コード例 #1
0
    public Camera (Game game,Vector3 pos, Vector3 target, Vector3 up)
        : base (game)

    {
        view = matrix.createlookat(pos, target, up);
        projection = matrix.createperspectivefieldofview(
            mathhelper.PiOver4,
            (float)Game.Window.ClientBounds.Width / (float)Game.Window.ClientBounds.Height,
            1, 100);
    }
コード例 #2
0
ファイル: fit.cs プロジェクト: pjuelsgaard/PrakProg
    public static matrix cov(matrix A)
    {
        /*
         * matrix R = new matrix(A.size2, A.size2);
         * matrix Q = A.copy();
         * matrix.qr_gs_decomp(Q,R);
         * matrix invR = matrix.rtri_invert(R);
         * matrix S = invR*invR.T;
         */


        matrix ATA = A.T * A;
        matrix Q   = ATA.copy();
        matrix R   = new matrix(ATA.size2, ATA.size2);

        matrix.qr_gs_decomp(Q, R);
        matrix S = matrix.qr_gs_inverse(Q, R);

        return(S);
    }
コード例 #3
0
        public static matrix create_matrix(int rows, int columns)
        {
            var result = new matrix();
            int r, c;

            result.row = new matrix_row[rows];

            for (r = 0; r < rows; r++)
            {
                result.row[r]     = new matrix_row();
                result.row[r].col = new double[columns];

                for (c = 0; c < columns; c++)
                {
                    result.row[r].col[c] = 0;
                }
            }

            return(result);
        }
コード例 #4
0
    public static void Main()
    {
        Write("==== C ====\n");
        Write("Checking the implementation of the Givens rotation for QR-factorization on random matrix A:\n");
        matrix a = rndMat.randomMatrix(5, 5);
        vector b = rndMat.randomVector(5);

        a.print("A = ");
        Write("Checking by solving Ax=b for random vector b:\n");
        b.print("b = ");
        qrDecompositionGivens qrGivens = new qrDecompositionGivens(a);
        vector x = qrGivens.solve(b);

        Write("The found solution x is:\n");
        x.print("x = ");
        Write("Checking the solution by calculating 0=Ax-b:\n");
        vector diff = a * x - b;

        diff.print("A*x-b = ");
    } //Main
コード例 #5
0
        public void update(particleSystem pS)
        {
            vector r = FriedChiken.getResidual();
            matrix J = FriedChiken.getJacobian();

            currentVolume = 0;
            for (int i = 0; i < J.nCol; i++)
            {
                J[number, i] = 0;
            }
            for (int i = 0; i < (int)elemList.Count; i++)
            {
                elements.element e = elemList[i];
                e.copyFrom(pS.particles);
                e.Update();
                e.Merge(pS, J, this.number);
                currentVolume += e.Volume;
            }
            r[number] = currentVolume - refVolume;
        }
コード例 #6
0
    public lsq_qr(double[] x, double[] y, double[] dy, Func <double, double>[] F)
    {
        A = new matrix(x.Length, F.Length);
        for (int i = 0; i < F.Length; i++)
        {
            for (int j = 0; j < x.Length; j++)
            {
                A[i][j] = F[i](x[j]) / dy[j];               // Row/column convention interchanged
            }
        }
        vector b = new vector(x.Length);

        for (int i = 0; i < x.Length; i++)
        {
            b[i] = y[i] / dy[i];
        }
        qr AQR = new qr(A);

        c = AQR.solve(b);
    }
コード例 #7
0
    public static void Main(string[] args)
    {
        //Process.GetCurrentProcess().PriorityClass = ProcessPriorityClass.High;
        int       max   = 300;          // max n
        int       step  = 10;
        double    scale = 7.0 / 135000; // 300^3*scale = 1400
        Stopwatch timer = new Stopwatch();

        WriteLine(string.Format("# {0, -6} {1, -8} {2, -8}", "n", "cyclic", "n^3"));
        for (int n = 10; n < max; n += step)
        {
            matrix A = GenRandSymMatrix(n, n);
            timer.Start();
            cyclic(A);
            timer.Stop();

