CORR - Pearson's Correlation Coefficient

This commit is contained in:
Miha Kralj
2022-11-15 21:12:03 -08:00
parent 80d82e5863
commit 73b41ac0a0
9 changed files with 1242 additions and 1141 deletions
+356 -356
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@@ -1,356 +1,356 @@
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+15 -2
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@@ -2,13 +2,13 @@
using System;
/* <summary>
Abstract classes with all scaffolding required to build indicators.
All abstracts support period, NaN, and all permutations of Add() methods.
All abstracts support period, NaN, and all permutations of Add() methods.
Indicator classess need to implement:
- Chaining constructor (Abstract's constructor executes first)
- Default Add(value) class
- optional Add(series) bulk insert class (for optimization of historical analysis)
Single_TSeries_Indicator - one single-value TSeries in, one TSeries out.
Single_TSeries_Indicator - one single-value TSeries in, one TSeries out.
Pair_TSeries_Indicator - Two TSeries in, one TSeries out. (includes simple semaphoring)
Single_TBars_Indicator - One OHLCV TBars in, one TSeries out.
@@ -42,11 +42,24 @@ public abstract class Single_TSeries_Indicator : TSeries
public abstract class Pair_TSeries_Indicator : TSeries
{
protected readonly int _p;
protected readonly bool _NaN;
protected readonly TSeries _d1;
protected readonly TSeries _d2;
protected readonly double _dd1, _dd2;
// Chainable Constructors - add them at the end of primary constructors if needed
protected Pair_TSeries_Indicator(TSeries source1, TSeries source2, int period, bool useNaN)
{
this._p = period;
this._NaN = useNaN;
this._d1 = source1;
this._d2 = source2;
this._dd1 = double.NaN;
this._dd2 = double.NaN;
this._d1.Pub += this.Sub;
this._d2.Pub += this.Sub;
}
protected Pair_TSeries_Indicator(TSeries source1, TSeries source2)
{
this._d1 = source1;
+46 -46
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@@ -1,47 +1,47 @@
namespace QuanTAlib;
using System;
using System.Text.Json;
/* <summary>
Yahoo Finance - Free API feed to collect daily market quotes
Parameters:
Symbol: stock symbol (default: "IBM")
Period: number of days of collected history (default: 252)
Usage:
Yahoo_Feed ticker = new("MSFT", 20)
</summary> */
public class Yahoo_Feed : TBars
{
public Yahoo_Feed(string Symbol = "IBM", int Period = 252) {
string requestUrl = "https://query1.finance.yahoo.com/v8/finance/chart/"+
Symbol+"?interval=1d&period1="+
(int)new DateTimeOffset(DateTime.UtcNow.AddDays(-Period+1)).ToUnixTimeSeconds()+"&period2="+
(int)new DateTimeOffset(DateTime.UtcNow).ToUnixTimeSeconds();
System.Net.Http.HttpClient client = new();
var msg = client.GetStringAsync(requestUrl).Result;
var jresult = JsonSerializer.Deserialize<JsonDocument>(msg).RootElement;
jresult.TryGetProperty("chart",out JsonElement json);
json.TryGetProperty("result",out json);
json[0].TryGetProperty("timestamp",out JsonElement datetime);
json[0].TryGetProperty("indicators",out json);
json.TryGetProperty("quote",out json);
json[0].TryGetProperty("open",out JsonElement open);
json[0].TryGetProperty("high",out JsonElement high);
json[0].TryGetProperty("low",out JsonElement low);
json[0].TryGetProperty("close",out JsonElement close);
json[0].TryGetProperty("volume",out JsonElement volume);
for (int i=0; i<datetime.GetArrayLength(); i++) {
DateTime d = DateTimeOffset.FromUnixTimeSeconds(long.Parse(datetime[i].GetRawText())).DateTime;
double o = Math.Round(double.Parse(open[i].GetRawText()),3);
double h = Math.Round(double.Parse(high[i].GetRawText()),3);
double l = Math.Round(double.Parse(low[i].GetRawText()),3);
double c = Math.Round(double.Parse(close[i].GetRawText()),3);
double v = Math.Round(double.Parse(volume[i].GetRawText()),3);
base.Add(d, o, h, l, c, v);
}
}
namespace QuanTAlib;
using System;
using System.Text.Json;
/* <summary>
Yahoo Finance - Free API feed to collect daily market quotes
Parameters:
Symbol: stock symbol (default: "IBM")
Period: number of days of collected history (default: 252)
Usage:
Yahoo_Feed ticker = new("MSFT", 20)
</summary> */
public class Yahoo_Feed : TBars
{
public Yahoo_Feed(string Symbol = "IBM", int Period = 252) {
string requestUrl = "https://query1.finance.yahoo.com/v8/finance/chart/"+
