public void Test1()
{
// SplitMix64
var seed = 1234567ul;
Xoshiro256StarStar.SplitMix64(ref seed).Is(6457827717110365317ul);
Xoshiro256StarStar.SplitMix64(ref seed).Is(3203168211198807973ul);
Xoshiro256StarStar.SplitMix64(ref seed).Is(9817491932198370423ul);
Xoshiro256StarStar.SplitMix64(ref seed).Is(4593380528125082431ul);
Xoshiro256StarStar.SplitMix64(ref seed).Is(16408922859458223821ul);
var xo = new Xoshiro256StarStar(42);
DoubleToString(xo.NextDouble()).Is("0.0838629710598822");
DoubleToString(xo.NextDouble()).Is("0.3789802506626686");
DoubleToString(xo.NextDouble()).Is("0.6800434110281394");
DoubleToString(xo.NextDouble()).Is("0.9246929453253876");
DoubleToString(xo.NextDouble()).Is("0.9918039142821028");
string DoubleToString(double d) => d.ToString("F16");
xo.NextUInt64().Is(14199186830065750584ul);
xo.NextUInt64().Is(13267978908934200754ul);
xo.NextUInt64().Is(15679888225317814407ul);
xo.NextUInt64().Is(14044878350692344958ul);
xo.NextUInt64().Is(10760895422300929085ul);
}
public static void QuickStart_Xoshiro256StarStar()
{
// xoshiro256** is a pseudo-random number generator.
var xo = new Xoshiro256StarStar(42);
var ul = xo.NextUInt64(); // [0, 2^64-1]
var d = xo.NextDouble(); // [0,1)
var bytes = new byte[10];
xo.NextBytes(bytes);
}
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}");
}
public static void P3()
{
Xoshiro256StarStar rand = new Xoshiro256StarStar();
int RunProcess(int time)
{
int popsize = 1;
for (int t = 0; t < time; t++)
{
int newpopSize = popsize;
for (int i = 0; i < popsize; i++)
{
double val = rand.NextDouble();
if (val < 0.25)
{
newpopSize--;
}
if (val > 0.5)
{
newpopSize++;
}
if (val > 0.75)
{
newpopSize++;
}
}
popsize = newpopSize;
}
return(popsize);
}
int sum = 0;
int tests = 10000000;
/*
* for (int i = 0; i < tests; i++)
* {
* sum += RunProcess(5);
* }
* double avgAfter5 = sum *1.0 / tests;
*
* Console.WriteLine($"E(5) = {avgAfter5}");
*
* int count = 0;
* tests = 5000;
* int limit = 30;
* for (int i = 0; i < tests; i++)
* {
* if (RunProcess(limit) == 0) { count++; }
* }
* double proportionDead = count * 1.0 / tests;
*
* Console.WriteLine($"Pi_0 = {proportionDead}");
*/
tests = 100000000;
sum = 0;
double lambda1 = 1.0 / 11;
double lambda2 = 1.0 / 9;
double lambda3 = 1.0 / 8;
for (int i = 0; i < tests; i++)
{
double s1, s2, s3;
s1 = Exponential.Sample(rand, lambda1);
s2 = Exponential.Sample(rand, lambda2);
s3 = Exponential.Sample(rand, lambda3);
if (s1 > 10 && s2 > 10 && s3 > 10)
{
sum++;
}
}
double proportionLess = sum * 1.0 / tests;
Console.WriteLine($"Proportion = {proportionLess}");
//Console.WriteLine($"L1 / (L1 + L2) = {lambda1 / (lambda1 + lambda2)}");
Console.ReadLine();
}