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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:
Miha Kralj
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using TradingPlatform.BusinessLayer;
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namespace QuanTAlib.Tests;
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public class SmaIndicatorTests
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{
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[Fact]
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public void SmaIndicator_Constructor_SetsDefaults()
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{
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var indicator = new SmaIndicator();
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Assert.Equal(10, 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("SMA - Simple Moving Average", indicator.Name);
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Assert.False(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 SmaIndicator_MinHistoryDepths_EqualsZero()
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{
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var indicator = new SmaIndicator { Period = 20 };
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Assert.Equal(0, SmaIndicator.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 SmaIndicator_ShortName_IncludesPeriodAndSource()
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{
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var indicator = new SmaIndicator { Period = 15 };
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Assert.Contains("SMA", indicator.ShortName, StringComparison.Ordinal);
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Assert.Contains("15", indicator.ShortName, StringComparison.Ordinal);
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}
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[Fact]
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public void SmaIndicator_Initialize_CreatesInternalSma()
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{
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var indicator = new SmaIndicator { Period = 10 };
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// Initialize should not throw
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indicator.Initialize();
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// After init, line series should exist
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Assert.Single(indicator.LinesSeries);
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}
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[Fact]
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public void SmaIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
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{
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var indicator = new SmaIndicator { Period = 3 };
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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 SmaIndicator_ProcessUpdate_NewBar_ComputesValue()
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{
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var indicator = new SmaIndicator { Period = 3 };
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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 SmaIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
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{
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var indicator = new SmaIndicator { Period = 3 };
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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.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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double firstValue = indicator.LinesSeries[0].GetValue(0);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
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double secondValue = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(firstValue));
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Assert.True(double.IsFinite(secondValue));
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}
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[Fact]
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public void SmaIndicator_MultipleUpdates_ProducesCorrectSmaSequence()
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{
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var indicator = new SmaIndicator { Period = 3 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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double[] closes = { 100, 102, 104, 103, 105 };
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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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// Last SMA(3) should be average of last 3 values: (103 + 105 + 104) / 3 ≈ 104
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// Actually: (104 + 103 + 105) / 3 = 104
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double lastSma = indicator.LinesSeries[0].GetValue(0);
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Assert.True(lastSma >= 103 && lastSma <= 105);
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}
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[Fact]
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public void SmaIndicator_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 SmaIndicator { Period = 3, 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 SmaIndicator_Period_CanBeChanged()
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{
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var indicator = new SmaIndicator { Period = 5 };
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Assert.Equal(5, indicator.Period);
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indicator.Period = 20;
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Assert.Equal(20, indicator.Period);
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Assert.Equal(0, SmaIndicator.MinHistoryDepths);
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}
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}
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@@ -0,0 +1,601 @@
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namespace QuanTAlib.Tests;
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public class SmaTests
