Math.NET Numerics
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// <copyright file="Exponential.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) 2009-2013 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>
using System;
using System.Collections.Generic;
using System.Linq;
using MathNet.Numerics.Properties;
using MathNet.Numerics.Random;
using MathNet.Numerics.Threading;
namespace MathNet.Numerics.Distributions
{
/// <summary>
/// Continuous Univariate Exponential distribution.
/// The exponential distribution is a distribution over the real numbers parameterized by one non-negative parameter.
/// <a href="http://en.wikipedia.org/wiki/Exponential_distribution">Wikipedia - exponential distribution</a>.
/// </summary>
public class Exponential : IContinuousDistribution
{
System.Random _random;
double _rate;
/// <summary>
/// Initializes a new instance of the <see cref="Exponential"/> class.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
public Exponential(double rate)
{
_random = SystemRandomSource.Default;
SetParameters(rate);
}
/// <summary>
/// Initializes a new instance of the <see cref="Exponential"/> class.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <param name="randomSource">The random number generator which is used to draw random samples.</param>
public Exponential(double rate, System.Random randomSource)
{
_random = randomSource ?? SystemRandomSource.Default;
SetParameters(rate);
}
/// <summary>
/// A string representation of the distribution.
/// </summary>
/// <returns>a string representation of the distribution.</returns>
public override string ToString()
{
return "Exponential(λ = " + _rate + ")";
}
/// <summary>
/// Sets the parameters of the distribution after checking their validity.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <exception cref="ArgumentOutOfRangeException">When the parameters are out of range.</exception>
void SetParameters(double rate)
{
if (rate < 0.0 || Double.IsNaN(rate))
{
throw new ArgumentException(Resources.InvalidDistributionParameters);
}
_rate = rate;
}
/// <summary>
/// Gets or sets the rate (λ) parameter of the distribution. Range: λ ≥ 0.
/// </summary>
public double Rate
{
get { return _rate; }
set { SetParameters(value); }
}
/// <summary>
/// Gets or sets the random number generator which is used to draw random samples.
/// </summary>
public System.Random RandomSource
{
get { return _random; }
set { _random = value ?? SystemRandomSource.Default; }
}
/// <summary>
/// Gets the mean of the distribution.
/// </summary>
public double Mean
{
get { return 1.0/_rate; }
}
/// <summary>
/// Gets the variance of the distribution.
/// </summary>
public double Variance
{
get { return 1.0/(_rate*_rate); }
}
/// <summary>
/// Gets the standard deviation of the distribution.
/// </summary>
public double StdDev
{
get { return 1.0/_rate; }
}
/// <summary>
/// Gets the entropy of the distribution.
/// </summary>
public double Entropy
{
get { return 1.0 - Math.Log(_rate); }
}
/// <summary>
/// Gets the skewness of the distribution.
/// </summary>
public double Skewness
{
get { return 2.0; }
}
/// <summary>
/// Gets the mode of the distribution.
/// </summary>
public double Mode
{
get { return 0.0; }
}
/// <summary>
/// Gets the median of the distribution.
/// </summary>
public double Median
{
get { return Math.Log(2.0)/_rate; }
}
/// <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 probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
/// </summary>
/// <param name="x">The location at which to compute the density.</param>
/// <returns>the density at <paramref name="x"/>.</returns>
/// <seealso cref="PDF"/>
public double Density(double x)
{
return x < 0.0 ? 0.0 : _rate*Math.Exp(-_rate*x);
}
/// <summary>
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
/// </summary>
/// <param name="x">The location at which to compute the log density.</param>
/// <returns>the log density at <paramref name="x"/>.</returns>
/// <seealso cref="PDFLn"/>
public double DensityLn(double x)
{
return Math.Log(_rate) - (_rate*x);
}
/// <summary>
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
/// </summary>
/// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CDF"/>
public double CumulativeDistribution(double x)
{
return x < 0.0 ? 0.0 : 1.0 - Math.Exp(-_rate*x);
}
/// <summary>
/// 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.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
/// <seealso cref="InvCDF"/>
public double InverseCumulativeDistribution(double p)
{
return p >= 1.0 ? double.PositiveInfinity : -Math.Log(1 - p)/_rate;
}
/// <summary>
/// Draws a random sample from the distribution.
