protected override IndicatorDataPoint Calculate(T input)
{
Inputs.Add(input);
if (Inputs.Count < Period)
{
return(IndicatorDataPoint.Zero);
}
double min = double.MaxValue, max = double.MinValue;
for (int i = 0; i < Period; i++)
{
var val = Inputs[i].Value;
if (val > max)
{
max = val;
}
if (val < min)
{
min = val;
}
}
if (max > min)
{
return(new IndicatorDataPoint(input.Time, 2d * (input.Value - min) / (max - min) - 1));
}
else
{
throw new Exception("Unexpected error in Normalize indicator");
}
}
protected override IndicatorDataPoint Calculate(ITradeBar input)
{
Inputs.Add(input);
if (Inputs.Count >= Period)
{
var m = 0d;
int nh = 0, nl = 0;
for (int i = 1; i < Period; i++)
{
var vi = Inputs[i].Value;
var vi1 = Inputs[i - 1].Value;
if (vi > m && vi > vi1)
{
nl++;
}
else if (vi < m && vi < vi1)
{
nh++;
}
}
var value = 100d * (nl + nh) / (Period - 1);
return(new IndicatorDataPoint(input.Time, value));
}
return(IndicatorDataPoint.Zero);
}
protected override IndicatorDataPoint Calculate(ITradeBar input)
{
TrueRange.Update(input);
if (TrueRange.IsReady)
{
TrueRanges.Add(TrueRange.Current);
int stepsCnt = Math.Min(TrueRanges.Count, Period);
RollingSum += TrueRange.Current.Value;
if (TrueRanges.Count >= Period)
{
RollingSum -= TrueRanges[Period].Value;
}
var res = new IndicatorDataPoint(input.Time, RollingSum / stepsCnt);
return(res);
}
return(null);
}
protected override MeanAndVarianceRecord Calculate(T input)
{
//remove the sample that's exiting the window from the rolling sum
if (Inputs.Count >= Period)
{
var valueToRemove = Inputs[Period - 1].Value;
_rollingSum -= valueToRemove;
_rollingSumOfSquares -= valueToRemove * valueToRemove;
}
Inputs.Add(input);
_rollingSum += input.Value;
_rollingSumOfSquares += input.Value * input.Value;
//inputs has been set as Period + 1 so max size is number of sampes + 1
var mean = _rollingSum / Inputs.Count;
var meanOfSquares = _rollingSumOfSquares / Inputs.Count;
var variance = meanOfSquares - mean * mean;
return(new MeanAndVarianceRecord(input.Time, mean, variance));
}
protected override IBaseData Calculate(IBaseData input)
{
Inputs.Add(input);
IBaseData output;
var oneRemoved = Inputs.Samples > Inputs.Size;
if (Inputs.Count < 2)
{
output = input;
}
else if (!oneRemoved || Inputs.MostRecentlyRemoved.Low > LastOutput.Low)
{
//if the sample that's going out of range is NOT the current min then we only need to check if the new sample is lower than current min
output = input.Low < LastOutput.Low ? input : LastOutput;
}
else if (input.Low <= Inputs.MostRecentlyRemoved.Low)
{
//the current minimum is going out of range, but signalIn is lower than min then signalIn IS the new min
output = input;
}
else
{
//min is going out of window so we need to search again
var inputs = Inputs.GetRawSamples();
output = inputs[0];
foreach (var rec in inputs)
{
if (rec.Low < output.Low)
{
output = rec;
}
}
}
output = new IndicatorDataPoint(output.Time, output.Low);
LastOutput = output;
return(output);
}