Compare commits
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2d196f9c52
Author | SHA1 | Date | |
---|---|---|---|
Bruno BELANYI | 2d196f9c52 | ||
Bruno BELANYI | 626bc0f2af | ||
Bruno BELANYI | d492bcb109 | ||
Bruno BELANYI | 041cd69d18 |
107
2024/d20/ex1/ex1.py
Executable file
107
2024/d20/ex1/ex1.py
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#!/usr/bin/env python
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import itertools
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import sys
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from collections.abc import Iterator
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from typing import NamedTuple
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class Point(NamedTuple):
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x: int
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y: int
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def neighbours(self) -> Iterator["Point"]:
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for dx, dy in (
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(-1, 0),
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(1, 0),
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(0, -1),
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(0, 1),
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):
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yield Point(self.x + dx, self.y + dy)
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class ParsedMap(NamedTuple):
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start: Point
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end: Point
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tracks: set[Point]
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MIN_SAVE = 100
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def solve(input: str) -> int:
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def parse(input: list[str]) -> ParsedMap:
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start: Point | None = None
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end: Point | None = None
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tracks: set[Point] = set()
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for x, line in enumerate(input):
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for y, c in enumerate(line):
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if c == "#":
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continue
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p = Point(x, y)
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if c == "S":
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start = p
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elif c == "E":
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end = p
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tracks.add(p)
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assert start is not None and end is not None # Sanity check
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return ParsedMap(start, end, tracks)
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def flood_distance(start: Point, points: set[Point]) -> dict[Point, int]:
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res = {start: 0}
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queue = {start}
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while queue:
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p = queue.pop()
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dist = res[p]
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for n in p.neighbours():
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if n in res:
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continue
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if n not in points:
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continue
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res[n] = dist + 1
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queue.add(n)
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return res
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def dist(a: Point, b: Point) -> int:
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return abs(a.x - b.x) + abs(a.y - b.y)
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def disk(p: Point, radius: int) -> Iterator[Point]:
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for dx, dy in itertools.product(range(-radius, radius + 1), repeat=2):
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n = Point(p.x + dx, p.y + dy)
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if dist(p, n) > radius:
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continue
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yield n
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def find_cheats(start: Point, end: Point, tracks: set[Point]) -> int:
