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I'm trying to create a Matlab cell array in python and save it as a .mat file, but am running into problems when all the cells contain 2 values:

import scipy.io as sio

twoValues = {'a': array([[array([[2, 2]]), array([[3, 3]])]])}
sio.savemat('test.mat',twoValues)

In Matlab:

load('test.mat')
>>> a

a(:,:,1,1) =

           2           3


a(:,:,1,2) =

           2           3


>>> class(a)

ans =

int32

Back in python:

threeValues = {'a': array([[array([[2, 2, 2]]), array([[3, 3]])]])}
sio.savemat('test.mat',threeValues)

In Matlab:

>>> a

a = 

    [3x1 int32]    [2x1 int32]


>>> class(a)

ans =

cell

What's the reason for this?

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1 Answer

When you do this:

a = np.array([[np.array([[2, 2]]), np.array([[3, 3]])]])

the final call to np.array actually concatenates the inner two, so you get one array at the end:

>>> a
array([[[[2, 2]],

        [[3, 3]]]])

>>> a.shape
(1, 2, 1, 2)

But to mimic a cell array you want to basically have an array of arrays. You can acheive this by setting dtype=object, but you must create the array and set the elements separately to avoid the automatic merging.

three = array([[array([[2, 2, 2]]), array([[3, 3]])]])
two = np.empty(three.shape, dtype=object)
two[0,0,0] = np.array([[2,2]])
two[0,1,0] = np.array([[3,3]])

Then:

sio.savemat('two.mat', {'two': two})

to see what they look like:

>>> two
array([[[array([[2, 2]])],
        [array([[3, 3]])]]], dtype=object)

>>> two.shape
(1, 2, 1)

Note that I may have gotten confused about your desired shape, since you have so many nested brackets, so you might have to reshape some of this, but the idea should hold regardless.


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