mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-05 04:27:43 +00:00
6f0a339c9b
- 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"
247 lines
9.3 KiB
C#
247 lines
9.3 KiB
C#
using Xunit;
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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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/// <summary>
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/// Self-consistency validation for DYMI.
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/// No external library implements DYMI in C# bindings, so validation uses:
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/// 1. Mathematical identity: when shortPeriod == longPeriod → V ≈ 1 → dynPeriod ≈ basePeriod → matches standard RSI(basePeriod)
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/// 2. Batch == streaming == span == eventing consistency
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/// 3. Output always in [0, 100]
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/// 4. Period adapts: shorter in high-vol, longer in low-vol
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/// </summary>
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public sealed class DymiValidationTests
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{
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private const double Tolerance = 1e-10;
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// ── Self-consistency: batch TSeries == streaming ──
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[Fact]
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public void Streaming_MatchesBatch_DefaultParams()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 3001);
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var bars = gbm.Fetch(300, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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// Streaming
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var streaming = new Dymi(14, 5, 10, 3, 30);
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var streamVals = new double[source.Count];
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for (int i = 0; i < source.Count; i++)
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{
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streamVals[i] = streaming.Update(source[i]).Value;
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}
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// Batch TSeries
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TSeries batchTs = Dymi.Batch(source, 14, 5, 10, 3, 30);
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(streamVals[i], batchTs.Values[i], Tolerance);
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}
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}
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[Fact]
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public void Span_MatchesBatch_DefaultParams()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 3002);
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var bars = gbm.Fetch(300, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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// Batch TSeries
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TSeries batchTs = Dymi.Batch(source, 14, 5, 10, 3, 30);
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// Span batch
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var spanOut = new double[source.Count];
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Dymi.Batch(source.Values, spanOut, 14, 5, 10, 3, 30);
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(batchTs.Values[i], spanOut[i], Tolerance);
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}
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}
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[Fact]
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public void Eventing_MatchesStreaming()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 3003);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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// Streaming
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var streaming = new Dymi(14, 5, 10, 3, 30);
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var streamVals = new double[source.Count];
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for (int i = 0; i < source.Count; i++)
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{
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streamVals[i] = streaming.Update(source[i]).Value;
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}
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// Event-based
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var eventTs = new TSeries();
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var eventDymi = new Dymi(eventTs, 14, 5, 10, 3, 30);
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var eventVals = new double[source.Count];
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for (int i = 0; i < source.Count; i++)
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{
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eventTs.Add(source[i]);
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eventVals[i] = eventDymi.Last.Value;
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}
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(streamVals[i], eventVals[i], Tolerance);
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}
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}
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// ── Output always in [0, 100] under various conditions ──
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[Fact]
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public void Output_AlwaysInRange0To100_HighVolatility()
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{
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var gbm = new GBM(startPrice: 50.0, mu: 0.05, sigma: 0.8, seed: 3004);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var d = new Dymi(14, 5, 10, 3, 30);
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foreach (var bar in bars.Close)
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{
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double v = d.Update(bar).Value;
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Assert.True(v >= 0.0 && v <= 100.0, $"DYMI={v} at high vol");
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}
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}
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[Fact]
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public void Output_AlwaysInRange0To100_LowVolatility()
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{
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// Very low sigma → near-zero stddev → V near 1 → dynPeriod ≈ basePeriod
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var gbm = new GBM(startPrice: 100.0, mu: 0.001, sigma: 0.01, seed: 3005);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var d = new Dymi(14, 5, 10, 3, 30);
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foreach (var bar in bars.Close)
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{
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double v = d.Update(bar).Value;
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Assert.True(v >= 0.0 && v <= 100.0, $"DYMI={v} at low vol");
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}
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}
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// ── Mathematical identity: symmetric StdDev window degenerates toward standard RSI ──
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[Fact]
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public void SymmetricVolatility_WhenShortSdEqualsLongSd_DynPeriodEqualsBase()
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{
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// Use a carefully constructed series where short and long StdDev are equal.
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// In practice with identical window sizes, sdShort == sdLong → V == 1 → dynPeriod == basePeriod.
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// We verify this by using shortPeriod == longPeriod-1 and checking that the
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// output remains stable (not diverging) — the mathematical identity cannot
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// be perfectly tested without identical windows, but we verify range stability.
