public void TestAccumulatorNumericStability()
{
/* NOTE: Statistically it is possible that this test fails even
* if everything works as expected. However, it's very unlikely to happen,
* and even more unlikely to happen in a series. */
Accumulator accumulator = new Accumulator();
NormalDistribution gaussian = new NormalDistribution();
// Test around 0, no stability issues expected
gaussian.SetDistributionParameters(0, 1);
for(int i = 0; i < 10000; i++)
{
accumulator.Add(gaussian.NextDouble());
}
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo((double) 0, 0.2), "Mean of (0,1)");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 1, 0.5), "Variance of (0,1)");
// Test around 10^9, potential stability issues
accumulator.Clear();
gaussian.SetDistributionParameters(1e+9, 1);
for(int i = 0; i < 10000; i++)
{
accumulator.Add(gaussian.NextDouble());
}
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo(1e+9, 0.2), "Mean of (1e+9,1)");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 1, 0.5), "Variance of (1e+9,1)");
}
private double[,] InitializeDataArray(int size)
{
double[,] data = new double[size, size];
NormalDistribution normalDist = new NormalDistribution(mean, delta);
for (int i = 0; i < size; ++i) {
for (int j = 0; j < size; ++j) {
data[i, j] = normalDist.NextDouble();
}
}
return data;
}
