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java.lang.Objectorg.ejml.alg.block.linsol.chol.BlockCholeskyOuterSolver
public class BlockCholeskyOuterSolver
Linear solver that uses a block cholesky decomposition.
Solver works by using the standard Cholesky solving strategy:
A=L*LT
A*x=b
L*LT*x = b
L*y = b
LT*x = y
x = L-Ty
It is also possible to use the upper triangular cholesky decomposition.
| Constructor Summary | |
|---|---|
BlockCholeskyOuterSolver()
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| Method Summary | |
|---|---|
void |
invert(BlockMatrix64F A_inv)
Computes the inverse of of the 'A' matrix passed into LinearSolver.setA(org.ejml.data.Matrix64F)
and writes the results to the provided matrix. |
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(BlockMatrix64F A)
Decomposes and overwrites the input matrix. |
void |
solve(BlockMatrix64F B,
BlockMatrix64F X)
If X == null then the solution is written into B. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
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public BlockCholeskyOuterSolver()
| Method Detail |
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public boolean setA(BlockMatrix64F A)
setA in interface LinearSolver<BlockMatrix64F>A - Semi-Positive Definite (SPD) system matrix. 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<BlockMatrix64F>
public void solve(BlockMatrix64F B,
BlockMatrix64F X)
solve in interface LinearSolver<BlockMatrix64F>B - A matrix ℜ m × p. Might be modified.X - A matrix ℜ n × p, where the solution is written to. Modified.public void invert(BlockMatrix64F A_inv)
LinearSolverLinearSolver.setA(org.ejml.data.Matrix64F)
and writes the results to the provided matrix. If 'A_inv' needs to be different from 'A'
is implementation dependent.
invert in interface LinearSolver<BlockMatrix64F>A_inv - Where the inverted matrix saved. Modified.public boolean modifiesA()
LinearSolverLinearSolver.setA(org.ejml.data.Matrix64F)
is modified.
modifiesA in interface LinearSolver<BlockMatrix64F>public boolean modifiesB()
LinearSolverLinearSolver.solve(org.ejml.data.Matrix64F, org.ejml.data.Matrix64F)
is modified.
modifiesB in interface LinearSolver<BlockMatrix64F>
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