On Sat, Feb 14, 2015 at 2:36 PM, Georg Brandl <g.bra...@gmx.net> wrote:
> > In the case of int, there is a good reason for this behavior - bool. In > python, > > we want True + True == 2. In numpy, where binary operations preserve > > subclasses, you have > > > >>>> import numpy > >>>> numpy.bool_(1) + numpy.bool_(1) > > True > > I don't think numpy.bool_ subclasses some class like numpy.int_. And numpy.bool_ subclasses don't preserve type in addition: >>> import numpy >>> class Bool(numpy.bool_): ... pass ... >>> numpy.bool_.mro() [<class 'numpy.bool_'>, <class 'numpy.generic'>, <class 'object'>] >>> Bool(1) + Bool(1) True >>> type(_) <class 'numpy.bool_'> So there goes my theory. :-) I think all these examples just highlight the need for a clear guidance when self.__class__() can be called in base classes to construct instances of derived classes. Apparently numpy has it both ways. One way for scalars (see above) and the other for arrays: >>> class Array(numpy.ndarray): ... pass ... >>> a = Array(1) >>> a[0] = 1 >>> a+a Array([ 2.])
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