// // Math.NET Numerics, part of the Math.NET Project // http://mathnet.opensourcedotnet.info // // Copyright (c) 2009 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. // namespace MathNet.Numerics.UnitTests.DistributionTests { using System; using MbUnit.Framework; using MathNet.Numerics.Distributions; [TestFixture] public class NormalTests { [Test, MultipleAsserts] public void CanCreateStandardNormal() { var n = new Normal(); AssertEx.AreEqual(0.0, n.Mean); AssertEx.AreEqual(1.0, n.StdDev); } [Test, MultipleAsserts] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void CanCreateNormal(double mean, double sdev) { var n = new Normal(mean, sdev); AssertEx.AreEqual(mean, n.Mean); AssertEx.AreEqual(sdev, n.StdDev); } [Test] [ExpectedException(typeof(ArgumentOutOfRangeException))] public void NormalCreateFailsWithMeanIsNaN() { var n = new Normal(Double.NaN, 1.0); } [Test] [ExpectedException(typeof(ArgumentOutOfRangeException))] public void NormalCreateFailsWithStdDevIsNaN() { var n = new Normal(0.0, Double.NaN); } [Test, MultipleAsserts] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void CanCreateNormalFromMeanAndStdDev(double mean, double sdev) { var n = Normal.WithMeanStdDev(mean, sdev); AssertEx.AreEqual(mean, n.Mean); AssertEx.AreEqual(sdev, n.StdDev); } [Test, MultipleAsserts] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void CanCreateNormalFromMeanAndVariance(double mean, double var) { var n = Normal.WithMeanVariance(mean, var); AssertHelpers.AlmostEqual(mean, n.Mean, 16); AssertHelpers.AlmostEqual(var, n.Variance, 16); } [Test, MultipleAsserts] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void CanCreateNormalFromMeanAndPrecision(double mean, double prec) { var n = Normal.WithMeanAndPrecision(mean, prec); AssertHelpers.AlmostEqual(mean, n.Mean, 15); AssertHelpers.AlmostEqual(prec, n.Precision, 15); } [Test] public void ToStringTest() { var n = new Normal(1.0, 2.0); AssertEx.AreEqual("Normal(Mean = 1, StdDev = 2)", n.ToString()); } [Test] public void CanGetRandomNumberGenerator() { var n = new Normal(); var rs = n.RandomSource; Assert.IsNotNull(rs); } [Test] public void CanSetRandomNumberGenerator() { var n = new Normal(); n.RandomSource = new Random(); } [Test] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void CanSetPrecision(double prec) { var n = new Normal(); n.Precision = prec; } [Test] [ExpectedException(typeof(ArgumentOutOfRangeException))] public void SetPrecisionFailsWithNegativePrecision() { var n = new Normal(); n.Precision = -1.0; } [Test] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void CanSetVariance(double var) { var n = new Normal(); n.Variance = var; } [Test] [ExpectedException(typeof(ArgumentOutOfRangeException))] public void SetVarianceFailsWithNegativeVariance() { var n = new Normal(); n.Variance = -1.0; } [Test] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void CanSetStdDev(double sdev) { var n = new Normal(); n.StdDev = sdev; } [Test] [ExpectedException(typeof(ArgumentOutOfRangeException))] public void SetStdDevFailsWithNegativeStdDev() { var n = new Normal(); n.StdDev = -1.0; } [Test] [Row(Double.NegativeInfinity)] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void CanSetMean(double mean) { var n = new Normal(); n.Mean = mean; } [Test] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void ValidateEntropy(double sdev) { var n = new Normal(1.0, sdev); AssertEx.AreEqual(MathNet.Numerics.Constants.LogSqrt2PiE + Math.Log(n.StdDev), n.Entropy); } [Test] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void