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{
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[Fact]
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public void Sma_Constructor_ValidatesInput()
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{
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Assert.Throws<ArgumentException>(() => new Sma(0));
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Assert.Throws<ArgumentException>(() => new Sma(-1));
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var sma = new Sma(10);
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Assert.NotNull(sma);
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}
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[Fact]
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public void Sma_Calc_ReturnsValue()
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{
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var sma = new Sma(10);
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Assert.Equal(0, sma.Last.Value);
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TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.True(result.Value > 0);
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Assert.Equal(result.Value, sma.Last.Value);
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}
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[Fact]
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public void Sma_FirstValue_ReturnsItself()
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{
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var sma = new Sma(10);
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TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.Equal(100.0, result.Value, 1e-10);
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}
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[Fact]
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public void Sma_Calc_IsNew_AcceptsParameter()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
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double value1 = sma.Last.Value;
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sma.Update(new TValue(DateTime.UtcNow, 200), isNew: true);
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double value2 = sma.Last.Value;
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// Values should change with new bars
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Assert.NotEqual(value1, value2);
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}
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[Fact]
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public void Sma_Calc_IsNew_False_UpdatesValue()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110), isNew: true);
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double beforeUpdate = sma.Last.Value;
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sma.Update(new TValue(DateTime.UtcNow, 120), isNew: false);
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double afterUpdate = sma.Last.Value;
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// Update should change the value
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Assert.NotEqual(beforeUpdate, afterUpdate);
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}
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[Fact]
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public void Sma_Reset_ClearsState()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 105));
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double valueBefore = sma.Last.Value;
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sma.Reset();
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Assert.Equal(0, sma.Last.Value);
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// After reset, should accept new values
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sma.Update(new TValue(DateTime.UtcNow, 50));
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Assert.NotEqual(0, sma.Last.Value);
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Assert.NotEqual(valueBefore, sma.Last.Value);
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}
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[Fact]
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public void Sma_Properties_Accessible()
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{
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var sma = new Sma(10);
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Assert.Equal(0, sma.Last.Value);
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Assert.False(sma.IsHot);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.NotEqual(0, sma.Last.Value);
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}
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[Fact]
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public void Sma_IsHot_BecomesTrueWhenBufferFull()
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{
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var sma = new Sma(5);
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Assert.False(sma.IsHot);
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for (int i = 1; i <= 4; i++)
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{
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sma.Update(new TValue(DateTime.UtcNow, i * 10));
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Assert.False(sma.IsHot);
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}
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sma.Update(new TValue(DateTime.UtcNow, 50));
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Assert.True(sma.IsHot);
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}
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[Fact]
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public void Sma_CalculatesCorrectAverage()
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{
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var sma = new Sma(5);
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sma.Update(new TValue(DateTime.UtcNow, 10));
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sma.Update(new TValue(DateTime.UtcNow, 20));
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sma.Update(new TValue(DateTime.UtcNow, 30));
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sma.Update(new TValue(DateTime.UtcNow, 40));
