-- # Reducing the result of a filter -- -- Suppose we wish to sum all the positive values of some array. The -- obvious way to write it is as follows: def sum_pos (xs: []i32) = reduce (+) 0 (filter (>0) xs) -- This gives the right result, but it is not optimal. Since `filter` -- is a reasonably expensive operation, it is better to implement this -- pattern by `map`ing the "removed" elements to the [neutral -- element](scan-reduce.html): def sum_pos_better (xs: []i32) = reduce (+) 0 (map (\x -> if x > 0 then x else 0) xs) -- These `map`-`reduce` compositions are one of the most efficient -- parallel programming patterns - quite parallel, and with low -- execution overhead. If we wish, we can factor this -- filter-then-reduce strategy into a separate higher-order function: def reduce_some 'a (op: a -> a -> a) (ne: a) (p: a -> bool) (xs: []a) : a = reduce op ne (map (\x -> if p x then x else ne) xs) -- Then we can define our function as simply: def sum_pos_best (xs: []i32) = reduce_some (+) 0 (>0) xs -- # See also -- -- [Reducing or scanning without a neutral -- element](no-neutral-element.html), [Scattering the result of a -- filter](filter-scatter.html).