Merge branch 'dev' into main

.github/workflows/main_automation.yml

@@ -80,14 +80,14 @@ jobs:
         project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
         coverage-reports: ./coveragereport.xml
 
-#    - name: Release
-#      uses: marvinpinto/action-automatic-releases@latest
-#      with:
-#        repo_token: "${{ secrets.GITHUB_TOKEN }}"
-#        automatic_release_tag: "latest"
-#        prerelease: true
-#        title: "Latest Build"
-#        files: /Quantower/Settings/Scripts/Indicators/QuanTAlib/*.dll
+    - name: Release
+      uses: marvinpinto/action-automatic-releases@latest
+      with:
+        repo_token: "${{ secrets.GITHUB_TOKEN }}"
+        automatic_release_tag: "latest"
+        prerelease: true
+        title: "Latest Build"
+        files: /Quantower/Settings/Scripts/Indicators/QuanTAlib/*.dll
 
     - name: Authenticate to Github packages source
       run: dotnet nuget add source

Source/Trends/DEMA_Series.cs

@@ -30,6 +30,7 @@ public class DEMA_Series : Single_TSeries_Indicator
     {
         _k = 2.0 / (_p + 1);
 		_useSMA = useSMA;
+    _lastema1 = _lastema2 =0;
 		if (_data.Count > 0) { base.Add(_data); }
     }
 
@@ -48,22 +49,9 @@ public class DEMA_Series : Single_TSeries_Indicator
             _ema1 = 0;
             for (int i=0; i<_buffer1.Count; i++) { _ema1 += _buffer1[i]; }
             _ema1 /= _buffer1.Count;
-
-            Add_Replace_Trim(_buffer2, _ema1, _p, update);
-            _ema2 = 0;
-            for (int i = 0; i < _buffer2.Count; i++) { _ema2 += _buffer2[i]; }
-            _ema2 /= _buffer2.Count;
+            _ema2 = _ema1;
         }
-        else if(this.Count < (2*_p - 1) && _useSMA) // second _p
-        {
-            _ema1 = (TValue.v - _lastema1) * _k + _lastema1;
-
-            Add_Replace_Trim(_buffer2, _ema1, _p, update);
-            _ema2 = 0;
-            for (int i = 0; i < _buffer2.Count; i++) { _ema2 += _buffer2[i]; }
-            _ema2 /= _buffer2.Count; 
-        }
-        else // all others
+        else
         {
             _ema1 = (TValue.v - _lastema1) * _k + _lastema1;
             _ema2 = (_ema1 - _lastema2) * _k + _lastema2;

Tests/Tests.csproj

@@ -9,6 +9,8 @@
     <Platforms>AnyCPU;x64</Platforms>
   </PropertyGroup>
   <ItemGroup>
+      <PackageReference Include="Python.Included" Version="3.11.1" />
+      <PackageReference Include="pythonnet" Version="3.0.1" />
       <PackageReference Include="xunit" Version="2.4.2" />
     <PackageReference Include="xunit.runner.visualstudio" Version="2.4.5">
       <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
@@ -16,7 +18,7 @@
     </PackageReference>
     <PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.5.0-preview-20221221-03" />
     <PackageReference Include="TALib.NETCore" Version="0.4.4" />
-    <PackageReference Include="Skender.Stock.Indicators" Version="2.4.5" />
+    <PackageReference Include="Skender.Stock.Indicators" Version="2.4.6" />
     <PackageReference Include="Tulip.NETCore" Version="0.8.0.1" />
     <PackageReference Include="System.Text.Json" Version="7.0.1" />
   </ItemGroup>

Tests/Validations/Trends/Pandas_TA.cs

@@ -1,4 +1,8 @@
+<<<<<<< HEAD
 /*
+=======
+
+>>>>>>> dev
 using Xunit;
 using System;
 using QuanTAlib;
@@ -20,7 +24,7 @@ public class PandasTA : IDisposable
 	public PandasTA() {
         bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0);
         period = rnd.Next(maxValue: 28) + 3;
-        sample = 200;
+        sample = period+1;
 	    digits = 10;
 
 		// Checking the host OS and setting PythonDLL accordingly
@@ -186,7 +190,20 @@ public class PandasTA : IDisposable
             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 MACD() {
+		MACD_Series QL = new(bars.Close, 26,fast: 12,signal:9);
+		var pta = df.ta.macd(close: df.close).to_numpy();
+		for (int i = QL.Length; i > QL.Length - sample; i--) {
+			double QL_item = QL[i - 1].v;
+			double PanTA_item = (double)pta[i - 1][0];
+			Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+			QL_item = QL.Signal[i - 1].v;
+			PanTA_item = (double)pta[i - 1][2];
+			Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
 	[Fact] void MAD()
 	{
 		MAD_Series QL = new(bars.Close, period, useNaN: false);
@@ -380,4 +397,7 @@ public class PandasTA : IDisposable
     }
 