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sma.Update(new TValue(DateTime.UtcNow, 50));
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// SMA(5) of 10,20,30,40,50 = 150/5 = 30
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Assert.Equal(30.0, sma.Last.Value, 1e-10);
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}
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[Fact]
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public void Sma_SlidingWindow_Works()
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{
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var sma = new Sma(3);
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sma.Update(new TValue(DateTime.UtcNow, 10));
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sma.Update(new TValue(DateTime.UtcNow, 20));
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sma.Update(new TValue(DateTime.UtcNow, 30));
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// SMA(3) of 10,20,30 = 60/3 = 20
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Assert.Equal(20.0, sma.Last.Value, 1e-10);
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sma.Update(new TValue(DateTime.UtcNow, 40));
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// SMA(3) of 20,30,40 = 90/3 = 30
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Assert.Equal(30.0, sma.Last.Value, 1e-10);
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sma.Update(new TValue(DateTime.UtcNow, 50));
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// SMA(3) of 30,40,50 = 120/3 = 40
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Assert.Equal(40.0, sma.Last.Value, 1e-10);
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}
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[Fact]
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public void Sma_IterativeCorrections_RestoreToOriginalState()
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{
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var sma = new Sma(5);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
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// Feed 10 new values
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TValue tenthInput = default;
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for (int i = 0; i < 10; i++)
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{
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var bar = gbm.Next(isNew: true);
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tenthInput = new TValue(bar.Time, bar.Close);
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sma.Update(tenthInput, isNew: true);
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}
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// Remember SMA state after 10 values
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double smaAfterTen = sma.Last.Value;
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// Generate 9 corrections with isNew=false (different values)
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for (int i = 0; i < 9; i++)
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{
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var bar = gbm.Next(isNew: false);
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sma.Update(new TValue(bar.Time, bar.Close), isNew: false);
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}
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// Feed the remembered 10th input again with isNew=false
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TValue finalSma = sma.Update(tenthInput, isNew: false);
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// SMA should match the original state after 10 values
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Assert.Equal(smaAfterTen, finalSma.Value, 1e-10);
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}
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[Fact]
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public void Sma_BatchCalc_MatchesIterativeCalc()
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{
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var smaIterative = new Sma(10);
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var smaBatch = new Sma(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
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// Generate data
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var series = new TSeries();
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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series.Add(bar.Time, bar.Close);
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}
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Assert.True(series.Count > 0);
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// Calculate iteratively
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var iterativeResults = new TSeries();
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foreach (var item in series)
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{
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iterativeResults.Add(smaIterative.Update(item));
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}
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// Calculate batch
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var batchResults = smaBatch.Update(series);
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// Compare
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Assert.Equal(iterativeResults.Count, batchResults.Count);
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for (int i = 0; i < iterativeResults.Count; i++)
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{
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Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
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Assert.Equal(iterativeResults[i].Time, batchResults[i].Time);
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}
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}
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[Fact]
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public void Sma_Result_ImplicitConversionToDouble()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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// This should compile and work because TValue has implicit conversion to double
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double result = sma.Last.Value;
