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https://github.com/mihakralj/QuanTAlib.git
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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 ConvIndicatorTests
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{
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[Fact]
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public void ConvIndicator_Constructor_SetsDefaults()
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{
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var indicator = new ConvIndicator();
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Assert.Equal("0.1, 0.2, 0.3, 0.4", indicator.WeightsInput);
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Assert.Equal(SourceType.Close, indicator.Source);
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Assert.True(indicator.ShowColdValues);
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Assert.Equal("CONV - Convolution", 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 ConvIndicator_MinHistoryDepths_EqualsWeightsLength()
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{
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var indicator = new ConvIndicator { WeightsInput = "1, 2, 3, 4, 5" };
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indicator.Initialize(); // Initialize to parse weights
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Assert.Equal(0, ConvIndicator.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 ConvIndicator_ShortName_IncludesSource()
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{
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var indicator = new ConvIndicator();
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Assert.Contains("CONV", indicator.ShortName, StringComparison.Ordinal);
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Assert.Contains("Close", indicator.ShortName, StringComparison.Ordinal);
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}
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[Fact]
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public void ConvIndicator_SourceCodeLink_IsValid()
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{
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var indicator = new ConvIndicator();
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Assert.Contains("github.com", indicator.SourceCodeLink, StringComparison.Ordinal);
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Assert.Contains("Conv.Quantower.cs", indicator.SourceCodeLink, StringComparison.Ordinal);
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}
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[Fact]
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public void ConvIndicator_Initialize_CreatesInternalConv()
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{
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var indicator = new ConvIndicator();
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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 ConvIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
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{
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var indicator = new ConvIndicator { WeightsInput = "0.5, 0.5" };
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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 ConvIndicator_ProcessUpdate_NewBar_ComputesValue()
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{
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var indicator = new ConvIndicator { WeightsInput = "0.5, 0.5" };
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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 ConvIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
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{
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var indicator = new ConvIndicator { WeightsInput = "0.5, 0.5" };
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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 ConvIndicator_MultipleUpdates_ProducesCorrectSequence()
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{
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// Weights [0.5, 1.0]
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var indicator = new ConvIndicator { WeightsInput = "0.5, 1.0" };
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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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}
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[Fact]
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public void ConvIndicator_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 ConvIndicator { WeightsInput = "0.5, 0.5", 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 ConvIndicator_InvalidWeights_FallsBackToDefault()
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{
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var indicator = new ConvIndicator { WeightsInput = "invalid" };
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// Should not throw, but fallback
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indicator.Initialize();
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Assert.Single(indicator.LinesSeries);
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}
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[Fact]
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public void ConvIndicator_DescriptionIsSet()
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{
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var indicator = new ConvIndicator();
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Assert.Contains("Convolution", indicator.Description, StringComparison.Ordinal);
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}
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}
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@@ -0,0 +1,231 @@
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namespace QuanTAlib;
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public class ConvTests
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{
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[Fact]
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public void Constructor_EmptyKernel_ThrowsArgumentException()
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{
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Assert.Throws<ArgumentException>(() => new Conv(Array.Empty<double>()));
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Assert.Throws<ArgumentException>(() => new Conv(null!));
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}
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[Fact]
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public void BasicCalculation_MatchesExpected()
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{
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// Kernel: [0.5, 1.0]
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// Data: [1, 2, 3, 4]
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// 1: 1*1.0 = 1.0 (partial)
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// 2: 1*0.5 + 2*1.0 = 2.5
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// 3: 2*0.5 + 3*1.0 = 4.0
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// 4: 3*0.5 + 4*1.0 = 5.5
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double[] kernel = [0.5, 1.0];
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var conv = new Conv(kernel);
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var result1 = conv.Update(new TValue(DateTime.UtcNow, 1));
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Assert.Equal(1.0, result1.Value);
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var result2 = conv.Update(new TValue(DateTime.UtcNow, 2));
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Assert.Equal(2.5, result2.Value);
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var result3 = conv.Update(new TValue(DateTime.UtcNow, 3));
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Assert.Equal(4.0, result3.Value);
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var result4 = conv.Update(new TValue(DateTime.UtcNow, 4));
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Assert.Equal(5.5, result4.Value);
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}
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[Fact]
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public void BarCorrection_UpdatesCorrectly()
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{
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double[] kernel = [0.5, 1.0];
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var conv = new Conv(kernel);
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// 1
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conv.Update(new TValue(DateTime.UtcNow, 1));
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// 2 (isNew=true) -> 2.5
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var res1 = conv.Update(new TValue(DateTime.UtcNow, 2), isNew: true);
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Assert.Equal(2.5, res1.Value);
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// Update 2 to 3 (isNew=false)
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// Buffer was [1, 2]. Now [1, 3].