Symbol+"?interval=1d&period1="+
(int)new DateTimeOffset(DateTime.UtcNow.AddDays(-Period+1)).ToUnixTimeSeconds()+"&period2="+
(int)new DateTimeOffset(DateTime.UtcNow).ToUnixTimeSeconds();
System.Net.Http.HttpClient client = new();
var msg = client.GetStringAsync(requestUrl).Result;
var jresult = JsonSerializer.Deserialize<JsonDocument>(msg).RootElement;
jresult.TryGetProperty("chart",out JsonElement json);
json.TryGetProperty("result",out json);
json[0].TryGetProperty("timestamp",out JsonElement datetime);
json[0].TryGetProperty("indicators",out json);
json.TryGetProperty("quote",out json);
json[0].TryGetProperty("open",out JsonElement open);
json[0].TryGetProperty("high",out JsonElement high);
json[0].TryGetProperty("low",out JsonElement low);
json[0].TryGetProperty("close",out JsonElement close);
json[0].TryGetProperty("volume",out JsonElement volume);
for (int i=0; i<datetime.GetArrayLength(); i++) {
DateTime d = DateTimeOffset.FromUnixTimeSeconds(long.Parse(datetime[i].GetRawText())).DateTime;
double o = Math.Round(double.Parse(open[i].GetRawText()),3);
double h = Math.Round(double.Parse(high[i].GetRawText()),3);
double l = Math.Round(double.Parse(low[i].GetRawText()),3);
double c = Math.Round(double.Parse(close[i].GetRawText()),3);
double v = Math.Round(double.Parse(volume[i].GetRawText()),3);
base.Add(d, o, h, l, c, v);
}
}
}
+70
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@@ -0,0 +1,70 @@
namespace QuanTAlib;
using System;
/* <summary>
CORR: Pearson's Correlation Coefficient
PCC is a measure of linear correlation between two sets of data.
It is the ratio between the covariance of two variables and the product of
their standard deviations; it is essentially a normalized measurement of
the covariance, such that the result always has a value between 1 and 1.
Sources:
https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
</summary> */
public class CORR_Series : Pair_TSeries_Indicator
{
public CORR_Series(TSeries d1, TSeries d2, int period, bool useNaN = false) : base(d1, d2, period, useNaN)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
private readonly System.Collections.Generic.List<double> _x = new();
private readonly System.Collections.Generic.List<double> _xx = new();
private readonly System.Collections.Generic.List<double> _y = new();
private readonly System.Collections.Generic.List<double> _yy = new();
private readonly System.Collections.Generic.List<double> _xy = new();
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
if (update)
{
_x[_x.Count - 1] = TValue1.v;
_xx[_xx.Count - 1] = TValue1.v * TValue1.v;
_y[_y.Count - 1] = TValue2.v;
_y[_yy.Count - 1] = TValue2.v * TValue2.v;
_xy[_xy.Count - 1] = TValue1.v * TValue2.v;
}
else
{
_x.Add(TValue1.v);
_xx.Add(TValue1.v * TValue1.v);
_y.Add(TValue2.v);
_yy.Add(TValue2.v * TValue2.v);
_xy.Add(TValue1.v * TValue2.v);
}
if (_x.Count > this._p) { _x.RemoveAt(0); }
if (_xx.Count > this._p) { _xx.RemoveAt(0); }
if (_y.Count > this._p) { _y.RemoveAt(0); }
if (_yy.Count > this._p) { _yy.RemoveAt(0); }
if (_xy.Count > this._p) { _xy.RemoveAt(0); }
double _sumx = 0;
for (int i = 0; i < _x.Count; i++) { _sumx += _x[i]; }
double _sumxx = 0;
for (int i = 0; i < _xx.Count; i++) { _sumxx += _xx[i]; }
double _sumy = 0;
for (int i = 0; i < _y.Count; i++) { _sumy += _y[i]; }
double _sumyy = 0;
for (int i = 0; i < _yy.Count; i++) { _sumyy += _yy[i]; }
double _sumxy = 0;
for (int i = 0; i < _xy.Count; i++) { _sumxy += _xy[i]; }
double _div = (_sumxx - _sumx * _sumx / _p) * (_sumyy - _sumy * _sumy / _p);
double _cor = (_div != 0) ? (_sumxy - _sumx * _sumy / _p) / Math.Sqrt(_div) : 0.0;
var result = (TValue1.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _cor);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
+92 -92
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@@ -1,93 +1,93 @@
namespace QuanTAlib;
using System;
/* <summary>
LINREG: Linear Regression (using Least Square Method)
Linear Regression provides a slope of a straight line that is the best approximation of the given set of data.
The method of least squares is a standard approach in linear regression analysis to approximate the solution
by minimizing the sum of the squares of the residuals made in the results of each individual equation.
