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I would like to turn an array into an array of arrays following another array of arrays. I'm not sure how to do this, here are the arrays:

orig_array = [[0,1],[4],[3],[],[3,2,6],[]]
my_array = [2,0,1,3,3,4,5]

wanted_array = [[2,0],[1],[3],[],[3,4,5],[]]

I would like to keep the empty arrays.

Thanks

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  • What's the significance of the numpy tag? It looks like you have lists; list of list, but still lists. Even if orig_array is a numpy array, it is object type, and basically a list. Commented Jun 20, 2016 at 2:13
  • @user2520932 if one of the below answers helped you, please consider marking it as accepted. This will give reputation to the answerer (making answering worth their while), and at the same time indicate that your question is already answered. While we're at it: you should also consider upvoting questions and answers that you find useful. Commented Aug 13, 2016 at 21:25

4 Answers 4

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3

Get the lengths of each element in orig_array, perform cumumlative summations along the length values to give us the indices at which my_array needs to be split and finally use np.split to actually perform the splitting. Thus, the implementation would look something like this -

lens = [len(item) for item in orig_array]
out = np.split(my_array,np.cumsum(lens))[:-1]

Sample run -

In [72]: orig_array = np.array([[0,1],[4],[3],[],[3,2,6],[]])
    ...: my_array = np.array([2,0,1,3,3,4,5])
    ...: 

In [73]: lens = [len(item) for item in orig_array]
    ...: out = np.split(my_array,np.cumsum(lens))[:-1]
    ...: 

In [74]: out
Out[74]: 
[array([2, 0]),
 array([1]),
 array([3]),
 array([], dtype=int64),
 array([3, 4, 5]),
 array([], dtype=int64)]
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4 Comments

@MartinHallén my_array is just used for extracting elements from. So, should not be dependent if its sorted or not.
Sorry, edited question to better reflect actual my_array
You are right. Requires numpy, but nice solution. Have my upvote :)
@user2520932 Edited sample run to showcase usage with it.
2 
def do(format, values):
    if type(format) == list:
        return [do(v, values) for v in format]
    else:
        return values.pop(0)

print do(orig_array, my_array)

Note: this destroys the array where the values come from.

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1

You could do the following:

import copy

def reflect_array(orig_array, order):
    wanted_array = copy.deepcopy(orig_array)
    for i, part_list in enumerate(orig_array):
        for j, _ in enumerate(part_list):
            wanted_array[i][j] = order.pop()
    return wanted_array

Test run:

orig_array = [[0,1],[4],[3],[],[3,2,6],[]]
my_array = [2,0,1,3,3,4,5]

print reflect_array(orig_array, my_array)
# [[2, 0], [1], [3], [], [3, 4, 5], []]
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1 
In [858]: my_array = [2,0,1,3,3,4,5]

In [859]: [[my_array.pop(0) for _ in range(len(x))] for x in orig_array]
Out[859]: [[2, 0], [1], [3], [], [3, 4, 5], []]

Use b=my_array[:] if you don't want to change my_array.

This operates on the same principle as @karoly's answer; just more direct because it assumes only one level of nesting.

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