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I have code like this:

import numpy as np

area = np.zeros([2,2])
f = area
print(area)
f[0][0]=1
print(area)
print(f)

Which produces the following arrays

[[0. 0.]
 [0. 0.]]

[[1. 0.]
 [0. 0.]]

[[1. 0.]
 [0. 0.]]

How do I get it so that the area array is not 'linked' to the f array i.e. after the calculation the f array changes but the area array does not?

You need to make a copy of area:

f = area.copy()

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They're not just "linked"; they are 2 names for the same array.

If you want them to be distinct, make a copy of area to assign to f.

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You should copy your first array:

f = area.copy()

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You can prevent this by making a copy:

1.

A=B

Assignment of list is happened , so that's why change in one place creates change another list.

2.

B[:] = A

This only works if B is already existing.

3.

B = A.copy()

Both 2 and 3 copies the list into another but they don't get linked to each other.

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Comments
  • These aren't two arrays that are "linked", it is the same array. x = y says "let the name x now refer to the object currently being referenced by the name y", it doesn't say, "copy the object being referred to by y and assign it to the name x"
  • Does this answer your question? Python numpy create copy and not reference
  • which one? A.copy()?
  • The OP is working with a numpy array, not a list, as you have written in your question
  • Yes but you are using the word list in you answer, that is what I'm saying, and the op is a out numpy arrays