ufkc7e3d
/
mathnet-numerics
forked from tsai/mathnet-numerics
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Statistics: TruncatedNormal minor formatting tweaks #344

truncatednormal
Christoph Ruegg 11 years ago
parent
701027ff3c
commit
7e0b98c625
3 changed files with 71 additions and 71 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 87
      src/Numerics/Distributions/TruncatedNormal.cs
  2. 4
      src/UnitTests/DistributionTests/CommonDistributionTests.cs
  3. 51
      src/UnitTests/DistributionTests/Continuous/TruncatedNormalTests.cs

87
src/Numerics/Distributions/TruncatedNormal.cs
View File

@ -4,7 +4,7 @@
// http://github.com/mathnet/mathnet-numerics // http://github.com/mathnet/mathnet-numerics
// http://mathnetnumerics.codeplex.com // http://mathnetnumerics.codeplex.com
// //
// Copyright (c) 2009-2013 Math.NET // Copyright (c) 2009-2015 Math.NET
// //
// Permission is hereby granted, free of charge, to any person // Permission is hereby granted, free of charge, to any person
// obtaining a copy of this software and associated documentation // obtaining a copy of this software and associated documentation
@ -42,24 +42,27 @@ namespace MathNet.Numerics.Distributions {
/// </summary> /// </summary>
public class TruncatedNormal : IContinuousDistribution public class TruncatedNormal : IContinuousDistribution
{ {
System.Random _random; System.Random _random;
/// <summary> /// <summary>
/// Mean of the untruncated normal distribution. /// Mean of the untruncated normal distribution.
/// </summary> /// </summary>
readonly double _mu; readonly double _mu;
/// <summary> /// <summary>
/// Standard deviation of the uncorrected normal distribution. /// Standard deviation of the uncorrected normal distribution.
/// </summary> /// </summary>
readonly double _sigma; readonly double _sigma;
readonly double _lowerBound; readonly double _lowerBound;
readonly double _upperBound; readonly double _upperBound;
readonly Normal _standardNormal = new Normal(0.0, 1.0); readonly Normal _standardNormal = new Normal(0.0, 1.0);
/// <summary> /// <summary>
/// Position in the standard normal distribution of the lower bound. /// Position in the standard normal distribution of the lower bound.
/// </summary> /// </summary>
readonly double _alpha; readonly double _alpha;
/// <summary> /// <summary>
/// Position in the standard normal distribution of the upper bound. /// Position in the standard normal distribution of the upper bound.
/// </summary> /// </summary>
@ -73,7 +76,7 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Initializes a new instance of the TruncatedNormal class. The distribution will /// Initializes a new instance of the TruncatedNormal class. The distribution will
/// be initialized with the default <seealso cref="System.Random"/> random number generator. The mean /// be initialized with the default <seealso cref="System.Random"/> random number generator. The mean
/// and standard deviation are that of the untruncated normal distribution. /// and standard deviation are that of the untruncated normal distribution.
/// </summary> /// </summary>
/// <param name="mean">The mean (μ) of the untruncated distribution.</param> /// <param name="mean">The mean (μ) of the untruncated distribution.</param>
@ -81,10 +84,9 @@ namespace MathNet.Numerics.Distributions {
/// <param name="lowerBound">The inclusive lower bound of the truncated distribution. Default is double.NegativeInfinity.</param> /// <param name="lowerBound">The inclusive lower bound of the truncated distribution. Default is double.NegativeInfinity.</param>
/// <param name="upperBound">The inclusive upper bound of the truncated distribution. Must be larger than <paramref name="lowerBound"/>. /// <param name="upperBound">The inclusive upper bound of the truncated distribution. Must be larger than <paramref name="lowerBound"/>.
/// Default is double.PositiveInfinity.</param> /// Default is double.PositiveInfinity.</param>
public TruncatedNormal(double mean, double stddev, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity) public TruncatedNormal(double mean, double stddev, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity)
:this(mean, stddev, SystemRandomSource.Default, lowerBound, upperBound) : this(mean, stddev, SystemRandomSource.Default, lowerBound, upperBound)
{ {
} }
/// <summary> /// <summary>
@ -98,9 +100,9 @@ namespace MathNet.Numerics.Distributions {
/// <param name="upperBound">The inclusive upper bound of the truncated distribution. Must be larger than <paramref name="lowerBound"/>. /// <param name="upperBound">The inclusive upper bound of the truncated distribution. Must be larger than <paramref name="lowerBound"/>.