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start_dist = flood_distance(start, tracks)
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end_dist = flood_distance(end, tracks)
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assert start_dist[end] == end_dist[start]
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fastest = start_dist[end]
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res = 0
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for a in tracks:
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for b in disk(a, 2):
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if b not in tracks:
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continue
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time = start_dist[a] + dist(a, b) + end_dist[b]
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if (fastest - time) < MIN_SAVE:
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continue
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res += 1
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return res
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start, end, tracks = parse(input.splitlines())
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return find_cheats(start, end, tracks)
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def main() -> None:
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input = sys.stdin.read()
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print(solve(input))
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if __name__ == "__main__":
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main()
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2024/d20/ex1/input
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141
2024/d20/ex1/input
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#############################################################################################################################################
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#...#.#.#...........#...#.#...#.......#...#...#.....#...#.#.#...#...#.....###...#.#...#.#.#...#...#.#...............#.#.#.#...........#.....#
|
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|
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|
||||
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#...#...###.....#.......#.....###...###.......###...#...............#.........###.......#...#...#...#.......#...#...#.........#...#.........#
|
||||
#############################################################################################################################################
|
107
2024/d20/ex2/ex2.py
Executable file
107
2024/d20/ex2/ex2.py
Executable file
|
@ -0,0 +1,107 @@
|
|||
#!/usr/bin/env python
|
||||
|
||||
import itertools
|
||||
import sys
|
||||
from collections.abc import Iterator
|
||||
from typing import NamedTuple
|
||||
|
||||
|
||||
class Point(NamedTuple):
|
||||
x: int
|
||||
y: int
|
||||
|
||||
def neighbours(self) -> Iterator["Point"]:
|
||||
for dx, dy in (
|
||||
(-1, 0),
|
||||
(1, 0),
|
||||
(0, -1),
|
||||
(0, 1),
|
||||
):
|
||||
yield Point(self.x + dx, self.y + dy)
|
||||
|
||||
|
||||
class ParsedMap(NamedTuple):
|
||||
start: Point
|
||||
end: Point
|
||||
tracks: set[Point]
|
||||
|
||||
|
||||
MIN_SAVE = 100
|
||||
|
||||
|
||||
def solve(input: str) -> int:
|
||||
def parse(input: list[str]) -> ParsedMap:
|
||||
start: Point | None = None
|
||||
end: Point | None = None
|
||||
tracks: set[Point] = set()
|
||||
|
||||
for x, line in enumerate(input):
|
||||
for y, c in enumerate(line):
|
||||
if c == "#":
|
||||
continue
|
||||
p = Point(x, y)
|
||||
if c == "S":
|
||||
start = p
|
||||
elif c == "E":
|
||||
end = p
|
||||
tracks.add(p)
|
||||
|
||||
assert start is not None and end is not None # Sanity check
|
||||
return ParsedMap(start, end, tracks)
|
||||
|
||||
def flood_distance(start: Point, points: set[Point]) -> dict[Point, int]:
|
||||
res = {start: 0}
|
||||
queue = {start}
|
||||
|
||||
while queue:
|
||||
p = queue.pop()
|
||||
dist = res[p]
|
||||
for n in p.neighbours():
|
||||
if n in res:
|
||||
continue
|
||||
if n not in points:
|
||||
continue
|
||||
res[n] = dist + 1
|
||||
queue.add(n)
|
||||
|
||||
return res
|
||||
|
||||
def dist(a: Point, b: Point) -> int:
|
||||
return abs(a.x - b.x) + abs(a.y - b.y)
|
||||
|
||||
def disk(p: Point, radius: int) -> Iterator[Point]:
|
||||
for dx, dy in itertools.product(range(-radius, radius + 1), repeat=2):
|
||||
n = Point(p.x + dx, p.y + dy)
|
||||
if dist(p, n) > radius:
|
||||
continue
|
||||
yield n
|
||||
|
||||
def find_cheats(start: Point, end: Point, tracks: set[Point]) -> int:
|
||||
start_dist = flood_distance(start, tracks)
|
||||
end_dist = flood_distance(end, tracks)
|
||||
|
||||
assert start_dist[end] == end_dist[start]
|
||||
fastest = start_dist[end]
|
||||
|
||||
