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)");
}
/// <summary>
/// Create a gaussian noise source with normally distributed amplitudes.
/// </summary>
/// <param name="uniformWhiteRandomSource">Uniform white random source.</param>
/// <param name="mean">mu-parameter of the normal distribution</param>
/// <param name="standardDeviation">sigma-parameter of the normal distribution</param>
public WhiteGaussianNoiseSource(
RandomSource uniformWhiteRandomSource,
double mean,
double standardDeviation
)
{
NormalDistribution gaussian = new NormalDistribution(uniformWhiteRandomSource);
gaussian.SetDistributionParameters(mean, standardDeviation);
_distribution = gaussian;
}
