mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-03 03:47:42 +00:00
Merge branch 'dev' into main
This commit is contained in:
Miha Kralj
@@ -354,3 +354,4 @@ MigrationBackup/
|
||||
# Ionide (cross platform F# VS Code tools) working folder
|
||||
.ionide/
|
||||
dotCover.Output.dcvr
|
||||
/Tests/GlobalSuppressions.cs
|
||||
|
||||
@@ -34,9 +34,11 @@
|
||||
<Link>QuanTAlib\%(RecursiveDir)%(Filename)%(Extension)</Link>
|
||||
</Compile>
|
||||
</ItemGroup>
|
||||
<!--
|
||||
<Target Name="CopyCustomContent" AfterTargets="AfterBuild">
|
||||
<Copy SourceFiles=".\bin\$(Configuration)\net48\Quantower_QTAlib.dll" DestinationFolder="\Quantower\Settings\Scripts\Indicators\QuanTAlib" />
|
||||
</Target>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<AdditionalFiles Include="..\.sonarlint\mihakralj_quantalib\CSharp\SonarLint.xml" Link="SonarLint.xml" />
|
||||
</ItemGroup>
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
|
||||
/* <summary>
|
||||
Abstract classes with all scaffolding required to build indicators.
|
||||
@@ -17,47 +18,54 @@ Abstract classes with all scaffolding required to build indicators.
|
||||
</summary> */
|
||||
public abstract class Single_TSeries_Indicator : TSeries
|
||||
{
|
||||
protected readonly int _p;
|
||||
protected readonly bool _NaN;
|
||||
protected readonly TSeries _data;
|
||||
protected readonly int _period;
|
||||
protected readonly bool _NaN;
|
||||
protected readonly TSeries _data;
|
||||
protected int _p;
|
||||
|
||||
// Chainable Constructor - add it at the end of primary constructor :base(source: source, period: period, useNaN: useNaN)
|
||||
protected Single_TSeries_Indicator(TSeries source, int period, bool useNaN)
|
||||
// Chainable Constructor - add it at the end of primary constructor :base(source: source, period: period, useNaN: useNaN)
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||||
protected Single_TSeries_Indicator(TSeries source, int period, bool useNaN)
|
||||
{
|
||||
this._data = source;
|
||||
this._period = period;
|
||||
this._p = _period;
|
||||
this._NaN = useNaN;
|
||||
this._data.Pub += this.Sub;
|
||||
}
|
||||
|
||||
// overridable Add() method to add/update a single item at the end of the list
|
||||
|
||||
public virtual void Add((System.DateTime t, double v) TValue, bool update, bool useNaN)
|
||||
{
|
||||
if (_period == 0) { _p = this.Length; }
|
||||
var res = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : TValue.v);
|
||||
base.Add(res, update);
|
||||
}
|
||||
public new virtual void Add((System.DateTime t, double v) TValue, bool update) => base.Add(TValue, update);
|
||||
|
||||
// potentially overridable Add() method for the whole series (could be replaced with faster bulk algo)
|
||||
public virtual void Add(TSeries data) { for (int i = 0; i < data.Count; i++) { this.Add(TValue: data[i], update: false); } }
|
||||
|
||||
public new void Add((System.DateTime t, double v) TValue) => this.Add(TValue: TValue, update: false);
|
||||
public void Add(bool update) => this.Add(TValue: this._data[this._data.Count - 1], update: update);
|
||||
public void Add() => this.Add(TValue: this._data[this._data.Count - 1], update: false);
|
||||
public new void Sub(object source, TSeriesEventArgs e) => this.Add(TValue: this._data[this._data.Count - 1], update: e.update);
|
||||
|
||||
protected static void Add_Replace(List<double> l, double v, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ l[l.Count - 1] = v; }
|
||||
else
|
||||
{ l.Add(v); }
|
||||
}
|
||||
protected static double Add_Replace_Trim(List<double> l, double v, int p, bool update)
|
||||
{
|
||||
Add_Replace(l, v, update);
|
||||
double ret = (l.Count > 0) ? l.First() : 0;
|
||||
if (l.Count > p && p != 0)
|
||||
{
|
||||
this._data = source;
|
||||
this._p = period;
|
||||
this._NaN = useNaN;
|
||||
this._data.Pub += this.Sub;
|
||||
}
|
||||
|
||||
// overridable Add() method to add/update a single item at the end of the list
|
||||
|
||||
public virtual void Add((System.DateTime t, double v) TValue, bool update, bool useNaN)
|
||||
{
|
||||
var res = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : TValue.v);
|
||||
base.Add(res, update);
|
||||
}
|
||||
public new virtual void Add((System.DateTime t, double v) TValue, bool update) => base.Add(TValue, update);
|
||||
|
||||
// potentially overridable Add() method for the whole series (could be replaced with faster bulk algo)
|
||||
public virtual void Add(TSeries data) { for (int i = 0; i < data.Count; i++) { this.Add(TValue: data[i], update: false); }}
|
||||
|
||||
public new void Add((System.DateTime t, double v) TValue) => this.Add(TValue: TValue, update: false);
|
||||
public void Add(bool update) => this.Add(TValue: this._data[this._data.Count - 1], update: update);
|
||||
public void Add() => this.Add(TValue: this._data[this._data.Count - 1], update: false);
|
||||
public new void Sub(object source, TSeriesEventArgs e) => this.Add(TValue: this._data[this._data.Count - 1], update: e.update);
|
||||
|
||||
protected static void Add_Replace(List<double> l, double v, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ l[l.Count - 1] = v; }
|
||||
else
|
||||
{ l.Add(v); }
|
||||
}
|
||||
protected static void Add_Replace_Trim(List<double> l, double v, int p, bool update)
|
||||
{
|
||||
Add_Replace(l, v, update);
|
||||
if (l.Count > p && p!=0)
|
||||
{ l.RemoveAt(0); }
|
||||
l.RemoveAt(0);
|
||||
}
|
||||
return ret;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -22,10 +22,12 @@ public class GBM_Feed : TBars
|
||||
{
|
||||
private double seed;
|
||||
readonly double drift, volatility;
|
||||
public GBM_Feed(int Bars = 252, double Volatility = 1.0, double Drift = 0.05, double Seed = 100.0) {
|
||||
readonly int precision;
|
||||
public GBM_Feed(int Bars = 252, double Volatility = 1.0, double Drift = 0.05, double Seed = 100.0, int Precision = 2) {
|
||||
this.seed = Seed;
|
||||
volatility = Volatility*0.01;
|
||||
drift = Drift*0.01;
|
||||
precision = Precision;
|
||||
for (int i = 0; i <Bars; i++) {
|
||||
DateTime Timestamp = DateTime.Today.AddDays(i - Bars);
|
||||
this.Add(Timestamp);
|
||||
@@ -33,28 +35,28 @@ public class GBM_Feed : TBars
|
||||
}
|
||||
|
||||
public void Add(DateTime timestamp, bool update = false) {
|
||||
double Open = GBM_value(seed, volatility*volatility, drift);
|
||||
double Close = GBM_value(Open, volatility, drift);
|
||||
double Open = GBM_value(seed, volatility*volatility, drift, precision);
|
||||
double Close = GBM_value(Open, volatility, drift, precision);
|
||||
|
||||
double OCMax = Math.Max(Open,Close);
|
||||
double High = (GBM_value(seed, volatility*0.5, 0));
|
||||
double High = (GBM_value(seed, volatility*0.5, 0, precision));
|
||||
High = (High<OCMax)? (2 * OCMax) - High : High;
|
||||
|
||||
double OCMin = Math.Min(Open,Close);
|
||||
double Low = (GBM_value(seed, volatility*0.5, 0));
|
||||
double Low = (GBM_value(seed, volatility*0.5, 0, precision));
|
||||
Low = (Low>OCMin)? (2 * OCMin) - Low : Low;
|
||||
|
||||
double Volume = GBM_value(seed*10, volatility*2, Drift:0);
|
||||
double Volume = GBM_value(seed*10, volatility*2, Drift:0, precision: 1);
|
||||
|
||||
base.Add((timestamp, Open, High, Low, Close, Volume), update);
|
||||
seed = Close;
|
||||
}
|
||||
|
||||
private static double GBM_value (double Seed, double Volatility, double Drift) {
|
||||
private static double GBM_value(double Seed, double Volatility, double Drift, int precision) {
|
||||
Random rnd = new();
|
||||
double U1 = 1.0-rnd.NextDouble();
|
||||
double U2 = 1.0-rnd.NextDouble();
|
||||
double Z = Math.Sqrt(-2.0 * Math.Log(U1)) * Math.Sin(2.0 * Math.PI * U2);
|
||||
return Seed * Math.Exp( Drift - (Volatility*Volatility*0.5) + (Volatility * Z));
|
||||
return Math.Round(Seed * Math.Exp( Drift - (Volatility*Volatility*0.5) + (Volatility * Z)), digits: precision);
|
||||
}
|
||||
}
|
||||
@@ -2,7 +2,7 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<Title>QuanTAlib</Title>
|
||||
<Version>0.1.22</Version>
|
||||
<Version>0.1.23</Version>
|
||||
<Product>Library of Technical Indicators for .NET</Product>
|
||||
<Description>Quantitative Technical Analysis library for both real-time (streaming) and historical data analysis</Description>
|
||||
<RepositoryType>git</RepositoryType>
|
||||
@@ -66,7 +66,6 @@
|
||||
<Visible>False</Visible>
|
||||
<PackagePath></PackagePath>
|
||||
</None>
|
||||
<PackageReference Include="System.Collections" Version="4.3.0" />
|
||||
<PackageReference Include="System.Text.Json" Version="7.0.0" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -1,6 +1,7 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Linq;
|
||||
using System.Runtime.CompilerServices;
|
||||
|
||||
/* <summary>
|
||||
DEMA: Double Exponential Moving Average
|
||||
@@ -18,15 +19,15 @@ Remark:
|
||||
|
||||
public class DEMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private readonly System.Collections.Generic.List<double> _buffer1 = new();
|
||||
private readonly System.Collections.Generic.List<double> _buffer2 = new();
|
||||
private readonly double _k;
|
||||
private double _lastema1, _lastlastema1;
|
||||
private double _lastema2, _lastlastema2;
|
||||
|
||||
public DEMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 2.0 / (this._p + 1);
|
||||
this._k1m = 1.0 - this._k;
|
||||
_k = 2.0 / (_p + 1);
|
||||
if (_data.Count > 0) { base.Add(_data); }
|
||||
}
|
||||
|
||||
@@ -34,26 +35,40 @@ public class DEMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
if (update)
|
||||
{
|
||||
this._lastema1 = this._lastlastema1;
|
||||
this._lastema2 = this._lastlastema2;
|
||||
_lastema1 = _lastlastema1;
|
||||
_lastema2 = _lastlastema2;
|
||||
}
|
||||
|
||||
double _ema1, _ema2;
|
||||
|
||||
if (this.Count < this._p)
|
||||
double _ema1, _ema2, _dema;
|
||||
if (this.Count < _p)
|
||||
{
|
||||
Add_Replace_Trim(_buffer, TValue.v, _p, update);
|
||||
double _sma = _buffer.Average();
|
||||
Add_Replace_Trim(_buffer1, TValue.v, _p, update);
|
||||
_ema1 = 0;
|
||||
for (int i=0; i<_buffer1.Count; i++) { _ema1 += _buffer1[i]; }
|
||||
_ema1 /= _buffer1.Count;
|
||||
|
||||
_ema1 = _ema2 = _sma;
|
||||
Add_Replace_Trim(_buffer2, _ema1, _p, update);
|
||||
_ema2 = 0;
|
||||
for (int i = 0; i < _buffer2.Count; i++) { _ema2 += _buffer2[i]; }
|
||||
_ema2 /= _buffer2.Count;
|
||||
}
|
||||
else
|
||||
else if(this.Count < (2*_p - 1)) // second _p
|
||||
{
|
||||
_ema1 = (TValue.v * this._k) + (this._lastema1 * this._k1m);
|
||||
_ema2 = (_ema1 * this._k) + (this._lastema2 * this._k1m);
|
||||
}
|
||||
_ema1 = (TValue.v - _lastema1) * _k + _lastema1;
|
||||
|
||||
Add_Replace_Trim(_buffer2, _ema1, _p, update);
|
||||
_ema2 = 0;
|
||||
for (int i = 0; i < _buffer2.Count; i++) { _ema2 += _buffer2[i]; }
|
||||
_ema2 /= _buffer2.Count;
|
||||
}
|
||||
else // all others
|
||||
{
|
||||
_ema1 = (TValue.v - _lastema1) * _k + _lastema1;
|
||||
_ema2 = (_ema1 - _lastema2) * _k + _lastema2;
|
||||
|
||||
}
|
||||
_dema = 2*_ema1 - _ema2;
|
||||
|
||||
double _dema = (2 * _ema1) - _ema2;
|
||||
this._lastlastema1 = this._lastema1;
|
||||
this._lastlastema2 = this._lastema2;
|
||||
this._lastema1 = _ema1;
|
||||
@@ -61,4 +76,4 @@ public class DEMA_Series : Single_TSeries_Indicator
|
||||
|
||||
base.Add((TValue.t, _dema), update, _NaN);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,39 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
DWMA: Double (linearly) Weighted Moving Average
|
||||
The weights are linearly decreasing over the period and the most recent data has
|
||||
the heaviest weight.
|
||||
|
||||
Sources:
|
||||
|
||||
|
||||
</summary> */
|
||||
|
||||
public class DWMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
public DWMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
for (int i = 0; i < this._p; i++) { this._weights.Add(i + 1); }
|
||||
if (base._data.Count > 0) { base.Add(base._data); }
|
||||
}
|
||||
private readonly System.Collections.Generic.List<double> _buffer1 = new();
|
||||
private readonly System.Collections.Generic.List<double> _buffer2 = new();
|
||||
private readonly System.Collections.Generic.List<double> _weights = new();
|
||||
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
Add_Replace_Trim(_buffer1, TValue.v, _p, update);
|
||||
double _wma = 0;
|
||||
for (int i = 0; i < _buffer1.Count; i++) { _wma += _buffer1[i] * this._weights[i]; }
|
||||
_wma /= (this._buffer1.Count * (this._buffer1.Count + 1)) * 0.5;
|
||||
|
||||
Add_Replace_Trim(_buffer2, TValue.v, _p, update);
|
||||
double _dwma = 0;
|
||||
for (int i = 0; i < _buffer2.Count; i++) { _dwma += _buffer2[i] * this._weights[i]; }
|
||||
_dwma /= (this._buffer2.Count * (this._buffer2.Count + 1)) * 0.5;
|
||||
|
||||
base.Add((TValue.t, _dwma), update, _NaN);
|
||||
}
|
||||
}
|
||||
@@ -25,12 +25,14 @@ public class EMA_Series : Single_TSeries_Indicator
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private double _lastema, _lastlastema;
|
||||
private bool _useSMA;
|
||||
|
||||
public EMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
public EMA_Series(TSeries source, int period, bool useNaN = false, bool useSMA = true) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 2.0 / (this._p + 1);
|
||||
this._k1m = 1.0 - this._k;
|
||||
this._lastema = this._lastlastema = double.NaN;
|
||||
this._lastema = this._lastlastema = 0;
|
||||
_useSMA = useSMA;
|
||||
if (this._data.Count > 0) { base.Add(this._data); }
|
||||
}
|
||||
|
||||
@@ -38,11 +40,14 @@ public class EMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
double _ema;
|
||||
if (update) { this._lastema = this._lastlastema; }
|
||||
if (this.Count == 0) { _lastema = TValue.v; }
|
||||
|
||||
if (this.Count < this._p)
|
||||
if (this.Count < this._p && _useSMA)
|
||||
{
|
||||
Add_Replace(_buffer, TValue.v, update);
|
||||
_ema = _buffer.Average();
|
||||
_ema = 0;
|
||||
for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
|
||||
_ema /= _buffer.Count;
|
||||
}
|
||||
else
|
||||
{
|
||||
|
||||
+67
-126
@@ -1,5 +1,6 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Linq;
|
||||
|
||||
/* <summary>
|
||||
JMA: Jurik Moving Average
|
||||
@@ -18,141 +19,81 @@ Issues:
|
||||
original algo is slightly different, yet this approximation is close enough.
