How to change an new array without changing the initial array that the new array was created?

Question

img_1 = np.arange(25).reshape(5,5)

img_2 = img_1

locs = np.where(img_2 >= 0)

img_2[locs]  = [65000]

Wondering is there an way to have img_1 with initial array and only img_2 will will be modified?

Both img_1 and img_2 array is changing.

You can use img2 = img1.copy(). img2 = img1 makes img2 point to the same data as img1. — B Remmelzwaal
– B Remmelzwaal, Commented Feb 7, 2023 at 2:09
This isn't unique to numpy arrays. img2 = img1 will make img2 reference the exact same object as img1, regardless of what img1 is. For more on this, see what does it mean by 'passed by assignment'? — Brian61354270
– Brian61354270, Commented Feb 7, 2023 at 2:14
for a numpy array or a pandas dataframe.. img2=img1.copy() will give you a copy .. for other objects which donot have a copy() method inplemented ... import copy and obj2=copy.deepcopy(obj1) will give you true copy and not a reference — geekay
– geekay, Commented Feb 7, 2023 at 2:34
In addition, there's also a shorter way to do the operation you did the code. img_2[img_2>=0] produces the same result. The argument produces a Boolean for each element of img_2, i.e., accordingly the array img_2 takes the values. — Pixel_Bear
– Pixel_Bear, Commented Feb 7, 2023 at 4:14

relent95 · Accepted Answer · 2023-02-07 05:39:11Z

1

All you need is just the np.where() alone. Do like this.

import numpy as np

img_1 = np.arange(25).reshape(5,5)
img_2 = np.where(img_1 >= 0, 65000, img_1)

answered Feb 7, 2023 at 5:39

relent95

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