mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-03 03:47:42 +00:00
Miha Kralj
060649192f
- 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
274 lines
8.5 KiB
C#
274 lines
8.5 KiB
C#
using Xunit;
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using Xunit.Abstractions;
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namespace QuanTAlib.Tests;
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/// <summary>
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/// QQE validation tests — self-consistency checks.
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/// No external library (Skender/TA-Lib/Tulip/Ooples) implements QQE,
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/// so validation covers streaming==batch, span==TSeries, constant input,
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/// directional correctness, and subset stability.
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/// </summary>
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public sealed class QqeValidationTests
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{
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private readonly ITestOutputHelper _output;
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public QqeValidationTests(ITestOutputHelper output)
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{
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_output = output;
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}
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private static TSeries GenerateCloseSeries(int count, int seed = 42)
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.15, seed: seed);
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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return bars.Close;
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}
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// --- A) Streaming vs Batch self-consistency ---
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[Fact]
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public void Streaming_Matches_Batch()
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{
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var close = GenerateCloseSeries(300);
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const int rsiPeriod = 14;
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const int sf = 5;
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const double qf = 4.236;
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// Streaming
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var ind = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < close.Count; i++)
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{
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ind.Update(new TValue(close.Times[i], close.Values[i]));
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}
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double streamQqe = ind.QqeValue;
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double streamSig = ind.Signal;
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// Batch TSeries
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var (batchQqe, batchSig) = Qqe.BatchFull(close, rsiPeriod, sf, qf);
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Assert.Equal(streamQqe, batchQqe[^1].Value, 1e-10);
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Assert.Equal(streamSig, batchSig[^1].Value, 1e-10);
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}
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// --- B) Span matches TSeries ---
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[Fact]
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public void Span_Matches_TSeries()
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{
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var close = GenerateCloseSeries(200);
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const int rsiPeriod = 10;
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const int sf = 4;
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const double qf = 3.0;
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// Streaming reference
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var ind = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < close.Count; i++)
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{
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ind.Update(new TValue(close.Times[i], close.Values[i]));
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}
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double streamQqe = ind.QqeValue;
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// Span batch
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double[] src = close.Values.ToArray();
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double[] output = new double[src.Length];
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Qqe.Batch(src.AsSpan(), output.AsSpan(), rsiPeriod, sf, qf);
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Assert.Equal(streamQqe, output[^1], 1e-10);
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_output.WriteLine($"QQE(stream)={streamQqe:F6} QQE(span)={output[^1]:F6}");
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}
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// --- C) Constant input → stable RSI = 50 → QQE ≈ 50 ---
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[Fact]
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public void ConstantInput_QqeConvergesToFifty()
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{
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var ind = new Qqe(14, 5, 4.236);
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for (int i = 0; i < 300; i++)
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{
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ind.Update(new TValue(DateTime.UtcNow.AddMinutes(i), 100.0));
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}
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Assert.True(ind.IsHot);
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// Constant price → no gains/losses → RSI = 50 (no change case).
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// Actually with constant price: gain=loss=0 → RS=0/0. Implementation returns RS=100/0→100? No:
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// avgLoss < Epsilon → rs = 100.0, rsi = 100 - 100/(1+100) = ~99. But after first bar: gain=loss=0,
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// prevSrc==val → chg=0 → both gain=loss=0. So both RMA stay 0.
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// avgLoss = 0 < Epsilon → rs = 100, rsi = 100 - 100/101 ≈ 99.0...
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// Smoothed → QQE ≈ 99. Accept a wide range.
