Package org.ejml.dense.row.decomposition.eig.watched

Class WatchedDoubleStepQREigen_FDRM

java.lang.Object
org.ejml.dense.row.decomposition.eig.watched.WatchedDoubleStepQREigen_FDRM
Direct Known Subclasses:
WatchedDoubleStepQREigen_MT_FDRM
@Generated("org.ejml.dense.row.decomposition.eig.watched.WatchedDoubleStepQREigen_DDRM") public class WatchedDoubleStepQREigen_FDRM extends Object

The float step implicit Eigenvalue decomposition algorithm is fairly complicated and needs to be designed so that it can handle several special cases. To aid in development and debugging this class was created. It allows individual components to be tested and to print out their results. This shows how each step is performed.

Do not use this class to compute the eigenvalues since it is much slower than a non-debug implementation.

  • Field Details

    • u

      protected FMatrixRMaj u

    • gamma

      protected float gamma

    • _temp

      protected FMatrixRMaj _temp

    • createR

      public boolean createR

    • Q

      @Nullable public @Nullable FMatrixRMaj Q

  • Constructor Details

    • WatchedDoubleStepQREigen_FDRM

      public WatchedDoubleStepQREigen_FDRM()

  • Method Details

    • incrementSteps

      public void incrementSteps()

    • setQ

      public void setQ(@Nullable @Nullable FMatrixRMaj Q)

    • setChecks

      public void setChecks(boolean hessenberg, boolean orthogonal, boolean uncountable)

    • isZero

      public boolean isZero(int x1, int x2)

    • setup

      public void setup(FMatrixRMaj A)

    • exceptionalShift

      public void exceptionalShift(int x1, int x2)
      Perform a shift in a random direction that is of the same magnitude as the elements in the matrix.

    • implicitDoubleStep

      public void implicitDoubleStep(int x1, int x2)
      Performs an implicit float step using the values contained in the lower right hand side of the submatrix for the estimated eigenvector values.

    • performImplicitDoubleStep

      public void performImplicitDoubleStep(int x1, int x2, float real, float img)
      Performs an implicit float step given the set of two imaginary eigenvalues provided. Since one eigenvalue is the complex conjugate of the other only one set of real and imaginary numbers is needed.
      Parameters:
      x1 - upper index of submatrix.
      x2 - lower index of submatrix.
      real - Real component of each of the eigenvalues.
      img - Imaginary component of one of the eigenvalues.

    • performImplicitSingleStep

      public void performImplicitSingleStep(int x1, int x2, float eigenvalue)

    • createBulgeSingleStep

      public boolean createBulgeSingleStep(int x1, float eigenvalue)

    • bulgeDoubleStepQn

      public boolean bulgeDoubleStepQn(int i)

    • bulgeDoubleStepQn

      public boolean bulgeDoubleStepQn(int i, float a11, float a21, float a31, float threshold, boolean set)

    • bulgeSingleStepQn

      public boolean bulgeSingleStepQn(int i)

    • bulgeSingleStepQn

      public boolean bulgeSingleStepQn(int i, float a11, float a21, float threshold, boolean set)

    • eigen2by2_scale

      public void eigen2by2_scale(float a11, float a12, float a21, float a22)

    • getNumberOfEigenvalues

      public int getNumberOfEigenvalues()

    • getEigenvalues

      public Complex_F32[] getEigenvalues()

    • addComputedEigen2x2

      public void addComputedEigen2x2(int x1, int x2)

    • isReal2x2

      public boolean isReal2x2(int x1, int x2)

    • addEigenAt

      public void addEigenAt(int x1)

    • rank1UpdateMultL

      protected void rank1UpdateMultL(FMatrixRMaj A, float gamma, int colA0, int w0, int w1)

    • rank1UpdateMultR

      protected void rank1UpdateMultR(FMatrixRMaj A, float gamma, int colA0, int w0, int w1)

    • printSteps

      public void printSteps()