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Assert.Equal(100.0, result, 1e-10);
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}
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[Fact]
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public void Sma_NaN_Input_UsesLastValidValue()
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{
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var sma = new Sma(5);
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// Feed some valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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// Feed NaN - should use last valid value (110)
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var resultAfterNaN = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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// Result should be finite (not NaN)
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Assert.True(double.IsFinite(resultAfterNaN.Value));
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Assert.NotEqual(0, resultAfterNaN.Value);
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}
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[Fact]
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public void Sma_Infinity_Input_UsesLastValidValue()
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{
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var sma = new Sma(5);
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// Feed some valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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// Feed positive infinity - should use last valid value
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var resultAfterPosInf = sma.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(resultAfterPosInf.Value));
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// Feed negative infinity - should use last valid value
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var resultAfterNegInf = sma.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
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Assert.True(double.IsFinite(resultAfterNegInf.Value));
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}
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[Fact]
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public void Sma_MultipleNaN_ContinuesWithLastValid()
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{
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var sma = new Sma(5);
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// Feed valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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sma.Update(new TValue(DateTime.UtcNow, 120));
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// Feed multiple NaN values
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var r1 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r2 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r3 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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// All results should be finite
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Assert.True(double.IsFinite(r1.Value));
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Assert.True(double.IsFinite(r2.Value));
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Assert.True(double.IsFinite(r3.Value));
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}
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[Fact]
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public void Sma_BatchCalc_HandlesNaN()
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{
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var sma = new Sma(5);
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// Create series with NaN values interspersed
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var series = new TSeries();
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series.Add(DateTime.UtcNow.Ticks, 100);
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series.Add(DateTime.UtcNow.Ticks + 1, 110);
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series.Add(DateTime.UtcNow.Ticks + 2, double.NaN);
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series.Add(DateTime.UtcNow.Ticks + 3, 120);
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series.Add(DateTime.UtcNow.Ticks + 4, double.PositiveInfinity);
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series.Add(DateTime.UtcNow.Ticks + 5, 130);
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var results = sma.Update(series);
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// All results should be finite
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foreach (var result in results)
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{
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Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
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}
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}
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[Fact]
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public void Sma_Reset_ClearsLastValidValue()
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{
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var sma = new Sma(5);
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// Feed values including NaN
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sma.Update(new TValue(DateTime.UtcNow, 100));
|
||||
sma.Update(new TValue(DateTime.UtcNow, double.NaN));
|
||||
|
||||
// Reset
|
||||
sma.Reset();
|
||||
|
||||
// After reset, first valid value should establish new baseline
|
||||
var result = sma.Update(new TValue(DateTime.UtcNow, 50));
|
||||
Assert.Equal(50.0, result.Value, 1e-10);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_StaticBatch_Works()
|
||||
{
|
||||
var series = new TSeries();
|
||||
series.Add(DateTime.UtcNow.Ticks, 10);
|
||||
series.Add(DateTime.UtcNow.Ticks + 1, 20);
|
||||
series.Add(DateTime.UtcNow.Ticks + 2, 30);
|
||||
series.Add(DateTime.UtcNow.Ticks + 3, 40);
|
||||
series.Add(DateTime.UtcNow.Ticks + 4, 50);
|
||||
|
||||
var results = Sma.Batch(series, 3);
|
||||
|
||||
Assert.Equal(5, results.Count);
|
||||
// SMA(3) for last value: (30+40+50)/3 = 40
|
||||
Assert.Equal(40.0, results.Last.Value, 1e-10);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_Period1_ReturnsInputValues()
|
||||
{
|
||||