            WriteLine($"{n, -8} {timer.ElapsedMilliseconds, -8:F3} {Pow(n, 3)*scale, -8:F3}");
            timer.Reset();
        }
    }
コード例 #8
0
ファイル: matrixHelp.cs プロジェクト: SimonHawk/ppnm
    public static matrix makeRandSymMatrix(int n)
    {
        var    rand = new System.Random();
        matrix A    = new matrix(n, n);

        for (int i = 0; i < n; i++)
        {
            A[i, i] = rand.NextDouble();
        }
        for (int i = 0; i < n; i++)
        {
            for (int j = i + 1; j < n; j++)
            {
                double Aij = rand.NextDouble();
                A[i, j] = Aij;
                A[j, i] = Aij;
            }
        }
        return(A);
    }
コード例 #9
0
using static RNG; // Secure RNG
class main { public static int Main()
             {
                 int    n_2 = RandomInt(3, 5);
                 vector b   = new vector(n_2);
                 var    A_2 = new matrix(n_2, n_2);

                 for (int i = 0; i < n_2; i = i + 1)
                 {
                     RandomDouble(0, 1); for (int j = 0; j < n_2; j = j + 1)
                     {
                         A_2[j, i] = RandomDouble(-20, 20); b[j] = RandomDouble(-20, 20);
                     }
                 }
                 (A_2).print("\nA = ");
                 (b).print("\nb = ");
                 (GivensSolve(Givens(A_2), b)).print("\nx = ");
                 (Givens(A_2) * GivensSolve(Givens(A_2), b)).print("\nAx = ");
                 WriteLine($"\nDet(A) = {Det(A_2)}");
                 return(0);
             }
コード例 #10
0
ファイル: main.cs プロジェクト: jsinkbaek/ppnm
    static void A2()
    {
        WriteLine("Problem A2");
        var    rand = new System.Random();
        int    n    = 2 + rand.Next(20);
        matrix A    = make_random_matrix(n, n);
        vector b    = make_random_vector(n);

        WriteLine("Random square matrix A:");
        A.print("A = ");

        WriteLine("Random vector b:");
        b.print("b = ");

        qr_decomp_GS decomposition = new qr_decomp_GS(A);
        vector       x             = decomposition.solve(b);

        x.print("Solution x = ");
        (A * x - b).print("A*x-b = ");
    }
コード例 #11
0
 /// <summary>
 ///
 /// </summary>
 /// <param name="N">要素の次元</param>
 /// <param name="dim">1節点の自由度、3か6が普通</param>
 public integralPoint(int N, matrix _nodes, int dim) : base()
 {
     //親要素の節点
     this.nodes       = _nodes;
     __N              = N;
     this.dof         = __dim * _nodes.nRow;
     metric           = new matrix(N, N).eye();
     refMetric        = new matrix(N, N).zeros();
     invMetric        = new matrix(N, N).eye();
     refInvMetric     = new matrix(N, N).eye();
     stress           = new matrix(N, N).eye();
     stress2          = new matrix(N, N).eye();
     strain           = new matrix(N, N).zeros();
     difMetric        = new matrixVector(N, N, dof);
     covariantBases   = new matrix(N, __dim).zeros();
     number           = new matrixINT(N, N).zeros();
     gravity          = new vector(dim).zeros();
     gravity[dim - 1] = 1.0;
     energyDensity    = 0;
 }
コード例 #12
0
ファイル: qr-stuff.cs プロジェクト: CruderDegree/ppnm
    public static vector qr_gs_solve(matrix Q, matrix R, vector b)
    {
        vector x = new vector(R.size1);
        // Make system triangular
        vector c = Q.transpose() * b;

        for (int i = x.size - 1; i >= 0; i--)
        {
            double s = 0;
            int    k = i + 1;

            while (k < x.size)
            {
                s += R[i, k] * x[k];
                k++;
            }
            x[i] = 1 / R[i, i] * (c[i] - s);
        }
        return(x);
    }
コード例 #13
0
    public static Tuple <vector, matrix> box(int n)
    {
        double s = 1.0 / (n + 1);
        matrix H = new matrix(n, n);

