Пример #1
0
    private Matrix SqrtSPKF(Matrix PDash) {
      // Only works with a symmetric Positive Definite matrix
      // [V,D] = eig(A)
      // S = V*diag(sqrt(diag(D)))*V'
      //
      // //PDash in
      // System.out.println("PDash: ");
      // PDash.print(3, 2);

      // Matrix NegKeeper = Matrix.identity(9, 9);
      // //Testing Forced Compliance
      // for(int i = 0; i< 9; i++){
      // if (PDash.get(i, i)< 0){
      // NegKeeper.set(i,i,-1);
      // PDash.set(i, i, -PDash.get(i, i));
      // }
      // }
      EigenvalueDecomposition eig = PDash.eig();
      Matrix V = eig.getV();
      Matrix D = eig.getD();
      int iDSize = D.getRowDimension();
      for (int i = 0; i < iDSize; i++) {
        D.set(i, i, Math.sqrt(D.get(i, i)));
      }
      Matrix S = V.times(D).times(V.inverse());
      // S = S.times(NegKeeper);
      return S;
    }
  float normMaxEval(Matrix U, Matrix uVal, Matrix uVec) {
    /* *
     * Decomposition:
     * U = V * D * V.inv()
     * V has eigenvectors as columns
     * D is a diagonal Matrix with eigenvalues as elements
     * V.inv() is the inverse of V
     * */
    //		uVec = uVec.transpose();
    Matrix uVinv = uVec.inverse();

    // Normalize min eigenvalue to 1 to expand patch in the direction of min eigenvalue of U.inv()
    double uval1 = uVal.get(0, 0);
    double uval2 = uVal.get(1, 1);

    if (Math.abs(uval1) < Math.abs(uval2)) {
      uVal.set(0, 0, 1);
      uVal.set(1, 1, uval2 / uval1);

    } else {
      uVal.set(1, 1, 1);
      uVal.set(0, 0, uval1 / uval2);
    }

    // U normalized
    U.setMatrix(0, 1, 0, 1, uVec.times(uVal).times(uVinv));

    return (float)
        (Math.max(Math.abs(uVal.get(0, 0)), Math.abs(uVal.get(1, 1)))
            / Math.min(
                Math.abs(uVal.get(0, 0)),
                Math.abs(uVal.get(1, 1)))); // define the direction of warping
  }
  /*
   * Calculates second moments matrix square root
   */
  float calcSecondMomentSqrt(AbstractStructureTensorIPD ipd, Pixel p, Matrix Mk) {
    Matrix M, V, eigVal, Vinv;

    M = calcSecondMomentMatrix(ipd, p.x, p.y);

    /* *
     * M = V * D * V.inv()
     * V has eigenvectors as columns
     * D is a diagonal Matrix with eigenvalues as elements
     * V.inv() is the inverse of V
     * */
    //		EigenvalueDecomposition meig = M.eig();
    EigenValueVectorPair meig = MatrixUtils.symmetricEig2x2(M);
    eigVal = meig.getValues();
    V = meig.getVectors();

    //		V = V.transpose();
    Vinv = V.inverse();

    double eval1 = Math.sqrt(eigVal.get(0, 0));
    eigVal.set(0, 0, eval1);
    double eval2 = Math.sqrt(eigVal.get(1, 1));
    eigVal.set(1, 1, eval2);

    // square root of M
    Mk.setMatrix(0, 1, 0, 1, V.times(eigVal).times(Vinv));

    // return q isotropic measure
    return (float) (Math.min(eval1, eval2) / Math.max(eval1, eval2));
  }
Пример #4
0
  private double[] metNewton(double R0, double Z0) {
    Matrix actuel = new Matrix(2, 1);
    Matrix prochain = new Matrix(2, 1);
    Matrix hessienne = new Matrix(2, 2);
    Matrix gradient = new Matrix(2, 1);
    Matrix inverse = new Matrix(2, 2);
    int nPas = 0;
    boolean trouve = false;
    // point de depart
    actuel.set(0, 0, R0);
    actuel.set(1, 0, Z0);

    while (nPas <= MAX_PAS && trouve == false) {
      // Construction de la matrice hessienne au point actuel
      hessienne = makeHessienne(R0, Z0);
      // Test si matrice singulaire
      if (hessienne.det() == 0) {
        return null;
      }
      // Calcul de la matrice inverse
      inverse = hessienne.inverse();
      // Construction du gradient au point actuel
      gradient.set(0, 0, d_phi_d_R(actuel.get(0, 0), actuel.get(1, 0)));
      gradient.set(1, 0, d_phi_d_Z(actuel.get(0, 0), actuel.get(1, 0)));
      // Calcul du prochain point
      prochain = actuel.minus(inverse.times(gradient));

      // Test de la solution
      if (Math.pow(
              Math.pow(prochain.get(0, 0) - actuel.get(0, 0), 2)
                  + Math.pow(prochain.get(1, 0) - actuel.get(1, 0), 2),
              0.5)
          < TOLERANCE) {
        // Solution trouvé
        trouve = true;
      }

      // Actualisation du point actuel
      actuel = prochain;
      nPas++;
    }

    if (trouve == true) // Si point trouvé, renvoie la réponse
    {
      // Conversion de Matrix vers double[]
      double[] reponse = new double[2];
      reponse[0] = actuel.get(0, 0);
      reponse[1] = actuel.get(1, 0);

      return reponse;
    }
    // Renvoie 0 si la méthode ne converge pas
    return null;
  }
  /**
   * Update the covariance Matrix of the weight posterior distribution (SIGMA) along with its
   * cholesky factor:
   *
   * <p>SIGMA = (A + beta * PHI^t * PHI)^{-1}
   *
   * <p>SIGMA_chol with SIGMA_chol * SIGMA_chol^t = SIGMA
   */
  protected void updateSIGMA() {

    Matrix SIGMA_inv = PHI_t.times(PHI_t.transpose());
    SIGMA_inv.timesEquals(beta);
    SIGMA_inv.plusEquals(A);

    /** Update the factor ... */
    SECholeskyDecomposition CD = new SECholeskyDecomposition(SIGMA_inv.getArray());
    Matrix U = CD.getPTR().times(CD.getL());
    SIGMA_chol = U.inverse();

    /** Update SIGMA */
    SIGMA = (SIGMA_chol.transpose()).times(SIGMA_chol);
  }
  private double[] estimateVariance() {
    double[] beta = getBestValuesEver();

    Matrix hessian = new Matrix(beta.length, beta.length);
    for (Example example : exampleSet) {
      double[] values = new double[beta.length];
      double eta = 0.0d;
      int j = 0;
      for (Attribute attribute : example.getAttributes()) {
        double value = example.getValue(attribute);
        values[j] = value;
        eta += beta[j] * value;
        j++;
      }
      if (addIntercept) {
        values[beta.length - 1] = 1.0d;
        eta += beta[beta.length - 1];
      }
      double pi = Math.exp(eta) / (1 + Math.exp(eta));

      double weightValue = 1.0d;
      if (weight != null) weightValue = example.getValue(weight);
      for (int x = 0; x < beta.length; x++) {
        for (int y = 0; y < beta.length; y++) {
          // sum is second derivative of log likelihood function
          double h = hessian.get(x, y) - values[x] * values[y] * weightValue * pi * (1 - pi);
          hessian.set(x, y, h);
        }
      }
    }

    double[] variance = new double[beta.length];
    Matrix varianceCovarianceMatrix = null;
    try {
      // asymptotic variance-covariance matrix is inverse of hessian matrix
      varianceCovarianceMatrix = hessian.inverse();
    } catch (Exception e) {
      logging.logWarning("could not determine variance-covariance matrix, hessian is singular");
      for (int j = 0; j < beta.length; j++) {
        variance[j] = Double.NaN;
      }
      return variance;
    }
    for (int j = 0; j < beta.length; j++) {
      // get diagonal elements
      variance[j] = Math.abs(varianceCovarianceMatrix.get(j, j));
    }

    return variance;
  }
Пример #7
0
  /** toy example */
  public static void test2() {
    int N = 500;
    double[][] m1 = new double[N][N];
    double[][] m2 = new double[N][N];
    double[][] m3 = new double[N][N];

    // init
    Random rand = new Random();
    for (int i = 0; i < N; i++)
      for (int j = 0; j < N; j++) {
        m1[i][j] = 10 * (rand.nextDouble() - 0.2);
        m2[i][j] = 20 * (rand.nextDouble() - 0.8);
      }

