namespace QuanTAlib.Tests; public class HammaTests { [Fact] public void Hamma_Constructor_ValidatesInput() { var ex1 = Assert.Throws(() => new Hamma(0)); Assert.Equal("period", ex1.ParamName); var ex2 = Assert.Throws(() => new Hamma(-1)); Assert.Equal("period", ex2.ParamName); var hamma = new Hamma(10); Assert.NotNull(hamma); } [Fact] public void Hamma_Calc_ReturnsValue() { var hamma = new Hamma(10); TValue result = hamma.Update(new TValue(DateTime.UtcNow, 100)); Assert.True(result.Value > 0); } [Fact] public void Hamma_IsHot_BecomesTrueWhenBufferFull() { var hamma = new Hamma(5); Assert.False(hamma.IsHot); for (int i = 0; i < 4; i++) { hamma.Update(new TValue(DateTime.UtcNow, 100)); Assert.False(hamma.IsHot); } hamma.Update(new TValue(DateTime.UtcNow, 100)); Assert.True(hamma.IsHot); } [Fact] public void Hamma_StreamingMatchesBatch() { var hammaStreaming = new Hamma(10); var hammaBatch = new Hamma(10); var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42); var series = new TSeries(); for (int i = 0; i < 100; i++) { var bar = gbm.Next(isNew: true); series.Add(new TValue(bar.Time, bar.Close)); } // Streaming var streamingResults = new TSeries(); Assert.True(series.Count > 0); foreach (var item in series) { streamingResults.Add(hammaStreaming.Update(item)); } // Batch var batchResults = hammaBatch.Update(series); Assert.Equal(streamingResults.Count, batchResults.Count); for (int i = 0; i < batchResults.Count; i++) { Assert.Equal(streamingResults[i].Value, batchResults[i].Value, 1e-9); } } [Fact] public void Hamma_StaticCalculate_MatchesInstance() { var series = new TSeries(); var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42); for (int i = 0; i < 100; i++) { var bar = gbm.Next(isNew: true); series.Add(bar.Time, bar.Close); } var instanceResults = new Hamma(10).Update(series); var staticResults = Hamma.Batch(series, 10); for (int i = 0; i < instanceResults.Count; i++) { Assert.Equal(instanceResults[i].Value, staticResults[i].Value, 1e-9); } } [Fact] public void Hamma_SpanCalculate_MatchesSeries() { var series = new TSeries(); var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42); for (int i = 0; i < 100; i++) { var bar = gbm.Next(isNew: true); series.Add(bar.Time, bar.Close); } var seriesResults = Hamma.Batch(series, 10); double[] input = series.Values.ToArray(); double[] output = new double[input.Length]; Hamma.Batch(input.AsSpan(), output.AsSpan(), 10); for (int i = 0; i < input.Length; i++) { Assert.Equal(seriesResults[i].Value, output[i], 1e-9); } } [Fact] public void Hamma_Update_IsNewFalse_CorrectsValue() { var hamma = new Hamma(10); var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42); // Feed initial data for (int i = 0; i < 20; i++) { var bar = gbm.Next(isNew: true); hamma.Update(new TValue(bar.Time, bar.Close), isNew: true); } // Update with isNew=false (correction) var newBar = gbm.Next(isNew: true); hamma.Update(new TValue(newBar.Time, newBar.Close), isNew: true); double valueAfterCommit = hamma.Last.Value; // Now update the SAME bar with a different value hamma.Update(new TValue(newBar.Time, newBar.Close + 10.0), isNew: false); double valueAfterCorrection = hamma.Last.Value; Assert.NotEqual(valueAfterCommit, valueAfterCorrection); // Now restore original value hamma.Update(new TValue(newBar.Time, newBar.Close), isNew: false); Assert.Equal(valueAfterCommit, hamma.Last.Value, 1e-9); } [Fact] public void Hamma_NaN_Input_UsesLastValidValue() { var hamma = new Hamma(5); hamma.Update(new TValue(DateTime.UtcNow, 100)); hamma.Update(new TValue(DateTime.UtcNow, 110)); var resultAfterNaN = hamma.Update(new TValue(DateTime.UtcNow, double.NaN)); Assert.True(double.IsFinite(resultAfterNaN.Value)); Assert.NotEqual(0, resultAfterNaN.Value); } [Fact] public void Hamma_Reset_ClearsState() { var hamma = new Hamma(10); hamma.Update(new TValue(DateTime.UtcNow, 100)); hamma.Update(new TValue(DateTime.UtcNow, 110)); Assert.True(hamma.Last.Value > 0); hamma.Reset(); Assert.Equal(0, hamma.Last.Value); Assert.False(hamma.IsHot); } [Fact] public void Hamma_FirstValue_ReturnsExpected() { var hamma = new Hamma(10); TValue result = hamma.Update(new TValue(DateTime.UtcNow, 100)); Assert.Equal(100.0, result.Value, 1e-9); } [Fact] public void Hamma_Properties_Accessible() { var hamma = new Hamma(10); Assert.False(hamma.IsHot); Assert.Equal(0, hamma.Last.Value); } [Fact] public void Hamma_Calc_IsNew_AcceptsParameter() { var hamma = new Hamma(10); hamma.Update(new TValue(DateTime.UtcNow, 100), isNew: true); Assert.Equal(100, hamma.Last.Value); } [Fact] public void Hamma_IterativeCorrections_RestoreToOriginalState() { var hamma = new Hamma(10); var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1); // Feed 10 new values TValue tenthInput = default; for (int i = 0; i < 10; i++) { var bar = gbm.Next(isNew: true); tenthInput = new TValue(bar.Time, bar.Close); hamma.Update(tenthInput, isNew: true); } // Remember state after 10 values double valueAfterTen = hamma.Last.Value; // Generate 9 corrections with isNew=false (different values) for (int i = 0; i < 9; i++) { var bar = gbm.Next(isNew: false); hamma.Update(new TValue(bar.Time, bar.Close), isNew: false); } // Feed the remembered 10th input again with isNew=false TValue finalValue = hamma.Update(tenthInput, isNew: false); // Should match the original state after 10 values Assert.Equal(valueAfterTen, finalValue.Value, 1e-9); } [Fact] public void Hamma_Infinity_Input_UsesLastValidValue() { var hamma = new Hamma(10); hamma.Update(new TValue(DateTime.UtcNow, 100)); hamma.Update(new TValue(DateTime.UtcNow, 110)); var resultPosInf = hamma.