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// 1*0.5 + 3*1.0 = 3.5
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var res2 = conv.Update(new TValue(DateTime.UtcNow, 3), isNew: false);
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Assert.Equal(3.5, res2.Value);
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// New bar 4 (isNew=true)
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// Buffer was [1, 3]. New bar 4. Buffer becomes [3, 4].
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// 3*0.5 + 4*1.0 = 1.5 + 4 = 5.5
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var res3 = conv.Update(new TValue(DateTime.UtcNow, 4), isNew: true);
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Assert.Equal(5.5, res3.Value);
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}
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[Fact]
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public void NanHandling_UsesLastValid()
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{
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double[] kernel = [1.0, 1.0]; // Sum of last 2
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var conv = new Conv(kernel);
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// 1 -> 1
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conv.Update(new TValue(DateTime.UtcNow, 1));
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// NaN -> treated as 1. Buffer: [1, 1]. Result: 2.
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var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.Equal(2.0, res.Value);
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// 2 -> Buffer: [1, 2]. Result: 3.
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res = conv.Update(new TValue(DateTime.UtcNow, 2));
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Assert.Equal(3.0, res.Value);
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}
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[Fact]
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public void StaticCalculate_MatchesObjectApi()
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{
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double[] kernel = [0.5, 1.0];
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var source = new TSeries();
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source.Add(new TValue(DateTime.UtcNow, 1));
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source.Add(new TValue(DateTime.UtcNow, 2));
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source.Add(new TValue(DateTime.UtcNow, 3));
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source.Add(new TValue(DateTime.UtcNow, 4));
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var result = Conv.Batch(source, kernel);
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Assert.Equal(1.0, result.Values[0]);
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Assert.Equal(2.5, result.Values[1]);
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Assert.Equal(4.0, result.Values[2]);
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Assert.Equal(5.5, result.Values[3]);
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}
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[Fact]
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public void Reset_ClearsState()
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{
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double[] kernel = [1.0, 1.0];
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var conv = new Conv(kernel);
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conv.Update(new TValue(DateTime.UtcNow, 1));
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conv.Update(new TValue(DateTime.UtcNow, 2));
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Assert.True(conv.IsHot);
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conv.Reset();
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Assert.False(conv.IsHot);
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Assert.Equal(0, conv.Last.Value);
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// Should behave as new
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var res = conv.Update(new TValue(DateTime.UtcNow, 1));
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Assert.Equal(1.0, res.Value);
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}
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[Fact]
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public void LeadingNaN_RemainsNaN()
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{
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double[] kernel = [1.0];
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var conv = new Conv(kernel);
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var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsNaN(res.Value));
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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double[] kernel = [0.5, 1.0];
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var conv = new Conv(kernel);
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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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conv.Update(tenthInput, isNew: true);
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}
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// Remember state after 10 values
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double valueAfterTen = conv.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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conv.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 finalValue = conv.Update(tenthInput, isNew: false);
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// Should match the original state after 10 values
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Assert.Equal(valueAfterTen, finalValue.Value, 1e-9);
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}
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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// Arrange
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double[] kernel = [0.1, 0.2, 0.3, 0.4];
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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// 1. Batch Mode
