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Miha Kralj
2022-11-15 21:26:58 -08:00
parent 5c988bdbc8 73b41ac0a0
commit fd2a686ba5
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@@ -1,355 +1,356 @@
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GitVersion.yml
+2 -1
View File
@@ -1,3 +1,4 @@
next-version: 0.1.19
minor-version-bump-message: \+semver:\s?(feature|new)
branches:
main:
@@ -11,6 +12,6 @@ branches:
regex: ^dev(elop)?(ment)?$
is-release-branch: false
mode: ContinuousDelivery
tag: 'v'
tag: 'nightly'
increment: Inherit
update-build-number: true
Source/Basics/Abstracts.cs
+15 -2
View File
@@ -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;
Source/Feeds/Yahoo_Feed.cs
+46 -53
View File
@@ -1,54 +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;
JsonElement json = new();
JsonElement datetime = new();
JsonElement open = new();
JsonElement high = new();
JsonElement low = new();
JsonElement close = new();
JsonElement volume = new();
jresult.TryGetProperty("chart",out json);
json.TryGetProperty("result",out json);
json[0].TryGetProperty("timestamp",out datetime);
json[0].TryGetProperty("indicators",out json);
json.TryGetProperty("quote",out json);
json[0].TryGetProperty("open",out open);
json[0].TryGetProperty("high",out high);
json[0].TryGetProperty("low",out low);
json[0].TryGetProperty("close",out close);
json[0].TryGetProperty("volume",out 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);
}
}
}
Source/QuanTAlib.csproj
+7 -2
View File
@@ -51,7 +51,11 @@
<PackageIcon>QuanTAlib2.png</PackageIcon>
<PackageIconUrl>https://raw.githubusercontent.com/mihakralj/QuanTAlib/main/.github/QuanTAlib2.png</PackageIconUrl>
<EnforceCodeStyleInBuild>True</EnforceCodeStyleInBuild>
<CodeAnalysisRuleSet>..\.sonarlint\mihakralj_quantalibcsharp.ruleset</CodeAnalysisRuleSet>
</PropertyGroup>
<ItemGroup>
<AdditionalFiles Include="..\.sonarlint\mihakralj_quantalib\CSharp\SonarLint.xml" Link="SonarLint.xml" />
</ItemGroup>
<ItemGroup>
<None Include="..\Docs\readme.md">
<Pack>True</Pack>
@@ -64,10 +68,11 @@
</None>
</ItemGroup>
<ItemGroup>
<PackageReference Include="System.Text.Json" Version="7.0.0" />
<PackageReference Include="GitVersion.MsBuild" Version="5.11.1">
<PrivateAssets>All</PrivateAssets>
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="System.Text.Json" Version="7.0.0" />
</ItemGroup>
</Project>
Source/Statistics/CORR_Series.cs
+70
View File
@@ -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); }
}
}
Source/Statistics/LINREG_Series.cs
+92 -95
View File
@@ -1,96 +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 TSeries Intercept { get; }
public TSeries RSquared { get; }
public TSeries StdDev { get; }
private readonly System.Collections.Generic.List<double> _buffer = new();
public LINREG_Series(TSeries source, int period, bool useNaN = false)
: base(source, period, useNaN)
{
this.Intercept = new();
this.RSquared = new();
this.StdDev = new();
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);
}
}
Source/Statistics/ZSCORE_Series.cs
+51
View File
@@ -0,0 +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);
}
}
Tests/Validations/Pandas_TA.cs
+31 -6
View File
@@ -57,8 +57,9 @@ public class PandasTA : IDisposable
public void Dispose()
{
PythonEngine.Shutdown();
}
PythonEngine.Shutdown();
GC.SuppressFinalize(this);
}
[Fact]
void HL2()
@@ -191,10 +192,34 @@ public class PandasTA : IDisposable
{
TEMA_Series QL = new(bars.Close, period, false);
var pta = df.ta.tema(close: df.close, length: period);
Assert.Equal(Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
}
[Fact]
Assert.Equal(Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
}
[Fact]
void SDEV()
{
SDEV_Series QL = new(bars.Close, period, useNaN: false);
var pta = df.ta.stdev(close: df.close, length: period, ddof: 0);
Assert.Equal(Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
}
[Fact]
void SSDEV()
{
SSDEV_Series QL = new(bars.Close, period, useNaN: false);
var pta = df.ta.stdev(close: df.close, length: period, ddof: 1);
Assert.Equal(Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
}
[Fact]
void ZSCORE()
{
ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
var pta = df.ta.zscore(close: df.close, length: period, ddof: 0);
Assert.Equal(Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
}
[Fact]
void ENTP()
{
ENTP_Series QL = new(bars.Close, period, useNaN: false);
Tests/Validations/Skender_Stock.cs
+301 -274
View File
@@ -5,278 +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 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((double)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 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((double)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((double)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((double)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((double)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));
}
}
Tests/Validations/TA_LIB.cs
+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));
}
}
docs/.md
-87
View File
@@ -1,87 +0,0 @@
## 1. Prepare the Peloton tablet
Stop Peloton overlay app:
- tap on Settings in the top right corner and select Device Settings
- tap Apps and scroll down to find and tap Peloton app (not Peloton Launcher, just Peloton)
- tap FORCE STOP to stop the app overlay
- confrm by tapping OK
Turn on developer mode
- return to Settings page
- tap About tablet in System section
- tap Build number repeatedly until you activate developer mode
Enable USB debugging
- return to Settings page
- tap (now visible) Developer options in System section
- scroll down to find USB Debugging option
- Enable USB debugging
- Confirm by tapping OK
## 3. Prepare the PC with Zwift/Rouvy
- Create your Splashtop account https://my.splashtop.com/login
- Download and install Splashtop Streamer https://www.splashtop.com/downloads#pers
- Download Android Platform Tools https://developer.android.com/studio/releases/platform-tools
- Download Nova launcher APK (or any other launcher that works on Android 7) https://apkpure.com/nova-launcher/com.teslacoilsw.launcher/download/62019-APK
- Download Splashtop APK https://apkpure.com/splashtop-personal-access/com.splashtop.remote.pad.v2
- Unzip Android tools into a new folder
- move both APKs to the same folder
- Run Command Prompt (CMD) and move to the same folder
- Launch Android Debuging Bridge: adb start-server
- Connect PC and Peloton tablet with USB cable
- Peloton tablet will check for confirmation; Accept debugging over USB
- Verify connectivity on PC in the Command window: adb devices
## 4. Side-load APKs
- Execute the following three commands on PC:
adb shell settings put secure install_non_market_apps 1
adb install <name_of_nova_launcher.apk>
adb install <name_of_splashtop.apk>
- Disconnect USB cable
- On Peloton tablet tap Peloton 'P' logo at the bottom
- Select Nova as a default launcher
- Accept all defaults for Nova launcher - you can customize it later
- (optional) Bring Peloton and Splashtop icons to the main page of Nova launcher
- Choosing Peloton launches Peloton app; Choosing Splashtop launches Splashtop app
- Swiping down from the top of the screen reveals the hidden 'P' launcher button
## 5. Connect Peloton tablet and PC
- Launch Splashtop app on Peloton tablet
- Login with Splashtop credentials
- Connect to PC that runs Splashtop streamer (and Zwift/Rouvy)
- Launch Zwift/Rouvy
## 5. Enable sensors
- (optional): buy ANT+ USB dongle https://www.amazon.com/s?k=ant%2B+USB+stick
Peloton Tread:
Speed: Runn https://npe-inc.com/runn-smart-treadmill-sensor-2/
(or Stryd https://www.stryd.com/us/en)
Cadence: Garmin foodpod (or Stryd)
Heartrate: any HR monitor (BT or ANT+) https://www.amazon.com/s?k=bluetooth+HR+monitor
Power: Stryd
Peloton Bike (gen1):
Power & Cadence: DFC (Data Fitness Connector) https://www.crowdsupply.com/intelligenate/data-fitness-connector
Heartrate:vany HR monitor (BT or ANT+)
## 6. Navigation
Nova is now a default launcher on Android tablet, but on Tread we need to run Peloton app in the background to prevent locking of treadmill:
- Launch Peloton app
- Swipe down from the top and return to Nova launcher
- Launch Splashtop app
- Connect to PC
- Launch Zwift or Rouvy
- Connect all sensors
- Run/Ride!
