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using System;
using System.Collections.Generic;
using IStation.Numerics.Random;
using IStation.Numerics.Threading;
namespace IStation.Numerics.Distributions
{
///
/// Continuous Univariate Cauchy distribution.
/// The Cauchy distribution is a symmetric continuous probability distribution. For details about this distribution, see
/// Wikipedia - Cauchy distribution.
///
public class Cauchy : IContinuousDistribution
{
System.Random _random;
readonly double _location;
readonly double _scale;
///
/// Initializes a new instance of the class with the location parameter set to 0 and the scale parameter set to 1
///
public Cauchy() : this(0, 1)
{
}
///
/// Initializes a new instance of the class.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
public Cauchy(double location, double scale)
{
if (!IsValidParameterSet(location, scale))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = SystemRandomSource.Default;
_location = location;
_scale = scale;
}
///
/// Initializes a new instance of the class.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// The random number generator which is used to draw random samples.
public Cauchy(double location, double scale, System.Random randomSource)
{
if (!IsValidParameterSet(location, scale))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = randomSource ?? SystemRandomSource.Default;
_location = location;
_scale = scale;
}
///
/// A string representation of the distribution.
///
/// a string representation of the distribution.
public override string ToString()
{
return $"Cauchy(x0 = {_location}, γ = {_scale})";
}
///
/// Tests whether the provided values are valid parameters for this distribution.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
public static bool IsValidParameterSet(double location, double scale)
{
return scale > 0.0 && !double.IsNaN(location);
}
///
/// Gets the location (x0) of the distribution.
///
public double Location => _location;
///
/// Gets the scale (γ) of the distribution. Range: γ > 0.
///
public double Scale => _scale;
///
/// Gets or sets the random number generator which is used to draw random samples.
///
public System.Random RandomSource
{
get => _random;
set => _random = value ?? SystemRandomSource.Default;
}
///
/// Gets the mean of the distribution.
///
public double Mean => throw new NotSupportedException();
///
/// Gets the variance of the distribution.
///
public double Variance => throw new NotSupportedException();
///
/// Gets the standard deviation of the distribution.
///
public double StdDev => throw new NotSupportedException();
///
/// Gets the entropy of the distribution.
///
public double Entropy => Math.Log(4.0*Constants.Pi*_scale);
///
/// Gets the skewness of the distribution.
///
public double Skewness => throw new NotSupportedException();
///
/// Gets the mode of the distribution.
///
public double Mode => _location;
///
/// Gets the median of the distribution.
///
public double Median => _location;
///
/// Gets the minimum of the distribution.
///
public double Minimum => double.NegativeInfinity;
///
/// Gets the maximum of the distribution.
///
public double Maximum => double.PositiveInfinity;
///
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
///
/// The location at which to compute the density.
/// the density at .
///
public double Density(double x)
{
return 1.0/(Constants.Pi*_scale*(1.0 + (((x - _location)/_scale)*((x - _location)/_scale))));
}
///
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
///
/// The location at which to compute the log density.
/// the log density at .
///
public double DensityLn(double x)
{
return -Math.Log(Constants.Pi*_scale*(1.0 + (((x - _location)/_scale)*((x - _location)/_scale))));
}
///
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
///
/// The location at which to compute the cumulative distribution function.
/// the cumulative distribution at location .
///
public double CumulativeDistribution(double x)
{
return ((1.0/Constants.Pi)*Math.Atan((x - _location)/_scale)) + 0.5;
}
///
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the quantile or percent point function.
///
/// The location at which to compute the inverse cumulative density.
/// the inverse cumulative density at .
///
public double InverseCumulativeDistribution(double p)
{
return p <= 0.0 ? double.NegativeInfinity : p >= 1.0 ? double.PositiveInfinity
: _location + _scale*Math.Tan((p - 0.5)*Constants.Pi);
}
///
/// Draws a random sample from the distribution.
///
/// A random number from this distribution.
public double Sample()
{
return SampleUnchecked(_random, _location, _scale);
}
///
/// Fills an array with samples generated from the distribution.
///
public void Samples(double[] values)
{
SamplesUnchecked(_random, values, _location, _scale);
}
///
/// Generates a sequence of samples from the Cauchy distribution.
///
/// a sequence of samples from the distribution.
public IEnumerable Samples()
{
return SamplesUnchecked(_random, _location, _scale);
}
static double SampleUnchecked(System.Random rnd, double location, double scale)
{
return location + scale*Math.Tan(Constants.Pi*(rnd.NextDouble() - 0.5));
}
static void SamplesUnchecked(System.Random rnd, double[] values, double location, double scale)
{
rnd.NextDoubles(values);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
values[i] = location + scale*Math.Tan(Constants.Pi*(values[i] - 0.5));
}
});
}
static IEnumerable SamplesUnchecked(System.Random rnd, double location, double scale)
{
while (true)
{
yield return location + scale*Math.Tan(Constants.Pi*(rnd.NextDouble() - 0.5));
}
}
///
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// The location at which to compute the density.
/// the density at .
///
public static double PDF(double location, double scale, double x)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return 1.0/(Constants.Pi*scale*(1.0 + (((x - location)/scale)*((x - location)/scale))));
}
///
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// The location at which to compute the density.
/// the log density at .
///
public static double PDFLn(double location, double scale, double x)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return -Math.Log(Constants.Pi*scale*(1.0 + (((x - location)/scale)*((x - location)/scale))));
}
///
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
///
/// The location at which to compute the cumulative distribution function.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// the cumulative distribution at location .
///
public static double CDF(double location, double scale, double x)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return Math.Atan((x - location)/scale)/Constants.Pi + 0.5;
}
///
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the quantile or percent point function.
///
/// The location at which to compute the inverse cumulative density.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// the inverse cumulative density at .
///
public static double InvCDF(double location, double scale, double p)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return p <= 0.0 ? double.NegativeInfinity : p >= 1.0 ? double.PositiveInfinity
: location + scale*Math.Tan((p - 0.5)*Constants.Pi);
}
///
/// Generates a sample from the distribution.
///
/// The random number generator to use.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sample from the distribution.
public static double Sample(System.Random rnd, double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SampleUnchecked(rnd, location, scale);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The random number generator to use.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(System.Random rnd, double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(rnd, location, scale);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The random number generator to use.
/// The array to fill with the samples.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sequence of samples from the distribution.
public static void Samples(System.Random rnd, double[] values, double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(rnd, values, location, scale);
}
///
/// Generates a sample from the distribution.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sample from the distribution.
public static double Sample(double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SampleUnchecked(SystemRandomSource.Default, location, scale);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(SystemRandomSource.Default, location, scale);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The array to fill with the samples.
/// The location (x0) of the distribution.
/// The scale (γ) of the distribution. Range: γ > 0.
/// a sequence of samples from the distribution.
public static void Samples(double[] values, double location, double scale)
{
if (scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(SystemRandomSource.Default, values, location, scale);
}
}
}