org.ejml.alg.dense.linsol.qr
Class LinearSolverQrp

java.lang.Object
  org.ejml.alg.dense.linsol.LinearSolverAbstract
      org.ejml.alg.dense.linsol.qr.LinearSolverQrp

All Implemented Interfaces:

LinearSolver<DenseMatrix64F>

public class LinearSolverQrp
extends LinearSolverAbstract

A solver for a generic QR column pivot decomposition algorithm. This will in general be a bit slower than the specialized once since the full Q, R, and P matrices need to be extracted.

It solve for x by first multiplying b by the transpose of Q then solving for the result.
Q*R*P^Tx=b

Author:

Peter Abeles

Field Summary

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

A, numCols, numRows

Constructor Summary

LinearSolverQrp(QRPDecomposition<DenseMatrix64F> decomposition)

Method Summary

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) Specifies the A matrix in the linear equation.
void	solve(DenseMatrix64F B, DenseMatrix64F X) Solves for X in the linear system, A*X=B.

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

LinearSolverQrp

public LinearSolverQrp(QRPDecomposition<DenseMatrix64F> decomposition)

Method Detail

setA

public boolean setA(DenseMatrix64F A)

Description copied from interface: LinearSolver

Specifies the A matrix in the linear equation. A reference might be saved and it might also be modified depending on the implementation. If it is modified then LinearSolver.modifiesA() will return true.

If this value returns true that does not guarantee a valid solution was generated. This is because some decompositions don't detect singular matrices.

Parameters:

A - The 'A' matrix in the linear equation. Might be modified or save the reference.

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)

Description copied from interface: LinearSolver

Solves for X in the linear system, A*X=B.

In some implementations 'B' and 'X' can be the same instance of a variable. Call LinearSolver.modifiesB() to determine if 'B' is modified.

Parameters:

B - A matrix ℜ ^{m × p}. Might be modified.

X - A matrix ℜ ^{n × p}, where the solution is written 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).