// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // // Copyright (c) 2009-2014 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. // using System; using System.Collections.Generic; using IStation.Numerics.Random; namespace IStation.Numerics.Distributions { /// /// Discrete Univariate Uniform distribution. /// The discrete uniform distribution is a distribution over integers. The distribution /// is parameterized by a lower and upper bound (both inclusive). /// Wikipedia - Discrete uniform distribution. /// public class DiscreteUniform : IDiscreteDistribution { System.Random _random; readonly int _lower; readonly int _upper; /// /// Initializes a new instance of the DiscreteUniform class. /// /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. public DiscreteUniform(int lower, int upper) { if (!IsValidParameterSet(lower, upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } _random = SystemRandomSource.Default; _lower = lower; _upper = upper; } /// /// Initializes a new instance of the DiscreteUniform class. /// /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// The random number generator which is used to draw random samples. public DiscreteUniform(int lower, int upper, System.Random randomSource) { if (!IsValidParameterSet(lower, upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } _random = randomSource ?? SystemRandomSource.Default; _lower = lower; _upper = upper; } /// /// Returns a that represents this instance. /// /// /// A that represents this instance. /// public override string ToString() { return $"DiscreteUniform(Lower = {_lower}, Upper = {_upper})"; } /// /// Tests whether the provided values are valid parameters for this distribution. /// /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. public static bool IsValidParameterSet(int lower, int upper) { return lower <= upper; } /// /// Gets the inclusive lower bound of the probability distribution. /// public int LowerBound => _lower; /// /// Gets the inclusive upper bound of the probability distribution. /// public int UpperBound => _upper; /// /// Gets or sets the random number generator which is used to draw random samples. /// public System.Random RandomSource { get => _random; set => _random = value ?? SystemRandomSource.Default; } /// /// Gets the mean of the distribution. /// public double Mean => (_lower + _upper)/2.0; /// /// Gets the standard deviation of the distribution. /// public double StdDev => Math.Sqrt((((_upper - _lower + 1.0)*(_upper - _lower + 1.0)) - 1.0)/12.0); /// /// Gets the variance of the distribution. /// public double Variance => (((_upper - _lower + 1.0)*(_upper - _lower + 1.0)) - 1.0)/12.0; /// /// Gets the entropy of the distribution. /// public double Entropy => Math.Log(_upper - _lower + 1.0); /// /// Gets the skewness of the distribution. /// public double Skewness => 0.0; /// /// Gets the smallest element in the domain of the distributions which can be represented by an integer. /// public int Minimum => _lower; /// /// Gets the largest element in the domain of the distributions which can be represented by an integer. /// public int Maximum => _upper; /// /// Gets the mode of the distribution; since every element in the domain has the same probability this method returns the middle one. /// public int Mode => (int)Math.Floor((_lower + _upper)/2.0); /// /// Gets the median of the distribution. /// public double Median => (_lower + _upper)/2.0; /// /// Computes the probability mass (PMF) at k, i.e. P(X = k). /// /// The location in the domain where we want to evaluate the probability mass function. /// the probability mass at location . public double Probability(int k) { return PMF(_lower, _upper, k); } /// /// Computes the log probability mass (lnPMF) at k, i.e. ln(P(X = k)). /// /// The location in the domain where we want to evaluate the log probability mass function. /// the log probability mass at location . public double ProbabilityLn(int k) { return PMFLn(_lower, _upper, k); } /// /// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). /// /// The location at which to compute the cumulative distribution function. /// the cumulative distribution at location . public double CumulativeDistribution(double x) { return CDF(_lower, _upper, x); } /// /// Computes the probability mass (PMF) at k, i.e. P(X = k). /// /// The location in the domain where we want to evaluate the probability mass function. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// the probability mass at location . public static double PMF(int lower, int upper, int k) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return k >= lower && k <= upper ? 1.0/(upper - lower + 1) : 0.0; } /// /// Computes the log probability mass (lnPMF) at k, i.e. ln(P(X = k)). /// /// The location in the domain where we want to evaluate the log probability mass function. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// the log probability mass at location . public static double PMFLn(int lower, int upper, int k) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return k >= lower && k <= upper ? -Math.Log(upper - lower + 1) : double.NegativeInfinity; } /// /// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). /// /// The location at which to compute the cumulative distribution function. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// the cumulative distribution at location . /// public static double CDF(int lower, int upper, double x) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } if (x < lower) { return 0.0; } if (x >= upper) { return 1.0; } return Math.Min(1.0, (Math.Floor(x) - lower + 1)/(upper - lower + 1)); } /// /// Generates one sample from the discrete uniform distribution. This method does not do any parameter checking. /// /// The random source to use. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// A random sample from the discrete uniform distribution. static int SampleUnchecked(System.Random rnd, int lower, int upper) { return rnd.Next(lower, upper + 1); } static void SamplesUnchecked(System.Random rnd, int[] values, int lower, int upper) { rnd.NextInt32s(values, lower, upper + 1); } static IEnumerable SamplesUnchecked(System.Random rnd, int lower, int upper) { return rnd.NextInt32Sequence(lower, upper + 1); } /// /// Draws a random sample from the distribution. /// /// a sample from the distribution. public int Sample() { return SampleUnchecked(_random, _lower, _upper); } /// /// Fills an array with samples generated from the distribution. /// public void Samples(int[] values) { SamplesUnchecked(_random, values, _lower, _upper); } /// /// Samples an array of uniformly distributed random variables. /// /// a sequence of samples from the distribution. public IEnumerable Samples() { return SamplesUnchecked(_random, _lower, _upper); } /// /// Samples a uniformly distributed random variable. /// /// The random number generator to use. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// A sample from the discrete uniform distribution. public static int Sample(System.Random rnd, int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SampleUnchecked(rnd, lower, upper); } /// /// Samples a sequence of uniformly distributed random variables. /// /// The random number generator to use. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// a sequence of samples from the discrete uniform distribution. public static IEnumerable Samples(System.Random rnd, int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SamplesUnchecked(rnd, lower, upper); } /// /// Fills an array with samples generated from the distribution. /// /// The random number generator to use. /// The array to fill with the samples. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// a sequence of samples from the discrete uniform distribution. public static void Samples(System.Random rnd, int[] values, int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } SamplesUnchecked(rnd, values, lower, upper); } /// /// Samples a uniformly distributed random variable. /// /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// A sample from the discrete uniform distribution. public static int Sample(int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SampleUnchecked(SystemRandomSource.Default, lower, upper); } /// /// Samples a sequence of uniformly distributed random variables. /// /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// a sequence of samples from the discrete uniform distribution. public static IEnumerable Samples(int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SamplesUnchecked(SystemRandomSource.Default, lower, upper); } /// /// Fills an array with samples generated from the distribution. /// /// The array to fill with the samples. /// Lower bound, inclusive. Range: lower ≤ upper. /// Upper bound, inclusive. Range: lower ≤ upper. /// a sequence of samples from the discrete uniform distribution. public static void Samples(int[] values, int lower, int upper) { if (!(lower <= upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } SamplesUnchecked(SystemRandomSource.Default, values, lower, upper); } } }