Documentation update

Quantower/Indicators/PSDEV_chart.cs

@@ -1,53 +0,0 @@
-using System.Drawing;
-using TradingPlatform.BusinessLayer;
-namespace QuanTAlib;
-
-public class PSDEV_chart : Indicator
-{
-    #region Parameters
-
-    [InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
-    private int Period = 10;
-
-    [InputParameter("Data source", 1, variants: new object[]
-      { "Open", 0, "High", 1,  "Low", 2,  "Close", 3,  "HL2", 4,  "OC2", 5,
-      "OHL3", 6,  "HLC3", 7,  "OHLC4", 8,  "Weighted (HLCC4)", 9 })]
-    private int DataSource = 8;
-
-    #endregion Parameters
-
-    private TBars bars;
-
-    ///////dotnet
-    private SDEV_Series indicator;
-    ///////
-
-    public PSDEV_chart()
-    {
-        this.SeparateWindow = true;
-        this.Name = "PSDEV - Population Standard Deviation (Biased)";
-        this.Description = "PSDEV description";
-        this.AddLineSeries("PSDEV", Color.RoyalBlue, 3, LineStyle.Solid);
-    }
-
-    protected override void OnInit()
-    {
-	    this.bars = new(); 
-	    this.ShortName =
-            "PSDEV (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
-        this.indicator = new(source: bars.Select(this.DataSource),
-                             period: this.Period, useNaN: true);
-    }
-    protected override void OnUpdate(UpdateArgs args)
-    {
-        bool update = !(args.Reason == UpdateReason.NewBar ||
-                        args.Reason == UpdateReason.HistoricalBar);
-        this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
-                      this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
-                      this.GetPrice(PriceType.Close),
-                      this.GetPrice(PriceType.Volume), update);
-        double result = this.indicator[this.indicator.Count - 1].v;
-
-        this.SetValue(result, 0);
-    }
-}

Quantower/Indicators/PSDEV_chart.cs~HEAD

@@ -1,53 +0,0 @@
-using System.Drawing;
-using TradingPlatform.BusinessLayer;
-namespace QuanTAlib;
-
-public class PSDEV_chart : Indicator
-{
-    #region Parameters
-
-    [InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
-    private int Period = 10;
-
-    [InputParameter("Data source", 1, variants: new object[]
-      { "Open", 0, "High", 1,  "Low", 2,  "Close", 3,  "HL2", 4,  "OC2", 5,
-      "OHL3", 6,  "HLC3", 7,  "OHLC4", 8,  "Weighted (HLCC4)", 9 })]
-    private int DataSource = 8;
-
-    #endregion Parameters
-
-    private TBars bars;
-
-    ///////dotnet
-    private PSDEV_Series indicator;
-    ///////
-
-    public PSDEV_chart()
-    {
-        this.SeparateWindow = true;
-        this.Name = "PSDEV - Population Standard Deviation (Biased)";
-        this.Description = "PSDEV description";
-        this.AddLineSeries("PSDEV", Color.RoyalBlue, 3, LineStyle.Solid);
-    }
-
-    protected override void OnInit()
-    {
-	    this.bars = new(); 
-	    this.ShortName =
-            "PSDEV (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
-        this.indicator = new(source: bars.Select(this.DataSource),
-                             period: this.Period, useNaN: true);
-    }
-    protected override void OnUpdate(UpdateArgs args)
-    {
-        bool update = !(args.Reason == UpdateReason.NewBar ||
-                        args.Reason == UpdateReason.HistoricalBar);
-        this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
-                      this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
-                      this.GetPrice(PriceType.Close),
-                      this.GetPrice(PriceType.Volume), update);
-        double result = this.indicator[this.indicator.Count - 1].v;
-
-        this.SetValue(result, 0);
-    }
-}

Quantower/Indicators/PSDEV_chart.cs~parent of 32615af... for dev branch

@@ -1,53 +0,0 @@
-using System.Drawing;
-using TradingPlatform.BusinessLayer;
-namespace QuanTAlib;
-
-public class PSDEV_chart : Indicator
-{
-    #region Parameters
-
-    [InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
-    private int Period = 10;
-
-    [InputParameter("Data source", 1, variants: new object[]
-      { "Open", 0, "High", 1,  "Low", 2,  "Close", 3,  "HL2", 4,  "OC2", 5,
-      "OHL3", 6,  "HLC3", 7,  "OHLC4", 8,  "Weighted (HLCC4)", 9 })]
-    private int DataSource = 8;
-
-    #endregion Parameters
-
-    private TBars bars;
-
-    ///////dotnet
-    private PSDEV_Series indicator;
-    ///////
-
-    public PSDEV_chart()
-    {
-        this.SeparateWindow = true;
-        this.Name = "PSDEV - Population Standard Deviation (Biased)";
-        this.Description = "PSDEV description";
-        this.AddLineSeries("PSDEV", Color.RoyalBlue, 3, LineStyle.Solid);
-    }
-
-    protected override void OnInit()
-    {
-	    this.bars = new(); 
-	    this.ShortName =
-            "PSDEV (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
-        this.indicator = new(source: bars.Select(this.DataSource),
-                             period: this.Period, useNaN: true);
-    }
-    protected override void OnUpdate(UpdateArgs args)
-    {
-        bool update = !(args.Reason == UpdateReason.NewBar ||
-                        args.Reason == UpdateReason.HistoricalBar);
-        this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
-                      this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
-                      this.GetPrice(PriceType.Close),
-                      this.GetPrice(PriceType.Volume), update);
-        double result = this.indicator[this.indicator.Count - 1].v;
-
-        this.SetValue(result, 0);
-    }
-}