|
||||
|
||||
</summary>
|
||||
TODO: buggy - rework
|
||||
*/
|
||||
public class JMA_Series : Single_TSeries_Indicator {
|
||||
private readonly System.Collections.Generic.List<double> volty_10 = new();
|
||||
private readonly System.Collections.Generic.List<double> vsum_buff = new();
|
||||
private readonly double pr, beta;
|
||||
|
||||
public class JMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> vbuffer10;
|
||||
private readonly System.Collections.Generic.List<double> vsum65;
|
||||
private double upperBand, lowerBand, _phase, vsum, Kv, del1, del2, prev_del1, prev_del2;
|
||||
private double prev_ma1, prev_det0, prev_det1, prev_vsum, prev_jma;
|
||||
private double p_upperBand, p_lowerBand, p_Kv, p_prev_ma1, p_prev_det0, p_prev_det1, p_prev_vsum, p_prev_jma;
|
||||
|
||||
private double prev_ma1, prev_det0, prev_det1, prev_jma, bsmax, bsmin;
|
||||
private double o_prev_ma1, o_prev_det0, o_prev_det1, o_prev_jma, o_bsmax, o_bsmin;
|
||||
public JMA_Series(TSeries source, int period, double phase = 0.0, bool useNaN = false) : base(source, period, useNaN) {
|
||||
upperBand = lowerBand = prev_ma1 = prev_det0 = prev_det1 = prev_vsum = prev_jma = Kv = del1 = del2 = 0.0;
|
||||
Kv = 0;
|
||||
pr = (phase * 0.01) + 1.5;
|
||||
if (phase < -100) pr = 0.5;
|
||||
if (phase > 100) pr = 2.5;
|
||||
beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
|
||||
|
||||
private readonly double pr, pow1, len2, beta, rvolty;
|
||||
if (base._data.Count > 0) { base.Add(base._data); }
|
||||
}
|
||||
|
||||
public JMA_Series(TSeries source, int period, double phase = 0.0, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this.vbuffer10 = new();
|
||||
this.vsum65 = new();
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update) {
|
||||
if (update) {
|
||||
upperBand = p_upperBand; lowerBand = p_lowerBand; Kv = p_Kv; prev_vsum = p_prev_vsum;
|
||||
prev_ma1 = p_prev_ma1; prev_det0 = p_prev_det0; prev_det1 = p_prev_det1; prev_jma = p_prev_jma;
|
||||
} else {
|
||||
p_upperBand = upperBand; p_lowerBand = lowerBand; p_Kv = Kv; p_prev_vsum = prev_vsum;
|
||||
p_prev_ma1 = prev_ma1; p_prev_det0 = prev_det0; p_prev_det1 = prev_det1; p_prev_jma = prev_jma;
|
||||
}
|
||||
|
||||
// constants
|
||||
this.pr = (phase < -100) ? 0.5 : (phase > 100) ? 2.5 : (phase * 0.01) + 1.5;
|
||||
double len1 = Math.Max((Math.Log(Math.Sqrt(0.5 * (_p - 1))) / Math.Log(2.0)) + 2.0, 0);
|
||||
this.pow1 = Math.Max(len1 - 2, 0.5);
|
||||
this.rvolty = Math.Exp((1 / this.pow1) * Math.Log(len1));
|
||||
this.len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
|
||||
this.beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
|
||||
if (base._data.Count > 0) { base.Add(base._data); }
|
||||
}
|
||||
// from Tvalue to volty
|
||||
del1 = TValue.v - upperBand;
|
||||
del2 = TValue.v - lowerBand;
|
||||
upperBand = (del1 > 0) ? TValue.v : TValue.v - (Kv * del1);
|
||||
lowerBand = (del2 < 0) ? TValue.v : TValue.v - (Kv * del2);
|
||||
double volty = 0;
|
||||
if (Math.Abs(del1) > Math.Abs(del2)) { volty = Math.Abs(del1); }
|
||||
if (Math.Abs(del1) < Math.Abs(del2)) { volty = Math.Abs(del2); }
|
||||
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
if (this.Count == 0)
|
||||
{
|
||||
this.prev_ma1 = this.prev_jma = TValue.v;
|
||||
this.bsmax = this.bsmin = this.prev_det0 = this.prev_det1 = 0;
|
||||
}
|
||||
//// from volty to avolty
|
||||
if (update) { volty_10[volty_10.Count - 1] = volty; } else { volty_10.Add(volty); }
|
||||
if (volty_10.Count > 10) { volty_10.RemoveAt(0); }
|
||||
vsum = prev_vsum + 0.1 * (volty - volty_10.First());
|
||||
if (update) { vsum_buff[vsum_buff.Count - 1] = vsum; } else { vsum_buff.Add(vsum); }
|
||||
if (vsum_buff.Count > 65) vsum_buff.RemoveAt(0);
|
||||
double avolty = 0;
|
||||
for (int i = 0; i < vsum_buff.Count; i++) { avolty += vsum_buff[i]; }
|
||||
avolty /= vsum_buff.Count;
|
||||
|
||||
if (update)
|
||||
{
|
||||
this.prev_jma = this.o_prev_jma;
|
||||
this.prev_ma1 = this.o_prev_ma1;
|
||||
this.prev_det0 = this.o_prev_det0;
|
||||
this.prev_det1 = this.o_prev_det1;
|
||||
this.bsmax = this.o_bsmax;
|
||||
this.bsmin = this.o_bsmin;
|
||||
}
|
||||
else
|
||||
{
|
||||
this.o_prev_jma = this.prev_jma;
|
||||
this.o_prev_ma1 = this.prev_ma1;
|
||||
this.o_prev_det0 = this.prev_det0;
|
||||
this.o_prev_det1 = this.prev_det1;
|
||||
this.o_bsmax = this.bsmax;
|
||||
this.o_bsmin = this.bsmin;
|
||||
}
|
||||
/// from avolty to rolty
|
||||
double rvolty = (avolty > 0) ? volty / avolty : 0;
|
||||
double len1 = (Math.Log(Math.Sqrt(_p)) / Math.Log(2.0)) + 2;
|
||||
if (len1 < 0) len1 = 0;
|
||||
double pow1 = Math.Max(len1 - 2.0, 0.5);
|
||||
if (rvolty > Math.Pow(len1, 1.0 / pow1)) rvolty = Math.Pow(len1, 1.0 / pow1);
|
||||
if (rvolty < 1) rvolty = 1;
|
||||
|
||||
double hprice = TValue.v;
|
||||
double lprice = TValue.v;
|
||||
for (int i = 0; i <= Math.Min(9, this._data.Count - 1); i++)
|
||||
{
|
||||
var _item = this._data[this._data.Count - 1 - i].v;
|
||||
hprice = (_item > hprice) ? _item : hprice;
|
||||
lprice = (_item < lprice) ? _item : lprice;
|
||||
}
|
||||
double del1 = hprice - this.bsmax;
|
||||
double del2 = lprice - this.bsmin;
|
||||
//// from rvolty to second smoothing
|
||||
double pow2 = Math.Pow(rvolty, pow1);
|
||||
double len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
|
||||
Kv = Math.Pow(len2 / (len2 + 1), Math.Sqrt(pow2));
|
||||
double alpha = Math.Pow(beta, pow2);
|
||||
double ma1 = (1 - alpha) * TValue.v + alpha * prev_ma1;
|
||||
prev_ma1 = ma1;
|
||||
double det0 = (1 - beta) * (TValue.v - ma1) + beta * prev_det0;
|
||||
prev_det0 = det0;
|
||||
|
||||
double volty = (Math.Abs(del1) != Math.Abs(del2))
|
||||
? Math.Max(Math.Abs(del1), Math.Abs(del2))
|
||||
: 0;
|
||||
if (update)
|
||||
{
|
||||
this.vbuffer10[this.vbuffer10.Count - 1] = volty;
|
||||
}
|
||||
else
|
||||
{
|
||||
this.vbuffer10.Add(volty);
|
||||
}
|
||||
if (this.vbuffer10.Count > 10)
|
||||
{
|
||||
this.vbuffer10.RemoveAt(0);
|
||||
}
|
||||
/// from second smoothing to jma
|
||||
double ma2 = ma1 + pr * det0;
|
||||
double det1 = (1 - alpha) * (1 - alpha) * (ma2 - prev_jma) + alpha * alpha * prev_det1;
|
||||
prev_det1 = det1;
|
||||
double jma = prev_jma + det1;
|
||||
prev_jma = jma;
|
||||
|
||||
double prevvsum =
|
||||
(this.vsum65.Count > 0) ? this.vsum65[this.vsum65.Count - 1] : 0;
|
||||
double vsumitem = prevvsum + 0.1 * (volty - this.vbuffer10[0]);
|
||||
if (update)
|
||||
{
|
||||
this.vsum65[this.vsum65.Count - 1] = vsumitem;
|
||||
}
|
||||
else
|
||||
{
|
||||
this.vsum65.Add(vsumitem);
|
||||
}
|
||||
if (this.vsum65.Count > 65)
|
||||
{
|
||||
this.vsum65.RemoveAt(0);
|
||||
}
|
||||
base.Add((TValue.t, jma), update, _NaN);
|
||||
}
|
||||
}
|
||||
|
||||
double avolty = 0;
|
||||
for (int i = 0; i < this.vsum65.Count; i++)
|
||||
{
|
||||
avolty += this.vsum65[i];
|
||||
}
|
||||
|
||||
avolty /= this.vsum65.Count;
|
||||
double dvolty = (avolty > 0) ? volty / avolty : 0;
|
||||
dvolty = Math.Max((dvolty > this.rvolty) ? this.rvolty : dvolty, 1.0);
|
||||
|
||||
double pow2 = Math.Exp(this.pow1 * Math.Log(dvolty));
|
||||
double kv =
|
||||
Math.Exp(Math.Sqrt(pow2) * Math.Log(this.len2 / (this.len2 + 1)));
|
||||
|
||||
this.bsmax = (del1 > 0) ? hprice : hprice - (kv * del1);
|
||||
this.bsmin = (del2 < 0) ? lprice : lprice - (kv * del2);
|
||||
|
||||
// adaptive EMA dynamic factor
|
||||
double pow = Math.Pow(dvolty, this.pow1);
|
||||
double alpha = Math.Pow(this.beta, pow);
|
||||
|
||||
// 1st stage - preliminary smoothing by adaptive EMA
|
||||
double ma1 = TValue.v * (1 - alpha) + this.prev_ma1 * alpha;
|
||||
this.prev_ma1 = ma1;
|
||||
|
||||
// 2nd stage - one more preliminary smoothing by Kalman filter
|
||||
double det0 = (TValue.v - ma1) * (1 - this.beta) + this.prev_det0 * this.beta;
|
||||
this.prev_det0 = det0;
|
||||
double ma2 = ma1 + (this.pr * det0);
|
||||
|
||||
// 3rd stage - final smoothing by Jurik adaptive filter
|
||||
double det1 = ((ma2 - this.prev_jma) * (1 - alpha) * (1 - alpha)) +
|
||||
(this.prev_det1 * alpha * alpha);
|
||||
this.prev_det1 = det1;
|
||||
var _jma = this.prev_jma + det1;
|
||||
this.prev_jma = _jma;
|
||||
|
||||
base.Add((TValue.t, _jma), update, _NaN);
|
||||
}
|
||||
}
|
||||
@@ -21,12 +21,10 @@ public class MAMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
fastl = fastlimit;
|
||||
slowl = slowlimit;
|
||||
i = 0;
|
||||
Fama = new();
|
||||
if (base._data.Count > 0) { base.Add(base._data); }
|
||||
}
|
||||
|
||||
private int i;
|
||||
private double sumPr, jI, jQ, fastl, slowl;
|
||||
private (double i, double i1, double i2, double i3, double i4, double i5, double i6, double io) pr, i1, q1, sm, dt;
|
||||
private (double i, double i1, double io) i2, q2, re, im, pd, ph, mama, fama;
|
||||
@@ -51,7 +49,7 @@ public class MAMA_Series : Single_TSeries_Indicator
|
||||
mama.io = mama.i1; mama.i1 = mama.i;
|
||||
fama.io = fama.i1; fama.i1 = fama.i;
|
||||
}
|
||||
|
||||
int i = base.Count;
|
||||
pr.i = TValue.v;
|
||||
if (i > 5) {
|
||||
double adj = (0.075 * pd.i1) + 0.54;
|
||||
@@ -113,7 +111,6 @@ public class MAMA_Series : Single_TSeries_Indicator
|
||||
mama.i = fama.i = sumPr / (i+1);
|
||||
}
|
||||
|
||||
if (!update) { i++; }
|
||||
base.Add((TValue.t, mama.i), update, _NaN);
|
||||
var result = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : fama.i);
|
||||
Fama.Add(result, update);
|
||||
|
||||
+40
-13
@@ -1,6 +1,5 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Linq;
|
||||
|
||||
/* <summary>
|
||||
SMA: Simple Moving Average
|
||||
@@ -19,17 +18,45 @@ Remark:
|
||||
|
||||
public class SMA_Series : Single_TSeries_Indicator
|
||||
{
|
||||
public SMA_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();
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private double _sma, _oldsma;
|
||||
private double _topv, _oldtopv;
|
||||
public SMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
if (base._data.Count > 0)
|
||||
{ base.Add(base._data); }
|
||||
}
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
_topv = Add_Replace_Trim(_buffer, TValue.v, _p, update);
|
||||
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
Add_Replace_Trim(_buffer, TValue.v, _p, update);
|
||||
double _sma = _buffer.Sum() / _buffer.Count;
|
||||
// rolling back if update, storing data for potential future update
|
||||
if (update)
|
||||
{
|
||||
_sma = _oldsma;
|
||||
_topv = _oldtopv;
|
||||
}
|
||||
else
|
||||
{
|
||||
_oldsma = _sma;
|
||||
_oldtopv = _topv;
|
||||
}
|
||||
|
||||
base.Add((TValue.t, _sma), update, _NaN);
|
||||
}
|
||||
}
|
||||
// main additive calculation of SMA - for data points that are larger than _p period
|
||||
// this.Count > _p
|
||||
if (this.Count > _p)
|
||||
{
|
||||
_sma += (TValue.v - _topv) / _p;
|
||||
}
|
||||
else
|
||||
{
|
||||
// calculate SMA the traditional way (sum all, divide with _p) for data points within _p period
|
||||
_sma = 0;
|
||||
for (int i = 0; i < _buffer.Count; i++)
|
||||
{ _sma += _buffer[i]; }
|
||||
_sma /= _buffer.Count;
|
||||
}
|
||||
|
||||
base.Add((TValue.t, _sma), update, _NaN);
|
||||
}
|
||||
}
|
||||
+24
-14
@@ -4,19 +4,30 @@ using System.Linq;
|
||||
using System.Numerics;
|
||||
|
||||
/* <summary>
|
||||
T3: Triple Exponential Moving Average
|
||||
TEMA uses EMA(EMA(EMA())) to calculate less laggy Exponential moving average.
|
||||
T3: Tillson T3 Moving Average
|
||||
Tim Tillson described it in "Technical Analysis of Stocks and Commodities", January 1998 in the
|
||||
article "Better Moving Averages". Tillson’s moving average becomes a popular indicator of
|
||||
technical analysis as it gets less lag with the price chart and its curve is considerably smoother.
