Index: nodes/channelea.ml
===================================================================
--- nodes/channelea.ml	(revision 1998)
+++ nodes/channelea.ml	(revision 1999)
@@ -119,4 +119,6 @@
 (** Shorthand for List.tail *)
 let tail = List.tl
+let even x = (x mod 2) == 0
+(*let shuffle = Array.sort (fun _ _ -> 1 - Random.int(2))*)
 let just x = match x with
 	       Nothing -> assert false
@@ -208,4 +210,24 @@
 	let print_node n = print_string (n.node_name ^ ": " ^ (wis n) ^ "\n") in
 	List.iter print_node sorted_nodes
+
+(** n-point crossover operator. pick n points along the length of the parents, 
+    produce a child by copying from one parent, switching parents when hitting a
+    chosen crossover point *)
+let crossover n c1 c2 = 
+	let keys1 = keys (c1.conf) in
+	let numkeys1 = List.length keys1 in
+	let pickpoint i = (if even i then c1.conf else c2.conf),
+			  (if i < n then (Random.int numkeys1) else numkeys1) in
+	let crosspoints = Array.init (n + 1) pickpoint in
+	let result = Hashtbl.create (List.length keys1) in
+	let i = ref 0 in
+	Array.sort (fun a b -> compare (snd a) (snd b)) crosspoints;
+	Array.iter (fun (h, p) -> while !i < p do
+					let key = List.nth keys1 !i in
+					Hashtbl.add result key (Hashtbl.find h key);
+					incr i
+				  done) crosspoints;
+	assert ((List.length (keys result)) == (List.length keys1));
+	{ score = 0; conf = result }
 
 (** Generalized evolutionary algorithm driver. 
@@ -223,8 +245,9 @@
 	let generation = ref 0 in
 	let all_nodes = values nodes in
-	let iterate = recombine $ mutate $ evaluate $ select in
+	(*let iterate = recombine $ mutate $ evaluate $ select in*)
+	let iterate = select $ evaluate $ mutate $ recombine in 
 	while !iterations_since_new_high_score < max_stagnant_iterations do
 		let newpop = iterate population in
-		Array.sort (fun a b -> compare b.score a.score) newpop;
+		assert ((Array.length newpop) == population_size);
 		copyarray newpop population;
 		let high_score = population.(0).score in
@@ -337,5 +360,12 @@
 	let evaluate_hash = score_configuration all_nodes in
 	let initialize () = Array.init population_size (fun _ -> random_configuration groups evaluate_hash) in
-	let recombine x = x in
+	let recombine pop = pop in
+(*
+		let numoffspring = Random.int population_size in
+		let children = Array.init numoffspring (fun _ -> 
+			let father = pop.(Random.int population_size) in
+			let mother = pop.(Random.int population_size) in
+			crossover 2 father mother) in
+		Array.append pop children in *)
 	let maxchannel essid =
 		let group = Hashtbl.find groups essid in
@@ -357,5 +387,8 @@
 		Array.iter (fun c -> c.score <- evaluate_hash c.conf) population;
 		population in
-	let select p = Array.sub p 0 ((Array.length p) / 2) in
+	let select p = 
+		Array.sort (fun a b -> compare b.score a.score) p;
+		(*shuffle p;*)
+		Array.sub p 0 population_size in
 	let best = evolutionary_algorithm initialize recombine mutate evaluate select in
 	print_conf best.conf;;