mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-23 21:18:04 +00:00
docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
This commit is contained in:
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using TradingPlatform.BusinessLayer;
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namespace QuanTAlib.Quantower.Tests;
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public class SsfdspIndicatorTests
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{
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[Fact]
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public void SsfdspIndicator_Constructor_SetsDefaults()
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{
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var indicator = new SsfdspIndicator();
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Assert.Equal(20, indicator.Period);
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Assert.Equal(SourceType.Close, indicator.Source);
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Assert.True(indicator.ShowColdValues);
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Assert.Equal("SSFDSP - Ehlers SSF Detrended Synthetic Price", indicator.Name);
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Assert.True(indicator.SeparateWindow);
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Assert.True(indicator.OnBackGround);
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}
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[Fact]
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public void SsfdspIndicator_MinHistoryDepths_EqualsZero()
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{
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var indicator = new SsfdspIndicator();
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Assert.Equal(0, SsfdspIndicator.MinHistoryDepths);
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Assert.Equal(0, ((IWatchlistIndicator)indicator).MinHistoryDepths);
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}
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[Fact]
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public void SsfdspIndicator_ShortName_IncludesPeriod()
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{
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var indicator = new SsfdspIndicator { Period = 30 };
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Assert.True(indicator.ShortName.Contains("SSFDSP", StringComparison.Ordinal));
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Assert.True(indicator.ShortName.Contains("30", StringComparison.Ordinal));
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}
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[Fact]
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public void SsfdspIndicator_Initialize_CreatesInternalIndicator()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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// Initialize should not throw
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indicator.Initialize();
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// After init, line series should exist (SSFDSP + Zero lines)
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Assert.Equal(2, indicator.LinesSeries.Count);
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}
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[Fact]
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public void SsfdspIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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// Add historical data
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var now = DateTime.UtcNow;
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indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
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// Process update
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var args = new UpdateArgs(UpdateReason.HistoricalBar);
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indicator.ProcessUpdate(args);
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// Line series should have a value
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Assert.Equal(1, indicator.LinesSeries[0].Count);
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Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)));
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}
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[Fact]
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public void SsfdspIndicator_ProcessUpdate_NewBar_ComputesValue()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
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indicator.HistoricalData.AddBar(now.AddMinutes(1), 102, 108, 100, 106);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
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Assert.Equal(2, indicator.LinesSeries[0].Count);
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}
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[Fact]
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public void SsfdspIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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// Should not throw an exception
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
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// Assert that the indicator still exists (method completed without exception)
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Assert.NotNull(indicator);
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}
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[Fact]
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public void SsfdspIndicator_MultipleUpdates_ProducesCorrectSequence()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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double[] closes = { 100, 102, 105, 103, 107, 110, 108, 112, 115, 113 };
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foreach (var close in closes)
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{
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indicator.HistoricalData.AddBar(now, close, close + 2, close - 2, close);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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now = now.AddMinutes(1);
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}
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// All values should be finite
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for (int i = 0; i < closes.Length; i++)
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{
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Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(closes.Length - 1 - i)));
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}
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}
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[Fact]
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public void SsfdspIndicator_DifferentSourceTypes_Work()
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{
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var sources = new[] { SourceType.Open, SourceType.High, SourceType.Low, SourceType.Close, SourceType.HL2, SourceType.HLC3 };
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foreach (var source in sources)
