public void CanCreateSymmetricDirichlet()
{
var d = new Dirichlet(0.3, 5);
for (var i = 0; i < 5; i++)
{
Assert.AreEqual(0.3, d.Alpha[i]);
}
}
public void CanGetAlpha()
{
Dirichlet d = new Dirichlet(0.3, 10);
double[] alpha = new double[10];
for (int i = 0; i < 10; i++)
{
Assert.AreEqual(0.3, d.Alpha[i]);
}
}
public void CanCreateDirichlet()
{
var alpha = new double[10];
for (var i = 0; i < 10; i++)
{
alpha[i] = i;
}
var d = new Dirichlet(alpha);
for (var i = 0; i < 5; i++)
{
Assert.AreEqual(i, d.Alpha[i]);
}
}
public void ValidateDensity(double[] x, double res)
{
var d = new Dirichlet(new[] { 0.1, 0.3, 0.5, 0.8 });
AssertHelpers.AlmostEqualRelative(res, d.Density(x), 12);
}
public void ValidateVariance()
{
var alpha = new double[10];
var sum = 0.0;
for (var i = 0; i < 10; i++)
{
alpha[i] = i;
sum += i;
}
var d = new Dirichlet(alpha);
for (var i = 0; i < 10; i++)
{
AssertHelpers.AlmostEqualRelative(i * (sum - i) / (sum * sum * (sum + 1.0)), d.Variance[i], 15);
}
}
public void ValidateMean()
{
var d = new Dirichlet(0.3, 5);
for (var i = 0; i < 5; i++)
{
AssertHelpers.AlmostEqualRelative(0.3 / 1.5, d.Mean[i], 15);
}
}
public void CanSetRandomSource(int i)
{
Dirichlet d = new Dirichlet(0.3, 5);
d.RandomSource = new Random();
}
public void CanSampleSingularDirichlet()
{
var d = new Dirichlet(new[] { 2.0, 1.0, 0.0, 3.0 });
d.Sample();
}
public void ValidateEntropy(double[] x)
{
var d = new Dirichlet(x);
var sum = x.Sum(t => (t - 1) * SpecialFunctions.DiGamma(t));
var res = SpecialFunctions.GammaLn(x.Sum()) + ((x.Sum() - x.Length) * SpecialFunctions.DiGamma(x.Sum())) - sum;
AssertHelpers.AlmostEqualRelative(res, d.Entropy, 12);
}
public void CanSampleSymmetricDirichlet()
{
Dirichlet d = new Dirichlet(1.0, 5);
double[] s = d.Sample();
}
public void CanSampleSingularDirichlet()
{
Dirichlet d = new Dirichlet(new double[] {2.0, 1.0, 0.0, 3.0});
double[] s = d.Sample();
}
public void ValidateVariance()
{
double[] alpha = new double[10];
double sum = 0.0;
for (int i = 0; i < 10; i++)
{
alpha[i] = i;
sum += i;
}
Dirichlet d = new Dirichlet(alpha);
for (int i = 0; i < 10; i++)
{
AssertHelpers.AlmostEqual(i * (sum - i) / (sum * sum * (sum + 1.0)), d.Variance[i], 15);
}
}
public void ValidateMean()
{
Dirichlet d = new Dirichlet(0.3, 5);
for (int i = 0; i < 5; i++)
{
AssertHelpers.AlmostEqual(0.3/1.5, d.Mean[i], 15);
}
}
public void FailSetRandomSourceWithNullReference(int i)
{
Dirichlet d = new Dirichlet(0.3, 5);
d.RandomSource = null;
}
public void FailCreateDirichlet(double alpha)
{
Dirichlet d = new Dirichlet(alpha, 5);
}
public void ValidateDensityLn(double[] x)
{
var d = new Dirichlet(new[] { 0.1, 0.3, 0.5, 0.8 });
AssertHelpers.AlmostEqualRelative(d.DensityLn(x), Math.Log(d.Density(x)), 12);
}
public void ValidateBetaSpecialCaseDensityLn(double x)
{
var d = new Dirichlet(new[] { 0.1, 0.3 });
var beta = new Beta(0.1, 0.3);
AssertHelpers.AlmostEqualRelative(d.DensityLn(new[] { x }), beta.DensityLn(x), 10);
}
public void HasRandomSourceEvenAfterSetToNull()
{
var d = new Dirichlet(0.3, 5);
Assert.DoesNotThrow(() => d.RandomSource = null);
Assert.IsNotNull(d.RandomSource);
}
public void CanSampleSymmetricDirichlet()
{
var d = new Dirichlet(1.0, 5);
d.Sample();
}
public void CanGetDimension()
{
var d = new Dirichlet(0.3, 10);
Assert.AreEqual(10, d.Dimension);
}
public void CanGetAlpha()
{
var d = new Dirichlet(0.3, 10);
for (var i = 0; i < 10; i++)
{
Assert.AreEqual(0.3, d.Alpha[i]);
}
}
public void CanSetAlpha()
{
var d = new Dirichlet(0.3, 10);
var alpha = new double[10];
for (var i = 0; i < 10; i++)
{
alpha[i] = i;
}
d.Alpha = alpha;
}
public void HasRandomSource()
{
var d = new Dirichlet(0.3, 5);
Assert.IsNotNull(d.RandomSource);
}
public void CanSetAlpha()
{
Dirichlet d = new Dirichlet(0.3, 10);
double[] alpha = new double[10];
for (int i = 0; i < 10; i++)
{
alpha[i] = i;
}
d.Alpha = alpha;
}
