mirror of
https://github.com/mihakralj/QuanTAlib.git
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91 lines
3.1 KiB
C#
91 lines
3.1 KiB
C#
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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SSDEV: (Corrected) Sample Standard Deviation
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Sample Standard Deviaton uses Bessel's correction to correct the bias in the variance.
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Sources:
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https://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation
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Bessel's correction: https://en.wikipedia.org/wiki/Bessel%27s_correction
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Remark:
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SSDEV (Sample Standard Deviation) is also known as a unbiased/corrected Standard Deviation.
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For a population/biased/uncorrected Standard Deviation, use PSDEV instead
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</summary> */
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public class SSDEV_Series : TSeries
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{
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private readonly System.Collections.Generic.List<double> _buffer = 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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//core constructors
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public SSDEV_Series(int period, bool useNaN)
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{
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_period = period;
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_NaN = useNaN;
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Name = $"SSDEV({period})";
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}
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public SSDEV_Series(TSeries source, int period, bool useNaN) : this(period, useNaN)
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{
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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 SSDEV_Series() : this(period: 0, useNaN: false) { }
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public SSDEV_Series(int period) : this(period: period, useNaN: false) { }
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public SSDEV_Series(TBars source) : this(source.Close, 0, false) { }
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public SSDEV_Series(TBars source, int period) : this(source.Close, period, false) { }
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public SSDEV_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public SSDEV_Series(TSeries source) : this(source, 0, false) { }
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public SSDEV_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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{
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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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double _sma = _buffer.Average();
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double _svar = 0;
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for (int i = 0; i < this._buffer.Count; i++) { _svar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
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_svar /= (_buffer.Count > 1) ? _buffer.Count - 1 : 1; // Bessel's correction
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double _ssdev = Math.Sqrt(_svar);
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _ssdev);
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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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{
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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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{
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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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{
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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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{
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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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{
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_buffer.Clear();
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}
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} |