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)); }
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; }
/** 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"); */ }
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(); }
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"); }
public static PImage apply(Matrix H, PImage img, Point dstDimension) { return invert(H.inverse(), img, dstDimension); }
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(); }
public static PImage apply(Matrix H, PImage img) { return invert(H.inverse(), img); }
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; }
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; }