mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-03 03:47:42 +00:00
Miha Kralj
1084644a3d
- Implemented Aroon Indicator with constructor, initialization, and update methods. - Added unit tests for AroonIndicator to verify default settings, historical depth, short name, source code link, and processing of historical bars. - Created Aroon class for core calculations, including methods for updating with TBar and TBarSeries. - Added validation tests to ensure Aroon calculations match results from Skender and TA-Lib. - Updated documentation for Aroon Indicator with calculation methods and usage examples. - Refactored Dema and Wma classes to use Batch methods for calculations. - Enhanced performance benchmarks by increasing bar count and integrating OoplesFinance indicators. - Updated project dependencies to include OoplesFinance.StockIndicators.
332 lines
12 KiB
C#
332 lines
12 KiB
C#
using BenchmarkDotNet.Attributes;
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using BenchmarkDotNet.Columns;
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using BenchmarkDotNet.Configs;
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using BenchmarkDotNet.Jobs;
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using BenchmarkDotNet.Running;
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using BenchmarkDotNet.Toolchains.InProcess.NoEmit;
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using QuanTAlib;
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using QuanTAlib.Benchmarks;
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using Skender.Stock.Indicators;
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using TALib;
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using Tulip;
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using OoplesFinance.StockIndicators;
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using OoplesFinance.StockIndicators.Models;
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using OoplesFinance.StockIndicators.Enums;
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namespace QuanTAlib.Benchmarks;
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public static class Program
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{
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public static void Main(string[] args)
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{
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var config = ManualConfig.Create(DefaultConfig.Instance)
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.AddJob(Job.ShortRun
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.WithToolchain(InProcessNoEmitToolchain.Instance)
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.WithId(".NET 10.0"))
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.AddColumn(StatisticColumn.Mean)
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.AddColumn(StatisticColumn.StdDev)
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.HideColumns(Column.Job, Column.Error, Column.RatioSD);
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if (args.Length == 0)
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{
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BenchmarkRunner.Run<IndicatorBenchmarks>(config);
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}
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else
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{
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BenchmarkSwitcher.FromAssembly(typeof(Program).Assembly).Run(args, config);
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}
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}
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}
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[MemoryDiagnoser]
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[MarkdownExporter, HtmlExporter]
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[GroupBenchmarksBy(BenchmarkLogicalGroupRule.ByCategory)]
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public class IndicatorBenchmarks
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{
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private const int BarCount = 500_000;
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private const int Period = 220;
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private double[] _closeValues = null!;
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private TSeries _closeTseries = null!;
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private List<Quote> _quotes = null!;
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private List<TickerData> _ooplesData = null!;
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// Pre-allocated outputs for TA-Lib
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private double[] _talibOutput = null!;
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// Pre-allocated outputs for Tulip
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private double[][] _tulipSmaInputs = null!;
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private double[] _tulipSmaOptions = null!;
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private double[][] _tulipSmaOutputs = null!;
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private double[][] _tulipEmaInputs = null!;
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private double[] _tulipEmaOptions = null!;
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private double[][] _tulipEmaOutputs = null!;
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private double[][] _tulipWmaInputs = null!;
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private double[] _tulipWmaOptions = null!;
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private double[][] _tulipWmaOutputs = null!;
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private double[][] _tulipHmaInputs = null!;
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private double[] _tulipHmaOptions = null!;
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private double[][] _tulipHmaOutputs = null!;
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// Pre-allocated outputs for QuanTAlib Span API
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private double[] _quantalibOutput = null!;
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[GlobalSetup]
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public void Setup()
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{
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// Generate data using GBM
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var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42);
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var bars = gbm.Fetch(BarCount, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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_closeValues = bars.Close.Values.ToArray();
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_closeTseries = bars.Close;
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// Create Skender Quote format
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_quotes = new List<Quote>(BarCount);
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for (int i = 0; i < BarCount; i++)
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{
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_quotes.Add(new Quote
