[Numpy-discussion] Oddity with numpy.int64 integer division

Christian Marquardt christian@marquardt...
Mon Apr 23 15:41:56 CDT 2007


Hmmm,

On Mon, April 23, 2007 22:29, Christian Marquardt wrote:
> Actually,
>
> it happens for normal integers as well:
>
>    >>> n = np.array([-5, -100, -150])
>    >>> n // 100
>    array([ 0, -1, -1])
>    >>> -5//100, -100//100, -150//100
>    (-1, -1, -2)

and finally:

   >>> n % 100
   array([95,  0, 50])
   >>> -5 % 100, -100 % 100, -150 % 100
   (95, 0, 50)

So plain python / using long provides consistent results across //
and %, but numpy doesn't...

  Christian.

> On Mon, April 23, 2007 22:20, Christian Marquardt wrote:
>> Dear all,
>>
>> this is odd:
>>
>>    >>> import numpy as np
>>    >>> fact = 28250000L * 86400L
>>    >>> nn = np.array([-20905000L])
>>    >>> nn
>>    array([-20905000], dtype=int64)
>>    >>> nn[0] // fact
>>    0
>>
>> But:
>>
>>    >>> long(nn[0]) // fact
>>    -1L
>>
>> Is this a bug in numpy, or in python's implementation of longs? I would
>> think both should give the same, really... (Python 2.5, numpy
>> 1.0.3dev3725,
>> Linux, Intel compilers...)
>>
>> Many thanks for any ideas / advice,
>>
>>   Christian
>>
>> _______________________________________________
>> Numpy-discussion mailing list
>> Numpy-discussion@scipy.org
>> http://projects.scipy.org/mailman/listinfo/numpy-discussion
>>
>
>
> _______________________________________________
> Numpy-discussion mailing list
> Numpy-discussion@scipy.org
> http://projects.scipy.org/mailman/listinfo/numpy-discussion
>




More information about the Numpy-discussion mailing list