问题
We have a main array called main_arr, and we want to transform it into another array called result with the same size, using a guide_arr, again with the same size:
import numpy as np
main_arr = np.array([[3, 7, 4], [2, 5, 6]])
guide_arr = np.array([[2, 0, 1], [0, 2, 1]])
result = np.zeros(main_arr.shape)
we need the result to equal to:
if np.array_equal(result, np.array([[7, 4, 3], [2, 6, 5]])):
print('success!')
How should we use guide_arr?
guide_arr[0,0] is 2, meaning that result[0,2] = main_arr[0,0]
guide_arr[0, 1] is 0 meaning that result[0, 0] = main_arr[0, 1]
guide_arr[0, 2] is 1 meaning that result[0, 1] = main_arr[0,2]
The same goes for row 1.
In summary, items in main_arr should be reordered (within a row, row never changes) so that their new column index equals the number in guide_arr.
回答1:
In [199]: main_arr = np.array([[3, 7, 4], [2, 5, 6]])
...: guide_arr = np.array([[2, 0, 1], [0, 2, 1]])
...:
The usual way of reordering columns, where the order differs by row, is with indexing like this:
In [200]: main_arr[np.arange(2)[:,None],guide_arr]
Out[200]:
array([[4, 3, 7],
[2, 6, 5]])
The arange(2)[:,None] is a column array that broadcasts with the (2,3) index array.
We can apply the same idea to using guide_arr to identify columns in the result:
In [201]: result = np.zeros_like(main_arr)
In [202]: result[np.arange(2)[:,None], guide_arr] = main_arr
In [203]: result
Out[203]:
array([[7, 4, 3],
[2, 6, 5]])
This may clarify how the broadcasting works:
In [204]: np.broadcast_arrays(np.arange(2)[:,None], guide_arr)
Out[204]:
[array([[0, 0, 0],
[1, 1, 1]]),
array([[2, 0, 1],
[0, 2, 1]])]
来源：https://stackoverflow.com/questions/50112085/reoder-the-columns-of-each-row-of-a-numpy-array-based-on-another-numpy-array