public KaufmanAdaptiveMovingAverage(IEnumerable <TInput> inputs, Func <TInput, decimal> inputMapper, int periodCount, int emaFastPeriodCount, int emaSlowPeriodCount) : base(inputs, inputMapper)
{
_er = new EfficiencyRatioByTuple(inputs.Select(inputMapper), periodCount);
Func <int, decimal> sc = i =>
{
double erValue = Convert.ToDouble(_er[i]);
return(Convert.ToDecimal(Math.Pow(erValue * (2.0 / (emaFastPeriodCount + 1) - 2.0 / (emaSlowPeriodCount + 1)) + 2.0 / (emaSlowPeriodCount + 1), 2)));
};
_gema = new GenericMovingAverage(
periodCount - 1,
i => inputs.Select(inputMapper).ElementAt(i),
i => inputs.Select(inputMapper).ElementAt(i),
sc,
inputs.Count());
PeriodCount = periodCount;
EmaFastPeriodCount = emaFastPeriodCount;
EmaSlowPeriodCount = emaSlowPeriodCount;
}
public KaufmanAdaptiveMovingAverage(IEnumerable <TInput> inputs, Func <TInput, decimal> inputMapper, int periodCount, int emaFastPeriodCount, int emaSlowPeriodCount) : base(inputs, inputMapper)
{
_er = new EfficiencyRatioByTuple(inputs.Select(inputMapper), periodCount);
Func <int, decimal> smoothingFactor = i =>
{
var s = Smoothing.Ema(emaSlowPeriodCount)(i) + _er[i].Value * (Smoothing.Ema(emaFastPeriodCount)(i) - Smoothing.Ema(emaSlowPeriodCount)(i));
return(s * s);
};
_gma = new GenericMovingAverage(
periodCount - 1,
i => inputs.Select(inputMapper).ElementAt(i),
i => inputs.Select(inputMapper).ElementAt(i),
smoothingFactor,
inputs.Count());
PeriodCount = periodCount;
EmaFastPeriodCount = emaFastPeriodCount;
EmaSlowPeriodCount = emaSlowPeriodCount;
}
