Update RSI_Series to check for period != 0 before calculating RSI

2026-08-21 12:08:05 +00:00 · 2023-04-27 22:23:50 -07:00
parent c80f57ddab
commit abdcbf5f20
145 changed files with 4826 additions and 4207 deletions
@@ -0,0 +1,96 @@
+namespace QuanTAlib;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+
+/* <summary>
+SMMA: Smoothed Moving Average
+    The Smoothed Moving Average (SMMA) is a combination of a SMA and an EMA. It gives the recent prices
+    an equal weighting as the historic prices as it takes all available price data into account.
+    The main advantage of a smoothed moving average is that it removes short-term fluctuations.
+
+    SMMA(i) = (SMMA-1*(N-1) + CLOSE (i)) / N
+
+Sources:
+    https://blog.earn2trade.com/smoothed-moving-average
+    https://guide.traderevolution.com/traderevolution/mobile-applications/phone/android/technical-indicators/moving-averages/smma-smoothed-moving-average
+    https://www.chartmill.com/documentation/technical-analysis-indicators/217-MOVING-AVERAGES-%7C-The-Smoothed-Moving-Average-%28SMMA%29
+
+</summary> */
+
+public class SMMA_Series : TSeries {
+	private readonly System.Collections.Generic.List<double> _buffer = new();
+
+	protected readonly int _period;
+	protected readonly bool _NaN;
+	protected readonly TSeries _data;
+	private double _lastsmma, _lastlastsmma;
+
+	//core constructors
+	public SMMA_Series(int period, bool useNaN) : base() {
+		_period = period;
+		_NaN = useNaN;
+		Name = $"SMMA({period})";
+	}
+	public SMMA_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
+		_data = source;
+		Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
+		_data.Pub += Sub;
+		Add(_data);
+	}
+	public SMMA_Series() : this(period: 0, useNaN: false) { }
+	public SMMA_Series(int period) : this(period: period, useNaN: false) { }
+	public SMMA_Series(TBars source) : this(source.Close, 0, false) { }
+	public SMMA_Series(TBars source, int period) : this(source.Close, period, false) { }
+	public SMMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
+	public SMMA_Series(TSeries source) : this(source, 0, false) { }
+	public SMMA_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
+
+	//////////////////
+	// core Add() algo
+	public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
+		if (double.IsNaN(TValue.v)) {
+			return base.Add((TValue.t, double.NaN),update);
+		}
+
+		double _smma = 0;
+		if (update) { this._lastsmma = this._lastlastsmma; }
+
+		if (this.Count < this._period) {
+			BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
+			_smma = _buffer.Average();
+		}
+		else {
+			_smma = ((_lastsmma * (_period - 1)) + TValue.v) / _period;
+		}
+
+		this._lastlastsmma = this._lastsmma;
+		this._lastsmma = _smma;
+		var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _smma);
+		return base.Add(res, update);
+	}
+
+	public override (DateTime t, double v) Add(TSeries data) {
+		if (data == null) { return (DateTime.Today, Double.NaN); }
+		foreach (var item in data) { Add(item, false); }
+		return _data.Last;
+	}
+	public new (DateTime t, double v) Add((DateTime t, double v) TValue) {
+		return Add(TValue, false);
+	}
+	public (DateTime t, double v) Add(bool update) {
+		return this.Add(TValue: _data.Last, update: update);
+	}
+	public (DateTime t, double v) Add() {
+		return Add(TValue: _data.Last, update: false);
+	}
+	private new void Sub(object source, TSeriesEventArgs e) {
+		Add(TValue: _data.Last, update: e.update);
+	}
+
+	//reset calculation
+	public override void Reset() {
+		_buffer.Clear();
+		this._lastsmma = this._lastlastsmma = 0;
+	}
+}