I’m trying to initialize an “empty” array with each elements containing t_list a 8×8 np.zeros array :
t_list = np.zeros((8,8), dtype=np.float32)
I would now want to have a np.array with multiple t_list at each indexes:
result = np.array((t_list, t_list, ...., tlist))
I would like to be able to control the number of time t_list is in result.
I know that I could use list instead of arrays. The problem is, I put this in a numba njit function so I need to precise everything.
The aim is then to change each values in a double for loop.
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Answer
The shape param of numpy.zeros can be a tuple of ints of any length, so you can create an ndarray with multiple dimensions.
e.g.:
n = 5 # or any other number that you want result = np.zeros((n,8,8), dtype=np.float32)