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{
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Date = new DateTime(_closeTseries.Times[i]),
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Open = (decimal)bars.Open.Values[i],
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High = (decimal)bars.High.Values[i],
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Low = (decimal)bars.Low.Values[i],
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Close = (decimal)_closeValues[i],
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Volume = (decimal)bars.Volume.Values[i]
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});
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}
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// Create Ooples TickerData format
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_ooplesData = new List<TickerData>(BarCount);
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for (int i = 0; i < BarCount; i++)
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{
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_ooplesData.Add(new TickerData
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{
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Date = new DateTime(_closeTseries.Times[i]),
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Open = bars.Open.Values[i],
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High = bars.High.Values[i],
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Low = bars.Low.Values[i],
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Close = _closeValues[i],
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Volume = bars.Volume.Values[i]
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});
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}
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// Pre-allocate TA-Lib output
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_talibOutput = new double[BarCount];
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// Pre-allocate Tulip arrays
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int smaLookback = Period - 1;
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_tulipSmaInputs = new[] { _closeValues };
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_tulipSmaOptions = new double[] { Period };
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_tulipSmaOutputs = new[] { new double[BarCount - smaLookback] };
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_tulipEmaInputs = new[] { _closeValues };
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_tulipEmaOptions = new double[] { Period };
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_tulipEmaOutputs = new[] { new double[BarCount] };
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_tulipWmaInputs = new[] { _closeValues };
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_tulipWmaOptions = new double[] { Period };
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_tulipWmaOutputs = new[] { new double[BarCount - smaLookback] };
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int hmaLookback = Period + (int)Math.Sqrt(Period) - 2;
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_tulipHmaInputs = new[] { _closeValues };
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_tulipHmaOptions = new double[] { Period };
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_tulipHmaOutputs = new[] { new double[BarCount - hmaLookback] };
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// Pre-allocate QuanTAlib output
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_quantalibOutput = new double[BarCount];
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}
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// ==================== SMA ====================
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "QuanTAlib SMA (Span)")]
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public void QuanTAlib_Sma_Span() => Sma.Batch(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "QuanTAlib SMA (Batch)")]
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public TSeries QuanTAlib_Sma_TSeries() => Sma.Calculate(_closeTseries, Period).Results;
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "QuanTAlib SMA (Streaming)")]
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public void QuanTAlib_Sma_Streaming()
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{
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var sma = new Sma(Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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_quantalibOutput[i] = sma.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
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}
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}
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "QuanTAlib SMA (Eventing)")]
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public void QuanTAlib_Sma_Eventing()
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{
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var source = new TSeries();
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var sma = new Sma(source, Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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source.Add(new TValue(_closeTseries.Times[i], _closeValues[i]));
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_quantalibOutput[i] = sma.Last.Value;
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}
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}
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "Tulip SMA")]
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public void Tulip_Sma() => Tulip.Indicators.sma.Run(_tulipSmaInputs, _tulipSmaOptions, _tulipSmaOutputs);
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "TALib SMA")]
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public Core.RetCode TALib_Sma() => TALib.Functions.Sma<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "Skender SMA")]
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public object Skender_Sma() => _quotes.GetSma(Period);
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[BenchmarkCategory("SMA")]
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[Benchmark(Description = "Ooples SMA")]
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public object Ooples_Sma() => new StockData(_ooplesData).CalculateSimpleMovingAverage(Period);
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// ==================== EMA ====================
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "QuanTAlib EMA (Span)")]
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public void QuanTAlib_Ema_Span() => Ema.Batch(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "QuanTAlib EMA (Batch)")]
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public TSeries QuanTAlib_Ema_TSeries() => Ema.Calculate(_closeTseries, Period).Results;
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "QuanTAlib EMA (Streaming)")]
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public void QuanTAlib_Ema_Streaming()
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{
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var ema = new Ema(Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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_quantalibOutput[i] = ema.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
