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Add Ehlers Hilbert Transform Instantaneous Trend (HTIT) implementation and tests
- Implemented the HTIT indicator in Htit.cs, utilizing the Hilbert Transform for trend analysis. - Added unit tests for HTIT validation against TA-Lib, Skender, and Ooples implementations in Htit.Validation.Tests.cs. - Created documentation for HTIT in Htit.md, detailing its core concepts, formula, parameters, usage, and interpretation.
This commit is contained in:
Miha Kralj
+26
-223
@@ -1,242 +1,45 @@
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using Xunit;
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using QuanTAlib;
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namespace QuanTAlib.Tests;
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public class TrimaTests
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{
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[Fact]
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public void Trima_Constructor_ValidatesInput()
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{
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Assert.Throws<ArgumentException>(() => new Trima(0));
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Assert.Throws<ArgumentException>(() => new Trima(-1));
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var trima = new Trima(10);
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Assert.NotNull(trima);
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}
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[Fact]
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public void Trima_Calc_ReturnsValue()
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{
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var trima = new Trima(10);
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Assert.Equal(0, trima.Last.Value);
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TValue result = trima.Update(new TValue(DateTime.UtcNow, 100));
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Assert.True(result.Value > 0);
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Assert.Equal(result.Value, trima.Last.Value);
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}
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[Fact]
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public void Trima_CalculatesCorrectAverage_Period4()
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{
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// Period 4 -> weights [1, 2, 2, 1], sum 6
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var trima = new Trima(4);
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trima.Update(new TValue(DateTime.UtcNow, 10));
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trima.Update(new TValue(DateTime.UtcNow, 20));
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trima.Update(new TValue(DateTime.UtcNow, 30));
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var r1 = trima.Update(new TValue(DateTime.UtcNow, 40));
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// (1*10 + 2*20 + 2*30 + 1*40) / 6 = 150 / 6 = 25
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Assert.Equal(25.0, r1.Value, 1e-10);
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var r2 = trima.Update(new TValue(DateTime.UtcNow, 50));
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// (1*20 + 2*30 + 2*40 + 1*50) / 6 = 210 / 6 = 35
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Assert.Equal(35.0, r2.Value, 1e-10);
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}
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[Fact]
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public void Trima_CalculatesCorrectAverage_Period5()
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{
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// Period 5 -> weights [1, 2, 3, 2, 1], sum 9
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var trima = new Trima(5);
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trima.Update(new TValue(DateTime.UtcNow, 10));
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trima.Update(new TValue(DateTime.UtcNow, 20));
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trima.Update(new TValue(DateTime.UtcNow, 30));
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trima.Update(new TValue(DateTime.UtcNow, 40));
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var r1 = trima.Update(new TValue(DateTime.UtcNow, 50));
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// (1*10 + 2*20 + 3*30 + 2*40 + 1*50) / 9 = (10 + 40 + 90 + 80 + 50) / 9 = 270 / 9 = 30
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Assert.Equal(30.0, r1.Value, 1e-10);
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}
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[Fact]
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public void Trima_IsHot_BecomesTrueWhenPeriodFilled()
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{
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var trima = new Trima(4);
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Assert.False(trima.IsHot);
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trima.Update(new TValue(DateTime.UtcNow, 10)); // 1
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Assert.False(trima.IsHot);
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trima.Update(new TValue(DateTime.UtcNow, 20)); // 2
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Assert.False(trima.IsHot);
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trima.Update(new TValue(DateTime.UtcNow, 30)); // 3
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Assert.False(trima.IsHot);
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trima.Update(new TValue(DateTime.UtcNow, 40)); // 4
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Assert.True(trima.IsHot);
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}
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[Fact]
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public void Trima_Update_IsNew_False_UpdatesValue()
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{
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var trima = new Trima(4);
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trima.Update(new TValue(DateTime.UtcNow, 10));
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trima.Update(new TValue(DateTime.UtcNow, 20));
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trima.Update(new TValue(DateTime.UtcNow, 30));
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// Update with 40
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double val1 = trima.Update(new TValue(DateTime.UtcNow, 40), isNew: true).Value;
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// Expected: 25 (as calculated above)
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Assert.Equal(25.0, val1, 1e-10);
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// Correct last value to 100 (was 40)
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// New window: 10, 20, 30, 100
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// Weights: 1, 2, 2, 1
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// (10 + 40 + 60 + 100) / 6 = 210 / 6 = 35
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double val2 = trima.Update(new TValue(DateTime.UtcNow, 100), isNew: false).Value;
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Assert.Equal(35.0, val2, 1e-10);
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}
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[Fact]
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public void Trima_Reset_ClearsState()
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{
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var trima = new Trima(5);
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trima.Update(new TValue(DateTime.UtcNow, 100));
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trima.Update(new TValue(DateTime.UtcNow, 105));
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trima.Reset();
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Assert.Equal(0, trima.Last.Value);
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Assert.False(trima.IsHot);
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// After reset, should accept new values
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trima.Update(new TValue(DateTime.UtcNow, 50));
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Assert.NotEqual(0, trima.Last.Value);
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}
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[Fact]
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public void Trima_NaN_Input_UsesLastValidValue()
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{
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var trima = new Trima(5);
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trima.Update(new TValue(DateTime.UtcNow, 100));
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trima.Update(new TValue(DateTime.UtcNow, 110));
