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Bug fixes in Bernoulli distribution. 

Signed-off-by: jvangael <jurgen.vangael@gmail.com>
pull/2/head
jvangael 17 years ago
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2 changed files with 40 additions and 45 deletions
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  1. 6
      src/Numerics/Distributions/Discrete/Bernoulli.cs
  2. 79
      src/UnitTests/DistributionTests/Discrete/BernoulliTests.cs

6
src/Numerics/Distributions/Discrete/Bernoulli.cs
View File

@ -37,7 +37,7 @@ namespace MathNet.Numerics.Distributions
/// p specifies the probability that a 1 is generated.
/// </summary>
/// <remarks><para>The distribution will use the <see cref="System.Random"/> by default.
/// Users can set the random number generator by using the <see cref="RandomNumberGenerator"/> property.</para>
/// Users can set the random number generator by using the <see cref="RandomSource"/> property.</para>
/// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
/// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
/// to false, all parameter checks can be turned off.</para></remarks>
@ -198,11 +198,11 @@ namespace MathNet.Numerics.Distributions
/// <returns>the cumulative density at <paramref name="x"/>.</returns>
public double CumulativeDistribution(double x)
{
if (x < 0)
if (x < 0.0)
{
return 0.0;
}
if (x == 0)
else if (x < 1.0)
{
return 1.0 - _p;
}

