Files
QuanTAlib/lib/statistics/variance/Variance.Quantower.cs
T
Miha Kralj 4dbb093892 Add Kahan-Babuška Summation Algorithm and Enhance Variance Indicator Tests
- Introduced a new `Sum` class implementing the Kahan-Babuška algorithm for high-precision rolling summation.
- Added comprehensive documentation for the `Sum` class, detailing its mathematical foundation, performance profile, and use cases.
- Refactored `VarianceIndicator` tests to improve clarity and coverage, including checks for different source types and the ability to change properties.
- Enhanced `UsfIndicator` tests to validate initialization, processing of updates, and property changes.
- Updated `UsfIndicator` implementation to simplify source handling and improve short name generation.
- Modified Qodana configuration to exclude unused auto property accessor warnings.
2025-12-29 18:56:10 -08:00

67 lines
2.3 KiB
C#

using System.Drawing;
using System.Runtime.CompilerServices;
using TradingPlatform.BusinessLayer;
namespace QuanTAlib;
[SkipLocalsInit]
public sealed class VarianceIndicator : Indicator, IWatchlistIndicator
{
[InputParameter("Period", sortIndex: 1, 1, 2000, 1, 0)]
public int Period { get; set; } = 20;
[InputParameter("Population Variance", sortIndex: 2)]
public bool IsPopulation { get; set; } = false;
[IndicatorExtensions.DataSourceInput]
public SourceType Source { get; set; } = SourceType.Close;
[InputParameter("Show cold values", sortIndex: 21)]
public bool ShowColdValues { get; set; } = true;
private Variance? _variance;
private readonly LineSeries? _series;
private Func<IHistoryItem, double>? _priceSelector;
public static int MinHistoryDepths => 0;
int IWatchlistIndicator.MinHistoryDepths => MinHistoryDepths;
public override string ShortName => $"Variance {Period}";
public override string SourceCodeLink => "https://github.com/mihakralj/QuanTAlib/blob/main/lib/statistics/variance/Variance.Quantower.cs";
public VarianceIndicator()
{
OnBackGround = true;
SeparateWindow = true;
Name = "Variance - Rolling Variance";
Description = "Measures the dispersion of a set of data points around their mean";
_series = new(name: "Variance", color: IndicatorExtensions.Statistics, width: 2, style: LineStyle.Solid);
AddLineSeries(_series);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override void OnInit()
{
_variance = new Variance(Period, IsPopulation);
_priceSelector = Source.GetPriceSelector();
base.OnInit();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override void OnUpdate(UpdateArgs args)
{
if (args.Reason != UpdateReason.NewBar && args.Reason != UpdateReason.HistoricalBar)
return;
var item = this.HistoricalData[this.Count - 1, SeekOriginHistory.Begin];
double value = _priceSelector!(item);
var time = this.HistoricalData.Time();
var input = new TValue(time, value);
TValue result = _variance!.Update(input, args.IsNewBar());
_series!.SetValue(result.Value, _variance.IsHot, ShowColdValues);
}
}