How to get 2D array values based on 1D array values?

Question

>>> image = np.arange(20).reshape((4, 5))
>>> image
array([[ 0,  1,  2,  3,  4],
       [ 5,  6,  7,  8,  9],
       [10, 11, 12, 13, 14],
       [15, 16, 17, 18, 19]])
>>> idx = [[2, 1], [2, 3], [3, 4]]

How do I get the values from the image array which coordinate is specified in idx? From the above code, I want to get the values 11 (image[2, 1]), 13 (image[2, 3]), and 19 (image[3, 4]). Thank you.

13 is at image [2,3]. I cannot edit, as it takes less than six chars. — Bartłomiej
– Bartłomiej, Commented Aug 25, 2018 at 22:23

Rendicahya · Accepted Answer · 2018-08-30 09:33:58Z

2

(if ya gonna use numpy, use numpy)

Make definitions:

>>> image = np.arange(20).reshape((4, 5))
>>> idx = np.array([[2, 1], [2, 3], [3, 4]]).T

Solution using fancy indexing capabilities of Numpy:

>>> image[tuple(idx)]
array([11, 13, 19])

edited Aug 30, 2018 at 9:33

Rendicahya

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answered Aug 25, 2018 at 19:09

kevinkayaks

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1 Comment

xdze2 Over a year ago

image[tuple(idx)] gives array([11, 13, 18]) using your idx definition. Found at the very end of docs.scipy.org/doc/numpy/user/basics.indexing.html

kevh · Accepted Answer · 2018-08-25 15:40:39Z

0

You can use a list comprehension:

[image[x[0], x[1]] for x in idx]

>>> [11, 13, 19]

answered Aug 25, 2018 at 15:40

kevh

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