来自 Getting indices of both zero and nonzero elements in array ，我可以像这样在 numpy 的一维数组中获取非零元素的索引:

indices_nonzero = numpy.arange(len(array))[~bindices_zero]

有没有办法把它扩展成二维数组？

请您参考如下方法:

你可以使用numpy.nonzero

下面的代码是不言自明的

import numpy as np 
 
A = np.array([[1, 0, 1], 
              [0, 5, 1], 
              [3, 0, 0]]) 
nonzero = np.nonzero(A) 
# Returns a tuple of (nonzero_row_index, nonzero_col_index) 
# That is (array([0, 0, 1, 1, 2]), array([0, 2, 1, 2, 0])) 
 
nonzero_row = nonzero[0] 
nonzero_col = nonzero[1] 
 
for row, col in zip(nonzero_row, nonzero_col): 
    print("A[{}, {}] = {}".format(row, col, A[row, col])) 
""" 
A[0, 0] = 1 
A[0, 2] = 1 
A[1, 1] = 5 
A[1, 2] = 1 
A[2, 0] = 3 
""" 

你甚至可以这样做

A[nonzero] = -100 
print(A) 
""" 
[[-100    0 -100] 
 [   0 -100 -100] 
 [-100    0    0]] 
 """ 

其他变化

np.where(数组)

它等价于np.nonzero(array) 但是，np.nonzero 是首选，因为它的名字很清楚

np.argwhere(数组)

它等价于np.transpose(np.nonzero(array))

print(np.argwhere(A)) 
""" 
[[0 0] 
 [0 2] 
 [1 1] 
 [1 2] 
 [2 0]] 
 """