/// Default is double.PositiveInfinity.</param> /// Default is double.PositiveInfinity.</param>
public TruncatedNormal(double untruncatedMean, double untruncatedStdDev, System.Random randomSource, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity) public TruncatedNormal(double untruncatedMean, double untruncatedStdDev, System.Random randomSource, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity)
{ {
if (!IsValidParameterSet(untruncatedMean, untruncatedStdDev, lowerBound, upperBound)) if (!IsValidParameterSet(untruncatedMean, untruncatedStdDev, lowerBound, upperBound))
{ {
throw new ArgumentException(Resources.InvalidDistributionParameters); throw new ArgumentException(Resources.InvalidDistributionParameters);
} }
@ -121,23 +123,24 @@ namespace MathNet.Numerics.Distributions {
/// </summary> /// </summary>
/// <param name="mean">The mean (μ) of the normal distribution.</param> /// <param name="mean">The mean (μ) of the normal distribution.</param>
/// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ > 0.</param> /// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ > 0.</param>
public static bool IsValidParameterSet(double mean, double stddev, double lowerBound, double upperBound) public static bool IsValidParameterSet(double mean, double stddev, double lowerBound, double upperBound)
{ {
bool normalRequirements = Normal.IsValidParameterSet(mean, stddev) && stddev > 0; bool normalRequirements = Normal.IsValidParameterSet(mean, stddev) && stddev > 0;
bool boundsAreOrdered = lowerBound < upperBound; bool boundsAreOrdered = lowerBound < upperBound;
return normalRequirements && boundsAreOrdered; return normalRequirements && boundsAreOrdered;
} }
public override string ToString() { public override string ToString()
{
return "TruncatedNormal(μ = " + _mu + ", σ = " + _sigma +", LowerBound = " + _lowerBound + ", UpperBound = " + _upperBound + ")"; return "TruncatedNormal(μ = " + _mu + ", σ = " + _sigma +", LowerBound = " + _lowerBound + ", UpperBound = " + _upperBound + ")";
} }
/// <summary> /// <summary>
/// Gets the mode of the normal distribution. /// Gets the mode of the truncated normal distribution.
/// </summary> /// </summary>
public double Mode public double Mode
{ {
get get
{ {
if (_mu < _lowerBound) if (_mu < _lowerBound)
return _lowerBound; return _lowerBound;
@ -150,7 +153,7 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the minimum of the truncated normal distribution. /// Gets the minimum of the truncated normal distribution.
/// </summary> /// </summary>
public double Minimum public double Minimum
{ {
get { return _lowerBound; } get { return _lowerBound; }
} }
@ -158,7 +161,7 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the maximum of the truncated normal distribution. /// Gets the maximum of the truncated normal distribution.
/// </summary> /// </summary>
public double Maximum public double Maximum
{ {
get { return _upperBound; } get { return _upperBound; }
} }
@ -166,9 +169,9 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the mean (μ) of the truncated normal distribution. /// Gets the mean (μ) of the truncated normal distribution.
/// </summary> /// </summary>
public double Mean public double Mean
{ {
get get
{ {
var pdfDifference = _standardNormal.Density(_alpha) - _standardNormal.Density(_beta); var pdfDifference = _standardNormal.Density(_alpha) - _standardNormal.Density(_beta);
var diffFromUncorrected = pdfDifference * _sigma / _cumulativeDensityWithinBounds; var diffFromUncorrected = pdfDifference * _sigma / _cumulativeDensityWithinBounds;
@ -177,11 +180,11 @@ namespace MathNet.Numerics.Distributions {
} }
/// <summary> /// <summary>
/// Gets the variance of the truncated normal distribution. /// Gets the variance of the truncated normal distribution.
/// </summary> /// </summary>
public double Variance public double Variance
{ {
get get
{ {
//Apparently "Barr and Sherrill (1999)" has a simpler expression for one sided truncations, if anyone has access... //Apparently "Barr and Sherrill (1999)" has a simpler expression for one sided truncations, if anyone has access...
