gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-24 21:48:03 +00:00
Code Issues Packages Projects Releases Wiki Activity

refactor structs to records, add new classes for financial calculations, implement EMA and SMA with circular buffer. Generate random financial data using GBM model. Also, test the SMA calculation with sample data.

Browse Source
This commit is contained in:
Miha Kralj
2024-07-28 21:26:44 -07:00
parent ef534393db
commit 3455baaf6c
95 changed files with 8661 additions and 7012 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Calculations/_Updated/SMA_Series.cs
+86 -70
View File
@@ -16,81 +16,97 @@ Remark:
implementation, but it does allow incremental additions of inputs and real-time calculations of SMA()
</summary> */
public class SMA_Series : TSeries {
private readonly System.Collections.Generic.List<double> _buffer = new();
public class SMA_Series : TSeries
{
private readonly System.Collections.Generic.List<double> _buffer = new();
private double _sum, _oldsum;
private readonly int _period;
private readonly TSeries _data;
protected readonly bool _NaN;
private double _sum, _oldsum;
private readonly int _period;
private readonly TSeries _data;
protected readonly bool _NaN;
//core constructor
public SMA_Series(int period, bool useNaN) {
_period = Math.Max(0, period);
_NaN = useNaN;
Name = $"SMA({period})";
_sum = _oldsum = 0;
}
public SMA_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 SMA_Series() : this(0, false) {}
public SMA_Series(int period) : this(period, false) {}
public SMA_Series(TBars source) : this(source.Close, 0, false) {}
public SMA_Series(TBars source, int period) : this(source.Close, period, false) {}
public SMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) {}
public SMA_Series(TSeries source) : this(source, 0, false) {}
public SMA_Series(TSeries source, int period) : this(source, period, false) {}
//core constructor
public SMA_Series(int period, bool useNaN)
{
_period = Math.Max(0, period);
_NaN = useNaN;
Name = $"SMA({period})";
_sum = _oldsum = 0;
}
public SMA_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 SMA_Series() : this(0, false) { }
public SMA_Series(int period) : this(period, false) { }
public SMA_Series(TBars source) : this(source.Close, 0, false) { }
public SMA_Series(TBars source, int period) : this(source.Close, period, false) { }
public SMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
public SMA_Series(TSeries source) : this(source, 0, false) { }
public SMA_Series(TSeries source, int period) : this(source, period, 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 (TValue.t, double.NaN);
} else {
if (update && _buffer.Count > 0) {
_sum -= _buffer[^1];
_buffer[^1] = TValue.v;
_oldsum = _sum;
}
else {
_buffer.Add(TValue.v);
_oldsum = _sum;
}
//////////////////
// core Add() algo
public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false)
{
if (double.IsNaN(TValue.v))
{
return (TValue.t, double.NaN);
}
else
{
if (update && _buffer.Count > 0)
{
_sum -= _buffer[^1];
_buffer[^1] = TValue.v;
_oldsum = _sum;
}
else
{
_buffer.Add(TValue.v);
_oldsum = _sum;
}
_sum += TValue.v;
if (_period != 0 && _buffer.Count > _period) {
_sum -= _buffer[0];
_buffer.RemoveAt(0);
}
}
_sum += TValue.v;
if (_period != 0 && _buffer.Count > _period)
{
_sum -= _buffer[0];
_buffer.RemoveAt(0);
}
}
double _div = _period == 0 ? _buffer.Count : Math.Min(_buffer.Count, _period);
var _sma = _sum / _div;
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _sma);
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 (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);
}
double _div = _period == 0 ? _buffer.Count : Math.Min(_buffer.Count, _period);
var _sma = _sum / _div;
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _sma);
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 (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 = 0;
_buffer.Clear();
}
//reset calculation
public override void Reset()
{
_sum = _oldsum = 0;
_buffer.Clear();
}
}