mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-23 13:08:04 +00:00
fix: resolve build and test errors
- Sar.Quantower.Tests.cs: add missing opening quote on string literal (line 48) - Exports.cs: rename Correlation.Batch → Correl.Batch (CS0103) - Ad.Validation.Tests.cs: fix Ooples OutputValues key "Ad" → "Adl"
This commit is contained in:
Miha Kralj
@@ -0,0 +1,89 @@
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using TradingPlatform.BusinessLayer;
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using QuanTAlib;
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namespace QuanTAlib.Tests;
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public class AdIndicatorTests
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{
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[Fact]
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public void AdIndicator_Constructor_SetsDefaults()
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{
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var indicator = new AdIndicator();
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Assert.Equal("AD - Accumulation/Distribution Line", indicator.Name);
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Assert.True(indicator.SeparateWindow);
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Assert.True(indicator.OnBackGround);
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Assert.Equal(0, AdIndicator.MinHistoryDepths);
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}
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[Fact]
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public void AdIndicator_ShortName_IsCorrect()
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{
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var indicator = new AdIndicator();
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Assert.Equal("AD", indicator.ShortName);
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}
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[Fact]
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public void AdIndicator_MinHistoryDepths_EqualsZero()
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{
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var indicator = new AdIndicator();
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Assert.Equal(0, AdIndicator.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 AdIndicator_Initialize_CreatesInternalAd()
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{
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var indicator = new AdIndicator();
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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 AdIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
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{
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var indicator = new AdIndicator();
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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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for (int i = 0; i < 20; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 100 + i, 110 + i, 90 + i, 105 + i, 1000);
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// Process update for each bar to simulate history loading
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var args = new UpdateArgs(UpdateReason.HistoricalBar);
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indicator.ProcessUpdate(args);
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}
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// Line series should have a value
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double val = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(val));
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}
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[Fact]
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public void AdIndicator_ProcessUpdate_NewBar_ComputesValue()
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{
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var indicator = new AdIndicator();
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indicator.Initialize();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 20; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 100 + i, 110 + i, 90 + i, 105 + i, 1000);
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}
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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// Add new bar
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indicator.HistoricalData.AddBar(now.AddMinutes(20), 120, 130, 110, 125, 1500);
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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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}
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@@ -0,0 +1,209 @@
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namespace QuanTAlib.Tests;
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public class AdTests
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{
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[Fact]
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public void Ad_BasicCalculation_ReturnsExpectedValues()
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{
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// Arrange
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var ad = new Ad();
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var time = DateTime.UtcNow;
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// Bar 1: Close=10, High=12, Low=8. Range=4.
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// MFM = ((10-8) - (12-10)) / 4 = (2 - 2) / 4 = 0.
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// Vol = 100. MFV = 0. AD = 0.
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var bar1 = new TBar(time, 10, 12, 8, 10, 100);
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var val1 = ad.Update(bar1);
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Assert.Equal(0, val1.Value);
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// Bar 2: Close=12, High=12, Low=8. Range=4.
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// MFM = ((12-8) - (12-12)) / 4 = (4 - 0) / 4 = 1.
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// Vol = 200. MFV = 200. AD = 0 + 200 = 200.
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var bar2 = new TBar(time.AddMinutes(1), 10, 12, 8, 12, 200);
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var val2 = ad.Update(bar2);
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Assert.Equal(200, val2.Value);
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// Bar 3: Close=8, High=12, Low=8. Range=4.
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// MFM = ((8-8) - (12-8)) / 4 = (0 - 4) / 4 = -1.
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// Vol = 100. MFV = -100. AD = 200 - 100 = 100.
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var bar3 = new TBar(time.AddMinutes(2), 12, 12, 8, 8, 100);
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var val3 = ad.Update(bar3);
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Assert.Equal(100, val3.Value);
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}
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[Fact]
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public void Ad_IsNew_False_UpdatesSameBar()
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{
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var ad = new Ad();
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var time = DateTime.UtcNow;
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// Initial update
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// MFM = 1, Vol = 100 -> AD = 100
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var bar1 = new TBar(time, 10, 12, 8, 12, 100);
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ad.Update(bar1, isNew: true);
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Assert.Equal(100, ad.Last.Value);
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// Update same bar with different volume
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// MFM = 1, Vol = 200 -> AD = 200 (replaces previous 100)
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var bar1Update = new TBar(time, 10, 12, 8, 12, 200);
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ad.Update(bar1Update, isNew: false);
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Assert.Equal(200, ad.Last.Value);
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}
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[Fact]
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public void Ad_Reset_ClearsState()
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{
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var ad = new Ad();
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var bar = new TBar(DateTime.UtcNow, 10, 12, 8, 12, 100);
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ad.Update(bar);
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Assert.True(ad.IsHot);
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Assert.NotEqual(0, ad.Last.Value);
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ad.Reset();
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Assert.False(ad.IsHot);
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Assert.Equal(0, ad.Last.Value);
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}
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[Fact]
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public void Ad_HighEqualsLow_HandlesDivisionByZero()
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{
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var ad = new Ad();
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// High = Low = 10. Range = 0. MFM should be 0.
