25-Sep-2022 10:03:33

web_matrix_test():
  MATLAB/Octave version 9.8.0.1380330 (R2020a) Update 2
  Test web_matrix()

  Process the "tiny" web matrix

power_rank():
  Given an NxN incidence matrix A,
  compute the transition matrix T,
  Then start with a vector of N values 1/N,
  and repeatedly compute x <= T*x

  After many steps, compare last three iterates.
  If they are close, we are probably at an eigenvector
  associated with the eigenvalue 1.
  x, T*x, T*T*x
    1.0000    1.0000    1.0000
    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000
         0         0         0


  Process the "moler" web matrix

power_rank():
  Given an NxN incidence matrix A,
  compute the transition matrix T,
  Then start with a vector of N values 1/N,
  and repeatedly compute x <= T*x

  After many steps, compare last three iterates.
  If they are close, we are probably at an eigenvector
  associated with the eigenvalue 1.
  x, T*x, T*T*x
    0.0110    0.0106    0.0103
    0.0057    0.0055    0.0053
    0.0029    0.0028    0.0027
    0.0039    0.0038    0.0037
    0.9698    0.9708    0.9718
    0.0067    0.0065    0.0062


  Process the "sauer" web matrix

power_rank():
  Given an NxN incidence matrix A,
  compute the transition matrix T,
  Then start with a vector of N values 1/N,
  and repeatedly compute x <= T*x

  After many steps, compare last three iterates.
  If they are close, we are probably at an eigenvector
  associated with the eigenvalue 1.
  x, T*x, T*T*x
    0.0154    0.0154    0.0154
    0.0116    0.0116    0.0116
    0.0116    0.0116    0.0116
    0.0154    0.0154    0.0154
    0.0309    0.0309    0.0309
    0.0309    0.0309    0.0309
    0.0309    0.0309    0.0309
    0.0309    0.0309    0.0309
    0.0811    0.0811    0.0811
    0.1100    0.1100    0.1100
    0.1100    0.1100    0.1100
    0.0811    0.0811    0.0811
    0.1467    0.1467    0.1467
    0.1467    0.1467    0.1467
    0.1467    0.1467    0.1467


web_matrix_test():
  Normal end of execution.

25-Sep-2022 10:03:33