using System; using System.Linq; using Xunit; namespace QuanTAlib.Tests; public class KamaTests { [Fact] public void Kama_Constructor_ValidatesInput() { Assert.Throws(() => new Kama(0)); Assert.Throws(() => new Kama(10, fastPeriod: 0)); Assert.Throws(() => new Kama(10, slowPeriod: 0)); Assert.Throws(() => new Kama(10, fastPeriod: 10, slowPeriod: 5)); var kama = new Kama(10); Assert.NotNull(kama); } [Fact] public void Kama_Calc_ReturnsValue() { var kama = new Kama(10); TValue result = kama.Update(new TValue(DateTime.UtcNow, 100)); Assert.True(result.Value > 0); } [Fact] public void Kama_IsHot_BecomesTrueWhenBufferFull() { // Buffer size is period + 1 var kama = new Kama(5); Assert.False(kama.IsHot); for (int i = 0; i < 5; i++) { kama.Update(new TValue(DateTime.UtcNow, 100)); Assert.False(kama.IsHot); } kama.Update(new TValue(DateTime.UtcNow, 100)); Assert.True(kama.IsHot); } [Fact] public void Kama_StreamingMatchesBatch() { var kamaStreaming = new Kama(10); var kamaBatch = new Kama(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(bar.Time, bar.Close); } // Streaming var streamingResults = new TSeries(); Assert.True(series.Count > 0); foreach (var item in series) { streamingResults.Add(kamaStreaming.Update(item)); } // Batch var batchResults = kamaBatch.Update(series); Assert.Equal(streamingResults.Count, batchResults.Count); foreach (var (stream, batch) in streamingResults.Zip(batchResults)) { Assert.Equal(stream.Value, batch.Value, 1e-9); } } [Fact] public void Kama_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 Kama(10).Update(series); var staticResults = new double[series.Count]; Kama.Calculate(series.Values.ToArray().AsSpan(), staticResults.AsSpan(), 10); for (int i = 0; i < instanceResults.Count; i++) { Assert.Equal(instanceResults[i].Value, staticResults[i], 1e-9); } } [Fact] public void Kama_Update_IsNewFalse_CorrectsValue() { var kama = new Kama(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); kama.Update(new TValue(bar.Time, bar.Close), isNew: true); } // Update with isNew=false (correction) var newBar = gbm.Next(isNew: true); kama.Update(new TValue(newBar.Time, newBar.Close), isNew: true); double valueAfterCommit = kama.Last.Value; // Now update the SAME bar with a different value kama.Update(new TValue(newBar.Time, newBar.Close + 10.0), isNew: false); double valueAfterCorrection = kama.Last.Value; Assert.NotEqual(valueAfterCommit, valueAfterCorrection); // Now restore original value kama.Update(new TValue(newBar.Time, newBar.Close), isNew: false); Assert.Equal(valueAfterCommit, kama.Last.Value, 1e-9); } [Fact] public void Kama_NaN_Input_UsesLastValidValue() { var kama = new Kama(5); kama.Update(new TValue(DateTime.UtcNow, 100)); kama.Update(new TValue(DateTime.UtcNow, 110)); var resultAfterNaN = kama.Update(new TValue(DateTime.UtcNow, double.NaN)); Assert.True(double.IsFinite(resultAfterNaN.Value)); Assert.NotEqual(0, resultAfterNaN.Value); } [Fact] public void Kama_Reset_ClearsState() { var kama = new Kama(10); kama.Update(new TValue(DateTime.UtcNow, 100)); kama.Update(new TValue(DateTime.UtcNow, 110)); Assert.True(kama.Last.Value > 0); kama.Reset(); Assert.Equal(0, kama.Last.Value); Assert.False(kama.IsHot); } [Fact] public void Kama_FlatLine_ReturnsSameValue() { var kama = new Kama(10); for (int i = 0; i < 20; i++) { kama.Update(new TValue(DateTime.UtcNow, 100)); } Assert.Equal(100, kama.Last.Value); } [Fact] public void Kama_Calc_IsNew_AcceptsParameter() { var kama = new Kama(10); kama.Update(new TValue(DateTime.UtcNow, 100), isNew: true); Assert.Equal(100, kama.Last.Value); } [Fact] public void Kama_IterativeCorrections_RestoreToOriginalState() { var kama = new Kama(10); var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1); // Feed 20 new values (enough to fill buffer and stabilize) TValue lastInput = default; for (int i = 0; i < 20; i++) { var bar = gbm.Next(isNew: true); lastInput = new TValue(bar.Time, bar.Close); kama.Update(lastInput, isNew: true); } // Remember state double valueAfter = kama.Last.Value; // Generate 5 corrections with isNew=false (different values) for (int i = 0; i < 5; i++) { var bar = gbm.Next(isNew: false); kama.Update(new TValue(bar.Time, bar.Close), isNew: false); } // Feed the remembered last input again with isNew=false TValue finalValue = kama.Update(lastInput, isNew: false); // Should match the original state Assert.Equal(valueAfter, finalValue.Value, 1e-9); } [Fact] public void Kama_SpanCalc_ValidatesInput() { double[] source = [1, 2, 3, 4, 5]; double[] output = new double[5]; double[] wrongSizeOutput = new double[3]; Assert.Throws(() => Kama.Calculate(source.AsSpan(), output.AsSpan(), 0)); Assert.Throws(() => Kama.Calculate(source.AsSpan(), wrongSizeOutput.AsSpan(), 3)); } [Fact] public void Kama_SpanCalc_HandlesNaN() { double[] source = [100, 110, double.NaN, 120, 130]; double[] output = new double[5]; Kama.Calculate(source.AsSpan(), output.AsSpan(), 3); foreach (var val in output) { Assert.True(double.IsFinite(val)); } } [Fact] public void Kama_AllModes_ProduceSameResult() { // Arrange 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 = Kama.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]; Kama.Calculate(spanInput, spanOutput, period); double spanResult = spanOutput[^1]; // 3. Streaming Mode var streamingInd = new Kama(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 Kama(pubSource, period); for (int i = 0; i < series.Count; i++) { pubSource.Add(series[i]); } double eventingResult = eventingInd.Last.Value; // Assert Assert.Equal(expected, spanResult, precision: 9); Assert.Equal(expected, streamingResult, precision: 9); Assert.Equal(expected, eventingResult, precision: 9); } }