def test_wheel_timer():
task_data = Path(utils.project_root() / 'tasks' / 'part-0-mock' / 'wheels.desc').read_text()
task = GridTask(Task.parse(task_data))
actionlist = ('QQDD' +
'F' +
'ZZZZZZZZZZZZZZZZZZZZ' +
'F' +
'ZZZZZZZZZZZZZZZZZZZZ' +
'ZZZZZZZZZ' +
'ZZZZZZZZZZZZZZZZZZZZ' +
'ZZZZZZZZZZZZZZZZZZZZ' +
'ZZZZZZZZZZ' +
'D')
game = Game(task)
for a in actionlist:
game.apply_action(Action.simple(a))
solution = compose_actions(game.get_actions())
expected_score = game.finished()
assert expected_score is None
game = Game(task)
for a in actionlist:
game.apply_action(Action.simple(a))
game.apply_action(Action.WSAD('D'))
solution = compose_actions(game.get_actions())
expected_score = game.finished()
er = validate.run(task_data, solution)
assert er.time is not None
assert er.time == expected_score
def solve(self, task: str) -> SolverResult:
task = Task.parse(task)
min_score = None
min_actions = []
min_extra = {}
turnlist = [[]]
if self.turns:
turnlist += [[Action.turnCCW()],
[Action.turnCCW(), Action.turnCCW()],
[Action.turnCW()]]
# turnlist = [[Action.turnCW()]]
for turns in turnlist:
game = Game(GridTask(task))
for t in turns:
game.apply_action(t)
expected_score, actions, extra = solve(game, min_score)
if expected_score is None:
# solution has exceeded the best score and stopped
continue
if min_score is None or expected_score < min_score:
min_score, min_actions, min_extra = expected_score, actions, extra
return SolverResult(data=compose_actions(min_actions),
expected_score=min_score,
extra=min_extra)
def run_for_errors(actions: List[Action]):
task_data = Path(utils.project_root() / 'tasks' / 'part-0-mock' / 'prob-2003.desc').read_text()
task = GridTask(Task.parse(task_data))
game = Game(task)
try:
for a in actions:
game.apply_action(a)
except InvalidActionException:
return
else:
assert False
def run_one_bot_game(actions: List[Action]):
task_data = Path(utils.project_root() / 'tasks' / 'part-0-mock' / 'prob-2003.desc').read_text()
task = GridTask(Task.parse(task_data))
game = Game(task)
for a in actions:
game.apply_action(a)
solution = compose_actions(game.get_actions())
expected_score = game.finished()
er = validate.run(task_data, solution)
assert er.time is not None
assert er.time == expected_score
def main():
s = Path(utils.project_root() / 'tasks' / 'part-1-initial' /
'prob-145.desc').read_text()
solver = BoostySolver([])
t = time()
sol = solver.solve(s)
print(f'time elapsed: {time() - t:.4}')
print(sol)
task = Task.parse(s)
score, sol, _ = solve(Game(GridTask(task)))
print("score:", score)
sol = compose_actions(sol)
print(sol)
print(len(sol), 'time units')
sol_path = Path(utils.project_root() / 'outputs' / 'example-01-boosty.sol')
sol_path.write_text(sol)
print('result saved to', sol_path)
def solve(self, task: str) -> SolverResult:
task = Task.parse(task)
min_score = None
# min_actions = []
# min_extra = {}
turnlist = {
'Eastborne': [],
'Nordish': [Action.turnCCW()],
'Westerling': [Action.turnCCW(),
Action.turnCCW()],
'Southerner': [Action.turnCW()]
}
params = {}
params['boostlist'] = 'B'
if self.drill:
params['boostlist'] += 'L'
if self.teleport:
params['boostlist'] += 'R'
params['attach func'] = manip_configs[self.manipconf]
for direction in turnlist:
logger.info(f'{direction} started working')
params['best score'] = min_score
game = Game(GridTask(task))
for t in turnlist[direction]:
game.apply_action(t)
expected_score, actions, extra = solve(game, params)
logger.info(f'{direction} finished with {expected_score} score')
if expected_score is None:
# solution has exceeded the best score and stopped
continue
if min_score is None or expected_score < min_score:
min_score, min_actions, min_extra = expected_score, actions, extra
return SolverResult(data=compose_actions(min_actions),
expected_score=min_score,
extra=min_extra)
def solve(task: Task, max_depth) -> Tuple[int, List[List[Action]], dict]:
task = GridTask(task)
game = Game(task)
while not game.finished():
while game.inventory['B'] > 0:
logger.info('attach extension')
game.apply_action(Action.attach(1, len(game.bots[0].manipulator) - 2))
action = get_action(game, max_depth)
