mirror of
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richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
280 lines
9.4 KiB
C#
280 lines
9.4 KiB
C#
// Accord Statistics Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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namespace Accord.Statistics.Distributions.Univariate
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{
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using System;
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using Accord.Math;
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using Accord.Statistics.Distributions.Fitting;
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using Accord.Compat;
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/// <summary>
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/// Symmetric Geometric Distribution.
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/// </summary>
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///
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/// <remarks>
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/// <para>
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/// The Symmetric Geometric Distribution can be seen as a discrete case
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/// of the <see cref="LaplaceDistribution"/>.</para>
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/// </remarks>
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///
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/// <seealso cref="GeometricDistribution"/>
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/// <seealso cref="HypergeometricDistribution"/>
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///
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[Serializable]
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public class SymmetricGeometricDistribution : UnivariateDiscreteDistribution
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{
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// Distribution parameters
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private double p;
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// Derived measures
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private double lnconstant;
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/// <summary>
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/// Gets the success probability for the distribution.
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/// </summary>
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///
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public double ProbabilityOfSuccess
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{
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get { return p; }
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}
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/// <summary>
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/// Creates a new symmetric geometric distribution.
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/// </summary>
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///
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/// <param name="probabilityOfSuccess">The success probability.</param>
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///
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public SymmetricGeometricDistribution([Unit] double probabilityOfSuccess)
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{
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if (probabilityOfSuccess < 0 || probabilityOfSuccess > 1)
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throw new ArgumentOutOfRangeException("probabilityOfSuccess",
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"A probability must be between 0 and 1.");
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this.p = probabilityOfSuccess;
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this.lnconstant = Math.Log(p) - Math.Log(2.0 * (1.0 - p));
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}
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/// <summary>
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/// Gets the support interval for this distribution, which
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/// in the case of the Symmetric Geometric is [-inf, +inf].
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/// </summary>
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///
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/// <value>
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/// A <see cref="IntRange" /> containing
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/// the support interval for this distribution.
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/// </value>
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///
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public override IntRange Support
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{
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get { return new IntRange(Int32.MinValue, Int32.MaxValue); }
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}
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/// <summary>
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/// Gets the mean for this distribution, which in
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/// the case of the Symmetric Geometric is zero.
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/// </summary>
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///
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/// <value>
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/// The distribution's mean value.
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/// </value>
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///
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public override double Mean
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{
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get { return 0; }
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set { throw new NotImplementedException();}
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}
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/// <summary>
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/// Gets the variance for this distribution.
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/// </summary>
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///
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/// <value>The distribution's variance.</value>
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///
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public override double Variance
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{
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get { return ((2 - p) * (1 - p)) / (p * p); }
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set { throw new NotImplementedException();}
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}
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/// <summary>
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/// Not supported.
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/// </summary>
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///
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public override double Entropy
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{
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get { throw new NotSupportedException(); }
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set { throw new NotImplementedException();}
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}
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/// <summary>
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/// Not supported.
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/// </summary>
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///
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protected internal override double InnerDistributionFunction(int k)
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{
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throw new NotSupportedException();
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}
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/// <summary>
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/// Gets the probability mass function (pmf) for
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/// this distribution evaluated at point <c>x</c>.
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/// </summary>
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///
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/// <param name="k">A single point in the distribution range.</param>
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///
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/// <returns>
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/// The probability of <c>k</c> occurring
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/// in the current distribution.
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/// </returns>
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///
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/// <remarks>
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/// The Probability Mass Function (PMF) describes the
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/// probability that a given value <c>x</c> will occur.
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/// </remarks>
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///
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protected internal override double InnerProbabilityMassFunction(int k)
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{
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if (k == 0)
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return p; // need special case otherwise will be double at center
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return Math.Exp(lnconstant) * Math.Pow(1 - p, Math.Abs(k) - 1);
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}
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/// <summary>
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/// Gets the log-probability mass function (pmf) for
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/// this distribution evaluated at point <c>x</c>.
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/// </summary>
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///
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/// <param name="k">A single point in the distribution range.</param>
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///
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/// <returns>
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/// The logarithm of the probability of <c>x</c>
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/// occurring in the current distribution.
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/// </returns>
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///
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/// <remarks>
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/// The Probability Mass Function (PMF) describes the
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/// probability that a given value <c>k</c> will occur.
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/// </remarks>
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///
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protected internal override double InnerLogProbabilityMassFunction(int k)
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{
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if (k == 0)
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return Math.Log(p); // need special case otherwise will be double at center
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return lnconstant + (Math.Abs(k) - 1) * Math.Log(1 - p);
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}
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/// <summary>
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/// Generates a random observation from the current distribution.
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/// </summary>
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///
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/// <param name="source">The random number generator to use as a source of randomness.
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/// Default is to use <see cref="Accord.Math.Random.Generator.Random"/>.</param>
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///
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/// <returns>
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/// A random observations drawn from this distribution.
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/// </returns>
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///
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public override int Generate(Random source)
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{
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double u = source.NextDouble();
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return Math.Sign(u - 0.5) * (int)GeometricDistribution.Random(p, source);
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}
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/// <summary>
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/// Generates a random vector of observations from the current distribution.
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/// </summary>
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///
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/// <param name="samples">The number of samples to generate.</param>
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/// <param name="result">The location where to store the samples.</param>
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///
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/// <param name="source">The random number generator to use as a source of randomness.
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/// Default is to use <see cref="Accord.Math.Random.Generator.Random"/>.</param>
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///
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/// <returns>
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/// A random vector of observations drawn from this distribution.
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/// </returns>
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///
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public override double[] Generate(int samples, double[] result, Random source)
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{
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GeometricDistribution.Random(p, samples, result, source);
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for (int i = 0; i < samples; i++)
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result[i] *= Math.Sign(source.NextDouble() - 0.5);
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return result;
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}
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/// <summary>
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/// Generates a random vector of observations from the current distribution.
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/// </summary>
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///
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/// <param name="samples">The number of samples to generate.</param>
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/// <param name="result">The location where to store the samples.</param>
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/// <param name="source">The random number generator to use as a source of randomness.
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/// Default is to use <see cref="Accord.Math.Random.Generator.Random"/>.</param>
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///
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/// <returns>
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/// A random vector of observations drawn from this distribution.
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/// </returns>
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///
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public override int[] Generate(int samples, int[] result, Random source)
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{
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GeometricDistribution.Random(p, samples, result, source);
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for (int i = 0; i < samples; i++)
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result[i] *= Math.Sign(source.NextDouble() - 0.5);
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return result;
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}
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/// <summary>
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/// Creates a new object that is a copy of the current instance.
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/// </summary>
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///
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/// <returns>
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/// A new object that is a copy of this instance.
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/// </returns>
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///
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public override object Clone()
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{
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return new SymmetricGeometricDistribution(p);
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}
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/// <summary>
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/// Returns a <see cref="System.String"/> that represents this instance.
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/// </summary>
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///
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/// <returns>
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/// A <see cref="System.String"/> that represents this instance.
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/// </returns>
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///
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public override string ToString(string format, IFormatProvider formatProvider)
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{
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return String.Format(formatProvider, "SymmetricGeometric(x; p = {0})",
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p.ToString(format, formatProvider));
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}
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}
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}
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