/// <summary>
/// Linear regression is used to calculate a best fit line for the price data. In addition an upper and lower band is added by calculating the standard deviation of prices from the regression line.
/// </summary>
/// <returns></returns>
public RegressionChannel RegressionChannel(Data.IDataSeries input, int period, double width)
{
if (cacheRegressionChannel != null)
{
for (int idx = 0; idx < cacheRegressionChannel.Length; idx++)
{
if (cacheRegressionChannel[idx].Period == period && Math.Abs(cacheRegressionChannel[idx].Width - width) <= double.Epsilon && cacheRegressionChannel[idx].EqualsInput(input))
{
return(cacheRegressionChannel[idx]);
}
}
}
lock (checkRegressionChannel)
{
checkRegressionChannel.Period = period;
period = checkRegressionChannel.Period;
checkRegressionChannel.Width = width;
width = checkRegressionChannel.Width;
if (cacheRegressionChannel != null)
{
for (int idx = 0; idx < cacheRegressionChannel.Length; idx++)
{
if (cacheRegressionChannel[idx].Period == period && Math.Abs(cacheRegressionChannel[idx].Width - width) <= double.Epsilon && cacheRegressionChannel[idx].EqualsInput(input))
{
return(cacheRegressionChannel[idx]);
}
}
}
RegressionChannel indicator = new RegressionChannel();
indicator.BarsRequired = BarsRequired;
indicator.CalculateOnBarClose = CalculateOnBarClose;
#if NT7
indicator.ForceMaximumBarsLookBack256 = ForceMaximumBarsLookBack256;
indicator.MaximumBarsLookBack = MaximumBarsLookBack;
#endif
indicator.Input = input;
indicator.Period = period;
indicator.Width = width;
Indicators.Add(indicator);
indicator.SetUp();
RegressionChannel[] tmp = new RegressionChannel[cacheRegressionChannel == null ? 1 : cacheRegressionChannel.Length + 1];
if (cacheRegressionChannel != null)
{
cacheRegressionChannel.CopyTo(tmp, 0);
}
tmp[tmp.Length - 1] = indicator;
cacheRegressionChannel = tmp;
return(indicator);
}
}
/// <summary>
/// Linear regression is used to calculate a best fit line for the price data. In addition an upper and lower band is added by calculating the standard deviation of prices from the regression line.
/// </summary>
/// <returns></returns>
public RegressionChannel RegressionChannel(Data.IDataSeries input, int period, double width)
{
if (cacheRegressionChannel != null)
for (int idx = 0; idx < cacheRegressionChannel.Length; idx++)
if (cacheRegressionChannel[idx].Period == period && Math.Abs(cacheRegressionChannel[idx].Width - width) <= double.Epsilon && cacheRegressionChannel[idx].EqualsInput(input))
return cacheRegressionChannel[idx];
lock (checkRegressionChannel)
{
checkRegressionChannel.Period = period;
period = checkRegressionChannel.Period;
checkRegressionChannel.Width = width;
width = checkRegressionChannel.Width;
if (cacheRegressionChannel != null)
for (int idx = 0; idx < cacheRegressionChannel.Length; idx++)
if (cacheRegressionChannel[idx].Period == period && Math.Abs(cacheRegressionChannel[idx].Width - width) <= double.Epsilon && cacheRegressionChannel[idx].EqualsInput(input))
return cacheRegressionChannel[idx];
RegressionChannel indicator = new RegressionChannel();
indicator.BarsRequired = BarsRequired;
indicator.CalculateOnBarClose = CalculateOnBarClose;
#if NT7
indicator.ForceMaximumBarsLookBack256 = ForceMaximumBarsLookBack256;
indicator.MaximumBarsLookBack = MaximumBarsLookBack;
#endif
indicator.Input = input;
indicator.Period = period;
indicator.Width = width;
Indicators.Add(indicator);
indicator.SetUp();
RegressionChannel[] tmp = new RegressionChannel[cacheRegressionChannel == null ? 1 : cacheRegressionChannel.Length + 1];
if (cacheRegressionChannel != null)
cacheRegressionChannel.CopyTo(tmp, 0);
tmp[tmp.Length - 1] = indicator;
cacheRegressionChannel = tmp;
return indicator;
}
}