    // inverse
    System.out.println("Start");
    Matrix mat1 = new Matrix(m1);
    Matrix mat2 = mat1.inverse();
    Matrix mat3 = mat1.times(mat2);
    double[][] m4 = mat3.getArray();
    /*
       for (int i = 0; i < m4.length; i++) {
         int ss = 10;
         for (int j = 0; j < ss; j++) {
    System.out.printf("%f ", m4[i][j]);
         }
         System.out.print("\n");
       }
       */
    System.out.println("Done");

    /*
        // matrix *
        System.out.println("Start");
        for (int i = 0; i < N; i++) for (int j = 0; j < N; j++) {
          double cell = 0;
          for (int k = 0; k < N; k++)
    	cell += m1[i][k] * m2[k][j];
    //      System.out.printf("%f ", cell);
          m3[i][j] = cell;
        }
        System.out.println("Done");
        */
  }
Пример #8
0
  private void computeCovMat() {

    // array for inverse of Covriance matrix
    // the matrix is arraged as (x,y,z,c*t,x',y',p,k)
    double[][] invCovMat_a = new double[8][8];
    for (int i = 0; i < 8; i++) {
      for (int j = 0; j < 8; j++) {
        invCovMat_a[i][j] = 0.;
      }
    }
    invCovMat_a[0][0] =
        1.0 / pow(sigmaX, 2)
            + pow(cos(alpha), 2) / pow(sigmaW, 2)
            + pow(sin(alpha), 2) / pow(sigmaL, 2);
    invCovMat_a[0][2] = (1.0 / pow(sigmaL, 2) - 1.0 / pow(sigmaW, 2)) * sin(alpha) * cos(alpha);
    invCovMat_a[2][0] = invCovMat_a[0][2];
    invCovMat_a[0][3] = sin(alpha) / pow(sigmaL, 2);
    invCovMat_a[3][0] = invCovMat_a[0][3];
    invCovMat_a[1][1] = 1 / pow(sigmaY, 2);
    invCovMat_a[2][2] =
        1 / pow(sigmaZ, 2)
            + pow(cos(alpha), 2) / pow(sigmaL, 2)
            + pow(sin(alpha), 2) / pow(sigmaW, 2);
    invCovMat_a[2][3] = -1.0 / pow(sigmaZ, 2) + cos(alpha) / pow(sigmaL, 2);
    invCovMat_a[3][2] = invCovMat_a[2][3];
    invCovMat_a[3][3] = 1.0 / pow(sigmaZ, 2) + 1.0 / pow(sigmaL, 2);
    invCovMat_a[4][4] = 1.0 / pow(sigmaXp, 2);
    invCovMat_a[5][5] = 1.0 / pow(sigmaYp, 2);
    invCovMat_a[6][6] = 1.0 / pow(sigmaP, 2);
    invCovMat_a[7][7] = 1.0 / pow(sigmaK, 2);
    // transfer invCovMat_a array to matrix invCovMat
    Matrix invCovMat = new Matrix(invCovMat_a);
    // inverse invCovMat to CovMat
    Matrix CovMat_m = invCovMat.inverse();
    covMat = CovMat_m.getArray();
  }
Пример #9
0
    private void RunSPKF() {
      // SPKF Steps:
      // 1) Generate Test Points
      // 2) Propagate Test Points
      // 3) Compute Predicted Mean and Covariance
      // 4) Compute Measurements
      // 5) Compute Innovations and Cross Covariance
      // 6) Compute corrections and update

      // Line up initial variables from the controller!
      Double dAlpha = dGreek.get(0);
      Double dBeta = dGreek.get(1);
      cController.setAlpha(dAlpha);
      cController.setBeta(dBeta);
      cController.setKappa(dGreek.get(2));
      Double dGamma = cController.getGamma();
      Double dLambda = cController.getLambda();

      // // DEBUG - Print the Greeks
      // System.out.println("Greeks!");
      // System.out.println("Alpha - " + dAlpha);
      // System.out.println("Beta - " + dBeta);
      // System.out.println("Kappa - " + dGreek.get(2));
      // System.out.println("Lambda - " + dLambda);
      // System.out.println("Gamma - " + dGamma);

      // Let's get started:
      // Step 1: Generate Test Points
      Vector<Matrix> Chi = new Vector<Matrix>();
      Vector<Matrix> UpChi = new Vector<Matrix>();
      Vector<Matrix> UpY = new Vector<Matrix>();
      Matrix UpPx = new Matrix(3, 3, 0.0);
      Matrix UpPy = new Matrix(3, 3, 0.0);
      Matrix UpPxy = new Matrix(3, 3, 0.0);
      Matrix K;
      Vector<Double> wc = new Vector<Double>();
      Vector<Double> wm = new Vector<Double>();
      Chi.add(X); // Add Chi_0 - the current state estimate (X, Y, Z)

      // Big P Matrix is LxL diagonal
      Matrix SqrtP = SqrtSPKF(P);
      SqrtP = SqrtP.times(dGamma);

      // Set up Sigma Points
      for (int i = 0; i <= 8; i++) {
        Matrix tempVec = SqrtP.getMatrix(0, 8, i, i);
        Matrix tempX = X;
        Matrix tempPlus = tempX.plus(tempVec);
        // System.out.println("TempPlus");
        // tempPlus.print(3, 2);
        Matrix tempMinu = tempX.minus(tempVec);
        // System.out.println("TempMinus");
        // tempMinu.print(3, 2);
        // tempX = X.copy();
        // tempX.setMatrix(i, i, 0, 2, tempPlus);
        Chi.add(tempPlus);
        // tempX = X.copy();
        // tempX.setMatrix(i, i, 0, 2, tempMinu);
        Chi.add(tempMinu);
      }

      // DEBUG Print the lines inside the Chi Matrix (2L x L)
      // for (int i = 0; i<=(2*L); i++){
      // System.out.println("Chi Matrix Set: "+i);
      // Chi.get(i).print(5, 2);
      // }

      // Generate weights
      Double WeightZero = (dLambda / (L + dLambda));
      Double OtherWeight = (1 / (2 * (L + dLambda)));
      Double TotalWeight = WeightZero;
      wm.add(WeightZero);
      wc.add(WeightZero + (1 - (dAlpha * dAlpha) + dBeta));
      for (int i = 1; i <= (2 * L); i++) {
        TotalWeight = TotalWeight + OtherWeight;
        wm.add(OtherWeight);
        wc.add(OtherWeight);
      }
      // Weights MUST BE 1 in total
      for (int i = 0; i <= (2 * L); i++) {
        wm.set(i, wm.get(i) / TotalWeight);
        wc.set(i, wc.get(i) / TotalWeight);
      }

      // //DEBUG Print the weights
      // System.out.println("Total Weight:");
      // System.out.println(TotalWeight);
      // for (int i = 0; i<=(2*L); i++){
      // System.out.println("Weight M for "+i+" Entry");
      // System.out.println(wm.get(i));
      // System.out.println("Weight C for "+i+" Entry");
      // System.out.println(wc.get(i));
      // }

      // Step 2: Propagate Test Points
      // This will also handle computing the mean
      Double ux = dControl.elementAt(0);
      Double uy = dControl.elementAt(1);
      Double uz = dControl.elementAt(2);
      Matrix XhatMean = new Matrix(3, 1, 0.0);
      for (int i = 0; i < Chi.size(); i++) {
        Matrix ChiOne = Chi.get(i);
        Matrix Chixminus = new Matrix(3, 1, 0.0);
        Double Xhat = ChiOne.get(0, 0);
        Double Yhat = ChiOne.get(1, 0);
        Double Zhat = ChiOne.get(2, 0);
        Double Xerr = ChiOne.get(3, 0);
        Double Yerr = ChiOne.get(4, 0);
        Double Zerr = ChiOne.get(5, 0);

        Xhat = Xhat + ux + Xerr;
        Yhat = Yhat + uy + Yerr;
        Zhat = Zhat + uz + Zerr;

        Chixminus.set(0, 0, Xhat);
        Chixminus.set(1, 0, Yhat);
        Chixminus.set(2, 0, Zhat);
        // System.out.println("ChixMinus:");
        // Chixminus.print(3, 2);
        UpChi.add(Chixminus);
        XhatMean = XhatMean.plus(Chixminus.times(wm.get(i)));
      }

      // Mean is right!

      // System.out.println("XhatMean: ");
      // XhatMean.print(3, 2);

      // Step 3: Compute Predicted Mean and Covariance
      // Welp, we already solved the mean - let's do the covariance now
      for (int i = 0; i <= (2 * L); i++) {
        Matrix tempP = UpChi.get(i).minus(XhatMean);
        Matrix tempPw = tempP.times(wc.get(i));
        tempP = tempPw.times(tempP.transpose());
        UpPx = UpPx.plus(tempP);
      }

      // New Steps!

