Browse Source
Fixed bug in Dirichlet distribution (when one of the dimensions is singular). Signed-off-by: jvangael <jurgen.vangael@gmail.com>pull/36/head
Jurgen Van Gael
17 years ago
7 changed files with 739 additions and 4 deletions
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// <copyright file="Weibull.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://mathnet.opensourcedotnet.info
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//
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// Copyright (c) 2009 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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namespace MathNet.Numerics.Distributions |
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{ |
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using System; |
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using System.Collections.Generic; |
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using Properties; |
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/// <summary>
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/// Implements the Weibull distribution. For details about this distribution, see
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/// <a href="http://en.wikipedia.org/wiki/Weibull_distribution">Wikipedia - Weibull distribution</a>.
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/// </summary>
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/// <remarks>
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/// <para>The Weibull distribution is parametrized by a shape and scale parameter.</para>
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/// <para>The distribution will use the <see cref="System.Random"/> by default.
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/// Users can get/set the random number generator by using the <see cref="RandomSource"/> property.</para>
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/// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
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/// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
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/// to false, all parameter checks can be turned off.</para></remarks>
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public class Weibull : IContinuousDistribution |
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{ |
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/// <summary>
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/// Weibull shape parameter.
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/// </summary>
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private double _shape; |
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/// <summary>
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/// Weibull inverse scale parameter.
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/// </summary>
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private double _scale; |
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/// <summary>
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/// The distribution's random number generator.
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/// </summary>
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private Random _random; |
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/// <summary>
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/// Initializes a new instance of the Weibull class.
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/// </summary>
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/// <param name="shape">The shape of the Weibull distribution.</param>
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/// <param name="scale">The inverse scale of the Weibull distribution.</param>
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public Weibull(double shape, double scale) |
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{ |
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SetParameters(shape, scale); |
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RandomSource = new Random(); |
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} |
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/// <summary>
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/// A string representation of the distribution.
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/// </summary>
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/// <returns>a string representation of the distribution.</returns>
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public override string ToString() |
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{ |
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return "Weibull(Shape = " + _shape + ", Scale = " + _scale + ")"; |
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} |
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/// <summary>
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/// Checks whether the parameters of the distribution are valid.
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/// </summary>
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/// <param name="shape">The shape of the Weibull distribution.</param>
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/// <param name="scale">The scale of the Weibull distribution.</param>
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/// <returns>True when the parameters positive valid floating point numbers, false otherwise.</returns>
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private static bool IsValidParameterSet(double shape, double scale) |
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{ |
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if (shape <= 0.0 || scale <= 0.0 || Double.IsNaN(shape) || Double.IsNaN(scale)) |
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{ |
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return false; |
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} |
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return true; |
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} |
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/// <summary>
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/// Sets the parameters of the distribution after checking their validity.
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/// </summary>
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/// <param name="shape">The shape of the Weibull distribution.</param>
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/// <param name="scale">The inverse scale of the Weibull distribution.</param>
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/// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
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private void SetParameters(double shape, double scale) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, scale)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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_shape = shape; |
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_scale = scale; |
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} |
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/// <summary>
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/// Gets or sets the shape of the Weibull distribution.
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/// </summary>
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public double Shape |
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{ |
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get |
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{ |
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return _shape; |
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} |
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set |
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{ |
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SetParameters(value, _scale); |
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} |
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} |
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/// <summary>
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/// Gets or sets the scale of the Weibull distribution.
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/// </summary>
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public double Scale |
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{ |
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get |
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{ |
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return _scale; |
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} |
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set |
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{ |
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SetParameters(_shape, value); |
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} |
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} |
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#region IDistribution implementation
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/// <summary>
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/// Gets or sets the random number generator which is used to draw random samples.
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/// </summary>
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public Random RandomSource |
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{ |
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get |
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{ |
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return _random; |
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} |
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set |
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{ |
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if (value == null) |
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{ |
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throw new ArgumentNullException(); |
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} |
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_random = value; |
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} |
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} |
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/// <summary>
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/// Gets the mean of the Weibull distribution.
