Day 16 Part 2 works now!

2024/day16/code.py

@@ -3,7 +3,8 @@
 import sys, math
 import numpy as np
 
-def dijkstra(graph, s, v, a):
+
+def dijkstra(graph, v, a):
     Q = [n for n in graph.keys()]
     lq = len(Q)
     while len(Q) > 0:
@@ -14,27 +15,33 @@ def dijkstra(graph, s, v, a):
                 distance_update(graph, u,vo,a,v)
     return v, a
 
+
 def distance_update(g, u, vo, a, v):
     dist = 1 if vo[2] == u[2] else 1000
     alt = a[u] + dist
+    # joining the sets does not work because we never remove the older nodes!
     if alt <= a[vo]:
+        if alt < a[vo]:
+            v[vo] = set([])
+            a[vo] = alt
         v[vo].add(u)
         v[vo] = v[vo].union(set(v[u]))
-    if alt < a[vo]:
-        a[vo] = alt
 
-def count_set(edges):
+
+def count_set(edges, lab):
     edg = set([])
     for e in edges:
         edg.add((e[0], e[1]))
-    return len(edg)
+        lab[e[1]][e[0]] = 'O'
+    return edg
+
 
 if __name__ == '__main__':
     lab = [list(line.strip('\n')) for line in open(sys.argv[1])]
     rot90 = {(0,-1): [(-1,0),(1,0)], (1,0): [(0,-1),(0,1)], (0,1): [(1,0),(-1, 0)], (-1,0): [(0,1),(0,-1)]}
 
     start = (1, len(lab)-2, (1,0))
-    end = (len(lab[0])-2, 1)
+    end = (len(lab[0])-2, 1, (0,-1))
     graph = {}
     distance = {}
     pred = {}
@@ -46,20 +53,23 @@ if __name__ == '__main__':
                 pred[(x,y,d)] = set([])
                 graph[(x,y,d)] = []
                 for d1 in rot90[d]:
-                    graph[(x,y,d)].append((x,y,d1))
-                if lab[y+d[1]][x+d[0]] == '.' or lab[y+d[1]][x+d[0]] == 'E':
+                    if not lab[y+d1[1]][x+d1[0]] == '#': graph[(x,y,d)].append((x,y,d1))
+                if lab[y+d[1]][x+d[0]] != '#':
                     graph[(x,y,d)].append((x+d[0], y+d[1], d))
     distance[start] = 0
-    v, a = dijkstra(graph, start, pred, distance)
-    print([a[end[0], end[1], d] for d in [(0,1), (0,-1), (1,0), (-1,0)]], [1+count_set(v[end[0], end[1], d]) for d in [(0,1), (0,-1), (1,0), (-1,0)]])
+    v1, a1 = dijkstra(graph, pred, distance)
+    d1 = count_set(v1[end], lab)
 
     # challenge 1
-    res1 = min([a[end[0], end[1], d] for d in [(0,1), (0,-1), (1,0), (-1,0)]])
+    res1 = a1[end]
     print(f"challenge 1:\n{res1}\n")
 
-    # challenge 2
-    ind = [a[end[0], end[1], d] for d in [(0,1), (0,-1), (1,0), (-1,0)]].index(res1)
-    d = [(0,1), (0,-1), (1,0), (-1,0)][ind]
-    res2 = 1+count_set(v[end[0], end[1], d])
+    # challenge 2, needed some reddit help again...
+    d1.add((end[0],end[1]))
+    d1.add((start[0], start[1]))
+    res2 = len(d1)
     print(f"challenge 2:\n{res2}")
 
+    for line in lab:
+      print(''.join(line))
+

2024/day16/maze

@@ -0,0 +1,141 @@
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2024/day16/other_code.py

@@ -0,0 +1,79 @@
+from collections import namedtuple
+from math import sqrt
+from pathlib import Path
+ 
+ 
+Point = namedtuple('Point', ['y', 'x'])
+Node = namedtuple('Node', ['p', 'd'])
+ 
+# set up inputs
+text = Path('input').read_text('utf-8')
+board_lines = text.splitlines()
+width = len(board_lines[0])
+board = list(map(list, board_lines))
+start, end = Point(*divmod(text.find('S'), width + 1)), Point(*divmod(text.find('E'), width + 1))
+ 
+# simple cost heuristic based on distance to end node
+def cost_heuristic(p: Point) -> float:
+    return sqrt((p.x - end.x) ** 2 + (p.y - end.y) ** 2)
+ 
+# walks path backwards, scans for nodes with incoming paths of equal cost, and traverses all recursively
+def equal_cost_backtrace(parent: dict, node_cost: dict, current: Node) -> set[Point]:
+    last_direction = current.d
+ 
+    trace = {current.p}
+    while current := parent.get(current):
+        trace.add(current.p)
+        for d in map(lambda o: (current.d + o) & 3, [1, -1]):
+            test = Node(current.p, d)
+            if last_direction != current.d and (node_cost.get(test, 0) - node_cost[current]) == 1000:
+                trace.update(equal_cost_backtrace(parent, node_cost, parent.get(test)))
+ 
+        last_direction = current.d
+ 
+    return trace
+ 
+# simple A star
+def a_star() -> tuple[int, int]:
+    t_start = Node(start, 0)
+ 
+    pending: set[Node] = {t_start}
+    parent: dict[Node, Node] = {}
+    node_cost: dict[Node, float] = {t_start: 0.0}
+    total_cost: dict[Node, float] = {t_start: cost_heuristic(t_start.p)}
+ 
+    while len(pending):
+        current = min(pending, key=lambda t: total_cost[t])
+ 
+        if current.p == end:
+            return int(node_cost[current]), len(equal_cost_backtrace(parent, node_cost, current))
+ 
+        pending.remove(current)
+ 
+        # scan in all directions
+        for i, vector in enumerate([(0, 1), (1, 0), (0, -1), (-1, 0)]):
+            neighbor = Node(Point(current.p.y + vector[0], current.p.x + vector[1]), i)
+            if board[neighbor.p.y][neighbor.p.x] == '#':
+                continue
+            
+            # assign new cost based on rotation and step
+            new_cost = node_cost[current] + [0, 1000, 2000, 1000][(i - current.d) & 3] + 1
+            if new_cost >= node_cost.get(neighbor, 1e13):
+                continue
+ 
+            parent[neighbor] = current
+            node_cost[neighbor] = new_cost
+            total_cost[neighbor] = new_cost + cost_heuristic(neighbor.p)
+ 
+            if neighbor in pending:
+                continue
+ 
+            pending.add(neighbor)
+ 
+    return 0, 0
+ 
+ 
+lowest_cost, nodes = a_star()
+ 
+print("Part 1:", lowest_cost)
+print("Part 2:", nodes)