 }
-*/
+<<<<<<< HEAD
+*/
+=======
+>>>>>>> dev

Tests/Validations/Trends/Skender.cs

@@ -17,7 +17,7 @@ public class Skender
     bars = new(Bars: 10000, Volatility: 0.5, Drift: 0.0, Precision: 2);
     period = rnd.Next(30) + 5;
     digits = 5; //minimizing rounding errors in type conversions
-    skip = 300;
+    skip = period+2;
 
     quotes = bars.Select(q => new Quote
     {
@@ -156,7 +156,7 @@ public class Skender
   [Fact]
   public void DEMA()
   {
-    DEMA_Series QL = new(bars.Close, period, false);
+    DEMA_Series QL = new(bars.Close, period, false, useSMA: true);
     var SK = quotes.GetDema(period).Select(i => i.Dema.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
@@ -213,20 +213,19 @@ public class Skender
 			Assert.InRange(SK_item! - QL_item, -Math.Pow(10, -digits), Math.Pow(10, -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--)
+    for (int i = QL.Length; i > 250; i--)
     {
 			double QL_item = QL[i - 1].v;
 			double SK_item = SK.ElementAt(i - 1);
 			Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
-  } */
+  }
   [Fact]
   public void LINREG()
   {
@@ -253,14 +252,14 @@ public class Skender
   {
     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--)
+    for (int i = QL.Length; i > 27; 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.Pow(10,-digits), Math.Pow(10,-digits));
-      QL_item = Math.Round(QL.Signal[i - 1].v, digits: digits);
-      SK_item = Math.Round(SK.ElementAt(i - 1).Signal.Null2NaN()!, digits: digits);
+      double QL_item = QL[i - 1].v;
+      double SK_item = SK.ElementAt(i - 1).Macd.Null2NaN()!;
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
+      //QL_item = QL.Signal[i - 1].v;
+      //SK_item = SK.ElementAt(i - 1).Signal.Null2NaN()!;
+      //Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
   [Fact]
@@ -319,11 +318,10 @@ public class Skender
   {
     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--)
-    {
+    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);
+			// adding volume[0] to OBV to pass the test and keep compatibility with TA-LIB
+			double SK_item = Math.Round(SK.Last()! + (double)quotes.First().Volume!, digits: digits);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -411,8 +409,7 @@ public class Skender
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
-  /*
-  [Fact]
+	[Fact]
   public void T3()
   {
     T3_Series QL = new(source: bars.Close, period: period, vfactor: 0.7, false);
@@ -423,8 +420,18 @@ public class Skender
       double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
-  }*/
-  [Fact]
+  }
+	[Fact]
+	public void TRIX() {
+		TRIX_Series QL = new(bars.Close, period, false);
+		var SK = quotes.GetTrix(period).Select(i => i.Trix.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.Pow(10, -digits), Math.Pow(10, -digits));
+		}
+	}
+	[Fact]
   public void TEMA()
   {
     TEMA_Series QL = new(bars.Close, period, false);
@@ -448,7 +455,6 @@ public class Skender
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
-  /*
   [Fact]
   public void WMA()
   {
@@ -461,8 +467,7 @@ public class Skender
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
-  */
-  [Fact]
+    [Fact]
   public void ZSCORE()
   {
     ZSCORE_Series QL = new(bars.Close, period, useNaN: false);

Tests/Validations/Trends/TA_LIB.cs

@@ -21,7 +21,7 @@ public class Ta_Lib
   {
     bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0, Precision: 3);
     period = rnd.Next(28) + 3;
-    skip = 500;
+    skip = period+2;
     digits = 10;
 
