mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-16 09:38:05 +00:00
203 lines
8.9 KiB
C#
203 lines
8.9 KiB
C#
using Xunit;
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using System;
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using QuanTAlib;
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using Python.Runtime;
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using Python.Included;
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namespace Validations;
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public class PandasTA : IDisposable
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{
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private readonly GBM_Feed bars;
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private readonly Random rnd = new();
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private readonly int period;
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private int digits;
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private readonly string OStype;
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private readonly dynamic np;
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private readonly dynamic ta;
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private readonly dynamic df;
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public PandasTA() {
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bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0);
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period = rnd.Next(maxValue: 28) + 3;
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digits = 4; //minimizing rounding errors in type conversions
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// Checking the host OS and setting PythonDLL accordingly
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OStype = Path.GetFullPath(path: ".") + @"\python-3.10.0-embed-amd64\python310.dll";
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Installer.InstallPath = Path.GetFullPath(path: ".");
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Installer.SetupPython().Wait();
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Installer.TryInstallPip();
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Installer.PipInstallModule(module_name: "pandas-ta");
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Runtime.PythonDLL = OStype;
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PythonEngine.Initialize();
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np = Py.Import(name: "numpy");
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ta = Py.Import(name: "pandas_ta");
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string[] cols = { "open", "high", "low", "close", "volume" };
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double[,] ary = new double[bars.Count, 5];
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for (int i = 0; i < bars.Count; i++) {
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ary[i, 0] = bars.Open[i].v;
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ary[i, 1] = bars.High[i].v;
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ary[i, 2] = bars.Low[i].v;
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ary[i, 3] = bars.Close[i].v;
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ary[i, 4] = bars.Volume[i].v;
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}
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df = ta.DataFrame(data: np.array(ary), index: np.array(bars.Close.t), columns: np.array(cols));
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}
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public void Dispose()
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{
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PythonEngine.Shutdown();
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GC.SuppressFinalize(this);
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}
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[Fact] void ADL() {
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ADL_Series QL = new(bars);
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var pta = df.ta.ad(high: df.high, low: df.low, close:df.close, volume:df.volume);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void ADOSC() {
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ADOSC_Series QL = new(bars);
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var pta = df.ta.adosc(high: df.high, low: df.low, close: df.close, volume: df.volume);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void ATR() {
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ATR_Series QL = new(bars, period);
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var pta = df.ta.atr(high: df.high, low: df.low, close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void BIAS() {
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BIAS_Series QL = new(bars.Close, period, false);
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var pta = df.ta.bias(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void DEMA() {
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DEMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.dema(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void EMA() {
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EMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.ema(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void ENTROPY() {
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ENTROPY_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.entropy(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void HL2() {
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var pta = df.ta.hl2(high: df.high, low: df.low);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.HL2.Last().v, digits: digits));
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}
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[Fact] void HLC3() {
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var pta = df.ta.hlc3(high: df.high, low: df.low, close: df.close);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.HLC3.Last().v, digits: digits));
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}
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[Fact] void HMA() {
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HMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.hma(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void KAMA() {
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KAMA_Series QL = new(bars.Close, period);
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var pta = df.ta.kama(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void KURTOSIS() {
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KURTOSIS_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.kurtosis(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void MAD()
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{
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MAD_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.mad(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void MEDIAN() {
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MEDIAN_Series QL = new(bars.Close, period);
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var pta = df.ta.median(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void OBV() {
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OBV_Series QL = new(bars);
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var pta = df.ta.obv(close: df.close, volume: df.volume);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void OHLC4() {
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var pta = df.ta.ohlc4(open: df.open, high: df.high, low: df.low, close: df.close);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.OHLC4.Last().v, digits: digits));
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}
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[Fact] void RMA() {
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RMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.rma(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void RSI() {
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RSI_Series QL = new(bars.Close, period);
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var pta = df.ta.rsi(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void SDEV() {
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SDEV_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.stdev(close: df.close, length: period, ddof: 0);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void SMA() {
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SMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.sma(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void SSDEV() {
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SSDEV_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.stdev(close: df.close, length: period, ddof: 1);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void SVARIANCE() {
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SVAR_Series QL = new(bars.Close, period);
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var pta = df.ta.variance(close: df.close, length: period, ddof: 1);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void T3() {
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T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, useNaN: false);
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var pta = df.ta.t3(close: df.close, length: period, a: 0.7);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void TEMA() {
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TEMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.tema(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void TR() {
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TR_Series QL = new(bars);
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var pta = df.ta.true_range(high: df.high, low: df.low, close: df.close);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void TRIMA() {
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// TODO: return length to variable length (period) when Pandas-TA fixes trima to calculate even periods right
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TRIMA_Series QL = new(bars.Close, 11);
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var pta = df.ta.trima(close: df.close, length: 11);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void VARIANCE() {
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VAR_Series QL = new(bars.Close, period);
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var pta = df.ta.variance(close: df.close, length: period, ddof:0);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void WMA() {
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WMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.wma(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void ZLEMA() {
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ZLEMA_Series QL = new(bars.Close, period, false);
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var pta = df.ta.zlma(close: df.close, length: period);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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[Fact] void ZSCORE() {
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ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
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var pta = df.ta.zscore(close: df.close, length: period, ddof: 0);
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Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
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}
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} |