[Python] unexpected change in variable after python function call

Consider the following small python snippet where I add '2' to the first column of a 3 x 3 matrix:

import numpy as np

def changeValue(kernel):
kernel[0,0]=kernel[0,0]+ 2
kernel[1,0]=kernel[1,0]+ 2
kernel[2,0]=kernel[2,0]+ 2
return kernel

myKernel = np.array((
[0, -1, 0],
[-1, 5, -1],
[0, -1, 0]), dtype="int")
CVkernel=myKernel

print(CVkernel)
a=changeValue(myKernel)
print(a)
print(CVkernel)


I get the following output

[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]

[[ 2 -1 0]
[ 1 5 -1]
[ 2 -1 0]]

[[ 2 -1 0]
[ 1 5 -1]
[ 2 -1 0]]


The value of myKernel clobbers CVkernel. I think there is an unintentional call-by-reference (pass-by-reference?) going on but I am not sure why.

If I define the function slightly differently

def changeValue2(kernel):
kernel=kernel + 2
return kernel


Then CVkernel is left untouched

[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]

[[2 1 2]
[1 7 1]
[2 1 2]]

[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]


What is going on here? I tried printing out the address register of the variables with print(id(kernel)) and print(id(CVkernel)) and that does not shed any light.

EDIT Even when I use a 'safe' function call, kernel=kernel + 2 , the id of myKernel and CVkernel are the same.

id of myKernel 139994865303344
myKernel
[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]
id of CVKernel 139994865303344
CVKernel
[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]

**call made to changeValue2**

id of myKernel 139994865303344
myKernel
[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]
id of CVKernel 139994865303344
CVKernel
[[ 0 -1 0]
[-1 5 -1]
[ 0 -1 0]]
output a
[[2 1 2]
[1 7 1]
[2 1 2]]


Shouldn't the id of each variable be different if they are different instances?

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