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.tay...@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. > > Output with __array_priority__ uncommented: > > jtaylor@yukon:~$ python foo.py > Foo has control over [0 1 2] > 1 > Foo has control over [0 1 2] > 1 > > Thanks, > Jonathan. > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