        for (int i = 0; i < n - 1; i++)
        {
            matrix.set(H, i, i, -2);
            matrix.set(H, i, i + 1, 1);
            matrix.set(H, i + 1, i, 1);
        }
        matrix.set(H, n - 1, n - 1, -2);
        H = -1 / s / s * H;

        var    res = new jacobi_diagonalization(H);
        vector e   = res.get_eigenvalues();
        matrix V   = res.get_eigenvectors();

        return(new Tuple <vector, matrix>(e, V));
    }
コード例 #14
0
    public static matrix jacobian(Func <vector, vector> f, vector x, double dx = 1e-10)
    {
        vector fs = f(x);
        vector xj = new vector(x.size); for (int i = 0; i < x.size; i++)
        {
            xj[i] = x[i];
        }
        matrix J = new matrix(fs.size, x.size);

        for (int i = 0; i < x.size; i++)
        {
            for (int j = 0; j < x.size; j++)
            {
                xj[j]   = xj[j] + dx;
                J[j][i] = (f(xj)[i] - fs[i]) / dx;
                xj      = x.copy();
            }
        }
        return(J);
    }
コード例 #15
0
    private static void givensRot(matrix A, matrix U, int p, int q)
    {
        // Perform a rotation on A: G^T*A and updates U --> U*G = U'
        double App = A[p, p], Aqq = A[q, q], Apq = A[p, q], Aqp = A[q, p];
        double theta = Atan2(Aqp - Apq, App + Aqq);
        double c = Cos(theta), s = Sin(theta);

        for (int i = 0; i < A.size2; i++)
        {
            // A --> A' = G^T * A
            double Api = A[p, i], Aqi = A[q, i];
            A[p, i] = c * Api + s * Aqi;
            A[q, i] = c * Aqi - s * Api;

            // U --> U' = U*G
            double Uip = U[i, p], Uiq = U[i, q];
            U[i, p] = c * Uip + s * Uiq;
            U[i, q] = c * Uiq - s * Uip;
        }
    }
コード例 #16
0
ファイル: RandMatrix.cs プロジェクト: ryejakob/prog
    }//end randmatrix

    public static matrix randmatrix_sym(int n, int m)
    {
        matrix A  = new matrix(n, m);
        Random ra = new Random();

        //diagonal
        for (int n1 = 0; n1 < n; n1++)
        {
            A[n1, n1] = ra.NextDouble();
        }        // end for
        for (int n2 = 1; n2 < n; n2++)
        {
            for (int n3 = 0; n3 < n2; n3++)
            {
                A[n2, n3] = ra.NextDouble();
                A[n3, n2] = A[n2, n3];
            }
        }
        return(A);
    } // end ransmatrix_sys
コード例 #17
0
    // Helper function. Returns diaginal matrix D and resets A to its symetric form after evaluation
    static public matrix diag_cyclic_complete(matrix A, matrix V)
    {
        vector d = new vector(A.size1);

        diag_cyclic(A, V, d);
        for (int i = 0; i < A.size1; i++)
        {
            for (int j = i + 1; j < A.size2; j++)
            {
                A[i, j] = A[j, i];
            }
        }
        matrix D = new matrix(A.size1, A.size2);

