using System; using System.Collections.Generic; using System.Linq; using Skender.Stock.Indicators; using TALib; using Tulip; using Xunit; using Xunit.Abstractions; namespace QuanTAlib.Tests; public sealed class DemaValidationTests : IDisposable { private readonly ValidationTestData _testData; private readonly ITestOutputHelper _output; private bool _disposed; public DemaValidationTests(ITestOutputHelper output) { _output = output; _testData = new ValidationTestData(); } public void Dispose() { Dispose(true); } private void Dispose(bool disposing) { if (_disposed) { return; } _disposed = true; if (disposing) { _testData?.Dispose(); } } [Fact] public void Validate_Skender_Batch() { int[] periods = { 5, 10, 20, 50, 100 }; foreach (var period in periods) { // Calculate QuanTAlib DEMA (batch TSeries) var dema = new global::QuanTAlib.Dema(period); var qResult = dema.Update(_testData.Data); // Calculate Skender DEMA var sResult = _testData.SkenderQuotes.GetDema(period).ToList(); // Compare last 100 records ValidationHelper.VerifyData(qResult, sResult, (s) => s.Dema); } _output.WriteLine("DEMA Batch(TSeries) validated successfully against Skender.Stock.Indicators"); } [Fact] public void Validate_Talib_Batch() { int[] periods = { 5, 10, 20, 50, 100 }; // Prepare data for TA-Lib (double[]) double[] tData = _testData.RawData.ToArray(); double[] output = new double[tData.Length]; foreach (var period in periods) { // Calculate QuanTAlib DEMA (batch TSeries) var dema = new global::QuanTAlib.Dema(period); var qResult = dema.Update(_testData.Data); // Calculate TA-Lib DEMA var retCode = TALib.Functions.Dema(tData, 0..^0, output, out var outRange, period); Assert.Equal(Core.RetCode.Success, retCode); int lookback = TALib.Functions.DemaLookback(period); // Compare last 100 records ValidationHelper.VerifyData(qResult, output, outRange, lookback); } _output.WriteLine("DEMA Batch(TSeries) validated successfully against TA-Lib"); } [Fact] public void Validate_Tulip_Batch() { int[] periods = { 5, 10, 20, 50, 100 }; // Prepare data for Tulip (double[]) double[] tData = _testData.RawData.ToArray(); foreach (var period in periods) { // Calculate QuanTAlib DEMA (batch TSeries) var dema = new global::QuanTAlib.Dema(period); var qResult = dema.Update(_testData.Data); // Calculate Tulip DEMA var demaIndicator = Tulip.Indicators.dema; double[][] inputs = { tData }; double[] options = { period }; // Tulip DEMA lookback is usually period-1 for EMA, but DEMA is 2*EMA - EMA(EMA) // Let's rely on the output length to align. // Tulip DEMA lookback is same as EMA lookback? No, it involves double smoothing. // Actually, Tulip's DEMA implementation might have a specific lookback. // We'll calculate it based on output length. // Tulip.Indicators.dema.Run expects outputs to be sized correctly. // We'll use a large buffer and resize if needed, or just calculate lookback. // For DEMA(n), lookback is roughly n-1 (same as EMA). // Wait, DEMA uses EMA(EMA), so it might be 2*(n-1)? // Let's try with n-1 first, if it fails we adjust. // Actually, TA-Lib DEMA lookback is 2*(period-1). // Let's assume Tulip is similar. int lookback = 2 * (period - 1); double[][] outputs = { new double[tData.Length - lookback] }; demaIndicator.Run(inputs, options, outputs); var tResult = outputs[0]; // Compare last 100 records ValidationHelper.VerifyData(qResult, tResult, lookback); } _output.WriteLine("DEMA Batch(TSeries) validated successfully against Tulip"); } [Fact] public void Validate_Talib_Span() { int[] periods = { 5, 10, 20, 50, 100 }; // Prepare data double[] sourceData = _testData.RawData.ToArray(); double[] talibOutput = new double[sourceData.Length]; foreach (var period in periods) { // Calculate QuanTAlib DEMA (Span API) double[] qOutput = new double[sourceData.Length]; global::QuanTAlib.Dema.Calculate(sourceData.AsSpan(), qOutput.AsSpan(), period); // Calculate TA-Lib DEMA var retCode = TALib.Functions.Dema(sourceData, 0..^0, talibOutput, out var outRange, period); Assert.Equal(Core.RetCode.Success, retCode); int lookback = TALib.Functions.DemaLookback(period); // Compare last 100 records ValidationHelper.VerifyData(qOutput, talibOutput, outRange, lookback); } _output.WriteLine("DEMA Span validated successfully against TA-Lib"); } [Fact] public void Validate_Against_Ooples() { // Ooples Finance implementation of DEMA is standard: // DEMA = 2 * EMA(n) - EMA(EMA(n)) // We validate that our Dema class matches this composition using our own Ema class. int[] periods = { 5, 10, 14, 20 }; foreach (var period in periods) { var dema = new Dema(period); var ema1 = new Ema(period); var ema2 = new Ema(period); for (int i = 0; i < _testData.Data.Count; i++) { var item = _testData.Data[i]; // QuanTAlib DEMA var qVal = dema.Update(item); // Manual DEMA (Ooples logic) var e1 = ema1.Update(item); var e2 = ema2.Update(e1); // EMA of EMA double ooplesVal = 2 * e1.Value - e2.Value; // Compare // Note: There might be tiny differences due to floating point operations order // or internal state handling optimization in Dema class vs composed Ema classes. Assert.Equal(ooplesVal, qVal.Value, ValidationHelper.DefaultTolerance); } } _output.WriteLine("DEMA validated successfully against Ooples logic (2*EMA - EMA(EMA))"); } }