Quantower/Indicators/PVAR_chart.cs

@@ -1,54 +0,0 @@
-using System.Drawing;
-using TradingPlatform.BusinessLayer;
-namespace QuanTAlib;
-
-public class PVAR_chart : Indicator
-{
-    #region Parameters
-
-    [InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
-    private int Period = 10;
-
-    [InputParameter("Data source", 1, variants: new object[]
-      { "Open", 0, "High", 1,  "Low", 2,  "Close", 3,  "HL2", 4,  "OC2", 5,
-      "OHL3", 6,  "HLC3", 7,  "OHLC4", 8,  "Weighted (HLCC4)", 9 })]
-    private int DataSource = 8;
-
-    #endregion Parameters
-
-    private TBars bars;
-
-    ///////dotnet
-    private PVAR_Series indicator;
-    ///////
-
-    public PVAR_chart()
-    {
-        this.SeparateWindow = true;
-        this.Name = "PVAR - Population Variance (Biased)";
-        this.Description = "PVAR description";
-        this.AddLineSeries("PVAR", Color.RoyalBlue, 3, LineStyle.Solid);
-    }
-
-    protected override void OnInit()
-    {
-	    this.bars = new(); 
-	    this.ShortName =
-            "PVAR (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
-        this.indicator = new(source: bars.Select(this.DataSource),
-                             period: this.Period, useNaN: true);
-    }
-
-    protected override void OnUpdate(UpdateArgs args)
-    {
-        bool update = !(args.Reason == UpdateReason.NewBar ||
-                        args.Reason == UpdateReason.HistoricalBar);
-        this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
-                      this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
-                      this.GetPrice(PriceType.Close),
-                      this.GetPrice(PriceType.Volume), update);
-        double result = this.indicator[this.indicator.Count - 1].v;
-
-        this.SetValue(result, 0);
-    }
-}

Quantower/Indicators/SDEV_chart.cs

@@ -19,13 +19,13 @@ public class SDEV_chart : Indicator
     private TBars bars;
 
     ///////dotnet
-    private SSDEV_Series indicator;
+    private SDEV_Series indicator;
     ///////
 
     public SDEV_chart()
     {
         this.SeparateWindow = true;
-        this.Name = "SDEV - Sample Standard Deviation (Unbiased)";
+        this.Name = "SDEV - Standard Deviation";
         this.Description = "SDEV description";
         this.AddLineSeries("SDEV", Color.RoyalBlue, 3, LineStyle.Solid);
     }

Quantower/Indicators/VAR_chart.cs

@@ -25,7 +25,7 @@ public class VAR_chart : Indicator
     public VAR_chart()
     {
         this.SeparateWindow = true;
-        this.Name = "VAR - Sample Variance (Unbiased)";
+        this.Name = "VAR - Variance";
         this.Description = "VAR description";
         this.AddLineSeries("VAR", Color.RoyalBlue, 3, LineStyle.Solid);
     }

Source/Indicators/ADOSC_Series.cs

@@ -13,7 +13,7 @@ Sources:
 
 </summary> */
 
-public class ADO_Series : Single_TBars_Indicator
+public class ADOSC_Series : Single_TBars_Indicator
 {
 	private readonly ADL_Series _TSadl;
 
@@ -21,7 +21,7 @@ public class ADO_Series : Single_TBars_Indicator
 	private readonly EMA_Series _TSfast;
 	private readonly SUB_Series _TSado;
 
-	public ADO_Series(TBars source, bool useNaN = false) : base(source, period: 0, useNaN)
+	public ADOSC_Series(TBars source, bool useNaN = false) : base(source, period: 0, useNaN)
 	{
 		_TSadl = new(source: source, useNaN: false);
 		_TSslow = new(source: _TSadl, period: 10, useNaN: false);

Source/Indicators/ATRP_Series.cs

@@ -2,31 +2,28 @@
 using System;
 
 /* <summary>
-ATR: wildeR Moving Average
+ATRP: Average True Range Percent
-    The average true range (ATR) is a price volatility indicator
+    Average True Range Percent is (ATR/Close Price)*100. 
-    showing the average price variation of assets within a given time period.
+    This normalizes so it can be compared to other stocks.
 
 Sources:
-    https://en.wikipedia.org/wiki/Average_true_range
+    https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/atrp
-    https://www.tradingview.com/wiki/Average_True_Range_(ATR)
-    https://www.investopedia.com/terms/a/atr.asp
 
 </summary> */
 
-
+public class ATRP_Series : Single_TBars_Indicator
-public class ATR_Series : Single_TBars_Indicator
 {
     private readonly System.Collections.Generic.List<double> _buffer = new();
     private readonly double _k, _k1m;
     private double _lastema, _lastlastema, _lastcm1;
     private double _cm1 = double.NaN;
 
-    public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
+    public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
     {
         this._k = 1.0 / (double)(this._p);
         this._k1m = 1.0 - this._k;
         this._lastema = this._lastlastema = double.NaN;
-        if (this._bars.Count > 0) { base.Add(this._bars); }
+        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)
@@ -36,7 +33,7 @@ public class ATR_Series : Single_TBars_Indicator
             this._cm1 = this._lastcm1;
         }
 
-        if (this._cm1 is double.NaN) { this._cm1 = TBar.c; }
+        if (_cm1 is double.NaN) { _cm1 = TBar.c; }
         double d1 = Math.Abs(TBar.h - TBar.l);
         double d2 = Math.Abs(_cm1 - TBar.h);
         double d3 = Math.Abs(_cm1 - TBar.l);
@@ -58,7 +55,9 @@ public class ATR_Series : Single_TBars_Indicator
         this._lastlastema = this._lastema;
         this._lastema = _ema;
 
-        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
+        double _atrp = 100 * (_ema / TBar.c);
+
+        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
         base.Add(ret, update);
     }
 }

Source/Indicators/ATR_Series.cs

@@ -2,28 +2,31 @@
 using System;
 
 /* <summary>
-ATRP: Average True Range Percent
+ATR: wildeR Moving Average
-    Average True Range Percent is (ATR/Close Price)*100. 
+    The average true range (ATR) is a price volatility indicator
-    This normalizes so it can be compared to other stocks.
+    showing the average price variation of assets within a given time period.
 
