Sum rows in 2d numpy

Question

Assume the following 2d numpy is given:

myNP = np.array([[5., 2., 1.],
                [3., 3., 3.],
                [3., 3., 3.]])

One has to find the weight of each point in each row in relation to the sum of the row.

in reference to the example above the expected result need to be:

([[0.625, 0.25 , 0.125],
  [0.333, 0.333, 0.333],
  [0.333, 0.333, 0.333]])

Indeed it gives a solution – Elhanan Schwarts Nov 07 '20 at 21:10 — Elhanan Schwarts, Nov 07 '20 at 21:10
`myNP/myNP.sum(axis=1).reshape(-1,1)` – anon01 Nov 07 '20 at 21:18 — anon01, Nov 07 '20 at 21:18

score 1 · Answer 1 · answered Nov 07 '20 at 20:58

1

the sum function does exactly what you need. You just need to specify the axis. In your case myNP.sum(axis=1) should do the trick

answered Nov 07 '20 at 20:58

Flavio Moraes

Grayrigel · Accepted Answer · 2020-11-07T21:24:04.250

1

Try this:

myNP_weight = (myNP/myNP.sum(axis=1).reshape(-1,1)).round(3)

Or

myNP_weight = (myNP/myNP.sum(axis=1)[:, None]).round(3)

Output:

>>> print(myNP_weight)
array([[0.625, 0.25 , 0.125],
       [0.333, 0.333, 0.333],
       [0.333, 0.333, 0.333]])

edited Nov 07 '20 at 21:24

answered Nov 07 '20 at 21:16

Grayrigel

2 Answers2