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Reuse is one word :). 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1097918 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2011-04-29 19:08:09 +00:00
parent 556576e645
commit ec198897ee
2 changed files with 6 additions and 6 deletions
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6
src/main/java/org/apache/commons/math/linear/CholeskyDecompositionImpl.java
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@ -277,7 +277,7 @@ public class CholeskyDecompositionImpl implements CholeskyDecomposition {
* <p>The A matrix is implicit, it is provided by the underlying
* decomposition algorithm.</p>
* @param b right-hand side of the equation A &times; X = B
* @param reUseB if true, the b array will be reused and returned,
* @param reuseB if true, the b array will be reused and returned,
* instead of being copied
* @return a matrix X that minimizes the two norm of A &times; X - B
* @throws org.apache.commons.math.exception.DimensionMismatchException
@ -285,7 +285,7 @@ public class CholeskyDecompositionImpl implements CholeskyDecomposition {
* @throws SingularMatrixException
* if the decomposed matrix is singular.
*/
private double[][] solve(double[][] b, boolean reUseB) {
private double[][] solve(double[][] b, boolean reuseB) {
final int m = lTData.length;
if (b.length != m) {
throw new DimensionMismatchException(b.length, m);
@ -293,7 +293,7 @@ public class CholeskyDecompositionImpl implements CholeskyDecomposition {
final int nColB = b[0].length;
final double[][] x;
if (reUseB) {
if (reuseB) {
x = b;
} else {
x = new double[b.length][nColB];

6
src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java
View File

@ -342,7 +342,7 @@ public class EigenDecompositionImpl implements EigenDecomposition {
* <p>The A matrix is implicit, it is provided by the underlying
* decomposition algorithm.</p>
* @param b right-hand side of the equation A &times; X = B
* @param reUseB if true, the b array will be reused and returned,
* @param reuseB if true, the b array will be reused and returned,
* instead of being copied
* @return a matrix X that minimizes the two norm of A &times; X - B
* @throws org.apache.commons.math.exception.DimensionMismatchException
@ -350,7 +350,7 @@ public class EigenDecompositionImpl implements EigenDecomposition {
* @throws SingularMatrixException
* if the decomposed matrix is singular.
*/
private double[][] solve(double[][] b, boolean reUseB) {
private double[][] solve(double[][] b, boolean reuseB) {
if (!isNonSingular()) {
throw new SingularMatrixException();
@ -363,7 +363,7 @@ public class EigenDecompositionImpl implements EigenDecomposition {
final int nColB = b[0].length;
final double[][] bp;
if (reUseB) {
if (reuseB) {
bp = b;
} else {
bp = new double[m][nColB];