mirror of
https://github.com/mihakralj/QuanTAlib.git
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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
265 lines
9.7 KiB
C#
265 lines
9.7 KiB
C#
using Xunit;
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namespace QuanTAlib.Tests;
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/// <summary>
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/// FFT validation tests — verifies known spectral responses against analytical results.
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/// No external library implements this exact Ehlers-style windowed-DFT dominant cycle
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/// detector, so validation uses self-consistency and analytical known-answer tests.
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/// </summary>
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public class FftValidationTests
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{
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private const double Tolerance = 1e-10;
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private const double LooseTolerance = 3.0; // ±3 bars for period detection
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// ─── Self-consistency: batch vs streaming ─────────────────────────────────
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[Fact]
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public void Fft_BatchVsStreaming_AllValuesMatch()
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{
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int windowSize = 32;
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int count = 120;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 81001);
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var source = bars.Close;
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var streaming = new Fft(windowSize, maxPeriod: 16);
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var streamVals = new double[count];
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for (int i = 0; i < count; i++)
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{
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streaming.Update(source[i]);
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streamVals[i] = streaming.Last.Value;
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}
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var batch = Fft.Batch(source, windowSize, maxPeriod: 16);
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for (int i = 0; i < count; i++)
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{
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Assert.Equal(streamVals[i], batch[i].Value, Tolerance);
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}
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}
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// ─── Pure sine: dominant period detection ─────────────────────────────────
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[Fact]
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public void Fft_PureSine_Period16_Detected_N64()
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{
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// Sine at period 16, N=64, minP=4, maxP=32
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// Bin k=4 → period 64/4=16; should detect ≈ 16 ± 3
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int targetPeriod = 16;
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int windowSize = 64;
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var indicator = new Fft(windowSize, minPeriod: 4, maxPeriod: 32);
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var time = DateTime.UtcNow;
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for (int i = 0; i < windowSize * 3; i++)
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{
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double signal = 50.0 + (10.0 * Math.Sin(2.0 * Math.PI * i / targetPeriod));
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indicator.Update(new TValue(time.AddMinutes(i), signal), true);
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}
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Assert.True(indicator.IsHot);
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double detected = indicator.Last.Value;
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Assert.True(Math.Abs(detected - targetPeriod) <= LooseTolerance,
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$"Detected period {detected:F2} should be within {LooseTolerance} bars of {targetPeriod}");
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}
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[Fact]
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public void Fft_PureSine_Period8_Detected_N32()
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{
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// Sine at period 8, N=32, minP=4, maxP=16
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int targetPeriod = 8;
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int windowSize = 32;
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var indicator = new Fft(windowSize, minPeriod: 4, maxPeriod: 16);
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var time = DateTime.UtcNow;
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for (int i = 0; i < windowSize * 4; i++)
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{
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double signal = 50.0 + (10.0 * Math.Sin(2.0 * Math.PI * i / targetPeriod));
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indicator.Update(new TValue(time.AddMinutes(i), signal), true);
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}
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Assert.True(indicator.IsHot);
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double detected = indicator.Last.Value;
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Assert.True(Math.Abs(detected - targetPeriod) <= LooseTolerance,
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$"Detected period {detected:F2} should be within {LooseTolerance} bars of {targetPeriod}");
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}
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// ─── Constant input → clamped to maxPeriod ───────────────────────────────
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[Fact]
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public void Fft_ConstantInput_ClampedToMaxPeriod()
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{
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// Constant input has no spectral peak → should output maxPeriod (clamped)
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int windowSize = 32;
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int maxP = 16;
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var indicator = new Fft(windowSize, minPeriod: 4, maxPeriod: maxP);
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var time = DateTime.UtcNow;
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for (int i = 0; i < windowSize + 20; i++)
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{
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indicator.Update(new TValue(time.AddMinutes(i), 100.0));
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}
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Assert.True(indicator.IsHot);
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double detected = indicator.Last.Value;
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// Constant input → all bins equal zero → peak at minBin → period = N/minBin = maxPeriod
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Assert.InRange(detected, 4.0, (double)maxP);
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}
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// ─── Determinism ─────────────────────────────────────────────────────────
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[Fact]
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public void Fft_SameInput_SameOutput_Deterministic()
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{
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int windowSize = 32;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 81002);
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var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var ind1 = new Fft(windowSize, maxPeriod: 16);
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var ind2 = new Fft(windowSize, maxPeriod: 16);
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for (int i = 0; i < bars.Close.Count; i++)
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{
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ind1.Update(bars.Close[i]);
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ind2.Update(bars.Close[i]);
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}
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Assert.Equal(ind1.Last.Value, ind2.Last.Value, Tolerance);
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}
