CODEWITHSUNDEEP
pythonnumpy
Moormanly
Moormanly

Reputation: 1438

Rearranging axes in numpy?

I have an ndarray such as

>>> arr = np.random.rand(10, 20, 30, 40)
>>> arr.shape
(10, 20, 30, 40)

whose axes I would like to swap around into some arbitrary order such as

>>> rearranged_arr = np.swapaxes(np.swapaxes(arr, 1,3), 0,1)
>>> rearranged_arr.shape
(40, 10, 30, 20)

Is there a function which achieves this without having to chain together a bunch of np.swapaxes?

Upvotes: 31

Views: 51739

Answers (2)

hpaulj
hpaulj

Reputation: 231355

>>> arr = np.random.rand(10, 20, 30, 40)                                                               
>>> arr.transpose(3,0,2,1).shape                                                                       
(40, 10, 30, 20)

Upvotes: 13

Moormanly
Moormanly

Reputation: 1438

There are two options: np.moveaxis and np.transpose.

  • np.moveaxis(a, sources, destinations) docs

    This function can be used to rearrange specific dimensions of an array. For example, to move the 4th dimension to be the 1st and the 2nd dimension to be the last:

    >>> rearranged_arr = np.moveaxis(arr, [3, 1], [0, 3])
>>> rearranged_arr.shape
(40, 10, 30, 20)

    This can be particularly useful if you have many dimensions and only want to rearrange a small number of them. e.g.

    >>> another_arr = np.random.rand(0, 1, 2, 3, 4, 5, 6, 7, 8, 9)
>>> np.moveaxis(another_arr, [8, 9], [0, 1]).shape
(8, 9, 0, 1, 2, 3, 4, 5, 6, 7)

  • np.transpose(a, axes=None) docs

    This function can be used to rearrange all dimensions of an array at once. For example, to solve your particular case:

    >>> rearranged_arr = np.transpose(arr, axes=[3, 0, 2, 1])
>>> rearranged_arr.shape
(40, 10, 30, 20)

    or equivalently

    >>> rearranged_arr = arr.transpose(3, 0, 2, 1)
>>> rearranged_arr.shape
(40, 10, 30, 20)

Upvotes: 47

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