@ -209,7 +212,7 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the standard deviation (σ) of the truncated normal distribution. Range: σ > 0. /// Gets the standard deviation (σ) of the truncated normal distribution. Range: σ > 0.
/// </summary> /// </summary>
public double StdDev public double StdDev
{ {
get { return Math.Sqrt(Variance); } get { return Math.Sqrt(Variance); }
} }
@ -217,9 +220,9 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the entropy of the truncated normal distribution. /// Gets the entropy of the truncated normal distribution.
/// </summary> /// </summary>
public double Entropy public double Entropy
{ {
get get
{ {
var firstTerm = Constants.LogSqrt2PiE + Math.Log(_sigma + _cumulativeDensityWithinBounds); var firstTerm = Constants.LogSqrt2PiE + Math.Log(_sigma + _cumulativeDensityWithinBounds);
@ -232,7 +235,7 @@ namespace MathNet.Numerics.Distributions {
public double Skewness public double Skewness
{ {
get get
{ {
throw new NotImplementedException(); throw new NotImplementedException();
} }
@ -241,9 +244,9 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets the median of the truncated distribution. /// Gets the median of the truncated distribution.
/// </summary> /// </summary>
public double Median public double Median
{ {
get get
{ {
return InverseCumulativeDistribution(0.5); return InverseCumulativeDistribution(0.5);
} }
@ -252,7 +255,7 @@ namespace MathNet.Numerics.Distributions {
/// <summary> /// <summary>
/// Gets or sets the random number generator which is used to draw random samples. /// Gets or sets the random number generator which is used to draw random samples.
/// </summary> /// </summary>
public System.Random RandomSource public System.Random RandomSource
{ {
get { return _random; } get { return _random; }
set { _random = value ?? SystemRandomSource.Default; } set { _random = value ?? SystemRandomSource.Default; }
@ -264,7 +267,7 @@ namespace MathNet.Numerics.Distributions {
/// <param name="x">The location at which to compute the density.</param> /// <param name="x">The location at which to compute the density.</param>
/// <returns>the density at <paramref name="x"/>.</returns> /// <returns>the density at <paramref name="x"/>.</returns>
/// <seealso cref="PDF"/> /// <seealso cref="PDF"/>
public double Density(double x) public double Density(double x)
{ {
if (x < _lowerBound || _upperBound < x) if (x < _lowerBound || _upperBound < x)
return 0d; return 0d;
@ -278,29 +281,30 @@ namespace MathNet.Numerics.Distributions {
/// <param name="x">The location at which to compute the log density.</param> /// <param name="x">The location at which to compute the log density.</param>
/// <returns>the log density at <paramref name="x"/>.</returns> /// <returns>the log density at <paramref name="x"/>.</returns>
/// <seealso cref="PDFLn"/> /// <seealso cref="PDFLn"/>
public double DensityLn(double x) public double DensityLn(double x)
{ {
return _standardNormal.DensityLn((x - _mu) / _sigma) - Math.Log(_sigma) - Math.Log(_cumulativeDensityWithinBounds); return _standardNormal.DensityLn((x - _mu) / _sigma) - Math.Log(_sigma) - Math.Log(_cumulativeDensityWithinBounds);
} }
public double Sample()
public double Sample()
{ {
//TODO: implement sampling more efficiently/accurately, use method described by Mazet here: http://miv.u-strasbg.fr/mazet/rtnorm/ //TODO: implement sampling more efficiently/accurately, use method described by Mazet here: http://miv.u-strasbg.fr/mazet/rtnorm/
// see implementations listed on that page for examples. // see implementations listed on that page for examples.