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var bar = new TBar(DateTime.UtcNow, 10, 10, 10, 10, 100);
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var val = ad.Update(bar);
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Assert.Equal(0, val.Value);
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}
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[Fact]
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public void Ad_TValueUpdate_ThrowsNotSupportedException()
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{
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var ad = new Ad();
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var bar = new TBar(DateTime.UtcNow, 10, 12, 8, 12, 100);
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ad.Update(bar); // AD = 100
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// Update with TValue should throw since AD requires OHLCV bar data
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Assert.Throws<NotSupportedException>(() => ad.Update(new TValue(DateTime.UtcNow, 15)));
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}
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[Fact]
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public void Ad_Name_IsCorrect()
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{
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Assert.Equal("AD", Ad.Name);
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}
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[Fact]
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public void Ad_PubEvent_FiresOnUpdate()
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{
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var ad = new Ad();
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bool eventFired = false;
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ad.Pub += (object? sender, in TValueEventArgs args) => eventFired = true;
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ad.Update(new TBar(DateTime.UtcNow, 10, 12, 8, 10, 100));
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Assert.True(eventFired);
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}
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[Fact]
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public void Ad_UpdateTBarSeries_ReturnsCorrectSeries()
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{
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var ad = new Ad();
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var bars = new TBarSeries();
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var time = DateTime.UtcNow;
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// Add same bars as in BasicCalculation
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bars.Add(new TBar(time, 10, 12, 8, 10, 100)); // AD=0
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bars.Add(new TBar(time.AddMinutes(1), 10, 12, 8, 12, 200)); // AD=200
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bars.Add(new TBar(time.AddMinutes(2), 12, 12, 8, 8, 100)); // AD=100
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var result = ad.Update(bars);
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Assert.Equal(3, result.Count);
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Assert.Equal(0, result[0].Value);
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Assert.Equal(200, result[1].Value);
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Assert.Equal(100, result[2].Value);
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}
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[Fact]
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public void Ad_CalculateTBarSeries_ReturnsCorrectSeries()
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{
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var bars = new TBarSeries();
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var time = DateTime.UtcNow;
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bars.Add(new TBar(time, 10, 12, 8, 10, 100));
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bars.Add(new TBar(time.AddMinutes(1), 10, 12, 8, 12, 200));
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bars.Add(new TBar(time.AddMinutes(2), 12, 12, 8, 8, 100));
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var result = Ad.Batch(bars);
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Assert.Equal(3, result.Count);
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Assert.Equal(0, result[0].Value);
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Assert.Equal(200, result[1].Value);
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Assert.Equal(100, result[2].Value);
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}
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[Fact]
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public void Ad_CalculateSpan_ReturnsCorrectValues()
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{
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double[] high = { 12, 12, 12 };
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double[] low = { 8, 8, 8 };
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double[] close = { 10, 12, 8 };
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double[] volume = { 100, 200, 100 };
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double[] output = new double[3];
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Ad.Batch(high, low, close, volume, output);
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Assert.Equal(0, output[0]);
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Assert.Equal(200, output[1]);
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Assert.Equal(100, output[2]);
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}
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[Fact]
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public void Ad_CalculateSpan_ThrowsOnMismatchedLengths()
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{
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double[] high = { 10, 11 };
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double[] low = { 9, 10 };
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double[] close = { 9.5, 10.5 };
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double[] volume = { 100 }; // Short
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double[] output = new double[2];
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Assert.Throws<ArgumentException>(() =>
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Ad.Batch(high, low, close, volume, output));
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}
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[Fact]
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public void Ad_Calculate_EmptySeries_ReturnsEmpty()
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{
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var bars = new TBarSeries();
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var result = Ad.Batch(bars);
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Assert.Empty(result);
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}
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[Fact]
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public void Ad_CalculateSpan_SimdPath_ReturnsCorrectValues()
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{
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const int count = 100; // Enough to trigger SIMD
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double[] high = new double[count];
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double[] low = new double[count];
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double[] close = new double[count];
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double[] volume = new double[count];
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double[] output = new double[count];
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// Setup: High=12, Low=8, Close=12 (MFM=1), Vol=10
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// Expected AD increments by 10 each step.
