[Numpy-discussion] Type checking inconsistency
Sun Oct 16 11:48:58 CDT 2011
On Sun, Oct 16, 2011 at 12:39 PM, Tony Yu <email@example.com> wrote:
> I noticed a type-checking inconsistency between assignments using slicing
> and fancy-indexing. The first will happily cast on assignment (regardless of
> type), while the second will throw a type error if there's reason to believe
> the casting will be unsafe. I'm not sure which would be the "correct"
> behavior, but the inconsistency is surprising.
> >>> import numpy as np
> >>> a = np.arange(10)
> >>> b = np.ones(10, dtype=np.uint8)
> # this runs without error
> >>> b[:5] = a[:5]
> >>> mask = a < 5
> >>> b[mask] = b[mask]
> TypeError: array cannot be safely cast to required type
> And I just noticed that 1D arrays behave differently than 2D arrays. If you
replace the above definitions of a, b with:
>>> a = np.arange(10)[:, np.newaxis]
>>> b = np.ones((10, 1), dtype=np.uint8)
The rest of the code will run without error.
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