 Sources:
-    https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/atrp
+    https://en.wikipedia.org/wiki/Average_true_range
+    https://www.tradingview.com/wiki/Average_True_Range_(ATR)
+    https://www.investopedia.com/terms/a/atr.asp
 
 </summary> */
 
-public class ATRP_Series : Single_TBars_Indicator
+
+public class ATR_Series : Single_TBars_Indicator
 {
     private readonly System.Collections.Generic.List<double> _buffer = new();
     private readonly double _k, _k1m;
     private double _lastema, _lastlastema, _lastcm1;
     private double _cm1 = double.NaN;
 
-    public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
+    public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
     {
         this._k = 1.0 / (double)(this._p);
         this._k1m = 1.0 - this._k;
         this._lastema = this._lastlastema = double.NaN;
-        if (_bars.Count > 0) { base.Add(_bars); }
+        if (this._bars.Count > 0) { base.Add(this._bars); }
     }
 
     public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
@@ -33,7 +36,7 @@ public class ATRP_Series : Single_TBars_Indicator
             this._cm1 = this._lastcm1;
         }
 
-        if (_cm1 is double.NaN) { _cm1 = TBar.c; }
+        if (this._cm1 is double.NaN) { this._cm1 = TBar.c; }
         double d1 = Math.Abs(TBar.h - TBar.l);
         double d2 = Math.Abs(_cm1 - TBar.h);
         double d3 = Math.Abs(_cm1 - TBar.l);
@@ -55,9 +58,7 @@ public class ATRP_Series : Single_TBars_Indicator
         this._lastlastema = this._lastema;
         this._lastema = _ema;
 
-        double _atrp = 100 * (_ema / TBar.c);
+        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
-
-        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
         base.Add(ret, update);
     }
 }

Source/Statistics/PVAR_Series.cs

@@ -1,43 +0,0 @@
-namespace QuanTAlib;
-using System;
-
-/* <summary>
-PVAR: Population Variance
-  Population variance without Bessel's correction
-
-Sources:
-  https://en.wikipedia.org/wiki/Variance
-  Bessel's correction: https://en.wikipedia.org/wiki/Bessel%27s_correction
-
-Remark:
-  PVAR (Population Variance) is also known as a biased Sample Variance. For unbiased
-  sample variance use SVAR instead.
-    
-</summary> */
-
-public class PVAR_Series : Single_TSeries_Indicator
-{
-    public PVAR_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
-    {
-        if (base._data.Count > 0) { base.Add(base._data); }
-    }
-    private readonly System.Collections.Generic.List<double> _buffer = new();
-
-    public override void Add((System.DateTime t, double v) TValue, bool update)
-    {
-        if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
-        else { _buffer.Add(TValue.v); }
-        if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }
-
-        double _sma = 0;
-        for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; }
-        _sma /= this._buffer.Count;
-
-        double _pvar = 0;
-        for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
-        _pvar /= this._buffer.Count;
-
-        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _pvar);
-        base.Add(result, update);
-    }
-}

Source/Statistics/SVAR_Series.cs

@@ -0,0 +1,43 @@
+namespace QuanTAlib;
+using System;
+
+/* <summary>
+SVAR: Sample Variance
+  Sample variance uses Bessel's correction to correct the bias in the estimation of population variance.
+
+Sources:
+  https://en.wikipedia.org/wiki/Variance
+  Bessel's correction: https://en.wikipedia.org/wiki/Bessel%27s_correction
+
+Remark:
+  SVAR is also known as the Unbiased Sample Variance, while VAR (Population Variance) is known as
+  the Biased Sample Variance. 
+    
+</summary> */
+
+public class SVAR_Series : Single_TSeries_Indicator
+{
+    public SVAR_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
+    {
+        if (base._data.Count > 0) { base.Add(base._data); }
+    }
+    private readonly System.Collections.Generic.List<double> _buffer = new();
+
+    public override void Add((System.DateTime t, double v) TValue, bool update)
+    {
+        if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
+        else { this._buffer.Add(TValue.v); }
+        if (this._buffer.Count > this._p && this._p != 0) { this._buffer.RemoveAt(0); }
+
+        double _sma = 0;
+        for (int i = 0; i < this._buffer.Count; i++) { _sma += this._buffer[i]; }
+        _sma /= this._buffer.Count;
+
+        double _svar = 0;
+        for (int i = 0; i < this._buffer.Count; i++) { _svar += (this._buffer[i] - _sma) * (this._buffer[i] - _sma); }
+        _svar /= (this._buffer.Count > 1) ? this._buffer.Count - 1 : 1; // Bessel's correction
+
+        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _svar);
+        base.Add(result, update);
+    }
+}

Source/Statistics/VAR_Series.cs

@@ -2,16 +2,16 @@
 using System;
 
 /* <summary>
-VAR: Sample Variance
+VAR: Population Variance
-  Sample variance uses Bessel's correction to correct the bias in the estimation of population variance.
+  Population variance without Bessel's correction
 
 Sources:
   https://en.wikipedia.org/wiki/Variance
   Bessel's correction: https://en.wikipedia.org/wiki/Bessel%27s_correction
 
 Remark:
-  VAR is also known as the Unbiased Sample Variance, while PVAR (Population Variance) is known as
+  VAR (Population Variance) is also known as a biased Sample Variance. For unbiased
-  the Biased Sample Variance. 
+  sample variance use SVAR instead.
     
 </summary> */
 
@@ -25,19 +25,19 @@ public class VAR_Series : Single_TSeries_Indicator
 
     public override void Add((System.DateTime t, double v) TValue, bool update)
     {
-        if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
+        if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
-        else { this._buffer.Add(TValue.v); }
+        else { _buffer.Add(TValue.v); }
-        if (this._buffer.Count > this._p && this._p != 0) { this._buffer.RemoveAt(0); }
+        if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }
 
         double _sma = 0;
-        for (int i = 0; i < this._buffer.Count; i++) { _sma += this._buffer[i]; }
+        for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; }
         _sma /= this._buffer.Count;
 
-        double _svar = 0;
+        double _pvar = 0;
-        for (int i = 0; i < this._buffer.Count; i++) { _svar += (this._buffer[i] - _sma) * (this._buffer[i] - _sma); }
+        for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
-        _svar /= (this._buffer.Count > 1) ? this._buffer.Count - 1 : 1; // Bessel's correction
+        _pvar /= this._buffer.Count;
 