return InverseCumulativeDistribution(RandomSource.NextDouble()); return InverseCumulativeDistribution(RandomSource.NextDouble());
} }
public void Samples(double[] values) public void Samples(double[] values)
{ {
for(int i = 0; i < values.Length; i++) { for(int i = 0; i < values.Length; i++)
{
values[i] = Sample(); values[i] = Sample();
} }
} }
public IEnumerable<double> Samples() public IEnumerable<double> Samples()
{ {
while (true) { while (true)
{
yield return Sample(); yield return Sample();
} }
} }
@ -311,7 +315,7 @@ namespace MathNet.Numerics.Distributions {
/// <param name="x">The location at which to compute the cumulative distribution function.</param> /// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns> /// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CDF"/> /// <seealso cref="CDF"/>
public double CumulativeDistribution(double x) public double CumulativeDistribution(double x)
{ {
if (x < _lowerBound) if (x < _lowerBound)
return 0d; return 0d;
@ -329,13 +333,12 @@ namespace MathNet.Numerics.Distributions {
/// <param name="p">The location at which to compute the inverse cumulative density.</param> /// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns> /// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
/// <seealso cref="InvCDF"/> /// <seealso cref="InvCDF"/>
public double InverseCumulativeDistribution(double p) public double InverseCumulativeDistribution(double p)
{ {
//TODO check that this is correct with someone. //TODO check that this is correct with someone.
var pUntruncated = p * _cumulativeDensityWithinBounds + _standardNormal.CumulativeDistribution(_alpha); var pUntruncated = p * _cumulativeDensityWithinBounds + _standardNormal.CumulativeDistribution(_alpha);
return _standardNormal.InverseCumulativeDistribution(pUntruncated) * _sigma + _mu; return _standardNormal.InverseCumulativeDistribution(pUntruncated) * _sigma + _mu;
} }
} }
} }

4
src/UnitTests/DistributionTests/CommonDistributionTests.cs
View File

@ -89,8 +89,8 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
new StudentT(0.0, 1.0, 5.0), new StudentT(0.0, 1.0, 5.0),
new Triangular(0, 1, 0.7), new Triangular(0, 1, 0.7),
new Weibull(1.0, 1.0), new Weibull(1.0, 1.0),
new TruncatedNormal(0, 1.0, -1.0, 1.5), //Finite new TruncatedNormal(0, 1.0, -1.0, 1.5), //Finite
new TruncatedNormal(0, 1.0, -0.5), //Semi-finite new TruncatedNormal(0, 1.0, -0.5), //Semi-finite
}; };
[Test] [Test]

51
src/UnitTests/DistributionTests/Continuous/TruncatedNormalTests.cs
View File

@ -4,7 +4,7 @@
// http://github.com/mathnet/mathnet-numerics // http://github.com/mathnet/mathnet-numerics
// http://mathnetnumerics.codeplex.com // http://mathnetnumerics.codeplex.com
// //
// Copyright (c) 2009-2014 Math.NET // Copyright (c) 2009-2015 Math.NET
// //
// Permission is hereby granted, free of charge, to any person // Permission is hereby granted, free of charge, to any person
// obtaining a copy of this software and associated documentation // obtaining a copy of this software and associated documentation
@ -31,16 +31,13 @@
using MathNet.Numerics.Distributions; using MathNet.Numerics.Distributions;
using NUnit.Framework; using NUnit.Framework;
using System; using System;
using System.Collections.Generic;
using System.Linq; using System.Linq;
using System.Threading.Tasks;
namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
{ {
[TestFixture, Category("Distributions")] [TestFixture, Category("Distributions")]
public class TruncatedNormalTests public class TruncatedNormalTests
{ {
/// <summary> /// <summary>
/// Can create a truncated normal without bounds. /// Can create a truncated normal without bounds.