Additional outputs provided by LINREG:
.Intercept - y-intercept point of the best fit line
.RSquared - R-Squared (R²), Coefficient of Determination
.StdDev - Standard Deviation of data over given periods
y = Slope * x + Intercept
Sources:
https://en.wikipedia.org/wiki/Least_squares
</summary> */
public class LINREG_Series : Single_TSeries_Indicator
{
public readonly TSeries Intercept = new();
public readonly TSeries RSquared = new();
public readonly TSeries StdDev = new();
private readonly System.Collections.Generic.List<double> _buffer = new();
public LINREG_Series(TSeries source, int period, bool useNaN = false)
: base(source, period, useNaN)
{
if (this._data.Count > 0) { base.Add(this._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
else { this._buffer.Add(TValue.v); }
if (this._buffer.Count > this._p) { this._buffer.RemoveAt(0); }
int _len = this._buffer.Count;
// get averages for period
double sumX = 0;
double sumY = 0;
for (int p = 0; p < _len; p++)
{
sumX += this.Count - _len + 2 + p;
sumY += _buffer[p];
}
double avgX = sumX / _len;
double avgY = sumY / _len;
// least squares method
double sumSqX = 0;
double sumSqY = 0;
double sumSqXY = 0;
for (int p = 0; p < _len; p++)
{
double devX = this.Count - _len + 2 + p - avgX;
double devY = _buffer[p] - avgY;
sumSqX += devX * devX;
sumSqY += devY * devY;
sumSqXY += devX * devY;
}
double _slope = sumSqXY / sumSqX;
double _intercept = avgY - (_slope * avgX);
// calculate Standard Deviation and R-Squared
double stdDevX = Math.Sqrt(sumSqX / _len);
double stdDevY = Math.Sqrt(sumSqY / _len);
double _StdDev = stdDevY;
double arrr = (stdDevX * stdDevY != 0) ? sumSqXY / (stdDevX * stdDevY) / _len : 0;
double _RSquared = arrr * arrr;
var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _slope);
base.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _intercept);
Intercept.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _StdDev);
StdDev.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _RSquared);
RSquared.Add(ret, update);
}
namespace QuanTAlib;
using System;
/* <summary>
LINREG: Linear Regression (using Least Square Method)
Linear Regression provides a slope of a straight line that is the best approximation of the given set of data.
The method of least squares is a standard approach in linear regression analysis to approximate the solution
by minimizing the sum of the squares of the residuals made in the results of each individual equation.
Additional outputs provided by LINREG:
.Intercept - y-intercept point of the best fit line
.RSquared - R-Squared (R²), Coefficient of Determination
.StdDev - Standard Deviation of data over given periods
y = Slope * x + Intercept
Sources:
https://en.wikipedia.org/wiki/Least_squares
</summary> */
public class LINREG_Series : Single_TSeries_Indicator
{
public readonly TSeries Intercept = new();
public readonly TSeries RSquared = new();
public readonly TSeries StdDev = new();
private readonly System.Collections.Generic.List<double> _buffer = new();
public LINREG_Series(TSeries source, int period, bool useNaN = false)
: base(source, period, useNaN)
{
if (this._data.Count > 0) { base.Add(this._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
else { this._buffer.Add(TValue.v); }
if (this._buffer.Count > this._p) { this._buffer.RemoveAt(0); }
int _len = this._buffer.Count;
// get averages for period
double sumX = 0;
double sumY = 0;
for (int p = 0; p < _len; p++)
{
sumX += this.Count - _len + 2 + p;
sumY += _buffer[p];
}
double avgX = sumX / _len;
double avgY = sumY / _len;
// least squares method
double sumSqX = 0;
double sumSqY = 0;
double sumSqXY = 0;
for (int p = 0; p < _len; p++)
{
double devX = this.Count - _len + 2 + p - avgX;
double devY = _buffer[p] - avgY;
sumSqX += devX * devX;
sumSqY += devY * devY;
sumSqXY += devX * devY;
}
double _slope = sumSqXY / sumSqX;
double _intercept = avgY - (_slope * avgX);
// calculate Standard Deviation and R-Squared
double stdDevX = Math.Sqrt(sumSqX / _len);
double stdDevY = Math.Sqrt(sumSqY / _len);
double _StdDev = stdDevY;
double arrr = (stdDevX * stdDevY != 0) ? sumSqXY / (stdDevX * stdDevY) / _len : 0;
double _RSquared = arrr * arrr;
var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _slope);
base.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _intercept);
Intercept.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _StdDev);
StdDev.Add(ret, update);
ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _RSquared);
RSquared.Add(ret, update);
}
}
+50 -50
View File
@@ -1,51 +1,51 @@
namespace QuanTAlib;
using System;
/* <summary>
ZSCORE: number of standard deviations from SMA
Z-score describes a value's relationship to the mean of a series, as measured in
terms of standard deviations from the mean. If a Z-score is 0, it indicates that
the data point's score is identical to the mean score. A Z-score of 1.0 would
indicate a value that is one standard deviation from the mean. Z-scores may be
positive or negative, with a positive value indicating the score is above the
mean and a negative score indicating it is below the mean.
