numpy数组切片两次 [英] numpy array sliced twice

问题描述

我不确定我为什么不能这样做:

I'm not sure I understand why this doesn't work :

a = np.zeros((10, ))

# first slicing array
pos1 = np.zeros((10, ), dtype=np.bool)
pos1[::2] = True

a[pos1] = 1.
print a
# returns [ 1.  0.  1.  0.  1.  0.  1.  0.  1.  0.]


# second slicing array
pos2 = np.zeros((5, ), dtype=np.bool)
pos2[::2] = True

a[pos1][pos2] = 2.

print a
# still returns [ 1.  0.  1.  0.  1.  0.  1.  0.  1.  0.]

第二个切片为什么不影响整个阵列? 我以为a[pos1]只是原始数组子部分的视图" ...我缺少什么吗?

why does the second slicing didn't affect the full array? I thought a[pos1] was just a "view" of the subpart of the original array... Am I missing something?

(此示例只是一个没有实际用途的简单示例，它只是试图理解原因，因为我使用这种语法的次数很多，但我没想到会得到此结果)

(this example is just a simple example with no real use, it is just to try to understand cause I'm using this kind of syntax a lot and I didn't expect this result)

推荐答案

与最近的您使用的是布尔型掩码，因此a[pos1]是副本，而不是切片.

You are using a boolean mask, so a[pos1] is a copy, not a slice.

第一组有效是因为它直接调用__setitem__:

The first set works because it is a direct call to __setitem__:

a[pos1] = 1.
a.__setitem__(pos1) = 1

第二个不是因为set适用于副本a[pos1]:

The second does not because the set applies to a[pos1], a copy:

a[pos1][pos2] = 2.
a.__getitem__(pos1).__setitem__(pos2)

a[::2][pos2]=3之所以起作用，是因为a[::2]是切片-即使它产生的值与a[pos1]相同.

a[::2][pos2]=3 does work because a[::2] is a slice - even though it produces the same values as a[pos1].

检查某物是副本还是视图的一种方法是查看数组的数据指针

One way to check whether something is a copy or view is to look at the array's data pointer

 a.__array_interface__['data']
 a[pos1].__array_interface__['data'] # will be different
 a[::2].__array_interface__['data']  # should be the same

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