Documentation of 'org.ejml.alg.dense.linsol.qr.BaseLinearSolverQrp_D64' Java class
BaseLinearSolverQrp_D64
org.ejml.alg.dense.linsol.qr

Class BaseLinearSolverQrp_D64

  • All Implemented Interfaces:
    LinearSolver<DenseMatrix64F>
    Direct Known Subclasses:
    LinearSolverQrpHouseCol_D64, SolvePseudoInverseQrp_D64


    public abstract class BaseLinearSolverQrp_D64
    extends LinearSolverAbstract_D64

    Base class for QR pivot based pseudo inverse classes. It will return either the basic of minimal 2-norm solution. See [1] for details. The minimal 2-norm solution refers to the solution 'x' whose 2-norm is the smallest making it unique, not some other error function.

     R = [ R12  R12 ] r      P^T*x = [ y ] r       Q^T*b = [ c ] r
         [  0    0  ] m-r            [ z ] n -r            [ d ] m-r
            r   n-r
    
     where r is the rank of the matrix and (m,n) is the dimension of the linear system.
     

     The solution 'x' is found by solving the system below.  The basic solution is found by setting z=0
    
         [ R_11^-1*(c - R12*z) ]
     x = [          z          ]
     

    NOTE: The matrix rank is determined using the provided QR decomposition. [1] mentions that this will not always work and could cause some problems.

    [1] See page 258-259 in Gene H. Golub and Charles F. Van Loan "Matrix Computations" 3rd Ed, 1996

    • Method Detail

      • setA

        public boolean setA(DenseMatrix64F 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.

        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.
      • getDecomposition

        public QRPDecomposition<DenseMatrix64F> 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.

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