var sma = new Sma(1);
|
||||
|
||||
Assert.Equal(100.0, sma.Update(new TValue(DateTime.UtcNow, 100)).Value, 1e-10);
|
||||
Assert.Equal(200.0, sma.Update(new TValue(DateTime.UtcNow, 200)).Value, 1e-10);
|
||||
Assert.Equal(150.0, sma.Update(new TValue(DateTime.UtcNow, 150)).Value, 1e-10);
|
||||
}
|
||||
|
||||
// ============== Span API Tests ==============
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_ValidatesInput()
|
||||
{
|
||||
double[] source = [1, 2, 3, 4, 5];
|
||||
double[] output = new double[5];
|
||||
double[] wrongSizeOutput = new double[3];
|
||||
|
||||
// Period must be > 0
|
||||
Assert.Throws<ArgumentException>(() => Sma.Batch(source.AsSpan(), output.AsSpan(), 0));
|
||||
Assert.Throws<ArgumentException>(() => Sma.Batch(source.AsSpan(), output.AsSpan(), -1));
|
||||
|
||||
// Output must be same length as source
|
||||
Assert.Throws<ArgumentException>(() => Sma.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_MatchesTSeriesBatch()
|
||||
{
|
||||
var series = new TSeries();
|
||||
double[] source = new double[100];
|
||||
double[] output = new double[100];
|
||||
|
||||
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
|
||||
for (int i = 0; i < 100; i++)
|
||||
{
|
||||
var bar = gbm.Next(isNew: true);
|
||||
source[i] = bar.Close;
|
||||
series.Add(bar.Time, bar.Close);
|
||||
}
|
||||
|
||||
// Calculate with TSeries API
|
||||
var tseriesResult = Sma.Batch(series, 10);
|
||||
|
||||
// Calculate with Span API
|
||||
Sma.Batch(source.AsSpan(), output.AsSpan(), 10);
|
||||
|
||||
// Compare results
|
||||
for (int i = 0; i < 100; i++)
|
||||
{
|
||||
Assert.Equal(tseriesResult[i].Value, output[i], 1e-10);
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_CalculatesCorrectly()
|
||||
{
|
||||
double[] source = [10, 20, 30, 40, 50];
|
||||
double[] output = new double[5];
|
||||
|
||||
Sma.Batch(source.AsSpan(), output.AsSpan(), 3);
|
||||
|
||||
// SMA(3) warmup: 10, (10+20)/2=15, (10+20+30)/3=20, then sliding: (20+30+40)/3=30, (30+40+50)/3=40
|
||||
Assert.Equal(10.0, output[0], 1e-10);
|
||||
Assert.Equal(15.0, output[1], 1e-10);
|
||||
Assert.Equal(20.0, output[2], 1e-10);
|
||||
Assert.Equal(30.0, output[3], 1e-10);
|
||||
Assert.Equal(40.0, output[4], 1e-10);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_ZeroAllocation()
|
||||
{
|
||||
double[] source = new double[10000];
|
||||
|
||||
double[] output = new double[10000];
|
||||
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
source[i] = gbm.Next().Close;
|
||||
}
|
||||
|
||||
// Warm up
|
||||
Sma.Batch(source.AsSpan(), output.AsSpan(), 100);
|
||||
|
||||
// This test verifies the method runs without throwing
|
||||
// (allocation is measured by BenchmarkDotNet, not unit tests)
|
||||
Assert.True(double.IsFinite(output[^1]));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_HandlesNaN()
|
||||
{
|
||||
double[] source = [100, 110, double.NaN, 120, 130];
|
||||
double[] output = new double[5];
|
||||
|
||||
Sma.Batch(source.AsSpan(), output.AsSpan(), 3);
|
||||
|
||||
// All outputs should be finite
|
||||
foreach (var val in output)
|
||||
{
|
||||
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_SpanBatch_Period1_ReturnsInput()
|
||||
{
|
||||
double[] source = [10, 20, 30, 40, 50];
|
||||
double[] output = new double[5];
|
||||
|
||||
Sma.Batch(source.AsSpan(), output.AsSpan(), 1);
|
||||
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
Assert.Equal(source[i], output[i], 1e-10);
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void Sma_AllModes_ProduceSameResult()
|
||||
{
|
||||
// Arrange
|
||||
const int period = 10;
|
||||
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
|
||||
var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
var series = bars.Close;
|
||||
|
||||
// 1. Batch Mode
|
||||
var batchSeries = Sma.Batch(series, period);
|
||||
double expected = batchSeries.Last.Value;
|
||||
|
||||
// 2. Span Mode
|
||||
var tValues = series.Values.ToArray();
|
||||
var spanInput = new ReadOnlySpan<double>(tValues);
|
||||
var spanOutput = new double[tValues.Length];
|
||||
Sma.Batch(spanInput, spanOutput, period);
|
||||
double spanResult = spanOutput[^1];
|
||||
|
||||
// 3. Streaming Mode
|
||||
var streamingInd = new Sma(period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
{
|
||||
streamingInd.Update(series[i]);
|
||||
}
|
||||
double streamingResult = streamingInd.Last.Value;
|
||||
|
||||
// 4. Eventing Mode
|
||||
var pubSource = new TSeries();
|
||||
var eventingInd = new Sma(pubSource, period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
{
|
||||
pubSource.Add(series[i]);
|
||||
}
|
||||
double eventingResult = eventingInd.Last.Value;
|
||||
|
||||
// Assert
|
||||
Assert.Equal(expected, spanResult, precision: 9);
|
||||
Assert.Equal(expected, streamingResult, precision: 9);
|
||||
Assert.Equal(expected, eventingResult, precision: 9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Chainability_Works()
|
||||
{
|
||||
var source = new TSeries();
|
||||
var sma = new Sma(source, 10);
|
||||
|
||||
source.Add(new TValue(DateTime.UtcNow, 100));
|
||||
Assert.Equal(100, sma.Last.Value);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void WarmupPeriod_IsSetCorrectly()
|
||||
{
|
||||
var sma = new Sma(10);
|
||||
Assert.Equal(10, sma.WarmupPeriod);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Prime_SetsStateCorrectly()
|
||||
{
|
||||
var sma = new Sma(5);
|
||||
double[] history = [10, 20, 30, 40, 50]; // SMA(5) = 30
|
||||
|
||||
sma.Prime(history);
|
||||
|
||||
Assert.True(sma.IsHot);
|
||||
Assert.Equal(30.0, sma.Last.Value, 1e-10);
|
||||
|
||||
// Verify it continues correctly
|
||||
sma.Update(new TValue(DateTime.UtcNow, 60)); // 20,30,40,50,60 -> 40
|
||||
Assert.Equal(40.0, sma.Last.Value, 1e-10);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Prime_WithInsufficientHistory_IsNotHot()
|
||||
{
|
||||
var sma = new Sma(10);
|
||||
double[] history = [10, 20, 30, 40, 50];
|
||||
|
||||
sma.Prime(history);
|
||||
|
||||
Assert.False(sma.IsHot);
|
||||
Assert.Equal(30.0, sma.Last.Value, 1e-10); // It still calculates what it can
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Prime_HandlesNaN_InHistory()
|
||||
{
|
||||
var sma = new Sma(3);
|
||||
double[] history = [10, 20, double.NaN, 40];
|
||||
// 10
|
||||
// 10, 20
|
||||
// 10, 20, 20 (NaN replaced by 20) -> Avg(10,20,20) = 16.666...
|
||||
// 20, 20, 40 -> Avg(20,20,40) = 26.666...
