[Numpy-discussion] matrices and __radd__
Wed May 21 18:07:43 CDT 2008
On Wed, May 21, 2008 at 5:28 PM, Keith Goodman <email@example.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
> 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.
"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
More information about the Numpy-discussion