game.apply_action(action)
score = game.finished()
logger.info(game.inventory)
extra = dict(final_manipulators = len(game.bots[0].manipulator))
return score, game.get_actions(), extra
def run_cloned_game(actions: List[List[Action]]):
task_data = Path(utils.project_root() / 'tasks' / 'part-0-mock' / 'prob-2003.desc').read_text()
task = GridTask(Task.parse(task_data))
game = Game(task)
indices = [0] * len(actions)
current = 0
while not game.finished():
if current == 0:
botcount = len(game.bots)
i = indices[current]
game.apply_action(actions[current][i], current)
indices[current] += 1
current = (current + 1) % botcount
solution = compose_actions(game.get_actions())
expected_score = game.finished()
er = validate.run(task_data, solution)
assert er.time is not None
assert er.time == expected_score
def solve(task: Task, max_depth) -> Tuple[int, List[List[Action]], dict]:
task = GridTask(task)
game = Game(task)
st_root = game.bots[0].pos
spanning_tree = calculate_spanning_tree(game, st_root)
target = None
while not game.finished():
while game.inventory['B'] > 0:
logger.info('attach extension')
action = attach_lined(game)
wrap_updates = game.apply_action(action)
for p in wrap_updates:
assert game.is_wrapped(p)
spanning_tree[p].wrap()
bot = game.bots[0]
if target is None:
target = spanning_tree[bot.pos].get_next_unwrapped().pos
distfield = calculate_distance_field(game, target, bot.pos)
#print_distfield(game, distfield)
action = get_action(game, max_depth, distfield, target)
assert action
wrap_updates = game.apply_action(action)
for p in wrap_updates:
assert game.is_wrapped(p)
spanning_tree[p].wrap()
if game.is_wrapped(target):
target = None
score = game.finished()
logger.info(game.inventory)
extra = dict(final_manipulators=len(game.bots[0].manipulator))
return score, game.get_actions(), extra
def solve(self, task: str) -> SolverResult:
task = Task.parse(task)
task = GridTask(task)
game = Game(task)
if not game.clone_spawn:
return SolverResult(data=Pass(),
expected_score=None,
extra=dict(reason='no clone spawns'))
if not game.inventory['C'] and not game.map_contains_booster('C'):
return SolverResult(data=Pass(),
expected_score=None,
extra=dict(reason='no clone boosters'))
cnt = 0
while not game.finished():
cnt += 1
if cnt % 200 == 0:
logging.info(
f'{len(game.bots)} bots; {game.remaining_unwrapped} unwrapped'
)
used_bots = [False for bot in game.bots]
actions = [None for bot in game.bots]
orig_bots = game.bots[:]
if game.clone_spawn and game.inventory['C']:
logging.info('need spawn')
df = DistanceField(game.grid)
df.build(game.clone_spawn)
dist = df.dist
best_rank = 1e10
best_bot = None
best_action = None
for bot_index, bot in enumerate(orig_bots):
if dist[bot.pos] == 0:
continue
for d, a in Action.DIRS.items():
p = bot.pos + d
if not game.grid.in_bounds(p):
continue
rank = dist[p]
if rank < best_rank:
best_rank = rank
best_bot = bot_index
best_action = a
#assert best_bot is not None
#game.apply_action(best_action, best_bot)
if best_bot is not None:
actions[best_bot] = best_action
used_bots[best_bot] = True
boosters = [b.pos for b in game.boosters if b.code == 'C']
if not game.finished() and game.clone_spawn and not game.inventory[
'C'] and boosters and not all(used_bots):
df = DistanceField(game.grid)
df.build(boosters)
dist = df.dist
best_rank = 1e10
best_bot = None
best_action = None
for bot_index, bot in enumerate(orig_bots):
if used_bots[bot_index]:
continue
for d, a in Action.DIRS.items():
p = bot.pos + d
if not game.grid.in_bounds(p):
continue
rank = dist[p]
if rank < best_rank:
best_rank = rank
best_bot = bot_index
best_action = a
assert best_bot is not None
actions[best_bot] = best_action
used_bots[best_bot] = True
if game.finished():
break
df = DistanceField(game.grid)
starts = list_unwrapped(game._wrapped)
df.build(starts)
dist = df.dist
for bot_index, bot in enumerate(orig_bots):
if game.finished():
break
if used_bots[bot_index]:
game.apply_action(actions[bot_index], bot_index)
continue
if game.inventory['C'] and bot.pos in game.clone_spawn:
game.apply_action(Action.clone(), bot_index)
logging.info('clone!!!')
