dost

@@ -61,15 +61,23 @@ def show_mat(distances: DistTable) -> str:

         rows.append(row)

     return "\n".join(rows)

-# good results, slow

+# this and other quirks in cachey_nearest are legitimately for speed

+def min2(a, b):

+    return a if a < b else b

+

+# good results, slow: O(n^3)

 def cachey_nearest(distances: DistTable) -> IndSeq:

     seq = []

     options = set(range(len(distances)))

     nearests = [math.inf for _ in range(len(distances))]

     while options:

-        reduceds = {o: [min(distances[o][i], nearests[i]) for i in range(len(nearests))] for o in options}

-        best = min(options, key=lambda o: sum(reduceds[o]))

-        nearests = reduceds[best]

+        best, brds, score = None, None, None

+        for o in options:

+            reduced = [min2(x, y) for x, y in zip(distances[o], nearests)]

+            sr = sum(reduced)

+            if best is None or sr < score:

+                best, brds, score = o, reduced, sr

+        nearests = brds

         seq.append(best)

         options.remove(best)

     return seq

@@ -83,7 +91,7 @@ def cachey_maximin(distances: DistTable) -> IndSeq:

     options.remove(start)

     score = math.inf

     while options:

-        updateds = {o: min(min(distances[o][i] for i in seq), score) for o in options}

+        updateds = {o: min2(min(distances[o][i] for i in seq), score) for o in options}

         best = max(options, key=lambda o: updateds[o])

         score = updateds[best]

         seq.append(best)