|
||||
|
||||
sma.Prime(history);
|
||||
|
||||
Assert.True(sma.IsHot);
|
||||
Assert.Equal(80.0 / 3.0, sma.Last.Value, 1e-9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Calculate_ReturnsCorrectResultsAndHotIndicator()
|
||||
{
|
||||
var series = new TSeries();
|
||||
for (int i = 1; i <= 10; i++)
|
||||
{
|
||||
series.Add(DateTime.UtcNow, i * 10);
|
||||
}
|
||||
// 10, 20, 30, 40, 50, 60, 70, 80, 90, 100
|
||||
|
||||
// SMA(5)
|
||||
var (results, indicator) = Sma.Calculate(series, 5);
|
||||
|
||||
// Check results
|
||||
Assert.Equal(10, results.Count);
|
||||
Assert.Equal(30.0, results[4].Value); // 5th element (index 4) is SMA(10..50) = 30
|
||||
Assert.Equal(80.0, results.Last.Value); // Last element is SMA(60..100) = 80
|
||||
|
||||
// Check indicator state
|
||||
Assert.True(indicator.IsHot);
|
||||
Assert.Equal(80.0, indicator.Last.Value);
|
||||
Assert.Equal(5, indicator.WarmupPeriod);
|
||||
|
||||
// Verify indicator continues correctly
|
||||
indicator.Update(new TValue(DateTime.UtcNow, 110));
|
||||
// Window was [60, 70, 80, 90, 100] -> Avg 80
|
||||
// New Window [70, 80, 90, 100, 110] -> Avg 90
|
||||
Assert.Equal(90.0, indicator.Last.Value);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,32 @@
|
||||
using Skender.Stock.Indicators;
|
||||
|
||||
namespace QuanTAlib.Tests;
|
||||
|
||||
public sealed class SmaToleranceTests : IDisposable
|
||||
{
|
||||
private readonly ValidationTestData _testData;
|
||||
|
||||
public SmaToleranceTests()
|
||||
{
|
||||
_testData = new ValidationTestData();
|
||||
}
|
||||
|
||||
public void Dispose()
|
||||
{
|
||||
_testData.Dispose();
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Check_Skender_Tolerance()
|
||||
{
|
||||
const int period = 20;
|
||||
var sma = new Sma(period);
|
||||
var qResult = sma.Update(_testData.Data);
|
||||
var sResult = _testData.SkenderQuotes.GetSma(period).ToList();
|
||||
|
||||
ValidationHelper.VerifyData(qResult, sResult, (s) => s.Sma);
|
||||
|
||||
// Add explicit assertion to satisfy SonarQube
|
||||
Assert.True(qResult.Count > 0);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,319 @@
|
||||
using OoplesFinance.StockIndicators;
|
||||
using OoplesFinance.StockIndicators.Models;
|
||||
using Skender.Stock.Indicators;
|
||||
using TALib;
|
||||
using Xunit.Abstractions;
|
||||
|
||||
namespace QuanTAlib.Tests;
|
||||
|
||||
public sealed class SmaValidationTests : IDisposable
|
||||
{
|
||||
private readonly ValidationTestData _testData;
|
||||
private readonly ITestOutputHelper _output;
|
||||
private bool _disposed;
|
||||
|
||||
public SmaValidationTests(ITestOutputHelper output)
|
||||
{
|
||||
_output = output;
|
||||
_testData = new ValidationTestData();
|
||||
}
|
||||
|
||||
public void Dispose()
|
||||
{
|
||||
Dispose(true);
|
||||
}
|
||||
|
||||
private void Dispose(bool disposing)
|
||||
{
|
||||
if (_disposed)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
_disposed = true;
|
||||
|
||||
if (disposing)
|
||||
{
|
||||
_testData?.Dispose();
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Skender_Batch()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (batch TSeries)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResult = sma.Update(_testData.Data);
|
||||
|
||||
// Calculate Skender SMA
|
||||
var sResult = _testData.SkenderQuotes.GetSma(period).ToList();
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResult, sResult, (s) => s.Sma);
|
||||
}
|
||||
_output.WriteLine("SMA Batch(TSeries) validated successfully against Skender");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Skender_Streaming()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (streaming)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResults = new List<double>();
|
||||
foreach (var item in _testData.Data)
|
||||
{
|
||||
qResults.Add(sma.Update(item).Value);
|
||||
}
|
||||
|
||||
// Calculate Skender SMA
|
||||
var sResult = _testData.SkenderQuotes.GetSma(period).ToList();
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResults, sResult, (s) => s.Sma);
|
||||
}
|
||||
_output.WriteLine("SMA Streaming validated successfully against Skender");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Skender_Span()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for Span API