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/// </summary>
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public double Mean |
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{ |
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get |
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{ |
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return _scale * SpecialFunctions.Gamma(1.0 + 1.0 / _shape); |
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} |
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} |
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/// <summary>
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/// Gets the variance of the Weibull distribution.
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/// </summary>
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public double Variance |
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{ |
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get |
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{ |
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double mu = this.Mean; |
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return _scale * _scale * SpecialFunctions.Gamma(1.0 + 2.0 / _shape) - mu * mu; |
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} |
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} |
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/// <summary>
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/// Gets the standard deviation of the Weibull distribution.
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/// </summary>
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public double StdDev |
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{ |
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get |
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{ |
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return Math.Sqrt(this.Variance); |
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} |
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} |
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/// <summary>
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/// Gets the entropy of the Weibull distribution.
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/// </summary>
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public double Entropy |
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{ |
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get |
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{ |
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throw new NotImplementedException(); |
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} |
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} |
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/// <summary>
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/// Gets the skewness of the Weibull distribution.
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/// </summary>
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public double Skewness |
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{ |
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get |
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{ |
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double mu = this.Mean; |
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double sigma = this.StdDev; |
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double sigma2 = sigma * sigma; |
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double sigma3 = sigma2 * sigma; |
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return (_scale * _scale * _scale * SpecialFunctions.Gamma(1.0 + 3.0 / _shape) |
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- 3.0 * sigma2 * mu - mu * mu * mu) / sigma3; |
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} |
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} |
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#endregion
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#region IContinuousDistribution implementation
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/// <summary>
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/// Gets the mode of the Weibull distribution.
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/// </summary>
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public double Mode |
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{ |
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get |
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{ |
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if (_shape > 1.0) |
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{ |
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return _scale * Math.Pow((_shape - 1.0) / _shape, 1.0 / _shape); |
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} |
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else |
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{ |
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return 0.0; |
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} |
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} |
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} |
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/// <summary>
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/// Gets the median of the Weibull distribution.
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/// </summary>
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public double Median |
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{ |
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get |
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{ |
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return _scale * Math.Pow(Constants.Ln2, 1.0 / _shape); |
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} |
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} |
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/// <summary>
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/// Gets the minimum of the Weibull distribution.
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/// </summary>
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public double Minimum |
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{ |
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get { return 0.0; } |
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} |
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/// <summary>
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/// Gets the maximum of the Weibull distribution.
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/// </summary>
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public double Maximum |
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{ |
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get { return Double.PositiveInfinity; } |
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} |
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/// <summary>
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/// Computes the density of the Weibull distribution.
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/// </summary>
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/// <param name="x">The location at which to compute the density.</param>
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/// <returns>the density at <paramref name="x"/>.</returns>
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public double Density(double x) |
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{ |
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if (x >= 0.0) |
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{ |
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if (x == 0.0 && _shape == 1.0) |
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{ |
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return _shape / _scale; |
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} |
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else |
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{ |
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return _shape * Math.Pow(x / _scale, _shape - 1.0) * Math.Exp(-Math.Pow(x / _scale, _shape)) / _scale; |
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} |
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} |
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return 0.0; |
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} |
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/// <summary>
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/// Computes the log density of the Weibull distribution.
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/// </summary>
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/// <param name="x">The location at which to compute the log density.</param>
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/// <returns>the log density at <paramref name="x"/>.</returns>
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public double DensityLn(double x) |
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{ |
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if (x >= 0.0) |
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{ |
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if (x == 0.0 && _shape == 1.0) |
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{ |
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return Math.Log(_shape) - Math.Log(_scale); |
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} |
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else |
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{ |
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return Math.Log(_shape) + (_shape - 1.0) * Math.Log(x / _scale) - Math.Pow(x / _scale, _shape) - Math.Log(_scale); |
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} |
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} |
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return double.NegativeInfinity; |
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} |
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/// <summary>
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/// Computes the cumulative distribution function of the Weibull distribution.
