public void Heronian()
{
// given
IList <double> list1 = new List <double>()
{
-1, 0, 1, 2, 3
};
IList <double> list2 = new List <double>()
{
0, 0
};
IList <IList <double> > list3 = new List <IList <double> >()
{
list1, list2
};
const double EXPECTED1 = 0.934195180782892;
const double EXPECTED2 = 0.0;
IList <double> expected3 = new List <double>()
{
EXPECTED1, EXPECTED2
};
// when
double result1 = Averages.Heronian(list1, GeometricMeanVariant.Offset).Value;
double result2 = Averages.Heronian(list2, GeometricMeanVariant.Offset).Value;
IList <double> result3 = Averages.Heronian(list3, GeometricMeanVariant.Offset);
// then
Assert.AreEqual(EXPECTED1, result1, Assertions.IBM_FLOAT_SURROUNDING);
Assert.AreEqual(EXPECTED2, result2, Assertions.IBM_FLOAT_SURROUNDING);
Assertions.SameValues(expected3, result3, 1.0E-14);
}
public bool?TryMakeAverageCurve(MeanType method, int curvesNo)
{
if (curvesNo < 0)
{
return(null);
}
string signature = string.Empty;
IList <double> result = new List <double>();
try {
signature = MethodBase.GetCurrentMethod().Name + '(' + method + ',' + curvesNo + ')';
IList <IList <double> > orderedSetOfCurves = SeriesAssist.GetOrderedCopy(ModifiedCurves, curvesNo);
switch (method)
{
case MeanType.Median:
result = Averages.Median(orderedSetOfCurves);
break;
case MeanType.Maximum:
result = Averages.Maximum(orderedSetOfCurves);
break;
case MeanType.Minimum:
result = Averages.Minimum(orderedSetOfCurves);
break;
case MeanType.Arithmetic:
result = Averages.Arithmetic(orderedSetOfCurves);
break;
case MeanType.Geometric:
result = Averages.Geometric(orderedSetOfCurves, MeansParams.Geometric.Variant);
break;
case MeanType.AGM:
result = Averages.AGM(orderedSetOfCurves, MeansParams.AGM.Variant);
break;
case MeanType.Heronian:
result = Averages.Heronian(orderedSetOfCurves, MeansParams.Heronian.Variant);
break;
case MeanType.Harmonic:
result = Averages.Harmonic(orderedSetOfCurves, MeansParams.Harmonic.Variant);
break;
case MeanType.Generalized:
result = Averages.Generalized(orderedSetOfCurves, MeansParams.Generalized.Variant, MeansParams.Generalized.Rank);
break;
case MeanType.SMA:
result = Averages.SMA(orderedSetOfCurves);
break;
case MeanType.Tolerance:
result = Averages.Tolerance(orderedSetOfCurves, MeansParams.Tolerance.Tolerance, MeansParams.Tolerance.Finisher);
break;
case MeanType.Central:
result = Averages.Central(orderedSetOfCurves, MeansParams.Central.MassPercent);
break;
case MeanType.NN:
result = Smoothers.NearestNeighbors(orderedSetOfCurves, MeansParams.NN.Amount);
break;
case MeanType.NadarayaWatson:
result = Smoothers.NadarayaWatson(orderedSetOfCurves, MeansParams.NadarayaWatson.Variant, MeansParams.NadarayaWatson.KernelType, MeansParams.NadarayaWatson.KernelSize);
break;
}
}
catch (ArgumentOutOfRangeException ex) {
log.Error(signature, ex);
return(false);
}
catch (OverflowException ex) {
log.Error(signature, ex);
return(false);
}
catch (InvalidOperationException ex) {
log.Error(signature, ex);
return(false);
}
catch (Exception ex) {
log.Fatal(signature, ex);
return(false);
}
AverageCurve.Points.Clear();
SeriesAssist.CopyPoints(AverageCurve, IdealCurve, result);
return(SeriesAssist.IsChartAcceptable(AverageCurve));
}
