Python numpy数组替换

Question

我有一个看起来像这样的数组:

array([[ 1,  1,  2,  0,  4],
       [ 5,  6,  7,  8,  9],
       [10,  0,  0, 13, 14],
       [15, 16, 17, 18, 19],
       [20, 21, 22,  0, 24],
       [25, 26, 27, 28, 29],
       [30, 31, 32, 33, 34],
       [35, 36, 37, 38, 39],
       [40, 41, 42, 43, 44],
       [45, 46, 47, 48, 49]])

我有另外两个数组,如:

array([[   0,    0,    0,    0],
       [   0,    0,    0,    0],
       [   0, 2891,    0,    0],
       [   0,    0,    0,    0],
       [   0,    0,    0, 2891]])

和

array([[  0,   0,   0, 643],
       [  0,   0,   0,   0],
       [  0,   0, 643,   0],
       [  0,   0,   0,   0],
       [  0,   0,   0,   0]])

我想要的是从第二个数组中选择值2891到相应位置的第一个数组,并从第三个数组中选择643到相应位置的第一个数组,这样最终数组应如下所示:

array([[   1,    1,    2,  643,    4],
       [   5,    6,    7,    8,    9],
       [  10, 2891,  643,   13,   14],
       [  15,   16,   17,   18,   19],
       [  20,   21,   22, 2891,   24],
       [  25,   26,   27,   28,   29],
       [  30,   31,   32,   33,   34],
       [  35,   36,   37,   38,   39],
       [  40,   41,   42,   43,   44],
       [  45,   46,   47,   48,   49]])

到目前为止,我尝试过这个命令:

np.place(a,a<1, np.amax(b))

其中a引用第一个数组并b引用第二个数组.它做什么只是将所有0值替换为2891值.有人可以帮忙吗？

Answer 1

您可以使用非零方法找到其中y和z非零的索引:

In [9]: y.nonzero()
Out[9]: (array([2, 4]), array([1, 3]))

In [10]: z.nonzero()
Out[10]: (array([0, 2]), array([3, 2]))

您可以通过扇形索引来选择关联的值:

In [11]: y[y.nonzero()]
Out[11]: array([2891, 2891])

并且您可以将这些值分配给xwith中的位置

In [13]: x[y.nonzero()] = y[y.nonzero()]

import numpy as np
x = np.array([[ 1,  1,  2,  0,  4],
              [ 5,  6,  7,  8,  9],
              [10,  0,  0, 13, 14],
              [15, 16, 17, 18, 19],
              [20, 21, 22,  0, 24],
              [25, 26, 27, 28, 29],
              [30, 31, 32, 33, 34],
              [35, 36, 37, 38, 39],
              [40, 41, 42, 43, 44],
              [45, 46, 47, 48, 49]])

y = np.array([[   0,    0,    0,    0],
              [   0,    0,    0,    0],
              [   0, 2891,    0,    0],
              [   0,    0,    0,    0],
              [   0,    0,    0, 2891]])

z = np.array([[  0,   0,   0, 643],
              [  0,   0,   0,   0],
              [  0,   0, 643,   0],
              [  0,   0,   0,   0],
              [  0,   0,   0,   0]])

x[y.nonzero()] = y[y.nonzero()]
x[z.nonzero()] = z[z.nonzero()]
print(x)

产量

[[   1    1    2  643    4]
 [   5    6    7    8    9]
 [  10 2891  643   13   14]
 [  15   16   17   18   19]
 [  20   21   22 2891   24]
 [  25   26   27   28   29]
 [  30   31   32   33   34]
 [  35   36   37   38   39]
 [  40   41   42   43   44]
 [  45   46   47   48   49]]