Efficiently get sorted sums of a sorted list

Question

You have an ascending list of numbers, what is the most efficient algorithm you can think of to get the ascending list of sums of every two numbers in that list. Duplicates in

Answer 1

This question has been wracking my brain for about a day now. Awesome.

Anyways, you can't get away from the n^2 nature of it easily, but you can do slightly better with the merge since you can bound the range to insert each element in.

If you look at all the lists you generate, they have the following form:

(a[i], a[j]) | j>=i

If you flip it 90 degrees, you get:

(a[i], a[j]) | i<=j

Now, the merge process should be taking two lists i and i+1 (which correspond to lists where the first member is always a[i] and a[i+1]), you can bound the range to insert element (a[i + 1], a[j]) into list i by the location of (a[i], a[j]) and the location of (a[i + 1], a[j + 1]).

This means that you should merge in reverse in terms of j. I don't know (yet) if you can leverage this across j as well, but it seems possible.

Answer 2

In SQL:

create table numbers(n int not null)
insert into numbers(n) values(1),(1), (2), (2), (3), (4)


select distinct num1.n+num2.n sum2n
from numbers num1
inner join numbers num2 
    on num1.n<>num2.n
order by sum2n

C# LINQ:

List<int> num = new List<int>{ 1, 1, 2, 2, 3, 4};
var uNum = num.Distinct().ToList();
var sums=(from num1 in uNum
        from num2 in uNum 
        where num1!=num2
        select num1+num2).Distinct();
foreach (var s in sums)
{
    Console.WriteLine(s);
}

Answer 3

The best I could come up with is to produce a matrix of sums of each pair, and then merge the rows together, a-la merge sort. I feel like I'm missing some simple insight that will reveal a much more efficient solution.

My algorithm, in Haskell:

matrixOfSums list = [[a+b | b <- list, b >= a] | a <- list]

sortedSums = foldl merge [] matrixOfSums

--A normal merge, save that we remove duplicates
merge xs [] = xs
merge [] ys = ys
merge (x:xs) (y:ys) = case compare x y of
    LT -> x:(merge xs (y:ys))
    EQ -> x:(merge xs (dropWhile (==x) ys))
    GT -> y:(merge (x:xs) ys)

I found a minor improvement, one that's more amenable to lazy stream-based coding. Instead of merging the columns pair-wise, merge all of them at once. The advantage being that you start getting elements of the list immediately.

-- wide-merge does a standard merge (ala merge-sort) across an arbitrary number of lists
-- wideNubMerge does this while eliminating duplicates
wideNubMerge :: Ord a => [[a]] -> [a]
wideNubMerge ls = wideNubMerge1 $ filter (/= []) ls
wideNubMerge1 [] = []
wideNubMerge1 ls = mini:(wideNubMerge rest)
    where mini = minimum $ map head ls
          rest = map (dropWhile (== mini)) ls

betterSortedSums = wideNubMerge matrixOfSums

However, if you know you're going to use all of the sums, and there's no advantage to getting some of them earlier, go with 'foldl merge []', as it's faster.

Answer 4

Rather than coding this out, I figure I'll pseudo-code it in steps and explain my logic, so that better programmers can poke holes in my logic if necessary.

On the first step we start out with a list of numbers length n. For each number we need to create a list of length n-1 becuase we aren't adding a number to itself. By the end we have a list of about n sorted lists that was generated in O(n^2) time.

step 1 (startinglist) 
for each number num1 in startinglist
   for each number num2 in startinglist
      add num1 plus num2 into templist
   add templist to sumlist
return sumlist 

In step 2 because the lists were sorted by design (add a number to each element in a sorted list and the list will still be sorted) we can simply do a mergesort by merging each list together rather than mergesorting the whole lot. In the end this should take O(n^2) time.

step 2 (sumlist) 
create an empty list mergedlist
for each list templist in sumlist
   set mergelist equal to: merge(mergedlist,templist)
return mergedlist

The merge method would be then the normal merge step with a check to make sure that there are no duplicate sums. I won't write this out because anyone can look up mergesort.

So there's my solution. The entire algorithm is O(n^2) time. Feel free to point out any mistakes or improvements.

Answer 5

Edit as of 2018: You should probably stop reading this. (But I can't delete it as it is accepted.)

If you write out the sums like this:

1 4  5  6  8  9
---------------
2 5  6  7  9 10
  8  9 10 12 13
    10 11 13 14
       12 14 15
          16 17
             18

You'll notice that since M[i,j] <= M[i,j+1] and M[i,j] <= M[i+1,j], then you only need to examine the top left "corners" and choose the lowest one.

e.g.

• only 1 top left corner, pick 2
• only 1, pick 5
• 6 or 8, pick 6
• 7 or 8, pick 7
• 9 or 8, pick 8
• 9 or 9, pick both :)
• 10 or 10 or 10, pick all
• 12 or 11, pick 11
• 12 or 12, pick both
• 13 or 13, pick both
• 14 or 14, pick both
• 15 or 16, pick 15
• only 1, pick 16
• only 1, pick 17
• only 1, pick 18

Of course, when you have lots of top left corners then this solution devolves.

I'm pretty sure this problem is Ω(n²), because you have to calculate the sums for each M[i,j] -- unless someone has a better algorithm for the summation :)

Answer 6

If you are looking for a truly language agnostic solution then you will be sorely disappointed in my opinion because you'll be stuck with a for loop and some conditionals. However if you opened it up to functional languages or functional language features (I'm looking at you LINQ) then my colleagues here can fill this page with elegant examples in Ruby, Lisp, Erlang, and others.