numpy学习之路（3）

numpy索引

import numpy as np
a=np.arange(3,15).reshape(3,4)
print(a)
print(a[1])
print(a[-2][3])#和列表基本一样
print(a[-2,3])#和上面一模一样
print(a[:,1:3])# :代表所有数
print(a.flat)#迭代器
print(a.flatten())
for item in b.flat:
    print(item)

结果

[[ 3  4  5  6]
 [ 7  8  9 10]
 [11 12 13 14]]
[ 7  8  9 10]
10
10
[[ 4  5]
 [ 8  9]
 [12 13]]
<numpy.flatiter object at 0x3b12100>
[ 3  4  5  6  7  8  9 10 11 12 13 14]
3
4
5
6
7
8
9
10
11
12
13
14

numpy的array合并

import numpy as np
a=np.array([1,1,1])
b=np.array([2,2,2])
c=np.vstack((a,b))#vertical tack上下合并
d=np.hstack((a,b))#horizontal tack左右合并
f=np.array([1,1,1])[np.newaxis]
g=np.array([2,2,2])[np.newaxis]
h=np.concatenate((f,g,f,g),axis=0)#多个合并
print(a,b)
print(c)
print(b.shape,c.shape)
print(a[np.newaxis,:])
print(a[np.newaxis,:].shape)#横向加一个维度
print(a[:,np.newaxis])
print(f)
print(h)

结果

[1 1 1] [2 2 2]
[[1 1 1]
 [2 2 2]]
(3,) (2, 3)
[[1 1 1]]
(1, 3)
[[1]
 [1]
 [1]]
[[1 1 1]]
[[1 1 1]
 [2 2 2]
 [1 1 1]
 [2 2 2]]

numpy的分割

import numpy as np
a=np.arange(12).reshape(3,4)
b=np.split(a,2,axis=1)#对行分割成两块只能进行对等分割
c=np.array_split(a,3,axis=1)#不对等分割，按照先多后少？
d=np.hsplit(a,2)#vsplit 纵向分割 hsplit 横向分割   也必须对称？
print(a)
print(b)
print(c)
print(d)

结果

[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2,  3],
       [ 6,  7],
       [10, 11]])]
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2],
       [ 6],
       [10]]), array([[ 3],
       [ 7],
       [11]])]
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2,  3],
       [ 6,  7],
       [10, 11]])]

numpy的复制

import numpy as np
a=np.arange(4)
b=a#b和a 一模一样指向同一对象
c=a.copy()#浅复制
d=np.array(a)#浅复制
a[0]=1
print(a,b,c,d)

[1 1 2 3] [1 1 2 3] [0 1 2 3] [0 1 2 3]