Documentation of 'mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition' Java class
SymmetricQRAlgorithmDecomposition
mikera.matrixx.decompose.impl.eigen

Class SymmetricQRAlgorithmDecomposition



  • public class SymmetricQRAlgorithmDecomposition
    extends java.lang.Object

    Computes the eigenvalues and eigenvectors of a real symmetric matrix using the symmetric implicit QR algorithm. Inside each iteration a QR decomposition of Ai-piI is implicitly computed.

    This implementation is based on the algorithm is sketched out in:
    David S. Watkins, "Fundamentals of Matrix Computations," Second Edition. page 377-385

    • Constructor Detail

      • SymmetricQRAlgorithmDecomposition

        public SymmetricQRAlgorithmDecomposition(boolean computeVectors)
    • Method Detail

      • setComputeVectorsWithValues

        public void setComputeVectorsWithValues(boolean computeVectorsWithValues)
      • setMaxIterations

        public void setMaxIterations(int max)
        Used to limit the number of internal QR iterations that the QR algorithm performs. 20 should be enough for most applications.
        Parameters:
        max - The maximum number of QR iterations it will perform.
      • getNumberOfEigenvalues

        public int getNumberOfEigenvalues()
      • getEigenvalue

        public Vector2 getEigenvalue(int index)
      • getEigenVector

        public AVector getEigenVector(int index)
      • decompose

        public EigenResult decompose(AMatrix orig)
        Decomposes the matrix using the QR algorithm. Care was taken to minimize unnecessary memory copying and cache skipping.
        Parameters:
        orig - The matrix which is being decomposed. Not modified.
        Returns:
        true if it decomposed the matrix or false if an error was detected. This will not catch all errors.

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