continue
if game.inventory['B'] > 0:
logger.info('attach extension')
game.apply_action(
Action.attach(1,
len(game.bots[0].manipulator) - 2))
continue
best_rank = 1e10
best_action = None
for d, a in Action.DIRS.items():
p = bot.pos + d
if not game.grid.in_bounds(p):
continue
rank = dist[p]
for j, bot2 in enumerate(orig_bots):
if j < bot_index:
d = bot.pos.manhattan_dist(bot2.pos)
rank += 10 * max(0, 30 - d)
if rank < best_rank:
best_rank = rank
best_action = a
assert best_action is not None
game.apply_action(best_action, bot_index)
expected_score = score = game.finished()
extra = dict(final_bots=len(game.bots))
return SolverResult(data=compose_actions(game.get_actions()),
expected_score=expected_score,
extra=extra)
def solve(task: Task,
turns: str,
bestscore=None) -> Tuple[Optional[int], List[List[Action]], dict]:
task = GridTask(task)
game = Game(task)
cnt = 0
for t in turns:
game.apply_action(Action.simple(t))
while not game.finished():
cnt += 1
if cnt % 1000 == 0:
logging.info(f'{game.remaining_unwrapped} unwrapped')
extensions = {b.pos for b in game.boosters if b.code == 'B'}
prev = {game.bots[0].pos: None}
frontier = [game.bots[0].pos]
while frontier:
best_rank = 0
dst = None
for p in frontier:
rank = 0
if p in extensions:
rank += 5
rank += len(
manipulators_will_wrap(game.grid, game._wrapped, p,
game.bots[0].manipulator))
if rank > best_rank:
best_rank = rank
dst = p
if dst is not None:
break
new_frontier = []
for p in frontier:
for d in Action.DIRS.keys():
p2 = p + d
if (p2 not in prev and game.in_bounds(p2)
and game.grid[p2] == '.'):
prev[p2] = p
new_frontier.append(p2)
frontier = new_frontier
assert dst is not None
assert dst != game.bots[0].pos
path = []
p = dst
while p != game.bots[0].pos:
d = p - prev[p]
path.append(Action.DIRS[d])
p = prev[p]
assert p is not None
path.reverse()
for a in path:
game.apply_action(a)
if bestscore is not None and game.turn >= bestscore:
return None, [], {}
if game.inventory['B'] > 0:
logger.info('attach extension')
attach_to = Pt(1, len(game.bots[0].manipulator) - 2)
for t in turns:
attach_to = turn_pt(attach_to, t)
game.apply_action(Action.attach(attach_to.x, attach_to.y))
score = game.finished()
logger.info(game.inventory)
extra = dict(final_manipulators=len(game.bots[0].manipulator))
return score, game.get_actions(), extra
def interactive(task_number):
task_data = utils.get_problem_raw(task_number)
use_db = task_number <= 999
if use_db:
conn = db.get_conn()
cur = conn.cursor()
cur.execute(
'''
SELECT id, data FROM tasks WHERE name = %s
''', [f'prob-{task_number:03d}'])
[task_id, task_data_db] = cur.fetchone()
task_data_db = zlib.decompress(task_data_db).decode()
assert task_data_db == task_data
task = GridTask(Task.parse(task_data))
game = Game(task)
score = None
with contextlib.closing(Display(game)) as display:
code, c = '', ''
display.draw_initial(game)
while not score:
display.draw(game, f'lastchar = {code} {c!r}')
code = display.stdscr.getch()
action = None
c = chr(code).upper()
if c in '\x1B':
break
if c in Action.SIMPLE:
action = Action.simple(c)
# to perform complex action type it without spaces: B(1,-1)
elif c in Action.PARAM:
while c[-1] != ')':
code = display.stdscr.getch()
c = c + chr(code).upper()
action = Action.parameterized(c)
if display.current == 0:
botcount = len(game.bots)
if action:
try:
game.apply_action(action, display.current)
except InvalidActionException as exc:
display.draw_error(str(exc))
else:
display.current = (display.current + 1) % botcount
score = game.finished()
if score is not None:
print(f'Score: {score}')
result = validate_replay(task_data, score, game.get_actions())
print(result)
if use_db:
submit_replay(conn, task_id, result)
else:
mock_solutions = utils.project_root(
) / 'outputs' / 'mock_solutions'
mock_solutions.mkdir(parents=True, exist_ok=True)
with mock_solutions / f'prob-{task_number}.sol' as fin:
fin.write_text(result.solution)
def solve(task: Task) -> Tuple[int, List[List[Action]], dict]:
task = GridTask(task)
game = Game(task)
cnt = 0
while not game.finished():
cnt += 1
if cnt % 1000 == 0:
logging.info(f'{game.remaining_unwrapped} unwrapped')
prev = {game.bots[0].pos: None}
frontier = [game.bots[0].pos]
while frontier:
best_rank = 0
dst = None
for p in frontier:
rank = len(
manipulators_will_wrap(game.grid, game._wrapped, p,
game.bots[0].manipulator))
if rank > best_rank:
best_rank = rank
dst = p
if dst is not None:
break
new_frontier = []
for p in frontier:
for d in Action.DIRS.keys():
p2 = p + d
if (p2 not in prev and game.in_bounds(p2)
and game.grid[p2] == '.'):
prev[p2] = p
new_frontier.append(p2)
frontier = new_frontier
assert dst is not None
assert dst != game.bots[0].pos
path = []
p = dst
while p != game.bots[0].pos:
d = p - prev[p]
path.append(Action.DIRS[d])
p = prev[p]
assert p is not None
path.reverse()
for a in path:
game.apply_action(a)
if game.inventory['B'] > 0:
logger.info('attach extension')
game.apply_action(
Action.attach(1,
len(game.bots[0].manipulator) - 2))
score = game.finished()
logger.info(game.inventory)
extra = dict(final_manipulators=len(game.bots[0].manipulator))
return score, game.get_actions(), extra
