Math.NET Numerics
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// <copyright file="Rayleigh.cs" company="Math.NET">
// Math.NET Numerics, part of the Math.NET Project
// http://numerics.mathdotnet.com
// http://github.com/mathnet/mathnet-numerics
// http://mathnetnumerics.codeplex.com
// Copyright (c) 2009-2010 Math.NET
// Permission is hereby granted, free of charge, to any person
// obtaining a copy of this software and associated documentation
// files (the "Software"), to deal in the Software without
// restriction, including without limitation the rights to use,
// copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the
// Software is furnished to do so, subject to the following
// conditions:
// The above copyright notice and this permission notice shall be
// included in all copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
// OTHER DEALINGS IN THE SOFTWARE.
// </copyright>
namespace MathNet.Numerics.Distributions
{
using System;
using System.Collections.Generic;
using Properties;
/// <summary>
/// The Rayleigh distribution (pronounced /ˈreɪli/) is a continuous probability distribution. As an
/// example of how it arises, the wind speed will have a Rayleigh distribution if the components of
/// the two-dimensional wind velocity vector are uncorrelated and normally distributed with equal variance.
/// For details about this distribution, see
/// <a href="http://en.wikipedia.org/wiki/Rayleigh_distribution">Wikipedia - Rayleigh distribution</a>.
/// </summary>
/// <remarks><para>The distribution will use the <see cref="System.Random"/> by default.
/// Users can get/set the random number generator by using the <see cref="RandomSource"/> property.</para>
/// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
/// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
/// to <c>false</c>, all parameter checks can be turned off.</para></remarks>
public class Rayleigh : IContinuousDistribution
{
/// <summary>
/// The scale parameter of the distribution.
/// </summary>
double _scale;
/// <summary>
/// The distribution's random number generator.
/// </summary>
Random _random;
/// <summary>
/// Initializes a new instance of the <see cref="Rayleigh"/> class.
/// </summary>
/// <param name="scale">The scale parameter of the distribution.</param>
/// <exception cref="ArgumentException">If <paramref name="scale"/> is negative.</exception>
public Rayleigh(double scale)
{
_random = new Random();
SetParameters(scale);
}
/// <summary>
/// Initializes a new instance of the <see cref="Rayleigh"/> class.
/// </summary>
/// <param name="scale">The scale parameter of the distribution.</param>
/// <param name="randomSource">The random number generator which is used to draw random samples.</param>
/// <exception cref="ArgumentException">If <paramref name="scale"/> is negative.</exception>
public Rayleigh(double scale, Random randomSource)
{
_random = randomSource ?? new Random();
SetParameters(scale);
}
/// <summary>
/// Sets the parameters of the distribution after checking their validity.
/// </summary>
/// <param name="scale">The scale parameter of the distribution.</param>
/// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
void SetParameters(double scale)
{
if (Control.CheckDistributionParameters && !IsValidParameterSet(scale))
{
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
}
_scale = scale;
}
/// <summary>
/// Checks whether the parameters of the distribution are valid.
/// </summary>
/// <param name="scale">The scale parameter of the distribution.</param>
/// <returns><c>true</c> when the parameters are valid, <c>false</c> otherwise.</returns>
static bool IsValidParameterSet(double scale)
{
if (scale <= 0)
{
return false;
}
if (Double.IsNaN(scale))
{
return false;
}
return true;
}
/// <summary>
/// Gets or sets the scale parameter of the distribution.
/// </summary>
public double Scale
{
get { return _scale; }
set { SetParameters(value); }
}
/// <summary>
/// A string representation of the distribution.
/// </summary>
/// <returns>a string representation of the distribution.</returns>
public override string ToString()
{
return "Rayleigh(Scale = " + _scale + ")";
}
#region IDistribution Members
/// <summary>
/// Gets or sets the random number generator which is used to draw random samples.
/// </summary>
public Random RandomSource
{
get { return _random; }
set
{
if (value == null)
{
throw new ArgumentNullException();
}
_random = value;
}
}
/// <summary>
/// Gets the mean of the distribution.
/// </summary>
public double Mean
{
get { return _scale*Math.Sqrt(Constants.PiOver2); }
}
/// <summary>
/// Gets the variance of the distribution.
