示例#1
0
 public void MixedMatrixSubtraction()
 {
     SquareMatrix MS = M - S;
     SquareMatrix SM = S - M;
 }
示例#2
0
 public void SquareMatrixInvalidDimensionTest()
 {
     SquareMatrix M = new SquareMatrix(0);
 }
示例#3
0
 public void MixedMatrixAddition()
 {
     SquareMatrix MS = M + S;
     SquareMatrix SM = S + M;
 }
        public void PC()
        {
            Random rng = new Random(1);
            double s   = 1.0 / Math.Sqrt(2.0);

            MultivariateSample MS = new MultivariateSample(2);
            RectangularMatrix  R  = new RectangularMatrix(1000, 2);

            for (int i = 0; i < 1000; i++)
            {
                double r1 = 2.0 * rng.NextDouble() - 1.0;
                double r2 = 2.0 * rng.NextDouble() - 1.0;
                double x  = r1 * 4.0 * s - r2 * 9.0 * s;
                double y  = r1 * 4.0 * s + r2 * 9.0 * s;
                R[i, 0] = x; R[i, 1] = y;
                MS.Add(x, y);
            }

            Console.WriteLine("x {0} {1}", MS.Column(0).Mean, MS.Column(0).Variance);
            Console.WriteLine("y {0} {1}", MS.Column(1).Mean, MS.Column(1).Variance);

            Console.WriteLine("SVD");

            SingularValueDecomposition SVD = R.SingularValueDecomposition();

            for (int i = 0; i < SVD.Dimension; i++)
            {
                Console.WriteLine("{0} {1}", i, SVD.SingularValue(i));
                ColumnVector v = SVD.RightSingularVector(i);
                Console.WriteLine("  {0} {1}", v[0], v[1]);
            }

            Console.WriteLine("PCA");

            PrincipalComponentAnalysis PCA = MS.PrincipalComponentAnalysis();

            Console.WriteLine("Dimension = {0} Count = {1}", PCA.Dimension, PCA.Count);
            for (int i = 0; i < PCA.Dimension; i++)
            {
                PrincipalComponent PC = PCA.Component(i);
                Console.WriteLine("  {0} {1} {2} {3}", PC.Index, PC.Weight, PC.VarianceFraction, PC.CumulativeVarianceFraction);
                RowVector v = PC.NormalizedVector();
                Console.WriteLine("  {0} {1}", v[0], v[1]);
            }

            // reconstruct
            SquareMatrix U  = SVD.LeftTransformMatrix();
            SquareMatrix V  = SVD.RightTransformMatrix();
            double       x1 = U[0, 0] * SVD.SingularValue(0) * V[0, 0] + U[0, 1] * SVD.SingularValue(1) * V[0, 1];

            Console.WriteLine("x1 = {0} {1}", x1, R[0, 0]);
            double y1 = U[0, 0] * SVD.SingularValue(0) * V[1, 0] + U[0, 1] * SVD.SingularValue(1) * V[1, 1];

            Console.WriteLine("y1 = {0} {1}", y1, R[0, 1]);
            double x100 = U[100, 0] * SVD.SingularValue(0) * V[0, 0] + U[100, 1] * SVD.SingularValue(1) * V[0, 1];

            Console.WriteLine("x100 = {0} {1}", x100, R[100, 0]);
            double y100 = U[100, 0] * SVD.SingularValue(0) * V[1, 0] + U[100, 1] * SVD.SingularValue(1) * V[1, 1];

            Console.WriteLine("y100 = {0} {1}", y100, R[100, 1]);

            ColumnVector d1 = U[0, 0] * SVD.SingularValue(0) * SVD.RightSingularVector(0) +
                              U[0, 1] * SVD.SingularValue(1) * SVD.RightSingularVector(1);

            Console.WriteLine("d1 = ({0} {1})", d1[0], d1[1]);
            ColumnVector d100 = U[100, 0] * SVD.SingularValue(0) * SVD.RightSingularVector(0) +
                                U[100, 1] * SVD.SingularValue(1) * SVD.RightSingularVector(1);

            Console.WriteLine("d100 = ({0} {1})", d100[0], d100[1]);

            Console.WriteLine("compare");
            MultivariateSample     RS  = PCA.TransformedSample();
            IEnumerator <double[]> RSE = RS.GetEnumerator();

            RSE.MoveNext();
            double[] dv1 = RSE.Current;
            Console.WriteLine("{0} {1}", dv1[0], dv1[1]);
            Console.WriteLine("{0} {1}", U[0, 0], U[0, 1]);
            RSE.Dispose();
        }