add small np.array to larger np.array

Question

In R, I can easily add a smaller vector to a larger vector (assuming length of larger vector is a multiple of length of smaller vector)

a <- seq(1,10,1)
# [1]  1  2  3  4  5  6  7  8  9 10
b <- seq(1,2,1)
# [1] 1 2
a+b
# [1]  2  4  4  6  6  8  8 10 10 12

Is there an easy way to do this in Python?

import numpy as np
a = np.arange(1, 10)
# array([1, 2, 3, 4, 5, 6, 7, 8, 9])
b = np.arange(1,4)
# array([1, 2, 3])

What I tried

a + b?
np.add(a, b)?

Nils Werner · Accepted Answer · 2019-09-08 15:00:57Z

4

NumPy does not simply assume that you might want to repeat b before adding it to a, you must tell it to do that yourself.

The system by which you can do that is called broadcasting. You create a 2D array by adding another axis of exactly the same length of b. Adding b to that 2D array has exactly the desired behaviour.

And afterwards we flatten the array back to 1D.

(a.reshape(-1, len(b)) + b).ravel()

edited Sep 8, 2019 at 15:00

answered Sep 8, 2019 at 14:55

Nils Werner

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1 Comment

CPak Over a year ago

Yeah, sorry, my example code contained a typo. Will accept your answer when it allows me.

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