Set numpy array values past a certain index to 0 using another array

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I have two arrays, one of floats and one of integers
[0.3, 1.8, 4.2]])

[0.3, 1.8, 4.2]])

I need to amend arr1 such that
arr1 [0, arr2[0]:] = 0
arr1 [1, arr2[1]:] = 0

arr1 [0, arr2[0]:] = 0
arr1 [1, arr2[1]:] = 0

obtaining
array([[1.5 , 0.75, 0. ],
[0.3 , 0. , 0. ]])

array([[1.5 , 0.75, 0. ],
[0.3 , 0. , 0. ]])

i.e. the nth element of arr2 dictates the number of non-zero elements in row n of arr1.
arr2
arr1
How can I vectorise this for large arrays, and extend this to further dimensions? Say

how can I change arr1 (or create a new arr3 depending on implementation) such that every slice
arr1
arr3
arr1[:, :, i], arr2[:, i]
arr1[:, :, i], arr2[:, i]
follows the above?
The final implementation will be on the order of 100,000 x 100 x 10,000.

Tags: python,arrays,numpySource of the question:

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