79
src/UnitTests/DistributionTests/Discrete/BernoulliTests.cs
View File

@ -57,7 +57,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
[Row(Double.NaN)]
[Row(-1.0)]
[Row(2.0)]
public void NormalCreateFailsWithBadParameters(double p)
public void BernoulliCreateFailsWithBadParameters(double p)
{
var bernoulli = new Bernoulli(p);
}
@ -66,7 +66,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateToString()
{
var b = new Bernoulli(0.3);
AssertEx.AreEqual<string>("Bernoulli(P = 0.3)", n.ToString());
AssertEx.AreEqual<string>("Bernoulli(P = 0.3)", b.ToString());
}
[Test]
@ -97,7 +97,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateEntropy(double p)
{
var b = new Bernoulli(p);
AssertEx.AreEqual<double>((1.0 - p) * Math.Log(1.0 - p) + p * Math.Log(p), b.Entropy);
AssertHelpers.AlmostEqual(-(1.0 - p) * Math.Log(1.0 - p) - p * Math.Log(p), b.Entropy, 14);
}
[Test]
@ -107,7 +107,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateSkewness(double p)
{
var b = new Bernoulli(p);
AssertEx.AreEqual<double>((1.0 - 2.0 * p) / Math.Sqrt(p * (1.0 - p)), n.Skewness);
AssertEx.AreEqual<double>((1.0 - 2.0 * p) / Math.Sqrt(p * (1.0 - p)), b.Skewness);
}
[Test]
@ -117,7 +117,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateMode(double p, double m)
{
var b = new Bernoulli(p);
AssertEx.AreEqual<double>(mean, n.Mode);
AssertEx.AreEqual<double>(m, b.Mode);
}
[Test]
@ -125,61 +125,56 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateMedian()
{
var b = new Bernoulli(0.3);
double m = b.Median;
}
[Test]
public void ValidateMinimum()
{
var b = new Bernoulli(0.3);
AssertEx.AreEqual<double>(0.0, n.Minimum);
AssertEx.AreEqual<double>(0.0, b.Minimum);
}
[Test]
public void ValidateMaximum()
{
var b = new Bernoulli(0.3);
AssertEx.AreEqual<double>(1.0, n.Maximum);
AssertEx.AreEqual<double>(1.0, b.Maximum);
}
[Test]
[Row(0.0, -1.0, 0.0)]
[Row(0.0, 0.0, 1.0)]
[Row(0.0, 0.5, 0.0)]
[Row(0.0, 1.0, 0.0)]
[Row(0.0, 2.0, 0.0)]
[Row(0.3, -1.0, 0.0)]
[Row(0.3, 0.0, 0.7)]
[Row(0.3, 0.5, 0.0)]
[Row(0.3, 1.0, 0.3)]
[Row(0.3, 2.0, 0.0)]
[Row(1.0, -1.0, 0.0)]
[Row(1.0, 0.0, 0.0)]
[Row(1.0, 0.5, 0.0)]
[Row(1.0, 1.0, 1.0)]
[Row(1.0, 2.0, 0.0)]
public void ValidateProbability(double p, double x, double d)
[Row(0.0, -1, 0.0)]
[Row(0.0, 0, 1.0)]
[Row(0.0, 1, 0.0)]
[Row(0.0, 2, 0.0)]
[Row(0.3, -1, 0.0)]
[Row(0.3, 0, 0.7)]
[Row(0.3, 1, 0.3)]
[Row(0.3, 2, 0.0)]
[Row(1.0, -1, 0.0)]
[Row(1.0, 0, 0.0)]
[Row(1.0, 1, 1.0)]
[Row(1.0, 2, 0.0)]
public void ValidateProbability(double p, int x, double d)
{
var b = new Bernoulli(p);
AssertEx.AreEqual(d, b.Probability(x));
}
[Test]
[Row(0.0, -1.0, Double.NegativeInfinity)]
[Row(0.0, 0.0, 0.0)]
[Row(0.0, 0.5, Double.NegativeInfinity)]
[Row(0.0, 1.0, Double.NegativeInfinity)]
[Row(0.0, 2.0, Double.NegativeInfinity)]
[Row(0.3, -1.0, Double.NegativeInfinity)]
[Row(0.3, 0.0, -0.35667494393873244235395440410727451457180907089949815)]
[Row(0.3, 0.5, Double.NegativeInfinity)]
[Row(0.3, 1.0, -1.2039728043259360296301803719337238685164245381839102)]
[Row(0.3, 2.0, Double.NegativeInfinity)]
[Row(1.0, -1.0, Double.NegativeInfinity)]
[Row(1.0, 0.0, Double.NegativeInfinity)]
[Row(1.0, 0.5, Double.NegativeInfinity)]
[Row(1.0, 1.0, 0.0)]
[Row(1.0, 2.0, Double.NegativeInfinity)]
public void ValidateProbabilityLn(double p, double x, double dln)
[Row(0.0, -1, Double.NegativeInfinity)]
[Row(0.0, 0, 0.0)]
[Row(0.0, 1, Double.NegativeInfinity)]
[Row(0.0, 2, Double.NegativeInfinity)]
[Row(0.3, -1, Double.NegativeInfinity)]
[Row(0.3, 0, -0.35667494393873244235395440410727451457180907089949815)]
[Row(0.3, 1, -1.2039728043259360296301803719337238685164245381839102)]
[Row(0.3, 2, Double.NegativeInfinity)]
[Row(1.0, -1, Double.NegativeInfinity)]
[Row(1.0, 0, Double.NegativeInfinity)]
[Row(1.0, 1, 0.0)]
[Row(1.0, 2, Double.NegativeInfinity)]
public void ValidateProbabilityLn(double p, int x, double dln)
{
var b = new Bernoulli(p);
AssertEx.AreEqual(dln, b.ProbabilityLn(x));
@ -215,14 +210,14 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
[Test]
public void CanSample()
{
var n = new Bernoulli();
var n = new Bernoulli(0.3);
var d = n.Sample();
}
[Test]
public void CanSampleSequence()
{
var n = new Bernoulli();
var n = new Bernoulli(0.3);
var ied = n.Samples();
var e = ied.Take(5).ToArray();
}
@ -246,7 +241,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
public void ValidateCumulativeDistribution(double p, double x, double cdf)
{
var b = new Bernoulli(p);
AssertEx.AreEqual(cdf, n.CumulativeDistribution(x));
AssertEx.AreEqual(cdf, b.CumulativeDistribution(x));
}
}
}
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