[Python-Dev] PEP 465: A dedicated infix operator for matrix multiplication

[Björn Lindqvist]

2014-04-08 12:23 GMT+02:00 Sturla Molden <sturla.molden at gmail.com>:
> Björn Lindqvist <bjourne at gmail.com> wrote:
>
>> import numpy as np
>> from numpy.linalg import inv, solve
>>
>> # Using dot function:
>> S = np.dot((np.dot(H, beta) - r).T,
>>            np.dot(inv(np.dot(np.dot(H, V), H.T)), np.dot(H, beta) - r))
>>
>> # Using dot method:
>> S = (H.dot(beta) - r).T.dot(inv(H.dot(V).dot(H.T))).dot(H.dot(beta) - r)
>>
>> Don't keep your reader hanging! Tell us what the magical variables H,
>> beta, r and V are. And why import solve when you aren't using it?
>> Curious readers that aren't very good at matrix math, like me, should
>> still be able to follow your logic. Even if it is just random data,
>> it's better than nothing!
>
> Perhaps. But you don't need to know matrix multiplication to see that those
> expressions are not readable. And by extension, you can still imagine that
> bugs can easily hide in unreadable code.
>
> Matrix multiplications are used extensively in anything from engineering to
> statistics to computer graphics (2D and 3D). This operator will be a good
> thing for a lot of us.

All I ask for is to be able to see that with my own eyes. Maybe there
is some drastic improvement I can invent to make the algorithm much
more readable? Then the PEP:s motivation falls down. I don't want to
have to believe that the code the pep author came up with is the most
optimal. I want to prove that for myself.


-- 
mvh/best regards Björn Lindqvist