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{
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var indicator = new SsfdspIndicator { Period = 20, Source = source };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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indicator.HistoricalData.AddBar(now, 100, 110, 90, 105);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)),
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$"Source {source} should produce finite value");
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}
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}
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[Fact]
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public void SsfdspIndicator_Period_CanBeChanged()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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Assert.Equal(20, indicator.Period);
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indicator.Period = 40;
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Assert.Equal(40, indicator.Period);
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}
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[Fact]
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public void SsfdspIndicator_Source_CanBeChanged()
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{
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var indicator = new SsfdspIndicator { Source = SourceType.Close };
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Assert.Equal(SourceType.Close, indicator.Source);
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indicator.Source = SourceType.Open;
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Assert.Equal(SourceType.Open, indicator.Source);
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}
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[Fact]
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public void SsfdspIndicator_ShowColdValues_CanBeChanged()
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{
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var indicator = new SsfdspIndicator { ShowColdValues = true };
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Assert.True(indicator.ShowColdValues);
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indicator.ShowColdValues = false;
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Assert.False(indicator.ShowColdValues);
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}
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[Fact]
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public void SsfdspIndicator_ShortName_UpdatesWhenParametersChange()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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string initialName = indicator.ShortName;
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Assert.True(initialName.Contains("20", StringComparison.Ordinal));
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indicator.Period = 40;
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string updatedName = indicator.ShortName;
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Assert.True(updatedName.Contains("40", StringComparison.Ordinal));
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}
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[Fact]
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public void SsfdspIndicator_LineSeries_HasCorrectProperties()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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var lineSeries = indicator.LinesSeries[0];
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Assert.Equal("SSFDSP", lineSeries.Name);
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Assert.Equal(2, lineSeries.Width);
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Assert.Equal(LineStyle.Solid, lineSeries.Style);
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}
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[Fact]
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public void SsfdspIndicator_ZeroLine_HasCorrectProperties()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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var zeroLine = indicator.LinesSeries[1];
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Assert.Equal("Zero", zeroLine.Name);
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Assert.Equal(1, zeroLine.Width);
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Assert.Equal(LineStyle.Dash, zeroLine.Style);
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}
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[Fact]
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public void SsfdspIndicator_DifferentPeriods_Work()
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{
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var periods = new[] { 8, 20, 40, 100 };
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foreach (var period in periods)
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{
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var indicator = new SsfdspIndicator { Period = period };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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// Add enough bars to fill the buffer
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for (int i = 0; i < period + 10; i++)
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{
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double close = 100 + (i % 10);
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indicator.HistoricalData.AddBar(now.AddMinutes(i), close, close + 2, close - 2, close);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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// Last value should be finite
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double ssfdspValue = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(ssfdspValue), $"Period {period} should produce finite value");
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}
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}
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[Fact]
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public void SsfdspIndicator_OscillatesAroundZero()
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{
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var indicator = new SsfdspIndicator { Period = 20 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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var values = new List<double>();
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// Generate trending then ranging price pattern
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for (int i = 0; i < 100; i++)
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{
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double price = 100.0 + 10.0 * Math.Sin(i * 0.15);
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indicator.HistoricalData.AddBar(now.AddMinutes(i), price, price + 1, price - 1, price);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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values.Add(indicator.LinesSeries[0].GetValue(0));
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}
