[英]Wrong examples in numpy indexing documentation?
On the numpy indexing page , there is a warning paragraph 在numpy索引页面上 ,有一个警告段落
The definition of advanced indexing means that x[(1,2,3),] is fundamentally different than x[(1,2,3)].
高级索引的定义意味着x [(1,2,3),]与x [(1,2,3)]根本不同。 The latter is equivalent to x[1,2,3] which will trigger basic selection while the former will trigger advanced indexing.
后者等效于x [1,2,3],它将触发基本选择,而前者将触发高级索引。 Be sure to understand why this occurs.
确保了解为什么会发生这种情况。
I tried to run the following code 我试图运行以下代码
import numpy as np
x = np.arange(3*4).reshape((3, 4))
y = x[(1, 2)]
z = x[(1, 2),]
print("base:", x.base, y.base, z.base)
print("id:", id(x.base), id(y.base), id(z.base))
print(np.shares_memory(x, y), np.shares_memory(x, z))
and got the results as 并得到了结果
base: [ 0 1 2 3 4 5 6 7 8 9 10 11] None None
id: 4299634928 4297628200 4297628200
False False
It seems that y
doesn't return a view and thus x[(1, 2)]
can't be a basic indexing because 似乎
y
不会返回视图 ,因此x[(1, 2)]
不能作为基本索引,因为
All arrays generated by basic slicing are always views of the original array.
通过基本切片生成的所有阵列始终都是原始阵列的视图。
Is it a mistake in the documentation? 文档中有错误吗? Or did I misunderstand somewhere?
还是我误解了某个地方?
y
isn't a view because it's a scalar, not an array. y
不是视图,因为它是标量,而不是数组。 All arrays generated by basic slicing are always views of the original array. 通过基本切片生成的所有阵列始终都是原始阵列的视图。
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