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for (int i = 0; i < count; i++)
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{
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high[i] = 12;
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low[i] = 8;
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close[i] = 12;
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volume[i] = 10;
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}
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Ad.Batch(high, low, close, volume, output);
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for (int i = 0; i < count; i++)
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{
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Assert.Equal((i + 1) * 10, output[i]);
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}
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}
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}
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@@ -0,0 +1,114 @@
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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.Tests;
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public class AdValidationTests
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{
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private readonly ValidationTestData _data;
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public AdValidationTests()
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{
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_data = new ValidationTestData();
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}
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[Fact]
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public void Ad_Matches_Skender()
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{
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// Skender
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var skenderResults = _data.SkenderQuotes.GetAdl();
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var skenderValues = skenderResults.Select(x => x.Adl).ToArray();
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// QuanTAlib
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var ad = new Ad();
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var quantalibValues = new List<double>();
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foreach (var bar in _data.Bars)
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{
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quantalibValues.Add(ad.Update(bar).Value);
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}
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ValidationHelper.VerifyData(quantalibValues.ToArray(), skenderValues, 0, 100, ValidationHelper.SkenderTolerance);
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}
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[Fact]
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public void Ad_Matches_Talib()
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{
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// TA-Lib
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var high = _data.Bars.High.Values.ToArray();
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var low = _data.Bars.Low.Values.ToArray();
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var close = _data.Bars.Close.Values.ToArray();
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var volume = _data.Bars.Volume.Values.ToArray();
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var talibValues = new double[high.Length];
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var retCode = TALib.Functions.Ad(high, low, close, volume, 0..^0, talibValues, out var outRange);
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Assert.Equal(TALib.Core.RetCode.Success, retCode);
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// QuanTAlib
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var ad = new Ad();
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var quantalibValues = new List<double>();
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foreach (var bar in _data.Bars)
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{
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quantalibValues.Add(ad.Update(bar).Value);
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}
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ValidationHelper.VerifyData(quantalibValues.ToArray(), talibValues, outRange, 0, 100, ValidationHelper.TalibTolerance);
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}
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[Fact]
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public void Ad_Matches_Tulip()
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{
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// Tulip
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var high = _data.Bars.High.Values.ToArray();
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var low = _data.Bars.Low.Values.ToArray();
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var close = _data.Bars.Close.Values.ToArray();
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var volume = _data.Bars.Volume.Values.ToArray();
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var tulipIndicator = Tulip.Indicators.ad;
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double[][] inputs = { high, low, close, volume };
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double[] options = Array.Empty<double>();
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double[][] outputs = { new double[high.Length] };
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tulipIndicator.Run(inputs, options, outputs);
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var tulipValues = outputs[0];
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// QuanTAlib
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var ad = new Ad();
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var quantalibValues = new List<double>();
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foreach (var bar in _data.Bars)
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{
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quantalibValues.Add(ad.Update(bar).Value);
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}
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ValidationHelper.VerifyData(quantalibValues.ToArray(), tulipValues, 0, 100, ValidationHelper.TulipTolerance);
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}
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[Fact]
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public void Ad_Matches_Ooples()
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{
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// Ooples
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var ooplesData = _data.SkenderQuotes.Select(q => new TickerData
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{
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Date = q.Date,
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Open = (double)q.Open,
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High = (double)q.High,
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Low = (double)q.Low,
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Close = (double)q.Close,
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Volume = (double)q.Volume
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}).ToList();
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var stockData = new StockData(ooplesData);
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var oResult = stockData.CalculateAccumulationDistributionLine();
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var oValues = oResult.OutputValues["Adl"];
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// QuanTAlib
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var ad = new Ad();
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var quantalibValues = new List<double>();
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foreach (var bar in _data.Bars)
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{
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quantalibValues.Add(ad.Update(bar).Value);
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}
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ValidationHelper.VerifyData(quantalibValues.ToArray(), oValues.ToArray(), 0, 100, ValidationHelper.OoplesTolerance);
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}
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}
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