How to select elements from a multidimensional array with python : array[:][i][j]?

In Python, I have a 3 dimensional array A :

A=np.random.random((3,2,3))

print(A)

Out[6]: [[[0.89565135 0.79502322 0.89015957]
  [0.40303084 0.80496231 0.50278239]]

 [[0.70610822 0.61269108 0.00470925]
  [0.29734101 0.67986295 0.34584381]]

 [[0.71822397 0.99326199 0.40949422]
  [0.97733739 0.38916931 0.91475145]]]

I would like to select the first element of each submatrix and to make an array from them [0.89565135,0.70610822,0.71822397] so I tried the following formula : A[:][0][0],A[0][:][0],A[0][0][:] but they all give me the same result, which is not the one I’m expecting…

A[:][0][0]
Out[7]: array([0.89565135, 0.79502322, 0.89015957])

A[0][:][0]
Out[8]: array([0.89565135, 0.79502322, 0.89015957])

A[0][0][:]
Out[9]: array([0.89565135, 0.79502322, 0.89015957])

What formula can I use to get the right array and how come the above formula give the same result ?

>Solution :

You can do as follows to select for all channel, the first element of the matrix:

A[:, 0, 0]

: references all channels, 0 the first row and 0 the first column.

Output:

array([0.89565135,0.70610822,0.71822397])

EDIT:

If your are working with nested list, you can do as follows:

[array[0][0]for array in A]

This shows one of the benefit of numpy array over python list as the selection is much more easier (and faster) using numpy.