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Typestring "h2" works in 1.6, fails in master #294

njsmith opened this Issue · 9 comments

5 participants

NumPy member

Problem (which breaks scipy):



  • Re-enable parsing of type-strings like "h2" before the 1.7 release [DONE]
  • Give a deprecation warning for type-strings like "h100". Possibly also for type-strings like "h2" -- this isn't obvious. [DONE]
  • Disable at least "h100"- style type-strings for 1.9, or whenever we decide to finalize the deprecations that started in 1.7.

@njsmith, is this issue fixed now?

NumPy member

The 1.7 part of it is; I moved the milestone to 1.8.


blackout@debian:~$ python3
Python 3.2.3 (default, Feb 20 2013, 14:44:27)
[GCC 4.7.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.

import numpy as np
np.empty((1,), dtype='>h1000000')
array([-22330], dtype=int16)
np.empty((1,), dtype='h100')
array([-14680], dtype=int16)

gives me negative numbers

NumPy member

Working now. Types like h100 also pass as the number is simply ignored. It might be better at some point to raise an error for those.

@charris charris closed this
NumPy member

We do, there is a deprecation warning in place.

NumPy member

It isn't enabled, at least I don't see it.

NumPy member

Just added it to the 1.7 deprecation follow up ticket. It is there (and I think was new in 1.7):

In [1]: import warnings; warnings.filterwarnings('always')

In [2]: np.dtype('h100')
/usr/bin/ipython:1: DeprecationWarning: Specified size is invalid for this data type.
Size will be ignored in NumPy 1.7 but may throw an exception in future versions.
  #! /usr/bin/python
Out[2]: dtype('int16')
NumPy member

wow, there is an explicit 1.7 there sneeking in, not quite right of course... Maybe we can even turn it into an error in 1.9...

NumPy member

Ah, gotcha. Yes, making wrong sizes an error in 1.9 seems reasonable, should be mentioned in the release notes if we do.

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