|
||||
|
||||
Sources:
|
||||
https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/triple-exponential-moving-average-tema/
|
||||
https://technicalindicators.net/indicators-technical-analysis/150-t3-moving-average
|
||||
http://www.binarytribune.com/forex-trading-indicators/t3-moving-average-indicator/
|
||||
|
||||
Calculation:
|
||||
a = 0.7 (but also 0.618);
|
||||
Ema1 = Ema (Close);
|
||||
Ema2 = Ema (Ema1);
|
||||
Ema3 = Ema (Ema2);
|
||||
Ema4 = Ema (Ema3);
|
||||
Ema5 = Ema (Ema4);
|
||||
Ema6 = Ema (Ema5);
|
||||
T3 = –(a*a*a) * Ema6 + (3*a*a + 3*a*a*a) * Ema5 + (–6*a*a – 3*a – 3*a*a*a) * Ema4 + (1 + 3*a + a*a*a + 3*a*a) * Ema3
|
||||
|
||||
</summary> */
|
||||
|
||||
public class T3_Series : Single_TSeries_Indicator
|
||||
{
|
||||
private int i;
|
||||
private double k, a;
|
||||
private double k, a;
|
||||
private double c1, c2, c3, c4;
|
||||
private double o_c1, o_c2, o_c3, o_c4;
|
||||
|
||||
@@ -26,9 +37,8 @@ public class T3_Series : Single_TSeries_Indicator
|
||||
private double sum1, sum2, sum3, sum4, sum5, sum6;
|
||||
private double o_sum1, o_sum2, o_sum3, o_sum4, o_sum5, o_sum6;
|
||||
|
||||
public T3_Series(TSeries source, int period, double vfactor, bool useNaN = false) : base(source, period, useNaN)
|
||||
public T3_Series(TSeries source, int period, double vfactor = 0.7, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
i = 0;
|
||||
k = 2.0 / (_p + 1);
|
||||
a = vfactor;
|
||||
c1 = -a * a * a;
|
||||
@@ -55,6 +65,7 @@ public class T3_Series : Single_TSeries_Indicator
|
||||
o_sum1 = sum1; o_sum2 = sum2; o_sum3 = sum3; o_sum4 = sum4; o_sum5 = sum5; o_sum6 = sum6;
|
||||
}
|
||||
double v = TValue.v;
|
||||
int i = base.Count;
|
||||
if (i > _p - 1) {
|
||||
e1 += k * (v - e1);
|
||||
if (i > 2 * (_p - 1)) {
|
||||
@@ -71,45 +82,44 @@ public class T3_Series : Single_TSeries_Indicator
|
||||
else {
|
||||
sum6 += e5;
|
||||
if (i == 6 * (_p - 1)) {
|
||||
e6 = sum6 / _p;
|
||||
e6 = sum6 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
}
|
||||
else {
|
||||
sum5 += e4;
|
||||
if (i == 5 * (_p - 1)) {
|
||||
sum6 = e5 = sum5 / _p;
|
||||
sum6 = e5 = sum5 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
}
|
||||
else {
|
||||
sum4 += e3;
|
||||
if (i == 4 * (_p - 1)) {
|
||||
sum5 = e4 = sum4 / _p;
|
||||
sum5 = e4 = sum4 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
}
|
||||
else {
|
||||
sum3 += e2;
|
||||
if (i == 3 * (_p - 1)) {
|
||||
sum4 = e3 = sum3 / _p;
|
||||
sum4 = e3 = sum3 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
}
|
||||
else {
|
||||
sum2 += e1;
|
||||
if (i == 2 * (_p - 1)) {
|
||||
sum3 = e2 = sum2 / _p;
|
||||
sum3 = e2 = sum2 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
}
|
||||
else {
|
||||
sum1 += v;
|
||||
if (i == _p - 1) {
|
||||
sum2 = e1 = sum1 / _p;
|
||||
sum2 = e1 = sum1 / Math.Max(_p, base.Count);
|
||||
}
|
||||
}
|
||||
if (!update) { i++; }
|
||||
|
||||
double t3 = (c1 * e6) + (c2 * e5) + (c3 * e4) + (c4 * e3);
|
||||
base.Add(TValue: (TValue.t, t3), update: update, useNaN: _NaN);
|
||||
|
||||
@@ -5,7 +5,7 @@ using System;
|
||||
ADL: Chaikin Accumulation/Distribution Line
|
||||
ADL is a volume-based indicator that measures the cumulative Money Flow Volume:
|
||||
|
||||
1. Money Flow Multiplier = [(Close - Low) - (High - Close)] /(High - Low)
|
||||
1. Money Flow Multiplier = [(Close - Low) - (High - Close)] /(High - Low)
|
||||
2. Money Flow Volume = Money Flow Multiplier x Volume for the Period
|
||||
3. ADL = Previous ADL + Current Period's Money Flow Volume
|
||||
|
||||
@@ -20,19 +20,17 @@ public class ADL_Series : Single_TBars_Indicator
|
||||
|
||||
public ADL_Series(TBars source, bool useNaN = false) : base(source, 0, useNaN)
|
||||
{
|
||||
this._lastadl = this._lastlastadl = 0;
|
||||
if (_bars.Count > 0)
|
||||
{ base.Add(_bars); }
|
||||
_lastadl = _lastlastadl = 0;
|
||||
if (_bars.Count > 0) { base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ this._lastadl = this._lastlastadl; }
|
||||
if (update) { this._lastadl = this._lastlastadl; }
|
||||
|
||||
double _mfm = ((TBar.c - TBar.l) - (TBar.h - TBar.c)) / (TBar.h - TBar.l);
|
||||
double _mfv = _mfm * TBar.v;
|
||||
double _adl = this._lastadl + _mfv;
|
||||
double _adl = 0;
|
||||
double tmp = TBar.h - TBar.l;
|
||||
if (tmp > 0.0 ) { _adl = _lastadl + ((2*TBar.c - TBar.l - TBar.h) / tmp * TBar.v); }
|
||||
|
||||
this._lastlastadl = this._lastadl;
|
||||
this._lastadl = _adl;
|
||||
|
||||
@@ -13,6 +13,47 @@ Sources:
|
||||
|
||||
</summary> */
|
||||
|
||||
|
||||
public class ADOSC_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly double _k1, _k2;
|
||||
private double _lastema1, _lastlastema1, _lastema2, _lastlastema2;
|
||||
private double _lastadl, _lastlastadl;
|
||||
|
||||
public ADOSC_Series(TBars source, int shortPeriod = 3, int longPeriod =10, bool useNaN = false) : base(source, period: 0, useNaN)
|
||||
{
|
||||
_k1 = 2.0 / (shortPeriod + 1);
|
||||
_k2 = 2.0 / (longPeriod + 1);
|
||||
_lastadl = _lastlastadl = _lastema1 = _lastlastema1 = _lastema2 = _lastlastema2 = 0;
|
||||
if (_bars.Count > 0) { base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update) {
|
||||
_lastadl = _lastlastadl;
|
||||
_lastema1 = _lastlastema1;
|
||||
_lastema2 = _lastlastema2;
|
||||
}
|
||||
|
||||
double _adl = 0;
|
||||
double tmp = TBar.h - TBar.l;
|
||||
if (tmp > 0.0) { _adl = _lastadl + ((2 * TBar.c - TBar.l - TBar.h) / tmp * TBar.v); }
|
||||
if (this.Count == 0) { _lastema1 = _lastema2 = _adl; }
|
||||
|
||||
double _ema1 = (_adl - _lastema1) * _k1 + _lastema1;
|
||||
double _ema2 = (_adl - _lastema2) * _k2 + _lastema2;
|
||||
|
||||
_lastlastadl = _lastadl; _lastadl = _adl;
|
||||
_lastlastema1 = _lastema1; _lastema1 = _ema1;
|
||||
_lastlastema2 = _lastema2; _lastema2 = _ema2;
|
||||
|
||||
double _adosc = _ema1 - _ema2;
|
||||
base.Add((TBar.t, _adosc), update, _NaN);
|
||||
}
|
||||
|
||||
}
|
||||
/*
|
||||
public class ADOSC_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly ADL_Series _TSadl;
|
||||
@@ -42,4 +83,5 @@ public class ADOSC_Series : Single_TBars_Indicator
|
||||
var result = (TBar.t, _ado);
|
||||
base.Add(result, update);
|
||||
}
|
||||
}
|
||||
}
|
||||
*/
|
||||
+13
-2
@@ -105,7 +105,7 @@ public class Update {
|
||||
Assert.Equal(lastCalc, QL.Last()); // same data
|
||||
}
|
||||
[Fact] public void COVAR() {
|
||||
COVAR_Series QL = new(d1: bars.High, d2: bars.Low, period: period);
|
||||
COVAR_Series QL = new(d1: bars.High, d2: bars.Low, period);
|
||||
var lastData = bars.Last();
|
||||
var lastCalc = QL.Last();
|
||||
int lastLen = QL.Count;
|
||||
@@ -124,7 +124,18 @@ public class Update {
|
||||
Assert.Equal(lastLen, QL.Count); // same size
|
||||
Assert.Equal(lastCalc, QL.Last()); // same data
|
||||
}
|
||||
[Fact] public void ENTROPY() {
|
||||
[Fact]
|
||||
public void DWMA() {
|
||||
DWMA_Series QL = new(source: bars.Close, period);
|
||||
var lastData = bars.Close.Last();
|
||||
var lastCalc = QL.Last();
|
||||
int lastLen = QL.Count;
|
||||
QL.Add((DateTime.Today, 0), update: true);
|
||||
QL.Add(lastData, update: true);
|
||||
Assert.Equal(lastLen, QL.Count); // same size
|
||||
Assert.Equal(lastCalc, QL.Last()); // same data
|
||||
}
|
||||
[Fact] public void ENTROPY() {
|
||||
ENTROPY_Series QL = new(source: bars.Close, period: period);
|
||||
var lastData = bars.Close.Last();
|
||||
var lastCalc = QL.Last();
|
||||
|
||||
@@ -19,6 +19,8 @@
|
||||
<PackageReference Include="TALib.NETCore" Version="0.4.4" />
|
||||
<PackageReference Include="Skender.Stock.Indicators" Version="2.4.0" />
|
||||
<PackageReference Include="pythonnet" Version="3.0.1" />
|
||||
<PackageReference Include="Tulip.NETCore" Version="0.8.0.1" />
|
||||
<PackageReference Include="System.Text.Json" Version="7.0.0" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
@@ -28,5 +30,7 @@
|
||||
<ItemGroup>
|
||||
<None Remove="Python.Included" />
|
||||
<None Remove="pythonnet" />
|
||||
<None Remove="Tulip.NETCore" />
|
||||
<None Remove="System.Text.Json" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
|
||||
@@ -1,203 +0,0 @@
|
||||
using Xunit;
|
||||
using System;
|
||||
using QuanTAlib;
|
||||
using Python.Runtime;
|
||||
using Python.Included;
|
||||
|
||||
namespace Validations;
|
||||
public class PandasTA : IDisposable
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period;
|
||||
private int digits;
|
||||
private readonly string OStype;
|
||||
private readonly dynamic np;
|
||||
private readonly dynamic ta;
|
||||
private readonly dynamic df;
|
||||
|
||||
public PandasTA() {
|
||||
bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0);
|
||||
period = rnd.Next(maxValue: 28) + 3;
|
||||
digits = 4; //minimizing rounding errors in type conversions
|
||||
|
||||
// Checking the host OS and setting PythonDLL accordingly
|
||||
OStype = Path.GetFullPath(path: ".") + @"\python-3.10.0-embed-amd64\python310.dll";
|
||||
|
||||
Installer.InstallPath = Path.GetFullPath(path: ".");
|
||||
Installer.SetupPython().Wait();
|
||||
Installer.TryInstallPip();
|
||||
Installer.PipInstallModule(module_name: "pandas-ta");
|
||||
Runtime.PythonDLL = OStype;
|
||||
PythonEngine.Initialize();
|
||||
np = Py.Import(name: "numpy");
|
||||
ta = Py.Import(name: "pandas_ta");
|
||||
|
||||
string[] cols = { "open", "high", "low", "close", "volume" };
|
||||
double[,] ary = new double[bars.Count, 5];
|
||||
for (int i = 0; i < bars.Count; i++) {
|
||||
ary[i, 0] = bars.Open[i].v;
|
||||
ary[i, 1] = bars.High[i].v;
|
||||
ary[i, 2] = bars.Low[i].v;
|
||||
ary[i, 3] = bars.Close[i].v;
|
||||
ary[i, 4] = bars.Volume[i].v;
|
||||
}
|
||||
df = ta.DataFrame(data: np.array(ary), index: np.array(bars.Close.t), columns: np.array(cols));
|
||||
}
|
||||
public void Dispose()
|
||||
{
|
||||
PythonEngine.Shutdown();
|
||||
GC.SuppressFinalize(this);
|
||||
}
|
||||
|
||||
[Fact] void ADL() {
|
||||
ADL_Series QL = new(bars);
|
||||
var pta = df.ta.ad(high: df.high, low: df.low, close:df.close, volume:df.volume);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void ADOSC() {
|
||||
ADOSC_Series QL = new(bars);
|
||||
var pta = df.ta.adosc(high: df.high, low: df.low, close: df.close, volume: df.volume);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void ATR() {
|
||||
ATR_Series QL = new(bars, period);
|
||||
var pta = df.ta.atr(high: df.high, low: df.low, close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void BIAS() {
|
||||
BIAS_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.bias(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void DEMA() {
|
||||
DEMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.dema(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void EMA() {
|
||||
EMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.ema(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void ENTROPY() {
|
||||
ENTROPY_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.entropy(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void HL2() {
|
||||
var pta = df.ta.hl2(high: df.high, low: df.low);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.HL2.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void HLC3() {
|
||||
var pta = df.ta.hlc3(high: df.high, low: df.low, close: df.close);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.HLC3.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void HMA() {
|
||||
HMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.hma(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void KAMA() {
|
||||
KAMA_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.kama(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void KURTOSIS() {
|
||||
KURTOSIS_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.kurtosis(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void MAD()
|
||||
{
|
||||
MAD_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.mad(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void MEDIAN() {
|
||||
MEDIAN_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.median(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void OBV() {
|
||||
OBV_Series QL = new(bars);
|
||||
var pta = df.ta.obv(close: df.close, volume: df.volume);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void OHLC4() {
|
||||
var pta = df.ta.ohlc4(open: df.open, high: df.high, low: df.low, close: df.close);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(bars.OHLC4.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void RMA() {
|
||||
RMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.rma(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void RSI() {
|
||||
RSI_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.rsi(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void SMA() {
|
||||
SMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.sma(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void SVARIANCE() {
|
||||
SVAR_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.variance(close: df.close, length: period, ddof: 1);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void T3() {
|
||||
T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, useNaN: false);
|
||||
var pta = df.ta.t3(close: df.close, length: period, a: 0.7);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void TEMA() {
|
||||
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), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void TR() {
|
||||
TR_Series QL = new(bars);
|
||||
var pta = df.ta.true_range(high: df.high, low: df.low, close: df.close);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void TRIMA() {
|
||||
// TODO: return length to variable length (period) when Pandas-TA fixes trima to calculate even periods right
|
||||
TRIMA_Series QL = new(bars.Close, 11);
|
||||
var pta = df.ta.trima(close: df.close, length: 11);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void VARIANCE() {
|
||||
VAR_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.variance(close: df.close, length: period, ddof:0);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void WMA() {
|
||||
WMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.wma(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] void ZLEMA() {
|
||||
ZLEMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.zlma(close: df.close, length: period);
|
||||
Assert.Equal(Math.Round((double)pta.tail(1), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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), digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,204 +0,0 @@
|
||||
using System;
|
||||
using QuanTAlib;
|
||||
using Skender.Stock.Indicators;
|
||||
using Xunit;
|
||||
|
||||
namespace Validations;
|
||||
public class Skender_Stock {
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, digits;
|
||||
private readonly IEnumerable<Quote> quotes;
|
||||
|
||||
public Skender_Stock() {
|
||||
bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0);
|
||||
period = rnd.Next(28) + 3;
|
||||
digits = 4; //minimizing rounding errors in type conversions
|
||||
|
||||
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 ADL() {
|
||||
ADL_Series QL = new(bars, false);
|
||||
var SK = quotes.GetAdl();
|
||||
Assert.Equal(Math.Round(SK.Last().Adl!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void ATR() {
|
||||
ATR_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetAtr(period);
|
||||
Assert.Equal(Math.Round((double)SK.Last().Atr!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void ATRP() {
|
||||
ATRP_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetAtr(period);
|
||||
Assert.Equal(Math.Round((double)SK.Last().Atrp!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Mid.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().UpperBand!, digits: digits), Math.Round(QL.Upper.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().LowerBand!, digits: digits), Math.Round(QL.Lower.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().Width!, digits: digits), Math.Round(QL.Bandwidth.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().PercentB!, digits: digits), Math.Round(QL.PercentB.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().ZScore!, digits: digits), Math.Round(QL.Zscore.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void CCI() {
|
||||
CCI_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetCci(period);
|
||||
Assert.Equal(Math.Round((double)SK.Last().Cci!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void COVAR() {
|
||||
COVAR_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().Covariance!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void HL2() {
|
||||
TSeries QL = bars.HL2;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.HL2);
|
||||
Assert.Equal(Math.Round(SK.Last().Value!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void HLC3() {
|
||||
TSeries QL = bars.HLC3;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.HLC3);
|
||||
Assert.Equal(Math.Round(SK.Last().Value!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().Intercept!, digits: digits), Math.Round(QL.Intercept.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().RSquared!, digits: digits), Math.Round(QL.RSquared.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().StdDev!, digits: digits), Math.Round(QL.StdDev.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().Signal!, digits: digits), Math.Round(QL.Signal.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void MAMA() {
|
||||
MAMA_Series QL = new(bars.HL2, fastlimit: 0.5, slowlimit: 0.05);
|
||||
var SK = quotes.GetMama(fastLimit: 0.5, slowLimit: 0.05);
|
||||
Assert.Equal(Math.Round((double)SK.Last().Mama!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round((double)SK.Last().Fama!, digits: digits), Math.Round(QL.Fama.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void OC2() {
|
||||
TSeries QL = bars.OC2;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OC2);
|
||||
Assert.Equal(Math.Round(SK.Last().Value!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void OHL3() {
|
||||
TSeries QL = bars.OHL3;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OHL3);
|
||||
Assert.Equal(Math.Round(SK.Last().Value!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void OHLC4() {
|
||||
TSeries QL = bars.OHLC4;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OHLC4);
|
||||
Assert.Equal(Math.Round(SK.Last().Value!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void T3() {
|
||||
T3_Series QL = new(source: bars.Close, period, vfactor: 0.7, false);
|
||||
var SK = quotes.GetT3(lookbackPeriods: period, volumeFactor: 0.7);
|
||||
Assert.Equal(Math.Round((double)SK.Last().T3!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void TR() {
|
||||
TR_Series QL = new(bars, useNaN: false);
|
||||
var SK = quotes.GetTr();
|
||||
Assert.Equal(Math.Round((double)SK.Last().Tr!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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!, digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,208 +0,0 @@
|
||||
using Xunit;
|
||||
using System;
|
||||
using TALib;
|
||||
using QuanTAlib;
|
||||
|
||||
namespace Validations;
|
||||
public class Ta_Lib
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, digits;
|
||||
private readonly double[] TALIB;
|
||||
private readonly double[] TALIB2;
|
||||
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(Bars: 5000, Volatility: 0.8, Drift: 0.0);
|
||||
period = rnd.Next(28) + 3;
|
||||
digits = 6;
|
||||
|
||||
TALIB = new double[bars.Count];
|
||||
TALIB2 = 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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Upper.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Mid.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Lower.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round(macdSignal[macdSignal.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Signal.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void MAMA() {
|
||||
MAMA_Series QL = new(bars.Close, fastlimit: 0.5, slowlimit: 0.05);
|
||||
Core.Mama(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outMama: TALIB, outFama: TALIB2, outBegIdx: out int outBegIdx, outNbElement: out _, optInFastLimit: 0.5, optInSlowLimit: 0.05);
|
||||
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[Fact] public void T3() {
|
||||
T3_Series QL = new(source: bars.Close, period: period, vfactor:0.7, useNaN: false);
|
||||
Core.T3(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outReal: TALIB, outBegIdx: out int outBegIdx, outNbElement: out _, optInTimePeriod: period, optInVFactor: 0.7);
|
||||
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
[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], digits: digits), Math.Round(QL.Last().v, digits: digits));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,361 @@
|
||||
using Xunit;
|
||||
using System;
|
||||
using QuanTAlib;
|
||||
using Python.Runtime;
|
||||
using Python.Included;
|
||||
|
||||
namespace Validations;
|
||||
public class PandasTA : IDisposable
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, sample;
|
||||
private int digits;
|
||||
private readonly string OStype;
|
||||
private readonly dynamic np;
|
||||
private readonly dynamic ta;
|
||||
private readonly dynamic df;
|
||||
|
||||
public PandasTA() {
|
||||
bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0);
|
||||
period = rnd.Next(maxValue: 28) + 3;
|
||||
sample = 200;
|
||||
digits = 10;
|
||||
|
||||
// Checking the host OS and setting PythonDLL accordingly
|
||||
OStype = Environment.OSVersion.ToString();
|
||||
if (OStype == "Unix 13.1.0")
|
||||
OStype = @"/usr/local/Cellar/python@3.10/3.10.8/Frameworks/Python.framework/Versions/3.10/lib/libpython3.10.dylib";
|
||||
else OStype = Path.GetFullPath(".") + @"\python-3.10.0-embed-amd64\python310.dll";
|
||||
|
||||
Installer.InstallPath = Path.GetFullPath(path: ".");
|
||||
Installer.SetupPython().Wait();
|
||||
Installer.TryInstallPip();
|
||||
Installer.PipInstallModule(module_name: "pandas-ta");
|
||||
Runtime.PythonDLL = OStype;
|
||||
PythonEngine.Initialize();
|
||||
np = Py.Import(name: "numpy");
|
||||
ta = Py.Import(name: "pandas_ta");
|
||||
|
||||
string[] cols = { "open", "high", "low", "close", "volume" };
|
||||
double[,] ary = new double[bars.Count, 5];
|
||||
for (int i = 0; i < bars.Count; i++) {
|
||||
ary[i, 0] = bars.Open[i].v;
|
||||
ary[i, 1] = bars.High[i].v;
|
||||
ary[i, 2] = bars.Low[i].v;
|
||||
ary[i, 3] = bars.Close[i].v;
|
||||
ary[i, 4] = bars.Volume[i].v;
|
||||
}
|
||||
df = ta.DataFrame(data: np.array(ary), index: np.array(bars.Close.t), columns: np.array(cols));
|
||||
}
|
||||
public void Dispose()
|
||||
{
|
||||
PythonEngine.Shutdown();
|
||||
GC.SuppressFinalize(this);
|
||||
}
|
||||
|
||||
[Fact] void ADL() {
|
||||
ADL_Series QL = new(bars);
|
||||
var pta = df.ta.ad(high: df.high, low: df.low, close:df.close, volume:df.volume);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i-1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i-1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
|
||||
}
|
||||
}
