/**
* Internal function call that stores the result of a matrix multiply into the given
* destinationMatrix.
*
* @param multiplicationMatrix matrix to postmultiply this by
* @param destinationMatrix matrix to store the matrix multiplication result, must have rows ==
* this.getNumRows and columns == multiplicationMatrix.getNumColumns
*/
protected void timesInto(
final AbstractMTJMatrix multiplicationMatrix, AbstractMTJMatrix destinationMatrix) {
int M = this.getNumRows();
int N = multiplicationMatrix.getNumColumns();
if ((M != destinationMatrix.getNumRows()) || (N != destinationMatrix.getNumColumns())) {
throw new DimensionalityMismatchException("Multiplication dimensions do not agree.");
}
this.internalMatrix.mult(multiplicationMatrix.internalMatrix, destinationMatrix.internalMatrix);
}
/**
* Solves for "X" in the equation this * X = B, where X is a DenseMatrix, "this" and "B" will be
* converted to a DenseMatrix (if not already)
*
* @param B AbstractMTJMatrix, will be converted to a DenseMatrix
* @return DenseMatrix of "X" in this * X = B
*/
public final Matrix solve(AbstractMTJMatrix B) {
DenseMatrix X = new DenseMatrix(this.getNumColumns(), B.getNumColumns());
DenseMatrix Bdense;
if (B instanceof DenseMatrix) {
Bdense = (DenseMatrix) B;
} else {
Bdense = new DenseMatrix(B);
}
DenseMatrix Adense;
if (this instanceof DenseMatrix) {
Adense = (DenseMatrix) this;
} else {
Adense = new DenseMatrix(this);
}
boolean usePseudoInverse = false;
try {
Adense.solveInto(Bdense, X);
usePseudoInverse = false;
} catch (MatrixSingularException e) {
Logger.getLogger(AbstractMTJMatrix.class.getName())
.log(Level.WARNING, "AbstractMTJMatrix.solve(): Matrix is singular.");
usePseudoInverse = true;
}
// Sometimes LAPACK will return NaNs or infs as the solutions, but MTJ
// won't throw the exception, so we need to check for this.
// If we detect this, then we'll use a pseudoinverse
if (!usePseudoInverse) {
for (int i = 0; i < X.getNumRows(); i++) {
for (int j = 0; j < X.getNumColumns(); j++) {
double v = X.getElement(i, j);
if (Double.isNaN(v) || Double.isInfinite(v)) {
Logger.getLogger(AbstractMTJMatrix.class.getName())
.log(Level.WARNING, "AbstractMTJMatrix.solve(): Solver produced invalid results.");
usePseudoInverse = true;
break;
}
}
if (usePseudoInverse) {
break;
}
}
}
if (usePseudoInverse) {
// The original LU solver produced a sucky answer, so let's use
// the absurdly expensive SVD least-squares solution
return Adense.pseudoInverse().times(Bdense);
}
return X;
}
/**
* Internal routine for storing a submatrix into and AbstractMTJMatrix. Gets the embedded
* submatrix inside of the Matrix, specified by the inclusive, zero-based indices such that the
* result matrix will have size (maxRow-minRow+1) x (maxColum-minCcolumn+1)
*
* @param minRow Zero-based index into the rows of the Matrix, must be less than or equal to
* maxRow
* @param maxRow Zero-based index into the rows of the Matrix, must be greater than or equal to
* minRow
* @param minColumn Zero-based index into the rows of the Matrix, must be less than or equal to
* maxColumn
* @param maxColumn Zero-based index into the rows of the Matrix, must be greater than or equal to
* minColumn
* @param destinationMatrix the destination submatrix of dimension
* (maxRow-minRow+1)x(maxColumn-minColumn+1)
*/
protected void getSubMatrixInto(
int minRow, int maxRow, int minColumn, int maxColumn, AbstractMTJMatrix destinationMatrix) {
if ((destinationMatrix.getNumRows() != (maxRow - minRow + 1))
|| (destinationMatrix.getNumColumns() != (maxColumn - minColumn + 1))) {
throw new DimensionalityMismatchException("Submatrix is incorrect size.");
}
for (int i = minRow; i <= maxRow; i++) {
for (int j = minColumn; j <= maxColumn; j++) {
destinationMatrix.setElement(i - minRow, j - minColumn, this.getElement(i, j));
}
}
}