[Numpy-discussion] numpy type mismatch

Charles R Harris charlesr.harris@gmail....
Fri Jun 10 15:02:21 CDT 2011


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
> address is different from the memory address for np.int32.
>
>
One of them is probably a long, print out the typecode, dtype.char.

Chuck
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