      // Step 4: Compute Measurements! (and Y mean!)
      Matrix YhatMean = new Matrix(3, 1, 0.0);
      for (int i = 0; i <= (2 * L); i++) {
        Matrix ChiOne = Chi.get(i);
        Matrix Chiyminus = new Matrix(3, 1, 0.0);
        Double Xhat = UpChi.get(i).get(0, 0);
        Double Yhat = UpChi.get(i).get(1, 0);
        Double Zhat = UpChi.get(i).get(2, 0);
        Double Xerr = ChiOne.get(6, 0);
        Double Yerr = ChiOne.get(7, 0);
        Double Zerr = ChiOne.get(8, 0);

        Xhat = Xhat + Xerr;
        Yhat = Yhat + Yerr;
        Zhat = Zhat + Zerr;

        Chiyminus.set(0, 0, Xhat);
        Chiyminus.set(1, 0, Yhat);
        Chiyminus.set(2, 0, Zhat);
        UpY.add(Chiyminus);
        YhatMean = YhatMean.plus(Chiyminus.times(wm.get(i)));
      }

      // // Welp, we already solved the mean - let's do the covariances
      // now
      // System.out.println("XHatMean and YHatMean = ");
      // XhatMean.print(3, 2);
      // YhatMean.print(3, 2);

      for (int i = 0; i <= (2 * L); i++) {
        Matrix tempPx = UpChi.get(i).minus(XhatMean);
        Matrix tempPy = UpY.get(i).minus(YhatMean);
        // System.out.println("ChiX - XhatMean and ChiY-YhatMean");
        // tempPx.print(3, 2);
        // tempPy.print(3, 2);

        Matrix tempPxw = tempPx.times(wc.get(i));
        Matrix tempPyw = tempPy.times(wc.get(i));

        tempPx = tempPxw.times(tempPy.transpose());
        tempPy = tempPyw.times(tempPy.transpose());
        UpPy = UpPy.plus(tempPy);
        UpPxy = UpPxy.plus(tempPx);
      }

      // Step 6: Compute Corrections and Update

      // Compute Kalman Gain!
      // System.out.println("Updated Px");
      // UpPx.print(5, 2);
      // System.out.println("Updated Py");
      // UpPy.print(5, 2);
      // System.out.println("Updated Pxy");
      // UpPxy.print(5, 2);
      K = UpPxy.times(UpPy.inverse());
      // System.out.println("Kalman");
      // K.print(5, 2);

      Matrix Mea = new Matrix(3, 1, 0.0);
      Mea.set(0, 0, dMeasure.get(0));
      Mea.set(1, 0, dMeasure.get(1));
      Mea.set(2, 0, dMeasure.get(2));

      Matrix Out = K.times(Mea.minus(YhatMean));
      Out = Out.plus(XhatMean);
      // System.out.println("Out:");
      // Out.print(3, 2);

      Matrix Px = UpPx.minus(K.times(UpPy.times(K.transpose())));

      // Update Stuff!
      // Push the P to the controller
      Matrix OutP = P.copy();
      OutP.setMatrix(0, 2, 0, 2, Px);
      X.setMatrix(0, 2, 0, 0, Out);

      Residual = XhatMean.minus(Out);
      cController.inputState(OutP, Residual);
      // cController.setL(L);

      cController.startProcess();
      while (!cController.finishedProcess()) {
        try {
          Thread.sleep(10);
        } catch (InterruptedException e) {
          e.printStackTrace();
        }
      }

      // System.out.println("Post Greeks: " + cController.getAlpha() + " ,
      // "+ cController.getBeta());

      dGreek.set(0, cController.getAlpha());
      dGreek.set(1, cController.getBeta());
      dGreek.set(2, cController.getKappa());
      P = cController.getP();

      // System.out.println("P is post Process:");
      // P.print(3, 2);

      StepDone = true;
    }
  public static void main(String argv[]) {
    Matrix A, B, C, Z, O, I, R, S, X, SUB, M, T, SQ, DEF, SOL;
    // Uncomment this to test IO in a different locale.
    // Locale.setDefault(Locale.GERMAN);
    int errorCount = 0;
    int warningCount = 0;
    double tmp, s;
    double[] columnwise = {1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12.};
    double[] rowwise = {1., 4., 7., 10., 2., 5., 8., 11., 3., 6., 9., 12.};
    double[][] avals = {{1., 4., 7., 10.}, {2., 5., 8., 11.}, {3., 6., 9., 12.}};
    double[][] rankdef = avals;
    double[][] tvals = {{1., 2., 3.}, {4., 5., 6.}, {7., 8., 9.}, {10., 11., 12.}};
    double[][] subavals = {{5., 8., 11.}, {6., 9., 12.}};
    double[][] rvals = {{1., 4., 7.}, {2., 5., 8., 11.}, {3., 6., 9., 12.}};
    double[][] pvals = {{4., 1., 1.}, {1., 2., 3.}, {1., 3., 6.}};
    double[][] ivals = {{1., 0., 0., 0.}, {0., 1., 0., 0.}, {0., 0., 1., 0.}};
    double[][] evals = {
      {0., 1., 0., 0.}, {1., 0., 2.e-7, 0.}, {0., -2.e-7, 0., 1.}, {0., 0., 1., 0.}
    };
    double[][] square = {{166., 188., 210.}, {188., 214., 240.}, {210., 240., 270.}};
    double[][] sqSolution = {{13.}, {15.}};
    double[][] condmat = {{1., 3.}, {7., 9.}};
    double[][] badeigs = {
      {0, 0, 0, 0, 0}, {0, 0, 0, 0, 1}, {0, 0, 0, 1, 0}, {1, 1, 0, 0, 1}, {1, 0, 1, 0, 1}
    };
    int rows = 3, cols = 4;
    int invalidld = 5; /* should trigger bad shape for construction with val */
    int raggedr = 0; /* (raggedr,raggedc) should be out of bounds in ragged array */
    int raggedc = 4;
    int validld = 3; /* leading dimension of intended test Matrices */
    int nonconformld = 4; /* leading dimension which is valid, but nonconforming */
    int ib = 1, ie = 2, jb = 1, je = 3; /* index ranges for sub Matrix */
    int[] rowindexset = {1, 2};
    int[] badrowindexset = {1, 3};
    int[] columnindexset = {1, 2, 3};
    int[] badcolumnindexset = {1, 2, 4};
    double columnsummax = 33.;
    double rowsummax = 30.;
    double sumofdiagonals = 15;
    double sumofsquares = 650;

    /**
     * Constructors and constructor-like methods: double[], int double[][] int, int int, int, double
     * int, int, double[][] constructWithCopy(double[][]) random(int,int) identity(int)
     */
    print("\nTesting constructors and constructor-like methods...\n");
    try {
      /** check that exception is thrown in packed constructor with invalid length * */
      A = new Matrix(columnwise, invalidld);
      errorCount =
          try_failure(
              errorCount,
              "Catch invalid length in packed constructor... ",
              "exception not thrown for invalid input");
    } catch (IllegalArgumentException e) {
      try_success("Catch invalid length in packed constructor... ", e.getMessage());
    }
    try {
      /** check that exception is thrown in default constructor if input array is 'ragged' * */
      A = new Matrix(rvals);
      tmp = A.get(raggedr, raggedc);
    } catch (IllegalArgumentException e) {
      try_success("Catch ragged input to default constructor... ", e.getMessage());
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "Catch ragged input to constructor... ",
              "exception not thrown in construction...ArrayIndexOutOfBoundsException thrown later");
    }
    try {
      /** check that exception is thrown in constructWithCopy if input array is 'ragged' * */
      A = Matrix.constructWithCopy(rvals);
      tmp = A.get(raggedr, raggedc);
    } catch (IllegalArgumentException e) {
      try_success("Catch ragged input to constructWithCopy... ", e.getMessage());
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "Catch ragged input to constructWithCopy... ",
              "exception not thrown in construction...ArrayIndexOutOfBoundsException thrown later");
    }

