public class LinearSolverQr extends LinearSolverAbstract
A solver for a generic QR decomposition algorithm. This will in general be a bit slower than the specialized once since the full Q and R matrices need to be extracted.
It solve for x by first multiplying b by the transpose of Q then solving for the result.
QRx=b
Rx=Q^T b
| Modifier and Type | Field and Description |
|---|---|
protected int |
maxCols |
protected int |
maxRows |
protected DenseMatrix64F |
Q |
protected DenseMatrix64F |
R |
A, numCols, numRows| Constructor and Description |
|---|
LinearSolverQr(QRDecomposition<DenseMatrix64F> decomposer)
Creates a linear solver that uses QR decomposition.
|
| Modifier and Type | Method and Description |
|---|---|
QRDecomposition<DenseMatrix64F> |
getDecomposer() |
DenseMatrix64F |
getQ() |
DenseMatrix64F |
getR() |
boolean |
modifiesA()
Returns true if the passed in matrix to
LinearSolver.setA(org.ejml.data.Matrix)
is modified. |
boolean |
modifiesB()
Returns true if the passed in 'B' matrix to
LinearSolver.solve(org.ejml.data.Matrix, org.ejml.data.Matrix)
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,
int maxCols)
Changes the size of the matrix it can solve for
|
void |
solve(DenseMatrix64F B,
DenseMatrix64F X)
Solves for X using the QR decomposition.
|
_setA, getA, invertprotected int maxRows
protected int maxCols
protected DenseMatrix64F Q
protected DenseMatrix64F R
public LinearSolverQr(QRDecomposition<DenseMatrix64F> decomposer)
public void setMaxSize(int maxRows,
int maxCols)
maxRows - Maximum number of rows in the matrix it will decompose.maxCols - Maximum number of columns in the matrix it will decompose.public boolean setA(DenseMatrix64F A)
A - not modified.public double quality()
LinearSolverReturns 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.
public void solve(DenseMatrix64F B, DenseMatrix64F X)
B - A matrix that is n by m. Not modified.X - An n by m matrix where the solution is written to. Modified.public boolean modifiesA()
LinearSolverLinearSolver.setA(org.ejml.data.Matrix)
is modified.public boolean modifiesB()
LinearSolverLinearSolver.solve(org.ejml.data.Matrix, org.ejml.data.Matrix)
is modified.public QRDecomposition<DenseMatrix64F> getDecomposer()
public DenseMatrix64F getQ()
public DenseMatrix64F getR()