dom/python
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

fix clockwise_twist

Browse Source
This commit is contained in:
DomNomNomVR 2025-04-15 10:46:18 +12:00
parent 5b972eb737
commit 8613d67ea6
1 changed files with 30 additions and 62 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

92
skewb_solver.py
View File

@ -275,7 +275,10 @@ def instructions(twists: list[Axis]) -> str:
def breadth_first_search( def breadth_first_search(
start: Skewb, is_end: Callable[[Skewb], bool], max_steps: int = 2000000 start: Skewb,
is_end: Callable[[Skewb], bool],
max_steps: int = 2000000,
bidirectional_fallback_threshold: int | None = None,
) -> list[Twist] | None: ) -> list[Twist] | None:
start.assert_valid() start.assert_valid()
if is_end(start): if is_end(start):
@ -293,10 +296,16 @@ def breadth_first_search(
out.reverse() out.reverse()
return out return out
step_count = 0
while q and max_steps > 0: while q and max_steps > 0:
max_steps -= 1 if max_steps % 1000 == 0 and step_count:
if max_steps % 1000 == 0:
print(".", end="", flush=True) print(".", end="", flush=True)
if (
bidirectional_fallback_threshold is not None
and step_count > bidirectional_fallback_threshold
):
return bidirectional_search(start, max_steps)
step_count += 1
parent = q.popleft() parent = q.popleft()
for twist in TWISTS: for twist in TWISTS:
@ -534,13 +543,15 @@ def get_paths_from_heuristic(
assert len(matches) == len(mask) assert len(matches) == len(mask)
return all(match >= m for match, m in zip(matches, mask)) return all(match >= m for match, m in zip(matches, mask))
print(f"{mask=} {s=}", end=" ")
if heuristic_i == len(heuristic_permutation) - 3: if heuristic_i == len(heuristic_permutation) - 3:
# print("going bidirectional now.") # print("going bidirectional now.")
path = bidirectional_search(s, max_steps=200000) path = bidirectional_search(s, max_steps=200000)
else: else:
path = breadth_first_search(s, step_finished) path = breadth_first_search(
# print() s, step_finished, bidirectional_fallback_threshold=20000
print(f"{mask=} {s=} {path=}") )
print(f" {path=}")
if path is None: if path is None:
raise ValueError("oh no! solver could not find solution") raise ValueError("oh no! solver could not find solution")
out.append(path) out.append(path)
@ -565,26 +576,21 @@ def quadratic_mean(values: list[float]) -> float:
return sqrt(sum(x * x for x in values) / len(values)) return sqrt(sum(x * x for x in values) / len(values))
def get_mean_path_length( def score_fn(values: list[float]) -> float:
start: Skewb, return -sum(2**i * v for i, v in enumerate(sorted(values)))
heuristic_permutation: list[int],
mean_fn: Callable[[list[float]], float] = quadratic_mean,
) -> float:
return mean_fn(
[len(p) for p in get_paths_from_heuristic(start, heuristic_permutation)]
)
@shelve_it("skewb_solver.evaluate_permutation.shelve.sqlite") @shelve_it("skewb_solver.evaluate_permutation.shelve.sqlite")
def evaluate_permutation( def evaluate_permutation(
heuristic_permutation: list[int], seed=4, sample_size: int = 10 heuristic_permutation: list[int], seed=4, sample_size: int = 10
) -> float: ) -> float:
pls = [] scores = []
for i in range(sample_size): for i in range(sample_size):
pl = get_mean_path_length(random_skewb(seed=i + seed), heuristic_permutation) paths = get_paths_from_heuristic(start, heuristic_permutation)
print(f"{pl=}") score = score_fn([len(p) for p in paths])
pls.append(pl) print(f"{score=}")
return sum(pls) / len(pls) scores.append(score)
return sum(scores) / len(scores)
def evaluate_all_1_swaps(hp: list[int]): def evaluate_all_1_swaps(hp: list[int]):
@ -605,49 +611,11 @@ def evaluate_all_1_swaps_except_first(hp: list[int]):
if __name__ == "__main__": if __name__ == "__main__":
# print(bidirectional_search(start, max_steps=20000000, end=solved_skewb)) hp = top_bot_mids = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
# print(breadth_first_search(start=start, is_end=lambda s: s == solved_skewb))
# hp = list(range(HURISTIC_PERMUTATION_LENGTH))
hp = top_down = [0, 1, 2, 3, 8, 9, 10, 11, 12, 4, 5, 6, 7] hp = top_down = [0, 1, 2, 3, 8, 9, 10, 11, 12, 4, 5, 6, 7]
# hp = small_corner_start = [0, 8, 11, 1, 2, 3, 9, 10, 12, 4, 5, 6, 7]
# hp = big_corner_start = [4, 0, 8, 11, 5, 7, 1, 2, 3, 9, 10, 12, 6]
# print(f"{evaluate_permutation(hp, sample_size=22)=}")
# evaluate_all_1_swaps(top_down) # evaluate_all_1_swaps(top_down)
# print( evaluate_all_1_swaps_except_first(hp)
# f"{(hp := [10, 1, 2, 3, 8, 9, 0, 11, 12, 4, 5, 6, 7])} {evaluate_permutation(hp, sample_size=100)=}"
# )
# print(
# f"{(hp := [0, 10, 2, 3, 8, 9, 1, 11, 12, 4, 5, 6, 7])} {evaluate_permutation(hp, sample_size=100)=}"
# )
# print(
# f"{(hp := [0, 1, 10, 3, 8, 9, 2, 11, 12, 4, 5, 6, 7])} {evaluate_permutation(hp, sample_size=100)=}"
# )
# print(
# f"{(hp := [0, 1, 2, 10, 8, 9, 3, 11, 12, 4, 5, 6, 7])} {evaluate_permutation(hp, sample_size=100)=}"
# )
# print(
# f"{(hp := [0, 1, 2, 3, 10, 9, 8, 11, 12, 4, 5, 6, 7])} {evaluate_permutation(hp, sample_size=100)=}"
# )
# hp = [10, 1, 2, 3, 8, 9, 0, 11, 12, 4, 5, 6, 7]
# print(f"{hp=} {evaluate_permutation(hp, seed=200, sample_size=200)=}")
# print(f"{hp=} {evaluate_permutation(hp, seed=200, sample_size=200)=}")
# evaluate_all_1_swaps_except_first(hp)
# hp = [10, 11, 2, 3, 8, 9, 0, 1, 12, 4, 5, 6, 7]
# print(f"{hp=} {evaluate_permutation(hp, seed=200, sample_size=200)=}")
# hp = [10, 11, 2, 3, 8, 9, 0, 1, 12, 4, 5, 6, 7]
# print(f"{hp=} {evaluate_permutation(hp, seed=200, sample_size=200)=}")
hp = [10, 0, 1, 2, 3, 8, 9, 11, 12, 4, 5, 6, 7] start = Skewb((G0, O0, B0, R0), (G0, R1, B2, O2), (BY, OY, RO, GR, YY))
print( # print(bidirectional_search(start, max_steps=1000000))
bidirectional_search( # print(get_paths_from_heuristic(start, hp))
Skewb(
top=(G0, O0, B0, R0), bot=(B1, O1, G2, R1), mids=(OO, YY, RO, GR, BO)
),
max_steps=1000000,
)
)
# path = get_paths_from_heuristic(
# Skewb(top=(G0, O0, B0, R0), bot=(B1, O1, G2, R1), mids=(OR, YY, RO, GR, BO)),
# hp,
# )
# RBOG