/**
* Normalizes a column of the transition-probability matrix
*
* @param A Transition probability matrix to normalize, modified by side effect
* @param j Column of the matrix to normalize
*/
protected static void normalizeTransitionMatrix(Matrix A, final int j) {
double sum = 0.0;
final int k = A.getNumRows();
for (int i = 0; i < k; i++) {
final double value = A.getElement(i, j);
if (value < 0.0) {
throw new IllegalArgumentException("Transition Probabilities must be >= 0.0");
}
sum += A.getElement(i, j);
}
if (sum <= 0.0) {
sum = 1.0;
}
if (sum != 1.0) {
for (int i = 0; i < k; i++) {
A.setElement(i, j, A.getElement(i, j) / sum);
}
}
}
public static Matrix plusInplace(Matrix mat, double etat) {
int nrows = mat.getNumRows();
int ncols = mat.getNumColumns();
for (int r = 0; r < nrows; r++) {
for (int c = 0; c < ncols; c++) {
mat.setElement(r, c, mat.getElement(r, c) + etat);
}
}
return mat;
}
public static double absSum(Matrix mat) {
double tot = 0;
int nrows = mat.getNumRows();
int ncols = mat.getNumColumns();
for (int r = 0; r < nrows; r++) {
for (int c = 0; c < ncols; c++) {
tot += Math.abs(mat.getElement(r, c));
}
}
return tot;
}
public static Matrix abs(Matrix mat) {
Matrix ret = mat.clone();
int nrows = ret.getNumRows();
int ncols = ret.getNumColumns();
for (int r = 0; r < nrows; r++) {
for (int c = 0; c < ncols; c++) {
ret.setElement(r, c, Math.abs(mat.getElement(r, c)));
}
}
return ret;
}
public static Vector diag(Matrix mat) {
Vector ret;
if (mat.getNumColumns() > mat.getNumRows()) {
ret = mat.getRow(0);
} else {
ret = mat.getColumn(0);
}
int rowcol = ret.getDimensionality();
for (int rc = 0; rc < rowcol; rc++) {
ret.setElement(rc, mat.getElement(rc, rc));
}
return ret;
}