docs/readme.md
+29 -29
View File
@@ -38,13 +38,13 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|--|:--:|:--:|:--:|:--:|
| ⭐ OC2 - (Open+Close)/2 |️ `.OC2` || CandlePart.OC2 ||
| ⭐ HL2 - Median Price | `.HL2` | MEDPRICE | CandlePart.HL2 ||
| ⭐ HLC3 - Typical Price | `.HLC3` | TYPPRICE | CandlePart.HLC3 ||
| ⭐ HL2 - Median Price | `.HL2` | MEDPRICE | CandlePart.HL2 | hl2 |
| ⭐ HLC3 - Typical Price | `.HLC3` | TYPPRICE | CandlePart.HLC3 | hlc3 |
| ⭐ OHL3 - (Open+High+Low)/3 | `.OHL3` || CandlePart.OHL3 ||
| ⭐ OHLC4 - Average Price | `.OHLC4` | AVGPRICE |️ CandlePart.OHLC4 ||
| ⭐ OHLC4 - Average Price | `.OHLC4` | AVGPRICE |️ CandlePart.OHLC4 | ohlc4 |
| ⭐ HLCC4 - Weighted Price | `.HLCC4` | WCLPRICE | CandlePart.HLCC4 ||
| ⭐ MIDPOINT - Midpoint value | `MIDPOINT_Series` | MIDPOINT |||
| ⭐ MIDPRICE - Midpoint price | `MIDPRICE_Series` | MIDPRICE |||
| ⭐ MIDPOINT - Midpoint value | `MIDPOINT_Series` | MIDPOINT || midpoint |
| ⭐ MIDPRICE - Midpoint price | `MIDPRICE_Series` | MIDPRICE || midprice |
| ⭐ MAX - Max value | `MAX_Series` | MAX |||
| ⭐ MIN - Min value | `MIN_Series` | MIN |||
| ⭐ SUM - Summation | `SUM_Series` | SUM |||
@@ -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 |
@@ -63,54 +63,54 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
| ⭐ MAD - Mean Absolute Deviation | `MAD_Series` || GetSma | mad |
| ⭐ MAPE - Mean Absolute Percent Error | `MAPE_Series` || GetSma ||
| ⭐ MED - Median value | `MED_Series` ||| median |
| ✔️ MSE - Mean Squared Error | `MSE_Series` || GetSma ||
| ⛔ SKEW - Skewness |||||
| ⭐ SDEV - Standard Deviation (Volatility) | `SDEV_Series` | STDDEV |||
| ✔️ SSDEV - Sample Standard Deviation | `SSDEV_Series` ||||
| ⭐ MSE - Mean Squared Error | `MSE_Series` || GetSma ||
| ⛔ SKEW - Skewness |||| skew |
| ⭐ SDEV - Standard Deviation (Volatility) | `SDEV_Series` | STDDEV | GetStdDev | stdev |
| ⭐ SSDEV - Sample Standard Deviation | `SSDEV_Series` ||| stdev |
| ✔️ SMAPE - Symmetric Mean Absolute Percent Error | `SMAPE_Series` ||||
| ⭐ VAR - Population Variance | `VAR_Series` | VAR || variance |
| ⭐ SVAR - Sample Variance | `SVAR_Series` ||| variance |
| ⛔ QUANT - Quantile |||||
| ⛔ QUANTILE - Quantile |||| quantile |
| ✔️ WMAPE - Weighted Mean Absolute Percent Error | `WMAPE_Series` ||||
| ⛔ ZSCORE - Number of standard deviations from mean |||||
| ⭐ 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 |||||
| ⭐ ALMA - Arnaud Legoux Moving Average | `ALMA_Series` || GetAlma ||
| ⭐ ALMA - Arnaud Legoux Moving Average | `ALMA_Series` || GetAlma | alma |
| ⛔ ARIMA - Autoregressive Integrated Moving Average |||||
| ⭐ DEMA - Double EMA Average | `DEMA_Series` | DEMA | GetDema | dema |
| ⭐ EMA - Exponential Moving Average | `EMA_Series` || GetEma | ema |