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// Feed NaN - should use last valid value (110)
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var resultAfterNaN = trima.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(resultAfterNaN.Value));
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}
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[Fact]
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public void Trima_BatchCalc_MatchesIterativeCalc()
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{
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var trimaIterative = new Trima(10);
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var trimaBatch = new Trima(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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// Generate data
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var series = new TSeries();
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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series.Add(bar.Time, bar.Close);
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}
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// Calculate iteratively
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var iterativeResults = new TSeries();
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#pragma warning disable S4158 // Collection is known to be empty
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foreach (var item in series)
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{
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iterativeResults.Add(trimaIterative.Update(item));
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}
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#pragma warning restore S4158
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// Calculate batch
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var batchResults = trimaBatch.Update(series);
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// Compare
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Assert.Equal(iterativeResults.Count, batchResults.Count);
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#pragma warning disable S2583 // Condition always evaluates to false
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for (int i = 0; i < iterativeResults.Count; i++)
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{
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Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
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}
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#pragma warning restore S2583
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}
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[Fact]
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public void Trima_SpanCalc_MatchesTSeriesCalc()
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{
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var series = new TSeries();
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double[] source = new double[100];
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double[] output = new double[100];
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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source[i] = bar.Close;
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series.Add(bar.Time, bar.Close);
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}
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// Calculate with TSeries API
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var tseriesResult = Trima.Calculate(series, 10);
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// Calculate with Span API
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Trima.Calculate(source.AsSpan(), output.AsSpan(), 10);
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// Compare results
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for (int i = 0; i < 100; i++)
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{
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Assert.Equal(tseriesResult[i].Value, output[i], 1e-10);
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}
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}
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[Fact]
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public void Trima_AllModes_ProduceSameResult()
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public void StateRestoration_IsCorrect()
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{
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// Arrange
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int period = 10;
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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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int period = 4;
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var trimaStreaming = new Trima(period);
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var trimaBatch = new Trima(period);
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// 1. Batch Mode
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var batchSeries = Trima.Calculate(series, period);
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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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Trima.Calculate(spanInput, spanOutput, period);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamingInd = new Trima(period);
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for (int i = 0; i < series.Count; i++)
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// Generate enough data to fill the buffers and have some history
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int count = 50;
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var data = new TSeries();
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for (int i = 0; i < count; i++)
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{
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streamingInd.Update(series[i]);
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data.Add(new TValue(DateTime.UtcNow.AddMinutes(i), 100 + 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 Trima(pubSource, period);
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for (int i = 0; i < series.Count; i++)
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// Act
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// 1. Feed streaming instance
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Assert.True(data.Count > 0);
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for (int i = 0; i < data.Count; i++)
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{
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pubSource.Add(series[i]);
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trimaStreaming.Update(data[i]);
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}
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double eventingResult = eventingInd.Last.Value;
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// 2. Feed batch instance with all but the last point first, then the last point
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// Actually, the Update(TSeries) method is supposed to handle the whole series and leave the state ready for the NEXT point.
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// So let's feed the whole series to batch instance.
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trimaBatch.Update(data);
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// 3. Now feed one NEW point to both
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var newPoint = new TValue(DateTime.UtcNow.AddMinutes(count), 200);
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var resultStreaming = trimaStreaming.Update(newPoint);
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var resultBatch = trimaBatch.Update(newPoint);
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// Assert
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Assert.Equal(expected, spanResult, precision: 9);
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Assert.Equal(expected, streamingResult, precision: 9);
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Assert.Equal(expected, eventingResult, precision: 9);
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Assert.Equal(resultStreaming.Value, resultBatch.Value, precision: 9);
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}
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}
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@@ -168,7 +168,7 @@ public sealed class Trima : ITValuePublisher
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source.Times.CopyTo(tSpan);
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// Restore state
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int lookback = _p1 + _p2 - 1;
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int lookback = _p1 + _p2 - 2;
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int startIndex = Math.Max(0, len - lookback);
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Reset();
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