如何在python中组合两个numpy数组元素?

时间:2022-04-04 12:08:28

I have two numpy arrays:

我有两个numpy数组:

A = np.array([1, 3, 5, 7])
B = np.array([2, 4, 6, 8])

and I want to get the following from combining the two:

我想从这两者的结合中得出以下结论:

C = [1, 2, 3, 4, 5, 6, 7, 8]

I'm able to get something close by using zip, but not quite what I'm looking for:

我可以通过使用zip来接近一些东西,但不是我想要的:

>>> zip(A, B)
[(1, 2), (3, 4), (5, 6), (7, 8)]

How do I combine the two numpy arrays element wise?

如何组合两个numpy数组元素?


I did a quick test of 50,000 elements in each array (100,000 combined elements). Here are the results:

我对每个数组中的50,000个元素进行了快速测试(100,000个组合元素)。这里是结果:

User Ma3x:      Time of execution: 0.0343832323429      Valid Array?:  True
User mishik:    Time of execution: 0.0439064509613      Valid Array?:  True
User Jaime:     Time of execution: 0.02767023558        Valid Array?:  True

Tested using Python 2.7, Windows 7 Enterprise 64-bit, Intel Core i7 2720QM @2.2 Ghz Sandy Bridge, 8 GB Mem

测试使用Python 2.7, Windows 7企业64位,Intel Core i7 2720QM @2.2 Ghz Sandy Bridge, 8gb Mem

5 个解决方案

#1


9  

Use np.insert:

使用np.insert:

>>> A = np.array([1, 3, 5, 7])
>>> B = np.array([2, 4, 6, 8])
>>> np.insert(B, np.arange(len(A)), A)
array([1, 2, 3, 4, 5, 6, 7, 8])

#2


5  

You can also use slices :

你也可以使用切片:

C = np.empty((A.shape[0]*2), dtype=A.dtype)
C[0::2] = A
C[1::2] = B

#3


3  

>>> import numpy as np
>>> A=np.array([1,3,5,7])
>>> B=np.array([2,4,6,8])
>>> C=np.dstack([A,B])
>>> D=C.reshape((1,8))[0]
>>> D
array([1, 2, 3, 4, 5, 6, 7, 8])

#4


1  

Some answers suggested sorting, but since you want to combine them element-wise sorting won't achieve the same result.

一些回答建议进行排序,但是由于您希望将它们组合在一起,按元素排序不会得到相同的结果。

Here is one way to do it

这是一种方法。

C = []
for elem in zip(A, B):
    C.extend(elem)

#5


0  

You can try this:

你可以试试这个:

C = sorted(A.tolist() + B.tolist())
  1. A.tolist() will yield [1, 3, 5, 7]
  2. A.tolist()会产生[1,3,5,7]
  3. B.tolist() will yield [2, 4, 6, 8]
  4. B.tolist()将产生[2,4,6,8]
  5. A.tolist() + B.tolist() - [1, 3, 5, 7, 2, 4, 6, 8]
  6. A.tolist B.tolist()+()——(1、3、5、7、2,4,6,8]
  7. sorted(...) - [1, 2, 3, 4, 5, 6, 7, 8]
  8. 排序(…)-[1、2、3、4、5、6、7、8]

Without sorting:

没有排序:

C = [y for x in zip(A, B) for y in x]

#1


9  

Use np.insert:

使用np.insert:

>>> A = np.array([1, 3, 5, 7])
>>> B = np.array([2, 4, 6, 8])
>>> np.insert(B, np.arange(len(A)), A)
array([1, 2, 3, 4, 5, 6, 7, 8])

#2


5  

You can also use slices :

你也可以使用切片:

C = np.empty((A.shape[0]*2), dtype=A.dtype)
C[0::2] = A
C[1::2] = B

#3


3  

>>> import numpy as np
>>> A=np.array([1,3,5,7])
>>> B=np.array([2,4,6,8])
>>> C=np.dstack([A,B])
>>> D=C.reshape((1,8))[0]
>>> D
array([1, 2, 3, 4, 5, 6, 7, 8])

#4


1  

Some answers suggested sorting, but since you want to combine them element-wise sorting won't achieve the same result.

一些回答建议进行排序,但是由于您希望将它们组合在一起,按元素排序不会得到相同的结果。

Here is one way to do it

这是一种方法。

C = []
for elem in zip(A, B):
    C.extend(elem)

#5


0  

You can try this:

你可以试试这个:

C = sorted(A.tolist() + B.tolist())
  1. A.tolist() will yield [1, 3, 5, 7]
  2. A.tolist()会产生[1,3,5,7]
  3. B.tolist() will yield [2, 4, 6, 8]
  4. B.tolist()将产生[2,4,6,8]
  5. A.tolist() + B.tolist() - [1, 3, 5, 7, 2, 4, 6, 8]
  6. A.tolist B.tolist()+()——(1、3、5、7、2,4,6,8]
  7. sorted(...) - [1, 2, 3, 4, 5, 6, 7, 8]
  8. 排序(…)-[1、2、3、4、5、6、7、8]

Without sorting:

没有排序:

C = [y for x in zip(A, B) for y in x]