        for (int i = 0; i < d.size; i++)
        {
            D[i, i] = d[i];
        }
        return(D);
    }
コード例 #18
0
ファイル: givens.cs プロジェクト: HeleneHJ/PPNM
public givens(matrix A){
		G = A.copy();
		int n=G.size1;
		int m=G.size2;
		double theta;
		double xp;
		double xq;
		for(int q=0;q<m;q++){ 					/* Iterating over the columns */
			for(int p=q+1;p<n;p++){ 			/* Iterating over all rows below the diagonal */
				theta=Atan2(G[p,q],G[q,q]); 	/* Recalculating the relevant rows (the angles are saved in the matrix instead of the 0's) */
				for(int k=q;k<m;k++){
					xp=Cos(theta)*G[q,k]+Sin(theta)*G[p,k];
					xq=-Sin(theta)*G[q,k]+Cos(theta)*G[p,k];
					G[q,k]=xp;
					G[p,k]=xq;	
				}	
				G[p,q]=theta;	
			}
		}
	}//givens
コード例 #19
0
    // Generate matrix containing non-linear parameters for the gaussian test
    // functions transformed to center of mass system
    /* public matrix generateA() { */
    /*   matrix A = new matrix(nParticles - 1, nParticles -1); */
    /*   List<double> alphas = makeAlphas(); */
    /*   // Generate values for every entry in the matrix A */
    /*   for (int k = 0; k < nParticles - 1; k++) { */
    /*     for (int l = 0; l < k; l++) { */
    /*       double akl = A_kl(k,l,alphas); */
    /*       A[l,k] = akl; */
    /*       A[k,l] = akl; */
    /*     } */
    /*     A[k,k] = A_kl(k,k,alphas); */
    /*   } */

    /*   return A; */
    /* } */

    public matrix generateA()
    {
        matrix A = new matrix(nParticles - 1, nParticles - 1);
        matrix B = new matrix(A.rows, A.cols);

        for (int i = 0; i < A.cols; i++)
        {
            for (int j = 0; j < A.cols; j++)
            {
                if (i == j)
                {
                    A[i, j] = Math.Log(1 - r.NextDouble()) / -1;
                }
                B[i, j] = Math.Log(1 - r.NextDouble()) / -1;
            }
        }
        matrix Q = new QRdecomposition(B).Q;

        return(Q * A * Q.transpose());
    }
コード例 #20
0
    // Below are two modified versions of the above algorithm in which the errors are collected to monitor the convergence
    public static void generate_convergences(int iteration, ref matrix A, ref matrix I, double e_0, vector v_0, double e_J, double tau = 1e-6, double eps = 1e-6, int n_max = 999, int updates = 999)
    {
        matrix As; double s = e_0;

        As = A - s * I;
        qr As_QR = new qr(As);

        List <double> errors   = new List <double>();
        List <double> errors_s = new List <double>();

        generate_errors(As_QR, ref A, ref I, ref errors, ref errors_s, s, updates, e_J, v_0, tau, eps);

        var outfile = new System.IO.StreamWriter($"./plotfiles/convergence_{iteration}.txt", append: false);

        for (int k = 0; k < errors.Count; k++)
        {
            outfile.WriteLine($"{k} {errors[k]} {errors_s[k]}");
        }
        outfile.Close();
    }
コード例 #21
0
    static void Main()
    {
        int    tend       = 100;
        double resulution = 1; // steps pr time unit for plot (dose not effect ODE)
        vector t          = linspace(0, tend, (int)(resulution * (tend + 1)));
        double h          = 1e-5;
        double acc        = 1e-4;
        double eps        = 1e-4;



        // Initial coniditions found at: https://arxiv.org/pdf/math/0011268.pdf
        double x10 = 0.97000436;
        double y10 = -0.24308753;
        double x20 = -x10;
        double y20 = -y10;
        double x30 = 0;
        double y30 = 0;

        double v3x0 = -0.93240737;
        double v3y0 = -0.86473146;
        double v2x0 = -0.5 * v3x0;
        double v2y0 = -0.5 * v3y0;
        double v1x0 = v2x0;
        double v1y0 = v2y0;

        vector Y0 = new vector(new double[] { x10, y10, v1x0, v1y0, x20, y20, v2x0, v2y0, x30, y30, v3x0, v3y0 });

        vector param = new vector(1, 1, 1);
        Func <double, vector, vector> f = (T, Y) => diffExplesit(T, Y, param);

        matrix yres = ode_integrator.driver(f, t, Y0, h, acc, eps);

