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

2026-08-24 13:38:05 +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 +1,119 @@
+namespace QuanTAlib;
+
+using System;
+using System.Linq;
+
+/* <summary>
+RMA: wildeR Moving Average
+    J. Welles Wilder introduced RMA as an alternative to EMA. RMA's weight (k) is
+    set as 1/period, giving less weight to the new data compared to EMA.
+
+Sources:
+    https://archive.org/details/newconceptsintec00wild/page/23/mode/2up
+	https://tlc.thinkorswim.com/center/reference/Tech-Indicators/studies-library/V-Z/WildersSmoothing
+    https://www.incrediblecharts.com/indicators/wilder_moving_average.php
+
+Issues:
+    Pandas-TA library calculates RMA using straight Exponential Weighted Mean:
+	pandas.ewm().mean() and returns incorrect first (period) of bars compared to
+	published formula. This implementation passess the validation test in Wilder's book.
+
+</summary> */
+
+public class RMA_Series : TSeries {
+	private double _k;
+	private double _lastrma, _oldrma;
+	private double _sum, _oldsum;
+	private readonly bool _useSMA;
+	private int _len;
+	protected readonly int _period;
+	protected readonly bool _NaN;
+	protected readonly TSeries _data;
+
+//core constructor
+	public RMA_Series(int period, bool useNaN, bool useSMA) : base() {
+		_period = period;
+		_NaN = useNaN;
+		_useSMA = useSMA;
+		Name = $"RMA({period})";
+		_k = 1.0 / (double)(this._period);
+		_len = 0;
+		_sum = _oldsum = _lastrma = _oldrma = 0;
+	}
+	//generic constructors (source)
+
+	public RMA_Series() : this(0, false, true) {}
+	public RMA_Series(int period) : this(period, false, true) {}
+	public RMA_Series(TBars source) : this(source.Close, 0, false) {}
+	public RMA_Series(TBars source, int period) : this(source.Close, period, false) {}
+	public RMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) {}
+	public RMA_Series(TSeries source, int period) : this(source, period, false, true) {}
+	public RMA_Series(TSeries source, int period, bool useNaN) : this(source, period, useNaN, true) {}
+	public RMA_Series(TSeries source, int period, bool useNaN, bool useSMA) : this(period, useNaN, useSMA) {
+		_data = source;
+		Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
+		_data.Pub += Sub;
+		Add(_data);
+	}
+
+// core Add() algo
+	public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update) {
+		if (update) {
+			_lastrma = _oldrma;
+			_sum = _oldsum;
+		}
+		else {
+			_oldrma = _lastrma;
+			_oldsum = _sum;
+			_len++;
+		}
+
+		double _rma = 0;
+		if (_period == 0) {
+			_k = 1.0 / (double)(this._len);
+		}
+
+		if (Count == 0) {
+			_rma = _sum = TValue.v;
+
+		} else if (_len <= _period && _useSMA && _period != 0) {
+			_sum += TValue.v;
+			if (_period != 0 && _len > _period) {
+				_sum -= _data[Count - _period - (update ? 1 : 0)].v;
+			}
+			_rma = _sum / Math.Min(_len, _period);
+		}
+		else {
+			_rma = _k * (TValue.v - _lastrma) + _lastrma;
+		}
+
+		_lastrma = double.IsNaN(_rma) ? _lastrma : _rma;
+		var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _rma);
+		return base.Add(res, update);
+	}
+
+//variation of Add()
+	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() {
+		_sum = _oldsum = _lastrma = _oldrma = 0;
+		_len = 0;
+	}
+}