    A = new Matrix(columnwise, validld);
    B = new Matrix(avals);
    tmp = B.get(0, 0);
    avals[0][0] = 0.0;
    C = B.minus(A);
    avals[0][0] = tmp;
    B = Matrix.constructWithCopy(avals);
    tmp = B.get(0, 0);
    avals[0][0] = 0.0;
    if ((tmp - B.get(0, 0)) != 0.0) {
      /** check that constructWithCopy behaves properly * */
      errorCount =
          try_failure(
              errorCount, "constructWithCopy... ", "copy not effected... data visible outside");
    } else {
      try_success("constructWithCopy... ", "");
    }
    avals[0][0] = columnwise[0];
    I = new Matrix(ivals);
    try {
      check(I, Matrix.identity(3, 4));
      try_success("identity... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "identity... ", "identity Matrix not successfully created");
    }

    /**
     * Access Methods: getColumnDimension() getRowDimension() getArray() getArrayCopy()
     * getColumnPackedCopy() getRowPackedCopy() get(int,int) getMatrix(int,int,int,int)
     * getMatrix(int,int,int[]) getMatrix(int[],int,int) getMatrix(int[],int[]) set(int,int,double)
     * setMatrix(int,int,int,int,Matrix) setMatrix(int,int,int[],Matrix)
     * setMatrix(int[],int,int,Matrix) setMatrix(int[],int[],Matrix)
     */
    print("\nTesting access methods...\n");

    /** Various get methods: */
    B = new Matrix(avals);
    if (B.getRowDimension() != rows) {
      errorCount = try_failure(errorCount, "getRowDimension... ", "");
    } else {
      try_success("getRowDimension... ", "");
    }
    if (B.getColumnDimension() != cols) {
      errorCount = try_failure(errorCount, "getColumnDimension... ", "");
    } else {
      try_success("getColumnDimension... ", "");
    }
    B = new Matrix(avals);
    double[][] barray = B.getArray();
    if (barray != avals) {
      errorCount = try_failure(errorCount, "getArray... ", "");
    } else {
      try_success("getArray... ", "");
    }
    barray = B.getArrayCopy();
    if (barray == avals) {
      errorCount = try_failure(errorCount, "getArrayCopy... ", "data not (deep) copied");
    }
    try {
      check(barray, avals);
      try_success("getArrayCopy... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "getArrayCopy... ", "data not successfully (deep) copied");
    }
    double[] bpacked = B.getColumnPackedCopy();
    try {
      check(bpacked, columnwise);
      try_success("getColumnPackedCopy... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "getColumnPackedCopy... ",
              "data not successfully (deep) copied by columns");
    }
    bpacked = B.getRowPackedCopy();
    try {
      check(bpacked, rowwise);
      try_success("getRowPackedCopy... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount, "getRowPackedCopy... ", "data not successfully (deep) copied by rows");
    }
    try {
      tmp = B.get(B.getRowDimension(), B.getColumnDimension() - 1);
      errorCount =
          try_failure(
              errorCount, "get(int,int)... ", "OutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        tmp = B.get(B.getRowDimension() - 1, B.getColumnDimension());
        errorCount =
            try_failure(
                errorCount, "get(int,int)... ", "OutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("get(int,int)... OutofBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount, "get(int,int)... ", "OutOfBoundsException expected but not thrown");
    }
    try {
      if (B.get(B.getRowDimension() - 1, B.getColumnDimension() - 1)
          != avals[B.getRowDimension() - 1][B.getColumnDimension() - 1]) {
        errorCount =
            try_failure(
                errorCount, "get(int,int)... ", "Matrix entry (i,j) not successfully retreived");
      } else {
        try_success("get(int,int)... ", "");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(errorCount, "get(int,int)... ", "Unexpected ArrayIndexOutOfBoundsException");
    }
    SUB = new Matrix(subavals);
    try {
      M = B.getMatrix(ib, ie + B.getRowDimension() + 1, jb, je);
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int,int)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        M = B.getMatrix(ib, ie, jb, je + B.getColumnDimension() + 1);
        errorCount =
            try_failure(
                errorCount,
                "getMatrix(int,int,int,int)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("getMatrix(int,int,int,int)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int,int)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      M = B.getMatrix(ib, ie, jb, je);
      try {
        check(SUB, M);
        try_success("getMatrix(int,int,int,int)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount,
                "getMatrix(int,int,int,int)... ",
                "submatrix not successfully retreived");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int,int)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }

    try {
      M = B.getMatrix(ib, ie, badcolumnindexset);
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int[])... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        M = B.getMatrix(ib, ie + B.getRowDimension() + 1, columnindexset);
        errorCount =
            try_failure(
                errorCount,
                "getMatrix(int,int,int[])... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("getMatrix(int,int,int[])... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int[])... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      M = B.getMatrix(ib, ie, columnindexset);
      try {
        check(SUB, M);
        try_success("getMatrix(int,int,int[])... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount, "getMatrix(int,int,int[])... ", "submatrix not successfully retreived");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int,int,int[])... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }
    try {
      M = B.getMatrix(badrowindexset, jb, je);
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int,int)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        M = B.getMatrix(rowindexset, jb, je + B.getColumnDimension() + 1);
        errorCount =
            try_failure(
                errorCount,
                "getMatrix(int[],int,int)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("getMatrix(int[],int,int)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int,int)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      M = B.getMatrix(rowindexset, jb, je);
      try {
        check(SUB, M);
        try_success("getMatrix(int[],int,int)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount, "getMatrix(int[],int,int)... ", "submatrix not successfully retreived");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int,int)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }
    try {
      M = B.getMatrix(badrowindexset, columnindexset);
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int[])... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        M = B.getMatrix(rowindexset, badcolumnindexset);
        errorCount =
            try_failure(
                errorCount,
                "getMatrix(int[],int[])... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("getMatrix(int[],int[])... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int[])... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      M = B.getMatrix(rowindexset, columnindexset);
      try {
        check(SUB, M);
        try_success("getMatrix(int[],int[])... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount, "getMatrix(int[],int[])... ", "submatrix not successfully retreived");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      errorCount =
          try_failure(
              errorCount,
              "getMatrix(int[],int[])... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }

    /** Various set methods: */
    try {
      B.set(B.getRowDimension(), B.getColumnDimension() - 1, 0.);
      errorCount =
          try_failure(
              errorCount,
              "set(int,int,double)... ",
              "OutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        B.set(B.getRowDimension() - 1, B.getColumnDimension(), 0.);
        errorCount =
            try_failure(
                errorCount,
                "set(int,int,double)... ",
                "OutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("set(int,int,double)... OutofBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "set(int,int,double)... ",
              "OutOfBoundsException expected but not thrown");
    }
    try {
      B.set(ib, jb, 0.);
      tmp = B.get(ib, jb);
      try {
        check(tmp, 0.);
        try_success("set(int,int,double)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount, "set(int,int,double)... ", "Matrix element not successfully set");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
      errorCount =
          try_failure(
              errorCount, "set(int,int,double)... ", "Unexpected ArrayIndexOutOfBoundsException");
    }
    M = new Matrix(2, 3, 0.);
    try {
      B.setMatrix(ib, ie + B.getRowDimension() + 1, jb, je, M);
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int,int,Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        B.setMatrix(ib, ie, jb, je + B.getColumnDimension() + 1, M);
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int,int,int,int,Matrix)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("setMatrix(int,int,int,int,Matrix)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int,int,Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      B.setMatrix(ib, ie, jb, je, M);
      try {
        check(M.minus(B.getMatrix(ib, ie, jb, je)), M);
        try_success("setMatrix(int,int,int,int,Matrix)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int,int,int,int,Matrix)... ",
                "submatrix not successfully set");
      }
      B.setMatrix(ib, ie, jb, je, SUB);
    } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int,int,Matrix)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }
    try {
      B.setMatrix(ib, ie + B.getRowDimension() + 1, columnindexset, M);
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int[],Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        B.setMatrix(ib, ie, badcolumnindexset, M);
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int,int,int[],Matrix)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("setMatrix(int,int,int[],Matrix)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int[],Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      B.setMatrix(ib, ie, columnindexset, M);
      try {
        check(M.minus(B.getMatrix(ib, ie, columnindexset)), M);
        try_success("setMatrix(int,int,int[],Matrix)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int,int,int[],Matrix)... ",
                "submatrix not successfully set");
      }
      B.setMatrix(ib, ie, jb, je, SUB);
    } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int,int,int[],Matrix)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }
    try {
      B.setMatrix(rowindexset, jb, je + B.getColumnDimension() + 1, M);
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int,int,Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        B.setMatrix(badrowindexset, jb, je, M);
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int[],int,int,Matrix)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("setMatrix(int[],int,int,Matrix)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int,int,Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      B.setMatrix(rowindexset, jb, je, M);
      try {
        check(M.minus(B.getMatrix(rowindexset, jb, je)), M);
        try_success("setMatrix(int[],int,int,Matrix)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int[],int,int,Matrix)... ",
                "submatrix not successfully set");
      }
      B.setMatrix(ib, ie, jb, je, SUB);
    } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int,int,Matrix)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }
    try {
      B.setMatrix(rowindexset, badcolumnindexset, M);
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int[],Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    } catch (java.lang.ArrayIndexOutOfBoundsException e) {
      try {
        B.setMatrix(badrowindexset, columnindexset, M);
        errorCount =
            try_failure(
                errorCount,
                "setMatrix(int[],int[],Matrix)... ",
                "ArrayIndexOutOfBoundsException expected but not thrown");
      } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
        try_success("setMatrix(int[],int[],Matrix)... ArrayIndexOutOfBoundsException... ", "");
      }
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int[],Matrix)... ",
              "ArrayIndexOutOfBoundsException expected but not thrown");
    }
    try {
      B.setMatrix(rowindexset, columnindexset, M);
      try {
        check(M.minus(B.getMatrix(rowindexset, columnindexset)), M);
        try_success("setMatrix(int[],int[],Matrix)... ", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount, "setMatrix(int[],int[],Matrix)... ", "submatrix not successfully set");
      }
    } catch (java.lang.ArrayIndexOutOfBoundsException e1) {
      errorCount =
          try_failure(
              errorCount,
              "setMatrix(int[],int[],Matrix)... ",
              "Unexpected ArrayIndexOutOfBoundsException");
    }