/// </summary>
/// <returns>A random number from this distribution.</returns>
public double Sample()
{
return SampleUnchecked(_random, _rate);
}
/// <summary>
/// Generates a sequence of samples from the Exponential distribution.
/// </summary>
/// <returns>a sequence of samples from the distribution.</returns>
public IEnumerable<double> Samples()
{
return SamplesUnchecked(_random, _rate);
}
/// <summary>
/// Samples the distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>a random number from the distribution.</returns>
static double SampleUnchecked(System.Random rnd, double rate)
{
var r = rnd.NextDouble();
while (r == 0.0)
{
r = rnd.NextDouble();
}
return -Math.Log(r)/rate;
}
static IEnumerable<double> SamplesUnchecked(System.Random rnd, double rate)
{
return rnd.NextDoubleSequence().Where(r => r != 0.0).Select(r => -Math.Log(r)/rate);
}
static void SamplesUnchecked(System.Random rnd, double[] values, double rate)
{
rnd.NextDoubles(values);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
// this happens very rarely
var r = values[i];
while (r == 0.0)
{
r = rnd.NextDouble();
}
values[i] = -Math.Log(r)/rate;
}
});
}
/// <summary>
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <param name="x">The location at which to compute the density.</param>
/// <returns>the density at <paramref name="x"/>.</returns>
/// <seealso cref="Density"/>
public static double PDF(double rate, double x)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return x < 0.0 ? 0.0 : rate*Math.Exp(-rate*x);
}
/// <summary>
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <param name="x">The location at which to compute the density.</param>
/// <returns>the log density at <paramref name="x"/>.</returns>
/// <seealso cref="DensityLn"/>
public static double PDFLn(double rate, double x)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return Math.Log(rate) - (rate*x);
}
/// <summary>
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
/// </summary>
/// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CumulativeDistribution"/>
public static double CDF(double rate, double x)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return x < 0.0 ? 0.0 : 1.0 - Math.Exp(-rate*x);
}
/// <summary>
/// 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.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
/// <seealso cref="InverseCumulativeDistribution"/>
public static double InvCDF(double rate, double p)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return p >= 1.0 ? double.PositiveInfinity : -Math.Log(1 - p)/rate;
}
/// <summary>
/// Draws a random sample from the distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>A random number from this distribution.</returns>
public static double Sample(System.Random rnd, double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return SampleUnchecked(rnd, rate);
}
/// <summary>
/// Generates a sequence of samples from the Exponential distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>a sequence of samples from the distribution.</returns>
public static IEnumerable<double> Samples(System.Random rnd, double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return SamplesUnchecked(rnd, rate);
}
/// <summary>
/// Fills an array with samples generated from the distribution.
/// </summary>
/// <param name="rnd">The random number generator to use.</param>
/// <param name="values">The array to fill with the samples.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>a sequence of samples from the distribution.</returns>
public static void Samples(System.Random rnd, double[] values, double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
SamplesUnchecked(rnd, values, rate);
}
/// <summary>
/// Draws a random sample from the distribution.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>A random number from this distribution.</returns>
public static double Sample(double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return SampleUnchecked(SystemRandomSource.Default, rate);
}
/// <summary>
/// Generates a sequence of samples from the Exponential distribution.
/// </summary>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>a sequence of samples from the distribution.</returns>
public static IEnumerable<double> Samples(double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
return SamplesUnchecked(SystemRandomSource.Default, rate);
}
/// <summary>
/// Fills an array with samples generated from the distribution.
/// </summary>
/// <param name="values">The array to fill with the samples.</param>
/// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
/// <returns>a sequence of samples from the distribution.</returns>
public static void Samples(double[] values, double rate)
{
if (rate < 0.0) throw new ArgumentException(Resources.InvalidDistributionParameters);
SamplesUnchecked(SystemRandomSource.Default, values, rate);
}
}
}