|
||||
[Fact] void ADOSC() {
|
||||
ADOSC_Series QL = new(bars);
|
||||
var pta = df.ta.adosc(high: df.high, low: df.low, close: df.close, volume: df.volume);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void ATR() {
|
||||
ATR_Series QL = new(bars, period);
|
||||
var pta = df.ta.atr(high: df.high, low: df.low, close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void BIAS() {
|
||||
BIAS_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.bias(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void DEMA() {
|
||||
DEMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.dema(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void EMA() {
|
||||
EMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.ema(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void ENTROPY() {
|
||||
ENTROPY_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.entropy(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void HL2() {
|
||||
var pta = df.ta.hl2(high: df.high, low: df.low);
|
||||
for (int i = bars.HL2.Length; i > bars.HL2.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(bars.HL2[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void HLC3() {
|
||||
var pta = df.ta.hlc3(high: df.high, low: df.low, close: df.close);
|
||||
for (int i = bars.HLC3.Length; i > bars.HLC3.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(bars.HLC3[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void HMA() {
|
||||
HMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.hma(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
|
||||
}
|
||||
[Fact] void KAMA() {
|
||||
KAMA_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.kama(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void KURTOSIS() {
|
||||
KURTOSIS_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.kurtosis(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void MAD()
|
||||
{
|
||||
MAD_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.mad(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void MEDIAN() {
|
||||
MEDIAN_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.median(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void OBV() {
|
||||
OBV_Series QL = new(bars);
|
||||
var pta = df.ta.obv(close: df.close, volume: df.volume);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void OHLC4() {
|
||||
var pta = df.ta.ohlc4(open: df.open, high: df.high, low: df.low, close: df.close);
|
||||
for (int i = bars.OHLC4.Length; i > bars.OHLC4.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(bars.OHLC4[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void RMA() {
|
||||
RMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.rma(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void RSI() {
|
||||
RSI_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.rsi(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void SDEV() {
|
||||
SDEV_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.stdev(close: df.close, length: period, ddof: 0);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void SMA() {
|
||||
SMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.sma(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void SSDEV() {
|
||||
SSDEV_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.stdev(close: df.close, length: period, ddof: 1);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact] void SVARIANCE() {
|
||||
SVAR_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.variance(close: df.close, length: period, ddof: 1);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact] void T3() {
|
||||
T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, useNaN: false);
|
||||
var pta = df.ta.t3(close: df.close, length: period, a: 0.7);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void TEMA() {
|
||||
TEMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.tema(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void TR() {
|
||||
TR_Series QL = new(bars);
|
||||
var pta = df.ta.true_range(high: df.high, low: df.low, close: df.close);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void TRIMA() {
|
||||
// TODO: return length to variable length (period) when Pandas-TA fixes trima to calculate even periods right
|
||||
TRIMA_Series QL = new(bars.Close, 11);
|
||||
var pta = df.ta.trima(close: df.close, length: 11);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void VARIANCE() {
|
||||
VAR_Series QL = new(bars.Close, period);
|
||||
var pta = df.ta.variance(close: df.close, length: period, ddof:0);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void WMA() {
|
||||
WMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.wma(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void ZLEMA() {
|
||||
ZLEMA_Series QL = new(bars.Close, period, false);
|
||||
var pta = df.ta.zlma(close: df.close, length: period);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact] void ZSCORE() {
|
||||
ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var pta = df.ta.zscore(close: df.close, length: period, ddof: 0);
|
||||
for (int i = QL.Length; i > QL.Length-sample; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double PanTA_item = Math.Round((double)pta[i - 1], digits: digits);
|
||||
Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,472 @@
|
||||
using System;
|
||||
using QuanTAlib;
|
||||
using Skender.Stock.Indicators;
|
||||
using Xunit;
|
||||
|
||||
namespace Validations;
|
||||
public class Skender
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, digits, skip;
|
||||
private readonly IEnumerable<Quote> quotes;
|
||||
|
||||
|
||||
public Skender()
|
||||
{
|
||||
bars = new(Bars: 10000, Volatility: 0.5, Drift: 0.0, Precision: 2);
|
||||
period = rnd.Next(30) + 5;
|
||||
skip = 200;
|
||||
digits = 10;
|
||||
|
||||
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 ADL()
|
||||
{
|
||||
ADL_Series QL = new(bars, false);
|
||||
var SK = quotes.GetAdl().Select(i => i.Adl);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ALMA()
|
||||
{
|
||||
ALMA_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetAlma(period).Select(i => i.Alma.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ATR()
|
||||
{
|
||||
ATR_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetAtr(period).Select(i => i.Atr.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ATRP()
|
||||
{
|
||||
ATRP_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetAtr(period).Select(i => i.Atrp.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void BBANDS()
|
||||
{
|
||||
BBANDS_Series QL = new(bars.Close, period, 2.0, useNaN: false);
|
||||
var SK = quotes.GetBollingerBands(period, 2.0);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL.Mid[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1).Sma!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Upper[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).UpperBand!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Lower[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).LowerBand!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Bandwidth[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).Width!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.PercentB[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).PercentB!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Zscore[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).ZScore!.Value, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void CCI()
|
||||
{
|
||||
CCI_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetCci(period).Select(i => i.Cci.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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).Select(i => i.Correlation.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void COVAR()
|
||||
{
|
||||
COVAR_Series QL = new(bars.High, bars.Low, period, false);
|
||||
var SK = quotes.Use(CandlePart.High).GetCorrelation(quotes.Use(CandlePart.Low), period).Select(i => i.Covariance.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact]
|
||||
public void DEMA()
|
||||
{
|
||||
DEMA_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetDema(period).Select(i => i.Dema.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact]
|
||||
public void EMA()
|
||||
{
|
||||
EMA_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetEma(period).Select(i => i.Ema.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact]
|
||||
public void HL2()
|
||||
{
|
||||
TSeries QL = bars.HL2;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.HL2).Select(i => i.Value);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void HLC3()
|
||||
{
|
||||
TSeries QL = bars.HLC3;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.HLC3).Select(i => i.Value);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact]
|
||||
public void HMA()
|
||||
{
|
||||
HMA_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetHma(period).Select(i => i.Hma.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact]
|
||||
public void KAMA()
|
||||
{
|
||||
// TODO: check precision of KAMA()
|
||||
KAMA_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetKama(period).Select(i => i.Kama.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits/2), Math.Exp(-digits/2));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact]
|
||||
public void LINREG()
|
||||
{
|
||||
LINREG_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetSlope(period);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1).Slope!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Intercept[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).Intercept!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.RSquared[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).RSquared!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.StdDev[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round((double)SK.ElementAt(i - 1).StdDev!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MACD()
|
||||
{
|
||||
MACD_Series QL = new(bars.Close, 26, 12, 9, useNaN: false);
|
||||
var SK = quotes.GetMacd(12, 26, 9);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1).Macd.Null2NaN()!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Signal[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round(SK.ElementAt(i - 1).Signal.Null2NaN()!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MAD()
|
||||
{
|
||||
MAD_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mad.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MAMA()
|
||||
{
|
||||
MAMA_Series QL = new(bars.HL2, fastlimit: 0.5, slowlimit: 0.05);
|
||||
var SK = quotes.GetMama(fastLimit: 0.5, slowLimit: 0.05);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1).Mama.Null2NaN()!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Fama[i - 1].v, digits: digits);
|
||||
SK_item = Math.Round(SK.ElementAt(i - 1).Fama.Null2NaN()!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MAPE()
|
||||
{
|
||||
MAPE_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mape.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MSE()
|
||||
{
|
||||
MSE_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mse.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void OBV()
|
||||
{
|
||||
OBV_Series QL = new(bars, period, false);
|
||||
var SK = quotes.GetObv(period).Select(i => i.Obv!);
|
||||
// adding volume[0] to OBV to pass the test and keep compatibility with TA-LIB
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL.Last().v, digits: digits);
|
||||
double SK_item = Math.Round(SK.Last()! + (double)quotes.First().Volume!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact]
|
||||
public void OC2()
|
||||
{
|
||||
TSeries QL = bars.OC2;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OC2).Select(i => i.Value);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void OHL3()
|
||||
{
|
||||
TSeries QL = bars.OHL3;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OHL3).Select(i => i.Value);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void OHLC4()
|
||||
{
|
||||
TSeries QL = bars.OHLC4;
|
||||
var SK = quotes.GetBaseQuote(CandlePart.OHLC4).Select(i => i.Value);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round((double)SK.ElementAt(i - 1)!, digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact]
|
||||
public void RSI()
|
||||
{
|
||||
RSI_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetRsi(period).Select(i => i.Rsi.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void SDEV()
|
||||
{
|
||||
SDEV_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetStdDev(period).Select(i => i.StdDev.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void SMA()
|
||||
{
|
||||
SMA_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetSma(period).Select(i => i.Sma.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void SMMA()
|
||||
{
|
||||
SMMA_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetSmma(period).Select(i => i.Smma.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[Fact]
|
||||
public void T3()
|
||||
{
|
||||
T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, false);
|
||||
var SK = quotes.GetT3(lookbackPeriods: period, volumeFactor: 0.7).Select(i => i.T3.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
*/
|
||||
[Fact]
|
||||
public void TEMA()
|
||||
{
|
||||
TEMA_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetTema(period).Select(i => i.Tema.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void TR()
|
||||
{
|
||||
TR_Series QL = new(bars, useNaN: false);
|
||||
var SK = quotes.GetTr().Select(i => i.Tr.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void WMA()
|
||||
{
|
||||
WMA_Series QL = new(bars.Close, period, false);
|
||||
var SK = quotes.GetWma(period).Select(i => i.Wma.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ZSCORE()
|
||||
{
|
||||
ZSCORE_Series QL = new(bars.Close, period, useNaN: false);
|
||||
var SK = quotes.GetStdDev(period).Select(i => i.ZScore.Null2NaN()!);
|
||||
for (int i = QL.Length; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i - 1].v, digits: digits);
|
||||
double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
|
||||
Assert.InRange(SK_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,452 @@
|
||||
using Xunit;
|
||||
using System;
|
||||
using TALib;
|
||||
using QuanTAlib;
|
||||
|
||||
namespace Validations;
|
||||
public class Ta_Lib
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, digits, skip;
|
||||
private readonly double[] TALIB;
|
||||
private readonly double[] TALIB2;
|
||||
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(Bars: 5000, Volatility: 0.8, Drift: 0.0, Precision: 3);
|
||||
period = rnd.Next(28) + 3;
|
||||
skip = 500;
|
||||
digits = 10;
|
||||
|
||||
TALIB = new double[bars.Count];
|
||||
TALIB2 = 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 _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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 _);
|
||||
for (int i = QL.Length - 1; i > 0; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ADOSC()
|
||||
{
|
||||
ADOSC_Series QL = new(bars, 3, 10, false);
|
||||
Core.AdOsc(inhigh, inlow, inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip * 15; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
/*
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL.Upper[i].v, digits: digits);
|
||||
double TA_item = Math.Round(outUpper[i - outBegIdx], digits: digits);
|
||||
Assert.Equal(TA_item!, QL_item);
|
||||
QL_item = Math.Round(QL.Mid[i].v, digits: digits);
|
||||
TA_item = Math.Round(outMiddle[i - outBegIdx], digits: digits);
|
||||
Assert.Equal(TA_item!, QL_item);
|
||||
QL_item = Math.Round(QL.Lower[i].v, digits: digits);
|
||||
TA_item = Math.Round(outLower[i - outBegIdx], digits: digits);
|
||||
Assert.Equal(TA_item!, QL_item);
|
||||
}
|
||||
Assert.Equal(Math.Round(outUpper[outUpper.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Upper.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Mid.Last().v, digits: digits));
|
||||
Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], digits: digits), Math.Round(QL.Lower.Last().v, digits: digits));
|
||||
}
|
||||
*/
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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 _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void HL2()
|
||||
{
|
||||
TSeries QL = bars.HL2;
|
||||
Core.MedPrice(inhigh, inlow, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void HLC3()
|
||||
{
|
||||
TSeries QL = bars.HLC3;
|
||||
Core.TypPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void HLCC4()
|
||||
{
|
||||
TSeries QL = bars.HLCC4;
|
||||
Core.WclPrice(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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 _);
|
||||
for (int i = QL.Length - 1; i > skip * 10; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.Equal(TA_item!, QL_item);
|
||||
QL_item = Math.Round(QL.Signal[i].v, digits: digits);
|
||||
TA_item = Math.Round(macdSignal[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void MAMA()
|
||||
{
|
||||
MAMA_Series QL = new(bars.Close, fastlimit: 0.5, slowlimit: 0.05);
|
||||
Core.Mama(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outMama: TALIB, outFama: TALIB2, outBegIdx: out int outBegIdx, outNbElement: out _, optInFastLimit: 0.5, optInSlowLimit: 0.05);
|
||||
for (int i = QL.Length - 1; i > skip * 15; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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 _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void OBV()
|
||||
{
|
||||
OBV_Series QL = new(bars, period, false);
|
||||
Core.Obv(inclose, involume, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void OHLC4()
|
||||
{
|
||||
TSeries QL = bars.OHLC4;
|
||||
Core.AvgPrice(inopen, inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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 _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void T3()
|
||||
{
|
||||
T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, useNaN: false);
|
||||
Core.T3(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outReal: TALIB, outBegIdx: out int outBegIdx, outNbElement: out _, optInTimePeriod: period, optInVFactor: 0.7);
|
||||
for (int i = QL.Length - 1; i > skip * 15; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip * 15; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void TR()
|
||||
{
|
||||
TR_Series QL = new(bars, false);
|
||||
Core.TRange(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip * 15; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[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);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
|
||||
Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,158 @@
|
||||
using Xunit;
|
||||
using System;
|
||||
using Tulip;
|
||||
using QuanTAlib;
|
||||
|
||||
namespace Validations;
|
||||
public class Tulip_Test
|
||||
{
|
||||
private readonly GBM_Feed bars;
|
||||
private readonly Random rnd = new();
|
||||
private readonly int period, digits, skip;
|
||||
private readonly double[] outdata;
|
||||
private readonly double[] inopen;
|
||||
private readonly double[] inhigh;
|
||||
private readonly double[] inlow;
|
||||
private readonly double[] inclose;
|
||||
private readonly double[] involume;
|
||||
|
||||
public Tulip_Test()
|
||||
{
|
||||
bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0, Precision: 3);
|
||||
period = rnd.Next(28) + 3;
|
||||
skip = 200;
|
||||
digits = 10;
|
||||
|
||||
outdata = 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 AD()
|
||||
{
|
||||
double[][] arrin = {inhigh, inlow, inclose, involume };
|
||||
double[][] arrout = { outdata };
|
||||
ADL_Series QL = new(bars, false);
|
||||
Tulip.Indicators.ad.Run(inputs: arrin, options: new double[] { }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ADD()
|
||||
{
|
||||
double[][] arrin = { inhigh, inlow };
|
||||
double[][] arrout = { outdata };
|
||||
ADD_Series QL = new(bars.High, bars.Low);
|
||||
Tulip.Indicators.add.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ADOSC()
|
||||
{
|
||||
double[][] arrin = { inhigh, inlow, inclose, involume };
|
||||
double[][] arrout = { outdata };
|
||||
int s = 3;
|
||||
ADOSC_Series QL = new(bars, s, period, false);
|
||||
Tulip.Indicators.adosc.Run(inputs: arrin, options: new double[] { s, period }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i-period+1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void ATR()
|
||||
{
|
||||
double[][] arrin = { inhigh, inlow, inclose };
|
||||
double[][] arrout = { outdata };
|
||||
|
||||
ATR_Series QL = new(bars, period, false);
|
||||
Tulip.Indicators.atr.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i - period + 1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void BBANDS()
|
||||
{
|
||||
double[][] arrin = { inclose };
|
||||
double[] outmid = new double[bars.Count];
|
||||
double[] outlower = new double[bars.Count];
|
||||
double[] outupper = new double[bars.Count];
|
||||
double[][] arrout = { outlower, outmid, outupper};
|
||||
BBANDS_Series QL = new(bars.Close, period, 2, false);
|
||||
Tulip.Indicators.bbands.Run(inputs: arrin, options: new double[] { period, 2 }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL.Lower[i].v, digits: digits);
|
||||
double TU_item = Math.Round(outlower[i - period + 1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Mid[i].v, digits: digits);
|
||||
TU_item = Math.Round(outmid[i - period + 1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
QL_item = Math.Round(QL.Upper[i].v, digits: digits);
|
||||
TU_item = Math.Round(outupper[i - period + 1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void EMA()
|
||||
{
|
||||
double[][] arrin = { inclose };
|
||||
double[][] arrout = { outdata };
|
||||
EMA_Series QL = new(bars.Close, period, false);
|
||||
Tulip.Indicators.ema.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void AVGPRICE()
|
||||
{
|
||||
double[][] arrin = { inopen, inhigh, inlow, inclose };
|
||||
double[][] arrout = { outdata };
|
||||
|
||||
TSeries QL = bars.OHLC4;
|
||||
Tulip.Indicators.avgprice.Run(inputs: arrin, options: new double[] { }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
[Fact]
|
||||
public void SMA()
|
||||
{
|
||||
double[][] arrin = { inclose };
|
||||
double[][] arrout = { outdata };
|
||||
SMA_Series QL = new(bars.Close, period, false);
|
||||
Tulip.Indicators.sma.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
|
||||
for (int i = QL.Length - 1; i > skip; i--)
|
||||
{
|
||||
double QL_item = Math.Round(QL[i].v, digits: digits);
|
||||
double TU_item = Math.Round(arrout[0][i-period+1], digits);
|
||||
Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
|
||||
}
|
||||
}
|
||||
}
|
||||
+38
@@ -0,0 +1,38 @@
|
||||
# EMA: Exponential Moving Average
|
||||
|
||||
EMA needs very short history buffer and calculates the EMA value using just the previous EMA value. The weight of the new datapoint (k) is k = 2 / (period-1)
|
||||
|
||||
## Calculation
|
||||
|
||||
There is an adopted practice to calculate $SMA$ when $n < period$.
