A Thursday 21 February 2008, Konrad Hinsen escrigué: > I agree. In fact, I'd rather see NumPy scalars move towards Python > scalars rather than towards NumPy arrays in behaviour. 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.
Yeah, that happened to me too quite frequently, and it is quite uncomfortable. Also, I find this specially unpleasant: In [87]: numpy.int(1)/numpy.uint64(2) Out[87]: 0.5 Is this avoidable, or it's a consequence of the coercing rules? I guess this is the same case of: In [88]: numpy.array([1])/numpy.array([2], 'uint64') Out[88]: array([ 0.5]) By the way: In [89]: numpy.array(1)/numpy.array(2, 'uint64') Out[89]: 0.5 shouldn't this be array(0.5)? Cheers, -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-" _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion