问题描述
import numpy as np
A = np.array(
[ [ [45,12,4],[45,13,5],[46,6] ],[ [46,14,11,5] ],[ [47,2],[48,15,[52,1] ] ])
print(A[1:3,0:2])
请对此进行解释。我一直在努力了解
解决方法
以这种方式访问3D数组时，您的要求是切出这些数组的每个嵌套级别的一部分：
A[1:3,0:2,0:3]
# ↑↑↑
# Of the outer array (the outer []),take elements 1 (inclusive) to 3 (exclusive).
# Mind that counting starts at 0,so this is the second and third line in your example
A[1:3,0:3]
# ↑↑↑
# Out of the second level array,take the elements 0 (inclusive) to 2 (exclusive).
# This is the first and the second group of three numbers each
A[1:3,0:3]
# ↑↑↑
# This you did not specify,but it is added automatically
# Of the third level arrays,take element 0 (inclusive) to 3 (exclusive)
# Those arrays only have 3 numbers each,so they are left untouched.
In [483]: A = np.array(
...: [ [ [45,12,4],[45,13,5],[46,6] ],...: [ [46,14,11,5] ],...: [ [47,2],[48,15,[52,1] ] ])
整个3d数组。如果需要在尺寸上加上名称，建议使用“ plane”，“ row”和“ column”：
In [484]: A
Out[484]:
array([[[45,6]],[[46,5]],[[47,1]]])
In [485]: A.shape
Out[485]: (3,3,3)
在第一个维度（最后两个平面）上进行切片：
In [486]: A[1:3]
Out[486]:
array([[[46,1]]])
从每个平面取2行：
In [487]: A[1:3,0:2]
Out[487]:
array([[[46,5]]])
最后一个维度（列）是完整的，相当于A[1:3,:]（后切片是自动的）。
3D切片与1d和2d（以及4d等）相同。 3d没有什么特别之处或真正不同之处。