|
| 1 | +# -------------------------------- Input data ---------------------------------------- # |
| 2 | +import os, pathfinding, heapq |
| 3 | + |
| 4 | +from complex_utils import * |
| 5 | + |
| 6 | +test_data = {} |
| 7 | + |
| 8 | +test = 1 |
| 9 | +test_data[test] = { |
| 10 | + "input": """######### |
| 11 | +#b.A.@.a# |
| 12 | +#########""", |
| 13 | + "expected": ["8", "Unknown"], |
| 14 | +} |
| 15 | + |
| 16 | +test += 1 |
| 17 | +test_data[test] = { |
| 18 | + "input": """######################## |
| 19 | +#f.D.E.e.C.b.A.@.a.B.c.# |
| 20 | +######################.# |
| 21 | +#d.....................# |
| 22 | +########################""", |
| 23 | + "expected": ["86", "Unknown"], |
| 24 | +} |
| 25 | + |
| 26 | +test += 1 |
| 27 | +test_data[test] = { |
| 28 | + "input": """######################## |
| 29 | +#...............b.C.D.f# |
| 30 | +#.###################### |
| 31 | +#.....@.a.B.c.d.A.e.F.g# |
| 32 | +########################""", |
| 33 | + "expected": ["132", "Unknown"], |
| 34 | +} |
| 35 | + |
| 36 | +test += 1 |
| 37 | +test_data[test] = { |
| 38 | + "input": """################# |
| 39 | +#i.G..c...e..H.p# |
| 40 | +########.######## |
| 41 | +#j.A..b...f..D.o# |
| 42 | +########@######## |
| 43 | +#k.E..a...g..B.n# |
| 44 | +########.######## |
| 45 | +#l.F..d...h..C.m# |
| 46 | +#################""", |
| 47 | + "expected": ["136", "Unknown"], |
| 48 | +} |
| 49 | + |
| 50 | +test += 1 |
| 51 | +test_data[test] = { |
| 52 | + "input": """######################## |
| 53 | +#@..............ac.GI.b# |
| 54 | +###d#e#f################ |
| 55 | +###A#B#C################ |
| 56 | +###g#h#i################ |
| 57 | +########################""", |
| 58 | + "expected": ["81", "Unknown"], |
| 59 | +} |
| 60 | + |
| 61 | +test += 1 |
| 62 | +test_data[test] = { |
| 63 | + "input": """####### |
| 64 | +#a.#Cd# |
| 65 | +##...## |
| 66 | +##.@.## |
| 67 | +##...## |
| 68 | +#cB#Ab# |
| 69 | +#######""", |
| 70 | + "expected": ["Unknown", "8"], |
| 71 | +} |
| 72 | + |
| 73 | +test += 1 |
| 74 | +test_data[test] = { |
| 75 | + "input": """############# |
| 76 | +#DcBa.#.GhKl# |
| 77 | +#.###...#I### |
| 78 | +#e#d#.@.#j#k# |
| 79 | +###C#...###J# |
| 80 | +#fEbA.#.FgHi# |
| 81 | +#############""", |
| 82 | + "expected": ["Unknown", "32"], |
| 83 | +} |
| 84 | + |
| 85 | +test += 1 |
| 86 | +test_data[test] = { |
| 87 | + "input": """############# |
| 88 | +#g#f.D#..h#l# |
| 89 | +#F###e#E###.# |
| 90 | +#dCba...BcIJ# |
| 91 | +#####.@.##### |
| 92 | +#nK.L...G...# |
| 93 | +#M###N#H###.# |
| 94 | +#o#m..#i#jk.# |
| 95 | +#############""", |
| 96 | + "expected": ["Unknown", "72"], |
| 97 | +} |
| 98 | + |
| 99 | +test = "real" |
| 100 | +input_file = os.path.join( |
| 101 | + os.path.dirname(__file__), |
| 102 | + "Inputs", |
| 103 | + os.path.basename(__file__).replace(".py", ".txt"), |
| 104 | +) |
| 105 | +test_data[test] = { |
| 106 | + "input": open(input_file, "r+").read().strip(), |
| 107 | + "expected": ["4844", "Unknown"], |
| 108 | +} |
| 109 | + |
| 110 | +# -------------------------------- Control program execution ------------------------- # |
| 111 | + |
| 112 | +case_to_test = "real" |
| 113 | +part_to_test = 2 |
| 114 | + |
| 115 | +# -------------------------------- Initialize some variables ------------------------- # |
| 116 | + |
| 117 | +puzzle_input = test_data[case_to_test]["input"] |
| 118 | +puzzle_expected_result = test_data[case_to_test]["expected"][part_to_test - 1] |
| 119 | +puzzle_actual_result = "Unknown" |
| 120 | + |
| 121 | + |
| 122 | +# -------------------------------- Actual code execution ----------------------------- # |
| 123 | +def grid_to_vertices(self, grid, diagonals_allowed=False, wall="#"): |
| 124 | + self.vertices = {} |
| 125 | + y = 0 |
| 126 | + |
| 127 | + for line in grid.splitlines(): |
