[Numpy-discussion] numpy array casting ruled not safe
Jaime Fernández del Río
jaime.frio at gmail.com
Sat Mar 7 21:21:21 EST 2015
On Sat, Mar 7, 2015 at 1:52 PM, Charles R Harris <charlesr.harris at gmail.com>
> On Sat, Mar 7, 2015 at 2:45 PM, Charles R Harris <
> charlesr.harris at gmail.com> wrote:
>> On Sat, Mar 7, 2015 at 2:02 PM, Dinesh Vadhia <dineshbvadhia at hotmail.com>
>>> This was originally posted on SO (
>>> and it was suggested it is probably a bug in numpy.take.
>>> Python 2.7.8 |Anaconda 2.1.0 (32-bit)| (default, Jul 2 2014, 15:13:35)
>>> [MSC v.1500 32 bit (Intel)] on win32
>>> Type "copyright", "credits" or "license()" for more information.
>>> >>> import numpy
>>> >>> numpy.__version__
>>> >>> a = numpy.array([9, 7, 5, 4, 3, 1], dtype=numpy.uint32)
>>> >>> b = numpy.array([1, 3], dtype=numpy.uint32)
>>> >>> c = a.take(b)
>>> Traceback (most recent call last):
>>> File "<pyshell#5>", line 1, in <module>
>>> c = a.take(b)
>>> TypeError: Cannot cast array data from dtype('uint32') to dtype('int32')
>>> according to the rule 'safe'
>> This actually looks correct for 32-bit windows. Numpy indexes with a
>> signed type big enough to hold a pointer to void, which in this case is an
>> int32, and the uint32 cannot be safely cast to that type.
> I note that on SO Jaime made the suggestion that take use unsafe casting
> and throw an error on out of bounds indexes. That sounds reasonable,
> although for sufficiently large integer types an index could wrap around to
> a good value. Maybe make it work only for npy_uintp.
It is mostly about consistency, and having take match what indexing already
does, which is to unsafely cast all integers:
In : np.arange(10)[np.uint64(2**64-1)]
I think no one has ever complained about that obviously wrong behavior, but
people do get annoyed if they cannot use their perfectly valid uint64 array
because we want to protect them from themselves. Sebastian has probably
given this more thought than anyone else, it would be interesting to hear
his thoughts on this.
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