     TALIB = new double[bars.Count];
@@ -81,32 +81,27 @@ public class Ta_Lib
       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);
+    BBANDS_Series QL = new(bars.Close, period: period, multiplier: 2.0, false);
+    Core.Bbands(inclose, 0, bars.Count - 1, outRealUpperBand: outUpper, outRealMiddleBand: outMiddle, outRealLowerBand: outLower, out int outBegIdx, out _, optInTimePeriod: period, 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);
+      double QL_item = QL.Upper[i].v;
+      double TA_item = outUpper[i - outBegIdx];
+			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), high: Math.Exp(-digits));
+			QL_item = QL.Mid[i].v;
+      TA_item = outMiddle[i - outBegIdx];
+			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), high: Math.Exp(-digits));
+      QL_item = QL.Lower[i].v;
+      TA_item = outLower[i - outBegIdx];
+			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), high: Math.Exp(-digits));
     }
-    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()
   {
@@ -119,7 +114,6 @@ public class Ta_Lib
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }
-/*
 	[Fact]
 	public void CMO() {
 		CMO_Series QL = new(bars.Close, period, false);
@@ -130,7 +124,6 @@ public class Ta_Lib
 			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
-*/
 	[Fact]
   public void CORR()
   {
@@ -146,9 +139,9 @@ public class Ta_Lib
   [Fact]
   public void DEMA()
   {
-    DEMA_Series QL = new(bars.Close, period, false);
+    DEMA_Series QL = new(bars.Close, period, false, useSMA: false);
     Core.Dema(inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
-    for (int i = QL.Length - 1; i > skip; i--)
+    for (int i = QL.Length - 1; i > skip*2; i--)
     {
       double QL_item = Math.Round(QL[i].v, digits: digits);
       double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
@@ -215,20 +208,31 @@ public class Ta_Lib
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }
-  [Fact]
+	[Fact]
+	public void KAMA() {
+		KAMA_Series QL = new(bars.Close, period, fast: 2, slow: 30);
+		Core.Kama(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outReal: TALIB, outBegIdx: out int outBegIdx, outNbElement: out _, optInTimePeriod: period);
+		for (int i = QL.Length - 1; i > skip * 15; i--) {
+			double QL_item = QL[i].v;
+			double TA_item = TALIB[i - outBegIdx];
+			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--)
+    // TA-LIB runs EMA without SMA, leaving first 100 values for convergence
+    Core.Macd(inclose, 0, bars.Count - 1, outMacd: TALIB, outMacdSignal: macdSignal, outMacdHist: macdHist, out int outBegIdx, out _, optInFastPeriod: 12, optInSlowPeriod: 26, optInSignalPeriod: 9);
+    for (int i = QL.Length - 1; i > 100; 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);
+      double QL_item = QL[i].v;
+      double TA_item = TALIB[i - outBegIdx];
+			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+      QL_item = QL.Signal[i].v;
+      TA_item = macdSignal[i - outBegIdx];
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }

Tests/Validations/Trends/Tulip.cs

@@ -20,7 +20,7 @@ public class Tulip_Test
   {
     bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0, Precision: 3);
     period = rnd.Next(28) + 3;
-    skip = 200;
+    skip = period+1;
     digits = 10;
 