-        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _svar);
+        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _pvar);
         base.Add(result, update);
     }
 }

Tests/Statistics/PVAR_Test .cs

@@ -9,7 +9,7 @@ public class PVAR_Test
 	public void Add_Test()
 	{
 		TSeries a = new() { 0, 1, 2, 3, 4, 5 };
-		PVAR_Series c = new(a, 3);
+		SVAR_Series c = new(a, 3);
 		Assert.Equal(6, c.Count);
 		a.Add(5);
 		Assert.Equal(a.Count, c.Count);
@@ -21,7 +21,7 @@ public class PVAR_Test
 	public void Edge_Test()
 	{
 		TSeries a = new() { double.NaN, double.Epsilon, double.PositiveInfinity, double.MaxValue };
-		PVAR_Series c = new(a, 3);
+		SVAR_Series c = new(a, 3);
 		Assert.Equal(a.Count, c.Count);
 		a.Add(double.NaN);
 		Assert.Equal(a.Count, c.Count);

Tests/Statistics/VAR_Test.cs

@@ -9,7 +9,7 @@ public class VAR_Test
 	public void Add_Test()
 	{
 		TSeries a = new() { 0, 1, 2, 3, 4, 5 };
-		VAR_Series c = new(a, 3);
+		SVAR_Series c = new(a, 3);
 		Assert.Equal(6, c.Count);
 		a.Add(5);
 		Assert.Equal(a.Count, c.Count);
@@ -21,7 +21,7 @@ public class VAR_Test
 	public void Edge_Test()
 	{
 		TSeries a = new() { double.NaN, double.Epsilon, double.PositiveInfinity, double.MaxValue };
-		VAR_Series c = new(a, 3);
+		SVAR_Series c = new(a, 3);
 		Assert.Equal(a.Count, c.Count);
 		a.Add(double.NaN);
 		Assert.Equal(a.Count, c.Count);

Tests/Tests.csproj

@@ -33,6 +33,7 @@
       <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
     </PackageReference>
     <PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.5.0-preview-20221003-04" />
+    <PackageReference Include="Python.Included" Version="3.10.0-preview5" />
     <PackageReference Include="TALib.NETCore" Version="0.4.4" />
     <PackageReference Include="Skender.Stock.Indicators" Version="2.4.0" />
     <PackageReference Include="xunit" Version="2.4.2" />

Tests/Validations/Pandas_TA.cs

@@ -1,4 +1,4 @@
-/*
+
 
 using Xunit;
 using System;
@@ -20,6 +20,8 @@ public class PandasTA
 		this.bars = new(1000);
 		this.period = this.rnd.Next(28) + 3;
 
+		Runtime.PythonDLL = @"python310.dll";
+		Installer.InstallPath = Path.GetFullPath(".");
 		Installer.SetupPython().Wait();
 		Installer.TryInstallPip();
 		Installer.PipInstallModule("numpy");
@@ -34,91 +36,89 @@ public class PandasTA
 	{
 		PythonEngine.Shutdown();
 	}
+	/*
+			[Fact]
+			void SMA()
+			{
+				SMA_Series QL = new(this.bars.Close, this.period, false);
+				var pta = this.ta.sma(close: this.df[0], length: this.period);
 
-	[Fact]
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	void SMA()
+			}
-	{
-		SMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.sma(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+			[Fact]
-	}
+			void EMA()
+			{
+				EMA_Series QL = new(this.bars.Close, this.period, false);
+				var pta = this.ta.ema(close: this.df[0], length: this.period);
+
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+			}
 
 
-	[Fact]
+			[Fact]
-	void EMA()
+			void TEMA()
-	{
+			{
-		EMA_Series QL = new(this.bars.Close, this.period, false);
+				TEMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.ema(close: this.df[0], length: this.period);
+				var pta = this.ta.tema(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	}
+			}
+
+			[Fact]
+			void ENTP()
+			{
+				ENTP_Series QL = new(this.bars.Close, this.period, useNaN:false);
+				var pta = this.ta.entropy(close: this.df[0], length: this.period);
+
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+			}
 
 
-	[Fact]
+			[Fact]
-	void TEMA()
+			void WMA()
-	{
+			{
-		TEMA_Series QL = new(this.bars.Close, this.period, false);
+				WMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.tema(close: this.df[0], length: this.period);
+				var pta = this.ta.wma(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	}
+			}
 
-	[Fact]
+			[Fact]
-	void ENTP()
+			void DEMA()
-	{
+			{
-		ENTP_Series QL = new(this.bars.Close, this.period, useNaN:false);
+				DEMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.entropy(close: this.df[0], length: this.period);
+				var pta = this.ta.dema(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	}
+			}
 
+			[Fact]
+			void BIAS()
+			{
+				BIAS_Series QL = new(this.bars.Close, this.period, false);
+				var pta = this.ta.bias(close: this.df[0], length: this.period);
 
-	[Fact]
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	void WMA()
+			}
-	{
-		WMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.wma(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+			[Fact]
-	}
+			void KURT()
+			{
+				KURT_Series QL = new(this.bars.Close, this.period, useNaN: false);
+				var pta = this.ta.kurtosis(close: this.df[0], length: this.period);
 
-	[Fact]
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
-	void DEMA()
+			}
-	{
-		DEMA_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.dema(close: this.df[0], length: this.period);
 
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
+			[Fact]
-	}
+			void MAD()
+			{
+				MAD_Series QL = new(this.bars.Close, this.period, useNaN: false);
+				var pta = this.ta.mad(close: this.df[0], length: this.period);
 
-	[Fact]
+				Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	void BIAS()
+			}
-	{
+		*/
-		BIAS_Series QL = new(this.bars.Close, this.period, false);
-		var pta = this.ta.bias(close: this.df[0], length: this.period);
-
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	}
-
-	[Fact]
-	void KURT()
-	{
-		KURT_Series QL = new(this.bars.Close, this.period, useNaN: false);
-		var pta = this.ta.kurtosis(close: this.df[0], length: this.period);
-
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
-	}
-
-	[Fact]
-	void MAD()
-	{
-		MAD_Series QL = new(this.bars.Close, this.period, useNaN: false);
-		var pta = this.ta.mad(close: this.df[0], length: this.period);
-
-		Assert.Equal(System.Math.Round((double)pta.tail(1), 7), Math.Round(QL.Last().v, 7));
-	}
 