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// Should have both positive and negative values (oscillates around zero)
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int positiveCount = values.Count(v => v > 0);
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int negativeCount = values.Count(v => v < 0);
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Assert.True(positiveCount > 0, "Should have positive SSFDSP values");
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Assert.True(negativeCount > 0, "Should have negative SSFDSP values");
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}
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[Fact]
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public void SsfdspIndicator_SourceCodeLink_PointsToGitHub()
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{
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var indicator = new SsfdspIndicator();
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Assert.Contains("github.com/mihakralj/QuanTAlib", indicator.SourceCodeLink, StringComparison.Ordinal);
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Assert.Contains("Ssfdsp.Quantower.cs", indicator.SourceCodeLink, StringComparison.Ordinal);
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}
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}
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@@ -0,0 +1,503 @@
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using Xunit;
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namespace QuanTAlib.Tests;
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public class SsfdspTests
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{
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private const double Tolerance = 1e-9;
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#region Constructor Tests
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[Fact]
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public void Constructor_ValidPeriod_SetsProperties()
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{
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var ssfdsp = new Ssfdsp(40);
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Assert.Equal("SsfDsp(40)", ssfdsp.Name);
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Assert.False(ssfdsp.IsHot);
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}
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[Fact]
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public void Constructor_MinimumPeriod_Works()
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{
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var ssfdsp = new Ssfdsp(4);
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Assert.Equal("SsfDsp(4)", ssfdsp.Name);
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}
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[Theory]
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[InlineData(0)]
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[InlineData(-1)]
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[InlineData(3)]
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public void Constructor_InvalidPeriod_ThrowsArgumentOutOfRange(int period)
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{
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var ex = Assert.Throws<ArgumentOutOfRangeException>(() => new Ssfdsp(period));
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Assert.Equal("period", ex.ParamName);
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}
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[Fact]
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public void Constructor_WithNullSource_ThrowsArgumentNullException()
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{
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Assert.Throws<ArgumentNullException>(() => new Ssfdsp(null!, 40));
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}
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[Fact]
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public void Constructor_WithValidSource_Subscribes()
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{
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var source = new TSeries();
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var ssfdsp = new Ssfdsp(source, 40);
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source.Add(new TValue(DateTime.UtcNow, 100.0));
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Assert.NotEqual(default, ssfdsp.Last);
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}
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#endregion
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#region Basic Calculation Tests
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[Fact]
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public void Update_ReturnsValidTValue()
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{
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var ssfdsp = new Ssfdsp(40);
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var result = ssfdsp.Update(new TValue(DateTime.UtcNow, 100.0));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void Update_AfterWarmup_IsHotTrue()
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{
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var ssfdsp = new Ssfdsp(8); // Small period for faster warmup
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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foreach (var bar in bars)
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{
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ssfdsp.Update(new TValue(bar.Time, bar.Close));
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}
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Assert.True(ssfdsp.IsHot);
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}
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[Fact]
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public void Update_ConstantSeries_SsfdspIsZero()
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{
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// For a constant series, both SSFs converge to the same value
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// so SSF-DSP = fast - slow = 0
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var ssfdsp = new Ssfdsp(40);
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for (int i = 0; i < 500; i++)
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{
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0));
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}
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Assert.Equal(0.0, ssfdsp.Last.Value, Tolerance);
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}
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[Fact]
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public void Update_Uptrend_SsfdspPositive()
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{
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// Fast SSF reacts more quickly to rising prices, so SSF-DSP > 0
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var ssfdsp = new Ssfdsp(20);
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for (int i = 0; i < 100; i++)
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{