ValidateSkewness(double sdev) { var n = new Normal(1.0, sdev); AssertEx.AreEqual(0.0, n.Skewness); } [Test] [Row(Double.NegativeInfinity)] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void ValidateMode(double mean) { var n = new Normal(mean, 1.0); AssertEx.AreEqual(mean, n.Mode); } [Test] [Row(Double.NegativeInfinity)] [Row(-0.0)] [Row(0.0)] [Row(0.1)] [Row(1.0)] [Row(10.0)] [Row(Double.PositiveInfinity)] public void ValidateMedian(double mean) { var n = new Normal(mean, 1.0); AssertEx.AreEqual(mean, n.Median); } [Test] public void ValidateMinimum() { var n = new Normal(); AssertEx.AreEqual(System.Double.NegativeInfinity, n.Minimum); } [Test] public void ValidateMaximum() { var n = new Normal(); AssertEx.AreEqual(System.Double.PositiveInfinity, n.Maximum); } [Test] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void ValidateDensity(double mean, double sdev) { var n = Normal.WithMeanStdDev(mean, sdev); for(int i = 0; i < 11; i++) { double x = i - 5.0; double d = (mean - x)/sdev; double pdf = Math.Exp(-0.5*d*d)/(sdev*Constants.Sqrt2Pi); AssertEx.AreEqual(pdf, n.Density(x)); } } [Test] [Row(0.0, 0.0)] [Row(0.0, 0.1)] [Row(0.0, 1.0)] [Row(0.0, 10.0)] [Row(10.0, 1.0)] [Row(-5.0, 100.0)] [Row(0.0, Double.PositiveInfinity)] public void ValidateDensityLn(double mean, double sdev) { var n = Normal.WithMeanStdDev(mean, sdev); for (int i = 0; i < 11; i++) { double x = i - 5.0; double d = (mean - x) / sdev; double pdfln = -0.5 * d * d - Math.Log(sdev) - Constants.LogSqrt2Pi; AssertEx.AreEqual(pdfln, n.DensityLn(x)); } } [Test] public void CanSampleStatic() { var d = Normal.Sample(new Random(), 0.0, 1.0); } [Test] public void CanSampleSequenceStatic() { var ied = Normal.Samples(new Random(), 0.0, 1.0); var e = ied.GetEnumerator(); e.MoveNext(); var d = e.Current; e.MoveNext(); var g = e.Current; } [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.GetEnumerator(); e.MoveNext(); var d = e.Current; e.MoveNext(); var g = e.Current; } [Test] [Row(Double.NegativeInfinity, 0.0)] [Row(-5.0, 0.00000028665157187919391167375233287464535385442301361187883)] [Row(-2.0, 0.0002326290790355250363499258867279847735487493358890356)] [Row(-0.0, 0.0062096653257761351669781045741922211278977469230927036)] [Row(0.0, 0.0062096653257761351669781045741922211278977469230927036)] [Row(4.0, 0.30853753872598689636229538939166226011639782444542207)] [Row(5.0, 0.5)] [Row(6.0, 0.69146246127401310363770461060833773988360217555457859)] [Row(10.0, 0.9937903346742238648330218954258077788721022530769078)] [Row(Double.PositiveInfinity, 1.0)] public void ValidateCumulativeDistribution(double x, double f) { var n = Normal.WithMeanStdDev(5.0, 2.0); AssertHelpers.AlmostEqual(f, n.CumulativeDistribution(x), 10); } [Test] [Row(Double.NegativeInfinity, 0.0)] [Row(-5.0, 0.00000028665157187919391167375233287464535385442301361187883)] [Row(-2.0, 0.0002326290790355250363499258867279847735487493358890356)] [Row(-0.0, 0.0062096653257761351669781045741922211278977469230927036)] [Row(0.0, 0.0062096653257761351669781045741922211278977469230927036)] [Row(4.0, 0.30853753872598689636229538939166226011639782444542207)] [Row(5.0, 0.5)] [Row(6.0, 0.69146246127401310363770461060833773988360217555457859)] [Row(10.0, 0.9937903346742238648330218954258077788721022530769078)] [Row(Double.PositiveInfinity, 1.0)] public void ValidateInverseCumulativeDistribution(double x, double f) { var n = Normal.WithMeanStdDev(5.0, 2.0); AssertHelpers.AlmostEqual(x, n.InverseCumulativeDistribution(f), 10); } } }