using System; using Xunit; namespace QuanTAlib.Tests; public class SkewTests { [Fact] public void Constructor_ValidatesPeriod() { Assert.Throws(() => new Skew(2)); var skew = new Skew(3); Assert.NotNull(skew); } [Fact] public void Update_CalculatesCorrectly_Sample() { // Test data: 1, 2, 3, 4, 5 // Mean = 3 // Variance (Sample) = 2.5 // StdDev (Sample) = 1.58113883 // Skewness (Sample) = 0 (Symmetric) var skew = new Skew(5, isPopulation: false); skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 2)); skew.Update(new TValue(DateTime.UtcNow, 3)); skew.Update(new TValue(DateTime.UtcNow, 4)); var result = skew.Update(new TValue(DateTime.UtcNow, 5)); Assert.Equal(0, result.Value, precision: 10); } [Fact] public void Update_CalculatesCorrectly_PositiveSkew() { // Test data: 1, 1, 1, 10 // Mean = 3.25 // Skewness should be positive (right tail) var skew = new Skew(4, isPopulation: false); skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 1)); var result = skew.Update(new TValue(DateTime.UtcNow, 10)); Assert.True(result.Value > 0); } [Fact] public void Update_CalculatesCorrectly_NegativeSkew() { // Test data: 10, 10, 10, 1 // Mean = 7.75 // Skewness should be negative (left tail) var skew = new Skew(4, isPopulation: false); skew.Update(new TValue(DateTime.UtcNow, 10)); skew.Update(new TValue(DateTime.UtcNow, 10)); skew.Update(new TValue(DateTime.UtcNow, 10)); var result = skew.Update(new TValue(DateTime.UtcNow, 1)); Assert.True(result.Value < 0); } [Fact] public void Update_HandlesUpdates_IsNewFalse() { var skew = new Skew(5); // 1, 2, 3, 4 skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 2)); skew.Update(new TValue(DateTime.UtcNow, 3)); skew.Update(new TValue(DateTime.UtcNow, 4)); // Add 5 skew.Update(new TValue(DateTime.UtcNow, 5), isNew: true); // Update 5 to 10 var res2 = skew.Update(new TValue(DateTime.UtcNow, 10), isNew: false); // Expected: Skew of 1, 2, 3, 4, 10 var expectedSkew = new Skew(5); expectedSkew.Update(new TValue(DateTime.UtcNow, 1)); expectedSkew.Update(new TValue(DateTime.UtcNow, 2)); expectedSkew.Update(new TValue(DateTime.UtcNow, 3)); expectedSkew.Update(new TValue(DateTime.UtcNow, 4)); var expected = expectedSkew.Update(new TValue(DateTime.UtcNow, 10)); Assert.Equal(expected.Value, res2.Value, precision: 10); } [Fact] public void Reset_ClearsState() { var skew = new Skew(5); for (int i = 0; i < 5; i++) skew.Update(new TValue(DateTime.UtcNow, i)); skew.Reset(); Assert.False(skew.IsHot); // Should behave like new skew.Update(new TValue(DateTime.UtcNow, 1)); Assert.Equal(0, skew.Last.Value); // Not enough data } [Fact] public void Batch_Matches_Streaming() { var data = new double[] { 1, 2, 3, 4, 5, 10, 1, 2, 3 }; int period = 5; // Streaming var skew = new Skew(period); var streamingResults = new System.Collections.Generic.List(); foreach (var val in data) { streamingResults.Add(skew.Update(new TValue(DateTime.UtcNow, val)).Value); } // Batch var series = new TSeries(new System.Collections.Generic.List(new long[data.Length]), new System.Collections.Generic.List(data)); var batchResult = Skew.Calculate(series, period); for (int i = 0; i < data.Length; i++) { Assert.Equal(streamingResults[i], batchResult.Values[i], precision: 10); } } [Fact] public void Update_CalculatesCorrectly_Population() { // Test data: 1, 2, 3 // Mean = 2 // Variance (Pop) = ((1-2)^2 + (2-2)^2 + (3-2)^2) / 3 = 2/3 // StdDev (Pop) = sqrt(2/3) // M3 (Pop) = ((1-2)^3 + (2-2)^3 + (3-2)^3) / 3 = 0 // Skew (Pop) = 0 var skew = new Skew(3, isPopulation: true); skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 2)); var result = skew.Update(new TValue(DateTime.UtcNow, 3)); Assert.Equal(0, result.Value, precision: 10); } [Fact] public void Update_HandlesConstantValues_ZeroVariance() { var skew = new Skew(5); for (int i = 0; i < 5; i++) { var result = skew.Update(new TValue(DateTime.UtcNow, 10)); Assert.Equal(0, result.Value); // Skew is undefined or 0 for constant values } } [Fact] public void Update_HandlesNaN() { var skew = new Skew(5); skew.Update(new TValue(DateTime.UtcNow, 1)); skew.Update(new TValue(DateTime.UtcNow, 2)); skew.Update(new TValue(DateTime.UtcNow, double.NaN)); // Should be treated as 0 or handled gracefully var result = skew.Last.Value; Assert.True(double.IsNaN(result) || result == 0); } [Fact] public void Resync_DoesNotDrift() { // Run for > 1000 updates to trigger Resync var skew = new Skew(10); var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123); for (int i = 0; i < 1100; i++) { skew.Update(new TValue(DateTime.UtcNow, gbm.Next().Close)); } Assert.True(double.IsFinite(skew.Last.Value)); } [Fact] public void Batch_LargeDataset_Simd() { // Create large dataset to trigger SIMD path (>= 256) int count = 1000; var data = new double[count]; for (int i = 0; i < count; i++) data[i] = (double)i; var series = new TSeries(new System.Collections.Generic.List(new long[count]), new System.Collections.Generic.List(data)); // Batch calculation var batchResult = Skew.Calculate(series, 10); // Verify last value against streaming var skew = new Skew(10); double lastStreaming = 0; foreach (var val in data) { lastStreaming = skew.Update(new TValue(DateTime.UtcNow, val)).Value; } Assert.Equal(lastStreaming, batchResult.Last.Value, precision: 10); } }