public void MaxTest2()
{
foreach (double max in new[] { 0.0, 2.0 })
{
double oldm = double.NaN;
double oldv = double.NaN;
for (int i = 0; i < 300; i++)
{
Gaussian a = new Gaussian(System.Math.Pow(10, i), 177);
Gaussian to_a = MaxGaussianOp.AAverageConditional(max, a, 0);
Gaussian to_b = MaxGaussianOp.BAverageConditional(max, 0, a);
Assert.Equal(to_a, to_b);
if (max == 0)
{
Gaussian to_a2 = IsPositiveOp.XAverageConditional(false, a);
double error = System.Math.Max(MMath.AbsDiff(to_a.MeanTimesPrecision, to_a2.MeanTimesPrecision, double.Epsilon),
MMath.AbsDiff(to_a.Precision, to_a2.Precision, double.Epsilon));
//Trace.WriteLine($"{a} {to_a} {to_a2} {error}");
Assert.True(error < 1e-12);
}
//else Trace.WriteLine($"{a} {to_a}");
double m, v;
to_a.GetMeanAndVariance(out m, out v);
if (!double.IsNaN(oldm))
{
Assert.True(v <= oldv);
double olddiff = System.Math.Abs(max - oldm);
double diff = System.Math.Abs(max - m);
Assert.True(diff <= olddiff);
}
oldm = m;
oldv = v;
}
}
}
// Test inference on a model where precision is scaled.
internal void GammaProductTest()
{
for (int i = 0; i <= 20; i++)
{
double minutesPlayed = System.Math.Pow(0.1, i);
if (i == 20)
{
minutesPlayed = 0;
}
var EventCountMean_F = Gaussian.PointMass(0);
var EventCountPrecision_F = GammaRatioOp.RatioAverageConditional(Gamma.PointMass(1), minutesPlayed);
var realCount_F = GaussianOp_PointPrecision.SampleAverageConditional(EventCountMean_F, EventCountPrecision_F);
var realCount_use_B = MaxGaussianOp.BAverageConditional(0.0, 0.0, realCount_F);
var EventCountPrecision_B = GaussianOp_PointPrecision.PrecisionAverageConditional(realCount_use_B, EventCountMean_F, EventCountPrecision_F);
var EventsPerMinutePrecision_B = GammaRatioOp.AAverageConditional(EventCountPrecision_B, minutesPlayed);
Console.WriteLine($"realCount_use_B = {realCount_use_B}, EventCountPrecision_B = {EventCountPrecision_B}, EventsPerMinutePrecision_B = {EventsPerMinutePrecision_B}");
}
}