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Updated GaussianDistributionTests.cs based off feedback from nsp

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This commit is contained in:
Jeff Moser 2010-04-19 07:39:24 -04:00
parent 67cada345e
commit 592a82b423
1 changed files with 47 additions and 5 deletions
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52
UnitTests/Numerics/GaussianDistributionTests.cs
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@ -9,6 +9,22 @@ namespace UnitTests.Numerics
{
private const double ErrorTolerance = 0.000001;
[Test]
public void CumulativeToTests()
{
// Verified with WolframAlpha
// (e.g. http://www.wolframalpha.com/input/?i=CDF%5BNormalDistribution%5B0%2C1%5D%2C+0.5%5D )
Assert.AreEqual(0.691462, GaussianDistribution.CumulativeTo(0.5), ErrorTolerance);
}
[Test]
public void AtTests()
{
// Verified with WolframAlpha
// (e.g. http://www.wolframalpha.com/input/?i=PDF%5BNormalDistribution%5B0%2C1%5D%2C+0.5%5D )
Assert.AreEqual(0.352065, GaussianDistribution.At(0.5), ErrorTolerance);
}
[Test]
public void MultiplicationTests()
{
@ -56,13 +72,39 @@ namespace UnitTests.Numerics
[Test]
public void LogProductNormalizationTests()
{
var m4s5 = new GaussianDistribution(4, 5);
var m6s7 = new GaussianDistribution(6, 7);
// Verified with Ralf Herbrich's F# implementation
var standardNormal = new GaussianDistribution(0, 1);
var lpn = GaussianDistribution.LogProductNormalization(standardNormal, standardNormal);
Assert.AreEqual(-1.2655121234846454, lpn, ErrorTolerance);
var product2 = m4s5 * m6s7;
var normConstant = 1.0 / (Math.Sqrt(2 * Math.PI) * product2.StandardDeviation);
var lpn = GaussianDistribution.LogProductNormalization(m4s5, m6s7);
var m1s2 = new GaussianDistribution(1, 2);
var m3s4 = new GaussianDistribution(3, 4);
var lpn2 = GaussianDistribution.LogProductNormalization(m1s2, m3s4);
Assert.AreEqual(-2.5168046699816684, lpn2, ErrorTolerance);
}
[Test]
public void LogRatioNormalizationTests()
{
// Verified with Ralf Herbrich's F# implementation
var m1s2 = new GaussianDistribution(1, 2);
var m3s4 = new GaussianDistribution(3, 4);
var lrn = GaussianDistribution.LogRatioNormalization(m1s2, m3s4);
Assert.AreEqual(2.6157405972171204, lrn, ErrorTolerance);
}
[Test]
public void AbsoluteDifferenceTests()
{
// Verified with Ralf Herbrich's F# implementation
var standardNormal = new GaussianDistribution(0, 1);
var absDiff = GaussianDistribution.AbsoluteDifference(standardNormal, standardNormal);
Assert.AreEqual(0.0, absDiff, ErrorTolerance);
var m1s2 = new GaussianDistribution(1, 2);
var m3s4 = new GaussianDistribution(3, 4);
var absDiff2 = GaussianDistribution.AbsoluteDifference(m1s2, m3s4);
Assert.AreEqual(0.4330127018922193, absDiff2, ErrorTolerance);
}
}
}