/// </summary>
public double Variance
{
get { return (2.0 - Constants.PiOver2)*_scale*_scale; }
}
/// <summary>
/// Gets the standard deviation of the distribution.
/// </summary>
public double StdDev
{
get { return Math.Sqrt(2.0 - Constants.PiOver2)*_scale; }
}
/// <summary>
/// Gets the entropy of the distribution.
/// </summary>
public double Entropy
{
get { return 1.0 + Math.Log(_scale/Math.Sqrt(2)) + (Constants.EulerMascheroni/2.0); }
}
/// <summary>
/// Gets the skewness of the distribution.
/// </summary>
public double Skewness
{
get { return (2.0*Math.Sqrt(Constants.Pi)*(Constants.Pi - 3.0))/Math.Pow(4.0 - Constants.Pi, 1.5); }
}
/// <summary>
/// Computes the cumulative distribution function of the distribution.
/// </summary>
/// <param name="x">The location at which to compute the cumulative density.</param>
/// <returns>the cumulative density at <paramref name="x"/>.</returns>
public double CumulativeDistribution(double x)
{
return 1.0 - Math.Exp(-x*x/(2.0*_scale*_scale));
}
#endregion
#region IContinuousDistribution Members
/// <summary>
/// Gets the mode of the distribution.
/// </summary>
public double Mode
{
get { return _scale; }
}
/// <summary>
/// Gets the median of the distribution.
/// </summary>
public double Median
{
get { return _scale*Math.Sqrt(Math.Log(4.0)); }
}
/// <summary>
/// Gets the minimum of the distribution.
/// </summary>
public double Minimum
{
get { return 0.0; }
}
/// <summary>
/// Gets the maximum of the distribution.
/// </summary>
public double Maximum
{
get { return Double.PositiveInfinity; }
}
/// <summary>
/// Computes the density of the distribution.
/// </summary>
/// <param name="x">The location at which to compute the density.</param>
/// <returns>the density at <paramref name="x"/>.</returns>
public double Density(double x)
{
return (x/(_scale*_scale))*Math.Exp(-x*x/(2.0*_scale*_scale));
}
/// <summary>
/// Computes the log density of the distribution.
/// </summary>
/// <param name="x">The location at which to compute the log density.</param>
/// <returns>the log density at <paramref name="x"/>.</returns>
public double DensityLn(double x)
{
return Math.Log(x/(_scale*_scale)) - (x*x/(2.0*_scale*_scale));
}
#endregion
/// <summary>
/// Generates a sample from the Rayleigh distribution without doing parameter checking.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="scale">The scale parameter.</param>
/// <returns>a random number from the Rayleigh distribution.</returns>
internal static double SampleUnchecked(Random rnd, double scale)
{
return scale*Math.Sqrt(-2.0*Math.Log(rnd.NextDouble()));
}
/// <summary>
/// Draws a random sample from the distribution.
/// </summary>
/// <returns>A random number from this distribution.</returns>
public double Sample()
{
return SampleUnchecked(RandomSource, _scale);
}
/// <summary>
/// Generates a sequence of samples from the Rayleigh distribution.
/// </summary>
/// <returns>a sequence of samples from the distribution.</returns>
public IEnumerable<double> Samples()
{
while (true)
{
yield return SampleUnchecked(RandomSource, _scale);
}
}
/// <summary>
/// Generates a sample from the distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="scale">The scale parameter.</param>
/// <returns>a sample from the distribution.</returns>
public static double Sample(Random rnd, double scale)
{
if (Control.CheckDistributionParameters && !IsValidParameterSet(scale))
{
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
}
return SampleUnchecked(rnd, scale);
}
/// <summary>
/// Generates a sequence of samples from the distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="scale">The scale parameter.</param>
/// <returns>a sequence of samples from the distribution.</returns>
public static IEnumerable<double> Samples(Random rnd, double scale)
{
if (Control.CheckDistributionParameters && !IsValidParameterSet(scale))
{
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
}
while (true)
{
yield return SampleUnchecked(rnd, scale);
}
}
}
}