Ejemplo n.º 1
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 public CentralLimitMersenneTwisterGaussianRng(MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_CentralLimitMersenneTwisterGaussianRng(MersenneTwisterUniformRng.getCPtr(rng)), true)
 {
     if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
     {
         throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
     }
 }
Ejemplo n.º 2
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 public MersenneTwisterUniformRsg(uint dimensionality, MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_MersenneTwisterUniformRsg__SWIG_0(dimensionality, MersenneTwisterUniformRng.getCPtr(rng)), true)
 {
     if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
     {
         throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
     }
 }
Ejemplo n.º 3
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 public MoroInvCumulativeMersenneTwisterGaussianRng(MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_MoroInvCumulativeMersenneTwisterGaussianRng(MersenneTwisterUniformRng.getCPtr(rng)), true)
 {
     if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
     {
         throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
     }
 }
Ejemplo n.º 4
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        public void testIncrementalStatistics()
        {
            // Testing incremental statistics

            MersenneTwisterUniformRng mt = new MersenneTwisterUniformRng(42);

            IncrementalStatistics stat = new IncrementalStatistics();

            for (int i = 0; i < 500000; ++i)
            {
                double x = 2.0 * (mt.nextReal() - 0.5) * 1234.0;
                double w = mt.nextReal();
                stat.add(x, w);
            }

            if (stat.samples() != 500000)
            {
                QAssert.Fail("stat.samples()  (" + stat.samples() + ") can not be reproduced against cached result (" + 500000 + ")");
            }

            TEST_INC_STAT(stat.weightSum(), 2.5003623600676749e+05);
            TEST_INC_STAT(stat.mean(), 4.9122325964293845e-01);
            TEST_INC_STAT(stat.variance(), 5.0706503959683329e+05);
            TEST_INC_STAT(stat.standardDeviation(), 7.1208499464378076e+02);
            TEST_INC_STAT(stat.errorEstimate(), 1.0070402569876076e+00);
            TEST_INC_STAT(stat.skewness(), -1.7360169326720038e-03);
            TEST_INC_STAT(stat.kurtosis(), -1.1990742562085395e+00);
            TEST_INC_STAT(stat.min(), -1.2339945045639761e+03);
            TEST_INC_STAT(stat.max(), 1.2339958308008499e+03);
            TEST_INC_STAT(stat.downsideVariance(), 5.0786776146975247e+05);
            TEST_INC_STAT(stat.downsideDeviation(), 7.1264841364431061e+02);


            // This is a test for numerical stability, actual implementation fails

            //InverseCumulativeRng<MersenneTwisterUniformRng,InverseCumulativeNormal> normal_gen =
            //   new InverseCumulativeRng<MersenneTwisterUniformRng, InverseCumulativeNormal>(mt);

            //IncrementalStatistics stat2 = new IncrementalStatistics();

            //for (int i = 0; i < 500000; ++i)
            //{
            //   double x = normal_gen.next().value * 1E-1 + 1E8;
            //   double w = 1.0;
            //   stat2.add(x, w);
            //}

            //double tol = 1E-5;

            //if(Math.Abs( stat2.variance() - 1E-2 ) > tol)
            //   QAssert.Fail("variance (" + stat2.variance() + ") out of expected range " + 1E-2 + " +- " + tol);
        }
Ejemplo n.º 5
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        public void testSpareMatrixReference()
        {
            int rows      = 10;
            int columns   = 10;
            int nMatrices = 5;
            int nElements = 50;

            MersenneTwisterUniformRng rng = new MersenneTwisterUniformRng(1234);