| ⛔ EPMA - Endpoint Moving Average ||| GetEpma ||
| ⛔ FRAMA - Fractal Adaptive Moving Average |||||
| ⛔ FWMA - Fibonacci's Weighted Moving Average |||||
| ⛔ HILO - Gann High-Low Activator |||||
| ⛔ FWMA - Fibonacci's Weighted Moving Average |||| fwma |
| ⛔ HILO - Gann High-Low Activator |||| hilo |
| ✔️ HEMA - Hull/EMA Average | `HEMA_Series` ||||
| ⛔ Hilbert Transform Instantaneous Trendline || HT_TRENDLINE | GetHtTrendline ||
| ⭐ HMA - Hull Moving Average | `HMA_Series` || GetHma | hma |
| ⛔ HWMA - Holt-Winter Moving Average |||||
| ✔️ JMA - Jurik Moving Average | `JMA_Series` ||||
| ⛔ HWMA - Holt-Winter Moving Average |||| hwma |
| ✔️ JMA - Jurik Moving Average | `JMA_Series` ||| jma |
| ⭐ KAMA - Kaufman's Adaptive Moving Average | `KAMA_Series` | KAMA | GetKama | kama |
| ⛔ KDJ - KDJ Indicator (trend reversal) |||||
| ⛔ KDJ - KDJ Indicator (trend reversal) |||| kdj |
| ⛔ LSMA - Least Squares Moving Average |||||
| ⭐ MACD - Moving Average Convergence/Divergence | `MACD_Series` | MACD | GetMacd ||
| ⭐ MACD - Moving Average Convergence/Divergence | `MACD_Series` | MACD | GetMacd | macd |
| ⛔ MAMA - MESA Adaptive Moving Average || MAMA | GetMama ||
| ⛔ MCGD - McGinley Dynamic |||||
| ⛔ MCGD - McGinley Dynamic |||| mcgd |
| ⛔ MMA - Modified Moving Average |||||
| ⛔ PPMA - Pivot Point Moving Average |||||
| ⛔ PWMA - Pascal's Weighted Moving Average |||||
| ⛔ PWMA - Pascal's Weighted Moving Average |||| pwma |
| ⭐ RMA - WildeR's Moving Average | `RMA_Series` ||| rma |
| ⛔ SINWMA - Sine Weighted Moving Average |||||
| ⛔ SINWMA - Sine Weighted Moving Average |||| sinwma |
| ⭐ SMA - Simple Moving Average | `SMA_Series` | SMA | GetSma | sma |
| ⭐ SMMA - Smoothed Moving Average | `SMMA_Series` || GetSmma ||
| ⛔ SSF - Ehler's Super Smoother Filter |||||
| ⛔ SUP - Supertrend |||||
| ⛔ SWMA - Symmetric Weighted Moving Average |||||
| ⛔ T3 - Tillson T3 Moving Average || T3 | GetT3 ||
| ⛔ SSF - Ehler's Super Smoother Filter |||| ssf |
| ⛔ SUPERTREND - Supertrend |||| supertrend |
| ⛔ SWMA - Symmetric Weighted Moving Average |||| swma |
| ⛔ T3 - Tillson T3 Moving Average || T3 | GetT3 | t3 |
| ⭐ TEMA - Triple EMA Average | `TEMA_Series` | TEMA | GetTema | tema |
| ⭐ TRIMA - Triangular Moving Average | `TRIMA_Series` | TRIMA |||
| ⭐ TRIMA - Triangular Moving Average | `TRIMA_Series` | TRIMA || trima |
| ⛔ TSF - Time Series Forecast || TSF |||
| ⛔ VIDYA - Variable Index Dynamic Average |||||
| ⛔ VOR - Vortex Indicator |||||
| ⛔ VIDYA - Variable Index Dynamic Average |||| vidya |
| ⛔ VORTEX - Vortex Indicator |||| vortex |
| ⭐ WMA - Weighted Moving Average | `WMA_Series` | WMA | GetWma | wma |
| ⭐ ZLEMA - Zero Lag EMA Average | `ZLEMA_Series` ||| zlma |
||||||