        System.IO.StreamWriter outputfile = new System.IO.StreamWriter("out.plotC.txt", append: false);

        for (int i = 0; i < t.size; i++)
        {
            outputfile.WriteLine("{0} {1} {2} {3} {4} {5} {6}", t[i], yres[i][0], yres[i][1], yres[i][4], yres[i][5], yres[i][8], yres[i][9]);
        }
        outputfile.Close();
    }
コード例 #22
0
ファイル: main.cs プロジェクト: nronne/ppnm
    static void Main()
    {
        int n = 7, m = n;
        var A   = new matrix(n, m);
        var rnd = new System.Random();

        for (int i = 0; i < A.size1; i++)
        {
            for (int j = 0; j < A.size2; j++)
            {
                A[i, j] = 2 * (rnd.NextDouble() - 1);
            }
        }
        A.print("random matrix A:");
        var b = new vector(m);

        for (int i = 0; i < b.size; i++)
        {
            b[i] = rnd.NextDouble();
        }
        b.print("random vector b:\n");
        var qra = new qrdecomposition(A);
        var x   = qra.solve(b);

        x.print("solution x to system A*x=b:\n");
        var Ax = A * x;

        Ax.print("check: A*x (should be equal b):\n");
        if (vector.approx(Ax, b))
        {
            WriteLine("test passed");
        }
        else
        {
            WriteLine("test failed");
        }
        var B = qra.inverse();

        (B * A).print("A^-1*A=");
        (A * B).print("A*A^-1=");
    }
コード例 #23
0
    // returns (min, steps)
    public static (vector, int) qnewton(Func <vector, double> f, vector x0, double eps)
    {
        int    n = 0;                    // total number of steps
        vector x = x0.copy(), s;         // position vectors
        double fx = f(x), fxs;           // function values
        vector gx = gradient(f, x), gxs; // gradient vectors
        matrix B = matrix.id(x.size);    // inverse Hessian, initialized to I

        while (eps < gx.norm())          // continue until the sum of diffs is almost zero
        {
            n++;
            vector Dx = -B * gx;                       // eq 6
            double min = 1.0 / Pow(2, limit), l = 1.0; // min is the smallest step allowed, l is lambda
            do                                         // backtracking
            {
                s   = l * Dx;                          // step, eq 8
                fxs = f(x + s);
                if (l < min)
                {
                    B = matrix.id(x.size);                     // advised to reset B if l < min by the text
                    break;
                }
                l /= 2;                           // halve the step size
            }while (!(fxs < fx + a * s.dot(gx))); // armijo condition
            gxs = gradient(f, x + s);
            vector y     = gxs - gx;              // eq 12
            vector u     = s - B * y;
            double denom = u.dot(y);
            if (Abs(denom) > eps)             // eq 18, abs very important
            {
                B.update(u, u, 1 / denom);    // dmitri has apparently already specified this operation
            }
            // B += u.dot(u)/denom;

            // prepare for next iteration
            x  = x + s;
            gx = gxs;
            fx = fxs;
        }
        return(x, n);
    }
コード例 #24
0
        public jcbi_cycl(matrix A, bool val_by_val = false, int evalnum = 1, bool invert = false)
        {        // constructor of jacobi diag object through sweep
            sweep = 0;
            n     = A.size1;
            v     = new matrix(n, n);
            d     = new vector(n);

            // diagonal of A, copy into vector d
            for (int i = 0; i < n; i++)
            {
                d[i] = A[i, i];
            }

            // set v diagonals to 1, off-diagonals 0
            for (int i = 0; i < n; i++)
            {
                v[i, i] = 1.0;
                for (int j = i + 1; j < n; j++)
                {
                    v[i, j] = 0.0; v[j, i] = 0.0;
                }
            }

            if (val_by_val)
            {
                for (p = 0; p < evalnum; p++)
                {
                    do
                    {
                        rot_vbv(A, evalnum, invert);
                    } while (cond);
                }
            }
            else
            {
                do
                {
                    rot_sweep(A);
                } while (cond);
            }
        }
コード例 #25
0
ファイル: QRdecomp.cs プロジェクト: anders6400/Prakprog
    } // Solve