| 128 | + for x in range(len(line)): |
| 129 | + if line[x] != wall: |
| 130 | + self.vertices[x - y * j] = line[x] |
| 131 | + y += 1 |
| 132 | + |
| 133 | + for source in self.vertices: |
| 134 | + for direction in directions_straight: |
| 135 | + target = source + direction |
| 136 | + if target in self.vertices: |
| 137 | + if source in self.edges: |
| 138 | + self.edges[source].append(target) |
| 139 | + else: |
| 140 | + self.edges[source] = [target] |
| 141 | + |
| 142 | + return True |
| 143 | + |
| 144 | + |
| 145 | +pathfinding.Graph.grid_to_vertices = grid_to_vertices |
| 146 | + |
| 147 | + |
| 148 | +def breadth_first_search(self, start, end=None): |
| 149 | + current_distance = 0 |
| 150 | + frontier = [(start, 0)] |
| 151 | + self.distance_from_start = {start: 0} |
| 152 | + self.came_from = {start: None} |
| 153 | + |
| 154 | + while frontier: |
| 155 | + vertex, current_distance = frontier.pop(0) |
| 156 | + current_distance += 1 |
| 157 | + neighbors = self.neighbors(vertex) |
| 158 | + if not neighbors: |
| 159 | + continue |
| 160 | + |
| 161 | + # Stop search when reaching another object |
| 162 | + if self.vertices[vertex] not in (".", "@") and vertex != start: |
| 163 | + continue |
| 164 | + |
| 165 | + for neighbor in neighbors: |
| 166 | + if neighbor in self.distance_from_start: |
| 167 | + continue |
| 168 | + # Adding for future examination |
| 169 | + frontier.append((neighbor, current_distance)) |
| 170 | + |
| 171 | + # Adding for final search |
| 172 | + self.distance_from_start[neighbor] = current_distance |
| 173 | + self.came_from[neighbor] = vertex |
| 174 | + |
| 175 | + if neighbor == end: |
| 176 | + return True |
| 177 | + |
| 178 | + if end: |
| 179 | + return True |
| 180 | + return False |
| 181 | + |
| 182 | + |
| 183 | +pathfinding.Graph.breadth_first_search = breadth_first_search |
| 184 | + |
| 185 | + |
| 186 | +def neighbors_part1(self, vertex): |
| 187 | + neighbors = {} |
| 188 | + for target_item in edges[vertex[0]]: |
| 189 | + if target_item == "@": |
| 190 | + neighbors[(target_item, vertex[1])] = edges[vertex[0]][target_item] |
| 191 | + elif target_item == target_item.lower(): |
| 192 | + if target_item in vertex[1]: |
| 193 | + neighbors[(target_item, vertex[1])] = edges[vertex[0]][target_item] |
| 194 | + else: |
| 195 | + keys = "".join(sorted([x for x in vertex[1]] + [target_item])) |
| 196 | + neighbors[(target_item, keys)] = edges[vertex[0]][target_item] |
| 197 | + else: |
| 198 | + if target_item.lower() in vertex[1]: |
| 199 | + neighbors[(target_item, vertex[1])] = edges[vertex[0]][target_item] |
| 200 | + else: |
| 201 | + continue |
| 202 | + |
| 203 | + return neighbors |
| 204 | + |
| 205 | + |
| 206 | +def neighbors_part2(self, vertex): |
| 207 | + neighbors = {} |
| 208 | + for robot in vertex[0]: |
| 209 | + for target_item in edges[robot]: |
| 210 | + new_position = vertex[0].replace(robot, target_item) |
| 211 | + distance = edges[robot][target_item] |
| 212 | + if target_item in "1234": |
| 213 | + neighbors[(new_position, vertex[1])] = distance |
| 214 | + elif target_item.islower(): |
| 215 | + if target_item in vertex[1]: |
| 216 | + neighbors[(new_position, vertex[1])] = distance |
| 217 | + else: |
| 218 | + keys = "".join(sorted([x for x in vertex[1]] + [target_item])) |
| 219 | + neighbors[(new_position, keys)] = distance |
| 220 | + else: |
| 221 | + if target_item.lower() in vertex[1]: |
| 222 | + neighbors[(new_position, vertex[1])] = distance |
| 223 | + |
| 224 | + return neighbors |
| 225 | + |
| 226 | + |
| 227 | +# Only the WeightedGraph method is replaced, so that it doesn't impact the first search |
| 228 | +if part_to_test == 1: |
| 229 | + pathfinding.WeightedGraph.neighbors = neighbors_part1 |
| 230 | +else: |