res = 0
|
||||
for a in tracks:
|
||||
for b in disk(a, 20):
|
||||
if b not in tracks:
|
||||
continue
|
||||
time = start_dist[a] + dist(a, b) + end_dist[b]
|
||||
if (fastest - time) < MIN_SAVE:
|
||||
continue
|
||||
res += 1
|
||||
return res
|
||||
|
||||
start, end, tracks = parse(input.splitlines())
|
||||
return find_cheats(start, end, tracks)
|
||||
|
||||
|
||||
def main() -> None:
|
||||
input = sys.stdin.read()
|
||||
print(solve(input))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
141
2024/d20/ex2/input
Normal file
141
2024/d20/ex2/input
Normal file
|
@ -0,0 +1,141 @@
|
|||
#############################################################################################################################################
|
||||
###.................#...............#...#...###.............#.....#...###...###.......#...#.......#...#.....#...#.........#.......#...#.....#
|
||||
###.###############.#.#############.#.#.#.#.###.###########.#.###.#.#.###.#.###.#####.#.#.#.#####.#.#.#.###.#.#.#.#######.#.#####.#.#.#.###.#
|
||||
#...#...#.....#.....#.........#.....#.#...#...#.#...........#.#...#.#.#...#...#.....#.#.#.#.....#.#.#.#...#...#...#...#...#.#.....#.#.#.#...#
|
||||
#.###.#.#.###.#.#############.#.#####.#######.#.#.###########.#.###.#.#.#####.#####.#.#.#.#####.#.#.#.###.#########.#.#.###.#.#####.#.#.#.###
|
||||
#.....#...#...#.#...###.......#.#...#.......#...#.........#...#.#...#.#.....#...#...#.#.#...###.#...#...#.#.........#...###.#.....#.#...#...#
|
||||
###########.###.#.#.###.#######.#.#.#######.#############.#.###.#.###.#####.###.#.###.#.###.###.#######.#.#.###############.#####.#.#######.#
|
||||
###...#...#...#...#...#.......#...#...###...#...#...#.....#...#...#...###...#...#...#.#...#.....#.......#.#...#.............#.....#...#.....#
|
||||
###.#.#.#.###.#######.#######.#######.###.###.#.#.#.#.#######.#####.#####.###.#####.#.###.#######.#######.###.#.#############.#######.#.#####
|
||||
#...#...#.###.#.......#.......#.......#...#...#...#...#...###.....#.#...#...#.#####.#...#.....#...###...#.#...#.#.......#...#.....#...#.#...#
|
||||
#.#######.###.#.#######.#######.#######.###.###########.#.#######.#.#.#.###.#.#####.###.#####.#.#####.#.#.#.###.#.#####.#.#.#####.#.###.#.#.#
|
||||
#.......#.#...#...#...#.......#.#.....#.#...#...#...#...#.....#...#.#.#.....#...#...#...#.....#.#...#.#...#...#.#...###...#.....#.#...#.#.#.#
|
||||
#######.#.#.#####.#.#.#######.#.#.###.#.#.###.#.#.#.#.#######.#.###.#.#########.#.###.###.#####.#.#.#.#######.#.###.###########.#.###.#.#.#.#
|
||||
#...#...#.#.....#...#.........#.#...#.#.#.###.#...#.#.#.......#...#.#.........#.#...#.....#.....#.#.#.....#...#.#...#.....#...#.#.###.#.#.#.#
|
||||
#.#.#.###.#####.###############.###.#.#.#.###.#####.#.#.#########.#.#########.#.###.#######.#####.#.#####.#.###.#.###.###.#.#.#.#.###.#.#.#.#
|
||||
#.#.#...#...###...............#.###.#...#.....#.....#.#.#...#...#.#.###...###.#...#.......#...#...#.......#.....#.....#...#.#.#...#...#...#.#
|
||||
#.#.###.###.#################.#.###.###########.#####.#.#.#.#.#.#.#.###.#.###.###.#######.###.#.#######################.###.#.#####.#######.#
|
||||
#.#...#.#...#...#...#...#.....#.....#.........#.......#...#.#.#...#.#...#...#...#.....#...#...#.....#...................#...#.#...#...#.....#
|
||||
#.###.#.#.###.#.#.#.#.#.#.###########.#######.#############.#.#####.#.#####.###.#####.#.###.#######.#.###################.###.#.#.###.#.#####
|
||||
#...#.#.#...#.#...#.#.#.#.........#...###...#...............#.....#.#.....#.#...#.....#...#.#...#...#...#...#...........#...#...#.#...#.....#
|
||||
###.#.#.###.#.#####.#.#.#########.#.#####.#.#####################.#.#####.#.#.###.#######.#.#.#.#.#####.#.#.#.#########.###.#####.#.#######.#
|
||||
#...#.#...#...#...#...#.......###.#.......#...#.....#...#...###...#.....#.#...#...#.....#.#...#.#...#...#.#.#.#.........#...#.....#.#...#...#
|
||||
#.###.###.#####.#.###########.###.###########.#.###.#.#.#.#.###.#######.#.#####.###.###.#.#####.###.#.###.#.#.#.#########.###.#####.#.#.#.###
|
||||
#...#...#.......#...#.......#.....#...........#...#.#.#...#.#...#.......#.#...#...#...#.#.#.....#...#.###.#.#.#.....#...#.#...#...#.#.#...###
|
||||
###.###.###########.#.#####.#######.#############.#.#.#####.#.###.#######.#.#.###.###.#.#.#.#####.###.###.#.#.#####.#.#.#.#.###.#.#.#.#######
|
||||
###...#.....###...#...#...#.......#.....###.......#.#.#.....#...#.###...#...#...#.#...#...#.#...#...#.#...#...#.....#.#.#.#.....#...#...#...#
|
||||
#####.#####.###.#.#####.#.#######.#####.###.#######.#.#.#######.#.###.#.#######.#.#.#######.#.#.###.#.#.#######.#####.#.#.#############.#.#.#
|
||||
#...#.#.....#...#.#.....#.#...###.....#.....#.......#.#.#.....#.#...#.#...#...#.#.#.......#...#...#.#...#.....#...#...#.#.#...........#...#.#
|
||||
#.#.#.#.#####.###.#.#####.#.#.#######.#######.#######.#.#.###.#.###.#.###.#.#.#.#.#######.#######.#.#####.###.###.#.###.#.#.#########.#####.#
