[numpy]numpy切片与索引

简单的总结一下numpy中的切片和索引。

先说索引。
1.一维数组的索引。

c = np.random.randint(10,size=8)
>>array([7, 5, 5, 4, 2, 1, 2, 2])
c[1]
>>5
c[-2]
2
c[0]
>>7
c[0] = 3.14159  #赋值给不同类型的元素。会导致
array([3, 5, 5, 4, 2, 1, 2, 2])  

2.二维数组的索引,要使用逗号将中间分隔开。前边是索引行。后边是索引列。

d = np.random.randint(14, size=(3, 4))
>>array([[ 8, 11, 10, 11],
         [ 4, 13, 13, 14],
         [ 0,  7, 11,  1]])
d[0,0]  
>>8
d[1,2]
>>13
d2[2, -1]
>>14
d2[0, 0] = 12
d
>>array([[12, 11, 10, 11],
   [ 4, 13, 13, 13],
   [ 0,  7, 11,  1]])

3.一维数组的切片。

e = np.arange(10)
>>array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
e[:5]
>>array([0,1,2,3,4])
e[5:]
>>array([5,6,7,8,9])
e[5:7]
>>array([5,6])
e[::2]
>>array([0,2,4,6,8])
e[1::2]
>>array([1,3,5,7,9])
e[::-1]
>>array([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])
e[5::-2]
>>array([5,3,1])

4.多维数组的切片。

f = np.random.randint(10, size=(3, 4))
f    
>>array([[2, 9, 5, 1],
        [9, 8, 3, 9],
        [6, 3, 4, 3]])
f[:2, :3]
>>array([[12,  5,  2],
        [ 7,  6,  8]])
f[:3, ::2] 
>>array([[12,  2],
         [ 7,  8],
         [ 1,  7]])
f[::-1, ::-1]
>>array([[ 7,  7,  6,  1],
         [ 8,  8,  6,  7],
         [ 4,  2,  5, 12]])

5.数组的链接。

x = np.array([1, 2, 3])
y = np.array([3, 2, 1])
np.concatenate([x, y])
>>array([1, 2, 3, 3, 2, 1])
#也可以链接不止两个。
z = [99, 99, 99]
np.concatenate([x, y, z])
>>array([ 1  2  3  3  2  1 99 99 99])
grid = np.array([[1, 2, 3],
                 [4, 5, 6]])
np.concatenate([grid,grid])
>>array([[1, 2, 3],
     [4, 5, 6],
     [1, 2, 3],
     [4, 5, 6]])
np.concatenate([grid,grid],axis=1)
>>array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]])

6.数组的拆分。

x = [1, 2, 3, 99, 99, 3, 2, 1]
x1, x2, x3 = np.split(x, [3, 5])
print(x1, x2, x3)
>>[1 2 3] [99 99] [3 2 1]

>>grid = np.arange(16).reshape((4, 4))
grid
>>array([[ 0,  1,  2,  3],
   [ 4,  5,  6,  7],
   [ 8,  9, 10, 11],
   [12, 13, 14, 15]])

upper, lower = np.vsplit(grid, [2])
print(upper)
print(lower)
>>[[0 1 2 3]
  [4 5 6 7]]
  [[ 8  9 10 11]
  [12 13 14 15]]

left, right = np.hsplit(grid, [2])
print(left)
print(right)
>>[[ 0  1]
[ 4  5]
[ 8  9]
[12 13]]
[[ 2  3]
[ 6  7]
[10 11]
[14 15]]