public void SuperSmootherComputesCorrectly()
{
int _period = 5;
DateTime time = DateTime.Now;
decimal[] actualValues = new decimal[20];
SuperSmoother sSmoother = new SuperSmoother(_period);
# region Arrays inputs
/// <summary>
/// Initializes a new instance of the <see cref="AutocorrelogramPeriodogram"/> class.
/// </summary>
/// <param name="name">The name of this indicator</param>
/// <param name="shortPeriod">The period of the low pass filter cut off frequency.</param>
/// <param name="longPeriod">The period of the high pass filter cut off frequency.</param>
/// <param name="correlationWidth">Number of pair observations used to estimate the autocorrelation coefficients.</param>
public AutocorrelogramPeriodogram(string name, int shortPeriod, int longPeriod, int correlationWidth)
: base(name, correlationWidth)
{
_shortPeriod = shortPeriod;
_longPeriod = longPeriod;
_bandwidth = longPeriod - shortPeriod;
_correlationWidth = correlationWidth;
_decayFactor = EstimateDecayFactor(_shortPeriod, _longPeriod);
hpf = new HighPassFilter(longPeriod);
sSmoother = new SuperSmoother(shortPeriod);
sSmootherWindow = new RollingWindow <double>(longPeriod + _correlationWidth);
R = Vector <double> .Build.Dense(_bandwidth + 1, 1d);
}
public void ResetsProperly()
{
int _period = 5;
DateTime time = DateTime.Now;
SuperSmoother sSmoother = new SuperSmoother(_period);
for (int i = 0; i < 6; i++)
{
sSmoother.Update(new IndicatorDataPoint(time, 1m));
time.AddMinutes(1);
}
Assert.IsTrue(sSmoother.IsReady, "SuperSmoother ready");
sSmoother.Reset();
TestHelper.AssertIndicatorIsInDefaultState(sSmoother);
}
/// <summary>
/// Called on each bar update event (incoming tick)
/// </summary>
protected override void OnBarUpdate()
{
if (CurrentBar < Poles)
{
SuperSmoother.Set(Input[0]);
return;
}
if (FirstTickOfBar)
{
if (Poles == 2)
{
recurrentPart = coeff2 * Value[1] + coeff3 * Value[2];
}
else if (Poles == 3)
{
recurrentPart = coeff2 * Value[1] + coeff3 * Value[2] + coeff4 * Value[3];
}
}
SuperSmoother.Set(recurrentPart + coeff1 * Input[0]);
}
public void SuperSmootherComputesCorrectly()
{
int _period = 5;
DateTime time = DateTime.Now;
decimal[] actualValues = new decimal[20];
SuperSmoother sSmoother = new SuperSmoother(_period);
# region Arrays inputs
decimal[] prices = new decimal[20]
{
/*
* Formula:
* prices[i] = 10 * sin(2 * pi / 20 * i) + 15
* i = [0, 1, 2,..., 19]
*/
15m, 18.09m, 20.88m, 23.09m, 24.51m, 25m, 24.51m, 23.09m, 20.88m, 18.09m,
15m, 11.91m, 9.12m, 6.91m, 5.49m, 5m, 5.49m, 6.91m, 9.12m, 11.91m
};
decimal[] expectedValues = new decimal[20]
{
// Estimated with Python:
15m, 18.09m, 19.5201m, 21.3652m, 23.261m, 24.5534m, 24.9032m, 24.2448m, 22.6636m, 20.3287m,
17.4727m, 14.3764m, 11.3411m, 8.6643m, 6.6086m, 5.374m, 5.0812m, 5.7594m, 7.3412m, 9.6731m
};
# endregion
for (int i = 0; i < prices.Length; i++)
{
sSmoother.Update(new IndicatorDataPoint(time, prices[i]));
actualValues[i] = Math.Round(sSmoother.Current.Value, 4);
Console.WriteLine(actualValues[i]);
time.AddMinutes(1);
}
Assert.AreEqual(expectedValues, actualValues, "Estimation SuperSmoother(5)");
}