| 231 | + pathfinding.WeightedGraph.neighbors = neighbors_part2 |
| 232 | + |
| 233 | + |
| 234 | +def dijkstra(self, start, end=None): |
| 235 | + current_distance = 0 |
| 236 | + frontier = [(0, start)] |
| 237 | + heapq.heapify(frontier) |
| 238 | + self.distance_from_start = {start: 0} |
| 239 | + self.came_from = {start: None} |
| 240 | + min_distance = float("inf") |
| 241 | + |
| 242 | + while frontier: |
| 243 | + current_distance, vertex = heapq.heappop(frontier) |
| 244 | + |
| 245 | + if current_distance > min_distance: |
| 246 | + continue |
| 247 | + |
| 248 | + neighbors = self.neighbors(vertex) |
| 249 | + if not neighbors: |
| 250 | + continue |
| 251 | + |
| 252 | + # print (vertex, min_distance, len(self.distance_from_start)) |
| 253 | + |
| 254 | + for neighbor, weight in neighbors.items(): |
| 255 | + # We've already checked that node, and it's not better now |
| 256 | + if neighbor in self.distance_from_start and self.distance_from_start[ |
| 257 | + neighbor |
| 258 | + ] <= (current_distance + weight): |
| 259 | + continue |
| 260 | + |
| 261 | + # Adding for future examination |
| 262 | + heapq.heappush(frontier, (current_distance + weight, neighbor)) |
| 263 | + |
| 264 | + # Adding for final search |
| 265 | + self.distance_from_start[neighbor] = current_distance + weight |
| 266 | + self.came_from[neighbor] = vertex |
| 267 | + |
| 268 | + if len(neighbor[1]) == nb_keys: |
| 269 | + min_distance = min(min_distance, current_distance + weight) |
| 270 | + |
| 271 | + return end is None or end in self.distance_from_start |
| 272 | + |
| 273 | + |
| 274 | +pathfinding.WeightedGraph.dijkstra = dijkstra |
| 275 | + |
| 276 | + |
| 277 | +maze = pathfinding.Graph() |
| 278 | +maze.grid_to_vertices(puzzle_input) |
| 279 | + |
| 280 | +# First, simplify the maze to have only the important items (@, keys, doors) |
| 281 | +items = "abcdefghijklmnopqrstuvwxyz" + "abcdefghijklmnopqrstuvwxyz".upper() + "@" |
| 282 | +items = maze.grid_search(puzzle_input, items) |
| 283 | +nb_keys = len([x for x in items if x in "abcdefghijklmnopqrstuvwxyz"]) |
| 284 | + |
| 285 | +if part_to_test == 2: |
| 286 | + # Separate the start point |
| 287 | + start = items["@"][0] |
| 288 | + del items["@"] |
| 289 | + items["1"] = [start + northwest] |
| 290 | + items["2"] = [start + northeast] |
| 291 | + items["3"] = [start + southwest] |
| 292 | + items["4"] = [start + southeast] |
| 293 | + |
| 294 | + for dir in directions_straight + [0]: |
| 295 | + maze.add_walls([start + dir]) |
| 296 | + |
| 297 | + |
| 298 | +edges = {} |
| 299 | +for item in items: |
| 300 | + maze.reset_search() |
| 301 | + |
| 302 | + maze.breadth_first_search(items[item][0]) |
| 303 | + edges[item] = {} |
| 304 | + for other_item in items: |
| 305 | + if other_item == item: |
| 306 | + continue |
| 307 | + if items[other_item][0] in maze.distance_from_start: |
| 308 | + edges[item][other_item] = maze.distance_from_start[items[other_item][0]] |
| 309 | + |
| 310 | + |
| 311 | +# Then, perform Dijkstra on the simplified graph |
| 312 | +graph = pathfinding.WeightedGraph() |
| 313 | +graph.edges = edges |
| 314 | +graph.reset_search() |
| 315 | +if part_to_test == 1: |
| 316 | + graph.dijkstra(("@", "")) |
| 317 | +else: |
| 318 | + graph.dijkstra(("1234", "")) |
| 319 | + |
| 320 | +puzzle_actual_result = min( |
| 321 | + [ |
| 322 | + graph.distance_from_start[x] |
| 323 | + for x in graph.distance_from_start |
| 324 | + if len(x[1]) == nb_keys |
| 325 | + ] |
| 326 | +) |
| 327 | + |
| 328 | + |
| 329 | +# -------------------------------- Outputs / results --------------------------------- # |
| 330 | + |
| 331 | +print("Expected result : " + str(puzzle_expected_result)) |
| 332 | +print("Actual result : " + str(puzzle_actual_result)) |
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