Merge branch 'dev' into main

.gitignore

@@ -354,3 +354,4 @@ MigrationBackup/
 # Ionide (cross platform F# VS Code tools) working folder
 .ionide/
 dotCover.Output.dcvr
+/Tests/GlobalSuppressions.cs

Quantower/Quantower.csproj

@@ -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>

Source/Basics/Single_TSeries_Abstract.cs

@@ -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 int _period;
-    protected readonly bool _NaN;
+  protected readonly bool _NaN;
-    protected readonly TSeries _data;
+  protected readonly TSeries _data;
+  protected int _p;
 
-    // Chainable Constructor - add it at the end of primary constructor :base(source: source, period: period, useNaN: useNaN)
+  // 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)
+  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;
+      l.RemoveAt(0);
-        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); }
     }
+    return ret;
+  }
 }

Source/Feeds/GBM_Feed.cs

@@ -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 Open = GBM_value(seed, volatility*volatility, drift, precision);
-        double Close = GBM_value(Open, volatility, drift);
+        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);
     }
 }

Source/QuanTAlib.csproj

@@ -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>

Source/Trends/DEMA_Series.cs

@@ -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 System.Collections.Generic.List<double> _buffer1 = new();
-    private readonly double _k, _k1m;
+    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);
+        _k = 2.0 / (_p + 1);
-        this._k1m = 1.0 - this._k;
         if (_data.Count > 0) { base.Add(_data); }
     }
 
@@ -34,26 +35,40 @@ public class DEMA_Series : Single_TSeries_Indicator
     {
         if (update)
         {
-            this._lastema1 = this._lastlastema1;
+            _lastema1 = _lastlastema1;
-            this._lastema2 = this._lastlastema2;
+            _lastema2 = _lastlastema2;
         }
 
-        double _ema1, _ema2;
+        double _ema1, _ema2, _dema;
-
+        if (this.Count < _p)
-        if (this.Count < this._p)
         {
-            Add_Replace_Trim(_buffer, TValue.v, _p, update);
+            Add_Replace_Trim(_buffer1, TValue.v, _p, update);
-            double _sma = _buffer.Average();
+            _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);
+            _ema1 = (TValue.v - _lastema1) * _k + _lastema1;
-            _ema2 = (_ema1 * this._k) + (this._lastema2 * this._k1m);
+
+            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);
     }
-}
+}

Source/Trends/DWMA_Series.cs

@@ -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);
+    }
+}

Source/Trends/EMA_Series.cs

@@ -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
         {

Source/Trends/JMA_Series.cs

@@ -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 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 readonly System.Collections.Generic.List<double> vbuffer10;
+	private double p_upperBand, p_lowerBand, p_Kv, p_prev_ma1, p_prev_det0, p_prev_det1, p_prev_vsum, p_prev_jma;
-    private readonly System.Collections.Generic.List<double> vsum65;
 
-    private double prev_ma1, prev_det0, prev_det1, prev_jma, bsmax, bsmin;
+	public JMA_Series(TSeries source, int period, double phase = 0.0, bool useNaN = false) : base(source, period, useNaN) {
-    private double o_prev_ma1, o_prev_det0, o_prev_det1, o_prev_jma, o_bsmax, o_bsmin;
+		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)
+	public override void Add((System.DateTime t, double v) TValue, bool update) {
-    {
+		if (update) {
-        this.vbuffer10 = new();
+			upperBand = p_upperBand; lowerBand = p_lowerBand; Kv = p_Kv; prev_vsum = p_prev_vsum;
-        this.vsum65 = new();
+			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
+		// from Tvalue to volty
-        this.pr = (phase < -100) ? 0.5 : (phase > 100) ? 2.5 : (phase * 0.01) + 1.5;
+		del1 = TValue.v - upperBand;
-        double len1 = Math.Max((Math.Log(Math.Sqrt(0.5 * (_p - 1))) / Math.Log(2.0)) + 2.0, 0);
+		del2 = TValue.v - lowerBand;
-        this.pow1 = Math.Max(len1 - 2, 0.5);
+		upperBand = (del1 > 0) ? TValue.v : TValue.v - (Kv * del1);
-        this.rvolty = Math.Exp((1 / this.pow1) * Math.Log(len1));
+		lowerBand = (del2 < 0) ? TValue.v : TValue.v - (Kv * del2);
-        this.len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
+		double volty = 0;
-        this.beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
+		if (Math.Abs(del1) > Math.Abs(del2)) { volty = Math.Abs(del1); }
-        if (base._data.Count > 0) { base.Add(base._data); }
+		if (Math.Abs(del1) < Math.Abs(del2)) { volty = Math.Abs(del2); }
-    }
 