Sources:
https://en.wikipedia.org/wiki/Z-score
https://www.investopedia.com/terms/z/zscore.asp
Calculation:
std = std * STDEV(close, length)
mean = SMA(close, length)
ZSCORE = (close - mean) / std
</summary> */
public class ZSCORE_Series : Single_TSeries_Indicator
{
public ZSCORE_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
if (base._data.Count > 0) { base.Add(base._data); }
}
private readonly System.Collections.Generic.List<double> _buffer = new();
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
else { _buffer.Add(TValue.v); }
if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }
double _sma = 0;
for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; }
_sma /= this._buffer.Count;
double _pvar = 0;
for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
_pvar /= this._buffer.Count;
double _psdev = Math.Sqrt(_pvar);
double _zscore = (_psdev == 0) ? double.NaN : (TValue.v - _sma) / _psdev;
var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _zscore);
base.Add(result, update);
}
namespace QuanTAlib;
using System;
/* <summary>
ZSCORE: number of standard deviations from SMA
Z-score describes a value's relationship to the mean of a series, as measured in
terms of standard deviations from the mean. If a Z-score is 0, it indicates that
the data point's score is identical to the mean score. A Z-score of 1.0 would
indicate a value that is one standard deviation from the mean. Z-scores may be
positive or negative, with a positive value indicating the score is above the
mean and a negative score indicating it is below the mean.
Sources:
https://en.wikipedia.org/wiki/Z-score
https://www.investopedia.com/terms/z/zscore.asp
Calculation:
std = std * STDEV(close, length)
mean = SMA(close, length)
ZSCORE = (close - mean) / std
</summary> */
public class ZSCORE_Series : Single_TSeries_Indicator
{
public ZSCORE_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
if (base._data.Count > 0) { base.Add(base._data); }
}
private readonly System.Collections.Generic.List<double> _buffer = new();
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
else { _buffer.Add(TValue.v); }
if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }
double _sma = 0;
for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; }
_sma /= this._buffer.Count;
double _pvar = 0;
for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
_pvar /= this._buffer.Count;
double _psdev = Math.Sqrt(_pvar);
double _zscore = (_psdev == 0) ? double.NaN : (TValue.v - _sma) / _psdev;
var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _zscore);
base.Add(result, update);
}
}
+301 -292
View File
@@ -5,296 +5,305 @@ using Xunit;
namespace Validations;
public class Skender_Stock
{
private readonly GBM_Feed bars;
private readonly Random rnd = new();
private readonly int period;
private readonly IEnumerable<Quote> quotes;
public Skender_Stock()
{
bars = new(Bars: 5000, Volatility: 0.7, Drift: 0.0);
period = rnd.Next(28) + 3;
quotes = bars.Select(
q => new Quote
{
Date = q.t,
Open = (decimal)q.o,
High = (decimal)q.h,
Low = (decimal)q.l,
Close = (decimal)q.c,
Volume = (decimal)q.v
});
}
[Fact]
public void SMA()
{
SMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSma(period);
Assert.Equal(Math.Round((double)SK.Last().Sma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void EMA()
{
EMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetEma(period);
Assert.Equal(Math.Round((double)SK.Last().Ema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void WMA()
{
WMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetWma(period);
Assert.Equal(Math.Round((double)SK.Last().Wma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void DEMA()
{
DEMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetDema(period);
Assert.Equal(Math.Round((double)SK.Last().Dema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void TEMA()
{
TEMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetTema(period);
Assert.Equal(Math.Round((double)SK.Last().Tema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MAD()
{
MAD_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mad!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MSE()
{
MSE_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mse!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MAPE()
{
MAPE_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mape!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ATR()
{
ATR_Series QL = new(bars, period, false);
var SK = quotes.GetAtr(period);
Assert.Equal(Math.Round((double)SK.Last().Atr!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OBV()
{
OBV_Series QL = new(bars, period, false);
var SK = quotes.GetObv(period);
// adding volume[0] to OBV to pass the test and keep compatibility with TA-LIB
Assert.Equal(Math.Round(SK.Last().Obv! + (double)quotes.First().Volume!, 5),
Math.Round(QL.Last().v, 5));
}
[Fact]
public void ADL()
{
ADL_Series QL = new(bars, false);
var SK = quotes.GetAdl();
Assert.Equal(Math.Round(SK.Last().Adl!, 5), Math.Round(QL.Last().v, 5));
}
[Fact]
public void CCI()
{
CCI_Series QL = new(bars, period, false);
var SK = quotes.GetCci(period);
Assert.Equal(Math.Round((double)SK.Last().Cci!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ATRP()
{
ATRP_Series QL = new(bars, period, false);
var SK = quotes.GetAtr(period);
Assert.Equal(Math.Round((double)SK.Last().Atrp!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void KAMA()
{
KAMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetKama(period);
