// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // // 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. // using System; using System.Collections.Generic; using IStation.Numerics.Random; using IStation.Numerics.Threading; namespace IStation.Numerics.Distributions { /// /// Continuous Univariate Uniform distribution. /// The continuous uniform distribution is a distribution over real numbers. For details about this distribution, see /// Wikipedia - Continuous uniform distribution. /// public class ContinuousUniform : IContinuousDistribution { System.Random _random; readonly double _lower; readonly double _upper; /// /// Initializes a new instance of the ContinuousUniform class with lower bound 0 and upper bound 1. /// public ContinuousUniform() : this(0.0, 1.0) { } /// /// Initializes a new instance of the ContinuousUniform class with given lower and upper bounds. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// If the upper bound is smaller than the lower bound. public ContinuousUniform(double lower, double 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 ContinuousUniform class with given lower and upper bounds. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// The random number generator which is used to draw random samples. /// If the upper bound is smaller than the lower bound. public ContinuousUniform(double lower, double upper, System.Random randomSource) { if (!IsValidParameterSet(lower, upper)) { throw new ArgumentException("Invalid parametrization for the distribution."); } _random = randomSource ?? SystemRandomSource.Default; _lower = lower; _upper = upper; } /// /// A string representation of the distribution. /// /// a string representation of the distribution. public override string ToString() { return $"ContinuousUniform(Lower = {_lower}, Upper = {_upper})"; } /// /// Tests whether the provided values are valid parameters for this distribution. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. public static bool IsValidParameterSet(double lower, double upper) { return lower <= upper; } /// /// Gets the lower bound of the distribution. /// public double LowerBound => _lower; /// /// Gets the upper bound of the distribution. /// public double 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 variance of the distribution. /// public double Variance => (_upper - _lower)*(_upper - _lower)/12.0; /// /// Gets the standard deviation of the distribution. /// public double StdDev => (_upper - _lower)/Math.Sqrt(12.0); /// /// Gets the entropy of the distribution. /// /// public double Entropy => Math.Log(_upper - _lower); /// /// Gets the skewness of the distribution. /// public double Skewness => 0.0; /// /// Gets the mode of the distribution. /// /// public double Mode => (_lower + _upper)/2.0; /// /// Gets the median of the distribution. /// /// public double Median => (_lower + _upper)/2.0; /// /// Gets the minimum of the distribution. /// public double Minimum => _lower; /// /// Gets the maximum of the distribution. /// public double Maximum => _upper; /// /// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. /// /// The location at which to compute the density. /// the density at . /// public double Density(double x) { return x < _lower || x > _upper ? 0.0 : 1.0/(_upper - _lower); } /// /// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). /// /// The location at which to compute the log density. /// the log density at . /// public double DensityLn(double x) { return x < _lower || x > _upper ? double.NegativeInfinity : -Math.Log(_upper - _lower); } /// /// 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 x <= _lower ? 0.0 : x >= _upper ? 1.0 : (x - _lower)/(_upper - _lower); } /// /// 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. /// /// The location at which to compute the inverse cumulative density. /// the inverse cumulative density at . /// public double InverseCumulativeDistribution(double p) { return p <= 0.0 ? _lower : p >= 1.0 ? _upper : _lower*(1.0 - p) + _upper*p; } /// /// Generates a sample from the ContinuousUniform distribution. /// /// a sample from the distribution. public double Sample() { return SampleUnchecked(_random, _lower, _upper); } /// /// Fills an array with samples generated from the distribution. /// public void Samples(double[] values) { SamplesUnchecked(_random, values, _lower, _upper); } /// /// Generates a sequence of samples from the ContinuousUniform distribution. /// /// a sequence of samples from the distribution. public IEnumerable Samples() { return SamplesUnchecked(_random, _lower, _upper); } static double SampleUnchecked(System.Random rnd, double lower, double upper) { return lower + rnd.NextDouble()*(upper - lower); } static IEnumerable SamplesUnchecked(System.Random rnd, double lower, double upper) { double difference = upper - lower; while (true) { yield return lower + rnd.NextDouble()*difference; } } internal static void SamplesUnchecked(System.Random rnd, double[] values, double lower, double upper) { rnd.NextDoubles(values); var difference = upper - lower; CommonParallel.For(0, values.Length, 4096, (a, b) => { for (int i = a; i < b; i++) { values[i] = lower + values[i]*difference; } }); } /// /// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// The location at which to compute the density. /// the density at . /// public static double PDF(double lower, double upper, double x) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return x < lower || x > upper ? 0.0 : 1.0/(upper - lower); } /// /// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// The location at which to compute the density. /// the log density at . /// public static double PDFLn(double lower, double upper, double x) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return x < lower || x > upper ? double.NegativeInfinity : -Math.Log(upper - lower); } /// /// 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. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// the cumulative distribution at location . /// public static double CDF(double lower, double upper, double x) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return x <= lower ? 0.0 : x >= upper ? 1.0 : (x - lower)/(upper - lower); } /// /// 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. /// /// The location at which to compute the inverse cumulative density. /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// the inverse cumulative density at . /// public static double InvCDF(double lower, double upper, double p) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return p <= 0.0 ? lower : p >= 1.0 ? upper : lower*(1.0 - p) + upper*p; } /// /// Generates a sample from the ContinuousUniform distribution. /// /// The random number generator to use. /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a uniformly distributed sample. public static double Sample(System.Random rnd, double lower, double upper) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SampleUnchecked(rnd, lower, upper); } /// /// Generates a sequence of samples from the ContinuousUniform distribution. /// /// The random number generator to use. /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a sequence of uniformly distributed samples. public static IEnumerable Samples(System.Random rnd, double lower, double upper) { if (upper < lower) { 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. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a sequence of samples from the distribution. public static void Samples(System.Random rnd, double[] values, double lower, double upper) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } SamplesUnchecked(rnd, values, lower, upper); } /// /// Generates a sample from the ContinuousUniform distribution. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a uniformly distributed sample. public static double Sample(double lower, double upper) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } return SampleUnchecked(SystemRandomSource.Default, lower, upper); } /// /// Generates a sequence of samples from the ContinuousUniform distribution. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a sequence of uniformly distributed samples. public static IEnumerable Samples(double lower, double upper) { if (upper < lower) { 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. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. /// a sequence of samples from the distribution. public static void Samples(double[] values, double lower, double upper) { if (upper < lower) { throw new ArgumentException("Invalid parametrization for the distribution."); } SamplesUnchecked(SystemRandomSource.Default, values, lower, upper); } } }