在python中，如何通过条件对一维数组的对应元素快速设置二维数组的每一行的值？

Question

For instance, I have the following numpy arrays:

a = numpy.array( [ [ 1 , 3 , 3 ] , [ 2 , 5 , 5 ] , [ 3 , 7 , 7 ] ] )
b = numpy.array( [ 1 , 2 , 3 ] )

I want to write a piece of code that will emulate:

a[ a == b ] = 0

which the output will be:

[ [ 0 , 3 , 3 ] , [ 0 , 5 , 5 ] , [ 0 , 7 , 7 ] ]

How to achieve this by not applying a for loop. Here it is just an example, in real reality the arrays are very large and for loop takes too much time to run.

Answer 1

you could do the following:

import numpy as np
a = np.array( [ [ 1 , 3 , 3 ] , [ 2 , 5 , 5 ] , [ 3 , 7 , 7 ] ] )
b = np.array( [ 1 , 2 , 3 ] )

def f(b, a):
    return np.where(a == b, 0, a)

print(np.array([*map(f, b, a)]))

which gives:

[[0 3 3]
 [0 5 5]
 [0 7 7]]