-    public override void Add((System.DateTime t, double v) TValue, bool update)
+		//// from volty to avolty
-    {
+		if (update) { volty_10[volty_10.Count - 1] = volty; } 	else { volty_10.Add(volty); }
-        if (this.Count == 0)
+		if (volty_10.Count > 10) { volty_10.RemoveAt(0); }
-        {
+		vsum = prev_vsum + 0.1 * (volty - volty_10.First());
-            this.prev_ma1 = this.prev_jma = TValue.v;
+		if (update) { vsum_buff[vsum_buff.Count - 1] = vsum; } else { vsum_buff.Add(vsum); }
-            this.bsmax = this.bsmin = this.prev_det0 = this.prev_det1 = 0;
+		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)
+		/// from avolty to rolty
-        {
+		double rvolty = (avolty > 0) ? volty / avolty : 0;
-            this.prev_jma = this.o_prev_jma;
+		double len1 = (Math.Log(Math.Sqrt(_p)) / Math.Log(2.0)) + 2;
-            this.prev_ma1 = this.o_prev_ma1;
+		if (len1 < 0) len1 = 0;
-            this.prev_det0 = this.o_prev_det0;
+		double pow1 = Math.Max(len1 - 2.0, 0.5);
-            this.prev_det1 = this.o_prev_det1;
+		if (rvolty > Math.Pow(len1, 1.0 / pow1)) rvolty = Math.Pow(len1, 1.0 / pow1);
-            this.bsmax = this.o_bsmax;
+		if (rvolty < 1)	rvolty = 1;
-            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;
-        }
 
-        double hprice = TValue.v;
+		//// from rvolty to second smoothing
-        double lprice = TValue.v;
+		double pow2 = Math.Pow(rvolty, pow1);
-        for (int i = 0; i <= Math.Min(9, this._data.Count - 1); i++)
+		double len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
-        {
+		Kv = Math.Pow(len2 / (len2 + 1), Math.Sqrt(pow2));
-            var _item = this._data[this._data.Count - 1 - i].v;
+		double alpha = Math.Pow(beta, pow2);
-            hprice = (_item > hprice) ? _item : hprice;
+		double ma1 = (1 - alpha) * TValue.v + alpha * prev_ma1; 
-            lprice = (_item < lprice) ? _item : lprice;
+		prev_ma1 = ma1;
-        }
+		double det0 = (1 - beta) * (TValue.v - ma1) + beta * prev_det0;	
-        double del1 = hprice - this.bsmax;
+		prev_det0 = det0;
-        double del2 = lprice - this.bsmin;
 
-        double volty = (Math.Abs(del1) != Math.Abs(del2))
+		/// from second smoothing to jma
-                           ? Math.Max(Math.Abs(del1), Math.Abs(del2))
+		double ma2 = ma1 + pr * det0;
-                           : 0;
+		double det1 = (1 - alpha) * (1 - alpha) * (ma2 - prev_jma) + alpha * alpha * prev_det1;
-        if (update)
+		prev_det1 = det1;
-        {
+		double jma = prev_jma + det1;
-            this.vbuffer10[this.vbuffer10.Count - 1] = volty;
+		prev_jma = jma;
-        }
-        else
-        {
-            this.vbuffer10.Add(volty);
-        }
-        if (this.vbuffer10.Count > 10)
-        {
-            this.vbuffer10.RemoveAt(0);
-        }
 
-        double prevvsum =
+		base.Add((TValue.t, jma), update, _NaN);
-            (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);
-        }
 
-        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);
-        }
-}

Source/Trends/MAMA_Series.cs

@@ -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);

