Modify parts of numpy array in for loop

Question

I want to loop through the first dimension of an array, do a computation on each sub-array, and assign the result back to the array. It doesn't work when I use the "pythonic" form for b in bob: -- but I know that it ought to, because if I modify b in place it actually changes the matrix.

Is there a way to carry out the assignment in the middle "for" loop, below?

import numpy as np

bob = np.arange(0, 60).reshape((3, 4, 5))

print(bob)

# This does not change elements in bob
for b in bob:
    b = b + 3
    
print(bob)

# This does change elements in bob
for b in bob:
    b += 3
    
print(bob)

b = b + 3 assigns a new object to the variable b. It does not modify the the original b. This is a basic Python iterative behavior. b[:] = b+3 should work like the b+=. — hpaulj
– hpaulj, Commented Apr 20, 2021 at 18:33

hpaulj · Accepted Answer · 2021-04-20 19:19:03Z

1

b = b + 3 assigns a new object to the variable b. It does not modify the the original b. This is a basic Python iterative behavior. b[:] = b+3 should work like the b+=

answered Apr 20, 2021 at 19:19

hpaulj

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