public void Evaluate_NormalSample()
{
var sample = Enumerable
.Range(1, 10)
.Select(n => new { p = Functions.NormalDistribution(n, 2.87f, 5), n = n })
.SelectMany(x => Enumerable.Range(1, (int)(x.p * 100)).Select(n => (x.n).OutOf(10)))
.ToList()
.AsQueryable();
var hist = new Histogram(0.02f);
var kde = new KernelDensityEstimator(0.02f);
var histF = hist.Evaluate(sample);
var kdeF = kde.Evaluate(sample);
var stdDevMu = Functions.MeanStdDev(sample);
Console.WriteLine("Mean\t{0}", stdDevMu.Item1);
Console.WriteLine("StdDev\t{0}", stdDevMu.Item2);
var hRes = Enumerable.Range(1, 10).Select(n => new { n = n, p = histF(n.OutOf(10)) });
var kRes = Enumerable.Range(1, 10).Select(n => kdeF(n.OutOf(10))).Normalise().ToList();
int i = 0;
foreach (var x in hRes)
{
var kr = kRes[i++];
Console.WriteLine("{0}\t{1}\t{2}", x.n, x.p.Value, kr.Value);
Assert.That(Math.Round(x.p.Value, 4), Is.EqualTo(Math.Round(kr.Value, 4)));
}
}