    /**
     * Array-like methods: minus minusEquals plus plusEquals arrayLeftDivide arrayLeftDivideEquals
     * arrayRightDivide arrayRightDivideEquals arrayTimes arrayTimesEquals uminus
     */
    print("\nTesting array-like methods...\n");
    S = new Matrix(columnwise, nonconformld);
    R = Matrix.random(A.getRowDimension(), A.getColumnDimension());
    A = R;
    try {
      S = A.minus(S);
      errorCount =
          try_failure(errorCount, "minus conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("minus conformance check... ", "");
    }
    if (A.minus(R).norm1() != 0.) {
      errorCount =
          try_failure(
              errorCount,
              "minus... ",
              "(difference of identical Matrices is nonzero,\nSubsequent use of minus should be suspect)");
    } else {
      try_success("minus... ", "");
    }
    A = R.copy();
    A.minusEquals(R);
    Z = new Matrix(A.getRowDimension(), A.getColumnDimension());
    try {
      A.minusEquals(S);
      errorCount =
          try_failure(errorCount, "minusEquals conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("minusEquals conformance check... ", "");
    }
    if (A.minus(Z).norm1() != 0.) {
      errorCount =
          try_failure(
              errorCount,
              "minusEquals... ",
              "(difference of identical Matrices is nonzero,\nSubsequent use of minus should be suspect)");
    } else {
      try_success("minusEquals... ", "");
    }

    A = R.copy();
    B = Matrix.random(A.getRowDimension(), A.getColumnDimension());
    C = A.minus(B);
    try {
      S = A.plus(S);
      errorCount =
          try_failure(errorCount, "plus conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("plus conformance check... ", "");
    }
    try {
      check(C.plus(B), A);
      try_success("plus... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "plus... ", "(C = A - B, but C + B != A)");
    }
    C = A.minus(B);
    C.plusEquals(B);
    try {
      A.plusEquals(S);
      errorCount =
          try_failure(errorCount, "plusEquals conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("plusEquals conformance check... ", "");
    }
    try {
      check(C, A);
      try_success("plusEquals... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "plusEquals... ", "(C = A - B, but C = C + B != A)");
    }
    A = R.uminus();
    try {
      check(A.plus(R), Z);
      try_success("uminus... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "uminus... ", "(-A + A != zeros)");
    }
    A = R.copy();
    O = new Matrix(A.getRowDimension(), A.getColumnDimension(), 1.0);
    C = A.arrayLeftDivide(R);
    try {
      S = A.arrayLeftDivide(S);
      errorCount =
          try_failure(
              errorCount, "arrayLeftDivide conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayLeftDivide conformance check... ", "");
    }
    try {
      check(C, O);
      try_success("arrayLeftDivide... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "arrayLeftDivide... ", "(M.\\M != ones)");
    }
    try {
      A.arrayLeftDivideEquals(S);
      errorCount =
          try_failure(
              errorCount,
              "arrayLeftDivideEquals conformance check... ",
              "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayLeftDivideEquals conformance check... ", "");
    }
    A.arrayLeftDivideEquals(R);
    try {
      check(A, O);
      try_success("arrayLeftDivideEquals... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "arrayLeftDivideEquals... ", "(M.\\M != ones)");
    }
    A = R.copy();
    try {
      A.arrayRightDivide(S);
      errorCount =
          try_failure(
              errorCount, "arrayRightDivide conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayRightDivide conformance check... ", "");
    }
    C = A.arrayRightDivide(R);
    try {
      check(C, O);
      try_success("arrayRightDivide... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "arrayRightDivide... ", "(M./M != ones)");
    }
    try {
      A.arrayRightDivideEquals(S);
      errorCount =
          try_failure(
              errorCount,
              "arrayRightDivideEquals conformance check... ",
              "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayRightDivideEquals conformance check... ", "");
    }
    A.arrayRightDivideEquals(R);
    try {
      check(A, O);
      try_success("arrayRightDivideEquals... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "arrayRightDivideEquals... ", "(M./M != ones)");
    }
    A = R.copy();
    B = Matrix.random(A.getRowDimension(), A.getColumnDimension());
    try {
      S = A.arrayTimes(S);
      errorCount =
          try_failure(errorCount, "arrayTimes conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayTimes conformance check... ", "");
    }
    C = A.arrayTimes(B);
    try {
      check(C.arrayRightDivideEquals(B), A);
      try_success("arrayTimes... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "arrayTimes... ", "(A = R, C = A.*B, but C./B != A)");
    }
    try {
      A.arrayTimesEquals(S);
      errorCount =
          try_failure(
              errorCount, "arrayTimesEquals conformance check... ", "nonconformance not raised");
    } catch (IllegalArgumentException e) {
      try_success("arrayTimesEquals conformance check... ", "");
    }
    A.arrayTimesEquals(B);
    try {
      check(A.arrayRightDivideEquals(B), R);
      try_success("arrayTimesEquals... ", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "arrayTimesEquals... ", "(A = R, A = A.*B, but A./B != R)");
    }

    /** I/O methods: read print serializable: writeObject readObject */
    print("\nTesting I/O methods...\n");
    try {
      DecimalFormat fmt = new DecimalFormat("0.0000E00");
      fmt.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));

      PrintWriter FILE = new PrintWriter(new FileOutputStream("JamaTestMatrix.out"));
      A.print(FILE, fmt, 10);
      FILE.close();
      R = Matrix.read(new BufferedReader(new FileReader("JamaTestMatrix.out")));
      if (A.minus(R).norm1() < .001) {
        try_success("print()/read()...", "");
      } else {
        errorCount =
            try_failure(
                errorCount,
                "print()/read()...",
                "Matrix read from file does not match Matrix printed to file");
      }
    } catch (java.io.IOException ioe) {
      warningCount =
          try_warning(
              warningCount,
              "print()/read()...",
              "unexpected I/O error, unable to run print/read test;  check write permission in current directory and retry");
    } catch (Exception e) {
      try {
        e.printStackTrace(System.out);
        warningCount =
            try_warning(
                warningCount,
                "print()/read()...",
                "Formatting error... will try JDK1.1 reformulation...");
        DecimalFormat fmt = new DecimalFormat("0.0000");
        PrintWriter FILE = new PrintWriter(new FileOutputStream("JamaTestMatrix.out"));
        A.print(FILE, fmt, 10);
        FILE.close();
        R = Matrix.read(new BufferedReader(new FileReader("JamaTestMatrix.out")));
        if (A.minus(R).norm1() < .001) {
          try_success("print()/read()...", "");
        } else {
          errorCount =
              try_failure(
                  errorCount,
                  "print()/read() (2nd attempt) ...",
                  "Matrix read from file does not match Matrix printed to file");
        }
      } catch (java.io.IOException ioe) {
        warningCount =
            try_warning(
                warningCount,
                "print()/read()...",
                "unexpected I/O error, unable to run print/read test;  check write permission in current directory and retry");
      }
    }

