Class LinearSolverCholLDL_FDRM
 All Implemented Interfaces:
LinearSolver<FMatrixRMaj,
,FMatrixRMaj> LinearSolverDense<FMatrixRMaj>

Field Summary
Fields inherited from class org.ejml.dense.row.linsol.LinearSolverAbstract_FDRM
A, numCols, numRows

Constructor Summary
ConstructorDescription 
Method Summary
Modifier and TypeMethodDescriptionIf a decomposition class was used internally then this will return that class.void
invert
(FMatrixRMaj inv) Sets the matrix 'inv' equal to the inverse of the matrix that was decomposed.boolean
Returns true if the passed in matrix toLinearSolver.setA(Matrix)
is modified.boolean
Returns true if the passed in 'B' matrix toLinearSolver.solve(Matrix, Matrix)
is modified.double
quality()
Returns a very quick to compute measure of how singular the system is.boolean
setA
(FMatrixRMaj A) Specifies the A matrix in the linear equation.void
solve
(FMatrixRMaj B, FMatrixRMaj X) Using the decomposition, finds the value of 'X' in the linear equation below:
A*x = b
where A has dimension of n by n, x and b are n by m dimension.Methods inherited from class org.ejml.dense.row.linsol.LinearSolverAbstract_FDRM
_setA, getA

Constructor Details

LinearSolverCholLDL_FDRM

LinearSolverCholLDL_FDRM
public LinearSolverCholLDL_FDRM()


Method Details

setA
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
Using the decomposition, finds the value of 'X' in the linear equation below:
A*x = b
where A has dimension of n by n, x and b are n by m dimension.*Note* that 'b' and 'x' can be the same matrix instance.
 Parameters:
B
 A matrix that is n by m. Not modified.X
 An n by m matrix where the solution is writen to. Modified.

invert
Sets the matrix 'inv' equal to the inverse of the matrix that was decomposed. Specified by:
invert
in interfaceLinearSolverDense<FMatrixRMaj>
 Overrides:
invert
in classLinearSolverAbstract_FDRM
 Parameters:
inv
 Where the value of the inverse will be stored. Modified.

modifiesA
public boolean modifiesA()Description copied from interface:LinearSolver
Returns true if the passed in matrix toLinearSolver.setA(Matrix)
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 toLinearSolver.solve(Matrix, Matrix)
is modified. Returns:
 true if B is modified in solve(B,X).

getDecomposition
Description copied from interface:LinearSolver
If a decomposition class was used internally then this will return that class. Most linear solvers decompose the input matrix into a more simplistic form. However some solutions do not require decomposition, e.g. inverse by minor. Returns:
 Internal decomposition class. If there is none then null.