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// ─── Two independent instances → same result ─────────────────────────────
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[Fact]
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public void Fft_TwoInstances_SameParameters_Consistent()
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{
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int windowSize = 32;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 81003);
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int count = 60;
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var indA = new Fft(windowSize, minPeriod: 4, maxPeriod: 16);
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var indB = new Fft(windowSize, minPeriod: 4, maxPeriod: 16);
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for (int i = 0; i < count; i++)
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{
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indA.Update(bars.Close[i]);
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indB.Update(bars.Close[i]);
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if (indA.IsHot)
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{
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Assert.Equal(indA.Last.Value, indB.Last.Value, Tolerance);
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}
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}
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}
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// ─── Span API self-consistency ────────────────────────────────────────────
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[Fact]
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public void Fft_SpanBatch_MatchesStreamingAllBars()
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{
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int windowSize = 32;
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int count = 80;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 81004);
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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double[] src = new double[count];
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for (int i = 0; i < count; i++)
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{
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src[i] = bars.Close[i].Value;
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}
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double[] spanOut = new double[count];
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Fft.Batch(src, spanOut, windowSize, maxPeriod: 16);
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var streaming = new Fft(windowSize, maxPeriod: 16);
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for (int i = 0; i < count; i++)
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{
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streaming.Update(bars.Close[i]);
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Assert.Equal(streaming.Last.Value, spanOut[i], Tolerance);
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}
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}
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// ─── Output clamp guarantee ───────────────────────────────────────────────
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[Fact]
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public void Fft_OutputNeverExceedsClampBounds_LargeDataset()
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{
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int windowSize = 64;
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int minP = 4;
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int maxP = 32;
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int count = 500;
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var gbm = new GBM(startPrice: 100, mu: 0.0, sigma: 0.5, seed: 81005);
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var indicator = new Fft(windowSize, minP, maxP);
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for (int i = 0; i < count; i++)
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{
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indicator.Update(bars.Close[i]);
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if (indicator.IsHot)
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{
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double v = indicator.Last.Value;
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Assert.True(v >= minP && v <= maxP,
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$"Bar {i}: output {v:F2} outside [{minP},{maxP}]");
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}
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}
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}
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// ─── Batch span NaN safety ────────────────────────────────────────────────
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[Fact]
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public void Fft_SpanBatch_WithNaN_AllOutputsFinite()
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{
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int windowSize = 32;
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int count = 80;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 81006);
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var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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double[] src = new double[count];
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for (int i = 0; i < count; i++)
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{
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src[i] = bars.Close[i].Value;
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}
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// Inject NaNs at various positions
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src[5] = double.NaN;
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src[20] = double.NaN;
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src[45] = double.NaN;
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double[] dst = new double[count];
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Fft.Batch(src, dst, windowSize, maxPeriod: 16);
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for (int i = 0; i < count; i++)
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{
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Assert.True(double.IsFinite(dst[i]),
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$"Output at {i} must be finite, got {dst[i]}");
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}
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}
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[Fact]
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public void Fft_Correction_StateRestores()
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{
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// The Hanning window maps idx=0 to the newest bar and _hanning[0]=0, so
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// corrections to the anchor bar carry zero spectral weight. isNew=false
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// determinism is still correct: restoring the original value reproduces the
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// original result exactly regardless of any intermediate correction.
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var ind = new Fft(windowSize: 32, maxPeriod: 16);
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var t0 = DateTime.MinValue;
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for (int i = 0; i < 50; i++)
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{
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ind.Update(new TValue(t0.AddSeconds(i), 100.0 + (10.0 * Math.Sin(2 * Math.PI * i / 8.0))));
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}
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var anchorTime = t0.AddSeconds(50);
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const double anchorPrice = 100.0;
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ind.Update(new TValue(anchorTime, anchorPrice), isNew: true);
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double anchorResult = ind.Last.Value;
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// Apply an arbitrary correction — spectral output is unchanged due to zero Hanning weight
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ind.Update(new TValue(anchorTime, anchorPrice * 100), isNew: false);
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// Restoring to original must exactly reproduce the original result
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ind.Update(new TValue(anchorTime, anchorPrice), isNew: false);
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Assert.Equal(anchorResult, ind.Last.Value, 1e-9);
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}
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}
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