When you do this:
代码语言：javascript复制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:
代码语言：javascript复制>>> 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.
代码语言：javascript复制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:
代码语言：javascript复制sio.savemat('two.mat', {'two': two})to see what they look like:
代码语言：javascript复制>>> 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.
例如：
代码语言：javascript复制npose = 5
nsmile = 2
poseSmile_cell = np.empty((npose,nsmile),dtype=object)
for i in range(5):
for k in range(2):
poseSmile_cell[i,k] = np.zeros((4,4))
print poseSmile_cell.shape参考文献：
https://stackoverflow.com/questions/19797822/creating-matlab-cell-arrays-in-python
