public void ConstructorTest()
{
// Valid input
{
var indexes = IndexCollection.Default(lastIndex: 5);
var randomIndexPermutation = new
RandomIndexPermutation(indexes: indexes);
int i = 0;
foreach (var index in randomIndexPermutation.Indexes)
{
Assert.AreEqual(
expected: indexes[i],
actual: index);
i++;
}
}
// indexes is null
{
IndexCollection indexes = null;
ArgumentExceptionAssert.Throw(
() =>
{
new RandomIndexPermutation(
indexes: indexes);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "indexes");
}
}
/// <summary>
/// Tests that method
/// <see cref="RandomIndexPermutation.Next"/>
/// terminates successfully as expected.
/// </summary>
/// <param name="indexes">
/// The indexes to permute.
/// </param>
/// <param name="numberOfRandomPermutations">
/// The number of permutations to draw.
/// </param>
/// <param name="criticalValue">
/// A quantile of the chi-squared distribution with a number of
/// degrees of freedom equal to the <see cref="IndexCollection.Count"/>
/// of <paramref name="indexes"/>
/// minus <c>1</c>.
/// To serve as the critical value for the Pearson's
/// chi-squared test whose null hypothesis assume that the
/// the distinct possible permutations
/// are equiprobable.
/// </param>
/// <param name="delta">The required accuracy.
/// Defaults to <c>.01</c>.</param>
public static void Succeed(
IndexCollection indexes,
int numberOfRandomPermutations,
double criticalValue,
double delta = .01)
{
var randomPermutation = new RandomIndexPermutation(indexes);
// Generate permutations
var permutations = new IndexCollection[numberOfRandomPermutations];
for (int i = 0; i < numberOfRandomPermutations; i++)
{
permutations[i] = randomPermutation.Next();
}
// Check the number of distinct generated permutations
var permutationIdentifiers =
IndexCollection.Default(numberOfRandomPermutations - 1);
var actualDistinctPermutations =
IndexPartition.Create(
permutationIdentifiers,
(i) => { return(permutations[i]); });
int numberOfActualDistinctPermutations =
actualDistinctPermutations.Count;
Assert.AreEqual(
expected: SpecialFunctions.Factorial(indexes.Count),
actual: numberOfActualDistinctPermutations);
// Compute the actual permutation probabilities
DoubleMatrix actualPermutationProbabilities =
DoubleMatrix.Dense(
numberOfActualDistinctPermutations, 1);
int j = 0;
foreach (var identifier in actualDistinctPermutations.Identifiers)
{
actualPermutationProbabilities[j] =
(double)actualDistinctPermutations[identifier].Count
/
(double)numberOfRandomPermutations;
j++;
}
// Check that the Chebyshev Inequality holds true
// for each permutation probability
var expectedPermutationProbabilities =
DoubleMatrix.Dense(
numberOfActualDistinctPermutations,
1,
1.0
/
(double)numberOfActualDistinctPermutations);
for (int i = 0; i < numberOfActualDistinctPermutations; i++)
{
ProbabilityDistributionTest.CheckChebyshevInequality(
new BernoulliDistribution(expectedPermutationProbabilities[i]),
actualPermutationProbabilities[i],
numberOfRandomPermutations,
delta);
}
// Check how good the actual permutation probabilities fit
// the expected ones
ProbabilityDistributionTest.CheckGoodnessOfFit(
expectedPermutationProbabilities,
actualPermutationProbabilities,
criticalValue);
}