            SparseMatrix        expected = new SparseMatrix(rows, columns);
            List <SparseMatrix> refs     = new List <SparseMatrix>();

            for (int i = 0; i < nMatrices; ++i)
            {
                SparseMatrix m = new SparseMatrix(rows, columns);
                for (int j = 0; j < nElements; ++j)
                {
                    int row    = Convert.ToInt32(rng.next().value *rows);
                    int column = Convert.ToInt32(rng.next().value *columns);

                    double value = rng.next().value;
                    m[row, column]        += value;
                    expected[row, column] += value;
                }

                refs.Add(m);
            }

            SparseMatrix calculated = refs.accumulate(1, refs.Count, refs[0], (a, b) => a + b);

            for (int i = 0; i < rows; ++i)
            {
                for (int j = 0; j < columns; ++j)
                {
                    if (Math.Abs(calculated[i, j] - expected[i, j]) > 100 * Const.QL_EPSILON)
                    {
                        QAssert.Fail("Error using sparse matrix references in " +
                                     "Element (" + i + ", " + j + ")" +
                                     "\n expected  : " + expected[i, j] +
                                     "\n calculated: " + calculated[i, j]);
                    }
                }
            }
        }
Ejemplo n.º 6
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        public void testQRSolve()
        {
            // Testing QR solve...
            setup();

            double tol = 1.0e-12;
            MersenneTwisterUniformRng rng = new MersenneTwisterUniformRng(1234);
            Matrix bigM = new Matrix(50, 100, 0.0);

            for (int i = 0; i < Math.Min(bigM.rows(), bigM.columns()); ++i)
            {
                bigM[i, i] = i + 1.0;
            }
            Matrix[] testMatrices = { M1, M2,                   M3, Matrix.transpose(M3),
                                      M4, Matrix.transpose(M4), M5, I,                   M7,bigM, Matrix.transpose(bigM) };

            for (int j = 0; j < testMatrices.Length; j++)
            {
                Matrix A = testMatrices[j];
                Vector b = new Vector(A.rows());

                for (int k = 0; k < 10; ++k)
                {
                    for (int i = 0; i < b.Count; ++i)
                    {
                        b[i] = rng.next().value;
                    }
                    Vector x = MatrixUtilities.qrSolve(A, b, true);

                    if (A.columns() >= A.rows())
                    {
                        if (norm(A * x - b) > tol)
                        {
                            QAssert.Fail("A*x does not match vector b (norm = "
                                         + norm(A * x - b) + ")");
                        }
                    }
                    else
                    {
                        // use the SVD to calculate the reference values
                        int    n  = A.columns();
                        Vector xr = new Vector(n, 0.0);

                        SVD    svd       = new SVD(A);
                        Matrix V         = svd.V();
                        Matrix U         = svd.U();
                        Vector w         = svd.singularValues();
                        double threshold = n * Const.QL_EPSILON;

                        for (int i = 0; i < n; ++i)
                        {
                            if (w[i] > threshold)
                            {
                                double u    = 0;
                                int    zero = 0;
                                for (int kk = 0; kk < U.rows(); kk++)
                                {
                                    u += (U[kk, i] * b[zero++]) / w[i];
                                }

                                for (int jj = 0; jj < n; ++jj)
                                {
                                    xr[jj] += u * V[jj, i];
                                }
                            }
                        }

                        if (norm(xr - x) > tol)
                        {
                            QAssert.Fail("least square solution does not match (norm = "
                                         + norm(x - xr) + ")");
                        }
                    }
                }
            }
        }
Ejemplo n.º 7
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 public MersenneTwisterUniformRsg(uint dimensionality, MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_MersenneTwisterUniformRsg(dimensionality, MersenneTwisterUniformRng.getCPtr(rng)), true) {
   if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
 }
 public MoroInvCumulativeMersenneTwisterGaussianRng(MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_MoroInvCumulativeMersenneTwisterGaussianRng(MersenneTwisterUniformRng.getCPtr(rng)), true) {
   if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
 }
Ejemplo n.º 9
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 internal static global::System.Runtime.InteropServices.HandleRef getCPtr(MersenneTwisterUniformRng obj) {
   return (obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.swigCPtr;
 }
 internal static global::System.Runtime.InteropServices.HandleRef getCPtr(MersenneTwisterUniformRng obj)
 {
     return((obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.swigCPtr);
 }
Ejemplo n.º 11
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 public ModFourthDeJong()
 {
     uniformRng_ = new MersenneTwisterUniformRng(4711);
 }
 public CentralLimitMersenneTwisterGaussianRng(MersenneTwisterUniformRng rng) : this(NQuantLibcPINVOKE.new_CentralLimitMersenneTwisterGaussianRng(MersenneTwisterUniformRng.getCPtr(rng)), true) {
   if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
 }