|
||||
|
||||
$$
|
||||
EMA_n = \left\{ \begin{array}{cl}
|
||||
\frac{1}{p}\left( data_{n}-data_{n-p}\right)+SMA_{n-1} & : \ n \leq period \\
|
||||
{k}\times ({data_{n}} - EMA_{n-1}) + EMA_{n-1} & : \ x > period
|
||||
\end{array} \right.
|
||||
$$
|
||||
|
||||
|
||||
## Implementation
|
||||
|
||||
``` csharp
|
||||
EMA_Series mean = new(source: data, period: p, useNaN: false);
|
||||
```
|
||||
|
||||
- `TSeries source` - List of value tuples (DateTime, double)
|
||||
- `int period` - Integer representing the period of SMA
|
||||
- `bool useNaN` - if true, initial values from 1 to period-1 will be replaced with NaN. If false, the initial calculation will return values for SMA(length) instead of SMA(period)
|
||||
|
||||
## Comparison & Validation
|
||||
|
||||
Validation tests
|
||||
Performance tests
|
||||
|
||||
## Visual analysis
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
## References
|
||||
+39
@@ -0,0 +1,39 @@
|
||||
|
||||
# SMA: Simple Moving Average
|
||||
SMA is one of the most basic trend-following indicators used in Technical Analysis. It is calculated as the *unweighted mean* of the previous $p$ (period) data-points.
|
||||
|
||||
|
||||
## Calculation
|
||||
|
||||
SMA is a rolling calculation looking backwards from the position ${n}$ and is denoted as ${SMA}_{p}{(data)}$ where $p$ represents the period and $data$ represents the list of data points:
|
||||
$$
|
||||
SMA_p{(data)} = \frac{1}{p}\sum_{i=n-p+1}^{n} data_i
|
||||
$$
|
||||
When calculating the value of next $SMA_{p,next}$ while knowing all previous SMA values, SMA calculation can be reduced to:
|
||||
$$
|
||||
SMA_{p,next} = SMA_{p,prev}+\frac{1}{p}\left( data_{n+1}-data_{n+1-p}\right)
|
||||
$$
|
||||
|
||||
## Implementation
|
||||
|
||||
``` csharp
|
||||
SMA_Series mean = new(source: data, period: p, useNaN: false);
|
||||
```
|
||||
|
||||
- `TSeries source` - List of value tuples (DateTime, double)
|
||||
- `int period` - Integer representing the period of SMA
|
||||
- `bool useNaN` - if true, initial values from 1 to period-1 will be replaced with NaN. If false, the initial calculation will return values for SMA(length) instead of SMA(period)
|
||||
|
||||
## Comparison & Validation
|
||||
|
||||
Validation tests
|
||||
Performance tests
|
||||
|
||||
## Visual analysis
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
## References
|
||||
- https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/simple-moving-average-sma/
|
||||
@@ -0,0 +1,13 @@
|
||||
* [Home](/)
|
||||
|
||||
* [Indicators](indicators.md "Indocators coverage")
|
||||
|
||||
* [SMA - Simple Moving Average](SMA.md "SMA - Simple Moving Average")
|
||||
* [WMA - Weighted Moving Average](WMA.md "WMA - Weighted Moving Average")
|
||||
* [EMA - Exponential Moving Average](EMA.md "EMA - Exponential Moving Average")
|
||||
* [DEMA - Double Exponential Moving Average](DEMA.md "DEMA - Double Exponential Moving Average")
|
||||
* [TEMA - Triple Exponential Moving Average](TEMA.md "TEMA - Triple Exponential Moving Average")
|
||||
* [HMA - Hull Moving Average](HMA.md "HMA - Hull Moving Average")
|
||||
* [ZLEMA - Zero-Lag Exponential Moving Average](ZLEMA.md "ZLEMA - Zero-Lag Exponential Moving Average")
|
||||
* [KAMA - Kaufman Adaptive Moving Average](KAMA.md "KAMA - Kaufman Adaptive Moving Average")
|
||||
* [MAMA - Mesa Adaptive Moving Average](MAMA.md "MAMA - Mesa Adaptive Moving Average")
|
||||
File diff suppressed because one or more lines are too long
+93
-101
@@ -2,7 +2,14 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"# Quick Start\n",
|
||||
"\n",
|
||||
@@ -17,35 +24,16 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div><div></div><div></div><div></div></div>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"ename": "Error",
|
||||
"evalue": "(3,1): error CS0246: The type or namespace name 'Yahoo_Feed' could not be found (are you missing a using directive or an assembly reference?)\r\n(10,15): error CS0019: Operator '<' cannot be applied to operands of type 'int' and 'method group'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"(3,1): error CS0246: The type or namespace name 'Yahoo_Feed' could not be found (are you missing a using directive or an assembly reference?)\r\n",
|
||||
"(10,15): error CS0019: Operator '<' cannot be applied to operands of type 'int' and 'method group'"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"#r \"nuget:QuanTAlib;\"\n",
|
||||
"using QuanTAlib;\n",
|
||||
@@ -63,7 +51,14 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Understanding QuanTAlib data model\n",
|
||||
"\n",
|
||||
@@ -72,26 +67,16 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<table><thead><tr><th><i>index</i></th><th>Item1</th><th>Item2</th></tr></thead><tbody><tr><td>0</td><td><span>2022-11-10 00:00:00Z</span></td><td><div class=\"dni-plaintext\">105.3</div></td></tr><tr><td>1</td><td><span>2022-11-10 15:47:46Z</span></td><td><div class=\"dni-plaintext\">293.1</div></td></tr><tr><td>2</td><td><span>2022-11-10 15:47:46Z</span></td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>3</td><td><span>2022-11-07 15:47:46Z</span></td><td><div class=\"dni-plaintext\">10</div></td></tr></tbody></table>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"var item1 = (DateTime.Today, 105.3); // (DateTime, Value) tuple\n",
|
||||
"double item2 = 293.1; // a simple double\n",
|
||||
@@ -107,66 +92,60 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"TSeries list can display only values (without timestamps) or only timestamps (without values) by using `.v` or `.t` properties"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<table><thead><tr><th><i>index</i></th><th>value</th></tr></thead><tbody><tr><td>0</td><td><div class=\"dni-plaintext\">105.3</div></td></tr><tr><td>1</td><td><div class=\"dni-plaintext\">293.1</div></td></tr><tr><td>2</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>3</td><td><div class=\"dni-plaintext\">10</div></td></tr></tbody></table>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"data.v"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"The last element on the list can be accessed by .Last() or by [^1] - and using `.t` (time) and `.v` (value) properties. Also, casting a TSeries into (double) will return the value of the last element"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div class=\"dni-plaintext\">10</div>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"bool IsTheSame = data.Last().v == data[^1].v;\n",
|
||||
"double lastvalue = data;\n",
|
||||
@@ -176,33 +155,30 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"All indicators are just modified TSeries classes; they get all required input during class construction (source of the datafeed, period...) and they automatically subscribe to events of the datafeed. Whenever datafeed gets a new value, indicator will calculate its own value. Indicators are also event publishers, so other indicators can subscribe to their results, chaining indicators together:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<table><thead><tr><th><i>index</i></th><th>value</th></tr></thead><tbody><tr><td>0</td><td><div class=\"dni-plaintext\">Infinity</div></td></tr><tr><td>1</td><td><div class=\"dni-plaintext\">0.6666666666666666</div></td></tr><tr><td>2</td><td><div class=\"dni-plaintext\">0.3333333333333333</div></td></tr><tr><td>3</td><td><div class=\"dni-plaintext\">0.2</div></td></tr><tr><td>4</td><td><div class=\"dni-plaintext\">0.14285714285714285</div></td></tr><tr><td>5</td><td><div class=\"dni-plaintext\">0.1111111111111111</div></td></tr><tr><td>6</td><td><div class=\"dni-plaintext\">0.09090909090909091</div></td></tr><tr><td>7</td><td><div class=\"dni-plaintext\">0.07692307692307693</div></td></tr><tr><td>8</td><td><div class=\"dni-plaintext\">0.06666666666666667</div></td></tr><tr><td>9</td><td><div class=\"dni-plaintext\">0.058823529411764705</div></td></tr><tr><td>10</td><td><div class=\"dni-plaintext\">0.25</div></td></tr></tbody></table>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"TSeries t1 = new() {0,1,2,3,4,5,6,7,8,9}; // t1 is loaded with data and activated as a publisher\n",
|
||||
"EMA_Series t2 = new(t1, 3); // t2 will auto-load all history of t1 and wait for events from t1\n",
|
||||
@@ -218,7 +194,14 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"# MACD compounded indicator\n",
|
||||
"\n",
|
||||
@@ -227,26 +210,16 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"vscode": {
|
||||
"languageId": "dotnet-interactive.csharp"
|
||||
"languageId": "polyglot-notebook"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<table><thead><tr><th><i>index</i></th><th>value</th></tr></thead><tbody><tr><td>0</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>1</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>2</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>3</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>4</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>5</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>6</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>7</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>8</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>9</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>10</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>11</td><td><div class=\"dni-plaintext\">0</div></td></tr><tr><td>12</td><td><div class=\"dni-plaintext\">0.13543589743590018</div></td></tr><tr><td>13</td><td><div class=\"dni-plaintext\">-0.03897954353340993</div></td></tr><tr><td>14</td><td><div class=\"dni-plaintext\">-0.17731008431411102</div></td></tr><tr><td>15</td><td><div class=\"dni-plaintext\">-0.24030671152304095</div></td></tr><tr><td>16</td><td><div class=\"dni-plaintext\">-0.08247055673614988</div></td></tr><tr><td>17</td><td><div class=\"dni-plaintext\">-0.47898448490240814</div></td></tr><tr><td>18</td><td><div class=\"dni-plaintext\">-0.9020715041856615</div></td></tr><tr><td>19</td><td><div class=\"dni-plaintext\">-1.3489730137363423</div></td></tr><tr><td colspan=\"2\"><i>(51 more)</i></td></tr></tbody></table>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"Yahoo_Feed aapl = new(\"AAPL\", 100);\n",
|
||||
"TSeries close = aapl.Close; // close will get data from history\n",
|
||||
@@ -266,14 +239,33 @@
|
||||
"language": "C#",
|
||||
"name": ".net-csharp"
|
||||
},
|
||||
"language_info": {
|
||||
"file_extension": ".cs",
|
||||
"mimetype": "text/x-csharp",
|
||||
"name": "C#",
|
||||
"pygments_lexer": "csharp",
|
||||
"version": "9.0"
|
||||
},
|
||||
"orig_nbformat": 4
|
||||
"polyglot_notebook": {
|
||||
"kernelInfo": {
|
||||
"defaultKernelName": "csharp",
|
||||
"items": [
|
||||
{
|
||||
"aliases": [
|
||||
"c#",
|
||||
"C#"
|
||||
],
|
||||
"languageName": "C#",
|
||||
"name": "csharp"
|
||||
},
|
||||
{
|
||||
"aliases": [
|
||||
"frontend"
|
||||
],
|
||||
"languageName": null,
|
||||
"name": "vscode"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"languageName": "KQL",
|
||||
"name": "kql"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
|
||||
@@ -0,0 +1,251 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div><div></div><div></div><div></div></div>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Loading extensions from `C:\\Users\\miha\\.nuget\\packages\\plotly.net.interactive\\3.0.2\\interactive-extensions\\dotnet\\Plotly.NET.Interactive.dll`"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"//#r \"nuget: QuanTAlib;\"\n",
|
||||
"\n",
|
||||
"#r \"nuget: Plotly.NET;\"\n",
|
||||
"#r \"nuget: Plotly.NET.Interactive;\"\n",
|
||||
"#r \"nuget: Plotly.NET.ImageExport;\"\n",
|
||||
"#r \"..\\..\\Source\\bin\\Debug\\net6.0\\QuanTAlib.dll\"\n",
|
||||
"\n",
|
||||
"using QuanTAlib;\n",
|
||||
"using Plotly.NET;\n",
|
||||
"using Plotly.NET.LayoutObjects;\n",
|
||||
"using Plotly.NET.ImageExport;"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"TSeries d1a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};\n",
|
||||
"TSeries d2a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1};\n",
|
||||
"TSeries d3a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};\n",
|
||||
"TSeries d4a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2};\n",
|
||||
"TSeries d5a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0.32,0.56,0.72,0.84,0.93,0.99,1,0.97,0.91,0.81,0.68,0.52,0.33,0.14,-0.06,-0.26,-0.44,-0.61,-0.76,-0.87,-0.95,-0.99,-1,-0.96,-0.88,-0.77,-0.63,-0.46,-0.28,-0.08,0.12,0.31,0.49,0.66,0.79,0.9,0.97,1,0.99,0.94,0.85,0.73,0.58,0.41,0.22,0.02,-0.17,-0.37,-0.54,-0.7,-0.83,-0.92,-0.98,-1,-0.98,-0.92,-0.82,-0.69,-0.54,-0.36,-0.17,0.03,0.23,0.42,0.59,0.74};\n",
|
||||
"TSeries d6a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1};\n",
|
||||
"TSeries d7a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0.93,0.27,-0.59,-1,-0.71,0.05,0.75,1,0.67,0,-0.67,-0.99,-0.85,-0.34,0.31,0.81,1,0.82,0.35,-0.22,-0.71,-0.98,-0.95,-0.66,-0.2,0.31,0.72,0.96,0.98,0.78,0.43,-0.01,-0.43,-0.77,-0.96,-0.99,-0.85,-0.58,-0.23,0.16,0.51,0.79,0.95,1,0.92,0.73,0.47,0.15,-0.17,-0.47,-0.72,-0.9,-0.99,-0.99,-0.9,-0.74,-0.52,-0.26,0.01,0.28,0.53,0.73,0.88,0.97,1,0.97};\n",
|
||||
"TSeries d8a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,0.03,-0.4,-0.47,0.19,-0.4,-0.23,0.31,0.41,0.19,0.16,-0.5,-0.31,-0.21,0.25,0.18,-0.48,-0.1,0.38,0.29,-0.38,-0.08,-0.21,0.34,0.01,-0.46,0.28,-0.48,0.11,0.02,-0.37,0.19,-0.2,0.1,0.24,0.08,-0.22,-0.12,0.15,0.36,-0.43,-0.03,-0.32,0.45,-0.5,-0.04,-0.04,-0.08,-0.18,0.13,-0.33,-0.19,0.36,-0.39,0.2,-0.31,0.28,-0.13,-0.07,-0.29,0.37,0.03,-0.25,-0.06,-0.3,-0.08,-0.09};\n",
|
||||
