Peter,
Thanks for the patch! It may take a little while for us to apply it, since we
need to discuss the strategy for extending the 1.0 matrix classes. It would be
great if you could open a Bugzilla ticket and attach the code below in a java
class. Don't worry about the name, but do include the apache license on top.
A corresponding class including junit tests would also help. Thanks!
-Phil
-----Original Message-----
From: Peter [mailto:[EMAIL PROTECTED]
Sent: Mon 12/13/2004 2:31 PM
To: [EMAIL PROTECTED]
Cc:
Subject: [PATCH] Cholesky decomposition
This method implements the Cholesky decomposition of a RealMatrix. It
can be easily modified to be incorporated under the RealMatrix class and
to decompose BigMatrixes as well.
I hope you place it in the next release.
Peter P. Lupo
Computer Science barchelor student. UFRJ-Brazil
http://www.dcc.ufrj.br
http://www.ufrj.br
/**
* Computes the cholesky decomposition of matrix. The return is a
lower triangular matrix that may be empty and also coincide with the original
matrix. The method only uses the upper right part of the matrix, which must be
square, symmetric and positive-definite by definition.
* @param matrix
* The matrix to decompose.
* @return
* The matrix with the result, which is lower triangular
and has the same dimensions of the original matrix.
* @exception InvalidMatrixException
* if matrix is not square, symmetric or
positive-definite.
*/
public static RealMatrix choleskyDecomposition(RealMatrix matrix) {
if (!matrix.isSquare()) throw new InvalidMatrixException("Not a
square/symmetric matrix."); //"matrix" is not square
if (!matrix.equals(matrix.transpose())) throw new
InvalidMatrixException("Not a symmetric matrix."); //"matrix" is not
square
double[][] matrixData = matrix.copy().getData();
double[][] cholesky = new
double[matrix.getRowDimension()][matrix.getColumnDimension()];
for (int i = 0; i < matrix.getColumnDimension(); i++) {
double[] ithRowOfL = cholesky[i];
double[] ithRowOfA = matrixData[i];
for (int j = i; j < matrix.getRowDimension(); j++) {
double[] jthRowOfL = cholesky[j];
double sum = ithRowOfA[j];
for (int k = i - 1; k >= 0; k--){
sum -= ithRowOfL[k] * jthRowOfL[k];
}
if (i == j) {
if (sum <= 0)throw new InvalidMatrixException("Not a
positive definite matrix."); //"matrix", with rounding errors is not
positive definite
if (cholesky != null){
cholesky[j][i] = Math.sqrt(sum);
}
} else {
if (cholesky != null){
cholesky[j][i] = sum / cholesky[i][i];
}
if (i < j){
cholesky[i][j] = 0;
}
}
}
}
return new RealMatrixImpl(cholesky);
}
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