public void should_work_with_random_uniform_distribution()
{
var random = new Random();
var desiredPercentiles = new double[] { 10, 20, 30, 40, 50, 60, 70, 80, 90 };
var builder = new ConstantErrorBasicCKMSBuilder(0.00001, desiredPercentiles);
var referenceBuilder = new NearestRankBuilder(desiredPercentiles);
for (var i = 0; i < 10000; ++i)
{
var value = random.NextDouble() * 100;
builder.AddValue(value);
referenceBuilder.AddValue(value);
}
var percentiles = builder.GetPercentiles().ToList();
var referencePercentiles = referenceBuilder.GetPercentiles().ToList();
Console.WriteLine("CKMS basic histogram");
var squaredErrors = new List <double>();
for (var i = 0; i < 9; ++i)
{
var deltaToPercentile = Math.Abs(percentiles[i].Value - referencePercentiles[i].Value);
Console.WriteLine("[" + percentiles[i].Rank + "] => " + percentiles[i].Value + " (" + deltaToPercentile + ")");
deltaToPercentile.ShouldBeLessThan(0.15);
squaredErrors.Add(Math.Pow(deltaToPercentile, 2));
}
Console.WriteLine("MSE: " + squaredErrors.Average());
}
public void should_work_with_sample_data(SampleFile sampleFile)
{
var builder = new NearestRankBuilder(new [] { 80, 90, 99, 99.9, 99.99, 99.999 });
foreach (var line in File.ReadAllLines(sampleFile.Filename))
{
var value = double.Parse(line, CultureInfo.InvariantCulture);
builder.AddValue(value);
}
builder.GetPercentiles().Select(p => (int)p.Value).ShouldBeEquivalentTo(sampleFile.ExpectedValues);
}
public void should_return_percentiles_for_given_data(Expectation expectation)
{
var builder = new NearestRankBuilder(expectation.DesiredPercentiles);
foreach (var datum in expectation.Values.Shuffle().ToArray())
{
builder.AddValue(datum);
}
var percentiles = builder.GetPercentiles().ToList();
percentiles.ShouldBeEquivalentTo(expectation.ExpectedPercentiles, true);
}
public void should_work_with_random_uniform_distribution()
{
var random = new Random();
var builder = new NearestRankBuilder();
for (var i = 0; i < 1000000; ++i)
{
builder.AddValue(random.NextDouble() * 100);
}
var percentiles = builder.GetPercentiles().ToList();
Console.WriteLine("Nearest rank");
var squaredErrors = new List <double>();
for (var i = 0; i < 9; ++i)
{
var deltaToPercentile = percentiles[i].Value - ((i + 1) * 10);
deltaToPercentile.ShouldBeLessThan(0.1);
Console.WriteLine("[" + percentiles[i].Rank + "] => " + percentiles[i].Value + " (" + deltaToPercentile + ")");
squaredErrors.Add(Math.Pow(deltaToPercentile, 2));
}
Console.WriteLine("MSE: " + squaredErrors.Average());
}