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/// </summary>
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/// <param name="x">The location at which to compute the cumulative density.</param>
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/// <returns>the cumulative density at <paramref name="x"/>.</returns>
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public double CumulativeDistribution(double x) |
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{ |
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if (x >= 0.0) |
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{ |
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return 1.0 - Math.Exp(-Math.Pow(x / _scale, _shape)); |
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} |
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return 0.0; |
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} |
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/// <summary>
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/// Generates a sample from the Weibull distribution.
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/// </summary>
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/// <returns>a sample from the distribution.</returns>
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public double Sample() |
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{ |
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return SampleWeibull(RandomSource, _shape, _scale); |
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} |
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/// <summary>
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/// Generates a sequence of samples from the Weibull distribution.
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/// </summary>
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/// <returns>a sequence of samples from the distribution.</returns>
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public IEnumerable<double> Samples() |
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{ |
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while (true) |
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{ |
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yield return SampleWeibull(RandomSource, _shape, _scale); |
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} |
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} |
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#endregion
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/// <summary>
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/// Generates a sample from the Weibull distribution.
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/// </summary>
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/// <param name="rng">The random number generator to use.</param>
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/// <param name="shape">The shape of the Weibull distribution from which to generate samples.</param>
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/// <param name="scale">The scale of the Weibull distribution from which to generate samples.</param>
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/// <returns>a sample from the distribution.</returns>
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public static double Sample(Random rng, double shape, double scale) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, scale)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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return SampleWeibull(rng, shape, scale); |
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} |
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/// <summary>
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/// Generates a sequence of samples from the Weibull distribution.
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/// </summary>
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/// <param name="rng">The random number generator to use.</param>
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/// <param name="shape">The shape of the Weibull distribution from which to generate samples.</param>
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/// <param name="scale">The scale of the Weibull distribution from which to generate samples.</param>
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/// <returns>a sequence of samples from the distribution.</returns>
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public static IEnumerable<double> Samples(Random rng, double shape, double scale) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, scale)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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while (true) |
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{ |
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yield return SampleWeibull(rng, shape, scale); |
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} |
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} |
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/// <summary>
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/// Generates one sample from the Weibull distribution. This method doesn't perform
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/// any parameter checks.
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/// </summary>
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/// <param name="rnd">The random number generator to use.</param>
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/// <param name="shape">The shape of the Weibull distribution.</param>
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/// <param name="scale">The scale of the Weibull distribution.</param>
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/// <returns>A sample from a Weibull distributed random variable.</returns>
