## org.jscience.physics.solids Class LUDecomposition

```java.lang.Object
org.jscience.physics.solids.LUDecomposition
```
All Implemented Interfaces:
java.io.Serializable

`public class LUDecompositionextends java.lang.Objectimplements java.io.Serializable`

LU Decomposition.

For an m-by-n matrix A with m >= n, the LU decomposition is an m-by-n unit lower triangular matrix L, an n-by-n upper triangular matrix U, and a permutation vector piv of length m so that A(piv,:) = L*U. If m < n, then L is m-by-m and U is m-by-n.

The LU decompostion with pivoting always exists, even if the matrix is singular, so the constructor will never fail. The primary use of the LU decomposition is in the solution of square systems of simultaneous linear equations. This will fail if isNonsingular() returns false.

Serialized Form

Constructor Summary
`LUDecomposition(AbstractDoubleMatrix A)`
LU Decomposition

Method Summary
` double` `det()`
Determinant
` double[]` `getDoublePivot()`
Return pivot permutation vector as a one-dimensional double array
` DoubleMatrix` `getL()`
Return lower triangular factor
` int[]` `getPivot()`
Return pivot permutation vector
` DoubleMatrix` `getU()`
Return upper triangular factor
` boolean` `isNonsingular()`
Is the matrix nonsingular?
` DoubleMatrix` `solve(AbstractDoubleMatrix B)`
Solve A*X = B

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### LUDecomposition

`public LUDecomposition(AbstractDoubleMatrix A)`
LU Decomposition

Parameters:
`A` - Rectangular matrix
Method Detail

### isNonsingular

`public boolean isNonsingular()`
Is the matrix nonsingular?

Returns:
true if U, and hence A, is nonsingular.

### getL

`public DoubleMatrix getL()`
Return lower triangular factor

Returns:
L

### getU

`public DoubleMatrix getU()`
Return upper triangular factor

Returns:
U

### getPivot

`public int[] getPivot()`
Return pivot permutation vector

Returns:
piv

### getDoublePivot

`public double[] getDoublePivot()`
Return pivot permutation vector as a one-dimensional double array

Returns:
(double) piv

### det

`public double det()`
Determinant

Returns:
det(A)
Throws:
`java.lang.IllegalArgumentException` - Matrix must be square

### solve

`public DoubleMatrix solve(AbstractDoubleMatrix B)`
Solve A*X = B

Parameters:
`B` - A Matrix with as many rows as A and any number of columns.
Returns:
X so that L*U*X = B(piv,:)
Throws:
`java.lang.IllegalArgumentException` - Matrix row dimensions must agree.
`java.lang.RuntimeException` - Matrix is singular.