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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