|
||||
#.#...#.#...#...#.#.....#.#.#.#...#...#.......#...###.#.#...#.#...#...#...#.#.#.#.#...#...#.......#...#...###...#...#...#.#.#.......#.#...#.#
|
||||
#.#####.#.#.###.#.#####.#.#.#.#.#.#.###.#######.#.###.#.###.#.###.#####.###.#.#.#.#.#.#.###.#########.#.#######.#####.###.#.#.#####.#.#.#.#.#
|
||||
#.#...#...#.....#.......#...#.#.#.#...#...#...#.#...#.#...#.#.#...#.....#E..#.#.#.#.#.#...#...#...#...#.......#.#...#...#.#.#.#.....#...#.#.#
|
||||
#.#.#.#######################.#.#.###.###.#.#.#.###.#.###.#.#.#.###.#########.#.#.#.#.###.###.#.#.#.#########.#.#.#.###.#.#.#.#.#########.#.#
|
||||
#.#.#.......................#...#.###.#...#.#.#.#...#...#.#.#.#.#...#...#####.#.#.#.#.###.#...#.#.#...#.......#.#.#...#...#...#.....#...#...#
|
||||
#.#.#######################.#####.###.#.###.#.#.#.#####.#.#.#.#.#.###.#.#####.#.#.#.#.###.#.###.#.###.#.#######.#.###.#############.#.#.#####
|
||||
#.#.#.....................#...#...#...#.#...#.#.#.#...#.#.#.#.#.#...#.#...###.#.#.#.#...#.#...#.#.#...#...#...#...###...............#.#.....#
|
||||
#.#.#.###################.###.#.###.###.#.###.#.#.#.#.#.#.#.#.#.###.#.###.###.#.#.#.###.#.###.#.#.#.#####.#.#.#######################.#####.#
|
||||
#.#.#.........#...#.....#.....#...#.#...#...#.#.#.#.#...#.#.#.#.#...#.#...###.#.#...###.#...#.#.#.#.#...#...#.....#...................#...#.#
|
||||
#.#.#########.#.#.#.###.#########.#.#.#####.#.#.#.#.#####.#.#.#.#.###.#.#####.#.#######.###.#.#.#.#.#.#.#########.#.###################.#.#.#
|
||||
#...#.........#.#...###.........#...#.....#.#.#.#.#.###...#.#...#.#...#.#####.#.......#.....#...#.#.#.#...........#.....#.......#...#...#...#
|
||||
#####.#########.###############.#########.#.#.#.#.#.###.###.#####.#.###.#####.#######.###########.#.#.#################.#.#####.#.#.#.#######
|
||||
#...#...........###.............#.......#...#...#.#...#.#...#...#.#.#...#####...#...#...........#...#.........#...###...#.....#...#...#...###
|
||||
#.#.###############.#############.#####.#########.###.#.#.###.#.#.#.#.#########.#.#.###########.#############.#.#.###.#######.#########.#.###
|
||||
#.#.......#...###...#.............#...#.......#...#...#.#.....#.#...#.#...#####.#.#...#...#...#.###...###...#...#...#...#.....#...###...#...#
|
||||
#.#######.#.#.###.###.#############.#.#######.#.###.###.#######.#####.#.#.#####.#.###.#.#.#.#.#.###.#.###.#.#######.###.#.#####.#.###.#####.#
|
||||
#.......#...#.....#...#.............#.#.......#...#...#...#...#.#.....#.#.#####.#...#.#.#...#.#.#...#.....#.......#.....#...#...#...#...#...#
|
||||
#######.###########.###.#############.#.#########.###.###.#.#.#.#.#####.#.#####.###.#.#.#####.#.#.###############.#########.#.#####.###.#.###
|
||||
#.......#...#.....#.#...#.......#...#...#...#####.....#...#.#.#.#.....#.#...###...#.#...#...#...#...............#.#...#.....#.....#.....#...#
|
||||
#.#######.#.#.###.#.#.###.#####.#.#.#####.#.###########.###.#.#.#####.#.###.#####.#.#####.#.###################.#.#.#.#.#########.#########.#
|
||||
#.....#...#...###...#.....#...#...#.#...#.#...###...###.....#.#.#.....#.#...#####...#.....#.#...#...............#...#.#.........#.#.....#...#
|
||||
#####.#.###################.#.#####.#.#.#.###.###.#.#########.#.#.#####.#.###########.#####.#.#.#.###################.#########.#.#.###.#.###
|
||||
#.....#.#...............#...#...#...#.#.#.#...#...#.......###.#.#...#...#.#...###S..#.....#.#.#.#.........#...#...###...........#.#.###...###
|
||||
#.#####.#.#############.#.#####.#.###.#.#.#.###.#########.###.#.###.#.###.#.#.#####.#####.#.#.#.#########.#.#.#.#.###############.#.#########
|
||||
#.....#.#...#.........#.#.....#.#.....#...#.....#...#...#...#.#...#.#...#...#...#...#.....#.#.#.#...#...#...#...#...#.........#...#...#.....#
|
||||
#####.#.###.#.#######.#.#####.#.#################.#.#.#.###.#.###.#.###.#######.#.###.#####.#.#.#.#.#.#.###########.#.#######.#.#####.#.###.#
|
||||
#...#...###...#...#...#.......#...........#...#...#.#.#.#...#.#...#.#...#.......#.###.#...#...#...#...#.............#.#.......#...#...#.#...#
|
||||
#.#.###########.#.#.#####################.#.#.#.###.#.#.#.###.#.###.#.###.#######.###.#.#.###########################.#.#########.#.###.#.###
|
||||
#.#.#...#...###.#.#.........#...#.......#...#...###...#...###...###.#...#...#...#...#.#.#...#...#.....#.........#...#.#...........#.....#...#
|
||||
#.#.#.#.#.#.###.#.#########.#.#.#.#####.###########################.###.###.#.#.###.#.#.###.#.#.#.###.#.#######.#.#.#.#####################.#
|
||||
#.#...#...#.....#.........#.#.#...#...#.#...........#.........#...#...#...#...#.#...#.#.#...#.#.#.###...#.......#.#...#...#...#.....#...#...#
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#############################################################################################################################################
|
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Reference in a new issue