/// <summary>
/// Alternative regression method with different output. </summary>
/// <param name="xData"> X values of data </param>
/// <param name="yData"> Y values of data </param>
/// <param name="degree"> Degree of polynomial which fits the given data </param>
/// <param name="normalize"> Normalize xData by mean and standard deviation if normalize == true </param>
/// <returns> PolynomialsLeastSquaresRegressionResult containing coefficients, rMatrix, degrees of freedom, norm of residuals, and mean, standard deviation </returns>
public virtual PolynomialsLeastSquaresFitterResult regressVerbose(double[] xData, double[] yData, int degree, bool normalize)
{
LeastSquaresRegressionResult result = regress(xData, yData, degree, normalize);
int nData = xData.Length;
DoubleMatrix rMatriX = _qrResult.R;
DoubleArray resResult = DoubleArray.copyOf(result.Residuals);
double resNorm = OG_ALGEBRA.getNorm2(resResult);
if (normalize == true)
{
return(new PolynomialsLeastSquaresFitterResult(result.Betas, rMatriX, nData - degree - 1, resNorm, _renorm));
}
return(new PolynomialsLeastSquaresFitterResult(result.Betas, rMatriX, nData - degree - 1, resNorm));
}
/// <summary>
/// Checks coefficients of polynomial f(x) are recovered and residuals, { y_i -f(x_i) }, are accurate
/// </summary>
public virtual void PolynomialFunctionRecoverTest()
{
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final PolynomialsLeastSquaresFitter regObj = new PolynomialsLeastSquaresFitter();
PolynomialsLeastSquaresFitter regObj = new PolynomialsLeastSquaresFitter();
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double[] coeff = new double[] {3.4, 5.6, 1.0, -4.0 };
double[] coeff = new double[] { 3.4, 5.6, 1.0, -4.0 };
DoubleFunction1D func = new RealPolynomialFunction1D(coeff);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final int degree = coeff.length - 1;
int degree = coeff.Length - 1;
const int nPts = 7;
double[] xValues = new double[nPts];
double[] yValues = new double[nPts];
for (int i = 0; i < nPts; ++i)
{
xValues[i] = -5.0 + 10 * i / (nPts - 1);
yValues[i] = func.applyAsDouble(xValues[i]);
}
double[] yValuesNorm = new double[nPts];
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double mean = _meanCal.apply(xValues);
double mean = _meanCal.apply(xValues);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double std = _stdCal.apply(xValues);
double std = _stdCal.apply(xValues);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double ratio = mean / std;
double ratio = mean / std;
for (int i = 0; i < nPts; ++i)
{
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double tmp = xValues[i] / std - ratio;
double tmp = xValues[i] / std - ratio;
yValuesNorm[i] = func.applyAsDouble(tmp);
}
/// <summary>
/// Tests for regress(..)
/// </summary>
LeastSquaresRegressionResult result = regObj.regress(xValues, yValues, degree);
double[] coeffResult = result.Betas;
for (int i = 0; i < degree + 1; ++i)
{
assertEquals(coeff[i], coeffResult[i], EPS * Math.Abs(coeff[i]));
}
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double[] residuals = result.getResiduals();
double[] residuals = result.Residuals;
func = new RealPolynomialFunction1D(coeffResult);
double[] yValuesFit = new double[nPts];
for (int i = 0; i < nPts; ++i)
{
yValuesFit[i] = func.applyAsDouble(xValues[i]);
}
for (int i = 0; i < nPts; ++i)
{
assertEquals(Math.Abs(yValuesFit[i] - yValues[i]), 0.0, Math.Abs(yValues[i]) * EPS);
}
for (int i = 0; i < nPts; ++i)
{
assertEquals(Math.Abs(yValuesFit[i] - yValues[i]), Math.Abs(residuals[i]), Math.Abs(yValues[i]) * EPS);
}
double sum = 0.0;
for (int i = 0; i < nPts; ++i)
{
sum += residuals[i] * residuals[i];
}
sum = Math.Sqrt(sum);
/// <summary>
/// Tests for regressVerbose(.., false)
/// </summary>
PolynomialsLeastSquaresFitterResult resultVer = regObj.regressVerbose(xValues, yValues, degree, false);
coeffResult = resultVer.Coeff;
func = new RealPolynomialFunction1D(coeffResult);
for (int i = 0; i < nPts; ++i)
{
yValuesFit[i] = func.applyAsDouble(xValues[i]);
}
assertEquals(nPts - (degree + 1), resultVer.Dof, 0);
for (int i = 0; i < degree + 1; ++i)
{
assertEquals(coeff[i], coeffResult[i], EPS * Math.Abs(coeff[i]));
}
for (int i = 0; i < nPts; ++i)
{
assertEquals(Math.Abs(yValuesFit[i] - yValues[i]), 0.0, Math.Abs(yValues[i]) * EPS);
}
assertEquals(sum, resultVer.DiffNorm, EPS);
/// <summary>
/// Tests for regressVerbose(.., true)
/// </summary>
PolynomialsLeastSquaresFitterResult resultNorm = regObj.regressVerbose(xValues, yValuesNorm, degree, true);
coeffResult = resultNorm.Coeff;
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double[] meanAndStd = resultNorm.getMeanAndStd();
double[] meanAndStd = resultNorm.MeanAndStd;
assertEquals(nPts - (degree + 1), resultNorm.Dof, 0);
assertEquals(mean, meanAndStd[0], EPS);
assertEquals(std, meanAndStd[1], EPS);
for (int i = 0; i < degree + 1; ++i)
{
assertEquals(coeff[i], coeffResult[i], EPS * Math.Abs(coeff[i]));
}
func = new RealPolynomialFunction1D(coeffResult);
for (int i = 0; i < nPts; ++i)
{
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double tmp = xValues[i] / std - ratio;
double tmp = xValues[i] / std - ratio;
yValuesFit[i] = func.applyAsDouble(tmp);
}
for (int i = 0; i < nPts; ++i)
{
assertEquals(Math.Abs(yValuesFit[i] - yValuesNorm[i]), 0.0, Math.Abs(yValuesNorm[i]) * EPS);
}
sum = 0.0;
for (int i = 0; i < nPts; ++i)
{
sum += (yValuesFit[i] - yValuesNorm[i]) * (yValuesFit[i] - yValuesNorm[i]);
}
sum = Math.Sqrt(sum);
assertEquals(sum, resultNorm.DiffNorm, EPS);
}
public WeightedLeastSquaresRegressionResult(LeastSquaresRegressionResult result) : base(result)
{
}
