Slicing Numpy array using List

Question

Consider 2D Numpy array A and in-place function x like

A = np.arange(9).reshape(3,3)
def x(M):
    M[:,2] = 0

Now, I have a list (or 1D numpy array) L pointing the rows, I want to select and apply the function f on them like

L = [0, 1]
x(A[L, :])

where the output will be written to A. Since I used index access to A, the matrix A is not affected at all:

A = array([[0, 1, 2],
           [3, 4, 5],
           [6, 7, 8]])

What I actually need is to slice the matrix such as

x(A[:2, :])

giving me the desired output

A = array([[0, 1, 0],
           [3, 4, 0],
           [6, 7, 8]])

The question is now, how to provide Numpy array slicing by the list L (either any automatic conversion of list to slice or if there is any build in function for that), because I am not able to convert the list L easily to slice like :2 in this case.

Note that I have both large matrix A and list L in my problem - that is the reason, why I would need the in-place operations to control the available memory.

Answer 1

Can you modify the function so as you can pass slice L inside it:

def func(M,L): 
    M[L,2] = 0

func(A,L)

print(A)

Out:

array([[0, 1, 0],
       [3, 4, 0],
       [6, 7, 8]])