On Wed, Apr 13, 2016 at 3:17 AM, Antony Lee <antony....@berkeley.edu> wrote: > > This kind of issue (see also https://github.com/numpy/numpy/issues/3511) has become more annoying now that indexing requires integers (indexing with a float raises a VisibleDeprecationWarning). The argument "dividing an uint by an int may give a result that does not fit in an uint nor in an int" does not sound very convincing to me,
It shouldn't because that's not the rule that numpy follows. The range of the result is never considered. Both *inputs* are cast to the same type that can represent the full range of either input type (for that matter, the actual *values* of the inputs are also never considered). In the case of uint64 and int64, there is no really good common type (the integer hierarchy has to top out somewhere), but float64 merely loses resolution rather than cutting off half of the range of uint64. -- Robert Kern
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