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}
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}
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "QuanTAlib EMA (Eventing)")]
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public void QuanTAlib_Ema_Eventing()
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{
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var source = new TSeries();
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var ema = new Ema(source, Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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source.Add(new TValue(_closeTseries.Times[i], _closeValues[i]));
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_quantalibOutput[i] = ema.Last.Value;
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}
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}
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "Tulip EMA")]
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public void Tulip_Ema() => Tulip.Indicators.ema.Run(_tulipEmaInputs, _tulipEmaOptions, _tulipEmaOutputs);
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "TALib EMA")]
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public Core.RetCode TALib_Ema() => TALib.Functions.Ema<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "Skender EMA")]
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public object Skender_Ema() => _quotes.GetEma(Period);
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[BenchmarkCategory("EMA")]
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[Benchmark(Description = "Ooples EMA")]
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public object Ooples_Ema() => new StockData(_ooplesData).CalculateExponentialMovingAverage(Period);
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// ==================== WMA ====================
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "QuanTAlib WMA (Span)")]
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public void QuanTAlib_Wma_Span() => Wma.Batch(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "QuanTAlib WMA (Batch)")]
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public TSeries QuanTAlib_Wma_TSeries() => Wma.Batch(_closeTseries, Period);
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "QuanTAlib WMA (Streaming)")]
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public void QuanTAlib_Wma_Streaming()
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{
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var wma = new Wma(Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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_quantalibOutput[i] = wma.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
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}
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}
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "QuanTAlib WMA (Eventing)")]
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public void QuanTAlib_Wma_Eventing()
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{
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var source = new TSeries();
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var wma = new Wma(source, Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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source.Add(new TValue(_closeTseries.Times[i], _closeValues[i]));
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_quantalibOutput[i] = wma.Last.Value;
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}
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}
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "Tulip WMA")]
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public void Tulip_Wma() => Tulip.Indicators.wma.Run(_tulipWmaInputs, _tulipWmaOptions, _tulipWmaOutputs);
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "TALib WMA")]
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public Core.RetCode TALib_Wma() => TALib.Functions.Wma<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "Skender WMA")]
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public object Skender_Wma() => _quotes.GetWma(Period);
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[BenchmarkCategory("WMA")]
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[Benchmark(Description = "Ooples WMA")]
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public object Ooples_Wma() => new StockData(_ooplesData).CalculateWeightedMovingAverage(Period);
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// ==================== HMA ====================
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "QuanTAlib HMA (Span)")]
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public void QuanTAlib_Hma_Span() => Hma.Calculate(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "QuanTAlib HMA (Batch)")]
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public TSeries QuanTAlib_Hma_TSeries() => Hma.Batch(_closeTseries, Period);
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "QuanTAlib HMA (Streaming)")]
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public void QuanTAlib_Hma_Streaming()
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{
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var hma = new Hma(Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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_quantalibOutput[i] = hma.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
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}
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}
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "QuanTAlib HMA (Eventing)")]
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public void QuanTAlib_Hma_Eventing()
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{
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var source = new TSeries();
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var hma = new Hma(source, Period);
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for (int i = 0; i < _closeValues.Length; i++)
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{
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source.Add(new TValue(_closeTseries.Times[i], _closeValues[i]));
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_quantalibOutput[i] = hma.Last.Value;
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}
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}
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "Tulip HMA")]
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public void Tulip_Hma() => Tulip.Indicators.hma.Run(_tulipHmaInputs, _tulipHmaOptions, _tulipHmaOutputs);
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "Skender HMA")]
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public object Skender_Hma() => _quotes.GetHma(Period);
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[BenchmarkCategory("HMA")]
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[Benchmark(Description = "Ooples HMA")]
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public object Ooples_Hma() => new StockData(_ooplesData).CalculateHullMovingAverage(MovingAvgType.WeightedMovingAverage, Period);
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}
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