 }
-
-*/

Tests/Validations/TA_LIB.cs

@@ -30,6 +30,42 @@ public class TA_LIB
 
 	/////////////////////////////////////////
 
+	[Fact]
+	public void ADD()
+	{
+		ADD_Series QL = new(this.bars.Open, this.bars.Close);
+		Core.Add(this.inopen, this.inclose, 0, this.bars.Count - 1, this.TALIB, out int outBegIdx, out _);
+
+		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
+	}
+
+	[Fact]
+	public void SUB()
+	{
+		SUB_Series QL = new(this.bars.Open, this.bars.Close);
+		Core.Sub(this.inopen, this.inclose, 0, this.bars.Count - 1, this.TALIB, out int outBegIdx, out _);
+
+		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
+	}
+
+	[Fact]
+	public void MUL()
+	{
+		MUL_Series QL = new(this.bars.Open, this.bars.Close);
+		Core.Mult(this.inopen, this.inclose, 0, this.bars.Count - 1, this.TALIB, out int outBegIdx, out _);
+
+		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
+	}
+
+	[Fact]
+	public void DIV()
+	{
+		DIV_Series QL = new(this.bars.Open, this.bars.Close);
+		Core.Div(this.inopen, this.inclose, 0, this.bars.Count - 1, this.TALIB, out int outBegIdx, out _);
+
+		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
+	}
+
 	[Fact]
 	public void SDEV()
 	{
@@ -39,6 +75,7 @@ public class TA_LIB
 		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
 	}
 
+
 	[Fact]
 	public void SMA()
 	{
@@ -112,9 +149,9 @@ public class TA_LIB
 	}
 
 	[Fact]
-	public void ADO()
+	public void ADOSC()
 	{
-		ADO_Series QL = new(this.bars, false);
+		ADOSC_Series QL = new(this.bars, false);
 		Core.AdOsc(this.inhigh, this.inlow, this.inclose, this.involume, 0, this.bars.Count - 1, this.TALIB, out int outBegIdx, out _);
 
 		Assert.Equal(Math.Round(this.TALIB[this.TALIB.Length - outBegIdx - 1], 8), Math.Round(QL.Last().v, 8));
@@ -175,9 +212,9 @@ public class TA_LIB
 		double[] outLower = new double[this.bars.Count];
 		BBANDS_Series QL = new(this.bars.Close, period:26, multiplier:2.0, false);
 		Core.Bbands(this.inclose, 0, this.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], 8), Math.Round(QL.Upper.Last().v, 8));
+		Assert.Equal(Math.Round(outUpper[outUpper.Length - outBegIdx - 1], 7), Math.Round(QL.Upper.Last().v, 7));
-		Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], 8), Math.Round(QL.Mid.Last().v, 8));
+		Assert.Equal(Math.Round(outMiddle[outMiddle.Length - outBegIdx - 1], 7), Math.Round(QL.Mid.Last().v, 7));
-	  Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], 8), Math.Round(QL.Lower.Last().v, 8));
+	  Assert.Equal(Math.Round(outLower[outLower.Length - outBegIdx - 1], 7), Math.Round(QL.Lower.Last().v, 7));
 
