Manipulating nested numpy array

Question

I have a numpy array:

array([[ 0,  1,  2,  3,  4,  5,  6],
       [14, 15, 16, 17, 18, 19, 20],
       [28, 29, 30, 31, 32, 33, 34]])

I want to divide elementwise by 10 and then round elementwise (<0.5 rounding down to 0).

Just do it? np.round(array / 10) This will be subject to a slightly different rounding bahaviour than you specified (depending on the python version) but this will only affect .5 values — MSeifert
– MSeifert, Commented Apr 6, 2016 at 14:00
This produces the error:TypeError: unsupported operand type(s) for /: 'list' and 'int'. — Chris Parry
– Chris Parry, Commented Apr 6, 2016 at 14:04

Francesco Nazzaro · Accepted Answer · 2016-04-06 14:26:06Z

1

try:

import numpy as np

array = np.array([[ 0,  1,  2,  3,  4,  5,  6],
                  [14, 15, 16, 17, 18, 19, 20],
                  [28, 29, 30, 31, 32, 33, 34]], dtype=float)
result = np.round(array / 10)

result will be array([[ 0., 0., 0., 0., 0., 0., 1.], [ 1., 2., 2., 2., 2., 2., 2.], [ 3., 3., 3., 3., 3., 3., 3.]])

edited Apr 6, 2016 at 14:26

answered Apr 6, 2016 at 14:09

Francesco Nazzaro

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MSeifert · Accepted Answer · 2016-04-06 14:18:21Z

0

There is a rounding function in numpy that can take care of rounding: numpy.round():

import numpy as np

array = np.array([[ 0,  1,  2,  3,  4,  5,  6],
                  [14, 15, 16, 17, 18, 19, 20],
                  [28, 29, 30, 31, 32, 33, 34]])

np.round(array / 10)

# array([[ 0.,  0.,  0.,  0.,  0.,  0.,  1.],
#        [ 1.,  2.,  2.,  2.,  2.,  2.,  2.],
#        [ 3.,  3.,  3.,  3.,  3.,  3.,  3.]])

this will however round x.5 (if x is even) down but y.5 (if y is odd) up. See the notes in np.around()

edited Apr 6, 2016 at 14:18

answered Apr 6, 2016 at 14:12

MSeifert

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