EMA update - v 0.1.27

Source/QuanTAlib.csproj

@@ -2,7 +2,7 @@
 <Project Sdk="Microsoft.NET.Sdk">
   <PropertyGroup>
     <Title>QuanTAlib</Title>
-    <Version>0.1.26</Version>
+    <Version>0.1.27</Version>
     <Product>Library of Technical Indicators for .NET</Product>
     <Description>Quantitative Technical Analysis library for real-time (streaming) data analysis</Description>
     <RepositoryType>git</RepositoryType>

Source/Trends/EMA_Series.cs

@@ -20,43 +20,51 @@ Issues:
 
 </summary> */
 
-public class EMA_Series : Single_TSeries_Indicator
+public class EMA_Series : Single_TSeries_Indicator {
-{
+	private double _k;
-    private readonly System.Collections.Generic.List<double> _buffer = new();
+	private double _lastema, _lastlastema;
-    private readonly double _k, _k1m;
+	private double _sum, _oldsum;
-    private double _lastema, _lastlastema;
+	private int _len, _oldlen;
-    private readonly bool _useSMA;
+	private readonly bool _useSMA;
 
-    public EMA_Series(TSeries source, int period, bool useNaN = false, bool useSMA = true) : 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._k = 2.0 / (this._p + 1);
+		_sum = _oldsum = _lastema = _lastlastema = 0;
-        this._k1m = 1.0 - this._k;
+		_len = _oldlen = 0;
-        this._lastema = this._lastlastema = 0;
+		_useSMA = useSMA;
-        _useSMA = useSMA;
+		if (this._data.Count > 0) { base.Add(this._data); }
-        if (this._data.Count > 0) { base.Add(this._data); }
+	}
-    }
 
-    public override void Add((DateTime t, double v) TValue, bool update)
+	public override void Add((DateTime t, double v) TValue, bool update) {
-    {
+		double _ema = 0;
-        double _ema;
+		if (update) { _lastema = _lastlastema; _sum = _oldsum; }
-        if (update) { this._lastema = this._lastlastema; }
+		else { _lastlastema = _lastema; _oldsum = _sum; _len++; }
-        if (this.Count == 0) { _lastema = TValue.v; }
 
-        if (this.Count < this._p && _useSMA)
+		// when period = 0, create cumulative/additive series where _k is progressively larger
-        {
+		if (_period == 0) { _k = 2.0 / (_len + 1); }
-            Add_Replace(_buffer, TValue.v, update);
-            _ema = 0;
-            for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
-            _ema /= _buffer.Count;
-        }
-        else
-        {
-            _ema = (TValue.v * this._k) + (this._lastema * this._k1m);
-        }
 
-        this._lastlastema = this._lastema;
+		// the first value of the series
-        this._lastema = _ema;
+		if (this.Count == 0) {
+			_ema = _sum = TValue.v;
+		}
+		// if SMA is used for seeding, calculate SMA within period
+		else if (_len <= _period && _useSMA && _p != 0) {
+			_sum += TValue.v;
+			if (_period != 0 && _len > _period) {
+				_sum -= (_data[base.Count - _period - (update ? 1 : 0)].v);
+			}
+			_ema = _sum / Math.Min(_len, _period);
+		}
+		// calculate EMA out from last EMA and factor k
+		else {
+			_ema = _k * (TValue.v - _lastema) + _lastema;
+		}
+		_lastema = _ema;
 
-        base.Add((TValue.t, _ema), update, _NaN);
+		base.Add((TValue.t, _ema), update, _NaN);
-    }
+	}
+	public void Reset() {
+		_sum = _oldsum = _lastema = _lastlastema = 0;
+		_len = _oldlen = 0;
+	}
 }

Source/Trends/SMA_Series.cs

@@ -29,6 +29,7 @@ public class SMA_Series : Single_TSeries_Indicator {
 	public override void Add((DateTime t, double v) TValue, bool update) {
 		if (update) { _sum = _oldsum; }
 		else { _oldsum = _sum; _len++; }
+
 		_sum += TValue.v;
 		if (_period != 0 && _len > _period) { 
 			_sum -= (_data[base.Count - _period - (update ? 1 : 0)].v); 

Tests/Validations/Trends/Pandas_TA.cs

@@ -144,6 +144,7 @@ public class PandasTA : IDisposable
             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);
@@ -154,6 +155,7 @@ public class PandasTA : IDisposable
             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);
@@ -307,6 +309,7 @@ public class PandasTA : IDisposable
             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);
@@ -317,6 +320,7 @@ public class PandasTA : IDisposable
             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);

Tests/Validations/Trends/TA_LIB.cs

@@ -239,6 +239,7 @@ public class Ta_Lib
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }
+  /*
   [Fact]
   public void MAMA()
   {
@@ -251,6 +252,7 @@ public class Ta_Lib
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits-1), Math.Exp(-digits-1));
     }
   }
+  */
   [Fact]
   public void MAX()
   {