public class WrapLinearSolverBlock64 extends Object implements LinearSolver<DenseMatrix64F>
to implements LinearSolver. It works
by converting DenseMatrix64F into BlockMatrix64F and calling the equivalent
functions. Since a local copy is made all input matrices are never modified.| Modifier and Type | Field and Description |
|---|---|
protected LinearSolver<BlockMatrix64F> |
alg |
protected BlockMatrix64F |
blockA |
protected BlockMatrix64F |
blockB |
protected BlockMatrix64F |
blockX |
| Constructor and Description |
|---|
WrapLinearSolverBlock64(LinearSolver<BlockMatrix64F> alg) |
| Modifier and Type | Method and Description |
|---|---|
void |
invert(DenseMatrix64F A_inv)
Creates a block matrix the same size as A_inv, inverts the matrix and copies the results back
onto A_inv.
|
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)
Converts 'A' into a block matrix and call setA() on the block matrix solver.
|
void |
solve(DenseMatrix64F B,
DenseMatrix64F X)
Converts B and X into block matrices and calls the block matrix solve routine.
|
protected LinearSolver<BlockMatrix64F> alg
protected BlockMatrix64F blockA
protected BlockMatrix64F blockB
protected BlockMatrix64F blockX
public WrapLinearSolverBlock64(LinearSolver<BlockMatrix64F> alg)
public boolean setA(DenseMatrix64F A)
setA in interface LinearSolver<DenseMatrix64F>A - The A matrix in the linear equation. Not modified. Reference saved.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.
quality in interface LinearSolver<DenseMatrix64F>public void solve(DenseMatrix64F B, DenseMatrix64F X)
solve in interface LinearSolver<DenseMatrix64F>B - A matrix ℜ m × p. Not modified.X - A matrix ℜ n × p, where the solution is written to. Modified.public void invert(DenseMatrix64F A_inv)
invert in interface LinearSolver<DenseMatrix64F>A_inv - Where the inverted matrix saved. Modified.public boolean modifiesA()
LinearSolverLinearSolver.setA(org.ejml.data.Matrix64F)
is modified.modifiesA in interface LinearSolver<DenseMatrix64F>public boolean modifiesB()
LinearSolverLinearSolver.solve(org.ejml.data.Matrix64F, org.ejml.data.Matrix64F)
is modified.modifiesB in interface LinearSolver<DenseMatrix64F>Copyright © 2013. All Rights Reserved.