|
||||
double[] sourceData = _testData.RawData.ToArray();
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (Span API)
|
||||
double[] qOutput = new double[sourceData.Length];
|
||||
global::QuanTAlib.Sma.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
|
||||
|
||||
// Calculate Skender SMA
|
||||
var sResult = _testData.SkenderQuotes.GetSma(period).ToList();
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qOutput, sResult, (s) => s.Sma);
|
||||
}
|
||||
_output.WriteLine("SMA Span validated successfully against Skender");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Talib_Batch()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for TA-Lib (double[])
|
||||
double[] tData = _testData.RawData.ToArray();
|
||||
double[] output = new double[tData.Length];
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (batch TSeries)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResult = sma.Update(_testData.Data);
|
||||
|
||||
// Calculate TA-Lib SMA
|
||||
var retCode = TALib.Functions.Sma<double>(tData, 0..^0, output, out var outRange, period);
|
||||
Assert.Equal(TALib.Core.RetCode.Success, retCode);
|
||||
|
||||
int lookback = TALib.Functions.SmaLookback(period);
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResult, output, outRange, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Batch(TSeries) validated successfully against TA-Lib");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Talib_Streaming()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for TA-Lib (double[])
|
||||
double[] tData = _testData.RawData.ToArray();
|
||||
double[] output = new double[tData.Length];
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (streaming)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResults = new List<double>();
|
||||
foreach (var item in _testData.Data)
|
||||
{
|
||||
qResults.Add(sma.Update(item).Value);
|
||||
}
|
||||
|
||||
// Calculate TA-Lib SMA
|
||||
var retCode = TALib.Functions.Sma<double>(tData, 0..^0, output, out var outRange, period);
|
||||
Assert.Equal(TALib.Core.RetCode.Success, retCode);
|
||||
|
||||
int lookback = TALib.Functions.SmaLookback(period);
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResults, output, outRange, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Streaming validated successfully against TA-Lib");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Talib_Span()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data
|
||||
double[] sourceData = _testData.RawData.ToArray();
|
||||
double[] talibOutput = new double[sourceData.Length];
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (Span API)
|
||||
double[] qOutput = new double[sourceData.Length];
|
||||
global::QuanTAlib.Sma.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
|
||||
|
||||
// Calculate TA-Lib SMA
|
||||
var retCode = TALib.Functions.Sma<double>(sourceData, 0..^0, talibOutput, out var outRange, period);
|
||||
Assert.Equal(TALib.Core.RetCode.Success, retCode);
|
||||
|
||||
int lookback = TALib.Functions.SmaLookback(period);
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qOutput, talibOutput, outRange, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Span validated successfully against TA-Lib");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Tulip_Batch()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for Tulip (double[])
|
||||
double[] tData = _testData.RawData.ToArray();
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (batch TSeries)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResult = sma.Update(_testData.Data);
|
||||
|
||||
// Calculate Tulip SMA
|
||||
var smaIndicator = Tulip.Indicators.sma;
|
||||
double[][] inputs = { tData };
|
||||
double[] options = { period };
|
||||
int lookback = period - 1;
|
||||
double[][] outputs = { new double[tData.Length - lookback] };
|
||||
|
||||
smaIndicator.Run(inputs, options, outputs);
|
||||
var tResult = outputs[0];
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResult, tResult, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Batch(TSeries) validated successfully against Tulip");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Tulip_Streaming()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for Tulip (double[])
