day 8

day8/1.py

@@ -1,34 +1,41 @@
-import numpy
-
 with open(r'day8/input.txt', 'r') as input:
     lines = list(map(lambda x: list(map(lambda y: int(y),x.split(','))),input.read().split('\n')[:-1]))
 
 def dist(a,b):
     return (a[0]-b[0])**2 + (a[1]-b[1])**2 + (a[2]-b[2])**2
 
-def find_best(i, exclusion = []):
-    best_distances[i] = [100000000,-1]
+excluded_neigbors = [set([i]) for i in range(len(lines))]
+
+def find_best(i):
+    best_distances[i] = [10**15,-1]
     for j,node2 in enumerate(lines):
-        print(exclusion)
-        if i == j or j in exclusion: continue
-        distance = dist(node,node2)
+        if j in excluded_neigbors[i]: continue
+        distance = dist(lines[i],node2)
         best_distances[i] = min([distance,j], best_distances[i],key=lambda x : x[0])
 
 best_distances = []
 
-idx_circuit = {}
+idx_circuit = list(range(len(lines)))
 
-for i,node in enumerate(lines):
-    idx_circuit[i] = i
+for i in range(len(lines)):
     best_distances.append(0)
     find_best(i)
 
-pairs_left = 1000
-while pairs_left > 0:
-    i = numpy.argmin(best_distances)
-    print(i, best_distances[i])
-    print(idx_circuit)
-    idx_circuit[best_distances[i][1]] = idx_circuit[i]
-    print(idx_circuit.keys())
-    find_best(i, exclusion=filter(lambda x: idx_circuit[x] == idx_circuit[i], idx_circuit.keys()))
-    
+for _ in range(1000):
+    min_idx = best_distances.index(min(best_distances, key = lambda x:x[0]))
+    if (old_idx := idx_circuit[min_idx]) != (new_idx := idx_circuit[(ass_idx := best_distances[min_idx][1])]): 
+        for i in range(len(lines)):
+            if idx_circuit[i] == old_idx:
+                idx_circuit[i] = new_idx
+    excluded_neigbors[min_idx].add(ass_idx)
+    excluded_neigbors[ass_idx].add(min_idx)
+    find_best(min_idx)
+    find_best(ass_idx)
+
+counts = []
+for circuit in set(idx_circuit):
+    count = len(list(filter(lambda x: idx_circuit[x] == circuit,idx_circuit)))
+    counts.append(count)
+counts.sort(reverse=True)
+print(counts)
+print("score:",counts[0]*counts[1]*counts[2])