def __init__(self, robot_move_strategy, topics):
# type: (ExploreMoveStrategy, List[dict]) -> None
self.robot_move_strategy = robot_move_strategy
self.topic_identifiers = lmap(lambda topic: topic['identifier'],
topics)
self.topics_values = lmap(lambda topic: topic['explore'], topics)
self.continue_enabled = all(
map(lambda topic: topic['explore'].get('continue', False), topics))
self.publishers_types = lmap(
lambda topic: dynamic_import(topic['type']), topics)
self.publishers = lmap(
lambda topic: rospy.Publisher(topic[1]['identifier'],
self.publishers_types[topic[0]],
queue_size=1), enumerate(topics))
self.responders = lmap(lambda topic: self.get_responder(topic), topics)
def p1(inp):
grid = np.array(lmap(list, inp.strip().splitlines()))
pos = np.array(np.where(grid == "@"))[:, 0]
grid[tuple(pos)] = "."
allkeys = set(list(re.sub(r"[^a-z]", "", inp)))
# print(allkeys)
# if DISPLAY:
# import pygame as pg
# pg.init()
# screen = pg.display.set_mode((grid.shape[0] * SCALE, grid.shape[1] * SCALE))
# gridsurf = pg.surface.Surface(grid.shape)
# def display():
# for ev in pg.event.get():
# if ev.type == pg.QUIT:
# sys.exit(0)
# pg.surfarray.blit_array(gridsurf, grid)
# pg.draw.circle(gridsurf, POS, tuple(pos), 0)
# pg.transform.scale(
# gridsurf, (grid.shape[0] * SCALE, grid.shape[1] * SCALE), screen
# )
# pg.display.flip()
return dijkstra(grid, allkeys, tuple(pos))
def parse(s):
def parseIng(x):
q, c = x.split(" ")
return (int(q), c)
ret = [lmap(lambda x: parseIng(x.strip()), re.split(r"=>|,", l)) for l in s.splitlines()]
return [(l[:-1], l[-1]) for l in ret]
def main():
inp = data_lines_nums()
# inp = [[-1, 0, 2], [2, -10, -7], [4, -8, 8], [3, 5, -1]]
# inp = [[-8, -10, 0], [5, 5, 10], [2, -7, 3], [9, -8, -3]]
inp = lmap(list, zip(inp, [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]))
inp = np.array(inp)
print(f"Solution for part 1:\n{p1(inp)}")
print(f"Solution for part 2:\n{p2(inp)}")
def p1(inp, debug=False):
scaffolds = ''.join(
map(chr,
IntComputer(inp, name="ASCII", debug=debug).run()))
scaffolds = np.array(lmap(list, scaffolds.strip().splitlines()))
psum = 0
for x in range(1, scaffolds.shape[0] - 1):
for y in range(1, scaffolds.shape[1] - 1):
if scaffolds[x, y] == '#' and scaffolds[
x + 1,
y] == '#' and scaffolds[x, y + 1] == '#' and scaffolds[
x - 1, y] == '#' and scaffolds[x, y - 1] == '#':
psum += x * y
return psum
def find_new_path(self):
rospy.loginfo("Finding new path")
if not self.actions:
self.current_path = [self.state]
return
backtrace = []
new_states = lmap(
lambda actions: tuple(
action.to_state(self.state) for action in actions),
self.actions)
combined_possible_states = self.get_combined_possible_new_states(
new_states)
for new_state in combined_possible_states:
if new_state in self.inaccessible or new_state in self.visited:
continue
reward = self.get_reward(new_state)
backtrace.append((reward, new_state, tuple(self.state)))
backtrace.sort(key=lambda pair: pair[0])
self.backtrace += lmap(lambda pair: pair[1:], backtrace)
next_state, source = self.backtrace.pop() if self.backtrace else tuple(
[None, None])
self.find_path(source, next_state)
def move(self, *additional_steps):
steps = self.get_steps(additional_steps)
while True:
states = self.robot_move_strategy.get_next_states()
if not states:
self.log_for_each_topic('is unable to get to next state')
break
responses = lmap(lambda args: self.move_to_state(*args),
enumerate(states))
self.robot_move_strategy.give_feedback(responses)
self.log_for_each_topic(' goal reached?: ', responses)
for step in steps:
threading.Thread(target=step).start()
def __init__(self, **kwargs):
self.state_machine = kwargs['state_machine']
self.model_confs = kwargs['model_confs']
