Comment by quietbritishjim

1 month ago

It means the same thing in MATLAB and numpy:

   Z = np.array([[1,2,3]])
   W = Z + Z.T
   print(W)

Gives:

   [[2 3 4]
    [3 4 5]
    [4 5 6]]

It's called broadcasting [1]. I'm not a fan of MATLAB, but this is an odd criticism.

[1] https://numpy.org/devdocs/user/basics.broadcasting.html#gene...

1 comment

quietbritishjim

adgjlsfhk1 1 month ago

One of the really nice things Julia does is make broadcasting explicit. The way you would write this in Julia is

    Z = [1,2,3]

    W = Z .+ Z' # note the . before the + that makes this a broadcasted

This has 2 big advantages. Firstly, it means that users get errors when the shapes of things aren't what they expected. A DimmensionMismatch error is a lot easier to debug than a silently wrong result. Secondly, it means that julia can use `exp(M)` etc to be a matrix exponential, while the element-wise exponential is `exp.(M)`. This allows a lot of code to naturally work generically over both arrays and scalars (e.g. exp of a complex number will work correctly if written as a 2x2 matrix)