示例#1
0
        public void Array2DArrayEstimatorTest()
        {
            // Create the estimator
            // element type is double[]
            //Estimator<GaussianArray2DArray> est = null;
            int length1 = ga2aArrayOfDist.GetLength(0);
            int length2 = ga2aArrayOfDist.GetLength(1);
            Array2DEstimator <GaussianArrayEstimator, GaussianArray2DArray, GaussianArray, double[]> est =
                new Array2DEstimator <GaussianArrayEstimator, GaussianArray2DArray, GaussianArray, double[]>(
                    Utilities.Util.ArrayInit(length1, length2, (i, j) =>
                                             new GaussianArrayEstimator(Utilities.Util.ArrayInit(ga2aArrayOfDist[i, j].Length, k => new GaussianEstimator()))
                                             ));

            // Add some samples to the estimator
            int nSamples = 5;

            // Create a sample an mean variable of the right structure
            double[, ][] mean = (double[, ][]) JaggedArray.ConvertToNew(
                ga2aArrayOfDist, typeof(double), delegate(object elt) { return(0.0); });
            double[, ][] sample = (double[, ][]) JaggedArray.ConvertToNew(
                ga2aArrayOfDist, typeof(double), delegate(object elt) { return(0.0); });

            // Create samples and add them to the estimator. Accumulate sum of samples at the same time
            for (int nSamp = 0; nSamp < nSamples; nSamp++)
            {
                JaggedArray.ConvertElements2(
                    sample, ga2aArrayOfDist, delegate(object smp, object dst) { return(((Gaussian)dst).Sample()); });
                est.Add(sample);

                JaggedArray.ConvertElements2(
                    mean, sample, delegate(object mn, object smp) { return((double)mn + (double)smp); });
            }

            // Hand calculate the sample mean
            JaggedArray.ConvertElements(
                mean, delegate(object mn) { return(((double)mn) / ((double)nSamples)); });

            // Let the estimator do the work
            GaussianArray2DArray result = new GaussianArray2DArray(length1, length2, (i, j) => new GaussianArray(ga2aArrayOfDist[i, j].Length));

            result = est.GetDistribution(result);

            // The results should be identical to a very high precision
            for (int i = 0; i < dim1; i++)
            {
                for (int j = 0; j < dim2; j++)
                {
                    for (int k = 0; k < result[i, j].Count; k++)
                    {
                        Assert.True(System.Math.Abs(result[i, j][k].GetMean() - mean[i, j][k]) < 1e-9);
                    }
                }
            }
        }
示例#2
0
 public EstimatorTest()
 {
     // Create distribution jagged 2D array, and create
     // the parallel jagged 2D array of distributions
     dim1            = 2;
     dim2            = 3;
     ga2aDistArray   = new GaussianArray2DArray(dim1, dim2);
     ga2aArrayOfDist = new Gaussian[dim1, dim2][];
     for (int i = 0; i < dim1; i++)
     {
         for (int j = 0; j < dim2; j++)
         {
             ga2aDistArray[i, j]   = new GaussianArray(i + j + 1);
             ga2aArrayOfDist[i, j] = new Gaussian[i + j + 1];
             for (int k = 0; k < ga2aDistArray[i, j].Count; k++)
             {
                 ga2aDistArray[i, j][k]   = Gaussian.FromMeanAndPrecision((double)k, (double)((k + 1) * (k + 1)));
                 ga2aArrayOfDist[i, j][k] = new Gaussian(ga2aDistArray[i, j][k]);
             }
         }
     }
 }