     outdata = new double[bars.Count];
@@ -40,8 +40,8 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
@@ -54,8 +54,8 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
@@ -69,8 +69,8 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i-period+1];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
@@ -84,8 +84,8 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
@@ -101,47 +101,220 @@ public class Tulip_Test
 		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);
+			double QL_item = QL.Lower[i].v;
+			double TU_item = outlower[i - period + 1];
 			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);
+			QL_item = QL.Mid[i].v;
+			TU_item = outmid[i - period + 1];
 			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);
+			QL_item = QL.Upper[i].v;
+			TU_item = outupper[i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void CCI() {
+		double[][] arrin = { inopen, inhigh, inlow, inclose, involume };
+		double[][] arrout = { outdata };
+		CCI_Series QL = new(bars, period, useNaN: false);
+		Tulip.Indicators.cci.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period-1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void CMO() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		CMO_Series QL = new(bars.Close, period, useNaN: false);
+		Tulip.Indicators.cmo.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
-	/*
 	[Fact]
 	public void DEMA() {
 		double[][] arrin = { inclose };
 		double[][] arrout = { outdata };
 		DEMA_Series QL = new(bars.Close, period, useNaN: false, useSMA: false);
 		Tulip.Indicators.dema.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+period-2)], digits);
+		for (int i = QL.Length - 1; i > skip*2; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i-(period+period-2)];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void DIV() {
+		double[][] arrin = { inhigh, inlow };
+		double[][] arrout = { outdata };
+		DIV_Series QL = new(bars.High, bars.Low);
+		Tulip.Indicators.div.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
 			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 EMA doesn't use SMA to warm-up
+		EMA_Series QL = new(bars.Close, period, false, useSMA: 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);
+      double QL_item = QL[i].v;
+      double TU_item = arrout[0][i];
       Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }
 	[Fact]
-	public void AVGPRICE()
+	public void HL2() {
+		double[][] arrin = { inhigh, inlow };
+		double[][] arrout = { outdata };
+
+		TSeries QL = bars.HL2;
+		Tulip.Indicators.medprice.Run(inputs: arrin, options: new double[] { }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void HLC3() {
+		double[][] arrin = { inhigh, inlow, inclose };
+		double[][] arrout = { outdata };
+
+		TSeries QL = bars.HLC3;
+		Tulip.Indicators.typprice.Run(inputs: arrin, options: new double[] { }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void HLCC4() {
+		double[][] arrin = { inhigh, inlow, inclose };
+		double[][] arrout = { outdata };
+
+		TSeries QL = bars.HLCC4;
+		Tulip.Indicators.wcprice.Run(inputs: arrin, options: new double[] { }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void HMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		HMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.hma.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period - 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void KAMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		KAMA_Series QL = new(bars.Close, period);
+		Tulip.Indicators.kama.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > 250; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void LINREG() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		LINREG_Series QL = new(bars.Close, period);
+		Tulip.Indicators.linregslope.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period+1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void MACD() {
+
+		double[] outsignal = new double[bars.Count];
+		double[] outhist = new double[bars.Count];
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata, outsignal, outhist };
+		MACD_Series QL = new(bars.Close, slow: 26,fast: 10, signal: 9);
+		Tulip.Indicators.macd.Run(inputs: arrin, options: new double[] { 10,26,9 }, outputs: arrout);
+		for (int i = QL.Length - 1; i > 150; i--) {
+			double QL_item = QL[i].v;
+			double TU_item =outdata[i - 26+1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void MAX() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		MAX_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.max.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i-period+1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void MIN() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		MIN_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.min.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void MUL() {
+		double[][] arrin = { inhigh, inlow };
+		double[][] arrout = { outdata };
+		MUL_Series QL = new(bars.High, bars.Low);
+		Tulip.Indicators.mul.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void OBV() {
+		double[][] arrin = { inclose, involume };
+		double[][] arrout = { outdata };
+		OBV_Series QL = new(bars, period, false);
+		Tulip.Indicators.obv.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void OHLC4()
 	{
 		double[][] arrin = { inopen, inhigh, inlow, inclose };
 		double[][] arrout = { outdata };
@@ -150,8 +323,32 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void RMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		RMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.wilders.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void RSI() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		RSI_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.rsi.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
@@ -164,33 +361,128 @@ public class Tulip_Test
 		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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i-period+1];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
-	/*
 	[Fact]
-	public void HMA() {
+	public void SDEV() {
 		double[][] arrin = { inclose };
 		double[][] arrout = { outdata };
-		HMA_Series QL = new(bars.Close, period, false);
-		Tulip.Indicators.hma.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		SDEV_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.stddev.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);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
-	}*/
+	}
 	[Fact]
-	public void CMO() {
+	public void SUB() {
+		double[][] arrin = { inhigh, inlow };
+		double[][] arrout = { outdata };
+		SUB_Series QL = new(bars.High, bars.Low);
+		Tulip.Indicators.sub.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void SUM() {
 		double[][] arrin = { inclose };
 		double[][] arrout = { outdata };
-		CMO_Series QL = new(bars.Close, period, useNaN: false);
-		Tulip.Indicators.cmo.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		SUM_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.sum.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], digits);
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void TR() {
+		double[][] arrin = { inhigh,inlow,inclose };
+		double[][] arrout = { outdata };
+		TR_Series QL = new(bars, false);
+		Tulip.Indicators.tr.Run(inputs: arrin, options: new double[] {}, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void TEMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		TEMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.tema.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void TRIMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		TRIMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.trima.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void TRIX() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		TRIX_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.trix.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period +1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void VAR() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		VAR_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.var.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void WMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		WMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.wma.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
+			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+		}
+	}
+	[Fact]
+	public void ZLEMA() {
+		double[][] arrin = { inclose };
+		double[][] arrout = { outdata };
+		ZLEMA_Series QL = new(bars.Close, period, false);
+		Tulip.Indicators.zlema.Run(inputs: arrin, options: new double[] { period }, outputs: arrout);
+		for (int i = QL.Length - 1; i > skip; i--) {
+			double QL_item = QL[i].v;
+			double TU_item = arrout[0][i - period + 1];
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}