Assert.Equal(Math.Round((double)SK.Last().Kama!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HMA()
{
HMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetHma(period);
Assert.Equal(Math.Round((double)SK.Last().Hma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void SMMA()
{
SMMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetSmma(period);
Assert.Equal(Math.Round((double)SK.Last().Smma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MACD()
{
MACD_Series QL = new(bars.Close, 26, 12, 9, useNaN: false);
var SK = quotes.GetMacd(12, 26, 9);
Assert.Equal(Math.Round((double)SK.Last().Macd!, 6), Math.Round(QL.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Signal!, 6), Math.Round(QL.Signal.Last().v, 6));
}
[Fact]
public void BBANDS()
{
BBANDS_Series QL = new(bars.Close, period, 2.0, useNaN: false);
var SK = quotes.GetBollingerBands(period, 2.0);
Assert.Equal(Math.Round((double)SK.Last().Sma!, 6), Math.Round(QL.Mid.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().UpperBand!, 6), Math.Round(QL.Upper.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().LowerBand!, 6), Math.Round(QL.Lower.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Width!, 6), Math.Round(QL.Bandwidth.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().PercentB!, 6), Math.Round(QL.PercentB.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().ZScore!, 6), Math.Round(QL.Zscore.Last().v, 6));
}
[Fact]
public void RSI()
{
RSI_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetRsi(period);
Assert.Equal(Math.Round((double)SK.Last().Rsi!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ALMA()
{
ALMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetAlma(period);
Assert.Equal(Math.Round((double)SK.Last().Alma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void SDEV()
{
SDEV_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetStdDev(period);
Assert.Equal(Math.Round((double)SK.Last().StdDev!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ZSCORE()
{
ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetStdDev(period);
Assert.Equal(Math.Round((double)SK.Last().ZScore!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void LINREG()
{
LINREG_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetSlope(period);
Assert.Equal(Math.Round((double)SK.Last().Slope!, 6), Math.Round(QL.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Intercept!, 6), Math.Round(QL.Intercept.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().RSquared!, 6), Math.Round(QL.RSquared.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().StdDev!, 6), Math.Round(QL.StdDev.Last().v, 6));
}
[Fact]
public void TR()
{
TR_Series QL = new(bars, useNaN: false);
var SK = quotes.GetTr();
Assert.Equal(Math.Round((double)SK.Last().Tr!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HL2()
{
TSeries QL = bars.HL2;
var SK = quotes.GetBaseQuote(CandlePart.HL2);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OC2()
{
TSeries QL = bars.OC2;
var SK = quotes.GetBaseQuote(CandlePart.OC2);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HLC3()
{
TSeries QL = bars.HLC3;
var SK = quotes.GetBaseQuote(CandlePart.HLC3);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OHL3()
{
TSeries QL = bars.OHL3;
var SK = quotes.GetBaseQuote(CandlePart.OHL3);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OHLC4()
{
TSeries QL = bars.OHLC4;
var SK = quotes.GetBaseQuote(CandlePart.OHLC4);
Assert.Equal(Math.Round((double)SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
{
private readonly GBM_Feed bars;
private readonly Random rnd = new();
private readonly int period;
private readonly IEnumerable<Quote> quotes;
public Skender_Stock()
{
bars = new(Bars: 5000, Volatility: 0.7, Drift: 0.0);
period = rnd.Next(28) + 3;
quotes = bars.Select(
q => new Quote
{
Date = q.t,
Open = (decimal)q.o,
High = (decimal)q.h,
Low = (decimal)q.l,
Close = (decimal)q.c,
Volume = (decimal)q.v
});
}
[Fact]
public void SMA()
{
SMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSma(period);
Assert.Equal(Math.Round((double)SK.Last().Sma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void EMA()
{
EMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetEma(period);
Assert.Equal(Math.Round((double)SK.Last().Ema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void WMA()
{
WMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetWma(period);
Assert.Equal(Math.Round((double)SK.Last().Wma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void DEMA()
{
DEMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetDema(period);
Assert.Equal(Math.Round((double)SK.Last().Dema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void TEMA()
{
TEMA_Series QL = new(bars.Close, period, false);
var SK = quotes.GetTema(period);
Assert.Equal(Math.Round((double)SK.Last().Tema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MAD()
{
MAD_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mad!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MSE()
{
MSE_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mse!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MAPE()
{
MAPE_Series QL = new(bars.Close, period, false);
var SK = quotes.GetSmaAnalysis(period);
Assert.Equal(Math.Round((double)SK.Last().Mape!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void CORR()
{
CORR_Series QL = new(bars.High, bars.Low, period, false);
var SK = quotes.Use(CandlePart.High).GetCorrelation(quotes.Use(CandlePart.Low), period);
Assert.Equal(Math.Round((double)SK.Last().Correlation!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ATR()
