# [Numpy-discussion] numpy type mismatch

Olivier Delalleau shish@keba...
Fri Jun 10 15:24:36 CDT 2011

```2011/6/10 Benjamin Root <ben.root@ou.edu>

>
>
> On Fri, Jun 10, 2011 at 3:02 PM, Charles R Harris <
> charlesr.harris@gmail.com> wrote:
>
>>
>>
>> On Fri, Jun 10, 2011 at 1:50 PM, Benjamin Root <ben.root@ou.edu> wrote:
>>
>>> Came across an odd error while using numpy master.  Note, my system is
>>> 32-bits.
>>>
>>> >>> import numpy as np
>>> >>> type(np.sum([1, 2, 3], dtype=np.int32)) == np.int32
>>> False
>>> >>> type(np.sum([1, 2, 3], dtype=np.int64)) == np.int64
>>> True
>>> >>> type(np.sum([1, 2, 3], dtype=np.float32)) == np.float32
>>> True
>>> >>> type(np.sum([1, 2, 3], dtype=np.float64)) == np.float64
>>> True
>>>
>>> So, only the summation performed with a np.int32 accumulator results in a
>>> type that doesn't match the expected type.  Now, for even more strangeness:
>>>
>>> >>> type(np.sum([1, 2, 3], dtype=np.int32))
>>> <type 'numpy.int32'>
>>> >>> hex(id(type(np.sum([1, 2, 3], dtype=np.int32))))
>>> '0x9599a0'
>>> >>> hex(id(np.int32))
>>> '0x959a80'
>>>
>>> So, the type from the sum() reports itself as a numpy int, but its memory
>>>
>>>
>> One of them is probably a long, print out the typecode, dtype.char.
>>
>> Chuck
>>
>>
>>
> Good intuition, but odd result...
>
> >>> import numpy as np
> >>> a = np.sum([1, 2, 3], dtype=np.int32)
> >>> b = np.int32(6)
> >>> type(a)
> <type 'numpy.int32'>
> >>> type(b)
> <type 'numpy.int32'>
> >>> a.dtype.char
> 'i'
> >>> b.dtype.char
> 'l'
>
> So, the standard np.int32 is getting listed as a long somehow?  To further
> investigate:
>
> >>> a.dtype.itemsize
> 4
> >>> b.dtype.itemsize
> 4
>
> So, at least the sizes are right.
>
> Ben Root
>

long on a 32 bit computer is indeed int32.

I think your issue is that in your version of numpy, numpy.dtype('i') !=
numpy.dtype('l') (while they are equal e.g. in Numpy 1.5.1).

-=- Olivier
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