[Numpy-discussion] Matching 0-d arrays and NumPy scalars
Thu Feb 21 01:47:58 CST 2008
Travis E. Oliphant wrote:
> Hi everybody,
> In writing some generic code, I've encountered situations where it would
> reduce code complexity to allow NumPy scalars to be "indexed" in the
> same number of limited ways, that 0-d arrays support.
> For example, 0-d arrays can be indexed with
> * Boolean masks
> * Ellipses x[...] and x[..., newaxis]
> * Empty tuple x[()]
> I think that numpy scalars should also be indexable in these particular
> cases as well (read-only of course, i.e. no setting of the value would
> be possible).
> This is an easy change to implement, and I don't think it would cause
> any backward compatibility issues.
> Any opinions from the list?
> Best regards,
> -Travis O.
As for me I would be glad to see same behavior for numbers as for arrays
at all, like it's implemented in MATLAB, i.e.
ok, for numpy having at least possibility to use
would be very convenient, now atleast_1d(a) is required very often, and
sometimes errors occur only some times later, already during execution
of user-installed code, when user usually pass several-variables arrays
and some time later suddenly single-variable array have been encountered.
I guess it could be implemented via a simple check:
if user calls for a and a is array of shape () (i.e. like
a=array(80)) then return a[()]
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