alvinalexander.com | career | drupal | java | mac | mysql | perl | scala | uml | unix

# Commons Math example source code file (DecompositionSolver.java)

This example Commons Math source code file (DecompositionSolver.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

## Java - Commons Math tags/keywords

decompositionsolver, illegalargumentexception, illegalargumentexception, invalidmatrixexception, invalidmatrixexception, realmatrix, realmatrix, realvector, realvector

## The Commons Math DecompositionSolver.java source code

```/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements.  See the NOTICE file distributed with
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License.  You may obtain a copy of the License at
*
*
* Unless required by applicable law or agreed to in writing, software
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
*/

package org.apache.commons.math.linear;

/**
* Interface handling decomposition algorithms that can solve A × X = B.
* <p>Decomposition algorithms decompose an A matrix has a product of several specific
* matrices from which they can solve A × X = B in least squares sense: they find X
* such that ||A × X - B|| is minimal.</p>
* <p>Some solvers like {@link LUDecomposition} can only find the solution for
* square matrices and when the solution is an exact linear solution, i.e. when
* ||A × X - B|| is exactly 0. Other solvers can also find solutions
* with non-square matrix A and with non-null minimal norm. If an exact linear
* solution exists it is also the minimal norm solution.</p>
*
* @version \$Revision: 811685 \$ \$Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) \$
* @since 2.0
*/
public interface DecompositionSolver {

/** Solve the linear equation A × X = B for matrices A.
* <p>The A matrix is implicit, it is provided by the underlying
* decomposition algorithm.</p>
* @param b right-hand side of the equation A × X = B
* @return a vector X that minimizes the two norm of A × X - B
* @exception IllegalArgumentException if matrices dimensions don't match
* @exception InvalidMatrixException if decomposed matrix is singular
*/
double[] solve(final double[] b)
throws IllegalArgumentException, InvalidMatrixException;

/** Solve the linear equation A × X = B for matrices A.
* <p>The A matrix is implicit, it is provided by the underlying
* decomposition algorithm.</p>
* @param b right-hand side of the equation A × X = B
* @return a vector X that minimizes the two norm of A × X - B
* @exception IllegalArgumentException if matrices dimensions don't match
* @exception InvalidMatrixException if decomposed matrix is singular
*/
RealVector solve(final RealVector b)
throws IllegalArgumentException, InvalidMatrixException;

/** Solve the linear equation A × X = B for matrices A.
* <p>The A matrix is implicit, it is provided by the underlying
* decomposition algorithm.</p>
* @param b right-hand side of the equation A × X = B
* @return a matrix X that minimizes the two norm of A × X - B
* @exception IllegalArgumentException if matrices dimensions don't match
* @exception InvalidMatrixException if decomposed matrix is singular
*/
RealMatrix solve(final RealMatrix b)
throws IllegalArgumentException, InvalidMatrixException;

/**
* Check if the decomposed matrix is non-singular.
* @return true if the decomposed matrix is non-singular
*/
boolean isNonSingular();

/** Get the inverse (or pseudo-inverse) of the decomposed matrix.
* @return inverse matrix
* @throws InvalidMatrixException if decomposed matrix is singular
*/
RealMatrix getInverse()
throws InvalidMatrixException;

}
```

## Other Commons Math examples (source code examples)

Here is a short list of links related to this Commons Math DecompositionSolver.java source code file:

 ... this post is sponsored by my books ... #1 New Release! FP Best Seller