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1

I have two numpy arrays:

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:

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:

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

How do I combine the two numpy arrays element wise?

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

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

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Here's a link to the code that I used to test this. – KronoS yesterday

4 Answers

up vote 2 down vote accepted

Use 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])
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up vote 0 down vote

You can also use slices :

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

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

Here is one way to do it

C = []
for elem in zip(A, B):
    C.extend(elem)
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up vote 2 down vote

You can try this:

C = sorted(A.tolist() + B.tolist())
  1. A.tolist() will yield [1, 3, 5, 7]
  2. B.tolist() will yield [2, 4, 6, 8]
  3. A.tolist() + B.tolist() - [1, 3, 5, 7, 2, 4, 6, 8]
  4. sorted(...) - [1, 2, 3, 4, 5, 6, 7, 8]

Without sorting:

C = [y for x in zip(A, B) for y in x]
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I don't want the elements to be sorted, as these are actually data samples that aren't in order of value. Your second option was used in my testing. – KronoS yesterday

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