mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-30 02:27:43 +00:00
Miha Kralj
7253f61299
- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic. - Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks. - Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations). - Enhanced documentation for TRAMA, including performance profiles and quality metrics. - Updated workspace configuration by removing unnecessary folder references.
81 lines
3.2 KiB
C#
81 lines
3.2 KiB
C#
using System.Drawing;
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using System.Runtime.CompilerServices;
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using TradingPlatform.BusinessLayer;
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namespace QuanTAlib;
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[SkipLocalsInit]
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public sealed class CcorIndicator : Indicator, IWatchlistIndicator
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{
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[InputParameter("Period", sortIndex: 1, 2, 200, 1, 0)]
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public int Period { get; set; } = 20;
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[InputParameter("Threshold", sortIndex: 2, 0.1, 90.0, 0.1, 1)]
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public double Threshold { get; set; } = 9.0;
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[IndicatorExtensions.DataSourceInput]
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public SourceType Source { get; set; } = SourceType.Close;
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[InputParameter("Show cold values", sortIndex: 21)]
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public bool ShowColdValues { get; set; } = true;
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private Ccor _ccor = null!;
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private readonly LineSeries _realSeries;
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private readonly LineSeries _imagSeries;
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private readonly LineSeries _angleSeries;
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private readonly LineSeries _stateSeries;
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private Func<IHistoryItem, double> _priceSelector = null!;
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public static int MinHistoryDepths => 0;
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int IWatchlistIndicator.MinHistoryDepths => MinHistoryDepths;
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public override string ShortName => $"CCOR ({Period},{Threshold:F1})";
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public override string SourceCodeLink => "https://github.com/mihakralj/QuanTAlib/blob/main/lib/cycles/ccor/Ccor.Quantower.cs";
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public CcorIndicator()
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{
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OnBackGround = true;
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SeparateWindow = true;
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Name = "CCOR - Ehlers Correlation Cycle";
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Description = "Ehlers' Correlation Cycle uses dual Pearson correlation (cosine + negative sine) to derive a phasor, monotonic angle, and market state classification";
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_realSeries = new LineSeries(name: "Real", color: IndicatorExtensions.Oscillators, width: 2, style: LineStyle.Solid);
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_imagSeries = new LineSeries(name: "Imag", color: Color.FromArgb(128, 128, 255), width: 1, style: LineStyle.Dash);
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_angleSeries = new LineSeries(name: "Angle", color: Color.FromArgb(200, 200, 100), width: 1, style: LineStyle.Dot);
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_stateSeries = new LineSeries(name: "State", color: Color.FromArgb(255, 165, 0), width: 2, style: LineStyle.Histogramm);
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AddLineSeries(_realSeries);
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AddLineSeries(_imagSeries);
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AddLineSeries(_angleSeries);
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AddLineSeries(_stateSeries);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void OnInit()
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{
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_ccor = new Ccor(Period, Threshold);
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_priceSelector = Source.GetPriceSelector();
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base.OnInit();
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void OnUpdate(UpdateArgs args)
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{
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if (args.Reason != UpdateReason.NewBar && args.Reason != UpdateReason.HistoricalBar)
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{
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return;
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}
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var item = this.HistoricalData[this.Count - 1, SeekOriginHistory.Begin];
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double value = _priceSelector(item);
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var time = this.HistoricalData.Time();
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var input = new TValue(time, value);
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TValue result = _ccor.Update(input, args.IsNewBar());
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_realSeries.SetValue(result.Value, _ccor.IsHot, ShowColdValues);
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_imagSeries.SetValue(_ccor.Imag, _ccor.IsHot, ShowColdValues);
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_angleSeries.SetValue(_ccor.Angle, _ccor.IsHot, ShowColdValues);
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_stateSeries.SetValue(_ccor.MarketState, _ccor.IsHot, ShowColdValues);
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}
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}
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