On Thu, Nov 15, 2012 at 11:37 PM, Charles R Harris <
charlesr.har...@gmail.com> wrote:
>
>
> On Thu, Nov 15, 2012 at 8:24 PM, Gökhan Sever <gokhanse...@gmail.com>wrote:
>
>> Hello,
>>
>> Could someone briefly explain why are these two operations are casting my
>> float32 arrays to float64?
>>
>> I1 (np.arange(5, dtype='float32')).dtype
>> O1 dtype('float32')
>>
>> I2 (100000*np.arange(5, dtype='float32')).dtype
>> O2 dtype('float64')
>>
>
> This one is depends on the size of the multiplier and is first present in
> 1.6.0. I suspect it is a side effect of making the type conversion code
> sensitive to magnitude.
>
>
>>
>>
>>
>> I3 (np.arange(5, dtype='float32')[0]).dtype
>> O3 dtype('float32')
>>
>> I4 (1*np.arange(5, dtype='float32')[0]).dtype
>> O4 dtype('float64')
>>
>
> This one probably depends on the fact that the element is a scalar, but
> doesn't look right. Scalars are promoted differently. Also holds in numpy
> 1.5.0 so is of old provenance.
>
>
This one has always bothered me:
In [3]: (-1*arange(5, dtype=uint64)).dtype
Out[3]: dtype('float64')
And there is another where the result is an object array, but I can't
recall it at the moment.
Chuck
> Chuck
>
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