Q:

Python equivalent of R "split"-function

In R, you could split a vector according to the factors of another vector:
> a <- 1:10
  [1]  1  2  3  4  5  6  7  8  9 10
> b <- rep(1:2,5)
  [1] 1 2 1 2 1 2 1 2 1 2

> split(a,b)

   $`1`
   [1] 1 3 5 7 9
   $`2`
   [1]  2  4  6  8 10

Thus, grouping a list (in terms of python) according to the values of another list (according to the order of the factors).
Is there anything handy in python like that, except from the itertools.groupby approach?

A:

From your example, it looks like each element in b contains the 1-indexed list in which the node will be stored. Python lacks the automatic numeric variables that R seems to have, so we'll return a tuple of lists. If you can do zero-indexed lists, and you only need two lists (i.e., for your R use case, 1 and 2 are the only values, in python they'll be 0 and 1)
>>> a = range(1, 11)
>>> b = [0,1] * 5

>>> split(a, b)
([1, 3, 5, 7, 9], [2, 4, 6, 8, 10])

Then you can use itertools.compress:
def split(x, f):
    return list(itertools.compress(x, f)), list(itertools.compress(x, (not i for i in f)))

If you need more general input (multiple numbers), something like the following will return an n-tuple:
def split(x, f):
    count = max(f) + 1
    return tuple( list(itertools.compress(x, (el == i for el in f))) for i in xrange(count) )  

>>> split([1,2,3,4,5,6,7,8,9,10], [0,1,1,0,2,3,4,0,1,2])
([1, 4, 8], [2, 3, 9], [5, 10], [6], [7])