{
ATR_Series QL = new(bars, period, false);
var SK = quotes.GetAtr(period);
Assert.Equal(Math.Round((double)SK.Last().Atr!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OBV()
{
OBV_Series QL = new(bars, period, false);
var SK = quotes.GetObv(period);
// adding volume[0] to OBV to pass the test and keep compatibility with TA-LIB
Assert.Equal(Math.Round(SK.Last().Obv! + (double)quotes.First().Volume!, 5),
Math.Round(QL.Last().v, 5));
}
[Fact]
public void ADL()
{
ADL_Series QL = new(bars, false);
var SK = quotes.GetAdl();
Assert.Equal(Math.Round(SK.Last().Adl!, 5), Math.Round(QL.Last().v, 5));
}
[Fact]
public void CCI()
{
CCI_Series QL = new(bars, period, false);
var SK = quotes.GetCci(period);
Assert.Equal(Math.Round((double)SK.Last().Cci!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ATRP()
{
ATRP_Series QL = new(bars, period, false);
var SK = quotes.GetAtr(period);
Assert.Equal(Math.Round((double)SK.Last().Atrp!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void KAMA()
{
KAMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetKama(period);
Assert.Equal(Math.Round((double)SK.Last().Kama!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HMA()
{
HMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetHma(period);
Assert.Equal(Math.Round((double)SK.Last().Hma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void SMMA()
{
SMMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetSmma(period);
Assert.Equal(Math.Round((double)SK.Last().Smma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MACD()
{
MACD_Series QL = new(bars.Close, 26, 12, 9, useNaN: false);
var SK = quotes.GetMacd(12, 26, 9);
Assert.Equal(Math.Round((double)SK.Last().Macd!, 6), Math.Round(QL.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Signal!, 6), Math.Round(QL.Signal.Last().v, 6));
}
[Fact]
public void BBANDS()
{
BBANDS_Series QL = new(bars.Close, period, 2.0, useNaN: false);
var SK = quotes.GetBollingerBands(period, 2.0);
Assert.Equal(Math.Round((double)SK.Last().Sma!, 6), Math.Round(QL.Mid.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().UpperBand!, 6), Math.Round(QL.Upper.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().LowerBand!, 6), Math.Round(QL.Lower.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Width!, 6), Math.Round(QL.Bandwidth.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().PercentB!, 6), Math.Round(QL.PercentB.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().ZScore!, 6), Math.Round(QL.Zscore.Last().v, 6));
}
[Fact]
public void RSI()
{
RSI_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetRsi(period);
Assert.Equal(Math.Round((double)SK.Last().Rsi!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ALMA()
{
ALMA_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetAlma(period);
Assert.Equal(Math.Round((double)SK.Last().Alma!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void SDEV()
{
SDEV_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetStdDev(period);
Assert.Equal(Math.Round((double)SK.Last().StdDev!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void ZSCORE()
{
ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetStdDev(period);
Assert.Equal(Math.Round((double)SK.Last().ZScore!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void LINREG()
{
LINREG_Series QL = new(bars.Close, period, useNaN: false);
var SK = quotes.GetSlope(period);
Assert.Equal(Math.Round((double)SK.Last().Slope!, 6), Math.Round(QL.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().Intercept!, 6), Math.Round(QL.Intercept.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().RSquared!, 6), Math.Round(QL.RSquared.Last().v, 6));
Assert.Equal(Math.Round((double)SK.Last().StdDev!, 6), Math.Round(QL.StdDev.Last().v, 6));
}
[Fact]
public void TR()
{
TR_Series QL = new(bars, useNaN: false);
var SK = quotes.GetTr();
Assert.Equal(Math.Round((double)SK.Last().Tr!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HL2()
{
TSeries QL = bars.HL2;
var SK = quotes.GetBaseQuote(CandlePart.HL2);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OC2()
{
TSeries QL = bars.OC2;
var SK = quotes.GetBaseQuote(CandlePart.OC2);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void HLC3()
{
TSeries QL = bars.HLC3;
var SK = quotes.GetBaseQuote(CandlePart.HLC3);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OHL3()
{
TSeries QL = bars.OHL3;
var SK = quotes.GetBaseQuote(CandlePart.OHL3);
Assert.Equal(Math.Round(SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void OHLC4()
{
TSeries QL = bars.OHLC4;
var SK = quotes.GetBaseQuote(CandlePart.OHLC4);
Assert.Equal(Math.Round((double)SK.Last().Value!, 6), Math.Round(QL.Last().v, 6));
}
}
+310 -301
View File
@@ -5,305 +5,314 @@ using QuanTAlib;
namespace Validations;
public class TA_LIB
{
private readonly GBM_Feed bars;
private readonly Random rnd = new();
private readonly int period;
private readonly double[] TALIB;
private readonly double[] inopen;
private readonly double[] inhigh;
private readonly double[] inlow;
private readonly double[] inclose;
private readonly double[] involume;
public TA_LIB()
{
bars = new(5000);
period = rnd.Next(28) + 3;
TALIB = new double[bars.Count];
inopen = bars.Open.v.ToArray();
inhigh = bars.High.v.ToArray();
inlow = bars.Low.v.ToArray();
inclose = bars.Close.v.ToArray();
involume = bars.Volume.v.ToArray();
}
/////////////////////////////////////////
[Fact]
public void ADD()
{
ADD_Series QL = new(bars.Open, bars.Close);
Core.Add(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SUB()
