[Numpy-discussion] matrices and __radd__

[Robert Kern]

On Wed, May 21, 2008 at 5:28 PM, Keith Goodman <kwgoodman@gmail.com> wrote:
> I have a class that stores some of its data in a matrix. I can't
> figure out how to do right adds with a matrix. Here's a toy example:
>
> class Myclass(object):
>
>    def __init__(self, x, a):
>        self.x = x  # numpy matrix
>        self.a = a  # some attribute, say, an integer
>
>    def __add__(self, other):
>        # Assume other is a numpy matrix
>        return Myclass(self.x + other, self.a += 1)
>
>    def __radd__(self, other):
>        print other
>
>>> from myclass import Myclass
>>> import numpy.matlib as mp
>>> m = Myclass(mp.zeros((2,2)), 1)
>>> x = mp.asmatrix(range(4)).reshape(2,2)
>>> radd = x + m
> 0
> 1
> 2
> 3
>
> The matrix.__add__ sends one element at a time. That sounds slow.

Well, what's actually going on here is this: ndarray.__add__() looks
at m and decides that it doesn't look like anything it can make an
array from. However, it does have an __add__() method, so it assumes
that it is intended to be a scalar. It uses broadcasting to treat it
as if it were an object array of the shape of x with each element
identical. Then it adds together the two arrays element-wise. Each
element-wise addition triggers the MyClass.__radd__() call.

> Do I
> have to grab the corresponding element of self.x and add it to the
> element passed in by matrix.__add__? Or is there a better way?

There probably is, but not being familiar with your actual use case,
I'm not sure what it would be.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
 -- Umberto Eco