if not self.state_machine:
rospy.logerr("stateMachine not specified in config")
raise RuntimeError("stateMachine not specified in config")
self.state_values = {
int(key): self.state_machine['values'][key]
for key in self.state_machine['values']
}
self.edges = {
int(key): lmap(int, self.state_machine['edges'][key])
for key in self.state_machine['edges']
}
self.edge_labels = {
eval(key): self.state_machine['labels'][key]
for key in self.state_machine['labels']
}
self.timestamps = {
eval(key): self.state_machine['timestamps'][key]
for key in self.state_machine['timestamps']
}
self.initial_state = int(self.state_machine['initialState'])
self.state_machine['values'] = self.state_values
self.state_machine['edges'] = self.edges
self.state_machine['labels'] = self.edge_labels
self.state_machine['timestamps'] = self.timestamps
self.topics = []
self.actions = []
self.action_lens = []
self.visited = set()
self.inaccessible = defaultdict(set)
self.path = []
self.path_cursor = 0
self.prev_state = None
self.state = None
self.next_state = None
self.connecting = False
self.success = True
self.closest_pairs = None
self.going_back = False
self.timestamp = None
async def async_run(self):
"""Start executing instructions until a hlt instruction and return self.out"""
self.out = []
self.input = self.data.copy()
self.mem.fill(0)
self.mem[: self.program.size] = self.program
self.ip = 0
self.rel = 0
while 1:
op = self.mem[self.ip]
modes = lmap(lambda i: op // i % 10, [100, 1000, 10000])
op = op % 100
_, nparams = self.OPCODES[op]
params = list(zip(self.mem[self.ip + 1 : self.ip + 1 + nparams], modes))
self.ip = await self.__operate(op, *params)
if self.ip < 0:
break
return self.out
def run(k, args, xs, conn):
"""
Parameters
----------
k : index of thread
args : struct of all arguments
xs: list of ids (int) of data points
conn : pipe to the main thread
function is run as a thread
iterates though all x in xs and samples errors
and reports them back to the main thread
"""
np.random.seed(1000 * args.seed + k)
data = lmap(itemgetter(0), get_dataset())
a_min = -args.alpha_min_max
a_max = args.alpha_min_max
for i in xs:
path = data[i]
y, sr = librosa.load(path, sr=None)
for _ in range(args.K):
a = np.random.uniform(a_min, a_max)
b = np.random.normal(0, args.beta_std)
diff, spect_diff, l_spect_diff = transform(y, sr, a, b, args)
l1 = np.linalg.norm(diff, ord=1)
l2 = np.linalg.norm(diff, ord=2)
linf = np.linalg.norm(diff, ord=np.inf)
ret = [i, a, b, l1, l2, linf]
s_l1 = np.linalg.norm(np.ravel(spect_diff), ord=1)
s_l2 = np.linalg.norm(np.ravel(spect_diff), ord=2)
s_linf = np.linalg.norm(np.ravel(spect_diff), ord=np.inf)
l_s_l1 = np.linalg.norm(np.ravel(l_spect_diff), ord=1)
l_s_l2 = np.linalg.norm(np.ravel(l_spect_diff), ord=2)
l_s_linf = np.linalg.norm(np.ravel(l_spect_diff), ord=np.inf)
ret.extend([s_l1, s_l2, s_linf, l_s_l1, l_s_l2, l_s_linf])
conn.send(ret)
parser.add_argument('--beta_std',
type=float,
default='0.85',
help='standard deviation for beta')
args = parser.parse_args()
np.random.seed(args.seed)
random.seed(args.seed)
data = get_dataset()
L = len(data)
N = min(L, args.N)
I = list(range(L))
samples = list(random.sample(I, N))
data = lmap(itemgetter(0), get_dataset())
a_min = -args.alpha_min_max
a_max = args.alpha_min_max
arg_tuples = []
for i in samples:
path = data[i]
y, sr = librosa.load(path, sr=None)
a_ = [np.random.uniform(a_min, a_max) for _ in range(args.K)]
betas_ = [
np.random.normal(0, args.beta_std, 100) for _ in range(args.K)
]
arg_tuples.append((args, y, sr, a_, betas_))
with mp.Pool() as pool:
def p2(inp, debug=False):
program = """A,B,A,B,C,B,A,C,B,C
L,12,L,8,R,10,R,10
L,6,L,4,L,12
R,10,L,8,L,4,R,10
n
"""
