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java.lang.Object cern.colt.matrix.tdouble.algo.decomposition.DoubleLUDecompositionQuick
public class DoubleLUDecompositionQuick
A low level version of DoubleLUDecomposition
, avoiding unnecessary
memory allocation and copying. The input to decompose methods is
overriden with the result (LU). The input to solve methods is
overriden with the result (X). In addition to LUDecomposition, this
class also includes a faster variant of the decomposition, specialized for
tridiagonal (and hence also diagonal) matrices, as well as a solver tuned for
vectors. Its disadvantage is that it is a bit more difficult to use than
LUDecomposition. Thus, you may want to disregard this class and come
back later, if a need for speed arises.
An instance of this class remembers the result of its last decomposition. Usage pattern is as follows: Create an instance of this class, call a decompose method, then retrieve the decompositions, determinant, and/or solve as many equation problems as needed. Once another matrix needs to be LU-decomposed, you need not create a new instance of this class. Start again by calling a decompose method, then retrieve the decomposition and/or solve your equations, and so on. In case a LU matrix is already available, call method setLU instead of decompose and proceed with solving et al.
If a matrix shall not be overriden, use matrix.copy() and hand the the copy to methods.
For an m x n matrix A with m >= n, the LU decomposition is an m x n unit lower triangular matrix L, an n x 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 x m and U is m x n.
The LU decomposition with pivoting always exists, even if the matrix is singular, so the decompose methods will never fail. The primary use of the LU decomposition is in the solution of square systems of simultaneous linear equations. Attempting to solve such a system will throw an exception if isNonsingular() returns false.
Constructor Summary | |
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DoubleLUDecompositionQuick()
Constructs and returns a new LU Decomposition object with default tolerance 1.0E-9 for singularity detection. |
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DoubleLUDecompositionQuick(double tolerance)
Constructs and returns a new LU Decomposition object which uses the given tolerance for singularity detection; |
Method Summary | |
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void |
decompose(DoubleMatrix2D A)
Decomposes matrix A into L and U (in-place). |
void |
decompose(DoubleMatrix2D A,
int semiBandwidth)
Decomposes the banded and square matrix A into L and U (in-place). |
double |
det()
Returns the determinant, det(A). |
DoubleMatrix2D |
getL()
Returns the lower triangular factor, L. |
DoubleMatrix2D |
getLU()
Returns a copy of the combined lower and upper triangular factor, LU. |
int[] |
getPivot()
Returns the pivot permutation vector (not a copy of it). |
DoubleMatrix2D |
getU()
Returns the upper triangular factor, U. |
boolean |
isNonsingular()
Returns whether the matrix is nonsingular (has an inverse). |
void |
setLU(DoubleMatrix2D LU)
Sets the combined lower and upper triangular factor, LU. |
void |
solve(DoubleMatrix1D B)
Solves the system of equations A*X = B (in-place). |
void |
solve(DoubleMatrix2D B)
Solves the system of equations A*X = B (in-place). |
String |
toString()
Returns a String with (propertyName, propertyValue) pairs. |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public DoubleLUDecompositionQuick()
public DoubleLUDecompositionQuick(double tolerance)
Method Detail |
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public void decompose(DoubleMatrix2D A)
A
- any matrix.public void decompose(DoubleMatrix2D A, int semiBandwidth)
decompose(DoubleMatrix2D)
.
semiBandwidth
- == 1 --> A is diagonal, == 2 --> A is tridiagonal.A
- any matrix.public double det()
IllegalArgumentException
- if A.rows() != A.columns() (Matrix must be
square).public DoubleMatrix2D getL()
public DoubleMatrix2D getLU()
public int[] getPivot()
public DoubleMatrix2D getU()
public boolean isNonsingular()
public void setLU(DoubleMatrix2D LU)
public void solve(DoubleMatrix1D B)
B
- A vector with B.size() == A.rows().
IllegalArgumentException
- if B.size() != A.rows().
IllegalArgumentException
- if A is singular, that is, if !isNonsingular().
IllegalArgumentException
- if A.rows() < A.columns().public void solve(DoubleMatrix2D B)
B
- A matrix with as many rows as A and any number of
columns.
IllegalArgumentException
- if B.rows() != A.rows().
IllegalArgumentException
- if A is singular, that is, if !isNonsingular().
IllegalArgumentException
- if A.rows() < A.columns().public String toString()
rank : 3 trace : 0
toString
in class Object
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