// <copyright file="IDiscreteDistribution.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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//
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// Copyright (c) 2009-2014 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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// Software is furnished to do so, subject to the following
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// </copyright>
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namespace IStation.Numerics.Distributions
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{
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using System.Collections.Generic;
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/// <summary>
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/// Discrete Univariate Probability Distribution.
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/// </summary>
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/// <seealso cref="IContinuousDistribution"/>
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public interface IDiscreteDistribution : IUnivariateDistribution
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{
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/// <summary>
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/// Gets the mode of the distribution.
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/// </summary>
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int Mode { get; }
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/// <summary>
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/// Gets the smallest element in the domain of the distribution which can be represented by an integer.
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/// </summary>
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int Minimum { get; }
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/// <summary>
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/// Gets the largest element in the domain of the distribution which can be represented by an integer.
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/// </summary>
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int Maximum { get; }
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/// <summary>
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/// Computes the probability mass (PMF) at k, i.e. P(X = k).
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/// </summary>
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/// <param name="k">The location in the domain where we want to evaluate the probability mass function.</param>
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/// <returns>the probability mass at location <paramref name="k"/>.</returns>
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double Probability(int k);
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/// <summary>
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/// Computes the log probability mass (lnPMF) at k, i.e. ln(P(X = k)).
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/// </summary>
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/// <param name="k">The location in the domain where we want to evaluate the log probability mass function.</param>
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/// <returns>the log probability mass at location <paramref name="k"/>.</returns>
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double ProbabilityLn(int k);
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/// <summary>
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/// Draws a random sample from the distribution.
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/// </summary>
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/// <returns>a sample from the distribution.</returns>
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int Sample();
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/// <summary>
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/// Fills an array with samples generated from the distribution.
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/// </summary>
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void Samples(int[] values);
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/// <summary>
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/// Draws a sequence of random samples from the distribution.
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/// </summary>
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/// <returns>an infinite sequence of samples from the distribution.</returns>
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IEnumerable<int> Samples();
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}
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}
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