/// <summary>
/// Computes the next value of this indicator from the given state
/// </summary>
/// <param name="input">The input given to the indicator</param>
/// <returns>A new value for this indicator</returns>
protected override decimal ComputeNextValue(IBaseDataBar input)
{
var typicalPrice = (input.High + input.Low + input.Close) / 3.0m;
TypicalPriceAverage.Update(input.Time, typicalPrice);
TypicalPriceMeanDeviation.Update(input.Time, typicalPrice);
// compare this to zero, since if the mean deviation is very small we can get
// precision errors due to non-floating point math
var weightedMeanDeviation = _k * TypicalPriceMeanDeviation.Current;
if (weightedMeanDeviation == 0.0m)
{
return(0.0m);
}
return((typicalPrice - TypicalPriceAverage) / weightedMeanDeviation);
}
/// <summary>
/// Computes the next value of this indicator from the given state
/// </summary>
/// <param name="time"></param>
/// <param name="input">The input given to the indicator</param>
/// <returns>A new value for this indicator</returns>
protected override DoubleArray Forward(long time, DoubleArray input)
{
var typicalPrice = (input[HighIdx] + input[LowIdx] + input[CloseIdx]) / 3.0d;
TypicalPriceAverage.Update(time, typicalPrice);
TypicalPriceMeanDeviation.Update(time, typicalPrice);
// compare this to zero, since if the mean deviation is very small we can get
// precision errors due to non-floating point math
var weightedMeanDeviation = _k * TypicalPriceMeanDeviation.Current;
if (weightedMeanDeviation == 0.0d)
{
return(0.0d);
}
return((typicalPrice - TypicalPriceAverage.Current.Value) / weightedMeanDeviation);
}
/// <summary>
/// Resets this indicator to its initial state
/// </summary>
public override void Reset()
{
TypicalPriceAverage.Reset();
TypicalPriceMeanDeviation.Reset();
base.Reset();
}
