python裏的列表切片【None，1】【1，None】

衆所周知，python裏沒有數組，有的是類似於c語言的列表
列表切片最簡單的理解就是，取數組中的某一段數據
接下來我們來看一下維數的理解，然後結合代碼深入瞭解一下

首先來看一下簡單的列表切片

import  numpy as np
a=np.array([[11,12,13,14,15,16,17,18,19],
            [21,22,23,24,25,26,27,28,29],
            [31,32,33,34,35,36,37,38,39],
            [41,42,43,44,45,46,47,48,49],
            [51,52,53,54,55,56,57,58,59],
            [61,62,63,64,65,66,67,68,69],
            [71,72,73,74,75,76,77,78,79],
            [81,82,83,84,85,86,87,88,89],
            [91,92,93,94,95,96,97,98,99],
            ])
#print(a[0:4:2,0:4:2])

結果如下

[[11 13]
 [31 33]]
[[11 13 15 17 19]
 [31 33 35 37 39]
 [51 53 55 57 59]
 [71 73 75 77 79]
 [91 93 95 97 99]]

numpy.newaxis效果和None是一樣的，None是它的別名
【None】就是增加了一個維數
nexaxis的講解在我這篇博客中
nexaxis

import  numpy as np
a=np.array([[11,12,13,14,15,16,17,18,19],
            [21,22,23,24,25,26,27,28,29],
            [31,32,33,34,35,36,37,38,39],
            [41,42,43,44,45,46,47,48,49],
            [51,52,53,54,55,56,57,58,59],
            [61,62,63,64,65,66,67,68,69],
            [71,72,73,74,75,76,77,78,79],
            [81,82,83,84,85,86,87,88,89],
            [91,92,93,94,95,96,97,98,99],
            ])
#print(a[0:4:2,0:4:2])
print(a[0:9:2,0:9:2])

print('0維爲None:')
print(a[None,0:4])
print('1維爲None:')
print(a[0:9,None])

結果如下

[[11 13 15 17 19]
 [31 33 35 37 39]
 [51 53 55 57 59]
 [71 73 75 77 79]
 [91 93 95 97 99]]
0維爲None:
[[[11 12 13 14 15 16 17 18 19]
  [21 22 23 24 25 26 27 28 29]
  [31 32 33 34 35 36 37 38 39]
  [41 42 43 44 45 46 47 48 49]]]
1維爲None:
[[[11 12 13 14 15 16 17 18 19]]

 [[21 22 23 24 25 26 27 28 29]]

 [[31 32 33 34 35 36 37 38 39]]

 [[41 42 43 44 45 46 47 48 49]]

 [[51 52 53 54 55 56 57 58 59]]

 [[61 62 63 64 65 66 67 68 69]]

 [[71 72 73 74 75 76 77 78 79]]

 [[81 82 83 84 85 86 87 88 89]]

 [[91 92 93 94 95 96 97 98 99]]]