Numpy 3D array arranging and reshaping

Question

I have a 3D numpy array that I need to reshape and arrange. For example, I have x=np.array([np.array([np.array([1,0,1]),np.array([1,1,1]),np.array([0,1,0]),np.array([1,1,0])]),np.array([np.array([0,0,1]),np.array([0,0,0]),np.array([0,1,1]),np.array([1,0,0])]),np.array([np.array([1,0,0]),np.array([1,0,1]),np.array([1,1,1]),np.array([0,0,0])])])

Which is a shape of (3,4,3), when printing it I get:

array([[[1, 0, 1],
        [1, 1, 1],
        [0, 1, 0],
        [1, 1, 0]],

       [[0, 0, 1],
        [0, 0, 0],
        [0, 1, 1],
        [1, 0, 0]],

       [[1, 0, 0],
        [1, 0, 1],
        [1, 1, 1],
        [0, 0, 0]]])

Now I need to reshape this array to a (4,3,3) by selecting the same index in each subarray and putting them together to end up with something like this:

array([[[1,0,1],[0,0,1],[1,0,0]],
[[1,1,1],[0,0,0],[1,0,1]],
[[0,1,0],[0,1,1],[1,1,1]],
[[1,1,0],[1,0,0],[0,0,0]]]

I tried reshape, all kinds of stacking and nothing worked (arranged the array like I need). I know I can do it manually but for large arrays manually isn't a choice.

Any help will be much appreciated. Thanks

You can simplify the array creation to: x= np.array([[[1,0,1], [1,1,1],...,1,1], [0,0,0]]]) — hpaulj
– hpaulj, Commented Jun 28, 2016 at 4:01

tom10 · Accepted Answer · 2016-06-28 03:57:00Z

6

swapaxes will do what you want. That is, if your input array is x and your desired output is y, then

np.all(y==np.swapaxes(x, 1, 0))

should give True.

edited Jun 28, 2016 at 3:57

answered Jun 28, 2016 at 3:35

tom10

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2 Comments

Mad Physicist Over a year ago

Also, possibly rollaxis. In this case the two will probably be equivalent, but for higher-dimensioned arrays, rollaxis is often the one you want since it preserves the order of the other axes better.

Ralph Over a year ago

Not sure why this isn't included under "See also" in the numpy documentation for reshape().

BENSALEM Mouhssen · Accepted Answer · 2018-06-02 15:51:49Z

2

For higher dimensional arrays, transpose will accept a tuple of axis numbers to permute the axes:

import numpy as np
foo = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]])
foo.transpose(1, 0, 2)

result:

array([[[ 1,  2],
        [ 5,  6],
        [ 9, 10]],

       [[ 3,  4],
        [ 7,  8],
        [11, 12]]])

answered Jun 2, 2018 at 15:51

BENSALEM Mouhssen

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1 Comment

blupp Over a year ago

Sometimes a 5 year old answer with no upvotes can save you tons of time. I'm happy I found this, thank you!

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