Author: celestin
Date: Sat Sep 24 04:54:28 2011
New Revision: 1175105
URL: http://svn.apache.org/viewvc?rev=1175105&view=rev
Log:
Merged RectangularCholeskyDecomposition and
RectangularCholeskyDecompositionImpl (see MATH-662).
Added:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecomposition.java
- copied, changed from r1175099,
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecompositionImpl.java
Removed:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecompositionImpl.java
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java
Copied:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecomposition.java
(from r1175099,
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecompositionImpl.java)
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecomposition.java?p2=commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecomposition.java&p1=commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecompositionImpl.java&r1=1175099&r2=1175105&rev=1175105&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecompositionImpl.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/RectangularCholeskyDecomposition.java
Sat Sep 24 04:54:28 2011
@@ -25,13 +25,24 @@ import org.apache.commons.math.util.Fast
* semidefinite matrix A consists of a rectangular matrix B with the same
* number of rows such that: A is almost equal to BB<sup>T</sup>, depending
* on a user-defined tolerance. In a sense, this is the square root of A.</p>
+ * <p>The difference with respect to the regular {@link CholeskyDecomposition}
+ * is that rows/columns may be permuted (hence the rectangular shape instead
+ * of the traditional triangular shape) and there is a threshold to ignore
+ * small diagonal elements. This is used for example to generate {@link
+ * org.apache.commons.math.random.CorrelatedRandomVectorGenerator correlated
+ * random n-dimensions vectors} in a p-dimension subspace (p < n).
+ * In other words, it allows generating random vectors from a covariance
+ * matrix that is only positive semidefinite, and not positive definite.</p>
+ * <p>Rectangular Cholesky decomposition is <em>not</em> suited for solving
+ * linear systems, so it does not provide any {@link DecompositionSolver
+ * decomposition solver}.</p>
*
* @see <a
href="http://mathworld.wolfram.com/CholeskyDecomposition.html";>MathWorld</a>
* @see <a
href="http://en.wikipedia.org/wiki/Cholesky_decomposition";>Wikipedia</a>
* @version $Id$
- * @since 2.0
+ * @since 2.0 (changed to concrete class in 3.0)
*/
-public class RectangularCholeskyDecompositionImpl implements
RectangularCholeskyDecomposition {
+public class RectangularCholeskyDecomposition {
/** Permutated Cholesky root of the symmetric positive semidefinite
matrix. */
private final RealMatrix root;
@@ -48,7 +59,7 @@ public class RectangularCholeskyDecompos
* @exception NonPositiveDefiniteMatrixException if the matrix is not
* positive semidefinite.
*/
- public RectangularCholeskyDecompositionImpl(RealMatrix matrix, double
small)
+ public RectangularCholeskyDecomposition(RealMatrix matrix, double small)
throws NonPositiveDefiniteMatrixException {
int order = matrix.getRowDimension();
@@ -139,12 +150,23 @@ public class RectangularCholeskyDecompos
}
- /** {@inheritDoc} */
+ /** Get the root of the covariance matrix.
+ * The root is the rectangular matrix <code>B</code> such that
+ * the covariance matrix is equal to <code>B.B<sup>T</sup></code>
+ * @return root of the square matrix
+ * @see #getRank()
+ */
public RealMatrix getRootMatrix() {
return root;
}
- /** {@inheritDoc} */
+ /** Get the rank of the symmetric positive semidefinite matrix.
+ * The r is the number of independent rows in the symmetric positive
semidefinite
+ * matrix, it is also the number of columns of the rectangular
+ * matrix of the decomposition.
+ * @return r of the square matrix.
+ * @see #getRootMatrix()
+ */
public int getRank() {
return rank;
}
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java?rev=1175105&r1=1175104&r2=1175105&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java
Sat Sep 24 04:54:28 2011
@@ -20,7 +20,6 @@ package org.apache.commons.math.random;
import org.apache.commons.math.exception.DimensionMismatchException;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.linear.RectangularCholeskyDecomposition;
-import org.apache.commons.math.linear.RectangularCholeskyDecompositionImpl;
/**
* A {@link RandomVectorGenerator} that generates vectors with with
@@ -95,7 +94,7 @@ public class CorrelatedRandomVectorGener
this.mean = mean.clone();
final RectangularCholeskyDecomposition decomposition =
- new RectangularCholeskyDecompositionImpl(covariance, small);
+ new RectangularCholeskyDecomposition(covariance, small);
root = decomposition.getRootMatrix();
this.generator = generator;
@@ -124,7 +123,7 @@ public class CorrelatedRandomVectorGener
}
final RectangularCholeskyDecomposition decomposition =
- new RectangularCholeskyDecompositionImpl(covariance, small);
+ new RectangularCholeskyDecomposition(covariance, small);
root = decomposition.getRootMatrix();
this.generator = generator;