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internal static double SampleWeibull(System.Random rnd, double shape, double scale) |
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{ |
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double x = rnd.NextDouble(); |
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return scale * Math.Pow(-Math.Log(x), 1.0 / shape); |
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} |
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} |
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} |
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@ -0,0 +1,304 @@ |
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// <copyright file="WeibullTests.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://mathnet.opensourcedotnet.info
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//
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// Copyright (c) 2009 Math.NET
|
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//
|
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// 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>
|
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|
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namespace MathNet.Numerics.UnitTests.DistributionTests |
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{ |
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using System; |
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using System.Linq; |
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using MbUnit.Framework; |
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using MathNet.Numerics.Distributions; |
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[TestFixture] |
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public class WeibullTests |
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{ |
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[SetUp] |
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public void SetUp() |
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{ |
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Control.CheckDistributionParameters = true; |
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} |
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[Test, MultipleAsserts] |
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[Row(1.0, 0.1)] |
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[Row(1.0, 1.0)] |
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[Row(10.0, 10.0)] |
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[Row(10.0, 1.0)] |
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[Row(10.0, Double.PositiveInfinity)] |
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public void CanCreateWeibull(double shape, double scale) |
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|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertEx.AreEqual<double>(shape, n.Shape); |
||||
|
AssertEx.AreEqual<double>(scale, n.Scale); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
[Row(Double.NaN, 1.0)] |
||||
|
[Row(1.0, Double.NaN)] |
||||
|
[Row(Double.NaN, Double.NaN)] |
||||
|
[Row(1.0, -1.0)] |
||||
|
[Row(-1.0, 1.0)] |
||||
|
[Row(-1.0, -1.0)] |
||||
|
[Row(0.0, 0.0)] |
||||
|
[Row(0.0, 1.0)] |
||||
|
[Row(1.0, 0.0)] |
||||
|
public void WeibullCreateFailsWithBadParameters(double shape, double scale) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateToString() |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 2.0); |
||||
|
AssertEx.AreEqual<string>("Weibull(Shape = 1, Scale = 2)", n.ToString()); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.1)] |
||||
|
[Row(1.0)] |
||||
|
[Row(10.0)] |
||||
|
[Row(Double.PositiveInfinity)] |
||||
|
public void CanSetShape(double shape) |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 1.0); |
||||
|
n.Shape = shape; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
[Row(-0.0)] |
||||
|
[Row(0.0)] |
||||
|
[Row(-1.0)] |
||||
|
public void SetShapeFailsWithNegativeShape(double shape) |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 1.0); |
||||
|
n.Shape = shape; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.1)] |
||||
|
[Row(1.0)] |
||||
|
[Row(10.0)] |
||||
|
[Row(Double.PositiveInfinity)] |
||||
|
public void CanSetScale(double scale) |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 1.0); |
||||
|
n.Scale = scale; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
[Row(-0.0)] |
||||
|
[Row(0.0)] |
||||
|
[Row(-1.0)] |
||||
|
public void SetScaleFailsWithNegativeScale(double scale) |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 1.0); |
||||
|
n.Scale = scale; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.1)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 9.5135076986687318362924871772654021925505786260884)] |
||||
|
[Row(10.0, 1.0, 0.95135076986687318362924871772654021925505786260884)] |
||||
|
public void ValidateMean(double shape, double scale, double mean) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(mean, n.Mean, 13); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.01)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 1.3100455073468309147154581687505295026863354547057)] |
||||
|
[Row(10.0, 1.0, 0.013100455073468309147154581687505295026863354547057)] |
||||
|
public void ValidateVariance(double shape, double scale, double var) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(var, n.Variance, 13); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.1)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 1.1445721940300799194124723631014002560036613065794)] |
||||
|
[Row(10.0, 1.0, 0.11445721940300799194124723631014002560036613065794)] |
||||
|
public void ValidateStdDev(double shape, double scale, double sdev) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(sdev, n.StdDev, 13); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 2.0)] |
