[Numpy-discussion] Behaviour of ndarray and other objects with __radd__?

[Charles R Harris]

On Wed, Jun 15, 2011 at 9:34 AM, Olivier Delalleau <shish at keba.be> wrote:

> I don't really understand this behavior either, but juste note that
> according to
> http://docs.scipy.org/doc/numpy/user/c-info.beyond-basics.html
> "This attribute can also be defined by objects that are not sub-types of
> the ndarray"
>
> -=- Olivier
>
>
> 2011/6/15 Jonathan Taylor <jonathan.taylor at utoronto.ca>
>
>> Hi,
>>
>> I would like to have objects that I can mix with ndarrays in
>> arithmetic expressions but I need my object to have control of the
>> operation even when it is on the right hand side of the equation.  I
>> realize from the documentation that the way to do this is to actually
>> subclass ndarray but this is undesirable because I do not need all the
>> heavy machinery of a ndarray and I do not want users to see all of the
>> ndarray methods.  Is there a way to somehow achieve these goals?
>>
>> I would also very much appreciate some clarification of what is
>> happening in the following basic example:
>>
>> import numpy as np
>> class Foo(object):
>>    # THE NEXT LINE IS COMMENTED
>>    # __array_priority__ = 0
>>    def __add__(self, other):
>>        print 'Foo has control over', other
>>        return 1
>>    def __radd__(self, other):
>>        print 'Foo has control over', other
>>        return 1
>>
>> x = np.arange(3)
>> f = Foo()
>>
>> print f + x
>> print x + f
>>
>> yields
>>
>> Foo has control over [0 1 2]
>> 1
>> Foo has control over 0
>> Foo has control over 1
>> Foo has control over 2
>> [1 1 1]
>>
>> I see that I have control from the left side as expected and I suspect
>> that what is happening in the second case is that numpy is trying to
>> "broadcast" my object onto the left side as if it was an object array?
>>
>> Now if I uncomment the line __array_priority__ = 0 I do seem to
>> accomplish my goals (see below) but I am not sure why.  I am
>> surprised, given what I have read in the documentation, that
>> __array_priority__ does anything in a non subclass of ndarray.
>> Furthermore, I am even more surprised that it does anything when it is
>> 0, which is the same as ndarray.__array_priority__ from what I
>> understand.  Any clarification of this would be greatly appreciated.
>>
>>
There's a bit of code in the ufunc implementation that checks for the
__array_priority__ attribute regardless of if the object subclasses ndarray,
probably because someone once needed to solve the same problem you are
having. The comment that goes with it is

    /*
     * FAIL with NotImplemented if the other object has
     * the __r<op>__ method and has __array_priority__ as
     * an attribute (signalling it can handle ndarray's)
     * and is not already an ndarray or a subtype of the same type.
    */

Chuck
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