Numpy Array Multiplication

Question

I couldn't seem to find this problem on stackoverflow although I'm sure someone has asked this before.

I have two numpy arrays as follows:

a = np.ones(shape = (2,10))
b = np.ones(2)

I want to multiply the first row of 10 of a by the first number in b and the second row by the second number. I can do this using lists as follows:

np.array([x*y for x,y in zip(b,a)])

I was wondering if there is a way to do this in numpy that would be a similar one liner to the list method.

I am aware I can reshape a to (1,2,10) and b to (2,1) to effectively achieve this - is this the only solution? Or is there a numpy method that can do this without manually reshaping.

Broadcasting adds leading dimensions as needed, but in this case you need a new trailing one. — hpaulj
– hpaulj, Commented Jun 3, 2020 at 2:18

Stack Player · Accepted Answer · 2020-06-03 01:29:00Z

1

This might be what you are looking for:

a*np.tile(np.expand_dims(b,axis=1),(1,10))

If you want to make use of the automatic numpy broadcasting, you need to reshape b first:

np.multiply(a, b.reshape(2,1))

edited Jun 3, 2020 at 1:29

answered Jun 3, 2020 at 1:20

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3 Comments

tryingtocode101 Over a year ago

That is! I'm guessing from this answer, there probably isn't a single built-in numpy method for this specific array multiplication scenario?

Stack Player Over a year ago

I edited my answer, might be clearer this time. You can use the multiply function for automating your broadcasting, but you still need to reshape to guide the function for the tiling dimension.

hpaulj Over a year ago

a * b[:, None] is another way to write the broadcasting solution.

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