public void should_return_no_percentiles_if_there_is_not_enough_data()
{
var builder = new PsquareHistogramAlgorithmBuilder();
var percentiles = builder.GetPercentiles().ToList();
percentiles.Count.ShouldEqual(0);
}
public void should_return_percentiles_for_given_data(Expectation expectation)
{
var builder = new PsquareHistogramAlgorithmBuilder(expectation.DesiredNumberOfBuckets);
foreach (var datum in expectation.Values.ToArray())
{
builder.AddValue(datum);
}
var percentiles = builder.GetPercentiles().ToList();
var roundedPercentiles = percentiles.Select(p => new Percentile(p.Rank, Math.Round(p.Value, 2))).ToList();
roundedPercentiles.ShouldBeEquivalentTo(expectation.ExpectedPercentiles, true);
}
public void should_work_with_random_uniform_distribution()
{
var random = new Random();
var builder = new PsquareHistogramAlgorithmBuilder();
for (var i = 0; i < 1000000; ++i)
{
builder.AddValue(random.NextDouble() * 100);
}
var percentiles = builder.GetPercentiles().ToList();
Console.WriteLine("P² histogram");
var squaredErrors = new List <double>();
for (var i = 0; i < 9; ++i)
{
var deltaToPercentile = Math.Abs(percentiles[i].Value - ((i + 1) * 10));
deltaToPercentile.ShouldBeLessThan(0.15);
Console.WriteLine("[" + percentiles[i].Rank + "] => " + percentiles[i].Value + " (" + deltaToPercentile + ")");
squaredErrors.Add(Math.Pow(deltaToPercentile, 2));
}
Console.WriteLine("MSE: " + squaredErrors.Average());
}