Source/Trends/SMA_Series.cs

@@ -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)
+	private readonly System.Collections.Generic.List<double> _buffer = new();
-    {
+	private double _sma, _oldsma;
-        if (base._data.Count > 0) { base.Add(base._data); }
+	private double _topv, _oldtopv;
-    }
+	public SMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
-    private readonly System.Collections.Generic.List<double> _buffer = new();
+	{
+		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)
+		// rolling back if update, storing data for potential future update
-    {
+		if (update)
-        Add_Replace_Trim(_buffer, TValue.v, _p, update);
+		{
-        double _sma = _buffer.Sum() / _buffer.Count;
+			_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);
+	}
+}

Source/Trends/T3_Series.cs

@@ -4,19 +4,30 @@ using System.Linq;
 using System.Numerics;
 
 /* <summary>
-T3: Triple Exponential Moving Average
+T3: Tillson T3 Moving Average
-    TEMA uses EMA(EMA(EMA())) to calculate less laggy Exponential 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);

Source/Volatility/ADL_Series.cs

@@ -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;
+		_lastadl = _lastlastadl = 0;
-		if (_bars.Count > 0)
+		if (_bars.Count > 0) { base.Add(_bars); }
-		{ base.Add(_bars); }
 	}
 
 	public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
 	{
-		if (update)
+		if (update) { this._lastadl = this._lastlastadl; }
-		{ this._lastadl = this._lastlastadl; }
 
-		double _mfm = ((TBar.c - TBar.l) - (TBar.h - TBar.c)) / (TBar.h - TBar.l);
+		double _adl = 0;
-		double _mfv = _mfm * TBar.v;
+		double tmp = TBar.h - TBar.l;
-		double _adl = this._lastadl + _mfv;
+		if (tmp > 0.0 ) { _adl = _lastadl + ((2*TBar.c - TBar.l - TBar.h) / tmp * TBar.v); }
 
 		this._lastlastadl = this._lastadl;
 		this._lastadl = _adl;

Source/Volatility/ADOSC_Series.cs

@@ -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);
 	}
-}
+}
+*/

Tests/Series/Update.cs

@@ -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();

Tests/Tests.csproj

@@ -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>

Tests/Validations/Pandas_TA.cs

@@ -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));
-	}
-
-}

Tests/Validations/Skender_Stock.cs

@@ -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));
-    }
-
-}

Tests/Validations/TA_LIB.cs

@@ -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));
-    }
-
-}

Tests/Validations/Trends/Pandas_TA.cs

@@ -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));
+        }
+    }
+
+}

Tests/Validations/Trends/Skender.cs

@@ -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));
+    }
+  }
+
+}

Tests/Validations/Trends/TA_LIB.cs

@@ -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));
+    }
+  }
+
+}

Tests/Validations/Trends/Tulip.cs

@@ -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));
+		}
+	}
+}

docs/EMA.md

@@ -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
+
+![Alt text](./img/EMA_chart.svg)
+
+
+
+## References

docs/SMA.md

@@ -0,0 +1,39 @@
+![Alt text](./img/SMA_chart.svg)
+# 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/

docs/_sidebar.md

@@ -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")

docs/getting_started.ipynb

@@ -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": [
+   "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'"
-     ]
-    }
-   ],
    "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": [
+   "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"
-    }
-   ],
    "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": [
+   "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"
-    }
-   ],
    "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": [
+   "outputs": [],
-    {
-     "data": {
-      "text/html": [
-       "<div class=\"dni-plaintext\">10</div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "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": [
+   "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"
-    }
-   ],
    "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": [
+   "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"
-    }
-   ],
    "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": {
+  "polyglot_notebook": {
-   "file_extension": ".cs",
+   "kernelInfo": {
-   "mimetype": "text/x-csharp",
+    "defaultKernelName": "csharp",
-   "name": "C#",
+    "items": [
-   "pygments_lexer": "csharp",
+     {
-   "version": "9.0"
+      "aliases": [
-  },
+       "c#",
-  "orig_nbformat": 4
+       "C#"
+      ],
+      "languageName": "C#",
+      "name": "csharp"
+     },
+     {
+      "aliases": [
+       "frontend"
+      ],
+      "languageName": null,
+      "name": "vscode"
+     },
+     {
+      "aliases": [],
+      "languageName": "KQL",
+      "name": "kql"
+     }
+    ]
+   }
+  }
  },
  "nbformat": 4,
  "nbformat_minor": 2