{
SUB_Series QL = new(bars.Open, bars.Close);
Core.Sub(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MUL()
{
MUL_Series QL = new(bars.Open, bars.Close);
Core.Mult(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void DIV()
{
DIV_Series QL = new(bars.Open, bars.Close);
Core.Div(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SDEV()
{
SDEV_Series QL = new(bars.Close, period, false);
Core.StdDev(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SMA()
{
SMA_Series QL = new(bars.Close, period, false);
Core.Sma(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SUM()
{
SUM_Series QL = new(bars.Close, period, false);
Core.Sum(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MIDPRICE()
{
MIDPRICE_Series QL = new(bars, period, false);
Core.MidPrice(inhigh, inlow, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void VAR()
{
VAR_Series QL = new(bars.Close, period, false);
Core.Var(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 5, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 5));
}
[Fact]
public void MIDPOINT()
{
MIDPOINT_Series QL = new(bars.Close, period, false);
Core.MidPoint(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TRIMA()
{
TRIMA_Series QL = new(bars.Close, period, false);
Core.Trima(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void EMA()
{
EMA_Series QL = new(bars.Close, period, false);
Core.Ema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void WMA()
{
WMA_Series QL = new(bars.Close, period, false);
Core.Wma(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void DEMA()
{
DEMA_Series QL = new(bars.Close, period, false);
Core.Dema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TEMA()
{
TEMA_Series QL = new(bars.Close, period, false);
Core.Tema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MAX()
{
MAX_Series QL = new(bars.Close, period, false);
Core.Max(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MIN()
{
MIN_Series QL = new(bars.Close, period, false);
Core.Min(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ADL()
{
ADL_Series QL = new(bars, false);
Core.Ad(inhigh, inlow, inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void OBV()
{
OBV_Series QL = new(bars, period, false);
Core.Obv(inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ADOSC()
{
ADOSC_Series QL = new(bars, false);
Core.AdOsc(inhigh, inlow, inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ATR()
{
ATR_Series QL = new(bars, period, false);
Core.Atr(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void CCI()
{
CCI_Series QL = new(bars, period, false);
Core.Cci(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void RSI()
{
RSI_Series QL = new(bars.Close, period, false);
Core.Rsi(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TR()
{
TR_Series QL = new(bars, false);
Core.TRange(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MACD()
{
double[] macdSignal = new double[bars.Count];
double[] macdHist = new double[bars.Count];
MACD_Series QL = new(bars.Close, slow: 26, fast: 12, signal: 9, false);
Core.Macd(inclose, 0, bars.Count - 1, outMacd: TALIB, outMacdSignal: macdSignal, outMacdHist: macdHist, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(macdSignal[macdSignal.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Signal.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void BBANDS()
{
double[] outMiddle = new double[bars.Count];
double[] outUpper = new double[bars.Count];
double[] outLower = new double[bars.Count];
BBANDS_Series QL = new(bars.Close, period: 26, multiplier: 2.0, false);
Core.Bbands(inclose, 0, bars.Count - 1, outRealUpperBand: outUpper, outRealMiddleBand: outMiddle, outRealLowerBand: outLower, out int outBegIdx, out _, optInTimePeriod: 26, optInNbDevUp: 2.0, optInNbDevDn: 2.0);
Assert.Equal(Math.Round(outUpper[outUpper.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Upper.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Mid.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Lower.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HL2()
{
TSeries QL = bars.HL2;
Core.MedPrice(inhigh, inlow, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HLC3()
{
TSeries QL = bars.HLC3;
Core.TypPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void OHLC4()
{
TSeries QL = bars.OHLC4;
Core.AvgPrice(inopen, inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HLCC4()
{
TSeries QL = bars.HLCC4;
Core.WclPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
{
private readonly GBM_Feed bars;
private readonly Random rnd = new();
private readonly int period;
private readonly double[] TALIB;
private readonly double[] inopen;
private readonly double[] inhigh;
private readonly double[] inlow;
private readonly double[] inclose;
private readonly double[] involume;
public TA_LIB()
{
bars = new(5000);
period = rnd.Next(28) + 3;
TALIB = new double[bars.Count];
inopen = bars.Open.v.ToArray();
inhigh = bars.High.v.ToArray();
inlow = bars.Low.v.ToArray();
inclose = bars.Close.v.ToArray();
involume = bars.Volume.v.ToArray();
}
/////////////////////////////////////////
[Fact]
public void ADD()
{
ADD_Series QL = new(bars.Open, bars.Close);
Core.Add(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SUB()
{
SUB_Series QL = new(bars.Open, bars.Close);
Core.Sub(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MUL()
{
MUL_Series QL = new(bars.Open, bars.Close);
Core.Mult(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void DIV()
{
DIV_Series QL = new(bars.Open, bars.Close);
Core.Div(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void CORR()
