Day 12

day12/input.txt

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+abcccccccccccccaaaaaaacccccccccccccccccccaaaaaaaaaaaaaaaacccccccccccaaaaaccccccccccccccccccaaaaacccaaccccaaaaccccaacaacccaaaccccjjjiqqqtttwwywwwwwwwwrrroofffcccccc
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+abccaaacccccccaaacaaacccccccccaaaaaaaacccaaaaaacccaaaaaaaaacccccaaaaaaaaaaaaaacccccccaaaaaccccaaaaaaaaccccccaaaaccccccccccccccccccccccccccaaaccccccccccccccccccaaaa
+abcaaaacccccccaaccccccccccccccaaaaaaaacccaaccaacccaaaaaaaaaaccccccccaaaaaaacaacccccccccaaaccccccaaacaaccccccaaaacccccccccccccccccccccccccccccccccccccccccccccaaaaaa

day12/part1.py

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+#!/usr/bin/env python3
+import heapq
+
+import numpy as np
+
+lines = np.array([np.array([ord(y) for y in x.strip()]) for x in open("input.txt")])
+start = tuple(np.array(np.where(lines == ord('S'))).T[0])
+end = tuple(np.array(np.where(lines == ord('E'))).T[0])
+
+lines[np.where(lines == ord('S'))] = ord('a')
+lines[np.where(lines == ord('E'))] = ord('z')
+lines = lines-ord('a')
+
+def neighbors(n):
+    x, y = n
+    if x > 0 and lines[n] + 1 >= lines[x-1, y]:
+        yield x - 1, y
+    if y > 0 and lines[n] + 1 >= lines[x, y-1]:
+        yield x, y - 1
+    if x+1 < len(lines) and lines[n] + 1 >= lines[x+1, y]:
+        yield x + 1, y
+    if y+1 < len(lines[0]) and lines[n] + 1 >= lines[x, y+1]:
+        yield x, y + 1
+
+def distance(n1, n2):
+    return 1
+
+def cost(n):
+    return abs(n[0]-end[0])+abs(n[1]-end[1])
+
+def is_end(n):
+    return n == end
+
+
+def find_path(start, end_fnct, neighbors_fnct, heuristic_cost_estimate_fnct, distance_between_fnct):
+    open = [(0, 0, start, None)]
+    closed = dict()
+    while open:
+        _, prio, n, prev = heapq.heappop(open)
+        if n in closed:
+            continue
+        closed[n] = (prio, prev)
+        if end_fnct(n):
+            path = [n]
+            while path[-1] is not None:
+                path.append(closed[path[-1]][1])
+            return path[:-1]
+
+        for neighbor in neighbors_fnct(n):
+            dist = prio + distance_between_fnct(n, neighbor)
+            heuristic = dist + heuristic_cost_estimate_fnct(neighbor)
+            heapq.heappush(open, (heuristic, dist, neighbor, n))
+    return None
+
+
+
+
+path = list(find_path(
+    start,
+    end_fnct=is_end,
+    neighbors_fnct=neighbors,
+    heuristic_cost_estimate_fnct=cost,
+    distance_between_fnct=distance
+))
+
+print(len(path)-1)

day12/part2.py

@@ -0,0 +1,66 @@
+#!/usr/bin/env python3
+import heapq
+
+import numpy as np
+
+lines = np.array([np.array([ord(y) for y in x.strip()]) for x in open("input.txt")])
+start = tuple(np.array(np.where(lines == ord('S'))).T[0])
+end = tuple(np.array(np.where(lines == ord('E'))).T[0])
+
+lines[np.where(lines == ord('S'))] = ord('a')
+lines[np.where(lines == ord('E'))] = ord('z')
+lines = lines-ord('a')
+
+def neighbors(n):
+    x, y = n
+    if x > 0 and lines[n] - 1 <= lines[x-1, y]:
+        yield x - 1, y
+    if y > 0 and lines[n] - 1 <= lines[x, y-1]:
+        yield x, y - 1
+    if x+1 < len(lines) and lines[n] - 1 <= lines[x+1, y]:
+        yield x + 1, y
+    if y+1 < len(lines[0]) and lines[n] - 1 <= lines[x, y+1]:
+        yield x, y + 1
+
+def distance(n1, n2):
+    return 1
+
+def cost(n):
+    return lines[n]
+
+def is_end(n):
+    return lines[n] == 0
+
+
+def find_path(start, end_fnct, neighbors_fnct, heuristic_cost_estimate_fnct, distance_between_fnct):
+    open = [(0, 0, start, None)]
+    closed = dict()
+    while open:
+        _, prio, n, prev = heapq.heappop(open)
+        if n in closed:
+            continue
+        closed[n] = (prio, prev)
+        if end_fnct(n):
+            path = [n]
+            while path[-1] is not None:
+                path.append(closed[path[-1]][1])
+            return path[:-1]
+
+        for neighbor in neighbors_fnct(n):
+            dist = prio + distance_between_fnct(n, neighbor)
+            heuristic = dist + heuristic_cost_estimate_fnct(neighbor)
+            heapq.heappush(open, (heuristic, dist, neighbor, n))
+    return None
+
+
+
+
+path = list(find_path(
+    end,
+    end_fnct=is_end,
+    neighbors_fnct=neighbors,
+    heuristic_cost_estimate_fnct=cost,
+    distance_between_fnct=distance
+))
+
+print(len(path)-1)