[SciPy-dev] Suppressing of numpy __mul__, __div__ etc
Sebastian Walter
sebastian.walter@gmail....
Thu Dec 17 09:22:09 CST 2009
2009/12/17 Dmitrey <tmp50@ukr.net>:
> От кого: Sebastian Walter <sebastian.walter@gmail.com>
>
> 1) From an abstract point of view, oofun should be a data type.
> And the container of choice would be a numpy.array of dtype ofun, not
> of dtype object.
>
> so array([1,2,3],dtype=float) * oofun(2) should return
> array([2,4,6],dtype=returntype(oofun,float))
>
> What do you mean under oofun(2) ?!
i don't know the intrinsic implementation of your AD tool. Maybe I'm
wrong, but in automatic differentiation,
a computational graph of an algorithm is
> oofun is
> array([1,2,3],dtype=float) * oofun_instance should return result of type
> oofun and nothing else.
> Same to other classes - SAGE, polinomials, etc.
could you elaborate on why someone would
want to do an `array * polynomial` operation and not expect it to
be an array of polynomial as result?
>
> When ndarray.__mul__(self, other) is called, and other is a container,
> it should simply check if it knows how to handle that container.
> If ndarray doesn't know, it should call the other.__rmul__ and hope
> that `other` knows what to do.
>
> E.g.
>
> class matrix:
> iscontainer = True
> ....
>
> class ndarray:
>
> def __mul__(self, other):
> if other.iscontainer:
> if not know_what_to_do_with(other):
> other.__rmul__(self)
>
> else:
> do what is done now: treat other as dtype=object
>
> then array * matrix
> would call the ndarray.__mul__ operator
> it then realizes that matrix is a container but ndarray doesnt know
> what to do with it. It would therefore call matrix.__rmul__
>
>
>
> If other is not a container it is treated as object and we would get
> the current behaviour. This would allow to stay backward compatible.
>
> As for me, I dislike the idea - it's too complicated, and some containers
> sometimes could want to take operations priority, using their __rmul__ etc
> instead of ndarray __mul__ etc.
you would simply add
class oofun:
iscontainer = True
to your oofun implementation and you would get exactly what you want....
I don't think this in any way complicated. It is basically what you
have asked for in your original post.
>
>
> _______________________________________________
> SciPy-Dev mailing list
> SciPy-Dev@scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-dev
>
>
More information about the SciPy-Dev
mailing list