 	}
 

docs/coverage.md

@@ -1,155 +1,164 @@
 # Coverage of indicators
 
-| Indicator | QuanTAlib | TA-LIB | Skender | Pandas-TA |
+✔️= Calculation exists in QuanTAlib
-|--|:--:|:--:|:--:|:--:|
+
-| **Basics** |||||
+⭐= Calculation is validated against other TA libraries
-| OC2 - (Open+Close)/2 |✔️|||✔️|
+
-| HL2 - (High+Low)/2 |✔️|||✔️|
+⛔= Not implemented in QuanTAlib (yet)
-| HLC3 - Typical Price |✔️|||✔️|
+
-| OHL3 - (Open+High+Low)/3 |✔️|||✔️|
+| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| OHLC4 - (O+H+L+C)/4 |✔️|||✔️|
+|--|:--:|:--:|:--:|
-| HLCC4 - Weighted Price |✔️||✔️|✔️|
+| ✔️ OC2 - (Open+Close)/2 |️ .OC2 || ️GetBaseQuote |
-| ZL - Zero Lag - De-lagged price |✔️|||✔️|
+| ⭐ HL2 - Median Price | .HL2 | MEDPRICE | ️GetBaseQuote |
-| ADD - Addition |✔️|✔️|||
+| ⭐ HLC3 - Typical Price | .HLC3 | TYPPRICE ||
-| SUB - Subtraction |✔️|✔️|||
+| ✔️ OHL3 - (Open+High+Low)/3 | .OHL3 |||
-| MUL - Multiplication |✔️|✔️|||
+| ⭐ OHLC4 - Average Price | .OHLC4 | AVGPRICE |️ GetBaseQuote |
-| DIV - Division |✔️|✔️|||
+| ⭐ HLCC4 - Weighted Price |  .HLCC4 | WCLPRICE ||
-||||||
+| ✔️ ZL - De-lagged price (Zero-Lag) | ZL_Series |||
-| **Statistics** |||||
+| ⭐ MAX - Max value | MAX_Series | MAX ||
-| BETA - Beta coefficient |||✔️||
+| ⛔ MID - Midpoint value || MIDPOINT ||
-| BIAS - Bias |✔️|||✔️|
+| ⛔ MIDP - Midpoint price || MIDPRICE ||
-| ENTR - Entropy |✔️|||✔️|
+| ⭐ MIN - Min value | MIN_Series | MIN ||
-| KUR - Kurtosis |✔️|||✔️|
+| ⭐ ADD - Addition | ADD_Series | ADD ||
-| LINREG - Linear Regression |✔️|✔️|✔️||
+| ⭐ SUB - Subtraction | SUB_Series | SUB ||
-| MAD - Mean Absolute Deviation |✔️||✔️|✔️|
+| ⭐ MUL - Multiplication | MUL_Series | MUL ||
-| MAPE - Mean Absolute Percent Error |✔️||✔️||
+| ⭐ DIV - Division | DIV_Series | DIV ||
-| MAX - Max value |✔️|✔️|||
+|||||
-| MIN - Min value |✔️|✔️|||
+| **STATISTICS & NUMERICAL ANALYSIS** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| MED - Median value |✔️|✔️||✔️|
+| ✔️ BIAS - Bias | BIAS_Series |||
-| MSE - Mean Squared Error |✔️||✔️||
+| ⛔ CORREL - Pearson's Correlation Coefficient || CORREL | GetCorrelation |
-| PSDEV - Population Standard Deviation |✔️||||
+| ⛔ COVAR - Covariance ||| GetCorrelation |
-| PVAR - Population Variance |✔️||||
+| ✔️ ENTP - Entropy | ENTP_Series |||
-| QUANTILE ||||✔️|
+| ✔️ KURT - Kurtosis | KURT_Series |||
-| SKEW - Skewness ||||✔️|
+| ⭐ LINREG - Linear Regression | LINREG_Series || GetSlope |
-| SMAPE - Symmetric Mean Absolute Percent Error |✔️||||
+| ⭐ MAD - Mean Absolute Deviation | MAD_Series || GetSma |
-| SDEV - Sample Standard Deviation |✔️|✔️|✔️|✔️|
+| ⭐ MAPE - Mean Absolute Percent Error | MAPE_Series || GetSma |
-| VAR - Sample Variance |✔️|||✔️|
+| ✔️ MED - Median value | MED_Series |||
-| WMAPE - Weighted Mean Absolute Percent Error |✔️||||
+| ✔️ MSE - Mean Squared Error | MSE_Series || GetSma |
-| ZSCORE |||✔️|✔️|
+| ⛔ SKEW - Skewness ||||
-||||||
+| ⭐ SDEV - Standard Deviation (Volatility) | SDEV_Series |||
-| **Moving Averages** |||||
+| ✔️ SSDEV - Sample Standard Deviation | SSDEV_Series |||
-| AFIRMA - Autoregressive Finite Impulse Response Moving Average |||||
+| ✔️ SMAPE - Symmetric Mean Absolute Percent Error | SMAPE_Series |||
-| ALMA - Arnaud Legoux Moving Average |✔️||✔️|✔️|
+| ✔️ VAR - Population Variance | VAR_Series |||
-| ARIMA - Autoregressive Integrated Moving Average |||||
+| ✔️ SVAR - Sample Variance | SVAR_Series |||
-| ATR - Average True Range |✔️|✔️|✔️|✔️|
+| ⛔ QUANT - Quantile ||||
-| ATRP - Average True Range Percent |✔️||✔️||
+| ✔️ WMAPE - Weighted Mean Absolute Percent Error | WMAPE_Series |||
-| DEMA - Double EMA |✔️|✔️|✔️|✔️|
+| ⛔ ZSCORE - Number of standard deviations from mean ||||
-| EMA - Exponential Moving Average |✔️|✔️|✔️|✔️|
+|||||
-| EPMA - Endpoint Moving Average |||✔️||
+| **TREND INDICATORS & AVERAGES** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| FWMA - Fibonacci's Weighted Moving Average ||||✔️|
+| ⛔ AFIRMA - Autoregressive Finite Impulse Response Moving Average ||||
-| HEMA - Hull Exponential Moving Average |✔️||||
+| ⭐ ALMA - Arnaud Legoux Moving Average | ALMA_Series || GetAlma |
-| HMA - Hull  Moving Average |✔️||✔️|✔️|
+| ⛔ ARIMA - Autoregressive Integrated Moving Average ||||
-| HWMA - Holt-Winter Moving Average ||||✔️|
+| ⭐ DEMA - Double EMA Average | DEMA_Series | DEMA | GetDema |
-| JMA - Jurik Moving Average |✔️|||✔️|
+| ⭐ EMA - Exponential Moving Average | EMA_Series || GetEma |
-| KAMA - Kaufman's Adaptive Moving Average |✔️|✔️|✔️|✔️|
+| ⛔ EPMA - Endpoint Moving Average ||| GetEpma |
-| LSMA - Least Squares Moving Average |||✔️||
+| ⛔ FWMA - Fibonacci's Weighted Moving Average ||||
-| MACD - Moving Average Convergence/Divergence |✔️|✔️|✔️|✔️|
+| ✔️ HEMA - Hull/EMA Average | HEMA_Series |||
-| MAMA - MESA Adaptive Moving Average ||✔️|✔️||
+| ⛔ Hilbert Transform Instantaneous Trendline || HT_TRENDLINE | GetHtTrendline |
-| MMA - Modified Moving Average |||✔️||
+| ⭐ HMA - Hull  Moving Average | HMA_Series || GetHma |
-| NATR - Normalized Average True Range ||✔️|✔️|✔️|
+| ⛔ HWMA - Holt-Winter Moving Average ||||
-| PPMA - Pivot Point Moving Average |||✔️||
+| ✔️ JMA - Jurik Moving Average | JMA_Series |||
-| PWMA - Pascal's Weighted Moving Average ||||✔️|
+| ⭐ KAMA - Kaufman's Adaptive Moving Average | KAMA_Series | KAMA | GetKama |
-| RMA - WildeR's Moving Average |✔️|||✔️|
+| ⛔ LSMA - Least Squares Moving Average ||||
-| SINWMA - Sine Weighted Moving Average ||||✔️|
+| ⭐ MACD - Moving Average Convergence/Divergence | MACD_Series | MACD | GetMacd |
-| SMA - Simple Moving Average |✔️|✔️|✔️|✔️|
+| ⛔ MAMA - MESA Adaptive Moving Average || MAMA | GetMama |
-| SMMA - Smoothed Moving Average |✔️||✔️||
+| ⛔ MMA - Modified Moving Average ||||
-| STOCH - Stochastic Oscillator ||✔️|✔️|✔️|
+| ⛔ PPMA - Pivot Point Moving Average ||||
-| SSF - Ehler's Super Smoother Filter ||||✔️|
+| ⛔ PWMA - Pascal's Weighted Moving Average ||||
-| SUP - Supertrend |||✔️|✔️|
+| ✔️ RMA - WildeR's Moving Average | RMA__Series |||
-| SWMA - Symmetric Weighted Moving Average ||||✔️|
+| ⛔ SINWMA - Sine Weighted Moving Average ||||
-| T3 - Tillson T3 Moving Average ||✔️|✔️|✔️|
+| ⭐ SMA - Simple Moving Average | SMA_Series |||
-| TEMA - Triple EMA |✔️|✔️|✔️|✔️|
+| ⭐ SMMA - Smoothed Moving Average | SMMA_Series |||
-| TRIMA - Triangular Moving Average ||✔️||✔️|
+| ⛔ SSF - Ehler's Super Smoother Filter ||||
-| VIDYA - Variable Index Dynamic Average ||||✔️|
+| ⛔ SUP - Supertrend ||||
-| VWAP - Volume Weighted Average Price |||✔️|✔️|
+| ⛔ SWMA - Symmetric Weighted Moving Average ||||
-| VWMA - Volume Weighted Moving Average |||✔️|✔️|
+| ⛔ T3 - Tillson T3 Moving Average ||||
-| WMA - Weighted Moving Average |✔️|✔️|✔️|✔️|
+| ⭐ TEMA - Triple EMA Average | TEMA_Series |||
-| ZLEMA - Zero Lag EMA |✔️|||✔️|
+| ⛔ TRIMA - Triangular Moving Average ||||
-||||||
+| ⛔ VIDYA - Variable Index Dynamic Average ||||
-| **Oscillators and Indices** |||||
+| ⭐ WMA - Weighted Moving Average | WMA_Series |||
-| AC - Acceleration Oscillator ||||✔️|
+| ✔️ ZLEMA - Zero Lag EMA Average | ZLEMA_Series |||
-| AD - Chaikin Accumulation Distribution ||✔️|✔️|✔️|
+|||||
-| ADOSC - Chaikin Accumulation Distribution Oscillator ||✔️|✔️||
+| **VOLATILITY INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| ADX - Average Directional Movement Index ||✔️|✔️|✔️|
+| ⭐ ADL - Chaikin Accumulation Distribution Line | ADL_Series | AD | GetAdl |
-| ADXR - Average Directional Movement Index Rating ||✔️|✔️||
+| ⭐ ADOSC - Chaikin Accumulation Distribution Oscillator | ADOSC_Series | ADOSC| GetAdl |
-| AO - Awesome Oscillator |||✔️|✔️|
+| ⭐ ATR - Average True Range | ATR_Series | ATR | GetAtr |
-| APO - Absolute Price Oscillator ||✔️||✔️|
+| ⭐ ATRP - Average True Range Percent | ATRP_Series || GetAtr |
-| AROON - Aroon oscillator ||✔️|✔️|✔️|
+| ✔️ BETA - Beta coefficient || BETA | GetBeta |
-| BBANDS - Bollinger Bands ||✔️|✔️|✔️|
+| ⭐ BBANDS - Bollinger Bands® | BBANDS_Series | BBANDS | GetBollingerBands |
-| BOP - Balance of Power ||✔️|✔️|✔️|
+| ⛔ CRSI - Connor RSI ||| GetConnorsRsi |
-| CCI - Commodity Channel Index |✔️|✔️|✔️|✔️|
+| ⛔ DON - Donchian Channels ||| GetDonchian |
-| CFO - Chande Forcast Oscillator ||||✔️|
+| ⛔ FCB - Fractal Chaos Bands ||| GetFcb |
-| CMF - Chaikin Money Flow |||✔️|✔️|
+| ⛔ HV - Historical Volatility ||||
-| CMO - Chande Momentum Oscillator ||✔️||✔️|
+| ⛔ ICH - Ichimoku ||| GetIchimoku |
-| COG - Center of Gravity ||||✔️|
+| ⛔ KEL - Keltner Channels ||| GetKeltner |
-| CRSI - Connor RSI |||✔️||
+| ⛔ NATR - Normalized Average True Range || NATR | GetAtr |
-| CTI - Ehler's Correlation Trend Indicator ||||✔️|
+| ⭐ RSI - Relative Strength Index | RSI_Series ||
-| DMI - Directional Movement Index ||✔️|✔️|✔️|
+| ⛔ SAR - Parabolic Stop and Reverse || SAR | GetParabolicSar |
-| EFI - Elder Ray's Force Index |||✔️|✔️|
+| ⛔ SRSI - Stochastic RSI ||||
-| GAT - Alligator oscillator |||✔️||
+| ⛔ STARC - Starc Bands ||||
-| KRI - Kairi Relative Index |||||
+| ⭐ TR - True Range | TR_Series |||
-| KVO - Klinger Volume Oscillator |||✔️|✔️|
+| ⛔ UI - Ulcer Index ||||
