CODEWITHSUNDEEP
pythonarraysnumpyscientific-computing
Javad Kasravi
Javad Kasravi

Reputation: 11

Append element wise in numpy

I want to append two NumPy arrays. These two arrays have the same shape and I would like to append each element of two arrays and store it in another NumPy array which has a less computational cost. for example:

a =  np.arange (12).reshape(4,3)
b = np.arange (2,14).reshape(4,3)

I would like to create the following np.array:

c = [[ (0,2)  (1,3)  (2,4)]
 [ (3,5)  (4,6)  (5,7)]
 [ (6,8)  (7,9) (8,10)]
 [(9,11) (10,12) (11,13)]]

it should be noted that by using for loop it can be created, but the computational cost for higher dimension is huge. it is better to use vectorized way. Could you please tell me how can create this np.array?

Upvotes: 0

Views: 1122

Answers (2)

Lukas Schmid
Lukas Schmid

Reputation: 1960

Using dstack and reshape, you can both zip and reform them. np.dstack((a, b)).reshape(4,3,2)

That leaves you with

[[[ 0  2]
  [ 1  3]
  [ 2  4]]

 [[ 3  5]
  [ 4  6]
  [ 5  7]]

 [[ 6  8]
  [ 7  9]
  [ 8 10]]

 [[ 9 11]
  [10 12]
  [11 13]]]

Which should provide the same functionality as tuples would. I've tried multiple approaches, but didn't manage to keep actual tuples in the numpy array

Upvotes: 0

juanpa.arrivillaga
juanpa.arrivillaga

Reputation: 96360

It is not exactly clear what shape you are expecting, but I believe you are looking for numpy.dstack:

>>> a
array([[ 0,  1,  2],
       [ 3,  4,  5],
       [ 6,  7,  8],
       [ 9, 10, 11]])
>>> b
array([[ 2,  3,  4],
       [ 5,  6,  7],
       [ 8,  9, 10],
       [11, 12, 13]])
>>> np.dstack([a,b])
array([[[ 0,  2],
        [ 1,  3],
        [ 2,  4]],

       [[ 3,  5],
        [ 4,  6],
        [ 5,  7]],

       [[ 6,  8],
        [ 7,  9],
        [ 8, 10]],

       [[ 9, 11],
        [10, 12],
        [11, 13]]])

Upvotes: 2

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