使用List进行NumPy索引编制? [英] NumPy indexing using List?
问题描述
SOF,
我在此URL中注意到了一个有趣的NumPy演示:
I noticed an interesting NumPy demo in this URL:
http://cs231n.github.io/python-numpy-tutorial/
我看到了:
import numpy as np
a = np.array([[1,2], [3, 4], [5, 6]])
# An example of integer array indexing.
# The returned array will have shape (3,) and
print( a[[0, 1, 2], [0, 1, 0]] )
# Prints "[1 4 5]"
我了解使用整数作为索引参数:
I understand using integers as index arguments:
a[1,1]
和此语法:
a[0:2,:]
通常, 如果我使用列表作为索引语法,那是什么意思?
Generally, If I use a list as index syntax, what does that mean?
具体来说, 我不明白为什么:
Specifically, I do not understand why:
print( a[[0, 1, 2], [0, 1, 0]] )
# Prints "[1 4 5]"
推荐答案
最后一条语句将以矩阵表示法打印a(0,0)
,a(1,1)
和a(2,0)
.在a[0][0]
,a[1][1]
和a[2][0]
的python表示法中.
The last statement will print (in matrix notation) a(0,0)
, a(1,1)
and a(2,0)
. In python notation that's a[0][0]
, a[1][1]
and a[2][0]
.
第一个索引列表包含第一个轴的索引(矩阵符号:行索引),第二个列表包含第二个轴的索引(列索引).
The first index list contains the indices for the first axis (matrix notation: row index), the second list contains the indices for the second axis (column index).
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