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package algs91; // section 9.9
import stdlib.*;
/* ***********************************************************************
* Compilation: javac Cholesky.java
* Execution: java Cholesky
*
* Compute XCholesky decomposition of symmetric positive definite
* matrix A = LL^T.
*
* % java Cholesky
* 2.00000 0.00000 0.00000
* 0.50000 2.17945 0.00000
* 0.50000 1.26179 3.62738
*
*************************************************************************/
public class XCholesky {
//private static final double EPSILON = 1e-10;
// is symmetric
public static boolean isSymmetric(double[][] A) {
int N = A.length;
for (int i = 0; i < N; i++) {
for (int j = 0; j < i; j++) {
if (A[i][j] != A[j][i]) return false;
}
}
return true;
}
// is symmetric
public static boolean isSquare(double[][] A) {
int N = A.length;
for (int i = 0; i < N; i++) {
if (A[i].length != N) return false;
}
return true;
}
// return XCholesky factor L of psd matrix A = L L^T
public static double[][] cholesky(double[][] A) {
if (!isSquare(A)) {
throw new Error("Matrix is not square");
}
if (!isSymmetric(A)) {
throw new Error("Matrix is not symmetric");
}
int N = A.length;
double[][] L = new double[N][N];
for (int i = 0; i < N; i++) {
for (int j = 0; j <= i; j++) {
double sum = 0.0;
for (int k = 0; k < j; k++) {
sum += L[i][k] * L[j][k];
}
if (i == j) L[i][i] = Math.sqrt(A[i][i] - sum);
else L[i][j] = 1.0 / L[j][j] * (A[i][j] - sum);
}
if (L[i][i] <= 0) {
throw new Error("Matrix not positive definite");
}
}
return L;
}
// sample client
public static void main(String[] args) {
int N = 3;
double[][] A = {
{ 4, 1, 1 },
{ 1, 5, 3 },
{ 1, 3, 15 }
};
double[][] L = cholesky(A);
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
StdOut.format("%8.5f ", L[i][j]);
}
StdOut.println();
}
}
}
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