    R = Matrix.random(A.getRowDimension(), A.getColumnDimension());
    String tmpname = "TMPMATRIX.serial";
    try {
      @SuppressWarnings("resource")
      ObjectOutputStream out = new ObjectOutputStream(new FileOutputStream(tmpname));
      out.writeObject(R);
      @SuppressWarnings("resource")
      ObjectInputStream sin = new ObjectInputStream(new FileInputStream(tmpname));
      A = (Matrix) sin.readObject();

      try {
        check(A, R);
        try_success("writeObject(Matrix)/readObject(Matrix)...", "");
      } catch (java.lang.RuntimeException e) {
        errorCount =
            try_failure(
                errorCount,
                "writeObject(Matrix)/readObject(Matrix)...",
                "Matrix not serialized correctly");
      }
    } catch (java.io.IOException ioe) {
      warningCount =
          try_warning(
              warningCount,
              "writeObject()/readObject()...",
              "unexpected I/O error, unable to run serialization test;  check write permission in current directory and retry");
    } catch (Exception e) {
      errorCount =
          try_failure(
              errorCount,
              "writeObject(Matrix)/readObject(Matrix)...",
              "unexpected error in serialization test");
    }

    /**
     * LA methods: transpose times cond rank det trace norm1 norm2 normF normInf solve
     * solveTranspose inverse chol eig lu qr svd
     */
    print("\nTesting linear algebra methods...\n");
    A = new Matrix(columnwise, 3);
    T = new Matrix(tvals);
    T = A.transpose();
    try {
      check(A.transpose(), T);
      try_success("transpose...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "transpose()...", "transpose unsuccessful");
    }
    A.transpose();
    try {
      check(A.norm1(), columnsummax);
      try_success("norm1...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "norm1()...", "incorrect norm calculation");
    }
    try {
      check(A.normInf(), rowsummax);
      try_success("normInf()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "normInf()...", "incorrect norm calculation");
    }
    try {
      check(A.normF(), Math.sqrt(sumofsquares));
      try_success("normF...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "normF()...", "incorrect norm calculation");
    }
    try {
      check(A.trace(), sumofdiagonals);
      try_success("trace()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "trace()...", "incorrect trace calculation");
    }
    try {
      check(A.getMatrix(0, A.getRowDimension() - 1, 0, A.getRowDimension() - 1).det(), 0.);
      try_success("det()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "det()...", "incorrect determinant calculation");
    }
    SQ = new Matrix(square);
    try {
      check(A.times(A.transpose()), SQ);
      try_success("times(Matrix)...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount, "times(Matrix)...", "incorrect Matrix-Matrix product calculation");
    }
    try {
      check(A.times(0.), Z);
      try_success("times(double)...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount, "times(double)...", "incorrect Matrix-scalar product calculation");
    }

    A = new Matrix(columnwise, 4);
    QRDecomposition QR = A.qr();
    R = QR.getR();
    try {
      check(A, QR.getQ().times(R));
      try_success("QRDecomposition...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "QRDecomposition...", "incorrect QR decomposition calculation");
    }
    SingularValueDecomposition SVD = A.svd();
    try {
      check(A, SVD.getU().times(SVD.getS().times(SVD.getV().transpose())));
      try_success("SingularValueDecomposition...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "SingularValueDecomposition...",
              "incorrect singular value decomposition calculation");
    }
    DEF = new Matrix(rankdef);
    try {
      check(DEF.rank(), Math.min(DEF.getRowDimension(), DEF.getColumnDimension()) - 1);
      try_success("rank()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "rank()...", "incorrect rank calculation");
    }
    B = new Matrix(condmat);
    SVD = B.svd();
    double[] singularvalues = SVD.getSingularValues();
    try {
      check(
          B.cond(),
          singularvalues[0]
              / singularvalues[Math.min(B.getRowDimension(), B.getColumnDimension()) - 1]);
      try_success("cond()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "cond()...", "incorrect condition number calculation");
    }
    int n = A.getColumnDimension();
    A = A.getMatrix(0, n - 1, 0, n - 1);
    A.set(0, 0, 0.);
    LUDecomposition LU = A.lu();
    try {
      check(A.getMatrix(LU.getPivot(), 0, n - 1), LU.getL().times(LU.getU()));
      try_success("LUDecomposition...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "LUDecomposition...", "incorrect LU decomposition calculation");
    }
    X = A.inverse();
    try {
      check(A.times(X), Matrix.identity(3, 3));
      try_success("inverse()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "inverse()...", "incorrect inverse calculation");
    }
    O = new Matrix(SUB.getRowDimension(), 1, 1.0);
    SOL = new Matrix(sqSolution);
    SQ = SUB.getMatrix(0, SUB.getRowDimension() - 1, 0, SUB.getRowDimension() - 1);
    try {
      check(SQ.solve(SOL), O);
      try_success("solve()...", "");
    } catch (java.lang.IllegalArgumentException e1) {
      errorCount = try_failure(errorCount, "solve()...", e1.getMessage());
    } catch (java.lang.RuntimeException e) {
      errorCount = try_failure(errorCount, "solve()...", e.getMessage());
    }
    A = new Matrix(pvals);
    CholeskyDecomposition Chol = A.chol();
    Matrix L = Chol.getL();
    try {
      check(A, L.times(L.transpose()));
      try_success("CholeskyDecomposition...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "CholeskyDecomposition...",
              "incorrect Cholesky decomposition calculation");
    }
    X = Chol.solve(Matrix.identity(3, 3));
    try {
      check(A.times(X), Matrix.identity(3, 3));
      try_success("CholeskyDecomposition solve()...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "CholeskyDecomposition solve()...",
              "incorrect Choleskydecomposition solve calculation");
    }
    EigenvalueDecomposition Eig = A.eig();
    Matrix D = Eig.getD();
    Matrix V = Eig.getV();
    try {
      check(A.times(V), V.times(D));
      try_success("EigenvalueDecomposition (symmetric)...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "EigenvalueDecomposition (symmetric)...",
              "incorrect symmetric Eigenvalue decomposition calculation");
    }
    A = new Matrix(evals);
    Eig = A.eig();
    D = Eig.getD();
    V = Eig.getV();
    try {
      check(A.times(V), V.times(D));
      try_success("EigenvalueDecomposition (nonsymmetric)...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(
              errorCount,
              "EigenvalueDecomposition (nonsymmetric)...",
              "incorrect nonsymmetric Eigenvalue decomposition calculation");
    }

    try {
      print("\nTesting Eigenvalue; If this hangs, we've failed\n");
      Matrix bA = new Matrix(badeigs);
      EigenvalueDecomposition bEig = bA.eig();
      try_success("EigenvalueDecomposition (hang)...", "");
    } catch (java.lang.RuntimeException e) {
      errorCount =
          try_failure(errorCount, "EigenvalueDecomposition (hang)...", "incorrect termination");
    }

    print("\nTestMatrix completed.\n");
    print("Total errors reported: " + Integer.toString(errorCount) + "\n");
    print("Total warnings reported: " + Integer.toString(warningCount) + "\n");
  }
Пример #11
0
 public static PImage apply(Matrix H, PImage img, Point dstDimension) {
   return invert(H.inverse(), img, dstDimension);
 }
Пример #12
0
  public static Matrix find(Stack<?> from, Stack<?> to) {

    //		System.out.println("Homographie:");
    //		System.out.println("From:");
    //		System.out.println("   "+from);
    //		System.out.println("To:");
    //		System.out.println("   "+to);

