How to get 'fair combination' from an array of n elements? - ruby

Question

Using combination method on Ruby,
[1, 2, 3, 4, 5, 6].combination(2).to_a
#=> [[1, 2], [1, 3], [1, 4], [1, 5], [1, 6], [2, 3],
# [2, 4], [2, 5], [2, 6], [3, 4], [3, 5], [3, 6],
# [4, 5], [4, 6], [5, 6]]
we can get a 2-dimensional array having 15 (6C2) elements.
I would like to create a fair_combination method that returns an array like this:
arr = [[1, 2], [3, 5], [4, 6],
[3, 4], [5, 1], [6, 2],
[5, 6], [1, 3], [2, 4],
[2, 3], [4, 5], [6, 1],
[1, 4], [2, 5], [3, 6]]
So that every three sub-arrays (half of 6) contain all the given elements:
arr.each_slice(3).map { |a| a.flatten.sort }
#=> [[1, 2, 3, 4, 5, 6],
# [1, 2, 3, 4, 5, 6],
# [1, 2, 3, 4, 5, 6],
# [1, 2, 3, 4, 5, 6],
# [1, 2, 3, 4, 5, 6]]
This makes it kind of "fair", by using as different elements as possible as arrays go on.
To make it more general, what it needs to satisfy is as follows:
(1) As you follow the arrays from start and count how many times each number appears, at any point it should be as flat as possible;
(1..7).to_a.fair_combination(3)
#=> [[1, 2, 3], [4, 5, 6], [7, 1, 4], [2, 5, 3], [6, 7, 2], ...]
The first 7 numbers make [1,2,...,7] and so do the following 7 numbers.
(2) Once number A comes in the same array with B, A does not want to be in the same array with B if possible.
(1..10).to_a.fair_combination(4)
#=> [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 1, 5], [2, 6, 9, 3], [4, 7, 10, 8], ...]
Is there any good algorithm that creates a "fair combination" like this ?

Answer 1

It's not guaranteed to give the best solution, but it gives a good enough one.
At each step, it chooses a minimal subpool which is the set of items of minimal height, for which there is still a combination to choose from (height is the number of times the items have been used before).
For instance, let the enumerator be
my_enum = FairPermuter.new('abcdef'.chars, 4).each
The first iteration may return
my_enum.next # => ['a', 'b', 'c', 'd']
At this point those letters have height 1, but there is not enough letters of height 0 to make a combination, so take just all of them for the next:
my_enum.next # => ['a', 'b', 'c', 'e'] for instance
Now the heights are 2 for a, b and c, 1 for d and e, and 0 for f, and still the optimal pool is the full initial set.
So this is not really optimized for combinations of large size. On the other side, if the size of the combination is at most half of the size of the initial set, then the algorithm is pretty decent.
class FairPermuter
def initialize(pool, size)
#pool = pool
#size = size
#all = Array(pool).combination(size)
#used = []
#counts = Hash.new(0)
#max_count = 0
end
def find_valid_combination
[*0..#max_count].each do |height|
candidates = #pool.select { |item| #counts[item] <= height }
next if candidates.size < #size
cand_comb = [*candidates.combination(#size)] - #used
comb = cand_comb.sample
return comb if comb
end
nil
end
def each
return enum_for(:each) unless block_given?
while combination = find_valid_combination
#used << combination
combination.each { |k| #counts[k] += 1 }
#max_count = #counts.values.max
yield combination
return if #used.size >= [*1..#pool.size].inject(1, :*)
end
end
end
Results for fair combinations of 4 over 6
[[1, 2, 4, 6], [3, 4, 5, 6], [1, 2, 3, 5],
[2, 4, 5, 6], [2, 3, 5, 6], [1, 3, 5, 6],
[1, 2, 3, 4], [1, 3, 4, 6], [1, 2, 4, 5],
[1, 2, 3, 6], [2, 3, 4, 6], [1, 2, 5, 6],
[1, 3, 4, 5], [1, 4, 5, 6], [2, 3, 4, 5]]
Results of fair combination of 2 over 6
[[4, 6], [1, 3], [2, 5],
[3, 5], [1, 4], [2, 6],
[4, 5], [3, 6], [1, 2],
[2, 3], [5, 6], [1, 6],
[3, 4], [1, 5], [2, 4]]
Results of fair combinations of 2 over 5
[[4, 5], [2, 3], [3, 5],
[1, 2], [1, 4], [1, 5],
[2, 4], [3, 4], [1, 3],
[2, 5]]
Time to get combinations of 5 over 12:
1.19 real 1.15 user 0.03 sys

Answer 2

Naïve implementation would be:
class Integer
# naïve factorial implementation; no checks
def !
(1..self).inject(:*)
end
end
class Range
# constant Proc instance for tests; not needed
C_N_R = -> (n, r) { n.! / ( r.! * (n - r).! ) }
def fair_combination(n)
to_a.permutation
.map { |a| a.each_slice(n).to_a }
.each_with_object([]) do |e, memo|
e.map!(&:sort)
memo << e if memo.all? { |me| (me & e).empty? }
end
end
end
▶ (1..6).fair_combination(2)
#⇒ [
# [[1, 2], [3, 4], [5, 6]],
# [[1, 3], [2, 5], [4, 6]],
# [[1, 4], [2, 6], [3, 5]],
# [[1, 5], [2, 4], [3, 6]],
# [[1, 6], [2, 3], [4, 5]]]
▶ (1..6).fair_combination(3)
#⇒ [
# [[1, 2, 3], [4, 5, 6]],
# [[1, 2, 4], [3, 5, 6]],
# [[1, 2, 5], [3, 4, 6]],
# [[1, 2, 6], [3, 4, 5]],
# [[1, 3, 4], [2, 5, 6]],
# [[1, 3, 5], [2, 4, 6]],
# [[1, 3, 6], [2, 4, 5]],
# [[1, 4, 5], [2, 3, 6]],
# [[1, 4, 6], [2, 3, 5]],
# [[1, 5, 6], [2, 3, 4]]]
▶ Range::C_N_R[6, 3]
#⇒ 20
Frankly, I do not understand how this function should behave for 10 and 4, but anyway this implementation is too memory consuming to work properly on big ranges (on my machine it gets stuck on ranges of size > 8.)
To adjust this to more robust solution one needs to get rid of permutation there in favor of “smart concatenate permuted arrays.”
Hope this is good for starters.