docs/img/EMA_chart.ipynb

@@ -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
+}

docs/img/SMA_chart.ipynb

@@ -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);"
+   ]
+  }
+ ],
+ "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
+}

docs/index.html

@@ -6,20 +6,28 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1" />
   <meta name="description" content="Description">
   <meta name="viewport" content="width=device-width, initial-scale=1.0, minimum-scale=1.0">
-  <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/docsify-themeable@0/dist/css/theme-simple.css">
+  <link rel="stylesheet" href="//cdn.jsdelivr.net/npm/docsify@4/lib/themes/vue.css">
+
 </head>
 <body>
   <div id="app"></div>
   <script>
     window.$docsify = {
-      name: 'QuanTAlib',
+      loadSidebar: true,
-      repo: 'mihakralj/quantalib'
+      subMaxLevel: 1,
-    }
+      name: '',
+      repo: '',
+      latex: {
+        inlineMath   : [['$', '$'], ['\\(', '\\)']], // default
+        displayMath  : [['$$', '$$']],               // default
+        }
+    };
   </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>
+  <!-- LaTeX display engine -->
-  <script src="//unpkg.com/@rakutentech/docsify-code-inline/dist/index.min.js"></script>
+  <script src="//cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
+  <!--  docsify-latex plugin -->
+  <script src="//cdn.jsdelivr.net/npm/docsify-latex@0"></script>
 </body>
 </html>

docs/indicators.md

@@ -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 |||||

docs/readme.md

@@ -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 |||
+| ⭐ MAX - Max value | `MAX_Series` | MAX ||| max |
-| ⭐ MIN - Min value | `MIN_Series` | MIN |||
+| ⭐ MIN - Min value | `MIN_Series` | MIN ||| min |
-| ⭐ SUM - Summation | `SUM_Series` | SUM |||
+| ⭐ SUM - Summation | `SUM_Series` | SUM ||| sum |
-| ⭐ ADD - Addition | `ADD_Series` | ADD |||
+| ⭐ ADD - Addition | `ADD_Series` | ADD ||| add |
-| ⭐ SUB - Subtraction | `SUB_Series` | SUB |||
+| ⭐ SUB - Subtraction | `SUB_Series` | SUB ||| sub |
-| ⭐ MUL - Multiplication | `MUL_Series` | MUL |||
+| ⭐ MUL - Multiplication | `MUL_Series` | MUL ||| mul |
-| ⭐ DIV - Division | `DIV_Series` | DIV |||
+| ⭐ 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 |
+| ⭐ DEMA - Double EMA Average | `DEMA_Series` | DEMA | GetDema | dema | dema |
-| ⭐ EMA - Exponential Moving Average | `EMA_Series` | EMA | GetEma | ema |
+| ⭐ 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** |
+| **VOLATILITY INDICATORS** |
-| ⭐ ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad |
+||||||
-| ⭐ ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ADOSC| GetAdl | adosc |
+| ⭐ ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad | ad |
-| ⭐ ATR - Average True Range | `ATR_Series` | ATR | GetAtr | atr |
+| ⭐ 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 |||||
 ||||||
-| **MOMENTUM INDICATORS & OSCILLATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
+| **MOMENTUM INDICATORS & OSCILLATORS** |
+||||||
 | ⛔ AC - Acceleration Oscillator |||||
-| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx ||
+| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx || adx |
-| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx ||
+| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx || adxr |
-| ⛔ AO - Awesome Oscillator ||| GetAwesome ||
+| ⛔ AO - Awesome Oscillator ||| GetAwesome || ao |
-| ⛔ APO - Absolute Price Oscillator || APO |||
+| ⛔ APO - Absolute Price Oscillator || APO ||| apo |
-| ⛔ AROON - Aroon oscillator || AROON | GetAroon ||
+| ⛔ AROON - Aroon oscillator || AROON | GetAroon || aroon |
-| ⛔ BOP - Balance of Power || BOP | GetBop ||
+| ⛔ BOP - Balance of Power || BOP | GetBop || bop |
-| ⭐ CCI - Commodity Channel Index | `CCI_Series` | CCI | GetCci ||
+| ⭐ 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 |||||