"TSeries d9a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,0,0.03,0.11,-0.1,-0.43,-0.08,0.36,-0.04,-0.04,-0.21,-0.3,0.26,0.2,0.28,0.2,0.27,-0.01,-0.1,-0.23,-0.13,-0.41,-0.23,-0.07,-0.21,0.32,-0.18,-0.48,0.3,0.46,-0.2,0.52,-0.81,-0.25,-0.21,-0.12,-0.18,0.18,0.52,0.29,0.44,0.18,-1.2,0.38,0.24,0.06,0.28,0.34,0.3,-0.13,0.19,-0.5,0.59,-0.36,0.22,-0.23,0.24,0.39,0.13,-0.33,-0.57,-0.23,0.49,-0.13,0.76,0.59,0.61};\n",
|
||||
"TSeries d10a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0,-0.28,0.41,-0.54,0.65,-0.75,0.84,-0.91,0.96,-0.99,1,-0.99,0.96,-0.92,0.85,-0.77,0.67,-0.56,0.44,-0.3,0.17,-0.03,-0.11,0.25,-0.39,0.51,-0.63,0.73,-0.82,0.89,-0.95,0.98,-1,0.99,-0.97,0.93,-0.86,0.78,-0.69,0.58,-0.46,0.33,-0.19,0.05,0.09,-0.23,0.36,-0.49,0.61,-0.71,0.81,-0.88,0.94,-0.98,1,-1,0.98,-0.94,0.88,-0.8,0.71,-0.6,0.48,-0.35,0.22,-0.08,-0.06};\n",
|
||||
"TSeries d11a = new() {-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,0,0.14,-0.76,-0.96,-0.28,0.66,0.99,0.41,-0.54,-1,-0.54,0.42,0.99,0.65,-0.29,-0.96,-0.75,0.15,0.91,0.84,-0.01,-0.85,-0.91,-0.13,0.76,0.96,0.27,-0.66,-0.99,-0.4,0.55,1,0.53,-0.43,-0.99,-0.64,0.3,0.96,0.75,-0.16,-0.92,-0.83,0.02,0.85,0.9,0.12,-0.77,-0.95,-0.26,0.67,0.99,0.4,-0.56,-1,-0.52,0.44,0.99,0.64,-0.3,-0.97,-0.74,0.17,0.92,0.83,-0.03,-0.86};\n",
|
||||
"TSeries d12a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,0.05,-0.25,-0.32,-0.09,0.22,0.33,0.14,-0.18,-0.33,-0.18,0.14,0.33,0.22,-0.1,-0.32,-0.25,0.05,0.3,0.28,0,-0.28,-0.3,-0.04,0.25,0.32,0.09,-0.22,-0.33,-0.13,0.18,0.33,0.18,0.86,0.67,0.79,1.1,1.32,1.25,0.95,0.69,0.72,1.01,1.28,1.3,1.04,0.74,0.68,0.91,1.22,1.33,1.13,0.81,0.67,0.83,1.15,1.33,1.21,0.9,0.68,0.75,1.06,1.31,1.28,0.99,0.71};\n",
|
||||
"TSeries d13a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,2.7,-0.8,-0.8,3.6,9.3,11.95,10.05,6.3,5,8.3,14.1,17.95,17.25,13.55,11.2,13.25,18.75,23.55,24.2,20.95,17.75,18.45,23.35,28.8,30.8,28.35,24.7,24.05,28,33.75,37,35.65,31.85,28.05,-3.2,1.5,4.8,3.75,-0.8,-4.6,-4.15,0.1,4.25,4.5,0.6,-3.85,-4.75,-1.3,3.35,4.95,2,-2.8,-5,-2.6,2.2,4.95,3.2,-1.5,-4.85,-3.7,0.85,4.6,4.15,-0.15,-4.3};\n",
|
||||
"TSeries d14a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,0.59,0.83,0.74,0.5,0.91,1.36,0.93,0.87,0.6,0.38,0.78,0.53,0.42,0.14,0.01,-0.45,-0.71,-0.99,-1,-1.36,-1.22,-1.07,-1.17,-0.56,-0.95,-1.11,-0.16,0.18,-0.28,0.64,-0.5,0.24,0.45,0.67,0.72,1.15,1.52,1.28,1.38,1.03,-0.47,0.96,0.65,0.28,0.3,0.17,-0.07,-0.67,-0.51,-1.33,-0.33,-1.34,-0.78,-1.21,-0.68,-0.43,-0.56,-0.87,-0.93,-0.4,0.52,0.1,1.18,1.18,1.35};\n",
|
||||
"TSeries d15a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1.3,0.3,-0.48,-1.1,-1.14,-0.03,1.11,0.96,0.63,-0.21,-0.97,-0.73,-0.65,-0.06,0.51,1.08,0.99,0.72,0.12,-0.35,-1.12,-1.21,-1.02,-0.87,0.12,0.13,0.24,1.26,1.44,0.58,0.95,-0.82,-0.68,-0.98,-1.08,-1.17,-0.67,-0.06,0.06,0.6,0.69,-0.41,1.33,1.24,0.98,1.01,0.81,0.45,-0.3,-0.28,-1.22,-0.31,-1.35,-0.77,-1.13,-0.5,-0.13,-0.13,-0.32,-0.29,0.3,1.22,0.75,1.73,1.59,1.58};\n",
|
||||
"TSeries d16a = new() {175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.44,176.27,176.04,176.99,175.49,175.68,174.34,176.4,174.05,174.4,174.2,176.16,175,177.72,174.33,176.96,174.62,174.76,170.9,171.12,171.05,170.01,169.24,172.64,171.96,175.72,174.16,175.81,177.3,178.38,176.75,177.19,175.55,178.49,176.52,178.45,178.04,178.25,177.8,176.97,172.94,174.92,173.98,172.29,171.19,172.54,172.11,175.32,175.63,176.65,173.8,176.04,172.74,175.24,171.84,171.54,172.17,171.85,172.38,170.78,173.49,173.69,171.71,174.38,173.99,174.83};"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"int period = 10;\n",
|
||||
"int cut = 26;\n",
|
||||
"\n",
|
||||
"EMA_Series d1b = new(d1a, period);\n",
|
||||
"EMA_Series d2b = new(d2a, period);\n",
|
||||
"EMA_Series d3b = new(d3a, period);\n",
|
||||
"EMA_Series d4b = new(d4a, period);\n",
|
||||
"EMA_Series d5b = new(d5a, period);\n",
|
||||
"EMA_Series d6b = new(d6a, period);\n",
|
||||
"EMA_Series d7b = new(d7a, period);\n",
|
||||
"EMA_Series d8b = new(d8a, period);\n",
|
||||
"EMA_Series d9b = new(d9a, period);\n",
|
||||
"EMA_Series d10b = new(d10a, period);\n",
|
||||
"EMA_Series d11b = new(d11a, period);\n",
|
||||
"EMA_Series d12b = new(d12a, period);\n",
|
||||
"EMA_Series d13b = new(d13a, period);\n",
|
||||
"EMA_Series d14b = new(d14a, period);\n",
|
||||
"EMA_Series d15b = new(d15a, period);\n",
|
||||
"EMA_Series d16b = new(d16a, period);\n",
|
||||
"\n",
|
||||
"List<int> x = Enumerable.Range(-cut,96).ToList<int>();\n",
|
||||
"GenericChart.GenericChart ch1a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d1a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch1b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d1b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch2a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d2a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch2b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d2b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch3a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d3a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch3b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d3b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch4a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d4a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch4b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d4b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch5a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d5a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch5b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d5b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch6a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d6a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch6b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d6b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch7a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d7a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch7b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d7b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch8a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d8a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch8b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d8b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch9a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d9a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch9b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d9b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch10a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d10a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch10b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d10b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch11a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d11a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch11b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d11b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch12a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d12a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch12b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d12b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch13a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d13a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch13b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d13b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch14a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d14a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch14b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d14b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch15a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d15a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch15b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d15b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch16a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d16a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch16b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d16b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"\n",
|
||||
"var ch1 = Chart.Combine(new []{ch1a,ch1b});\n",
|
||||
"var ch2 = Chart.Combine(new []{ch2a,ch2b});\n",
|
||||
"var ch3 = Chart.Combine(new []{ch3a,ch3b});\n",
|
||||
"var ch4 = Chart.Combine(new []{ch4a,ch4b});\n",
|
||||
"var ch5 = Chart.Combine(new []{ch5a,ch5b});\n",
|
||||
"var ch6 = Chart.Combine(new []{ch6a,ch6b});\n",
|
||||
"var ch7 = Chart.Combine(new []{ch7a,ch7b});\n",
|
||||
"var ch8 = Chart.Combine(new []{ch8a,ch8b});\n",
|
||||
"var ch9 = Chart.Combine(new []{ch9a,ch9b});\n",
|
||||
"var ch10 = Chart.Combine(new []{ch10a,ch10b});\n",
|
||||
"var ch11 = Chart.Combine(new []{ch11a,ch11b});\n",
|
||||
"var ch12 = Chart.Combine(new []{ch12a,ch12b});\n",
|
||||
"var ch13 = Chart.Combine(new []{ch13a,ch13b});\n",
|
||||
"var ch14 = Chart.Combine(new []{ch14a,ch14b});\n",
|
||||
"var ch15 = Chart.Combine(new []{ch15a,ch15b});\n",
|
||||
"var ch16 = Chart.Combine(new []{ch16a,ch16b});\n",
|
||||
"\n",
|
||||
"Layout layout = new Layout(); layout.SetValue(\"showlegend\",false);\n",
|
||||
"var chart1 = new []{ch1,ch2,ch3,ch4,ch5,ch6,ch7,ch8,ch9,ch10,ch11,ch12,ch13,ch14,ch15,ch16};\n",
|
||||
"var full = Chart.Grid<IEnumerable<GenericChart.GenericChart>>(8,2).Invoke(chart1).WithSize(1000,2200).WithMargin(Margin.init<int, int, int, int, int, bool>(30,20,20,30,7,false)).WithLayout(layout);\n",
|
||||
"full.SaveSVG(\"EMA_chart\", Width: 1000, Height: 2200);"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".NET (C#)",
|
||||
"language": "C#",
|
||||
"name": ".net-csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelInfo": {
|
||||
"defaultKernelName": "csharp",
|
||||
"items": [
|
||||
{
|
||||
"aliases": [
|
||||
"c#",
|
||||
"C#"
|
||||
],
|
||||
"languageName": "C#",
|
||||
"name": "csharp"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"name": ".NET"
|
||||
},
|
||||
{
|
||||
"aliases": [
|
||||
"f#",
|
||||
"F#"
|
||||
],
|
||||
"languageName": "F#",
|
||||
"name": "fsharp"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"languageName": "HTML",
|
||||
"name": "html"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"languageName": "KQL",
|
||||
"name": "kql"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"languageName": "Mermaid",
|
||||
"name": "mermaid"
|
||||
},
|
||||
{
|
||||
"aliases": [
|
||||
"powershell"
|
||||
],
|
||||
"languageName": "PowerShell",
|
||||
"name": "pwsh"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"languageName": "SQL",
|
||||
"name": "sql"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"name": "value"
|
||||
},
|
||||
{
|
||||
"aliases": [
|
||||
"frontend"
|
||||
],
|
||||
"name": "vscode"
|
||||
},
|
||||
{
|
||||
"aliases": [
|
||||
"js"
|
||||
],
|
||||
"languageName": "JavaScript",
|
||||
"name": "javascript"
|
||||
},
|
||||
{
|
||||
"aliases": [],
|
||||
"name": "webview"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
|
After Width: | Height: | Size: 154 KiB |
@@ -0,0 +1,242 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div><div></div><div></div><div></div></div>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"//#r \"nuget: QuanTAlib;\"\n",
|
||||
"\n",
|
||||
"#r \"nuget: Plotly.NET;\"\n",
|
||||
"#r \"nuget: Plotly.NET.Interactive;\"\n",
|
||||
"#r \"nuget: Plotly.NET.ImageExport;\"\n",
|
||||
"#r \"..\\..\\Source\\bin\\Debug\\net6.0\\QuanTAlib.dll\"\n",
|
||||
"\n",
|
||||
"using QuanTAlib;\n",
|
||||
"using Plotly.NET;\n",
|
||||
"using Plotly.NET.LayoutObjects;\n",
|
||||
"using Plotly.NET.ImageExport;"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"TSeries d1a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};\n",
|
||||
"TSeries d2a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1};\n",
|
||||
"TSeries d3a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};\n",
|
||||
"TSeries d4a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,33,32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2};\n",
|
||||
"TSeries d5a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0.32,0.56,0.72,0.84,0.93,0.99,1,0.97,0.91,0.81,0.68,0.52,0.33,0.14,-0.06,-0.26,-0.44,-0.61,-0.76,-0.87,-0.95,-0.99,-1,-0.96,-0.88,-0.77,-0.63,-0.46,-0.28,-0.08,0.12,0.31,0.49,0.66,0.79,0.9,0.97,1,0.99,0.94,0.85,0.73,0.58,0.41,0.22,0.02,-0.17,-0.37,-0.54,-0.7,-0.83,-0.92,-0.98,-1,-0.98,-0.92,-0.82,-0.69,-0.54,-0.36,-0.17,0.03,0.23,0.42,0.59,0.74};\n",
|
||||
"TSeries d6a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1};\n",
|
||||
"TSeries d7a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0.93,0.27,-0.59,-1,-0.71,0.05,0.75,1,0.67,0,-0.67,-0.99,-0.85,-0.34,0.31,0.81,1,0.82,0.35,-0.22,-0.71,-0.98,-0.95,-0.66,-0.2,0.31,0.72,0.96,0.98,0.78,0.43,-0.01,-0.43,-0.77,-0.96,-0.99,-0.85,-0.58,-0.23,0.16,0.51,0.79,0.95,1,0.92,0.73,0.47,0.15,-0.17,-0.47,-0.72,-0.9,-0.99,-0.99,-0.9,-0.74,-0.52,-0.26,0.01,0.28,0.53,0.73,0.88,0.97,1,0.97};\n",
|
||||
"TSeries d8a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,0.03,-0.4,-0.47,0.19,-0.4,-0.23,0.31,0.41,0.19,0.16,-0.5,-0.31,-0.21,0.25,0.18,-0.48,-0.1,0.38,0.29,-0.38,-0.08,-0.21,0.34,0.01,-0.46,0.28,-0.48,0.11,0.02,-0.37,0.19,-0.2,0.1,0.24,0.08,-0.22,-0.12,0.15,0.36,-0.43,-0.03,-0.32,0.45,-0.5,-0.04,-0.04,-0.08,-0.18,0.13,-0.33,-0.19,0.36,-0.39,0.2,-0.31,0.28,-0.13,-0.07,-0.29,0.37,0.03,-0.25,-0.06,-0.3,-0.08,-0.09};\n",
|
||||
"TSeries d9a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,0,0.03,0.11,-0.1,-0.43,-0.08,0.36,-0.04,-0.04,-0.21,-0.3,0.26,0.2,0.28,0.2,0.27,-0.01,-0.1,-0.23,-0.13,-0.41,-0.23,-0.07,-0.21,0.32,-0.18,-0.48,0.3,0.46,-0.2,0.52,-0.81,-0.25,-0.21,-0.12,-0.18,0.18,0.52,0.29,0.44,0.18,-1.2,0.38,0.24,0.06,0.28,0.34,0.3,-0.13,0.19,-0.5,0.59,-0.36,0.22,-0.23,0.24,0.39,0.13,-0.33,-0.57,-0.23,0.49,-0.13,0.76,0.59,0.61};\n",
