I am having a database of 7000 objects (list_of_objects), each one of these files contains a numpy array with size of 10x5x50x50x3
. I would like to create a 5d numpy array that will contain 7000*10x5x50x50x3
. I tried to do so using two for-loops. My sample code:
fnl_lst = []
for object in list_of_objects:
my_array = read_array(object) # size 10x5x50x50x3
for ind in my_array:
fnl_lst.append(ind)
fnl_lst= np.asarray( fnl_lst) # print(fnl_lst) -> (70000,)
That code result in the end in a nested numpy array which contains 70000 arrays each of them has a size of 5x50x50x3
. However, I would like instead to build a 5d array with size 70000x5x50x50x3
. How can I do that instead?
fnl_lst = np.stack([ind for ind in read_array(obj) for obj in list_of_objects])
or, just append to the existing code:
fnl_lst = np.stack(fnl_lst)
UPD: by hpaulj's comment, if my_array
is indeed 10x5x50x50x3, this might be enough:
fnl_lst = np.stack([read_array(obj) for obj in list_of_objects])
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