||||
|
[Row(1.0, 1.0, 2.0)] |
||||
|
[Row(10.0, 10.0, -0.63763713390314440916597757156663888653981696212127)] |
||||
|
[Row(10.0, 1.0, -0.63763713390314440916597757156663888653981696212127)] |
||||
|
public void ValidateSkewness(double shape, double scale, double skewness) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(skewness, n.Skewness, 11); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.0)] |
||||
|
[Row(1.0, 1.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 9.8951925820621439264623017041980483215553841533709)] |
||||
|
[Row(10.0, 1.0, 0.98951925820621439264623017041980483215553841533709)] |
||||
|
public void ValidateMode(double shape, double scale, double mode) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertEx.AreEqual<double>(mode, n.Mode); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.069314718055994530941723212145817656807550013436026)] |
||||
|
[Row(1.0, 1.0, 0.69314718055994530941723212145817656807550013436026)] |
||||
|
[Row(10.0, 10.0, 9.6401223546778973665856033763604752124634905617583)] |
||||
|
[Row(10.0, 1.0, 0.96401223546778973665856033763604752124634905617583)] |
||||
|
public void ValidateMedian(double shape, double scale, double median) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(median, n.Median, 13); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateMinimum() |
||||
|
{ |
||||
|
var n = new Weibull(1.0,1.0); |
||||
|
AssertEx.AreEqual<double>(0.0, n.Minimum); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateMaximum() |
||||
|
{ |
||||
|
var n = new Weibull(1.0, 1.0); |
||||
|
AssertEx.AreEqual<double>(System.Double.PositiveInfinity, n.Maximum); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.0, 10.0)] |
||||
|
[Row(1.0, 0.1, 1.0, 0.00045399929762484851535591515560550610237918088866565)] |
||||
|
[Row(1.0, 0.1, 10.0, 3.7200759760208359629596958038631183373588922923768e-43)] |
||||
|
[Row(1.0, 1.0, 0.0, 1.0)] |
||||
|
[Row(1.0, 1.0, 1.0, 0.36787944117144232159552377016146086744581113103177)] |
||||
|
[Row(1.0, 1.0, 10.0, 0.000045399929762484851535591515560550610237918088866565)] |
||||
|
[Row(10.0, 10.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 1.0, 9.9999999990000000000499999999983333333333750000000e-10)] |
||||
|
[Row(10.0, 10.0, 10.0, 0.36787944117144232159552377016146086744581113103177)] |
||||
|
[Row(10.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 1.0, 1.0, 3.6787944117144232159552377016146086744581113103177)] |
||||
|
[Row(10.0, 1.0, 10.0, 0.0)] |
||||
|
public void ValidateDensity(double shape, double scale, double x, double pdf) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(pdf, n.Density(x), 14); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(1.0, 0.1, 0.0, 2.3025850929940456840179914546843642076011014886288)] |
||||
|
[Row(1.0, 0.1, 1.0, -7.6974149070059543159820085453156357923988985113712)] |
||||
|
[Row(1.0, 0.1, 10.0, -97.697414907005954315982008545315635792398898511371)] |
||||
|
[Row(1.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 1.0, 1.0, -1.0)] |
||||
|
[Row(1.0, 1.0, 10.0, -10.0)] |
||||
|
[Row(10.0, 10.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, 10.0, 1.0, -20.723265837046411156161923092159277868409913397659)] |
||||
|
[Row(10.0, 10.0, 10.0, -1.0)] |
||||
|
[Row(10.0, 1.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, 1.0, 1.0, 1.3025850929940456840179914546843642076011014886288)] |
||||
|
[Row(10.0, 1.0, 10.0, -9.999999976974149070059543159820085453156357923988985113712e9)] |
||||
|
public void ValidateDensityLn(double shape, double scale, double x, double pdfln) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 14); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleStatic() |
||||
|
{ |
||||
|
var d = Weibull.Sample(new Random(), 1.0, 1.0); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleSequenceStatic() |
||||
|
{ |
||||
|
var ied = Weibull.Samples(new Random(), 1.0, 1.0); |
||||
|
var arr = ied.Take(5).ToArray(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void FailSampleStatic() |
||||
|
{ |
||||
|
var d = Normal.Sample(new Random(), 1.0, -1.0); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void FailSampleSequenceStatic() |
||||
|
{ |
||||
|
var ied = Normal.Samples(new Random(), 1.0, -1.0).First(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSample() |
||||
|
{ |
||||
|
var n = new Normal(); |
||||
|
var d = n.Sample(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleSequence() |
||||
|
{ |
||||
|
var n = new Normal(); |
||||
|
var ied = n.Samples(); |
||||
|
var e = ied.Take(5).ToArray(); |
||||
|
} |
||||
|
|
||||
|
[Test, Ignore("Catastrophic cancellation in one case. Fix this.")] |
||||
|
[Row(1.0, 0.1, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 1.0, 0.99995460007023751514846440848443944938976208191113)] |
||||
|
[Row(1.0, 0.1, 10.0, 0.99999999999999999999999999999999999999999996279924)] |
||||
|
[Row(1.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 1.0, 1.0, 0.63212055882855767840447622983853913255418886896823)] |
||||
|
[Row(1.0, 1.0, 10.0, 0.99995460007023751514846440848443944938976208191113)] |
||||
|
[Row(10.0, 10.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 1.0, 9.9999999995000000000166666666662500000000083333333e-11)] |
||||
|
[Row(10.0, 10.0, 10.0, 0.63212055882855767840447622983853913255418886896823)] |
||||
|
[Row(10.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 1.0, 1.0, 0.63212055882855767840447622983853913255418886896823)] |
||||
|
[Row(10.0, 1.0, 10.0, 1.0)] |
||||
|
public void ValidateCumulativeDistribution(double shape, double scale, double x, double cdf) |
||||
|
{ |
||||
|
var n = new Weibull(shape, scale); |
||||
|
AssertHelpers.AlmostEqual(cdf, n.CumulativeDistribution(x), 15); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
Loading…
Reference in new issue