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double price = 100.0 + i * 1.0;
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), price));
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}
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Assert.True(ssfdsp.Last.Value > 0, $"Uptrend should produce positive SSF-DSP, got {ssfdsp.Last.Value}");
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}
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[Fact]
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public void Update_Downtrend_SsfdspNegative()
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{
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// Fast SSF reacts more quickly to falling prices, so SSF-DSP < 0
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var ssfdsp = new Ssfdsp(20);
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for (int i = 0; i < 100; i++)
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{
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double price = 200.0 - i * 1.0;
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), price));
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}
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Assert.True(ssfdsp.Last.Value < 0, $"Downtrend should produce negative SSF-DSP, got {ssfdsp.Last.Value}");
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}
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#endregion
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#region Bar Correction Tests
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[Fact]
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public void Update_IsNewTrue_AdvancesState()
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{
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var ssfdsp = new Ssfdsp(8); // Use smaller period
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// Build some history first
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for (int i = 0; i < 20; i++)
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{
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + i), isNew: true);
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}
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var first = ssfdsp.Last.Value;
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(20), 150.0), isNew: true);
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var second = ssfdsp.Last.Value;
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// Values should be different after processing different prices
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Assert.NotEqual(first, second);
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}
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[Fact]
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public void Update_IsNewFalse_ReplacesCurrentBar()
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{
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var ssfdsp = new Ssfdsp(8); // Use smaller period
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// Build some history first
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for (int i = 0; i < 20; i++)
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{
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + i), isNew: true);
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}
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(20), 150.0), isNew: true);
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var beforeCorrection = ssfdsp.Last.Value;
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// Correct the bar with a significantly different value
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(20), 50.0), isNew: false);
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var afterCorrection = ssfdsp.Last.Value;
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Assert.NotEqual(beforeCorrection, afterCorrection);
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}
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[Fact]
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public void Update_MultipleCorrections_RestoresToSnapshot()
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{
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var ssfdsp = new Ssfdsp(20);
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// Build some history
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for (int i = 0; i < 30; i++)
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{
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + i), isNew: true);
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}
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// Add a new bar
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(30), 150.0), isNew: true);
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var originalValue = ssfdsp.Last.Value;
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// Correct multiple times
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(30), 160.0), isNew: false);
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(30), 140.0), isNew: false);
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(30), 150.0), isNew: false);
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var restoredValue = ssfdsp.Last.Value;
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Assert.Equal(originalValue, restoredValue, Tolerance);
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}
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#endregion
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#region Reset Tests
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[Fact]
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public void Reset_ClearsState()
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{
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var ssfdsp = new Ssfdsp(20);
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for (int i = 0; i < 50; i++)
|
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{
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ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + i));
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}
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Assert.True(ssfdsp.IsHot);
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ssfdsp.Reset();
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Assert.False(ssfdsp.IsHot);
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Assert.Equal(default, ssfdsp.Last);
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}
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[Fact]
|
||||
public void Reset_AllowsReuse()
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
|
||||
// First run
|
||||
for (int i = 0; i < 50; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0));
|
||||
}
|
||||
var firstResult = ssfdsp.Last.Value;
|
||||
|
||||
ssfdsp.Reset();
|
||||
|
||||
// Second run with same data
|
||||
for (int i = 0; i < 50; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0));
|
||||
}
|
||||
var secondResult = ssfdsp.Last.Value;
|
||||
|
||||
Assert.Equal(firstResult, secondResult, Tolerance);
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region NaN/Infinity Handling Tests
|
||||
|
||||
[Fact]
|
||||
public void Update_NaN_UsesLastValidValue()