    Stack fromC = new Stack(), toC = new Stack();
    for (Object p : from) {
      fromC.push(p);
    }
    for (Object p : to) {
      toC.push(p);
    }

    int n = from.size();
    if (n < 4) {
      throw new Error("Homographie.find: Not enought point");
    }
    if (n != to.size()) {
      throw new Error("Homographie.find: The 2 args don't have the same number of point");
    }
    if (!((from.peek() instanceof Pt2 && from.peek() instanceof Pt2)
        || (from.peek() instanceof Pt3 && from.peek() instanceof Pt3))) {
      throw new Error("Homographie.find: The 2 args don't have the same class, among Pt or Vect");
    }
    boolean typeIsPt = from.peek() instanceof Pt2;
    // On definit la matrice A et Q
    double[][] A_array = new double[2 * n][8];
    double[][] Q_array = new double[2 * n][1];
    int i = 0;
    while (!fromC.isEmpty()) {
      Pt2 p = (typeIsPt) ? (Pt2) fromC.pop() : new Pt2((Pt3) fromC.pop());
      Pt2 q = (typeIsPt) ? (Pt2) toC.pop() : new Pt2((Pt3) toC.pop());
      //		while (!from.isEmpty()) {
      //			Pt2 p = (typeIsPt) ? (Pt2) from.pop() : new Pt2((Pt3) from.pop());
      //			Pt2 q = (typeIsPt) ? (Pt2)   to.pop() : new Pt2((Pt3)   to.pop());
      double[] l1 = {p.x, p.y, 1, 0, 0, 0, -p.x * q.x, -p.y * q.x};
      double[] l2 = {0, 0, 0, p.x, p.y, 1, -p.x * q.y, -p.y * q.y};
      A_array[i] = l1;
      A_array[i + 1] = l2;
      Q_array[i][0] = q.x;
      Q_array[i + 1][0] = q.y;
      i += 2;
    }
    Matrix A = new Matrix(A_array);
    Matrix Q = new Matrix(Q_array);
    // On calcule son inverse ou son pseudo-inverse B
    Matrix B;
    if (n == 4) {
      B = A.inverse();
    } else {
      Matrix At = A.transpose();
      B = At.times(A).inverse().times(At);
    }
    // On calcule l'homographie
    Matrix h_vert = B.times(Q);
    double[][] H_array = {
      {h_vert.get(0, 0), h_vert.get(1, 0), h_vert.get(2, 0)},
      {h_vert.get(3, 0), h_vert.get(4, 0), h_vert.get(5, 0)},
      {h_vert.get(6, 0), h_vert.get(7, 0), 1}
    };
    Matrix H = new Matrix(H_array);
    return (typeIsPt) ? H : H.inverse().transpose();
  }
Пример #13
0
 public static PImage apply(Matrix H, PImage img) {
   return invert(H.inverse(), img);
 }
Пример #14
0
  public double calcularCC(Componente barra, HashMap<Componente, Double> barraTensionCC) {
    /*
     * Busca el valor de cc de la barra seleccionda, y los voltaje de cada
     * barra directamente relacionada a la barra seleccionda
     */

    // calcular matrizAdmitancia
    llenarMatrizAdmitancia();

    double calculoCC = 0;
    // El sistema busca el valor de la barra seleccionada en la matriz
    // inversa.
    int posBarra = barraPos.get(barra);
    System.out.println("posBarra" + posBarra);

    // carga matriz inversa con JAMA
    Matrix matrizCalculo = new Matrix(matrizAdmitancia);
    // double det = matrizCalculo.det();
    // System.out.println("DET: "+det);

    Matrix matrizInv = matrizCalculo.inverse();
    System.out.println("inversa:");
    matrizInv.print(5, 3);

    double matrizInversa[][] = matrizInv.getArray();

    /*
     * El sistema aplica esta formula para conocer la corriente de
     * cortocircuito en esa barra: If=Vref/Zkk, donde Vref es el voltaje de
     * referencia de la barra seleccionada, y Zkk es el elemento de la
     * matriz inversa que representa la barra.
     */
    double vref = ((Barra) barra).getVoltajeReferencia();
    double zkk = matrizInversa[posBarra][posBarra];
    double valorIf = vref / zkk;
    calculoCC = valorIf;
    System.out.println(
        "Calculo de CC en barra " + barra.getId() + ": " + valorIf + " = " + vref + "/" + zkk);

    /*
     * Por cada barra que esta directamente conectada a la barra
     * seleccionada,el sistema aplica esta formula para conocer el voltaje
     * de la barra: Vj=Vref-Zjk*If,donde Vref es el voltaje de referencia de
     * la barra seleccionada,Zjk es el elemento de la matriz inversa que
     * representa la barra que esta conectada a la barraseleccionada, e If
     * es la corriente de cortocircuito de la barra seleccionada (calculada
     * en el paso anterior).
     */
    double vj = 0;
    double zjk = 0;

    // recorre la matriz de admitancia en la columna de la barra seleccionada,
    // en cada valor <>0 indica que hay una barra directamente conectada
    for (int cont = 0; cont < matrizAdmitancia.length; cont++) {
      if ((matrizAdmitancia[posBarra][cont] != 0) && (posBarra != cont)) {
        zjk = matrizInversa[posBarra][cont];
        Componente barraConectada = barras.get(cont); // ojo		
        vj = vref - (zjk * valorIf);
        barraTensionCC.put(barraConectada, vj);
      }
    }
    return calculoCC;
  }
Пример #15
0
  private double generalizedCorrelationRatio(SampleIterator it, int inputDim, int out) {
    Map<Double, Integer> n_y = new HashMap<>();
    Map<Double, MultivariateSummaryStatistics> stat_y = new HashMap<>();
    List<RealMatrix> x = new ArrayList<>();
    MultivariateSummaryStatistics stat = new MultivariateSummaryStatistics(inputDim, unbiased);

    for (int i = 0; i < maxSamples && it.hasNext(); i++) {
      Sample sample = it.next();
      double[] input = sample.getEncodedInput().toArray();
      double output = sample.getEncodedOutput().getEntry(out);
      if (!n_y.containsKey(output)) {
        n_y.put(output, 0);
        stat_y.put(output, new MultivariateSummaryStatistics(inputDim, unbiased));
      }

      injectNoise(input);
      n_y.put(output, n_y.get(output) + 1);
      stat_y.get(output).addValue(input);
      x.add(new Array2DRowRealMatrix(input));
      stat.addValue(input);
    }

    RealMatrix x_sum = new Array2DRowRealMatrix(stat.getSum());
    Map<Double, RealMatrix> x_y_sum = new HashMap<>();
    for (Entry<Double, MultivariateSummaryStatistics> entry : stat_y.entrySet()) {
      x_y_sum.put(entry.getKey(), new Array2DRowRealMatrix(entry.getValue().getSum()));
    }

    RealMatrix H = new Array2DRowRealMatrix(inputDim, inputDim);
    RealMatrix temp = new Array2DRowRealMatrix(inputDim, inputDim);

    for (double key : n_y.keySet()) {
      temp =
          temp.add(
              x_y_sum
                  .get(key)
                  .multiply(x_y_sum.get(key).transpose())
                  .scalarMultiply(1.0 / n_y.get(key)));
    }
    H = temp.subtract(x_sum.multiply(x_sum.transpose()).scalarMultiply(1.0 / x.size()));

    RealMatrix E = new Array2DRowRealMatrix(inputDim, inputDim);
    for (RealMatrix m : x) {
      E = E.add(m.multiply(m.transpose()));
    }
    E = E.subtract(temp);

    List<Integer> zeroColumns = findZeroColumns(E);
    E = removeZeroColumns(E, zeroColumns);
    H = removeZeroColumns(H, zeroColumns);

    Matrix JE = new Matrix(E.getData());
    Matrix JH = new Matrix(H.getData());

    if (JE.rank() < JE.getRowDimension()) {
      Log.write(this, "Some error occurred (E matrix is singular)");
      return -1;
    } else {
      double lambda;
      if (useEigenvalues) {
        Matrix L = JE.inverse().times(JH);
        double[] eigs = L.eig().getRealEigenvalues();
        Arrays.sort(eigs);

        lambda = 1;
        int nonNullEigs = n_y.keySet().size() - 1;
        for (int i = eigs.length - nonNullEigs; i < eigs.length; i++) {
          if (Math.abs(eigs[i]) < zeroThreshold) {
            Log.write(this, "Some error occurred (E matrix has too many null eigenvalues)");
            return -1;
          }
          lambda *= 1.0 / (1.0 + eigs[i]);
        }
      } else {
        Matrix sum = JE.plus(JH);
        if (sum.rank() < sum.getRowDimension()) {
          Log.write(this, "Some error occourred (E+H is singular");
          return -1;
        }
        lambda = JE.det() / sum.det();
      }

      return Math.sqrt(1 - lambda);
    }
  }
  /*
   * Performs affine adaptation
   */
  boolean calcAffineAdaptation(
      final FImage fimage, EllipticInterestPointData kpt, AbstractStructureTensorIPD ipd) {
    //		DisplayUtilities.createNamedWindow("warp", "Warped Image ROI",true);
    Matrix transf = new Matrix(2, 3); // Transformation matrix
    Point2dImpl c = new Point2dImpl(); // Transformed point
    Point2dImpl p = new Point2dImpl(); // Image point

    Matrix U = Matrix.identity(2, 2); // Normalization matrix

    Matrix Mk = U.copy();
    FImage img_roi, warpedImg = new FImage(1, 1);
    float Qinv = 1, q, si = kpt.scale; // sd = 0.75f * si;
    float kptSize = 2 * 3 * kpt.scale;
    boolean divergence = false, convergence = false;
    int i = 0;