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var batchSeries = Conv.Batch(series, kernel);
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double expected = batchSeries.Last.Value;
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// 2. Span Mode
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var tValues = series.Values.ToArray();
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var spanInput = new ReadOnlySpan<double>(tValues);
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var spanOutput = new double[tValues.Length];
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Conv.Batch(spanInput, spanOutput, kernel);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamingInd = new Conv(kernel);
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for (int i = 0; i < series.Count; i++)
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{
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streamingInd.Update(series[i]);
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}
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double streamingResult = streamingInd.Last.Value;
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// 4. Eventing Mode
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var pubSource = new TSeries();
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var eventingInd = new Conv(pubSource, kernel);
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for (int i = 0; i < series.Count; i++)
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{
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pubSource.Add(series[i]);
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}
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double eventingResult = eventingInd.Last.Value;
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// Assert
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Assert.Equal(expected, spanResult, 1e-9);
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Assert.Equal(expected, streamingResult, 1e-9);
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Assert.Equal(expected, eventingResult, 1e-9);
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}
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[Fact]
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public void SpanCalc_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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double[] wrongSizeOutput = new double[3];
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double[] kernel = [0.5, 0.5];
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Assert.Throws<ArgumentException>(() => Conv.Batch(source.AsSpan(), output.AsSpan(), Array.Empty<double>()));
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Assert.Throws<ArgumentException>(() => Conv.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), kernel));
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}
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[Fact]
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public void SpanCalc_HandlesNaN()
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{
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double[] source = [100, 110, double.NaN, 120, 130];
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double[] output = new double[5];
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double[] kernel = [0.5, 0.5];
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Conv.Batch(source.AsSpan(), output.AsSpan(), kernel);
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foreach (var val in output)
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{
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Assert.True(double.IsFinite(val));
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}
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}
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}
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@@ -0,0 +1,210 @@
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using QuanTAlib.Tests;
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using Skender.Stock.Indicators;
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using OoplesFinance.StockIndicators;
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using OoplesFinance.StockIndicators.Models;
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namespace QuanTAlib;
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public sealed class ConvValidationTests : IDisposable
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{
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private readonly ValidationTestData _testData;
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private bool _disposed;
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public ConvValidationTests()
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{
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_testData = new ValidationTestData(count: 10000, seed: 123);
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}
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public void Dispose()
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{
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Dispose(true);
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}
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private void Dispose(bool disposing)
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{
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if (_disposed)
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{
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return;
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}
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_disposed = true;
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if (disposing)
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{
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_testData?.Dispose();
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}
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}
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private static double[] GenerateWmaKernel(int period)
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{
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double divisor = period * (period + 1) / 2.0;
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double[] kernel = new double[period];
