org.ejml.alg.dense.linsol.qr

Class LinearSolverQrHouse

java.lang.Object

org.ejml.alg.dense.linsol.LinearSolverAbstract

org.ejml.alg.dense.linsol.qr.LinearSolverQrHouse

All Implemented Interfaces:

LinearSolver<DenseMatrix64F>

public class LinearSolverQrHouse
extends LinearSolverAbstract

QR decomposition can be used to solve for systems. However, this is not as computationally efficient as LU decomposition and costs about 3n² flops.

It solve for x by first multiplying b by the transpose of Q then solving for the result.
QRx=b
Rx=Q^T b

Author:

Peter Abeles

Field Summary

Fields inherited from class org.ejml.alg.dense.linsol.LinearSolverAbstract

A, numCols, numRows

Constructor Summary

Constructors

Constructor and Description
LinearSolverQrHouse() Creates a linear solver that uses QR decomposition.

Method Summary

Methods

Modifier and Type	Method and Description
boolean	modifiesA() Returns true if the passed in matrix to LinearSolver.setA(org.ejml.data.Matrix64F) is modified.
boolean	modifiesB() Returns true if the passed in 'B' matrix to LinearSolver.solve(org.ejml.data.Matrix64F, org.ejml.data.Matrix64F) is modified.
double	quality() Returns a very quick to compute measure of how singular the system is.
boolean	setA(DenseMatrix64F A) Performs QR decomposition on A
void	setMaxSize(int maxRows)
void	solve(DenseMatrix64F B, DenseMatrix64F X) Solves for X using the QR decomposition.

Methods inherited from class org.ejml.alg.dense.linsol.LinearSolverAbstract

_setA, getA, invert

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LinearSolverQrHouse

public LinearSolverQrHouse()

Creates a linear solver that uses QR decomposition.

Method Detail

setMaxSize

public void setMaxSize(int maxRows)

setA

public boolean setA(DenseMatrix64F A)

Performs QR decomposition on A

Parameters:

A - not modified.

Returns:

true if it can be processed.

quality

public double quality()

Description copied from interface: LinearSolver

Returns a very quick to compute measure of how singular the system is. This measure will be invariant to the scale of the matrix and always be positive, with larger values indicating it is less singular. If not supported by the solver then the runtime exception IllegalArgumentException is thrown. This is NOT the matrix's condition.

How this function is implemented is not specified. One possible implementation is the following: In many decompositions a triangular matrix is extracted. The determinant of a triangular matrix is easily computed and once normalized to be scale invariant and its absolute value taken it will provide functionality described above.

Returns:

The quality of the linear system.

solve

public void solve(DenseMatrix64F B,
         DenseMatrix64F X)

Solves for X using the QR decomposition.

Parameters:

B - A matrix that is n by m. Not modified.

X - An n by m matrix where the solution is writen to. Modified.

modifiesA

public boolean modifiesA()

Description copied from interface: LinearSolver

Returns true if the passed in matrix to LinearSolver.setA(org.ejml.data.Matrix64F) is modified.

Returns:

true if A is modified in setA().

modifiesB

public boolean modifiesB()

Description copied from interface: LinearSolver

Returns true if the passed in 'B' matrix to LinearSolver.solve(org.ejml.data.Matrix64F, org.ejml.data.Matrix64F) is modified.

Returns:

true if B is modified in solve(B,X).