Package org.ejml.sparse.csc.linsol.lu

Class LinearSolverLu_FSCC

java.lang.Object
org.ejml.sparse.csc.linsol.lu.LinearSolverLu_FSCC
All Implemented Interfaces:
LinearSolver<FMatrixSparseCSC,FMatrixRMaj>, LinearSolverSparse<FMatrixSparseCSC,FMatrixRMaj>
@Generated("org.ejml.sparse.csc.linsol.lu.LinearSolverLu_DSCC") public class LinearSolverLu_FSCC extends Object implements LinearSolverSparse<FMatrixSparseCSC,FMatrixRMaj>
LU Decomposition based solver for square matrices. Uses LuUpLooking_FSCC internally.

  • Constructor Details

    • LinearSolverLu_FSCC

      public LinearSolverLu_FSCC(LuUpLooking_FSCC decomposition)

  • Method Details

    • setA

      public boolean setA(FMatrixSparseCSC 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.

      Specified by:
      setA in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      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.

      Specified by:
      quality in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      Returns:
      The quality of the linear system.

    • solveSparse

      public void solveSparse(FMatrixSparseCSC B, FMatrixSparseCSC X)
      Description copied from interface: LinearSolverSparse
      Solve against sparse matrices. A*X=B. In most situations its more desirable to solve against a dense matrix because of fill in.
      Specified by:
      solveSparse in interface LinearSolverSparse<FMatrixSparseCSC,FMatrixRMaj>
      Parameters:
      B - Input. Never modified.
      X - Output. Never modified.

    • setStructureLocked

      public void setStructureLocked(boolean locked)
      Description copied from interface: LinearSolverSparse

      Save results from structural analysis step. This can reduce computations of a matrix with the exactly same non-zero pattern is decomposed in the future. If a matrix has yet to be processed then the structure of the next matrix is saved. If a matrix has already been processed then the structure of the most recently processed matrix will be saved.

      Specified by:
      setStructureLocked in interface LinearSolverSparse<FMatrixSparseCSC,FMatrixRMaj>

    • isStructureLocked

      public boolean isStructureLocked()
      Description copied from interface: LinearSolverSparse
      Checks to see if the structure is locked.
      Specified by:
      isStructureLocked in interface LinearSolverSparse<FMatrixSparseCSC,FMatrixRMaj>
      Returns:
      true if locked or false if not locked.

    • solve

      public void solve(FMatrixRMaj B, FMatrixRMaj 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.

      Specified by:
      solve in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      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(Matrix) is modified.
      Specified by:
      modifiesA in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      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(Matrix, Matrix) is modified.
      Specified by:
      modifiesB in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      Returns:
      true if B is modified in solve(B,X).

    • getDecomposition

      public <D extends DecompositionInterface> D 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.
      Specified by:
      getDecomposition in interface LinearSolver<FMatrixSparseCSC,FMatrixRMaj>
      Type Parameters:
      D - Decomposition type
      Returns:
      Internal decomposition class. If there is none then null.