Ensure that indices are suitable for numpy.take. #92
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On a 32-bit machine, numpy.take may refuse to use int64 arrays for indices.
| dtype.num == numpy.dtype(numpy.int64).num): | ||
| # If both types have the same string description (byte order, basic | ||
| # type, and number of bytes), then it is safe to return a view. | ||
| if (dtype.str == rval.dtype.str): |
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Please also update the docstring of _asarray, more precisely the part that says:
Currently, this issue has only been causing trouble when the target
data type is 'int32' or 'int64', on some computers. As a result, we
silently fix it only in this situation: if a type mismatch is detected
with another data type, an exception is raised (if that happens, then this
function may need to be modified to also handle this other data type).
|
I'm going to merge this and fix the typo, and open a ticket for @lamblin to get the docstring. |
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Manually merged as 349f7f6 |
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Correction: 5e6ce10a3. |
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On a 32-bit machine, numpy.take may refuse to use int64 arrays for indices.