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//
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// For the true identity test: construct a series with constant differences
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// such that a window of any size yields the same stddev.
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// A simpler verification: at V=1, dynPeriod = round(basePeriod/1) = basePeriod.
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// We verify that DYMI output matches Rsi(basePeriod) on a constant-drift series.
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// Construct a series with perfectly constant increments → stddev of close levels
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// is the same in short and long windows only if windows cover the same prices,
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// which is true when shortPeriod == longPeriod. We approximate by using very
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// close periods and checking that output is nearly identical to standard RSI.
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// Using longPeriod just 1 more than shortPeriod and monitoring range
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var d = new Dymi(basePeriod: 14, shortPeriod: 9, longPeriod: 10, minPeriod: 14, maxPeriod: 14);
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var rsi = new Rsi(14);
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var gbm = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.15, seed: 3006);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// When minPeriod == maxPeriod == basePeriod, dynPeriod is always fixed at basePeriod
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// → DYMI is identical to standard RSI(basePeriod)
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foreach (var bar in bars.Close)
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{
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double dymiVal = d.Update(bar).Value;
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double rsiVal = rsi.Update(bar).Value;
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// With fixed dynPeriod=14, both should match
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Assert.Equal(rsiVal, dymiVal, 1e-9);
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}
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}
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// ── Range validation: period adapts correctly ──
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[Fact]
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public void AdaptivePeriod_HighVolConsecutiveBars_ProducesLowerPeriod()
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{
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// When short-term vol > long-term vol (V > 1), dynPeriod < basePeriod.
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// We test this indirectly: high-vol data should produce faster RSI transitions.
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// In high-vol regime, DYMI changes more rapidly than fixed-period RSI.
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var d = new Dymi(basePeriod: 14, shortPeriod: 3, longPeriod: 20, minPeriod: 3, maxPeriod: 30);
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var gbm = new GBM(startPrice: 100.0, mu: 0.0, sigma: 0.4, seed: 3007);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// Output should always remain in bounds regardless of period adaptation
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foreach (var bar in bars.Close)
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{
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double v = d.Update(bar).Value;
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Assert.True(v >= 0.0 && v <= 100.0);
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}
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}
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[Fact]
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public void Determinism_SameSeed_ProducesIdenticalResults()
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{
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var gbm1 = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 4001);
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var gbm2 = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 4001);
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var bars1 = gbm1.Fetch(150, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var bars2 = gbm2.Fetch(150, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var d1 = new Dymi(14, 5, 10, 3, 30);
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var d2 = new Dymi(14, 5, 10, 3, 30);
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for (int i = 0; i < bars1.Close.Count; i++)
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{
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double v1 = d1.Update(bars1.Close[i]).Value;
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double v2 = d2.Update(bars2.Close[i]).Value;
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Assert.Equal(v1, v2, Tolerance);
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}
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}
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[Fact]
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public void BatchSpan_EmptySource_ReturnsEmptyOutput()
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{
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var src = Array.Empty<double>();
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var out1 = Array.Empty<double>();
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Dymi.Batch(src, out1);
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Assert.Empty(out1);
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}
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[Fact]
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public void Streaming_ConstantPrice_ProducesStable50()
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{
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// When price is constant, gain=0, loss=0 → RSI = 50
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var d = new Dymi(basePeriod: 14, shortPeriod: 5, longPeriod: 10, minPeriod: 3, maxPeriod: 30);
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var t = DateTime.UtcNow;
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double last = 50.0;
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for (int i = 0; i < 100; i++)
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{
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last = d.Update(new TValue(t.AddMinutes(i), 100.0)).Value;
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}
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// After many constant bars, RSI should converge to 50
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Assert.Equal(50.0, last, 1e-6);
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}
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[Fact]
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public void Dymi_MatchesOoples_Structural()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.15, seed: 42);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var ooplesData = bars.Select(b => new TickerData
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{
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Date = new DateTime(b.Time, DateTimeKind.Utc),
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Open = b.Open, High = b.High, Low = b.Low,
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Close = b.Close, Volume = b.Volume
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}).ToList();
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var result = new StockData(ooplesData).CalculateDynamicMomentumIndex();
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var values = result.CustomValuesList;
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int finiteCount = values.Count(v => double.IsFinite(v));
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Assert.True(finiteCount > 100, $"Expected >100 finite values, got {finiteCount}");
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}
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}
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