-| MFI - Money Flow Index ||✔️|✔️|✔️|
+| ⛔ VSTOP - Volatility Stop ||||
-| MOM - Momentum |||✔️|✔️|
+|||||
-| NVI - Negative Volume Index ||||✔️|
+| **MOMENTUM INDICATORS & OSCILLATORS** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| PO - Price Oscillator ||||✔️|
+| ⛔ AC - Acceleration Oscillator ||||
-| PPO - Percentage Price Oscillator ||✔️||✔️|
+| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx |
-| PVI - Positive Volume Index ||||✔️|
+| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx |
-| RSI - Relative Strength Index |✔️|✔️|✔️|✔️|
+| ⛔ AO - Awesome Oscillator ||| GetAwesome |
-| RVGI - Relative Vigor Index ||||✔️|
+| ⛔ APO - Absolute Price Oscillator || APO ||
-| SRSI - Stochastic RSI |||✔️|✔️|
+| ⛔ AROON - Aroon oscillator || AROON | GetAroon |
-| TRIX - 1-day ROC of TEMA ||✔️|✔️|✔️|
+| ⛔ BOP - Balance of Power || BOP | GetBop |
-| TSI - True Strength Index |||✔️|✔️|
+| ⭐ CCI - Commodity Channel Index | CCI_Series | CCI | GetCci |
-| UI - Ulcer Index |||✔️|✔️|
+| ⛔ CFO - Chande Forcast Oscillator ||||
-| UO - Ultimate Oscillator ||✔️|✔️|✔️|
+| ⛔ CMF - Chaikin Money Flow ||||
-| WGAT - Williams Alligator |||✔️||
+| ⛔ CMO - Chande Momentum Oscillator || CMO | GetCmo |
-||||||
+| ⛔ COG - Center of Gravity ||||
-| **Volume** |||||
+| ⛔ CTI - Ehler's Correlation Trend Indicator ||||
-| AOBV - Archer On-Balance Volume ||||✔️|
+| ⛔ DPO - Detrended Price Oscillator ||| GetDpo |
-| OBV - On-Balance Volume ||✔️|✔️|✔️|
+| ⛔ DMI - Directional Movement Index || DX | GetAdx |
-| PRS - Price Relative Strength |||✔️||
+| ⛔ EFI - Elder Ray's Force Index ||| GetElderRay |
-| PVOL - Price-Volume |||||
+| ⛔ GAT - Alligator oscillator ||| GetGator |
-| PVR - Price Volume Rank ||||✔️|
+| ⛔ HURST - Hurst Exponent ||| GetHurst |
-| PVT - Price Volume Trend ||||✔️|
+| ⛔ KRI - Kairi Relative Index ||||
-| VP - Volume Profile ||||✔️|
+| ⛔ KVO - Klinger Volume Oscillator ||||
-||||||
+| ⛔ MFI - Money Flow Index || MFI | GetMfi |
-|**Unsorted**|||||
+| ⛔ ROC - Rate of Change (Momentum) || MOM | GetRoc |
-| CHN - Price Channel |||✔️||
+| ⛔ NVI - Negative Volume Index ||||
-| COPPOCK - Coppock Curve ||||✔️|
+| ⛔ PO - Price Oscillator ||||
-| CORREL - Pearson's Correlation Coefficient ||✔️|✔️||
+| ⛔ PPO - Percentage Price Oscillator || PPO ||
-| EOM - Ease of Movement ||||✔️|
+| ⛔ PMO - Price Momentum Oscillator ||||
-| HILO - Gann High-Low Activator ||||✔️|
+| ⛔ PVI - Positive Volume Index ||||
-| HV - Historical Volatility |||✔️||
+| ⛔ RVGI - Relative Vigor Index ||||
-| HT - HT Trendline |||✔️||
+| ⛔ SMI - Stochastic Momentum Index ||||
-| ICH - Ichimoku |||✔️|✔️|
+| ⛔ STOCH - Stochastic Oscillator ||||
-| MCGD - McGinley Dynamic ||||✔️|
+| ⛔ TRIX - 1-day ROC of TEMA ||||
-| ROC - Rate of Change ||✔️|✔️|✔️|
+| ⛔ TSI - True Strength Index ||||
-| SAR - Parabolic Stop and Reverse ||✔️|✔️|✔️|
+| ⛔ UO - Ultimate Oscillator ||||
-| STC - Schaff Trend Cycle |||✔️|✔️|
+| ⛔ WGAT - Williams Alligator ||||
-| TR - True Range ||✔️|✔️|✔️|
+|||||
-| WILLR - Larry Williams' %R ||✔️|✔️|✔️|
+| **VOLUME INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| HURST - Hurst Exponent |||✔️||
+| ⛔ AOBV - Archer On-Balance Volume ||||
-| VOR - Vortex Indicator |||✔️|✔️|
+| ⛔ OBV - On-Balance Volume || OBV | GetObv |
-| DON - Donchian Channels |||✔️|✔️|
+| ⛔ PRS - Price Relative Strength |||
-| FCB - Fractal Chaos Bands |||✔️||
+| ⛔ PVOL - Price-Volume ||||
-| KEL - Keltner Channels |||✔️|✔️|
+| ⛔ PVO - Percentage Volume Oscillator ||||
-| PVT - Pivot Points |||✔️||
+| ⛔ PVR - Price Volume Rank ||||
-| STARC - Starc Bands |||✔️||
+| ⛔ PVT - Price Volume Trend ||||
-| DPO - De-trended Price Oscillator |||✔️|✔️|
+| ⛔ VP - Volume Profile ||||
-| KDJ - KDJ Index |||✔️|✔️|
+| ⛔ VWAP - Volume Weighted Average Price ||||
-| SMI - Stochastic Momentum Index |||✔️|✔️|
+| ⛔ VWMA - Volume Weighted Moving Average ||||
-| CHAND - Chandelier Exit |||✔️||
+|||||
-| VSTOP - Volatility Stop |||✔️||
+|**Unsorted** | **QuanTAlib** | **TA-LIB** | **Skender** |
-| PVO - Percentage Volume Oscillator |||✔️|✔️|
+| ⛔ CHN - Price Channel ||||
-| Hilbert Transform Instantaneous Trendline |||||
+| ⛔ COPPOCK - Coppock Curve ||||
-| PMO - Price Momentum Oscillator |||✔️||
+| ⛔ EOM - Ease of Movement ||||
+| ⛔ HILO - Gann High-Low Activator ||||
+| ⛔ HT - HT Trendline ||||
+| ⛔ MCGD - McGinley Dynamic ||||
+| ⛔ STC - Schaff Trend Cycle ||||
+| ⛔ WILLR - Larry Williams' %R ||||
+| ⛔ VOR - Vortex Indicator ||||
+| ⛔ PVT - Pivot Points ||||
+| ⛔ KDJ - KDJ Index ||||
+| ⛔ CHAND - Chandelier Exit ||||