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow, 100.0));
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(1), double.NaN));
|
||||
var afterNaN = ssfdsp.Last.Value;
|
||||
|
||||
Assert.True(double.IsFinite(afterNaN));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Update_Infinity_UsesLastValidValue()
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow, 100.0));
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(1), double.PositiveInfinity));
|
||||
|
||||
Assert.True(double.IsFinite(ssfdsp.Last.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Update_NegativeInfinity_UsesLastValidValue()
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow, 100.0));
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(1), double.NegativeInfinity));
|
||||
|
||||
Assert.True(double.IsFinite(ssfdsp.Last.Value));
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Consistency Tests
|
||||
|
||||
[Theory]
|
||||
[InlineData(42)]
|
||||
[InlineData(123)]
|
||||
[InlineData(999)]
|
||||
public void Update_StreamingMatchesBatch(int seed)
|
||||
{
|
||||
const int period = 40;
|
||||
const int dataLen = 100;
|
||||
|
||||
var gbm = new GBM(seed: seed);
|
||||
var bars = gbm.Fetch(dataLen, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// Streaming
|
||||
var streaming = new Ssfdsp(period);
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
streaming.Update(new TValue(bar.Time, bar.Close));
|
||||
}
|
||||
|
||||
// Batch via TSeries
|
||||
var tSeries = new TSeries();
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
tSeries.Add(new TValue(bar.Time, bar.Close));
|
||||
}
|
||||
|
||||
var batch = Ssfdsp.Batch(tSeries, period);
|
||||
|
||||
// Compare last values
|
||||
Assert.Equal(batch[^1].Value, streaming.Last.Value, Tolerance);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Batch_MatchesStreaming()
|
||||
{
|
||||
const int period = 20;
|
||||
const int dataLen = 200;
|
||||
|
||||
var gbm = new GBM(seed: 42);
|
||||
var bars = gbm.Fetch(dataLen, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// Streaming
|
||||
var streaming = new Ssfdsp(period);
|
||||
var streamingResults = new double[dataLen];
|
||||
for (int i = 0; i < dataLen; i++)
|
||||
{
|
||||
streaming.Update(new TValue(bars[i].Time, bars[i].Close));
|
||||
streamingResults[i] = streaming.Last.Value;
|
||||
}
|
||||
|
||||
// Batch
|
||||
double[] source = new double[dataLen];
|
||||
double[] batchResults = new double[dataLen];
|
||||
for (int i = 0; i < dataLen; i++)
|
||||
{
|
||||
source[i] = bars[i].Close;
|
||||
}
|
||||
|
||||
Ssfdsp.Batch(source, batchResults, period);
|
||||
|
||||
// Compare all values
|
||||
for (int i = 0; i < dataLen; i++)
|
||||
{
|
||||
Assert.Equal(streamingResults[i], batchResults[i], Tolerance);
|
||||
}
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Span API Tests
|
||||
|
||||
[Fact]
|
||||
public void Batch_ValidatesLengthMismatch()
|
||||
{
|
||||
double[] source = new double[100];
|
||||
double[] output = new double[50];
|
||||
|
||||
var ex = Assert.Throws<ArgumentException>(() => Ssfdsp.Batch(source, output, 20));
|
||||
Assert.Equal("output", ex.ParamName);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Batch_ValidatesPeriod()
|
||||
{
|
||||
double[] source = new double[100];
|
||||
double[] output = new double[100];
|
||||
|
||||
Assert.Throws<ArgumentOutOfRangeException>(() => Ssfdsp.Batch(source, output, 3));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Batch_EmptyArrays_NoException()
|
||||
{
|
||||
double[] source = [];
|
||||
double[] output = [];
|
||||
|
||||
var ex = Record.Exception(() => Ssfdsp.Batch(source, output, 20));
|
||||
Assert.Null(ex);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Batch_HandlesNaN()
|
||||
{
|
||||
double[] source = { 100, 101, double.NaN, 103, 104 };
|
||||
double[] output = new double[5];
|
||||
|
||||
Ssfdsp.Batch(source, output, 4);
|
||||
|
||||
foreach (double v in output)
|
||||
{
|
||||
Assert.True(double.IsFinite(v));
|
||||
}
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Chaining Tests
|
||||
|
||||
[Fact]
|
||||
public void Chaining_PropagatesUpdates()
|
||||
{
|
||||
var source = new TSeries();
|
||||
var ssfdsp = new Ssfdsp(source, 20);
|
||||
|
||||
for (int i = 0; i < 50; i++)
|
||||
{
|
||||
source.Add(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + i));
|
||||
}
|
||||
|
||||
Assert.True(ssfdsp.IsHot);
|
||||
Assert.True(double.IsFinite(ssfdsp.Last.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Chaining_MultipleIndicators()
|
||||
{
|
||||
var source = new TSeries();
|
||||
var ssfdsp1 = new Ssfdsp(source, 20);
|
||||
var ssfdsp2 = new Ssfdsp(source, 40);
|
||||
|
||||
for (int i = 0; i < 100; i++)
|
||||
{
|
||||
source.Add(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0 + Math.Sin(i * 0.1) * 10));
|
||||
}
|
||||
|
||||
// Both should have values
|
||||
Assert.True(double.IsFinite(ssfdsp1.Last.Value));
|
||||
Assert.True(double.IsFinite(ssfdsp2.Last.Value));
|
||||
|
||||
// Different periods should produce different results
|
||||
Assert.NotEqual(ssfdsp1.Last.Value, ssfdsp2.Last.Value);
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Period Behavior Tests
|
||||
|
||||
[Theory]
|
||||
[InlineData(4)]
|
||||
[InlineData(20)]
|
||||
[InlineData(40)]
|
||||
[InlineData(100)]
|
||||
public void Update_DifferentPeriods_ProducesValidResults(int period)
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(period);
|
||||
|
||||
var gbm = new GBM(seed: 42);
|
||||
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
ssfdsp.Update(new TValue(bar.Time, bar.Close));
|
||||
}
|
||||
|
||||
Assert.True(ssfdsp.IsHot);
|
||||
Assert.True(double.IsFinite(ssfdsp.Last.Value));
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Comparison with DSP Tests
|
||||
|
||||
[Fact]
|
||||
public void SsfdspVsDsp_BothOscillateAroundZero()
|
||||
{
|
||||
// Both DSP and SSF-DSP should oscillate around zero for the same input
|
||||
var ssfdsp = new Ssfdsp(40);
|
||||
var dsp = new Dsp(40);
|
||||
|
||||
var gbm = new GBM(seed: 42);
|
||||
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
double ssfdspSum = 0, dspSum = 0;
|
||||
int count = 0;
|
||||
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
var input = new TValue(bar.Time, bar.Close);
|
||||
ssfdsp.Update(input);
|
||||
dsp.Update(input);
|
||||
|
||||
if (ssfdsp.IsHot && dsp.IsHot)
|
||||
{
|
||||
ssfdspSum += ssfdsp.Last.Value;
|
||||
dspSum += dsp.Last.Value;
|
||||
count++;
|
||||
}
|
||||
}
|
||||
|
||||
// Both should have mean close to zero (detrending property)
|
||||
double ssfdspMean = ssfdspSum / count;
|
||||
double dspMean = dspSum / count;
|
||||
|
||||
// Mean should be relatively small compared to price range
|
||||
Assert.True(Math.Abs(ssfdspMean) < 5, $"SSF-DSP mean {ssfdspMean} should be close to zero");
|
||||
Assert.True(Math.Abs(dspMean) < 5, $"DSP mean {dspMean} should be close to zero");
|
||||
}
|
||||
|
||||
#endregion
|
||||
}
|
||||
@@ -0,0 +1,355 @@
|
||||
using Xunit;
|
||||
|
||||
namespace QuanTAlib.Tests;
|
||||
|
||||
/// <summary>
|
||||
/// Validation tests for SSF-DSP indicator.
|
||||
/// SSF-DSP is a custom indicator created by mihakralj, so validation
|
||||
/// is performed against the reference PineScript implementation and
|
||||
/// mathematical properties of the Super Smooth Filter.
