Comment by nis251413

1 day ago

The syntax of actual array languages can be beautifully concise and expressive. You can express mathematical formulas in ways that makes sense when you read a single line, and once you get used to the notation and some originally non-intuitive quirks (from a programming background perspective), you can write in very few lines what otherwise would take you several lines of rather ugly, less readable code.

In my view, python+numpy is not actually an array language. Numpy as a library adds vectorization operations to python in order to help with speed. This is different. It does not (intend to) bring the advantages that array language syntax has, even if it was a bit more consistent.

7 comments

nis251413

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aborsy  1 day ago

Yeah. Compare

A = [1, 2; 3, 4];

x = [5; 6];

y = A * x;

with this uglier version:

import numpy as np

A = np.array([[1, 2], [3, 4]])

x = np.array([[5], [6]])

y = A @ x

  • threeducks  21 hours ago

    You don't have to wrap the lists in np.array if you use NumPy functions (or if one of the arguments already is a NumPy array, which usually is the case):

        from numpy import *

    A = [[1, 2], [3, 4]]
    x = [[5], [6]]
    y = dot(A, x)

    • nis251413  4 hours ago

      That's nice, but only works, as I understand it, if you use numpy-only functions, which means that you should not use those who denote also base-pythonic, eg +,* etc operations, because then they are interpreted differently. Eg `A + x` gives

          [[1, 2], [3, 4], [5], [6]]

      instead of

          array([[ 6,  7],[ 9, 10]])

      You have to keep track of the context there to know what you can do and what not I guess, which is not ideal.