Its purpose is to find the longest path in an equally-weighted tree denoted as such:
31 22 3The first number denotes both the number of vertices and the number of edges (3 - 1).
(defn farthest [edg current-node entry-node len] (let [ farthest-key (atom current-node) farthest-val (atom len) ] (do (dorun (map (fn [n] ; check if theres a way to this node and that we're not going back (if (not= n entry-node) (let [new (farthest edg n current-node (+ len 1)) new-val (second new) new-key (first new)] (if (> new-val @farthest-val) (do (reset! farthest-val new-val) (reset! farthest-key new-key) ) ) ) ) ) (aget edg current-node) ) ) [@farthest-key @farthest-val] ) ))(defn main [] (let [edge-count (read) edges (atom (to-array (repeat edge-count []) ) )] (dotimes [n (- edge-count 1)] (let [edge-a (- (read) 1) edge-b (- (read) 1)] (aset @edges edge-a (conj (aget @edges edge-a) edge-b) ) (aset @edges edge-b (conj (aget @edges edge-b) edge-a) ) ) ) (let [ ft (farthest @edges 0 0 0) ftv (first ft) sol (farthest @edges ftv ftv 0) ] (println (second sol)) ) ))(main)I've taken multiple attempts to optimize it, but I'm still struggling to make it run under the allowed time (1 second for a tree of up to 10000 vertices/connections). The most notable improvement was a change of the data structure from a connection matrix to a bunch of neighbourhood lists.
It is a university assignment, but I'm perfectly fine with disclosing that I got help here. I feel that I've already given it everything that I can and it simply requires more intricate knowledge about Clojure and its performance in particular, rather than a purely algorithmic change. (I know for a fact that one my colleagues managed to fit in the allocated time using the same algorithm on the same grading system).