使用np.all()和axis=1查找全零的行（all_zero_rows），使用axis=0查找全零的列（all_zero_columns）。
如果any(all_zero_rows)和any(all_zero_columns)都是true，这意味着有一个交集，然后我们可以使用np.where()来找到全零的行和列索引。

import numpy as np

uvv= np.array([[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
               [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
               [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0],
               [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
               [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

all_zero_rows = np.all(uvv == 0, axis=1)
all_zero_columns = np.all(uvv == 0, axis=0)

# Check if there is any intersection
if any(all_zero_rows) and any(all_zero_columns):
    zero_row_indices = np.where(all_zero_rows)[0]
    zero_column_indices = np.where(all_zero_columns)[0]

    # Change the intersection elements to 1
    uvv[zero_row_indices[:, np.newaxis], zero_column_indices] = 1

print(uvv)

要查找并填充所有可能的零行和零列之间的交叉点，请使用np.meshgrid来获得坐标矩阵沿着使用np.stack + np.reshape来获得表示所有交点的对数组。
具有3个归零行和3个归零列的扩展样本：

uvv = np.array([[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
                [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
                [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0],
                [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
                [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
                [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

m1 = ~uvv.any(1)  # zeroed rows flag
m2 = ~uvv.any(0)  # zeroed columns flag
if m1.any() and m2.any():
    ind = np.dstack(np.meshgrid(np.nonzero(m1)[0], np.nonzero(m2)[0])).reshape(-1, 2)
    uvv[ind[:, 0], ind[:, 1]] = 1
    print(uvv)

[[0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0]
 [0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]
 [0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]
 [0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0]
 [0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0]
 [0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]
 [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]]