namespace QuanTAlib; public class ConvTests { [Fact] public void Constructor_EmptyKernel_ThrowsArgumentException() { Assert.Throws(() => new Conv(Array.Empty())); Assert.Throws(() => new Conv(null!)); } [Fact] public void BasicCalculation_MatchesExpected() { // Kernel: [0.5, 1.0] // Data: [1, 2, 3, 4] // 1: 1*1.0 = 1.0 (partial) // 2: 1*0.5 + 2*1.0 = 2.5 // 3: 2*0.5 + 3*1.0 = 4.0 // 4: 3*0.5 + 4*1.0 = 5.5 double[] kernel = [0.5, 1.0]; var conv = new Conv(kernel); var result1 = conv.Update(new TValue(DateTime.UtcNow, 1)); Assert.Equal(1.0, result1.Value); var result2 = conv.Update(new TValue(DateTime.UtcNow, 2)); Assert.Equal(2.5, result2.Value); var result3 = conv.Update(new TValue(DateTime.UtcNow, 3)); Assert.Equal(4.0, result3.Value); var result4 = conv.Update(new TValue(DateTime.UtcNow, 4)); Assert.Equal(5.5, result4.Value); } [Fact] public void BarCorrection_UpdatesCorrectly() { double[] kernel = [0.5, 1.0]; var conv = new Conv(kernel); // 1 conv.Update(new TValue(DateTime.UtcNow, 1)); // 2 (isNew=true) -> 2.5 var res1 = conv.Update(new TValue(DateTime.UtcNow, 2), isNew: true); Assert.Equal(2.5, res1.Value); // Update 2 to 3 (isNew=false) // Buffer was [1, 2]. Now [1, 3]. // 1*0.5 + 3*1.0 = 3.5 var res2 = conv.Update(new TValue(DateTime.UtcNow, 3), isNew: false); Assert.Equal(3.5, res2.Value); // New bar 4 (isNew=true) // Buffer was [1, 3]. New bar 4. Buffer becomes [3, 4]. // 3*0.5 + 4*1.0 = 1.5 + 4 = 5.5 var res3 = conv.Update(new TValue(DateTime.UtcNow, 4), isNew: true); Assert.Equal(5.5, res3.Value); } [Fact] public void NanHandling_UsesLastValid() { double[] kernel = [1.0, 1.0]; // Sum of last 2 var conv = new Conv(kernel); // 1 -> 1 conv.Update(new TValue(DateTime.UtcNow, 1)); // NaN -> treated as 1. Buffer: [1, 1]. Result: 2. var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN)); Assert.Equal(2.0, res.Value); // 2 -> Buffer: [1, 2]. Result: 3. res = conv.Update(new TValue(DateTime.UtcNow, 2)); Assert.Equal(3.0, res.Value); } [Fact] public void StaticCalculate_MatchesObjectApi() { double[] kernel = [0.5, 1.0]; var source = new TSeries(); source.Add(new TValue(DateTime.UtcNow, 1)); source.Add(new TValue(DateTime.UtcNow, 2)); source.Add(new TValue(DateTime.UtcNow, 3)); source.Add(new TValue(DateTime.UtcNow, 4)); var result = Conv.Batch(source, kernel); Assert.Equal(1.0, result.Values[0]); Assert.Equal(2.5, result.Values[1]); Assert.Equal(4.0, result.Values[2]); Assert.Equal(5.5, result.Values[3]); } [Fact] public void Reset_ClearsState() { double[] kernel = [1.0, 1.0]; var conv = new Conv(kernel); conv.Update(new TValue(DateTime.UtcNow, 1)); conv.Update(new TValue(DateTime.UtcNow, 2)); Assert.True(conv.IsHot); conv.Reset(); Assert.False(conv.IsHot); Assert.Equal(0, conv.Last.Value); // Should behave as new var res = conv.Update(new TValue(DateTime.UtcNow, 1)); Assert.Equal(1.0, res.Value); } [Fact] public void LeadingNaN_RemainsNaN() { double[] kernel = [1.0]; var conv = new Conv(kernel); var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN)); Assert.True(double.IsNaN(res.Value)); } [Fact] public void IterativeCorrections_RestoreToOriginalState() { double[] kernel = [0.5, 1.0]; var conv = new Conv(kernel); 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); conv.Update(tenthInput, isNew: true); } // Remember state after 10 values double valueAfterTen = conv.Last.Value; // Generate 9 corrections with isNew=false (different values) for (int i = 0; i < 9; i++) { var bar = gbm.Next(isNew: false); conv.Update(new TValue(bar.Time, bar.Close), isNew: false); } // Feed the remembered 10th input again with isNew=false TValue finalValue = conv.Update(tenthInput, isNew: false); // Should match the original state after 10 values Assert.Equal(valueAfterTen, finalValue.Value, 1e-9); } [Fact] public void AllModes_ProduceSameResult() { // Arrange double[] kernel = [0.1, 0.2, 0.3, 0.4]; 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 = Conv.Batch(series, kernel); double expected = batchSeries.Last.Value; // 2. Span Mode var tValues = series.Values.ToArray(); var spanInput = new ReadOnlySpan(tValues); var spanOutput = new double[tValues.Length]; Conv.Batch(spanInput, spanOutput, kernel); double spanResult = spanOutput[^1]; // 3. Streaming Mode var streamingInd = new Conv(kernel); 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 Conv(pubSource, kernel); 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 SpanCalc_ValidatesInput() { double[] source = [1, 2, 3, 4, 5]; double[] output = new double[5]; double[] wrongSizeOutput = new double[3]; double[] kernel = [0.5, 0.5]; Assert.Throws(() => Conv.Batch(source.AsSpan(), output.AsSpan(), Array.Empty())); Assert.Throws(() => Conv.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), kernel)); } [Fact] public void SpanCalc_HandlesNaN() { double[] source = [100, 110, double.NaN, 120, 130]; double[] output = new double[5]; double[] kernel = [0.5, 0.5]; Conv.Batch(source.AsSpan(), output.AsSpan(), kernel); foreach (var val in output) { Assert.True(double.IsFinite(val)); } } }