|
||||
double[] tData = _testData.RawData.ToArray();
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (streaming)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResults = new List<double>();
|
||||
foreach (var item in _testData.Data)
|
||||
{
|
||||
qResults.Add(sma.Update(item).Value);
|
||||
}
|
||||
|
||||
// Calculate Tulip SMA
|
||||
var smaIndicator = Tulip.Indicators.sma;
|
||||
double[][] inputs = { tData };
|
||||
double[] options = { period };
|
||||
int lookback = period - 1;
|
||||
double[][] outputs = { new double[tData.Length - lookback] };
|
||||
|
||||
smaIndicator.Run(inputs, options, outputs);
|
||||
var tResult = outputs[0];
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResults, tResult, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Streaming validated successfully against Tulip");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Tulip_Span()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data
|
||||
double[] sourceData = _testData.RawData.ToArray();
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (Span API)
|
||||
double[] qOutput = new double[sourceData.Length];
|
||||
global::QuanTAlib.Sma.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
|
||||
|
||||
// Calculate Tulip SMA
|
||||
var smaIndicator = Tulip.Indicators.sma;
|
||||
double[][] inputs = { sourceData };
|
||||
double[] options = { period };
|
||||
int lookback = period - 1;
|
||||
double[][] outputs = { new double[sourceData.Length - lookback] };
|
||||
|
||||
smaIndicator.Run(inputs, options, outputs);
|
||||
var tResult = outputs[0];
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qOutput, tResult, lookback);
|
||||
}
|
||||
_output.WriteLine("SMA Span validated successfully against Tulip");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Ooples_Batch()
|
||||
{
|
||||
int[] periods = { 5, 10, 20, 50, 100 };
|
||||
|
||||
// Prepare data for Ooples (List<TickerData>)
|
||||
// Ooples requires TickerData which has Close, High, Low, Open, Volume, Date
|
||||
var ooplesData = _testData.SkenderQuotes.Select(q => new TickerData
|
||||
{
|
||||
Date = q.Date,
|
||||
Close = (double)q.Close,
|
||||
High = (double)q.High,
|
||||
Low = (double)q.Low,
|
||||
Open = (double)q.Open,
|
||||
Volume = (double)q.Volume
|
||||
}).ToList();
|
||||
|
||||
foreach (var period in periods)
|
||||
{
|
||||
// Calculate QuanTAlib SMA (batch TSeries)
|
||||
var sma = new global::QuanTAlib.Sma(period);
|
||||
var qResult = sma.Update(_testData.Data);
|
||||
|
||||
// Calculate Ooples SMA
|
||||
var stockData = new StockData(ooplesData);
|
||||
var sResult = stockData.CalculateSimpleMovingAverage(period).OutputValues.Values.First();
|
||||
|
||||
// Compare last 100 records
|
||||
ValidationHelper.VerifyData(qResult, sResult, (s) => s, 100, ValidationHelper.OoplesTolerance);
|
||||
}
|
||||
_output.WriteLine("SMA Batch(TSeries) validated successfully against Ooples");
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,33 @@
|
||||
|
||||
namespace QuanTAlib.Tests;
|
||||
|
||||
public class SmaZeroDivTests
|
||||
{
|
||||
[Fact]
|
||||
public void Sma_Update_WithIsNewFalse_OnEmptyBuffer_DoesNotThrow()
|
||||
{
|
||||
var sma = new Sma(10);
|
||||
|
||||
// Buffer is empty initially.
|
||||
// Calling Update with isNew=false should not cause division by zero.
|
||||
// It should return NaN or 0 or Last, but definitely not throw or return Infinity.
|
||||
|
||||
var result = sma.Update(new TValue(DateTime.UtcNow, 100), isNew: false);
|
||||
|
||||
// Since buffer count is 0, we expect NaN based on our fix.
|
||||
Assert.True(double.IsNaN(result.Value), $"Expected NaN but got {result.Value}");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Sma_Update_WithIsNewFalse_AfterReset_DoesNotThrow()
|
||||
{
|
||||
var sma = new Sma(10);
|
||||
sma.Update(new TValue(DateTime.UtcNow, 100));
|
||||
sma.Reset();
|
||||
|
||||
// Buffer is empty after Reset.
|
||||
var result = sma.Update(new TValue(DateTime.UtcNow, 200), isNew: false);
|
||||
|
||||
Assert.True(double.IsNaN(result.Value), $"Expected NaN but got {result.Value}");
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user