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for (int i = 0; i < period; i++)
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{
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kernel[i] = (i + 1) / divisor;
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}
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return kernel;
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}
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[Fact]
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public void Validate_Against_Sma()
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{
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// SMA(10) is equivalent to Conv with 10 weights of 1/10
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const int period = 10;
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double weight = 1.0 / period;
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double[] kernel = new double[period];
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Array.Fill(kernel, weight);
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var sma = new Sma(period);
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var conv = new Conv(kernel);
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for (int i = 0; i < _testData.Data.Count; i++)
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{
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var item = _testData.Data[i];
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var smaVal = sma.Update(item);
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var convVal = conv.Update(item);
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if (i >= period) // Skip warmup
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{
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Assert.Equal(smaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
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}
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}
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}
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[Fact]
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public void Validate_Against_Wma()
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{
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int period = 10;
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double[] kernel = GenerateWmaKernel(period);
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var wma = new Wma(period);
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var conv = new Conv(kernel);
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|
||||
for (int i = 0; i < _testData.Data.Count; i++)
|
||||
{
|
||||
var item = _testData.Data[i];
|
||||
var wmaVal = wma.Update(item);
|
||||
var convVal = conv.Update(item);
|
||||
|
||||
if (i >= period) // Skip warmup
|
||||
{
|
||||
Assert.Equal(wmaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Against_Trima()
|
||||
{
|
||||
// TRIMA(10) - Even period
|
||||
// Weights: 1, 2, 3, 4, 5, 5, 4, 3, 2, 1
|
||||
// Sum: 30
|
||||
int period = 10;
|
||||
double[] kernel = new double[period];
|
||||
double sum = 0;
|
||||
|
||||
// Generate triangular weights
|
||||
int mid = period / 2;
|
||||
for (int i = 0; i < period; i++)
|
||||
{
|
||||
double val = (i < mid) ? (i + 1) : (period - i);
|
||||
kernel[i] = val;
|
||||
sum += val;
|
||||
}
|
||||
|
||||
// Normalize
|
||||
for (int i = 0; i < period; i++)
|
||||
{
|
||||
kernel[i] /= sum;
|
||||
}
|
||||
|
||||
var trima = new Trima(period);
|
||||
var conv = new Conv(kernel);
|
||||
|
||||
for (int i = 0; i < _testData.Data.Count; i++)
|
||||
{
|
||||
var item = _testData.Data[i];
|
||||
var trimaVal = trima.Update(item);
|
||||
var convVal = conv.Update(item);
|
||||
|
||||
if (i >= period) // Skip warmup
|
||||
{
|
||||
Assert.Equal(trimaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Against_Skender_Wma()
|
||||
{
|
||||
int period = 14;
|
||||
var skenderWma = _testData.SkenderQuotes.GetWma(period).ToList();
|
||||
double[] kernel = GenerateWmaKernel(period);
|
||||
var conv = new Conv(kernel);
|
||||
var result = conv.Update(_testData.Data);
|
||||
|
||||
ValidationHelper.VerifyData(result, skenderWma, (s) => s.Wma, skip: period);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Against_TALib_Wma()
|
||||
{
|
||||
int period = 14;
|
||||
double[] input = _testData.Data.Values.ToArray();
|
||||
double[] output = new double[input.Length];
|
||||
|
||||
var retCode = TALib.Functions.Wma<double>(input, 0..^0, output, out var outRange, period);
|
||||
Assert.Equal(TALib.Core.RetCode.Success, retCode);
|
||||
|
||||
double[] kernel = GenerateWmaKernel(period);
|
||||
var conv = new Conv(kernel);
|
||||
var result = conv.Update(_testData.Data);
|
||||
|
||||
ValidationHelper.VerifyData(result, output, outRange, lookback: period - 1);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Against_Tulip_Wma()
|
||||
{
|
||||
int period = 14;
|
||||
double[] input = _testData.Data.Values.ToArray();
|
||||
|
||||
var wmaIndicator = Tulip.Indicators.wma;
|
||||
double[][] inputs = { input };
|
||||
double[] options = { period };
|
||||
double[][] outputs = { new double[input.Length - period + 1] };
|
||||
|
||||
wmaIndicator.Run(inputs, options, outputs);
|
||||
double[] output = outputs[0];
|
||||
|
||||
double[] kernel = GenerateWmaKernel(period);
|
||||
var conv = new Conv(kernel);
|
||||
var result = conv.Update(_testData.Data);
|
||||
|
||||
ValidationHelper.VerifyData(result, output, lookback: period - 1);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Validate_Against_Ooples_Wma()
|
||||
{
|
||||
int period = 14;
|
||||
var ooplesData = _testData.SkenderQuotes.Select(q => new TickerData
|
||||
{
|
||||
Date = q.Date,
|
||||
Open = (double)q.Open,
|
||||
High = (double)q.High,
|
||||
Low = (double)q.Low,
|
||||
Close = (double)q.Close,
|
||||
Volume = (double)q.Volume
|
||||
}).ToList();
|
||||
|
||||
var stockData = new StockData(ooplesData);
|
||||
var ooplesWma = stockData.CalculateWeightedMovingAverage(length: period).OutputValues["Wma"];
|
||||
|
||||
double[] kernel = GenerateWmaKernel(period);
|
||||
var conv = new Conv(kernel);
|
||||
var result = conv.Update(_testData.Data);
|
||||
|
||||
ValidationHelper.VerifyData(result, ooplesWma, (s) => s, skip: period, tolerance: ValidationHelper.OoplesTolerance);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user