/// </summary> /// </summary>
@ -50,7 +47,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(0.0, 10.0)] [TestCase(0.0, 10.0)]
[TestCase(10.0, 100.0)] [TestCase(10.0, 100.0)]
[TestCase(-5.0, Double.PositiveInfinity)] [TestCase(-5.0, Double.PositiveInfinity)]
public void CanCreateWithoutBounds(double mean, double stdDev) public void CanCreateWithoutBounds(double mean, double stdDev)
{ {
var truncatedNormal = new TruncatedNormal(mean, stdDev); var truncatedNormal = new TruncatedNormal(mean, stdDev);
Assert.IsTrue(double.IsNegativeInfinity(truncatedNormal.Minimum)); Assert.IsTrue(double.IsNegativeInfinity(truncatedNormal.Minimum));
@ -68,7 +65,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
/// <param name="upper"></param> /// <param name="upper"></param>
[TestCase(0.0, -1.0,-10d, 10d)] [TestCase(0.0, -1.0,-10d, 10d)]
[TestCase(0.0, 1.0, 10d, 9d)] [TestCase(0.0, 1.0, 10d, 9d)]
public void TruncatedNormalCreateFailsWithBadParameters(double mean, double stdDev, double lower, double upper) public void TruncatedNormalCreateFailsWithBadParameters(double mean, double stdDev, double lower, double upper)
{ {
Assert.That(() => new TruncatedNormal(mean, stdDev, lower, upper), Throws.ArgumentException); Assert.That(() => new TruncatedNormal(mean, stdDev, lower, upper), Throws.ArgumentException);
} }
@ -78,7 +75,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(-6.0, 1.0, -5.0, 5.0)] [TestCase(-6.0, 1.0, -5.0, 5.0)]
[TestCase(8.0, 1.0, -5.0, 5.0)] [TestCase(8.0, 1.0, -5.0, 5.0)]
[TestCase(15, 20.0, -20.0, 0.0)] [TestCase(15, 20.0, -20.0, 0.0)]
public void ValidateMode(double mean, double stdDev, double lower, double upper) public void ValidateMode(double mean, double stdDev, double lower, double upper)
{ {
double mode; double mode;
if(mean < lower) { if(mean < lower) {
@ -108,10 +105,10 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(6.0, .69146246127401310363770461060833773988360217555457859)] [TestCase(6.0, .69146246127401310363770461060833773988360217555457859)]
[TestCase(10.0, 0.9937903346742238648330218954258077788721022530769078)] [TestCase(10.0, 0.9937903346742238648330218954258077788721022530769078)]
[TestCase(Double.PositiveInfinity, 1.0)] [TestCase(Double.PositiveInfinity, 1.0)]
public void ValidateCumulativeNoBounds(double x, double p) public void ValidateCumulativeNoBounds(double x, double p)
{ {
var truncatedNormal = new TruncatedNormal(5.0, 2.0); var truncatedNormal = new TruncatedNormal(5.0, 2.0);
AssertHelpers.AlmostEqualRelative(p, truncatedNormal.CumulativeDistribution(x), 14); AssertHelpers.AlmostEqualRelative(p, truncatedNormal.CumulativeDistribution(x), 14);
} }
/// <summary> /// <summary>
@ -130,7 +127,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(6.0, .69146246127401310363770461060833773988360217555457859)] [TestCase(6.0, .69146246127401310363770461060833773988360217555457859)]
[TestCase(10.0, 0.9937903346742238648330218954258077788721022530769078)] [TestCase(10.0, 0.9937903346742238648330218954258077788721022530769078)]
[TestCase(Double.PositiveInfinity, 1.0)] [TestCase(Double.PositiveInfinity, 1.0)]
public void ValidateInverseCumulativeNoBounds(double x, double p) public void ValidateInverseCumulativeNoBounds(double x, double p)
{ {
var truncatedNormal = new TruncatedNormal(5.0, 2.0); var truncatedNormal = new TruncatedNormal(5.0, 2.0);
AssertHelpers.AlmostEqualRelative(x, truncatedNormal.InverseCumulativeDistribution(p), 14); AssertHelpers.AlmostEqualRelative(x, truncatedNormal.InverseCumulativeDistribution(p), 14);
@ -147,7 +144,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(0.0, 10.0)] [TestCase(0.0, 10.0)]
[TestCase(10.0, 100.0)] [TestCase(10.0, 100.0)]
[TestCase(-5.0, Double.PositiveInfinity)] [TestCase(-5.0, Double.PositiveInfinity)]
public void ValidateDensityNoBounds(double mean, double sdev) public void ValidateDensityNoBounds(double mean, double sdev)
{ {
var n = new TruncatedNormal(mean, sdev); var n = new TruncatedNormal(mean, sdev);
for (var i = 0; i < 11; i++) { for (var i = 0; i < 11; i++) {
@ -159,7 +156,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
} }
/// <summary> /// <summary>
/// Validate density when only one bound is are specified. /// Validate density when only one bound is are specified.
