I get the same results as you, Kathy.
*surprised*
(On OS X (Lion), 64 bit, numpy 2.0.0.dev-55472ca, Python 2.7.2.
On 24.01.2012, at 16:29, Kathleen M Tacina wrote:
> I was experimenting with np.min_scalar_type to make sure it worked as
> expected, and found some unexpected results for integers between 2**63 and
> 2**64-1. I would have expected np.min_scalar_type(2**64-1) to return uint64.
> Instead, I get object. Further experimenting showed that the largest
> integer for which np.min_scalar_type will return uint64 is 2**63-1. Is this
> expected behavior?
>
> On python 2.7.2 on a 64-bit linux machine:
> >>> import numpy as np
> >>> np.version.full_version
> '2.0.0.dev-55472ca'
> >>> np.min_scalar_type(2**8-1)
> dtype('uint8')
> >>> np.min_scalar_type(2**16-1)
> dtype('uint16')
> >>> np.min_scalar_type(2**32-1)
> dtype('uint32')
> >>> np.min_scalar_type(2**64-1)
> dtype('O')
> >>> np.min_scalar_type(2**63-1)
> dtype('uint64')
> >>> np.min_scalar_type(2**63)
> dtype('O')
>
> I get the same results on a Windows XP machine running python 2.7.2 and
> numpy 1.6.1.
>
> Kathy
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