gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-17 18:18:04 +00:00
Code Issues Packages Projects Releases Wiki Activity

style: format code with dotnet-format

Browse Source 
This commit fixes the style issues introduced in 931bbdb according to the output
from dotnet-format.

Details: https://github.com/mihakralj/QuanTAlib/pull/30
This commit is contained in:
deepsource-autofix[bot]
2024-10-08 17:31:29 +00:00
committed by GitHub
parent 931bbdb6a0
commit 85b9d9217a
8 changed files with 142 additions and 127 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lib/feeds/GbmFeed.cs
+56 -56
View File
@@ -4,67 +4,67 @@ namespace QuanTAlib;
public class GbmFeed : TBarSeries
{
private readonly double _mu, _sigma;
private readonly Random _random;
private double _lastClose, _lastHigh, _lastLow;
private readonly double _mu, _sigma;
private readonly Random _random;
private double _lastClose, _lastHigh, _lastLow;
public GbmFeed(double initialPrice = 100.0, double mu = 0.05, double sigma = 0.2)
{
_lastClose = _lastHigh = _lastLow = initialPrice;
_mu = mu;
_sigma = sigma;
_random = new Random((int)DateTime.Now.Ticks);
this.Name = $"GBM({_sigma:F2})";
}
public GbmFeed(double initialPrice = 100.0, double mu = 0.05, double sigma = 0.2)
{
_lastClose = _lastHigh = _lastLow = initialPrice;
_mu = mu;
_sigma = sigma;
_random = new Random((int)DateTime.Now.Ticks);
this.Name = $"GBM({_sigma:F2})";
}
public void Add(bool isNew = true) => Add(time: DateTime.Now, isNew: isNew);
public void Add(DateTime time, bool isNew = true) => base.Add(Generate(time, isNew));
public void Add(int count)
{
DateTime startTime = DateTime.UtcNow - TimeSpan.FromHours(count);
TBar lastBar = new();
for (int i = 0; i < count; i++)
{
Add(startTime, true);
Add(startTime, false);
Add(startTime, false);
startTime = startTime.AddHours(1);
}
}
public void Add(bool isNew = true) => Add(time: DateTime.Now, isNew: isNew);
public void Add(DateTime time, bool isNew = true) => base.Add(Generate(time, isNew));
public void Add(int count)
{
DateTime startTime = DateTime.UtcNow - TimeSpan.FromHours(count);
TBar lastBar = new();
for (int i = 0; i < count; i++)
{
Add(startTime, true);
Add(startTime, false);
Add(startTime, false);
startTime = startTime.AddHours(1);
}
}
public TBar Generate(DateTime time, bool isNew = true)
{
double dt = 1.0 / 252;
double drift = (_mu - 0.5 * _sigma * _sigma) * dt;
double diffusion = _sigma * Math.Sqrt(dt) * GenerateNormalRandom();
double newClose = _lastClose * Math.Exp(drift + diffusion);
public TBar Generate(DateTime time, bool isNew = true)
{
double dt = 1.0 / 252;
double drift = (_mu - 0.5 * _sigma * _sigma) * dt;
double diffusion = _sigma * Math.Sqrt(dt) * GenerateNormalRandom();
double newClose = _lastClose * Math.Exp(drift + diffusion);
double open = _lastClose;
double high = Math.Max(_lastHigh, Math.Max(open, newClose) * (1 + _random.NextDouble() * 0.01));
double low = Math.Min(_lastLow, Math.Min(open, newClose) * (1 - _random.NextDouble() * 0.01));
double volume = 1000 + _random.NextDouble() * 1000;
double open = _lastClose;
double high = Math.Max(_lastHigh, Math.Max(open, newClose) * (1 + _random.NextDouble() * 0.01));
double low = Math.Min(_lastLow, Math.Min(open, newClose) * (1 - _random.NextDouble() * 0.01));
double volume = 1000 + _random.NextDouble() * 1000;
if (isNew)
{
_lastClose = newClose;
}
else
{
high = Math.Max(_lastHigh, high);
low = Math.Min(_lastLow, low);
}
_lastHigh = high;
_lastLow = low;
if (isNew)
{
_lastClose = newClose;
}
else
{
high = Math.Max(_lastHigh, high);
low = Math.Min(_lastLow, low);
}
_lastHigh = high;
_lastLow = low;
TBar bar = new(time, open, high, low, newClose, volume, isNew);
return bar;
}
TBar bar = new(time, open, high, low, newClose, volume, isNew);
return bar;
}
private double GenerateNormalRandom()
{
// Box-Muller transform to generate standard normal random variable
double u1 = 1.0 - _random.NextDouble(); // Uniform(0,1] random doubles
double u2 = 1.0 - _random.NextDouble();
return Math.Sqrt(-2.0 * Math.Log(u1)) * Math.Sin(2.0 * Math.PI * u2);
}
private double GenerateNormalRandom()
{
// Box-Muller transform to generate standard normal random variable
double u1 = 1.0 - _random.NextDouble(); // Uniform(0,1] random doubles
double u2 = 1.0 - _random.NextDouble();
return Math.Sqrt(-2.0 * Math.Log(u1)) * Math.Sin(2.0 * Math.PI * u2);
}
}