[Numpy-discussion] Scalar coercion
Thu Mar 1 16:39:06 CST 2007
A ticket was posted that emphasizes that the current behavior of NumPy
with regards to scalar coercion is different than numarray's behavior.
If we were pre 1.0, I would probably change the behavior to be in-line
with numarray. But, now I think it needs some discussion because we are
changing the behavior of a released version of NumPy and we need some
more conservatism in how changes happen.
If we can classify the current behavior as a bug then we can change it.
Otherwise, I'm concerned.
The behavior has to do with a mixed scalar/array computation. NumPy
does not let scalars (equivalently 0-d arrays) determine the output type
of the array operation, *unless* the scalar is of a fundamentally
different kind (i.e. the array is an integer-type but the scalar is a
floating-point type). In this case, the current behavior is to coerce
the array to the smallest-type in that general category of scalars.
The reason for this behavior is to make sure that
array([1,2,3,4],int8)*10 returns an int8 (instead of an int32 because
of how the 10 is interpreted by Python).
The current behavior, however, also means that
array([1,2,3,4],int8)*10.0 will return a float32 array.
I think numarray would return a float64 array in this case (i.e. the
type of the scalar would be honored when the coercion was between two
different kinds of arrays).
So the question is: Do we keep the current behavior or change the
behavior to be more consistent with numarray. My current preference is
to change the behavior so it is more consistent with numarray (even
though it's actually not going to be trivial to do that).
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