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https://github.com/mihakralj/QuanTAlib.git
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Add new data structures and event handling classes for trading platform. Include base classes, value and bar structs, event arguments, emitters, listeners. Update ruleset for SonarLint.
This commit is contained in:
Miha Kralj
@@ -1,90 +1,90 @@
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using System.Linq;
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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CMO: Chande Momentum Oscillator
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Chande Momentum Oscillator (also known as CMO indicator) was developed by Tushar S. Chande
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CMO is similar to other momentum oscillators (e.g. RSI or Stochastics). Alike RSI oscillator,
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the CMO values move in the range from -100 to +100 points and its aim is to detect the
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overbought and oversold market conditions. CMO calculates the price momentum on both the up
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days as well as the down days. The CMO calculation is based on non-smoothed price values
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meaning that it can reach its extremes more frequently and the short-time swings are more visible.
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Sources:
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https://www.technicalindicators.net/indicators-technical-analysis/144-cmo-chande-momentum-oscillator
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</summary> */
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public class CMO_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buff_up = new();
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private readonly System.Collections.Generic.List<double> _buff_dn = new();
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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private double _plast_value, _last_value;
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//core constructors
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public CMO_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"CMO({period})";
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}
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public CMO_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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public CMO_Series() : this(period: 0, useNaN: false) { }
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public CMO_Series(int period) : this(period: period, useNaN: false) { }
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public CMO_Series(TBars source) : this(source.Close, 0, false) { }
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public CMO_Series(TBars source, int period) : this(source.Close, period, false) { }
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public CMO_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public CMO_Series(TSeries source) : this(source, 0, false) { }
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public CMO_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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//////////////////
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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if (update) { _last_value = _plast_value; } else { _plast_value = _last_value; }
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BufferTrim(buffer:_buff_up, (TValue.v > _last_value) ? TValue.v - _last_value : 0, period:_period, update: update);
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BufferTrim(buffer: _buff_dn, (TValue.v < _last_value) ? _last_value - TValue.v : 0, period: _period, update: update);
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_last_value = TValue.v;
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double _cmo_up = 0;
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double _cmo_dn = 0;
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for (int i = 0; i < Math.Min(_buff_up.Count, _buff_dn.Count); i++) {
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_cmo_up += _buff_up[i];
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_cmo_dn += _buff_dn[i];
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}
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double _cmo = 100 * (_cmo_up - _cmo_dn) / (_cmo_up + _cmo_dn);
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if (_cmo_up + _cmo_dn == 0) { _cmo = 0; }
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _cmo);
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return base.Add(res, update);
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}
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buff_up.Clear();
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_buff_dn.Clear();
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}
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using System.Linq;
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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CMO: Chande Momentum Oscillator
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Chande Momentum Oscillator (also known as CMO indicator) was developed by Tushar S. Chande
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CMO is similar to other momentum oscillators (e.g. RSI or Stochastics). Alike RSI oscillator,
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the CMO values move in the range from -100 to +100 points and its aim is to detect the
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overbought and oversold market conditions. CMO calculates the price momentum on both the up
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days as well as the down days. The CMO calculation is based on non-smoothed price values
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meaning that it can reach its extremes more frequently and the short-time swings are more visible.
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Sources:
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https://www.technicalindicators.net/indicators-technical-analysis/144-cmo-chande-momentum-oscillator
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</summary> */
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public class CMO_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buff_up = new();
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private readonly System.Collections.Generic.List<double> _buff_dn = new();
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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private double _plast_value, _last_value;
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//core constructors
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public CMO_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"CMO({period})";
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}
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public CMO_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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public CMO_Series() : this(period: 0, useNaN: false) { }
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public CMO_Series(int period) : this(period: period, useNaN: false) { }
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public CMO_Series(TBars source) : this(source.Close, 0, false) { }
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public CMO_Series(TBars source, int period) : this(source.Close, period, false) { }
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public CMO_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public CMO_Series(TSeries source) : this(source, 0, false) { }
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public CMO_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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//////////////////
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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if (update) { _last_value = _plast_value; } else { _plast_value = _last_value; }
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BufferTrim(buffer:_buff_up, (TValue.v > _last_value) ? TValue.v - _last_value : 0, period:_period, update: update);
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BufferTrim(buffer: _buff_dn, (TValue.v < _last_value) ? _last_value - TValue.v : 0, period: _period, update: update);
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_last_value = TValue.v;
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double _cmo_up = 0;
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double _cmo_dn = 0;
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for (int i = 0; i < Math.Min(_buff_up.Count, _buff_dn.Count); i++) {
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_cmo_up += _buff_up[i];
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_cmo_dn += _buff_dn[i];
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}
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double _cmo = 100 * (_cmo_up - _cmo_dn) / (_cmo_up + _cmo_dn);
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if (_cmo_up + _cmo_dn == 0) { _cmo = 0; }
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _cmo);
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return base.Add(res, update);
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}
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buff_up.Clear();
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_buff_dn.Clear();
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}
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}
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