scalar object bug or feature?

[Christopher Hanley]

Greetings,

I can't decide if the following is a bug or feature.  Numpy scalars are 
allowed to overflow silently while numarray upcasts to a larger python 
type.  I guess my biggest problem is that the overflow occurs silently.

In any case, is this known and expected behavior?

Thanks,
Chris



NUMARRAY example:

In [1]: import numarray as n

In [2]: a = n.array([2200,14000],type=n.UInt32)

In [3]: a0= a[0]

In [4]: a1 = a[1]

In [5]: adiff = a0-a1

In [6]: print a0,a1,adiff
2200 14000 -11800

In [7]: print type(a0),type(a1),type(adiff)
<type 'long'> <type 'long'> <type 'long'>

NUMPY example:
In [1]: import numpy as n

In [2]: a = n.array([2200,14000],dtype=n.uint32)

In [3]: a0= a[0]

In [4]: a1 = a[1]

In [5]: adiff = a0-a1

In [6]: print a0,a1,adiff
2200 14000 4294955496

In [7]: print type(a0),type(a1),type(adiff)
<type 'numpy.uint32'> <type 'numpy.uint32'> <type 'numpy.uint32'>



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