    public matrix inverse()
    {
        int n = Q.size1;
        int m = Q.size2;

        if (n != m)
        {
            Error.Write("Matrix must be a square matrix!");
        }

        matrix S = new matrix(n, m);
        vector e = new vector(n);

        for (int i = 0; i < n; i++)
        {
            e[i] = 1;
            S[i] = solve(e);
            e[i] = 0;
        }
        return(S);
    }
コード例 #26
0
        public static void decomp(matrix A, matrix R)
        {
            int    m = A.size2;
            double ujvi, ujuj;

            for (int i = 0; i < m; i++)
            {
                for (int j = 0; j < i; j++)
                {
                    ujvi     = A[j].dot(A[i]); ujuj = A[j].dot(A[j]);
                    R[j, i]  = ujvi / ujuj;          // a_ij
                    A[i]    -= R[j, i] * A[j];
                    R[j, i] *= R[j, j];
                }
                R[i, i] = A[i].norm();
            }
            for (int i = 0; i < m; i++)
            {
                A[i] = A[i] / R[i, i];       // At this point, Q[i] = A[i]
            }
        }
コード例 #27
0
    // Generates the Lambda matrix
    // TODO: Check lambda
    private matrix generateLambda()
    {
        int    nParticles = particles.Count;
        matrix Lambda     = new matrix(nParticles - 1, nParticles - 1);

        for (int i = 0; i < nParticles - 1; i++)
        {
            for (int j = 0; j < nParticles - 1; j++)
            {
                double lambda_ij = 0;
                for (int k = 0; k < nParticles; k++)
                {
                    lambda_ij += U[i, k] * U[j, k] / particles[k].getMass();
                }
                Lambda[i, j] = lambda_ij;
            }
        }


        return(Lambda);
    }
コード例 #28
0
    public static (int, int, vector) simplex_update(matrix simplex, vector f_values, int d)
    {
        int hi = 0;
        int lo = 0;

        for (int i = 1; i < d + 1; i++)
        {
            if (f_values[i] < f_values[lo])
            {
                lo = i;
            }
            if (f_values[i] > f_values[hi])
            {
                hi = i;
            }
        }

        vector centroid = calcCentroid(simplex, hi);

        return(hi, lo, centroid);
    }
コード例 #29
0
ファイル: gs.cs プロジェクト: joha3332/PPNM
    public gs(matrix A)
    {
        Q = (A).copy();
        int n = A.size1;
        int m = A.size2;

        Debug.Assert(n >= m);

        R = new matrix(m, m);
        for (int i = 0; i < m; i++)
        {
            R[i, i] = Q[i].norm();
            Q[i]   /= R[i, i];

            for (int j = i + 1; j < m; j++)
            {
                R[i, j] = Q[i].dot(Q[j]);
                Q[j]   -= Q[i] * R[i, j];
            }
        }
    }
コード例 #30
0
ファイル: qr.cs プロジェクト: nronne/ppnm
    public qrdecomposition(matrix M)
    {
        matrix A = M.copy();

        for (int q = 0; q < A.size2; q++)
        {
            for (int p = q + 1; p < A.size1; p++)
            {
                double theta = Atan2(A[p, q], A[q, q]);
                double c = Cos(theta), s = Sin(theta);
                for (int k = q; k < A.size2; k++)
                {
                    double xq = A[q, k], xp = A[p, k];
                    A[q, k] = xq * c + xp * s;
                    A[p, k] = -xq * s + xp * c;
                }
                A[p, q] = theta;
            }
        }
        QR = A;
    }
コード例 #31
0
ファイル: matrix.cs プロジェクト: CruderDegree/ppnm
    public static matrix operator*(matrix a, matrix b)
    {
        var c = new matrix(a.size1, b.size2);

        for (int k = 0; k < a.size2; k++)
        {
            for (int j = 0; j < b.size2; j++)
            {
                double bkj = b[k, j];
                var    cj  = c.data[j];
                var    ak  = a.data[k];
                int    n   = a.size1;
                for (int i = 0; i < n; i++)
                {
                    //c[i,j]+=a[i,k]*b[k,j];
                    cj[i] += ak[i] * bkj;
                }
            }
        }
        return(c);
    }
コード例 #32
0
        public static void StagePole( rotpol[] r,  int n, out CCEuler.EulerPole[] s_pole, out double[] s_angle)
        {
            int o;
            matrix[] m = new matrix[100];
            matrix[] mt = new matrix[100];
            matrix[] ms = new matrix[100];

            s_pole = new CCEuler.EulerPole[100];
            s_angle = new double[100];

