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using python itertools to manage nested for loops


I am trying to use itertools.product to manage the bookkeeping of some nested for loops, where the number of nested loops is not known in advance. Below is a specific example where I have chosen two nested for loops; the choice of two is only for clarity, what I need is a solution that works for an arbitrary number of loops.

This question provides an extension/generalization of the question appearing here: Efficient algorithm for evaluating a 1-d array of functions on a same-length 1d numpy array

Now I am extending the above technique using an itertools trick I learned here: Iterating over an unknown number of nested loops in python

Preamble:

from itertools import product

def trivial_functional(i, j): return lambda x : (i+j)*x

idx1 = [1, 2, 3, 4]
idx2 = [5, 6, 7]
joint = [idx1, idx2]

func_table  = []
for items in product(*joint):
    f = trivial_functional(*items)
    func_table.append(f)

At the end of the above itertools loop, I have a 12-element, 1-d array of functions, func_table, each element having been built from the trivial_functional.

Question:

Suppose I am given a pair of integers, (i_1, i_2), where these integers are to be interpreted as the indices of idx1 and idx2, respectively. How can I use itertools.product to determine the correct corresponding element of the func_table array?

I know how to hack the answer by writing my own function that mimics the itertools.product bookkeeping, but surely there is a built-in feature of itertools.product that is intended for exactly this purpose?


Solution

  • I don't know of a way of calculating the flat index other than doing it yourself. Fortunately this isn't that difficult:

    def product_flat_index(factors, indices):
      if len(factors) == 1: return indices[0]
      else: return indices[0] * len(factors[0]) + product_flat_index(factors[1:], indices[1:])
    
    >> product_flat_index(joint, (2, 1))
    9
    

    An alternative approach is to store the results in a nested array in the first place, making translation unnecessary, though this is more complex:

    from functools import reduce
    from operator import getitem, setitem, itemgetter
    
    def get_items(container, indices):
      return reduce(getitem, indices, container)
    
    def set_items(container, indices, value):
      c = reduce(getitem, indices[:-1], container)
      setitem(c, indices[-1], value)
    
    def initialize_table(lengths):
      if len(lengths) == 1: return [0] * lengths[0]
      subtable = initialize_table(lengths[1:])
      return [subtable[:] for _ in range(lengths[0])]
    
    func_table = initialize_table(list(map(len, joint)))
    for items in product(*map(enumerate, joint)):
      f = trivial_functional(*map(itemgetter(1), items))
      set_items(func_table, list(map(itemgetter(0), items)), f)
    
    >>> get_items(func_table, (2, 1)) # same as func_table[2][1]
    <function>