|
||||
"TSeries d10a = new() {-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0.4,-0.4,0,-0.28,0.41,-0.54,0.65,-0.75,0.84,-0.91,0.96,-0.99,1,-0.99,0.96,-0.92,0.85,-0.77,0.67,-0.56,0.44,-0.3,0.17,-0.03,-0.11,0.25,-0.39,0.51,-0.63,0.73,-0.82,0.89,-0.95,0.98,-1,0.99,-0.97,0.93,-0.86,0.78,-0.69,0.58,-0.46,0.33,-0.19,0.05,0.09,-0.23,0.36,-0.49,0.61,-0.71,0.81,-0.88,0.94,-0.98,1,-1,0.98,-0.94,0.88,-0.8,0.71,-0.6,0.48,-0.35,0.22,-0.08,-0.06};\n",
|
||||
"TSeries d11a = new() {-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,-0.6,0.6,0,0.14,-0.76,-0.96,-0.28,0.66,0.99,0.41,-0.54,-1,-0.54,0.42,0.99,0.65,-0.29,-0.96,-0.75,0.15,0.91,0.84,-0.01,-0.85,-0.91,-0.13,0.76,0.96,0.27,-0.66,-0.99,-0.4,0.55,1,0.53,-0.43,-0.99,-0.64,0.3,0.96,0.75,-0.16,-0.92,-0.83,0.02,0.85,0.9,0.12,-0.77,-0.95,-0.26,0.67,0.99,0.4,-0.56,-1,-0.52,0.44,0.99,0.64,-0.3,-0.97,-0.74,0.17,0.92,0.83,-0.03,-0.86};\n",
|
||||
"TSeries d12a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,0.05,-0.25,-0.32,-0.09,0.22,0.33,0.14,-0.18,-0.33,-0.18,0.14,0.33,0.22,-0.1,-0.32,-0.25,0.05,0.3,0.28,0,-0.28,-0.3,-0.04,0.25,0.32,0.09,-0.22,-0.33,-0.13,0.18,0.33,0.18,0.86,0.67,0.79,1.1,1.32,1.25,0.95,0.69,0.72,1.01,1.28,1.3,1.04,0.74,0.68,0.91,1.22,1.33,1.13,0.81,0.67,0.83,1.15,1.33,1.21,0.9,0.68,0.75,1.06,1.31,1.28,0.99,0.71};\n",
|
||||
"TSeries d13a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,2.7,-0.8,-0.8,3.6,9.3,11.95,10.05,6.3,5,8.3,14.1,17.95,17.25,13.55,11.2,13.25,18.75,23.55,24.2,20.95,17.75,18.45,23.35,28.8,30.8,28.35,24.7,24.05,28,33.75,37,35.65,31.85,28.05,-3.2,1.5,4.8,3.75,-0.8,-4.6,-4.15,0.1,4.25,4.5,0.6,-3.85,-4.75,-1.3,3.35,4.95,2,-2.8,-5,-2.6,2.2,4.95,3.2,-1.5,-4.85,-3.7,0.85,4.6,4.15,-0.15,-4.3};\n",
|
||||
"TSeries d14a = new() {-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0.2,-0.2,0,0,0.59,0.83,0.74,0.5,0.91,1.36,0.93,0.87,0.6,0.38,0.78,0.53,0.42,0.14,0.01,-0.45,-0.71,-0.99,-1,-1.36,-1.22,-1.07,-1.17,-0.56,-0.95,-1.11,-0.16,0.18,-0.28,0.64,-0.5,0.24,0.45,0.67,0.72,1.15,1.52,1.28,1.38,1.03,-0.47,0.96,0.65,0.28,0.3,0.17,-0.07,-0.67,-0.51,-1.33,-0.33,-1.34,-0.78,-1.21,-0.68,-0.43,-0.56,-0.87,-0.93,-0.4,0.52,0.1,1.18,1.18,1.35};\n",
|
||||
"TSeries d15a = new() {0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,0,0.01,1.3,0.3,-0.48,-1.1,-1.14,-0.03,1.11,0.96,0.63,-0.21,-0.97,-0.73,-0.65,-0.06,0.51,1.08,0.99,0.72,0.12,-0.35,-1.12,-1.21,-1.02,-0.87,0.12,0.13,0.24,1.26,1.44,0.58,0.95,-0.82,-0.68,-0.98,-1.08,-1.17,-0.67,-0.06,0.06,0.6,0.69,-0.41,1.33,1.24,0.98,1.01,0.81,0.45,-0.3,-0.28,-1.22,-0.31,-1.35,-0.77,-1.13,-0.5,-0.13,-0.13,-0.32,-0.29,0.3,1.22,0.75,1.73,1.59,1.58};\n",
|
||||
"TSeries d16a = new() {175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.1,175.6,175.44,176.27,176.04,176.99,175.49,175.68,174.34,176.4,174.05,174.4,174.2,176.16,175,177.72,174.33,176.96,174.62,174.76,170.9,171.12,171.05,170.01,169.24,172.64,171.96,175.72,174.16,175.81,177.3,178.38,176.75,177.19,175.55,178.49,176.52,178.45,178.04,178.25,177.8,176.97,172.94,174.92,173.98,172.29,171.19,172.54,172.11,175.32,175.63,176.65,173.8,176.04,172.74,175.24,171.84,171.54,172.17,171.85,172.38,170.78,173.49,173.69,171.71,174.38,173.99,174.83};"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"dotnet_interactive": {
|
||||
"language": "csharp"
|
||||
},
|
||||
"polyglot_notebook": {
|
||||
"kernelName": "csharp"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"int period = 10;\n",
|
||||
"int cut = 26;\n",
|
||||
"\n",
|
||||
"SMA_Series d1b = new(d1a, period);\n",
|
||||
"SMA_Series d2b = new(d2a, period);\n",
|
||||
"SMA_Series d3b = new(d3a, period);\n",
|
||||
"SMA_Series d4b = new(d4a, period);\n",
|
||||
"SMA_Series d5b = new(d5a, period);\n",
|
||||
"SMA_Series d6b = new(d6a, period);\n",
|
||||
"SMA_Series d7b = new(d7a, period);\n",
|
||||
"SMA_Series d8b = new(d8a, period);\n",
|
||||
"SMA_Series d9b = new(d9a, period);\n",
|
||||
"SMA_Series d10b = new(d10a, period);\n",
|
||||
"SMA_Series d11b = new(d11a, period);\n",
|
||||
"SMA_Series d12b = new(d12a, period);\n",
|
||||
"SMA_Series d13b = new(d13a, period);\n",
|
||||
"SMA_Series d14b = new(d14a, period);\n",
|
||||
"SMA_Series d15b = new(d15a, period);\n",
|
||||
"SMA_Series d16b = new(d16a, period);\n",
|
||||
"\n",
|
||||
"List<int> x = Enumerable.Range(-cut,96).ToList<int>();\n",
|
||||
"GenericChart.GenericChart ch1a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d1a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch1b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d1b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch2a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d2a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch2b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d2b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch3a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d3a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch3b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d3b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch4a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d4a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch4b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d4b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch5a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d5a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch5b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d5b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch6a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d6a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch6b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d6b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch7a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d7a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch7b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d7b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch8a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d8a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch8b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d8b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch9a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d9a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch9b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d9b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch10a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d10a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch10b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d10b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch11a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d11a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch11b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d11b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch12a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d12a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch12b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d12b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch13a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d13a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch13b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d13b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch14a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d14a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch14b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d14b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch15a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d15a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch15b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d15b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"GenericChart.GenericChart ch16a = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d16a.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 1.0, Color: Color.fromString(\"blue\"));\n",
|
||||
"GenericChart.GenericChart ch16b = Chart2D.Chart.Line<int,double,bool>(x.GetRange(cut,96-cut),d16b.v.GetRange(cut,96-cut),false,\"\").WithLineStyle(Width: 2.5, Color: Color.fromString(\"red\"));\n",
|
||||
"\n",
|
||||
"var ch1 = Chart.Combine(new []{ch1a,ch1b});\n",
|
||||
"var ch2 = Chart.Combine(new []{ch2a,ch2b});\n",
|
||||
"var ch3 = Chart.Combine(new []{ch3a,ch3b});\n",
|
||||
"var ch4 = Chart.Combine(new []{ch4a,ch4b});\n",
|
||||
"var ch5 = Chart.Combine(new []{ch5a,ch5b});\n",
|
||||
"var ch6 = Chart.Combine(new []{ch6a,ch6b});\n",
|
||||
"var ch7 = Chart.Combine(new []{ch7a,ch7b});\n",
|
||||
"var ch8 = Chart.Combine(new []{ch8a,ch8b});\n",
|
||||
"var ch9 = Chart.Combine(new []{ch9a,ch9b});\n",
|
||||
"var ch10 = Chart.Combine(new []{ch10a,ch10b});\n",
|
||||
"var ch11 = Chart.Combine(new []{ch11a,ch11b});\n",
|
||||
"var ch12 = Chart.Combine(new []{ch12a,ch12b});\n",
|
||||
"var ch13 = Chart.Combine(new []{ch13a,ch13b});\n",
|
||||
"var ch14 = Chart.Combine(new []{ch14a,ch14b});\n",
|
||||
"var ch15 = Chart.Combine(new []{ch15a,ch15b});\n",
|
||||
"var ch16 = Chart.Combine(new []{ch16a,ch16b});\n",
|
||||
"\n",
|
||||
"Layout layout = new Layout(); layout.SetValue(\"showlegend\",false);\n",
|
||||
"var chart1 = new []{ch1,ch2,ch3,ch4,ch5,ch6,ch7,ch8,ch9,ch10,ch11,ch12,ch13,ch14,ch15,ch16};\n",
|
||||
"var full = Chart.Grid<IEnumerable<GenericChart.GenericChart>>(8,2).Invoke(chart1).WithSize(1000,2200).WithMargin(Margin.init<int, int, int, int, int, bool>(30,20,20,30,7,false)).WithLayout(layout);\n",
|
||||
"full.SaveSVG(\"SMA_chart\", Width: 1000, Height: 2200);"
|
||||
]
|
||||
}
|
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],
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File diff suppressed because one or more lines are too long
|
After Width: | Height: | Size: 153 KiB |
+15
-7
@@ -6,20 +6,28 @@
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||||
repo: '',
|
||||
latex: {
|
||||
inlineMath : [['$', '$'], ['\\(', '\\)']], // default
|
||||
displayMath : [['$$', '$$']], // default
|
||||
}
|
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};
|
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</script>
|
||||
<script src="//cdn.jsdelivr.net/npm/prismjs@1/components/prism-csharp.min.js"></script>
|
||||
<!-- Docsify v4 -->
|
||||
<script src="//cdn.jsdelivr.net/npm/docsify@4"></script>
|
||||
<script src="//cdn.jsdelivr.net/npm/docsify-themeable@0/dist/js/docsify-themeable.min.js"></script>
|
||||
<script src="//unpkg.com/@rakutentech/docsify-code-inline/dist/index.min.js"></script>
|
||||
<!-- LaTeX display engine -->
|
||||
<script src="//cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
|
||||
<!-- docsify-latex plugin -->
|
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<script src="//cdn.jsdelivr.net/npm/docsify-latex@0"></script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,174 @@
|
||||
# Coverage
|
||||
|
||||
⭐= Calculation is validated against one or many TA libraries
|
||||
|
||||
✔️= Calculation exists but has no cross-validation tests
|
||||
|
||||
⛔= Not implemented (yet)
|
||||
|
||||
| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** | **Tulip** |
|
||||
|--|:--:|:--:|:--:|:--:|:--:|
|
||||
| OC2 - (Open+Close)/2 |️ `.OC2` || CandlePart.OC2 ||
|
||||
| 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 | avgprice |
|
||||
| HLCC4 - Weighted Price | `.HLCC4` | WCLPRICE | CandlePart.HLCC4 ||
|
||||
| MIDPOINT - Midpoint value | `MIDPOINT_Series` | MIDPOINT || midpoint |
|
||||
| MIDPRICE - Midpoint price | `MIDPRICE_Series` | MIDPRICE || midprice |
|
||||
| MAX - Max value | `MAX_Series` | MAX ||| max |
|
||||
| MIN - Min value | `MIN_Series` | MIN ||| min |
|
||||
| SUM - Summation | `SUM_Series` | SUM ||| sum |
|
||||
| ADD - Addition | `ADD_Series` | ADD ||| add |
|
||||
| SUB - Subtraction | `SUB_Series` | SUB ||| sub |
|
||||
| MUL - Multiplication | `MUL_Series` | MUL ||| mul |
|
||||
| DIV - Division | `DIV_Series` | DIV ||| div |
|
||||
|||||
|
||||
| **STATISTICS & NUMERICAL ANALYSIS** |
|
||||
||||||
|
||||
| BIAS - Bias | `BIAS_Series` ||| bias |
|
||||
| CORR - Pearson's Correlation Coefficient | `CORR_Series` | CORREL | GetCorrelation ||
|
||||
| COVAR - Covariance | `COVAR_Series` || GetCorrelation ||
|
||||
| DECAY - Linear Decay ||||| decay |
|
||||
| EDECAY - Exponential Decay ||||| edecay |
|
||||
| ENTROPY - Entropy | `ENTROPY_Series` ||| entropy |
|
||||
| KURTOSIS - Kurtosis | `KURT_Series` ||| kurtosis |
|
||||
| LINREG - Linear Regression | `LINREG_Series` || GetSlope ||
|
||||
| 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 |||| 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 |
|
||||
| QUANTILE - Quantile |||| quantile |
|
||||
| WMAPE - Weighted Mean Absolute Percent Error | `WMAPE_Series` ||||
|
||||
| ZSCORE - Number of standard deviations from mean | `ZSCORE_Series` || GetStdDev | zscore |
|
||||
||||||
|
||||
| **TREND INDICATORS & AVERAGES** |
|
||||
||||||
|
||||
| AFIRMA - Autoregressive Finite Impulse Response Moving Average |||||
|
||||
| ALMA - Arnaud Legoux Moving Average | `ALMA_Series` || GetAlma | alma |
|
||||
| ARIMA - Autoregressive Integrated Moving Average |||||
|
||||
| DEMA - Double EMA Average | `DEMA_Series` | DEMA | GetDema | dema | dema |
|
||||
| EMA - Exponential Moving Average | `EMA_Series` | EMA | GetEma | ema | ema |
|
||||
| EPMA - Endpoint Moving Average ||| GetEpma ||
|
||||
| FRAMA - Fractal Adaptive Moving Average |||||
|
||||
| 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 | hma |
