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np.array_repr fails on np.matrix objects

See original GitHub issue

Cause of #5875:

>>> np.array_repr(np.eye(2).view(np.matrix))
Traceback (most recent call last):
  File "<pyshell#52>", line 1, in <module>
    np.array_repr(np.matrix(np.eye(2)))
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\numeric.py", line 1807, in array_repr
    ', ', "array(")
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 447, in array2string
    separator, prefix, formatter=formatter)
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 325, in _array2string
    _summaryEdgeItems, summary_insert)[:-1]
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 519, in _formatArray
    summary_insert)
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 496, in _formatArray
    word = format_function(a[-1])
  File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 598, in __call__
    if isnan(x):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Spot the x[i].shape == x.shape[1:] fallacy…

Issue Analytics

State:
Created 7 years ago
Comments:5 (5 by maintainers)

Top GitHub Comments

1reaction

charriscommented, Jan 3, 2017

At some point we should deprecate matrices and be done with them. After all, the most likely users are newbies and they should be encouraged to use Python 3.5 and later now that there is the @ operator.

0reactions

njsmithcommented, Jan 3, 2017

Ugh, @rgommers is right, I forgot about scipy.sparse.