[Numpy-discussion] numpy type mismatch

[Benjamin Root]

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
address is different from the memory address for np.int32.

Weirdness...
Ben Root
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