/// </summary> /// </summary>
/// <param name="mean">Mean value.</param> /// <param name="mean">Mean value.</param>
/// <param name="sdev">Standard deviation value.</param> /// <param name="sdev">Standard deviation value.</param>
@ -168,11 +165,11 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(0.0, 10.0, -10.0)] [TestCase(0.0, 10.0, -10.0)]
[TestCase(10.0, 100.0, 15.0)] [TestCase(10.0, 100.0, 15.0)]
[TestCase(-5.0, Double.PositiveInfinity, -5.0)] [TestCase(-5.0, Double.PositiveInfinity, -5.0)]
public void ValidateDensitySemiFinite(double mean, double sdev, double lowerBound) public void ValidateDensitySemiFinite(double mean, double sdev, double lowerBound)
{ {
var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound); var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound);
var normal = new Normal(mean, sdev); var normal = new Normal(mean, sdev);
for (var i = 0; i < 11; i++) for (var i = 0; i < 11; i++)
{ {
var x = i - 5.0; var x = i - 5.0;
double density; double density;
@ -180,7 +177,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
{ {
density = 0d; density = 0d;
} }
else else
{ {
var d = (mean - x) / sdev; var d = (mean - x) / sdev;
var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi); var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi);
@ -200,19 +197,19 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(0.0, 10.0, -10.0, 15.0)] [TestCase(0.0, 10.0, -10.0, 15.0)]
[TestCase(10.0, 100.0, 15.0, 100.0)] [TestCase(10.0, 100.0, 15.0, 100.0)]
[TestCase(-5.0, Double.PositiveInfinity, -5.0, 0.0)] [TestCase(-5.0, Double.PositiveInfinity, -5.0, 0.0)]
public void ValidateDensityFinite(double mean, double sdev, double lowerBound, double upperBound) public void ValidateDensityFinite(double mean, double sdev, double lowerBound, double upperBound)
{ {
var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound, upperBound); var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound, upperBound);
var normal = new Normal(mean, sdev); var normal = new Normal(mean, sdev);
for (var i = 0; i < 11; i++) for (var i = 0; i < 11; i++)
{ {
var x = i - 5.0; var x = i - 5.0;
double density; double density;
if (x < lowerBound || upperBound < x) if (x < lowerBound || upperBound < x)
{ {
density = 0d; density = 0d;
} }
else else
{ {
var d = (mean - x) / sdev; var d = (mean - x) / sdev;
var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi); var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi);
@ -224,7 +221,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
/// <summary> /// <summary>
/// Validate density log when no bounds are specified. Uses same /// Validate density log when no bounds are specified. Uses same
/// test cases as the Normal distribution as should be equivalent in this case. /// test cases as the Normal distribution as should be equivalent in this case.
/// </summary> /// </summary>
/// <param name="mean">Mean value.</param> /// <param name="mean">Mean value.</param>
@ -234,10 +231,10 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
[TestCase(0.0, 10.0)] [TestCase(0.0, 10.0)]
[TestCase(10.0, 100.0)] [TestCase(10.0, 100.0)]
[TestCase(-5.0, Double.PositiveInfinity)] [TestCase(-5.0, Double.PositiveInfinity)]
public void ValidateDensityLnNoBounds(double mean, double sdev) public void ValidateDensityLnNoBounds(double mean, double sdev)
{ {
var n = new TruncatedNormal(mean, sdev); var n = new TruncatedNormal(mean, sdev);
for (var i = 0; i < 11; i++) for (var i = 0; i < 11; i++)
{ {
var x = i - 5.0; var x = i - 5.0;
var d = (mean - x) / sdev; var d = (mean - x) / sdev;
@ -247,7 +244,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
} }
[Test] [Test]
public void CanSample() public void CanSample()
{ {
var truncatedNormal = new TruncatedNormal(5.0, 2.0, -10, 10.0); var truncatedNormal = new TruncatedNormal(5.0, 2.0, -10, 10.0);
truncatedNormal.Sample(); truncatedNormal.Sample();
@ -258,7 +255,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
/// Can sample sequence. /// Can sample sequence.
/// </summary> /// </summary>
[Test] [Test]
public void CanSampleSequence() public void CanSampleSequence()
{ {
var truncatedNormal = new TruncatedNormal(5.0, 2.0, -10, 10.0); var truncatedNormal = new TruncatedNormal(5.0, 2.0, -10, 10.0);
var ied = truncatedNormal.Samples(); var ied = truncatedNormal.Samples();

Write Preview
Loading…
Cancel
Save