# Solved by hand; notes:
# ................................#####..............
# ................................#...#..............
# ................................#...#..............
# ................................#...#..............
# ................................#...#..............
# ................................#...#..............
# ..........................###########..............
# ..........................#.....#..................
# ..........................#.....#..................
# ..........................#.....#..................
# ..........................#.....#..................
# ..........................#.....#..................
# ......................###########..................
# ......................#...#........................
# ......................#...#........................
# ......................#...#........................
# ......................#...#########................
# ......................#...........#................
# ..........#...........#...........#................
# ..........#...........#...........#................
# ..........#...........#####.......#................
# ..........#...............#.......#................
# ..........#...............#.......#................
# ..........#...............#.......#................
# ..........#...........#######.....#................
# ..........#...........#...#.#.....#................
# ..........#.........#############.#...#############
# ..........#.........#.#...#.#...#.#...#............
# ..........#####.....#.#############...#............
# ..............#.....#.....#.#...#.....#............
# ..............#.....#.....#######.....#............
# ..............#.....#.......#.........#............
# ..............#.....#.......#.........#............
# ..............#.....#.......#.........#............
# ..............#.....#.......###########............
# ..............#.....#..............................
# ....###########.....#..............................
# ....#...............#..............................
# ....#.....#########.#########......................
# ....#.....#.......#.........#......................
# ....#.....#.......#.........#......................
# ....#.....#.......#.........#......................
# ###########.......#.........#......................
# #...#.............#.........#......................
# #...#.............#.........#......................
# #...#.............#.........#......................
# #...#.............#.........#......................
# #...#.............#.........#......................
# #####.............###########......................
# L,12,L,8,R,10,R,10,L,6,L,4,L,12,L,12,L,8,R,10,R,10,L,6,L,4,L,12,R,10,L,8,L,4,R,10,L,6,L,4,L,12,L,12,L,8,R,10,R,10,R,10,L,8,L,4,R,10,L6,L4,L12,R,10,L,8,L,4,R,10
# LFFFFFFFFFFFFLFFFFFFFFRFFFFFFFFFFRFFFFFFFFFF LFFFFFFLFFFFLFFFFFFFFFFFF LFFFFFFFFFFFFLFFFFFFFFRFFFFFFFFFFRFFFFFFFFFF LFFFFFFLFFFFLFFFFFFFFFFFF RFFFFFFFFFFLFFFFFFFFLFFFFRFFFFFFFFFF LFFFFFFLFFFFLFFFFFFFFFFFF LFFFFFFFFFFFFLFFFFFFFFRFFFFFFFFFFRFFFFFFFFFF RFFFFFFFFFFLFFFFFFFFLFFFFRFFFFFFFFFF LFFFFFFLFFFFLFFFFFFFFFFFF RFFFFFFFFFFLFFFFFFFFLFFFFRFFFFFFFFFF
# L,12,L,8,R,10,R,10
# L,6,L,4,L,12
# R,10,L,8,L,4,R,10
# ABABCBACBC
ret = -1
def write(val):
nonlocal ret
if val < 128:
sys.stdout.write(chr(val))
else:
ret = val
IntComputer("2" + inp[1:],
name="ASCII",
inp=lmap(ord, program),
writef=write,
debug=debug).run()
return ret
def main():
inp = lmap(int, data().strip())
inp = np.array(inp, dtype=np.int8)
print(f"Solution for part 1:\n{p1(inp)}")
print(f"Solution for part 2:\n{p2(inp)}")