    // Coordinates in image
    int py = (int) kpt.y;
    int px = (int) kpt.x;

    // Roi coordinates
    int roix, roiy;

    // Coordinates in U-trasformation
    int cx = px;
    int cy = py;
    int cxPr = cx;
    int cyPr = cy;

    float radius = kptSize / 2 * 1.4f;
    float half_width, half_height;

    Rectangle roi;

    // Affine adaptation
    while (i <= 10 && !divergence && !convergence) {
      // Transformation matrix
      MatrixUtils.zero(transf);
      transf.setMatrix(0, 1, 0, 1, U);

      kpt.setTransform(U);

      Rectangle boundingBox = new Rectangle();

      double ac_b2 = U.det();
      boundingBox.width = (float) Math.ceil(U.get(1, 1) / ac_b2 * 3 * si * 1.4);
      boundingBox.height = (float) Math.ceil(U.get(0, 0) / ac_b2 * 3 * si * 1.4);

      // Create window around interest point
      half_width = Math.min((float) Math.min(fimage.width - px - 1, px), boundingBox.width);
      half_height = Math.min((float) Math.min(fimage.height - py - 1, py), boundingBox.height);

      if (half_width <= 0 || half_height <= 0) return divergence;

      roix = Math.max(px - (int) boundingBox.width, 0);
      roiy = Math.max(py - (int) boundingBox.height, 0);
      roi = new Rectangle(roix, roiy, px - roix + half_width + 1, py - roiy + half_height + 1);

      // create ROI
      img_roi = fimage.extractROI(roi);

      // Point within the ROI
      p.x = px - roix;
      p.y = py - roiy;

      // Find coordinates of square's angles to find size of warped ellipse's bounding box
      float u00 = (float) U.get(0, 0);
      float u01 = (float) U.get(0, 1);
      float u10 = (float) U.get(1, 0);
      float u11 = (float) U.get(1, 1);

      float minx = u01 * img_roi.height < 0 ? u01 * img_roi.height : 0;
      float miny = u10 * img_roi.width < 0 ? u10 * img_roi.width : 0;
      float maxx =
          (u00 * img_roi.width > u00 * img_roi.width + u01 * img_roi.height
                  ? u00 * img_roi.width
                  : u00 * img_roi.width + u01 * img_roi.height)
              - minx;
      float maxy =
          (u11 * img_roi.width > u10 * img_roi.width + u11 * img_roi.height
                  ? u11 * img_roi.height
                  : u10 * img_roi.width + u11 * img_roi.height)
              - miny;

      // Shift
      transf.set(0, 2, -minx);
      transf.set(1, 2, -miny);

      if (maxx >= 2 * radius + 1 && maxy >= 2 * radius + 1) {
        // Size of normalized window must be 2*radius
        // Transformation
        FImage warpedImgRoi;
        FProjectionProcessor proc = new FProjectionProcessor();
        proc.setMatrix(transf);
        img_roi.accumulateWith(proc);
        warpedImgRoi = proc.performProjection(0, (int) maxx, 0, (int) maxy, null);

        //				DisplayUtilities.displayName(warpedImgRoi.clone().normalise(), "warp");

        // Point in U-Normalized coordinates
        c = p.transform(U);
        cx = (int) (c.x - minx);
        cy = (int) (c.y - miny);

        if (warpedImgRoi.height > 2 * radius + 1 && warpedImgRoi.width > 2 * radius + 1) {
          // Cut around normalized patch
          roix = (int) Math.max(cx - Math.ceil(radius), 0.0);
          roiy = (int) Math.max(cy - Math.ceil(radius), 0.0);
          roi =
              new Rectangle(
                  roix,
                  roiy,
                  cx - roix + (float) Math.min(Math.ceil(radius), warpedImgRoi.width - cx - 1) + 1,
                  cy
                      - roiy
                      + (float) Math.min(Math.ceil(radius), warpedImgRoi.height - cy - 1)
                      + 1);
          warpedImg = warpedImgRoi.extractROI(roi);

          // Coordinates in cutted ROI
          cx = cx - roix;
          cy = cy - roiy;
        } else {
          warpedImg.internalAssign(warpedImgRoi);
        }

        if (logger.getLevel() == Level.DEBUG) {
          displayCurrentPatch(
              img_roi.clone().normalise(),
              p.x,
              p.y,
              warpedImg.clone().normalise(),
              cx,
              cy,
              U,
              si * 3);
        }

        // Integration Scale selection
        si = selIntegrationScale(warpedImg, si, new Pixel(cx, cy));

        // Differentation scale selection
        if (fastDifferentiationScale) {
          ipd = selDifferentiationScaleFast(warpedImg, ipd, si, new Pixel(cx, cy));
        } else {
          ipd = selDifferentiationScale(warpedImg, ipd, si, new Pixel(cx, cy));
        }

        if (ipd.maxima.size() == 0) {
          divergence = true;
          continue;
        }
        // Spatial Localization
        cxPr = cx; // Previous iteration point in normalized window
        cyPr = cy;
        //
        //				float cornMax = 0;
        //				for (int j = 0; j < 3; j++)
        //				{
        //					for (int t = 0; t < 3; t++)
        //					{
        //						float dx2 = Lxm2smooth.pixels[cyPr - 1 + j][cxPr - 1 + t];
        //						float dy2 = Lym2smooth.pixels[cyPr - 1 + j][cxPr - 1 + t];
        //						float dxy = Lxmysmooth.pixels[cyPr - 1 + j][cxPr - 1 + t];
        //						float det = dx2 * dy2 - dxy * dxy;
        //						float tr = dx2 + dy2;
        //						float cornerness = (float) (det - (0.04 * Math.pow(tr, 2)));
        //
        //						if (cornerness > cornMax) {
        //							cornMax = cornerness;
        //							cx = cxPr - 1 + t;
        //							cy = cyPr - 1 + j;
        //						}
        //					}
        //				}

        FValuePixel max = ipd.findMaximum(new Rectangle(cxPr - 1, cyPr - 1, 3, 3));
        cx = max.x;
        cy = max.y;

        // Transform point in image coordinates
        p.x = px;
        p.y = py;

        // Displacement vector
        c.x = cx - cxPr;
        c.y = cy - cyPr;

        // New interest point location in image
        p.translate(c.transform(U.inverse()));
        px = (int) p.x;
        py = (int) p.y;

        q = calcSecondMomentSqrt(ipd, new Pixel(cx, cy), Mk);

        float ratio = 1 - q;

        // if ratio == 1 means q == 0 and one axes equals to 0
        if (!Float.isNaN(ratio) && ratio != 1) {
          // Update U matrix
          U = U.times(Mk);

          Matrix uVal, uV;
          //					EigenvalueDecomposition ueig = U.eig();
          EigenValueVectorPair ueig = MatrixUtils.symmetricEig2x2(U);
          uVal = ueig.getValues();
          uV = ueig.getVectors();

          Qinv = normMaxEval(U, uVal, uV);

          // Keypoint doesn't converge
          if (Qinv >= 6) {
            logger.debug("QInverse too large, feature too edge like, affine divergence!");
            divergence = true;
          } else if (ratio <= 0.05) { // Keypoint converges
            convergence = true;

            // Set transformation matrix
            MatrixUtils.zero(transf);
            transf.setMatrix(0, 1, 0, 1, U);
            // The order here matters, setTransform uses the x and y to calculate a new ellipse
            kpt.x = px;
            kpt.y = py;
            kpt.scale = si;
            kpt.setTransform(U);
            kpt.score = max.value;

            //						ax1 = (float) (1 / Math.abs(uVal.get(1, 1)) * 3 * si);
            //						ax2 = (float) (1 / Math.abs(uVal.get(0, 0)) * 3 * si);
            //						phi = Math.atan(uV.get(1, 1) / uV.get(0, 1));
            //						kpt.axes = new Point2dImpl(ax1, ax2);
            //						kpt.phi = phi;
            //						kpt.centre = new Pixel(px, py);
            //						kpt.si = si;
            //						kpt.size = 2 * 3 * si;

          } else {
            radius = (float) (3 * si * 1.4);
          }
        } else {
          logger.debug("QRatio was close to 0, affine divergence!");
          divergence = true;
        }
      } else {
        logger.debug("Window size has grown too fast, scale divergence!");
        divergence = true;
      }

      ++i;
    }
    if (!divergence && !convergence) {
      logger.debug("Reached max iterations!");
    }
    return convergence;
  }