On Mon, Aug 8, 2011 at 10:54 AM, Olivier Delalleau <shish@keba.be> wrote:

Hi,

This is with numpy 1.6.1 under Linux x86_64, testing the upcast mechanism of "scalar + array":

>>> import numpy; print (numpy.array(3, dtype=numpy.complex128) + numpy.ones(3, dtype=numpy.float32)).dtype
complex64

Since it has to upcast my array (float32 is not "compatible enough" with complex128), why does it upcast it to complex64 instead of complex128?
As far as I can tell 1.4.x and 1.5.x versions of numpy are indeed upcasting to complex128.

The 0 dimensional array is being treated as a scalar, hence is cast to the type of the 1d array. This seems more consistent with the idea that 0 dimensional arrays act like scalars, but I suppose that is open to discussion.

Chuck

I'm afraid I don't understand your reply. I know that the 0d array is a scalar, and thus should not lead to an upcast "unless the scalar is of a fundamentally different kind of data (i.e., under a different hierarchy in the data-type hierarchy) than the array" (quoted from http://docs.scipy.org/doc/numpy/reference/ufuncs.html).

This is one case where it is under a different hierarchy and thus should trigger an upcast. What I don't understand it why it upcasts to complex64 instead of complex128.

Note that:
1. When replacing "numpy.ones" with "numpy.array" it yields complex128 (expected upcast of scalar addition of complex128 with float32)
2. The behavior is similar if instead of "3" I use a number which cannot be represented exactly with a complex64 (so it's not a rule about picking the smallest data type able to exactly represent the result)

-=- Olivier