我在 numpy 中遇到了以下奇怪的事情，这可能是也可能不是错误:
import numpy as np
dt = np.dtype([('tuple', (int, 2))])
a = np.zeros(3, dt)
type(a['tuple'][0]) # ndarray
type(a[0]['tuple']) # ndarray
a['tuple'][0] = (1,2) # ok
a[0]['tuple'] = (1,2) # ValueError: shape-mismatch on array construction
我原以为下面的两个选项都有效。 意见？
最佳答案
我在 numpy 讨论列表上问过这个问题。 Travis Oliphant 回答了 here .
引用他的回答:
The short answer is that this is not really a "normal" bug, but it could be considered a "design" bug (although the issues may not be straightforward to resolve). What that means is that it may not be changed in the short term --- and you should just use the first spelling.
Structured arrays can be a confusing area of NumPy for several of reasons. You've constructed an example that touches on several of them. You have a data-type that is a "structure" array with one member ("tuple"). That member contains a 2-vector of integers.
First of all, it is important to remember that with Python, doing
a['tuple'][0] = (1,2)
is equivalent to
b = a['tuple']; b[0] = (1,2)
In like manner,
a[0]['tuple'] = (1,2)
is equivalent to
b = a[0]; b['tuple'] = (1,2)
To understand the behavior, we need to dissect both code paths and what happens. You built a (3,) array of those elements in 'a'. When you write b = a['tuple'] you should probably be getting a (3,) array of (2,)-integers, but as there is currently no formal dtype support for (n,)-integers as a general dtype in NumPy, you get back a (3,2) array of integers which is the closest thing that NumPy can give you. Setting the [0] row of this object via
a['tuple'][0] = (1,2)
works just fine and does what you would expect.
On the other hand, when you type:
b = a[0]
you are getting back an array-scalar which is a particularly interesting kind of array scalar that can hold records. This new object is formally of type numpy.void and it holds a "scalar representation" of anything that fits under the "VOID" basic dtype.
For some reason:
b['tuple'] = [1,2]
is not working. On my system I'm getting a different error: TypeError: object of type 'int' has no len()
I think this should be filed as a bug on the issue tracker which is for the time being here: http://projects.scipy.org/numpy
The problem is ultimately the void->copyswap function being called in voidtype_setfields if someone wants to investigate. I think this behavior should work.
对此的解释在 a numpy bug report 中给出。 .
关于python - 命名数据类型数组 : Difference between a[0] ['name' ] and a ['name' ][0]?，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/9470604/
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