1. Use the list as an index
1 a = np.around(10*np.random.random((3, 3))) 2 b = [0, 1, 2] 3 c = [0, 1, 2] 4 print(a) 5 print(a[b, c])
Results are as follows, using [0, 1, 2] as a row index, [0,1, 2] as a column, the output of a [0, 0], a [1, 1], a [2, 3].
2. Copy
(. 1) a = b b is copied to the id of b, and a and b are the same object
1 import numpy as np 2 3 a = np.arange(5) 4 print(a) 5 b = a 6 print(id(a)) 7 print(id(b))
The results can be seen by running the diagram, a is equal to b of id id, with a pointed object.
(2) b = a.view () is a shallow copy, b and a are different objects, but their elements are shared.
1 import numpy as np 2 3 a = np.arange(5) 4 print(a) 5 b = a.view() 6 print(id(a)) 7 print(id(b)) 8 b[0] = -1 9 print(a)
The results can be seen by running the following figure, a and b are different objects, but when I change a time element, b element also changed. '
(3) b = a.copy () is a deep copy, b of the element is a copy of the