            CCEuler.matrix_1(out m[1].ma);
            CCEuler.matrix_1(out mt[0].ma);
            for (o = 0; o <= n - 1; o++)
            {
                CCEuler.calc_pole2matrix(out m[o].ma, r[o].p, r[o].Angle);
                CCEuler.calc_pole2matrix(out mt[o].ma, r[o].p, -r[o].Angle);
            }
            for (o = 0; o < n-1; o++)
            {
                CCEuler.matrix_mult(mt[o].ma, m[o+1 ].ma, out ms[o+1].ma);
                CCEuler.calc_matrix2pole(ms[o+1].ma, out s_pole[o+1], out s_angle[o+1]);
            }
        }
コード例 #33
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 /*
 public int rows(){return data[0].size;}
 public int cols(){return data.GetLength(0);}
 */
 public matrix(matrix b)
 {
     nrows=b.rows; ncols=b.cols;
     data = new double[nrows*ncols];
     System.Array.Copy(b.data,data,b.data.Length);
 }
コード例 #34
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 public matrix transpose()
 {
     //	int ncols=this.cols, nrows=this.rows;
     matrix c = new matrix(ncols,nrows);
     for(int ir=0;ir<nrows;ir++)
     for(int ic=0;ic<ncols;ic++) c[ic,ir]=this[ir,ic];
     return c;
 }
コード例 #35
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 public matrix copy()
 {
     matrix c = new matrix(this);
     return c;
 }
コード例 #36
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 public static matrix operator ^(matrix a, matrix b)
 {
     int ac=a.cols, ar=a.rows, br=b.rows;
     matrix c = new matrix(ac,br);
     for(int ir=0;ir<ac;ir++)
     for(int ic=0;ic<br;ic++)
     {
     double s=0;
     for(int irar=ir*ar, icbr=ic*br; irar<ir*ar+ar;)
     //		for(int irar=ir*ar, icbr=ic*br, k=0;k<ar; k++)
         s+=a.data[irar++]*b.data[icbr++];
     //			s+=a.data[k+ir*ar]*b.data[k+ic*br];
     c.data[ir+ic*ar]=s;
     }
     /*
       {
     double s=0; int ar=a.rows;
     for(int k=0;k<ar;k++)
         s+=a[k,ir]*b[k,ic];
     c[ir,ic]=s;
     }
     */
     return c;
 }
コード例 #37
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 public static matrix operator +(matrix a, matrix b)
 {
     matrix c = new matrix(a.rows,a.cols);
     for(int i=0;i<a.rows;i++)
     for(int j=0;j<a.cols;j++)
     c[i,j]=a[i,j]+b[i,j];
     return c;
 }
コード例 #38
0
ファイル: matrix.cs プロジェクト: Bakkedal/QSL
 public static matrix operator *(matrix a, matrix b)
 {
     int n=a.rows, m=b.cols;
        if(a.cols != b.rows) System.Console.Error.Write("matrix mismatch\n");
        var c = new matrix(n,m);
        for (int k=0;k<a.cols;k++) for (int j=0;j<m;j++){
       double tmp=b.data[k+j*b.rows];
     //		for (int i=0;i<n;i++){
       for (int jn=j*n, kn=k*n; jn<j*n+n;){
     //       c.data[i+j*n]+=a.data[i+k*n]*tmp;
      c.data[jn++]+=a.data[kn++]*tmp;
     //			c[i,j]+=a[i,k]*tmp;
     }
        }
        return c;
 }