Yeah, I am not seeing any way around it at the moment. I guess I will have
to use the bitarray package for now. I was hoping for some fast per-element
processing, but at the moment, I guess I will have to sacrifice that just
to have something that worked correctly.
Ben Root
On Tue, Apr 28, 2015 at 10:19 AM, Jaime Fernández del Río <
jaime.f...@gmail.com> wrote:
> On Tue, Apr 28, 2015 at 7:00 AM, Benjamin Root <ben.r...@ou.edu> wrote:
>
>> I have a need to have a numpy array of 17 byte (more specifically, at
>> least 147 bits) values that I would be doing some bit twiddling on. I have
>> found that doing a dtype of "i17" yields a dtype of int32, which is
>> completely not what I intended. Doing 'u17' gets an "data type not
>> understood". I have tried 'a17', but then bitwise_or() and left_shift() do
>> not work (returns "NotImplemented").
>>
>
>> How should I be going about this?
>>
>
> The correct type to use would be a void dtype:
>
> >>> dt = np.dtype('V17')
> >>> dt.itemsize
> 17
>
> Unfortunately, it does not support bitwise operations either, which seems
> like an oddity to me:
>
> >>> a = np.empty(2, dt)
> >>> a[0] = 'abcdef'
> >>> a[1] = bytearray([64, 56, 78])
> >>> a[0] | a[1]
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> TypeError: unsupported operand type(s) for |: 'numpy.void' and 'numpy.void'
>
> Any fundamental reason for this?
>
> Jaime
>
> --
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> ( O.o)
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