[FIXED] Deep copy of a np.array of np.array

Issue

I have a numpy array of different numpy arrays and I want to make a deep copy of the arrays. I found out the following:

import numpy as np

pairs = [(2, 3), (3, 4), (4, 5)]
array_of_arrays = np.array([np.arange(a*b).reshape(a,b) for (a, b) in pairs])

a = array_of_arrays[:] # Does not work
b = array_of_arrays[:][:] # Does not work
c = np.array(array_of_arrays, copy=True) # Does not work
d = np.array([np.array(x, copy=True) for x in array_of_arrays])

array_of_arrays[0][0,0] = 100
print a[0][0,0], b[0][0,0], c[0][0,0], d[0][0,0]

Is d the best way to do this? Is there a deep copy function I missed? And what is the best way to interact with each element in this array of different sized arrays?

Solution

import numpy as np
import copy

pairs = [(2, 3), (3, 4), (4, 5)]
array_of_arrays = np.array([np.arange(a*b).reshape(a,b) for (a, b) in pairs])

a = copy.deepcopy(array_of_arrays)

Feel free to read up more about this here.

Oh, here is simplest test case:

a[0][0,0]
print a[0][0,0], array_of_arrays[0][0,0]

Answered By - Tomasz Plaskota