[Numpy-discussion] What's the difference between calling __mul__ and *?
Fri Jun 7 11:38:22 CDT 2013
That's how it works in python:
Note: If the right operand's type is a subclass of the left operand's type and that subclass provides the reflected method for the operation, this method will be called before the left operand's non-reflected method. This behavior allows subclasses to override their ancestors' operations.
Note that matrix is a subclass of ndarray.
Also note that __mul__ can return NotImplemented, in which case again the method of rhs argument will be used.
From: email@example.com [mailto:firstname.lastname@example.org] On Behalf Of Will Lee
Sent: Friday, June 07, 2013 12:30 PM
To: Discussion of Numerical Python
Subject: [Numpy-discussion] What's the difference between calling __mul__ and *?
Can somebody tell me why these operations are not the same in numpy?
In : a = numpy.array([1, 2, 3.])
In : matrix = numpy.matrix([[1, 2, 3.], [4, 5, 6], [7, 8, 9]])
In : a.__mul__(matrix)
matrix([[ 1., 4., 9.],
[ 4., 10., 18.],
[ 7., 16., 27.]])
In : a * matrix
matrix([[ 30., 36., 42.]])
Essentially I'm trying to extend from numpy.ndarray. From my subclass
__mul__ I'd like to call the parent's __mul__ method. I ran into
problem when I'm trying to call super(SubArrayClass, self).__mul__()
method when working with a matrix. I also can't think of a way to use
operator.mul() due to the subclass nature. Is there any way to make
Any help is greatly appreciated.
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