docs/indicators.md

@@ -4,171 +4,171 @@
 
 ✔️= Validation tests passed
 
-❌= Wrong implementation
+❌= Issue
 
-| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** | **Tulip** |
+|**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 |
+|OC2 - (Open+Close)/2|️ `.OC2`||✔️CandlePart.OC2||
+|⭐HL2 - Median Price|`.HL2`|✔️MEDPRICE|✔️CandlePart.HL2|✔️hl2|✔️medprice|
+|⭐HLC3 - Typical Price|`.HLC3`|✔️TYPPRICE|✔️CandlePart.HLC3|✔️hlc3|✔️typprice|
+|OHL3 - (Open+High+Low)/3|`.OHL3`||✔️CandlePart.OHL3||
+|⭐OHLC4 - Average Price|`.OHLC4`|✔️AVGPRICE|️✔️CandlePart.OHLC4|✔️ohlc4|✔️avgprice|
+|HLCC4 - Weighted Price|`.HLCC4`|✔️WCLPRICE|||✔️wcprice|
+|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** |
+|**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 |
+|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||✔️linregslope|
+|MAD - Mean Absolute Deviation|`MAD_Series`||✔️GetSmaAnalysis|✔️mad|
+|MAPE - Mean Absolute Percent Error|`MAPE_Series`||✔️GetSmaAnalysis||
+|MEDIAN - Median value|`MEDIAN_Series`|||✔️median|
+|MSE - Mean Squared Error|`MSE_Series`||✔️GetSmaAnalysis||
+|SKEW - Skewness||||skew|
+|⭐SDEV - Standard Deviation (Volatility)|`SDEV_Series`|✔️STDDEV|✔️GetStdDev|✔️stdev|✔️stddev|
+|SSDEV - Sample Standard Deviation|`SSDEV_Series`|||✔️stdev|
+|SMAPE - Symmetric Mean Absolute Percent Error|`SMAPE_Series`||||
+|VAR - Population Variance|`VAR_Series`|✔️VAR||✔️variance|✔️var|
+|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** |
+|**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 |
+|AFIRMA - Autoregressive Finite Impulse Response Moving Average|||||
+|ALMA - Arnaud Legoux Moving Average|`ALMA_Series`||✔️GetAlma|alma|
+|DEMA - Double EMA Average|`DEMA_Series`|❌DEMA|✔️GetDema|✔️dema|❌dema|
+|DWMA - Double WMA Average|`DWMA_Series`|||||
+|⭐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|||GetEpma||
+|⭐MACD - Moving Average Convergence/Divergence|`MACD_Series`|✔️MACD|✔️GetMacd|✔️macd|✔️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|✔️rma|
+|SINWMA - Sine Weighted Moving Average||||sinwma|
+|⭐SMA - Simple Moving Average|`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|❌tema|
+|⭐TRIMA - Triangular Moving Average|`TRIMA_Series`|✔️TRIMA||✔️trima|✔️trima|
+|TSF - Time Series Forecast||TSF|||
+|VIDYA - Variable Index Dynamic Average||||vidya|vidya|
+|VORTEX - Vortex Indicator||||vortex|
+|⭐WMA - Weighted Moving Average|`WMA_Series`|✔️WMA|✔️GetWma|✔️wma|✔️wma|
+|ZLEMA - Zero Lag EMA Average|`ZLEMA_Series`|||✔️zlma|❌zlema|
 ||||||
-| **VOLATILITY INDICATORS** |
+|**VOLATILITY INDICATORS**|
 ||||||
-| ⭐ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | ✔️AD | ✔️GetAdl | ✔️ad | ✔️ad |
-| ⭐ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ✔️ADOSC| | ✔️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 |||||
+|⭐ADL - Chaikin Accumulation Distribution Line|`ADL_Series`|✔️AD|✔️GetAdl|✔️ad|✔️ad|
+|⭐ADOSC - Chaikin Accumulation Distribution Oscillator|`ADOSC_Series`|✔️ADOSC||✔️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|✔️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|✔️tr|
+|UI - Ulcer Index|||||
+|VSTOP - Volatility Stop|||||
 ||||||
-| **MOMENTUM INDICATORS & OSCILLATORS** |
+|**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_Series` | ❌CMO | ❌GetCmo | ❌cmo | 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 | TRIX | GetTrix | trix |
-| TSI - True Strength Index |||||
-| UO - Ultimate Oscillator || ULTOSC | GetUltimate ||
-| WILLR - Larry Williams' %R || WILLR | GetWilliamsR ||
-| WGAT - Williams Alligator |||||
+|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_Series`|❌CMO|✔️GetCmo|❌cmo|✔️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_Series`|❌TRIX|❌GetTrix|✔️trix|❌trix|
+|TSI - True Strength Index|||||
+|UO - Ultimate Oscillator||ULTOSC|GetUltimate||ultosc|
+|WILLR - Larry Williams' %R||WILLR|GetWilliamsR||willr|
+|WGAT - Williams Alligator|||||
 ||||||
-| **VOLUME INDICATORS** |
+|**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 |||||
+|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|✔️obv|❌obv|
+|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|||||vwma|