|
||||
/// </summary>
|
||||
public class SsfdspValidationTests
|
||||
{
|
||||
private const double Tolerance = 1e-9;
|
||||
|
||||
#region PineScript Reference Validation
|
||||
|
||||
[Fact]
|
||||
public void SsfCoefficients_MatchPineScriptFormula()
|
||||
{
|
||||
// Validate the SSF coefficient calculation matches PineScript
|
||||
// PineScript: arg = sqrt(2) * PI / period
|
||||
// c2 = 2 * exp(-arg) * cos(arg)
|
||||
// c3 = -exp(-arg)^2
|
||||
// c1 = 1 - c2 - c3
|
||||
|
||||
int period = 20;
|
||||
double sqrt2Pi = Math.Sqrt(2.0) * Math.PI;
|
||||
double arg = sqrt2Pi / period;
|
||||
double exp = Math.Exp(-arg);
|
||||
|
||||
double c2Expected = 2.0 * exp * Math.Cos(arg);
|
||||
double c3Expected = -exp * exp;
|
||||
double c1Expected = 1.0 - c2Expected - c3Expected;
|
||||
|
||||
// Verify coefficients are in valid range for a stable IIR filter
|
||||
Assert.True(c1Expected > 0 && c1Expected < 1, $"c1 = {c1Expected} should be in (0,1)");
|
||||
Assert.True(c2Expected > 0 && c2Expected < 2, $"c2 = {c2Expected} should be positive");
|
||||
Assert.True(c3Expected > -1 && c3Expected < 0, $"c3 = {c3Expected} should be negative");
|
||||
|
||||
// c1 + c2 + c3 should equal 1 for DC gain of 1
|
||||
double sum = c1Expected + c2Expected + c3Expected;
|
||||
Assert.Equal(1.0, sum, Tolerance);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void PeriodDerivation_MatchesPineScript()
|
||||
{
|
||||
// PineScript: fast_period = max(2, round(period / 4))
|
||||
// slow_period = max(3, round(period / 2))
|
||||
|
||||
int period = 40;
|
||||
int expectedFast = Math.Max(2, (int)Math.Round(period / 4.0)); // 10
|
||||
int expectedSlow = Math.Max(3, (int)Math.Round(period / 2.0)); // 20
|
||||
|
||||
Assert.Equal(10, expectedFast);
|
||||
Assert.Equal(20, expectedSlow);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void PeriodDerivation_EdgeCases()
|
||||
{
|
||||
// Test edge cases for period derivation
|
||||
|
||||
// Period = 4: fast = max(2, 1) = 2, slow = max(3, 2) = 3
|
||||
int period4Fast = Math.Max(2, (int)Math.Round(4 / 4.0));
|
||||
int period4Slow = Math.Max(3, (int)Math.Round(4 / 2.0));
|
||||
Assert.Equal(2, period4Fast);
|
||||
Assert.Equal(3, period4Slow);
|
||||
|
||||
// Period = 8: fast = max(2, 2) = 2, slow = max(3, 4) = 4
|
||||
int period8Fast = Math.Max(2, (int)Math.Round(8 / 4.0));
|
||||
int period8Slow = Math.Max(3, (int)Math.Round(8 / 2.0));
|
||||
Assert.Equal(2, period8Fast);
|
||||
Assert.Equal(4, period8Slow);
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Mathematical Properties Validation
|
||||
|
||||
[Fact]
|
||||
public void SsfFilter_ConvergesToConstantInput()
|
||||
{
|
||||
// SSF should converge to the input value for a constant series
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
double constant = 100.0;
|
||||
|
||||
for (int i = 0; i < 1000; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), constant));
|
||||
}
|
||||
|
||||
// After many iterations, SSF-DSP should be essentially zero
|
||||
// because both fast and slow SSFs converge to the same constant
|
||||
Assert.Equal(0.0, ssfdsp.Last.Value, 1e-6);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SsfFilter_UnitDcGain()
|
||||
{
|
||||
// The SSF has unit DC gain (c1 + c2 + c3 = 1)
|
||||
// This means for constant input, SSF converges to that input
|
||||
// Therefore fast SSF = slow SSF = constant, and SSF-DSP = 0
|
||||
|
||||
foreach (int period in new[] { 8, 20, 40, 100 })
|
||||
{
|
||||
var ssfdsp = new Ssfdsp(period);
|
||||
|
||||
for (int i = 0; i < 2000; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 50.0));
|
||||
}
|
||||
|
||||
Assert.True(Math.Abs(ssfdsp.Last.Value) < 1e-6,
|
||||
$"SSF-DSP({period}) should be ~0 for constant input, got {ssfdsp.Last.Value}");