{
CORR_Series QL = new(bars.Open, bars.Close, period);
Core.Correl(inopen, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, optInTimePeriod: period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SDEV()
{
SDEV_Series QL = new(bars.Close, period, false);
Core.StdDev(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SMA()
{
SMA_Series QL = new(bars.Close, period, false);
Core.Sma(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void SUM()
{
SUM_Series QL = new(bars.Close, period, false);
Core.Sum(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MIDPRICE()
{
MIDPRICE_Series QL = new(bars, period, false);
Core.MidPrice(inhigh, inlow, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void VAR()
{
VAR_Series QL = new(bars.Close, period, false);
Core.Var(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 5, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 5));
}
[Fact]
public void MIDPOINT()
{
MIDPOINT_Series QL = new(bars.Close, period, false);
Core.MidPoint(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TRIMA()
{
TRIMA_Series QL = new(bars.Close, period, false);
Core.Trima(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void EMA()
{
EMA_Series QL = new(bars.Close, period, false);
Core.Ema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void WMA()
{
WMA_Series QL = new(bars.Close, period, false);
Core.Wma(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void DEMA()
{
DEMA_Series QL = new(bars.Close, period, false);
Core.Dema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TEMA()
{
TEMA_Series QL = new(bars.Close, period, false);
Core.Tema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MAX()
{
MAX_Series QL = new(bars.Close, period, false);
Core.Max(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MIN()
{
MIN_Series QL = new(bars.Close, period, false);
Core.Min(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ADL()
{
ADL_Series QL = new(bars, false);
Core.Ad(inhigh, inlow, inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void OBV()
{
OBV_Series QL = new(bars, period, false);
Core.Obv(inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ADOSC()
{
ADOSC_Series QL = new(bars, false);
Core.AdOsc(inhigh, inlow, inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void ATR()
{
ATR_Series QL = new(bars, period, false);
Core.Atr(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void CCI()
{
CCI_Series QL = new(bars, period, false);
Core.Cci(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void RSI()
{
RSI_Series QL = new(bars.Close, period, false);
Core.Rsi(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TR()
{
TR_Series QL = new(bars, false);
Core.TRange(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void MACD()
{
double[] macdSignal = new double[bars.Count];
double[] macdHist = new double[bars.Count];
MACD_Series QL = new(bars.Close, slow: 26, fast: 12, signal: 9, false);
Core.Macd(inclose, 0, bars.Count - 1, outMacd: TALIB, outMacdSignal: macdSignal, outMacdHist: macdHist, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(macdSignal[macdSignal.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Signal.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void BBANDS()
{
double[] outMiddle = new double[bars.Count];
double[] outUpper = new double[bars.Count];
double[] outLower = new double[bars.Count];
BBANDS_Series QL = new(bars.Close, period: 26, multiplier: 2.0, false);
Core.Bbands(inclose, 0, bars.Count - 1, outRealUpperBand: outUpper, outRealMiddleBand: outMiddle, outRealLowerBand: outLower, out int outBegIdx, out _, optInTimePeriod: 26, optInNbDevUp: 2.0, optInNbDevDn: 2.0);
Assert.Equal(Math.Round(outUpper[outUpper.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Upper.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Mid.Last().v, 6, MidpointRounding.AwayFromZero));
Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Lower.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HL2()
{
TSeries QL = bars.HL2;
Core.MedPrice(inhigh, inlow, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HLC3()
{
TSeries QL = bars.HLC3;
Core.TypPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void OHLC4()
{
TSeries QL = bars.OHLC4;
Core.AvgPrice(inopen, inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void HLCC4()
{
TSeries QL = bars.HLCC4;
Core.WclPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
}
+2 -2
View File
@@ -55,7 +55,7 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|||||
| **STATISTICS & NUMERICAL ANALYSIS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⭐ BIAS - Bias | `BIAS_Series` ||| bias |
| CORREL - Pearson's Correlation Coefficient || CORREL | GetCorrelation ||
| CORR - Pearson's Correlation Coefficient | `CORR_Series` | CORREL | GetCorrelation ||
| ⛔ COVAR - Covariance ||| GetCorrelation ||
| ⭐ ENTP - Entropy | `ENTP_Series` ||| entropy |
| ⭐ KURT - Kurtosis | `KURT_Series` ||| kurtosis |
@@ -72,7 +72,7 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
| ⭐ SVAR - Sample Variance | `SVAR_Series` ||| variance |
| ⛔ QUANTILE - Quantile |||| quantile |
| ✔️ WMAPE - Weighted Mean Absolute Percent Error | `WMAPE_Series` ||||
| ⭐ ZSCORE - Number of standard deviations from mean | ZSCORE_Series || GetStdDev | zscore |
| ⭐ ZSCORE - Number of standard deviations from mean | `ZSCORE_Series` || GetStdDev | zscore |
||||||
| **TREND INDICATORS & AVERAGES** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⛔ AFIRMA - Autoregressive Finite Impulse Response Moving Average |||||