numpy结构化数组添加记录 [英] numpy Structured array adding record

问题描述

我有一个像这样的结构化数组:

I have an Structured array like this:

a = np.array([(0. , 1. , 2.) , (10. , 11. , 12. )] ,
             dtype=[('PositionX', '<f8'), ('PositionY', '<f8'), ('PositionZ', '<f8')])

现在，我想添加记录0(a [0])和记录1(a [1])，以获得类似以下内容: (10.，12，14.)

Now, I want add record 0 (a[0]) and record 1 (a[1]), to get something like : (10. , 12. , 14. )

当我写类似的东西时:

a[0] + a[1]

我收到一个错误消息，告诉我您不能添加两个dtype对象或类似的东西.

I got error which tell me you cant add two dtype object or something like that.

因此，我想也许我可以将[0]设为常规向量，然后执行加法运算.

So, I think maybe I can turn a[0] to be a regular vector, then perform adding.

但是numpy.array(a [0])具有与a [0]相同的dtype，并且numpy.array(a[0],dtype=np.float64)也不起作用.

But numpy.array(a[0]) have same dtype as a[0], and numpy.array(a[0],dtype=np.float64) does not work too.

那么，谁能告诉我如何将a [0]转换为常规向量?请不要告诉我将结构化数组转换为常规数组.因为我只想提取阵列记录中的一部分并添加. 此外，我真的很想知道如何将像a [0]这样的对象转换为常规向量.

So, can anyone tell me how to convert a[0] to regular vector? please don't tell me to covert structured array to regular array. because I just want take few of my array record and do adding. Besides, I really want to know how to turn an object like a[0] to an regular vector.

推荐答案

仅仅因为a [i]是元组，您会收到一个错误，您不能直接添加元组.您必须访问它们，实现这一目标的更Python方式是:

You're getting an error just because the a[i] are tuples, you can't add directly tuple. You have to access them, a more pythonic way to achieve this would be:

map(sum, zip(*a))

zip函数可以完全满足您的需求，之后您必须根据需要处理每个条目，在您使用sum的情况下，您还可以尝试以下操作:

the zip function do exactly what you're looking for, after that you have to process each entry according to what you need, in your case sum , you can also try this:

result = []
for elem in zip(*a):
    result.append(sum(elem))

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