New array created based off old array, ids are different, but changing new array changes old array (python)

Question

Good afternoon!

The following is my snippet of code:

density_new = density_old[:,:,40:55]

for i in range(0,16):
    density_new[:,:,i] = 1020

Now, this should only change density_new, because by the way we allocate density_new it has its own memory ID (I double-checked using python's id() command on both variables). The problem is that when I run the code, it changes both density_old and density_new, and since they have different IDs, I don't know why this is happening. Any help would be appreciated.

Bernardo Costa · Accepted Answer · 2020-04-24 10:49:57Z

1

Another solution:

import copy

density_new = copy.deepcopy(density_old[:,:,40:55])

From https://docs.python.org/2/library/copy.html :

A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.

answered Apr 24, 2020 at 10:49

Bernardo Costa

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Sido4odus · Accepted Answer · 2020-01-06 20:47:57Z

0

when you copy a list to another one, python will make them refrence the same list so when updating one the other one automatically will be updated, but using list() function to copy a list will avoid this trick.

so just try this one:

density_new = list(density_old[:,:,40:55])

answered Jan 6, 2020 at 20:47

Sido4odus

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3 Comments

mathishard.butweloveit Over a year ago

I did try this trick, but the issue is that now density_new is not an array, it's a list, and assigning values as in the for loop does not work. Since I use it as an array farther down for a variety of things, I need it to keep its structure. Is there a way to do that with list?

Sido4odus Over a year ago

I'm not sure but you may use numpy arrays

mathishard.butweloveit Over a year ago

Ah, got it, using np.asarray will convert it back to array form.

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