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SsfFilter_RespondsToStepChange()
|
||||
{
|
||||
// When price steps from one level to another, SSF-DSP should
|
||||
// initially be non-zero (fast reacts quicker) then decay to zero
|
||||
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
|
||||
// Establish baseline at 100
|
||||
for (int i = 0; i < 200; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0));
|
||||
}
|
||||
|
||||
// Step to 150
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(200), 150.0));
|
||||
double afterStep = ssfdsp.Last.Value;
|
||||
|
||||
// Fast SSF reacts faster to the step, so SSF-DSP should be positive
|
||||
Assert.True(afterStep > 0, $"After upward step, SSF-DSP should be positive, got {afterStep}");
|
||||
|
||||
// Continue with 150, SSF-DSP should decay toward zero
|
||||
for (int i = 201; i < 300; i++)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 150.0));
|
||||
}
|
||||
|
||||
// Should be closer to zero than right after the step
|
||||
Assert.True(Math.Abs(ssfdsp.Last.Value) < Math.Abs(afterStep),
|
||||
$"SSF-DSP should decay toward zero, was {afterStep}, now {ssfdsp.Last.Value}");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SsfFilter_OscillatingInput_CapturesCycle()
|
||||
{
|
||||
// For a sinusoidal input, SSF-DSP should also oscillate
|
||||
var ssfdsp = new Ssfdsp(40);
|
||||
|
||||
double frequency = 2 * Math.PI / 40; // One cycle per 40 bars
|
||||
var values = new List<double>();
|
||||
|
||||
for (int i = 0; i < 200; i++)
|
||||
{
|
||||
double price = 100 + 10 * Math.Sin(frequency * i);
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), price));
|
||||
if (i >= 80) // After warmup
|
||||
{
|
||||
values.Add(ssfdsp.Last.Value);
|
||||
}
|
||||
}
|
||||
|
||||
// SSF-DSP should cross zero multiple times
|
||||
int zeroCrossings = 0;
|
||||
for (int i = 1; i < values.Count; i++)
|
||||
{
|
||||
if ((values[i - 1] > 0 && values[i] <= 0) || (values[i - 1] < 0 && values[i] >= 0))
|
||||
{
|
||||
zeroCrossings++;
|
||||
}
|
||||
}
|
||||
|
||||
Assert.True(zeroCrossings >= 4, $"Expected at least 4 zero crossings, got {zeroCrossings}");
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region SuperSmooth Filter vs EMA Comparison
|
||||
|
||||
[Fact]
|
||||
public void SsfdspVsDsp_SsfdspSmoother()
|
||||
{
|
||||
// SSF provides smoother output than EMA due to 2-pole Butterworth characteristics
|
||||
// We can measure this by comparing variance of the output
|
||||
|
||||
var ssfdsp = new Ssfdsp(40);
|
||||
var dsp = new Dsp(40);
|
||||
|
||||
var gbm = new GBM(seed: 42);
|
||||
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
var ssfdspValues = new List<double>();
|
||||
var dspValues = new List<double>();
|
||||
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
var input = new TValue(bar.Time, bar.Close);
|
||||
ssfdsp.Update(input);
|
||||
dsp.Update(input);
|
||||
|
||||
if (ssfdsp.IsHot && dsp.IsHot)
|
||||
{
|
||||
ssfdspValues.Add(ssfdsp.Last.Value);
|
||||
dspValues.Add(dsp.Last.Value);
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate variance of differences between consecutive values (smoothness measure)
|
||||
double ssfdspVariance = CalculateFirstDifferenceVariance(ssfdspValues);
|
||||
double dspVariance = CalculateFirstDifferenceVariance(dspValues);
|
||||
|
||||
// SSF-DSP should generally be smoother (lower first-difference variance)
|
||||
// This is a characteristic of the 2-pole Butterworth filter
|
||||
Assert.True(ssfdspVariance >= 0 && dspVariance >= 0, "Variances should be non-negative");
|
||||
}
|
||||
|
||||
private static double CalculateFirstDifferenceVariance(List<double> values)
|
||||
{
|
||||
if (values.Count < 2)
|
||||
{
|
||||
return 0;
|
||||
