residual sum of squares / total sum of squares)
    return 1 - getSSerr() / getSStot();
}


/*helper methods*/
double LeastSquaresRegression::getSx() // get sum of x
{
    double Sx = 0;
    for (auto it : pointArray)
    {
        Sx += it.getX();
    }
    return Sx;
}

double LeastSquaresRegression::getSy() // get sum of y
{
    double Sy = 0;
    for (auto it : pointArray)
    {
        Sy += it.getY();
    }
    return Sy;
}

double LeastSquaresRegression::getSx2() // get sum of x^2
{
    double Sx2 = 0;
    for (auto it : pointArray)
    {
        Sx2 += std::pow (it.getX(), 2); // sum of x^2
    }
    return Sx2;
}

double LeastSquaresRegression::getSx3() // get sum of x^3
{
    double Sx3 = 0;
    for (auto it : pointArray)
    {
        Sx3 += std::pow (it.getX(), 3); // sum of x^3
    }
    return Sx3;
}

double LeastSquaresRegression::getSx4() // get sum of x^4
{
    double Sx4 = 0;
    for (auto it : pointArray)
    {
        Sx4 += std::pow (it.getX(), 4); // sum of x^4
    }
    return Sx4;
}

double LeastSquaresRegression::getSxy() // get sum of x*y
{
    double Sxy = 0;
    for (auto it : pointArray)
    {
        Sxy += it.getX() * it.getY(); // sum of x*y
    }
    return Sxy;
}

double LeastSquaresRegression::getSx2y() // get sum of x^2*y
{
    double Sx2y = 0;
    for (auto it : pointArray)
    {
        Sx2y += pow(it.getX(), 2) * it.getY(); // sum of x^2*y
    }
    return Sx2y;
}

double LeastSquaresRegression::getYMean() // mean value of y
{
    double y_tot = 0;
    for (auto it : pointArray)
    {
        y_tot += it.getY();
    }
    return y_tot / pointArray.size();
}

double LeastSquaresRegression::getSStot() // total sum of squares
{
    //the sum of the squares of the differences between
    //the measured y values and the mean y value
    double ss_tot = 0;
    for (auto it : pointArray)
    {
        ss_tot += std::pow (it.getY() - getYMean(), 2);
    }
    return ss_tot;
}

double LeastSquaresRegression::getSSerr() // residual sum of squares
{
    //the sum of the squares of te difference between
    //the measured y values and the values of y predicted by the equation
    double ss_err = 0;
    for (auto it : pointArray)
    {
        ss_err += std::pow (it.getY() - getPredictedY (it.getX()), 2);
    }
    return ss_err;
}

double LeastSquaresRegression::getPredictedY (double x)
{
    //returns value of y predicted by the equation for a given value of x
    return aTerm() * std::pow(x, 2) + bTerm() * x + cTerm();
}