public PlotCollectionSet GetData(PlotCollectionSet dataset, int nDataIdx, int nLookahead, Guid?guid = null, bool bAddToParams = false)
{
BbData data = GetBbData(dataset, nDataIdx, nLookahead, bAddToParams);
return(new PlotCollectionSet(new List <PlotCollection>()
{
data.DstData
}));
}
public BbData GetBbData(PlotCollectionSet dataset, int nDataIdx, int nLookahead = 0, bool bAddToParams = false)
{
BbData data = Pre(dataset, nDataIdx);
MinMax minmax = new MinMax();
for (int i = 0; i < data.SrcData.Count; i++)
{
Process(data, i, minmax, nLookahead, bAddToParams);
}
data.DstData.SetMinMax(minmax);
return(data);
}
/// <summary>
/// Calculate the BB based on Investopedia's formula.
/// </summary>
/// <remarks>
/// @see [Bollinger Band Definition](https://www.investopedia.com/terms/b/bollingerbands.asp)
/// </remarks>
/// <param name="data">Specifies the BB data from the previous cycle.</param>
/// <param name="i">Specifies the current data index.</param>
/// <param name="minmax">Currently, not used here.</param>
/// <param name="nLookahead">Specifies the look ahead value if any.</param>
/// <param name="bAddToParams">Optionally, specifies whether or not to add the BB to the parameters of the original data.</param>
/// <returns>The new BB values are returned.</returns>
public Tuple <long, double, double, double, double, double> Process(BbData data, int i, MinMax minmax = null, int nLookahead = 0, bool bAddToParams = false)
{
bool bActive = data.SrcData[i].Active;
Plot plot = new Plot(data.SrcData[i].X, new float[] { 0, 0, 0 }, null, false, data.SrcData[i].Index, data.SrcData[i].Action1Active, data.SrcData[i].Action2Active);
data.DstData.Add(plot, false);
float fTypicalValue = (data.SrcData[i].Y_values.Length == 4) ? (data.SrcData[i].Y_values[1] + data.SrcData[i].Y_values[2] + data.SrcData[i].Y_values[3]) / 3 : data.SrcData[i].Y;
if (data.SrcData[i].Y_values.Length == 4 && m_target != TARGET.DEFAULT)
{
if (m_target == TARGET.BAR)
{
float fVal = (data.SrcData[i].Y_values[0] - data.SrcData[i].Y);
m_caValExt.Add(fVal, null, true);
}
else if (m_target == TARGET.RANGE)
{
float fVal = (data.SrcData[i].Y_values[1] - data.SrcData[i].Y_values[2]);
m_caValExt.Add(fVal, null, true);
}
}
if (m_caVal.Add(fTypicalValue, null, false))
{
data.Ave = (float)m_caVal.Average;
float fStdevTp = (float)m_caVal.StdDev;
if (m_target != TARGET.DEFAULT)
{
fStdevTp = (float)m_caValExt.StdDev;
}
double dfStdDvTp = (m_dfStdDev * fStdevTp);
data.BbAbove = data.Ave + dfStdDvTp;
data.BbBelow = data.Ave - dfStdDvTp;
plot.SetYValues(new float[] { (float)data.BbBelow, (float)data.Ave, (float)data.BbAbove }, true);
double dfAboveBelow = data.BbAbove - data.BbBelow;
data.BbPctb = 0;
if (dfAboveBelow != 0)
{
data.BbPctb = (data.SrcData[i].Y - data.BbBelow) / dfAboveBelow;
}
data.BbWid = 0;
if (data.Ave != 0)
{
data.BbWid = dfAboveBelow / data.Ave;
}
if (bAddToParams && bActive)
{
data.SrcData[i].SetParameter(data.DstData.Name + " Below", data.BbBelow);
data.SrcData[i].SetParameter(data.DstData.Name + " Ave", data.Ave);
data.SrcData[i].SetParameter(data.DstData.Name + " Above", data.BbAbove);
data.SrcData[i].SetParameter(data.DstData.Name + " %b", data.BbPctb);
data.SrcData[i].SetParameter(data.DstData.Name + " BandWidth", data.BbWid);
}
if (minmax != null)
{
minmax.Add(data.BbBelow);
minmax.Add(data.Ave);
minmax.Add(data.BbAbove);
}
}
data.Count++;
return(new Tuple <long, double, double, double, double, double>((long)data.SrcData[i].X, data.BbBelow, data.Ave, data.BbAbove, data.BbPctb, data.BbWid));
}
