Konrad Hinsen wrote: > On 21.02.2008, at 08:41, Francesc Altet wrote: > > >> Well, it seems like a non-intrusive modification, but I like the >> scalars >> to remain un-indexable, mainly because it would be useful to raise an >> error when you are trying to index them. In fact, I thought that when >> you want a kind of scalar but indexable, you should use a 0-d array. >> > > I agree. In fact, I'd rather see NumPy scalars move towards Python > scalars rather than towards NumPy arrays in behaviour. A good balance should be sought. I agree that improvements are needed, especially because much behavior is still just a side-effect of how things were implemented rather than specifically intentional. > In particular, > their nasty habit of coercing everything they are combined with into > arrays is still my #1 source of compatibility problems with porting > code from Numeric to NumPy. I end up converting NumPy scalars to > Python scalars explicitly in lots of places. > This bit, for example, comes from the fact that most of the math on scalars still uses ufuncs for their implementation. The numpy scalars could definitely use some improvements.
However, I think my proposal for limited indexing capabilities should be considered separately from coercion behavior of NumPy scalars. NumPy scalars are intentionally different from Python scalars, and I see this difference growing due to where Python itself is going. For example, the int/long unification is going to change the ability for numpy.int to inherit from int. I could also forsee the Python float being an instance of a Decimal object or some other infinite precision float at some point which would prevent inheritance for the numpy.float object. The legitimate question is *how* different should they really be in each specific case. -Travis _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
