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);
    }
Exemplo n.º 2
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    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);
    }
Exemplo n.º 3
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        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]}");
                }
            }
        }
Exemplo n.º 4
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        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}");
        }
Exemplo n.º 5
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        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();
        }