Fri Oct  7 21:06:07 2022

log_norm_test():
  Python version: 3.6.9
  Test log_norm()

  Test matrix:
[[-0.8  0.4  0.2]
 [ 1.  -3.   2. ]
 [ 0.   1.  -1. ]]
  p norms      4.4000    3.9967    6.0000
  log norms:   1.2000    0.0359    0.0000
  eigenvalues:
[-3.8185822  -0.92478235 -0.05663545]
  Test matrix:
[[ 5.  6.  3.]
 [-2.  7.  4.]
 [13.  9. -1.]]
  p norms     22.0000   17.8146   23.0000
  log norms:  22.0000   14.7033   21.0000
  eigenvalues:
[-5.27586464  3.62609414 12.6497705 ]
  Test matrix:
[[ 1.  2.  1.]
 [-2.  0.  3.]
 [-1. -3.  0.]]
  p norms      5.0000    3.9609    5.0000
  log norms:   5.0000    1.0000    5.0000
  eigenvalues:
[0.6534268+0.j         0.1732866+3.70722424j 0.1732866-3.70722424j]
  Test matrix:
[[  4. +7.j -10. -3.j   1. +6.j]
 [ -7. +1.j   4. +6.j  -2. +3.j]
 [ -5. +2.j   4.+11.j  -3. -6.j]]
  p norms     29.3561   19.8175   24.5853
  log norms:  26.1450   14.1173   20.5231
  eigenvalues:
[11.3788364 +6.45862336j -4.78237835+9.29945841j -1.59645804-8.75808177j]
  Test matrix:
[[-2.   0.   0. ]
 [ 0.  -1.   0. ]
 [ 0.   0.  -0.5]]
  p norms      2.0000    2.0000    2.0000
  log norms:  -0.5000   -0.5000   -0.5000
  eigenvalues:
[-2.  -1.  -0.5]

log_norm_test():
  Normal end of execution.
Fri Oct  7 21:06:07 2022