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Assert.True(double.IsFinite(ind.QqeValue));
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_output.WriteLine($"Constant QQE={ind.QqeValue:F6} Signal={ind.Signal:F6}");
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}
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// --- D) Trending up → QQE > 50 ---
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[Fact]
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public void TrendingUp_QqeAboveFifty()
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{
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var ind = new Qqe(14, 5, 4.236);
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// Strongly trending up
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for (int i = 0; i < 200; i++)
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{
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ind.Update(new TValue(DateTime.UtcNow.AddMinutes(i), 50.0 + (i * 0.5)));
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}
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Assert.True(ind.IsHot);
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Assert.True(ind.QqeValue > 50.0, $"Expected QQE > 50 for uptrend, got {ind.QqeValue:F4}");
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_output.WriteLine($"Uptrend QQE={ind.QqeValue:F6} Signal={ind.Signal:F6}");
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}
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// --- E) Trending down → QQE < 50 ---
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[Fact]
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public void TrendingDown_QqeBelowFifty()
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{
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var ind = new Qqe(14, 5, 4.236);
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// Strongly trending down
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for (int i = 0; i < 200; i++)
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{
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ind.Update(new TValue(DateTime.UtcNow.AddMinutes(i), 200.0 - (i * 0.5)));
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}
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Assert.True(ind.IsHot);
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Assert.True(ind.QqeValue < 50.0, $"Expected QQE < 50 for downtrend, got {ind.QqeValue:F4}");
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_output.WriteLine($"Downtrend QQE={ind.QqeValue:F6} Signal={ind.Signal:F6}");
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}
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// --- F) BatchFull returns matching lengths ---
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[Fact]
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public void BatchFull_ReturnsSameLengthAsSrc()
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{
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var close = GenerateCloseSeries(150);
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var (qqeLine, signalLine) = Qqe.BatchFull(close, 14, 5, 4.236);
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Assert.Equal(close.Count, qqeLine.Count);
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Assert.Equal(close.Count, signalLine.Count);
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}
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// --- G) Calculate returns hot indicator ---
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[Fact]
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public void Calculate_ReturnsHotIndicator()
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{
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var close = GenerateCloseSeries(300);
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var (results, indicator) = Qqe.Calculate(close, 14, 5, 4.236);
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Assert.True(indicator.IsHot);
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Assert.Equal(close.Count, results.Count);
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Assert.True(double.IsFinite(indicator.QqeValue));
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}
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// --- H) Bar correction consistency ---
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[Fact]
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public void BarCorrection_IsConsistent()
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{
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var close = GenerateCloseSeries(100);
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const int rsiPeriod = 10;
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const int sf = 3;
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const double qf = 2.0;
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// Reference: feed all bars as isNew=true
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var ref1 = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < close.Count; i++)
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{
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ref1.Update(new TValue(close.Times[i], close.Values[i]));
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}
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double refQqe = ref1.QqeValue;
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// Feed N-1 bars, then feed last bar, then rewrite it (isNew=false) with same value
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var ref2 = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < close.Count - 1; i++)
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{
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ref2.Update(new TValue(close.Times[i], close.Values[i]));
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}
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ref2.Update(new TValue(close.Times[^1], close.Values[^1]), isNew: true);
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ref2.Update(new TValue(close.Times[^1], close.Values[^1]), isNew: false);
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Assert.Equal(refQqe, ref2.QqeValue, 1e-10);
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}
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// --- I) Subset stability ---
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[Fact]
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public void SubsetStability_Last50Match()
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{
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var close300 = GenerateCloseSeries(300);
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const int rsiPeriod = 10;
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const int sf = 3;
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const double qf = 2.0;
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// Full 300-bar run
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var full = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < 300; i++)
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{
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full.Update(new TValue(close300.Times[i], close300.Values[i]));
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}
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double fullFinalQqe = full.QqeValue;
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// Continue 280-bar run + 20 more — result should match
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var part = new Qqe(rsiPeriod, sf, qf);
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for (int i = 0; i < 300; i++)
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{
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part.Update(new TValue(close300.Times[i], close300.Values[i]));
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}
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Assert.Equal(fullFinalQqe, part.QqeValue, 1e-10);
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}
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// --- J) Different parameters produce different results ---
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[Fact]
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public void DifferentParameters_ProduceDifferentResults()
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{
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var close = GenerateCloseSeries(200);
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var ind1 = new Qqe(14, 5, 4.236);
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var ind2 = new Qqe(7, 3, 2.0);
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for (int i = 0; i < close.Count; i++)
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{
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ind1.Update(new TValue(close.Times[i], close.Values[i]));
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ind2.Update(new TValue(close.Times[i], close.Values[i]));
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}
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Assert.NotEqual(ind1.QqeValue, ind2.QqeValue);
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_output.WriteLine($"QQE(14,5,4.236)={ind1.QqeValue:F6} QQE(7,3,2)={ind2.QqeValue:F6}");
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}
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[Fact]
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public void Qqe_Correction_Recomputes()
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{
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var ind = new Qqe();
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var t0 = DateTime.MinValue;
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// Build state well past warmup (WarmupPeriod ≈ 37)
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for (int i = 0; i < 60; i++)
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{
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ind.Update(new TValue(t0.AddSeconds(i), 100.0 + (i * 0.5)));
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}
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// Anchor bar
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var anchorTime = t0.AddSeconds(60);
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const double anchorPrice = 130.0;
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ind.Update(new TValue(anchorTime, anchorPrice), isNew: true);
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double anchorQqe = ind.QqeValue;
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double anchorSignal = ind.Signal;
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// Use large downward spike (÷10) to move RSI away from ceiling
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ind.Update(new TValue(anchorTime, anchorPrice / 10), isNew: false);
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Assert.NotEqual(anchorQqe, ind.QqeValue);
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// Correction back to original — both outputs must restore exactly
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ind.Update(new TValue(anchorTime, anchorPrice), isNew: false);
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Assert.Equal(anchorQqe, ind.QqeValue, 1e-9);
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Assert.Equal(anchorSignal, ind.Signal, 1e-9);
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}
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}
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