public static WrappedDistribution[] WrapDistributions(IContinuousDistribution[] distributions, double[] lowerBounds, double[] upperBounds)
{
WrappedDistribution[] result = new WrappedDistribution[distributions.Length];
for (int i = 0; i < distributions.Length; i++)
{
result[i] = new WrappedDistribution(distributions[i], lowerBounds[i], upperBounds[i]);
}
return(result);
}
public static void TestQuantileTrap()
{
Xoshiro256StarStar rand = new Xoshiro256StarStar(8675309);
const int numberOfDists = 10;
//const double meanOfNormals = 50;
//const double stdDevOfNormals = 0.002;
double Shape() => 2 *rand.NextDouble() - 1;
double Scale() => 0.002 *rand.NextDouble() + 0;
double Location() => 180 *rand.NextDouble();
IDistributionWrapper[] dists = new IDistributionWrapper[numberOfDists];
for (int i = 0; i < dists.Length; i++)
{
//dists[i] = new WrappedDistribution(new Normal(rand.NextDouble() * meanOfNormals * 2, 0 + Math.Abs(rand.NextDouble() * stdDevOfNormals)), -100, 200); // Bounds are unused here
dists[i] = new WrappedDistribution(new GEV(Location(), Scale(), Shape(), rand), -100, 100);
}
double[] exact = DiscardProbabilityComputation.ComplementsTrapezoid(dists, 50000);
Console.WriteLine("Exact:");
for (int i = 0; i < exact.Length; i++)
{
Console.WriteLine($"{i}: {dists[i].GetWrappedDistribution()} 1-P(D_i) = {exact[i]}");
}
exact = DiscardProbabilityComputation.ComplementsMonteCarloMaximizing(dists);
Console.WriteLine("MC:");
for (int i = 0; i < exact.Length; i++)
{
Console.WriteLine($"{i}: {dists[i].GetWrappedDistribution()} 1-P(D_i) = {exact[i]}");
}
double[] est;
int[] its = new int[] { 10, 20, 30, 40, 50, 75, 100, 200, 500, 1000, 2000, 20000 };
for (int i = 0; i < its.Length; i++)
{
int size = its[i];
est = DiscardProbabilityComputation.ComplementsQuantileTrapRule(dists, size);
Console.WriteLine($"Size {size}:");
for (int j = 0; j < est.Length; j++)
{
Console.WriteLine($"{j}: {dists[j].GetWrappedDistribution()} 1-P(D_i) = {est[j]}");
}
}
}
public static void TestGEVComplementComputations()
{
double ep = Math.Pow(2, -50);
double complementEp = 1.0 - ep;
int testSize = 20;
//GEV[] dists = new GEV[] { new GEV(0,200,-1), new GEV(0,100,-1) };
GEV[] dists = new GEV[testSize];
Random rand = new Xoshiro256StarStar(8675309);
for (int i = 0; i < dists.Length; i++)
{
dists[i] = new GEV(rand.NextDouble(), rand.NextDouble(), -rand.NextDouble(), rand);
}
IDistributionWrapper[] wrappedDists = new IDistributionWrapper[dists.Length];
for (int i = 0; i < dists.Length; i++)
{
wrappedDists[i] = new WrappedDistribution(dists[i], dists[i].InverseCumulativeDistribution(ep), dists[i].InverseCumulativeDistribution(complementEp));
}
double[] complements = DiscardProbabilityComputation.ComplementsClenshawCurtisAutomatic(wrappedDists);
double[] complemetnsTrap = DiscardProbabilityComputation.ComplementsTrapezoid(wrappedDists, 10000);
double[] mcComplements = DiscardProbabilityComputation.ComplementsMonteCarlo(wrappedDists, iterations: 10000000);
double totalc = 0;
double totalmc = 0;
double totalTrap = 0;
for (int i = 0; i < complements.Length; i++)
{
GEV dist = dists[i];
Program.logger.WriteLine($"Distribution Scale: {dist.scale} Loc {dist.location} Shape {dist.shape} " +
$"1-P(D) {complements[i]} MC {mcComplements[i]} Trap {complemetnsTrap[i]}");
totalc += complements[i];
totalmc += mcComplements[i];
totalTrap += complemetnsTrap[i];
}
Program.logger.WriteLine($"Total probability: {totalc} Total by MC: {totalmc} Total by Trap 10k: {totalTrap}");
}