On Wed, May 21, 2008 at 5:28 PM, Keith Goodman <[EMAIL PROTECTED]> 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 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
