Numpy 索引和切片

import numpy as np

01一维数组

一维数组的 索引和切片

a = np.arange(9)

3-7 不包括7

b = a[3:7]
print(b)

0-7步长为2

c = a[:7:2]
print(c)

下标翻转数组

d = a[::-1]
print(d)

# 输出结果
 [3 4 5 6]
 [0 2 4 6]
 [8 7 6 5 4 3 2 1 0]

02多维数组的切片和索引

reshape 改变数组的纬度,参数为正整数元组

a = np.arange(24).reshape(2,3,4)
print(a)

# 输出结果
 [[[ 0  1  2  3]
   [ 4  5  6  7]
   [ 8  9 10 11]]

  [[12 13 14 15]
   [16 17 18 19]
   [20 21 22 23]]]

多维数组的切片

b = a[0,0,0]  
print(b)

输出结果
 0  

c = a[:,0,0]
print(c)  

输出结果
 [ 0 12]

d = a[0]
print(d)

输出结果
 [[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]

e = a[0,:,:] #等价于e = a[0,...]   多个冒号等价于...
print(e)

 输出结果
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

f = a[0,1]
print(f)

输出结果
[4 5 6 7]

g = a[0,1,::2]
print(g)

输出结果
[4 6]

h = a[...,1]
print(h)

输出结果
[[ 1  5  9]
 [13 17 21]]

i = a[:,1]
print(i)

 输出结果
 [[ 4  5  6  7]
  [16 17 18 19]]

j = a[0,:,-1]
print(j)

输出结果
[ 3  7 11]

k = a[0,:,1]
print(k)

输出结果
[1 5 9]

l = a[0,::-1,-1]
print(l)

输出结果
[11  7  3]

m = a[0,::2,-1]
print(m)

输出结果
[ 3 11]

n = a[::-1]
print(n)

输出结果
 [[[12 13 14 15]
   [16 17 18 19]
   [20 21 22 23]]

  [[ 0  1  2  3]
   [ 4  5  6  7]
   [ 8  9 10 11]]]