Differences between the "@" operator and np.matmul()

Question

Is there an advantage to using the @ operator over numpy.matmul when multiplying vectors, matrices, etc? Is this mainly for readability? Whats is the convention?

Does this answer your question? [Difference between numpy dot() and Python 3.5+ matrix multiplication @](https://stackoverflow.com/questions/34142485/difference-between-numpy-dot-and-python-3-5-matrix-multiplication) — Warcupine, Jul 31 '20 at 19:44
Basically the same as the choice between `np.add` and `+`, or `np.multiply` and `*`. — hpaulj, Jul 31 '20 at 19:50
`@` was added precisely because [the Numpy community wanted an infix operator to replace explicit use of `matmul`](https://www.python.org/dev/peps/pep-0465/#motivation). — chepner, Jul 31 '20 at 20:25

score 3 · Answer 1 · answered Jul 31 '20 at 20:19

3

As the doc explains: The matmul function implements the semantics of the @ operator introduced in Python 3.5 following PEP465.

So basically, @ is the same as np.matmul without method parameters.

answered Jul 31 '20 at 20:19

Ehsan

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Differences between the "@" operator and np.matmul()

1 Answers1