|
||||
| HWMA - Holt-Winter Moving Average |||| hwma |
|
||||
| JMA - Jurik Moving Average | `JMA_Series` ||| jma |
|
||||
| KAMA - Kaufman's Adaptive Moving Average | `KAMA_Series` | KAMA | GetKama | kama | kama |
|
||||
| KDJ - KDJ Indicator (trend reversal) |||| kdj |
|
||||
| LSMA - Least Squares Moving Average |||||
|
||||
| MACD - Moving Average Convergence/Divergence | `MACD_Series` | MACD | GetMacd | macd |
|
||||
| MAMA - MESA Adaptive Moving Average | `MAMA_Series` | MAMA | GetMama ||
|
||||
| MCGD - McGinley Dynamic |||| mcgd |
|
||||
| MMA - Modified Moving Average |||||
|
||||
| PPMA - Pivot Point Moving Average |||||
|
||||
| PWMA - Pascal's Weighted Moving Average |||| pwma |
|
||||
| RMA - WildeR's Moving Average | `RMA_Series` ||| rma |
|
||||
| SINWMA - Sine Weighted Moving Average |||| sinwma |
|
||||
| ⭐ [SMA - Simple Moving Average](SMA.md) | `SMA_Series` | ⭐ SMA | ⭐ GetSma | ⭐ sma | ⭐ sma |
|
||||
| SMMA - Smoothed Moving Average | `SMMA_Series` || GetSmma ||
|
||||
| SSF - Ehler's Super Smoother Filter |||| ssf |
|
||||
| SUPERTREND - Supertrend |||| supertrend |
|
||||
| SWMA - Symmetric Weighted Moving Average |||| swma |
|
||||
| T3 - Tillson T3 Moving Average | `T3_Series` | T3 | GetT3 | t3 |
|
||||
| TEMA - Triple EMA Average | `TEMA_Series` | TEMA | GetTema | tema |
|
||||
| TRIMA - Triangular Moving Average | `TRIMA_Series` | TRIMA || trima |
|
||||
| TSF - Time Series Forecast || TSF |||
|
||||
| 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 |
|
||||
||||||
|
||||
| **VOLATILITY INDICATORS** |
|
||||
||||||
|
||||
| ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad | ad |
|
||||
| ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ADOSC| GetAdl | adosc | adosc |
|
||||
| ATR - Average True Range | `ATR_Series` | ATR | GetAtr | atr | atr |
|
||||
| ATRP - Average True Range Percent | `ATRP_Series` || GetAtr ||
|
||||
| BETA - Beta coefficient || BETA | GetBeta ||
|
||||
| BBANDS - Bollinger Bands® | `BBANDS_Series` | BBANDS | GetBollingerBands || bbands |
|
||||
| CHAND - Chandelier Exit ||| GetChandelier ||
|
||||
| CRSI - Connor RSI ||| GetConnorsRsi ||
|
||||
| CVI - Chaikins Volatility ||||| cvi |
|
||||
| DON - Donchian Channels ||| GetDonchian ||
|
||||
| FCB - Fractal Chaos Bands ||| GetFcb ||
|
||||
| FISHER - Fisher Transform ||| GetFcb || fisher |
|
||||
| HV - Historical Volatility |||||
|
||||
| ICH - Ichimoku ||| GetIchimoku ||
|
||||
| KEL - Keltner Channels ||| GetKeltner ||
|
||||
| NATR - Normalized Average True Range || NATR | GetAtr ||
|
||||
| CHN - Price Channel Indicator |||||
|
||||
| RSI - Relative Strength Index | `RSI_Series` | RSI | GetRsi | rsi |
|
||||
| SAR - Parabolic Stop and Reverse || SAR | GetParabolicSar ||
|
||||
| SRSI - Stochastic RSI || STOCHRSI | GetStochRsi ||
|
||||
| STARC - Starc Bands |||||
|
||||
| TR - True Range | `TR_Series` | TRANGE | GetTr | true_range |
|
||||
| UI - Ulcer Index |||||
|
||||
| VSTOP - Volatility Stop |||||
|
||||
||||||
|
||||
| **MOMENTUM INDICATORS & OSCILLATORS** |
|
||||
||||||
|
||||
| AC - Acceleration Oscillator |||||
|
||||
| ADX - Average Directional Movement Index || ADX | GetAdx || adx |
|
||||
| ADXR - Average Directional Movement Index Rating || ADXR | GetAdx || adxr |
|
||||
| AO - Awesome Oscillator ||| GetAwesome || ao |
|
||||
| APO - Absolute Price Oscillator || APO ||| apo |
|
||||
| AROON - Aroon oscillator || AROON | GetAroon || aroon |
|
||||
| BOP - Balance of Power || BOP | GetBop || bop |
|
||||
| CCI - Commodity Channel Index | `CCI_Series` | CCI | GetCci || cci |
|
||||
| CFO - Chande Forcast Oscillator |||||
|
||||
| CMO - Chande Momentum Oscillator || CMO | GetCmo || cmo |
|
||||
| COG - Center of Gravity |||||
|
||||
| COPPOCK - Coppock Curve |||||
|
||||
| CTI - Ehler's Correlation Trend Indicator |||||
|
||||
| DPO - Detrended Price Oscillator ||| GetDpo ||
|
||||
| DMI - Directional Movement Index || DX | GetAdx ||
|
||||
| EFI - Elder Ray's Force Index ||| GetElderRay ||
|
||||
| FOSC - Forecast oscillator ||||| fosc |
|
||||
| GAT - Alligator oscillator ||| GetGator ||
|
||||
| HURST - Hurst Exponent ||| GetHurst ||
|
||||
| KRI - Kairi Relative Index |||||
|
||||
| KVO - Klinger Volume Oscillator |||||
|
||||
| MFI - Money Flow Index || MFI | GetMfi ||
|
||||
| MOM - Momentum || MOM |||
|
||||
| NVI - Negative Volume Index |||||
|
||||
| PO - Price Oscillator |||||
|
||||
| PPO - Percentage Price Oscillator || PPO |||
|
||||
| PMO - Price Momentum Oscillator |||||
|
||||
| PVI - Positive Volume Index |||||
|
||||
| ROC - Rate of Change || MOM | GetRoc ||
|
||||
| RVGI - Relative Vigor Index |||||
|
||||
| SMI - Stochastic Momentum Index |||||
|
||||
| STC - Schaff Trend Cycle |||||
|
||||
| STOCH - Stochastic Oscillator || STOCH | GetStoch ||
|
||||
| TRIX - 1-day ROC of TEMA || TRIX | GetTrix ||
|
||||
| TSI - True Strength Index |||||
|
||||
| UO - Ultimate Oscillator || ULTOSC | GetUltimate ||
|
||||
| WILLR - Larry Williams' %R || WILLR | GetWilliamsR ||
|
||||
| WGAT - Williams Alligator |||||
|
||||
||||||
|
||||
| **VOLUME INDICATORS** |
|
||||
||||||
|
||||
| AOBV - Archer On-Balance Volume |||||
|
||||
| CMF - Chaikin Money Flow |||||
|
||||
| EOM - Ease of Movement ||||| emv |
|
||||
| KVO - Klinger Volume Oscilaltor ||||| kvo |
|
||||
| OBV - On-Balance Volume | `OBV_Series` | OBV | GetObv ||
|
||||
| PRS - Price Relative Strength ||||
|
||||
| PVOL - Price-Volume |||||
|
||||
| PVO - Percentage Volume Oscillator |||||
|
||||
| PVR - Price Volume Rank |||||
|
||||
| PVT - Price Volume Trend |||||
|
||||
| VP - Volume Profile |||||
|
||||
| VWAP - Volume Weighted Average Price |||||
|
||||
| VWMA - Volume Weighted Moving Average |||||
|
||||
+43
-32
@@ -34,28 +34,31 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|
||||
|
||||
⛔= Not implemented (yet)
|
||||
|
||||
| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
|--|:--:|:--:|:--:|:--:|
|
||||
| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** | **Tulip** |
|
||||
|--|:--:|:--:|:--:|:--:|:--:|
|
||||
| ⭐ OC2 - (Open+Close)/2 |️ `.OC2` || CandlePart.OC2 ||
|
||||
| ⭐ 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 |
|
||||
| ⭐ OHLC4 - Average Price | `.OHLC4` | AVGPRICE |️ CandlePart.OHLC4 | ohlc4 | avgprice |
|
||||
| ⭐ HLCC4 - Weighted Price | `.HLCC4` | WCLPRICE | CandlePart.HLCC4 ||
|
||||
| ⭐ 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 |||
|
||||
| ⭐ ADD - Addition | `ADD_Series` | ADD |||
|
||||
| ⭐ SUB - Subtraction | `SUB_Series` | SUB |||
|
||||
| ⭐ MUL - Multiplication | `MUL_Series` | MUL |||
|
||||
| ⭐ DIV - Division | `DIV_Series` | DIV |||
|
||||
| ⭐ MAX - Max value | `MAX_Series` | MAX ||| max |
|
||||
| ⭐ MIN - Min value | `MIN_Series` | MIN ||| min |
|
||||
| ⭐ SUM - Summation | `SUM_Series` | SUM ||| sum |
|
||||
| ⭐ ADD - Addition | `ADD_Series` | ADD ||| add |
|
||||
| ⭐ SUB - Subtraction | `SUB_Series` | SUB ||| sub |
|
||||
| ⭐ MUL - Multiplication | `MUL_Series` | MUL ||| mul |
|
||||
| ⭐ DIV - Division | `DIV_Series` | DIV ||| div |
|
||||
|||||
|
||||
| **STATISTICS & NUMERICAL ANALYSIS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
| **STATISTICS & NUMERICAL ANALYSIS** |
|
||||
||||||
|
||||
| ⭐ BIAS - Bias | `BIAS_Series` ||| bias |
|
||||
| ⭐ CORR - Pearson's Correlation Coefficient | `CORR_Series` | CORREL | GetCorrelation ||
|
||||
| ⭐ COVAR - Covariance | `COVAR_Series` || GetCorrelation ||
|
||||
| ⛔ DECAY - Linear Decay ||||| decay |
|
||||
| ⛔ EDECAY - Exponential Decay ||||| edecay |
|
||||
| ⭐ ENTROPY - Entropy | `ENTROPY_Series` ||| entropy |
|
||||
| ⭐ KURTOSIS - Kurtosis | `KURT_Series` ||| kurtosis |
|
||||
| ⭐ LINREG - Linear Regression | `LINREG_Series` || GetSlope ||
|
||||
@@ -73,22 +76,23 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|
||||
| ✔️ WMAPE - Weighted Mean Absolute Percent Error | `WMAPE_Series` ||||
|
||||
| ⭐ ZSCORE - Number of standard deviations from mean | `ZSCORE_Series` || GetStdDev | zscore |
|
||||
||||||
|
||||
| **TREND INDICATORS & AVERAGES** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
| **TREND INDICATORS & AVERAGES** |
|
||||
||||||
|
||||
| ⛔ AFIRMA - Autoregressive Finite Impulse Response Moving Average |||||
|
||||
| ⭐ 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` | EMA | GetEma | ema |
|
||||
| ⭐ DEMA - Double EMA Average | `DEMA_Series` | DEMA | GetDema | dema | dema |
|
||||
| ⭐ EMA - Exponential Moving Average | `EMA_Series` | EMA | GetEma | ema | ema |
|
||||
| ⛔ EPMA - Endpoint Moving Average ||| GetEpma ||
|
||||
| ⛔ FRAMA - Fractal Adaptive Moving Average |||||
|
||||
| ⛔ 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 |
|
||||
| ⭐ HMA - Hull Moving Average | `HMA_Series` || GetHma | hma | hma |
|
||||
| ⛔ HWMA - Holt-Winter Moving Average |||| hwma |
|
||||
| ✔️ JMA - Jurik Moving Average | `JMA_Series` ||| jma |
|
||||
| ⭐ KAMA - Kaufman's Adaptive Moving Average | `KAMA_Series` | KAMA | GetKama | kama |
|
||||
| ⭐ KAMA - Kaufman's Adaptive Moving Average | `KAMA_Series` | KAMA | GetKama | kama | kama |
|
||||
| ⛔ KDJ - KDJ Indicator (trend reversal) |||| kdj |
|
||||
| ⛔ LSMA - Least Squares Moving Average |||||
|
||||
| ⭐ MACD - Moving Average Convergence/Divergence | `MACD_Series` | MACD | GetMacd | macd |
|
||||
@@ -113,17 +117,20 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|
||||
| ⭐ WMA - Weighted Moving Average | `WMA_Series` | WMA | GetWma | wma |
|
||||
| ⭐ ZLEMA - Zero Lag EMA Average | `ZLEMA_Series` ||| zlma |
|
||||
||||||
|
||||
| **VOLATILITY INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
| ⭐ ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad |
|
||||
| ⭐ ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ADOSC| GetAdl | adosc |
|
||||
| ⭐ ATR - Average True Range | `ATR_Series` | ATR | GetAtr | atr |
|
||||
| **VOLATILITY INDICATORS** |
|
||||
||||||
|
||||
| ⭐ ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad | ad |
|
||||
| ⭐ ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ADOSC| GetAdl | adosc | adosc |
|
||||
| ⭐ ATR - Average True Range | `ATR_Series` | ATR | GetAtr | atr | atr |
|
||||
| ⭐ ATRP - Average True Range Percent | `ATRP_Series` || GetAtr ||
|
||||
| ⛔ BETA - Beta coefficient || BETA | GetBeta ||
|
||||
| ⭐ BBANDS - Bollinger Bands® | `BBANDS_Series` | BBANDS | GetBollingerBands ||
|
||||
| ⭐ BBANDS - Bollinger Bands® | `BBANDS_Series` | BBANDS | GetBollingerBands || bbands |
|
||||
| ⛔ CHAND - Chandelier Exit ||| GetChandelier ||
|
||||
| ⛔ CRSI - Connor RSI ||| GetConnorsRsi ||
|
||||
| ⛔ CVI - Chaikins Volatility ||||| cvi |
|
||||
| ⛔ DON - Donchian Channels ||| GetDonchian ||
|
||||
| ⛔ FCB - Fractal Chaos Bands ||| GetFcb ||
|
||||
| ⛔ FISHER - Fisher Transform ||| GetFcb || fisher |
|
||||
| ⛔ HV - Historical Volatility |||||
|
||||
| ⛔ ICH - Ichimoku ||| GetIchimoku ||
|
||||
| ⛔ KEL - Keltner Channels ||| GetKeltner ||
|
||||
@@ -137,23 +144,25 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|
||||
| ⛔ UI - Ulcer Index |||||
|
||||
| ⛔ VSTOP - Volatility Stop |||||
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||||
||||||
|
||||
| **MOMENTUM INDICATORS & OSCILLATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
| **MOMENTUM INDICATORS & OSCILLATORS** |
|
||||
||||||
|
||||
| ⛔ AC - Acceleration Oscillator |||||
|
||||
| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx ||
|
||||
| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx ||
|
||||
| ⛔ AO - Awesome Oscillator ||| GetAwesome ||
|
||||
| ⛔ APO - Absolute Price Oscillator || APO |||
|
||||
| ⛔ AROON - Aroon oscillator || AROON | GetAroon ||
|
||||
| ⛔ BOP - Balance of Power || BOP | GetBop ||
|
||||
| ⭐ CCI - Commodity Channel Index | `CCI_Series` | CCI | GetCci ||
|
||||
| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx || adx |
|
||||
| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx || adxr |
|
||||
| ⛔ AO - Awesome Oscillator ||| GetAwesome || ao |
|
||||
| ⛔ APO - Absolute Price Oscillator || APO ||| apo |
|
||||
| ⛔ AROON - Aroon oscillator || AROON | GetAroon || aroon |
|
||||
| ⛔ BOP - Balance of Power || BOP | GetBop || bop |
|
||||
| ⭐ CCI - Commodity Channel Index | `CCI_Series` | CCI | GetCci || cci |
|
||||
| ⛔ CFO - Chande Forcast Oscillator |||||
|
||||
| ⛔ CMO - Chande Momentum Oscillator || CMO | GetCmo ||
|
||||
| ⛔ CMO - Chande Momentum Oscillator || CMO | GetCmo || cmo |
|
||||
| ⛔ COG - Center of Gravity |||||
|
||||
| ⛔ COPPOCK - Coppock Curve |||||
|
||||
| ⛔ CTI - Ehler's Correlation Trend Indicator |||||
|
||||
| ⛔ DPO - Detrended Price Oscillator ||| GetDpo ||
|
||||
| ⛔ DMI - Directional Movement Index || DX | GetAdx ||
|
||||
| ⛔ EFI - Elder Ray's Force Index ||| GetElderRay ||
|
||||
| ⛔ FOSC - Forecast oscillator ||||| fosc |
|
||||
| ⛔ GAT - Alligator oscillator ||| GetGator ||
|
||||
| ⛔ HURST - Hurst Exponent ||| GetHurst ||
|
||||
| ⛔ KRI - Kairi Relative Index |||||
|
||||
@@ -176,10 +185,12 @@ See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/gett
|
||||
| ⛔ WILLR - Larry Williams' %R || WILLR | GetWilliamsR ||
|
||||
| ⛔ WGAT - Williams Alligator |||||
|
||||
||||||
|
||||
| **VOLUME INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|
||||
| **VOLUME INDICATORS** |
|
||||
||||||
|
||||
| ⛔ AOBV - Archer On-Balance Volume |||||
|
||||
| ⛔ CMF - Chaikin Money Flow |||||
|
||||
| ⛔ EOM - Ease of Movement |||||
|
||||
| ⛔ EOM - Ease of Movement ||||| emv |
|
||||
| ⛔ KVO - Klinger Volume Oscilaltor ||||| kvo |
|
||||
| ⭐ OBV - On-Balance Volume | `OBV_Series` | OBV | GetObv ||
|
||||
| ⛔ PRS - Price Relative Strength ||||
|
||||
| ⛔ PVOL - Price-Volume |||||
|
||||
|
||||
Reference in New Issue
Block a user