python - How to properly stack numpy arrays?

Question

I am having trouble understanding how data is being stacked in a numpy array and why I cannot match the last data that I added to an array with the last generated data. Here is a MWE:

import numpy as np
np.random.seed(1)

# build storage
container = []

# gen data
x = np.random.random((13, 1, 64, 768))

# add to container
container.append(x)

# gen data
x2 = np.random.random((13, 1, 64, 768))

# add to container
container.append(x2)

# convert to np array
container = np.asarray(container)

# reshape to [13, 2, 64, 768]
container = container.reshape(13, 2, 64, 768)

# check that the last generated data matches the last appended data
assert np.all(x2.flatten() == container[:, -1, :, :].flatten()), 'not a match'

question from:https://stackoverflow.com/questions/65644397/how-to-properly-stack-numpy-arrays

Answer 1

Instead of stacking manually with appending to lists and then reshaping you could use the vstack or the concatenate function of numpy.

# gen data
x1 = np.random.random((13, 1, 64, 768))
x2 = np.random.random((13, 1, 64, 768))

container = np.vstack((x1,x2))
assert np.all(x2.flatten()) == np.all(container[:, -1, :, :].flatten()), 'not a match'

To answer your question: your code does work, just make sure to put np.all() at both sides of the comparison. It's always a good idea to make your input much smaller (say (2,1,2,2)) so you can see what actually happens.