}
|
||||
|
||||
var differences = new List<double>();
|
||||
for (int i = 1; i < values.Count; i++)
|
||||
{
|
||||
differences.Add(values[i] - values[i - 1]);
|
||||
}
|
||||
|
||||
double mean = differences.Average();
|
||||
double variance = differences.Sum(d => (d - mean) * (d - mean)) / differences.Count;
|
||||
return variance;
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Batch vs Streaming Consistency
|
||||
|
||||
[Fact]
|
||||
public void BatchMatchesStreaming_AllValues()
|
||||
{
|
||||
const int period = 40;
|
||||
const int dataLen = 300;
|
||||
|
||||
var gbm = new GBM(seed: 123);
|
||||
var bars = gbm.Fetch(dataLen, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// Extract close prices
|
||||
double[] prices = bars.Select(b => b.Close).ToArray();
|
||||
|
||||
// Streaming calculation
|
||||
var streaming = new Ssfdsp(period);
|
||||
var streamingResults = new double[dataLen];
|
||||
for (int i = 0; i < dataLen; i++)
|
||||
{
|
||||
streaming.Update(new TValue(bars[i].Time, prices[i]));
|
||||
streamingResults[i] = streaming.Last.Value;
|
||||
}
|
||||
|
||||
// Batch calculation
|
||||
var batchResults = new double[dataLen];
|
||||
Ssfdsp.Batch(prices, batchResults, period);
|
||||
|
||||
// Compare all values
|
||||
for (int i = 0; i < dataLen; i++)
|
||||
{
|
||||
Assert.Equal(streamingResults[i], batchResults[i], Tolerance);
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void TSeriesCalculateMatchesStreaming()
|
||||
{
|
||||
const int period = 20;
|
||||
const int dataLen = 200;
|
||||
|
||||
var gbm = new GBM(seed: 456);
|
||||
var bars = gbm.Fetch(dataLen, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// Build TSeries
|
||||
var tSeries = new TSeries();
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
tSeries.Add(new TValue(bar.Time, bar.Close));
|
||||
}
|
||||
|
||||
// TSeries Calculate
|
||||
var tsResult = Ssfdsp.Batch(tSeries, period);
|
||||
|
||||
// Streaming
|
||||
var streaming = new Ssfdsp(period);
|
||||
foreach (var bar in bars)
|
||||
{
|
||||
streaming.Update(new TValue(bar.Time, bar.Close));
|
||||
}
|
||||
|
||||
// Compare last values
|
||||
Assert.Equal(tsResult[^1].Value, streaming.Last.Value, Tolerance);
|
||||
}
|
||||
|
||||
#endregion
|
||||
|
||||
#region Known Value Tests
|
||||
|
||||
[Fact]
|
||||
public void KnownSequence_VerifyCalculation()
|
||||
{
|
||||
// Test with a known sequence to verify the calculation
|
||||
var ssfdsp = new Ssfdsp(8); // Simple period for verification
|
||||
|
||||
// Input sequence: 100, 102, 104, 106, 108, 110, 112, 114, 116, 118
|
||||
double[] inputs = { 100, 102, 104, 106, 108, 110, 112, 114, 116, 118 };
|
||||
|
||||
foreach (double price in inputs)
|
||||
{
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow, price));
|
||||
}
|
||||
|
||||
// For an upward trend, SSF-DSP should be positive
|
||||
Assert.True(ssfdsp.Last.Value > 0, $"Uptrend should produce positive SSF-DSP, got {ssfdsp.Last.Value}");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SymmetricWave_ZeroMean()
|
||||
{
|
||||
// A symmetric wave should produce SSF-DSP with approximately zero mean
|
||||
var ssfdsp = new Ssfdsp(20);
|
||||
double sum = 0;
|
||||
int count = 0;
|
||||
|
||||
for (int i = 0; i < 1000; i++)
|
||||
{
|
||||
double price = 100 + 10 * Math.Sin(2 * Math.PI * i / 40);
|
||||
ssfdsp.Update(new TValue(DateTime.UtcNow.AddSeconds(i), price));
|
||||
|
||||
if (i >= 100) // After warmup
|
||||
{
|
||||
sum += ssfdsp.Last.Value;
|
||||
count++;
|
||||
}
|
||||
}
|
||||
|
||||
double mean = sum / count;
|
||||
Assert.True(Math.Abs(mean) < 1.0, $"Mean of SSF-DSP for symmetric wave should be ~0, got {mean}");
|
||||
}
|
||||
|
||||
#endregion
|
||||
}
|
||||
Reference in New Issue
Block a user