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;
}