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity)); Assert.True(double.IsFinite(resultPosInf.Value)); var resultNegInf = hamma.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity)); Assert.True(double.IsFinite(resultNegInf.Value)); } [Fact] public void Hamma_MultipleNaN_ContinuesWithLastValid() { var hamma = new Hamma(10); hamma.Update(new TValue(DateTime.UtcNow, 100)); var r1 = hamma.Update(new TValue(DateTime.UtcNow, double.NaN)); var r2 = hamma.Update(new TValue(DateTime.UtcNow, double.NaN)); Assert.True(double.IsFinite(r1.Value)); Assert.True(double.IsFinite(r2.Value)); } [Fact] public void Hamma_AllModes_ProduceSameResult() { // Arrange const int period = 10; var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123); var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1)); var series = bars.Close; // 1. Batch Mode var batchSeries = Hamma.Batch(series, period); double expected = batchSeries.Last.Value; // 2. Span Mode var tValues = series.Values.ToArray(); var spanInput = new ReadOnlySpan(tValues); var spanOutput = new double[tValues.Length]; Hamma.Batch(spanInput, spanOutput, period); double spanResult = spanOutput[^1]; // 3. Streaming Mode var streamingInd = new Hamma(period); for (int i = 0; i < series.Count; i++) { streamingInd.Update(series[i]); } double streamingResult = streamingInd.Last.Value; // 4. Eventing Mode var pubSource = new TSeries(); var eventingInd = new Hamma(pubSource, period); for (int i = 0; i < series.Count; i++) { pubSource.Add(series[i]); } double eventingResult = eventingInd.Last.Value; // Assert Assert.Equal(expected, spanResult, 1e-9); Assert.Equal(expected, streamingResult, 1e-9); Assert.Equal(expected, eventingResult, 1e-9); } [Fact] public void Hamma_SpanCalc_ValidatesInput() { double[] source = [1, 2, 3, 4, 5]; double[] output = new double[5]; double[] wrongSizeOutput = new double[3]; Assert.Throws(() => Hamma.Batch(source.AsSpan(), output.AsSpan(), 0)); Assert.Throws(() => Hamma.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3)); } [Fact] public void Hamma_SpanCalc_HandlesNaN() { double[] source = [100, 110, double.NaN, 120, 130]; double[] output = new double[5]; Hamma.Batch(source.AsSpan(), output.AsSpan(), 3); foreach (var val in output) { Assert.True(double.IsFinite(val)); } } [Fact] public void Hamma_HammingWindow_WeightSymmetry() { // Hamming window should be symmetric around center // w[i] = w[period-1-i] for all i int period = 11; // Odd for exact center // Verify weight symmetry by checking equal outputs for symmetric inputs var hamma1 = new Hamma(period); var hamma2 = new Hamma(period); // Feed ascending values to hamma1 double[] ascending = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]; foreach (var v in ascending) { hamma1.Update(new TValue(DateTime.UtcNow, v)); } // Feed descending values to hamma2 double[] descending = [11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]; foreach (var v in descending) { hamma2.Update(new TValue(DateTime.UtcNow, v)); } // Results should be the same (symmetric weights applied to symmetric data) Assert.Equal(hamma1.Last.Value, hamma2.Last.Value, 1e-9); } [Fact] public void Hamma_KnownValues_ManualCalculation() { // Manual verification with known Hamming weights // period=5: w[i] = 0.54 - 0.46 * cos(2π*i/4) // w[0] = 0.54 - 0.46 * cos(0) = 0.54 - 0.46 = 0.08 // w[1] = 0.54 - 0.46 * cos(π/2) = 0.54 - 0 = 0.54 // w[2] = 0.54 - 0.46 * cos(π) = 0.54 + 0.46 = 1.0 // w[3] = 0.54 - 0.46 * cos(3π/2) = 0.54 - 0 = 0.54 // w[4] = 0.54 - 0.46 * cos(2π) = 0.54 - 0.46 = 0.08 int period = 5; var hamma = new Hamma(period); double[] prices = [100, 102, 104, 103, 101]; foreach (var price in prices) { hamma.Update(new TValue(DateTime.UtcNow, price)); } // Calculate expected manually double twoPiOverPm1 = 2.0 * Math.PI / (period - 1); double[] weights = new double[period]; double weightSum = 0; for (int i = 0; i < period; i++) { weights[i] = 0.54 - 0.46 * Math.Cos(twoPiOverPm1 * i); weightSum += weights[i]; } double expected = 0; for (int i = 0; i < period; i++) { expected += prices[i] * weights[i]; } expected /= weightSum; Assert.Equal(expected, hamma.Last.Value, 1e-9); } [Fact] public void Hamma_PeriodOne_ReturnsInputValue() { var hamma = new Hamma(1); for (int i = 1; i <= 10; i++) { var input = new TValue(DateTime.UtcNow, i * 10.0); var result = hamma.Update(input); Assert.Equal(i * 10.0, result.Value, 1e-9); } } }