public void Run()
{
var values = new NormalDistribution(mean: 20, stdDev: 2).Random(1).Next(20)
.Concat(new NormalDistribution(mean: 40, stdDev: 2).Random(2).Next(20))
.Concat(new NormalDistribution(mean: 60, stdDev: 2).Random(3).Next(20))
.ToArray();
double GetMedian(int count, int halfLife)
{
double[] weights = ExponentialDecaySequence.CreateFromHalfLife(halfLife).GenerateReverseArray(count);
var sample = new Sample(values.Take(count).ToList(), weights);
return(HarrellDavisQuantileEstimator.Instance.GetQuantile(sample, 0.5));
}
Console.WriteLine("Size WeightedMedian");
Console.WriteLine(" 1 3 5 10 // Half-life");
for (int i = 10; i < values.Length; i++)
{
double median1 = GetMedian(i, 1);
double median3 = GetMedian(i, 3);
double median5 = GetMedian(i, 5);
double median10 = GetMedian(i, 10);
string hint = i % 20 == 0 ? $" // Mean={(i / 20 + 1) * 20}" : "";
Console.WriteLine($"{i} {median1:0.00} {median3:0.00} {median5:0.00} {median10:0.00}{hint}");
}
}
public void HarrellDavisQuantileEstimatorWeightedTest1()
{
var random = new Random(42);
var distribution = new BetaDistribution(2, 10);
double[] data1 = distribution.Random(random).Next(10);
double[] data2 = data1.Select(x => x + 100).ToArray();
double[] data = data1.Concat(data2).ToArray();
var samples = new List <Sample> {
new Sample(data1)
};
for (int i = 1; i <= 40; i++)
{
samples.Add(new Sample(data, ExponentialDecaySequence.CreateFromHalfLife(i).GenerateArray(data.Length)));
}
samples.Add(new Sample(data));
var medians = samples.Select(s => HarrellDavisQuantileEstimator.Instance.GetMedian(s)).ToList();
for (int i = 0; i < medians.Count; i++)
{
Output.WriteLine($"Median[{i}] = {medians[i]:N9}");
}
for (int i = 0; i < medians.Count - 1; i++)
{
Assert.True(medians[i] < medians[i + 1]);
}
}
public void WeightedSampleTest()
{
var random = new Random(42);
var values = new GumbelDistribution().Random(random).Next(30).Concat(
new GumbelDistribution(10).Random(random).Next(30)).ToList();
double[] weights = ExponentialDecaySequence.CreateFromHalfLife(10).GenerateReverseArray(values.Count);
var sample = new Sample(values, weights);
var simpleModalityData = detector.DetectModes(values);
output.WriteLine("SimpleModalityData.Modes:");
output.WriteLine(Present(simpleModalityData));
output.WriteLine();
output.WriteLine(simpleModalityData.DensityHistogram.Present());
output.WriteLine("------------------------------");
var weightedModalityData = detector.DetectModes(sample);
output.WriteLine("WeightedModalityData.Modes:");
output.WriteLine(Present(weightedModalityData));
output.WriteLine();
output.WriteLine(weightedModalityData.DensityHistogram.Present());
Assert.Equal(2, simpleModalityData.Modality);
Assert.Equal(1, weightedModalityData.Modality);
}
public void ExponentialDecayHalfLifeGetTest(int halfLife, int index, double expectedValue)
{
var sequence = ExponentialDecaySequence.CreateFromHalfLife(halfLife);
double actualValue1 = sequence.GetValue(index);
Assert.Equal(expectedValue, actualValue1, equalityComparer);
double actualValue2 = sequence.GenerateEnumerable().Skip(index).First();
Assert.Equal(expectedValue, actualValue2, equalityComparer);
}
public void ExponentialDecayNormalizationTest(int count, int initialValue, double decayConstant)
{
var values = new ExponentialDecaySequence(initialValue, decayConstant).GenerateArray(count, normalize: true);
Assert.Equal(1.0, values.Sum(), equalityComparer);
}
