Update day 15.
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@ -4,8 +4,72 @@ import sys
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import numpy as np
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import numpy as np
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import parse
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import parse
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def part1(sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], row: int) -> int:
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no_beacons_row_l: list[np.ndarray] = []
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for (sx, sy), (bx, by) in sensor_to_beacon.items():
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d = abs(sx - bx) + abs(sy - by) # closest
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no_beacons_row_l.append(sx - np.arange(0, d - abs(sy - row) + 1))
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no_beacons_row_l.append(sx + np.arange(0, d - abs(sy - row) + 1))
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beacons_at_row = set(bx for (bx, by) in sensor_to_beacon.values() if by == row)
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no_beacons_row = set(np.concatenate(no_beacons_row_l)).difference(beacons_at_row)
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return len(no_beacons_row)
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def part2_intervals(
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sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], xy_max: int
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) -> tuple[int, int, int]:
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from tqdm import trange
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for y in trange(xy_max + 1):
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its: list[tuple[int, int]] = []
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for (sx, sy), (bx, by) in sensor_to_beacon.items():
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d = abs(sx - bx) + abs(sy - by)
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dx = d - abs(sy - y)
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if dx >= 0:
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its.append((max(0, sx - dx), min(sx + dx, xy_max)))
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its = sorted(its)
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s, e = its[0]
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for si, ei in its[1:]:
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if si > e + 1:
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return si - 1, y, 4_000_000 * (si - 1) + y
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if ei > e:
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e = ei
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return (0, 0, 0)
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def part2_cplex(
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sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], xy_max: int
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) -> tuple[int, int, int]:
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from docplex.mp.model import Model
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from docplex.mp.model import Model
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m = Model()
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x, y = m.continuous_var_list(2, ub=xy_max, name=["x", "y"])
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for (sx, sy), (bx, by) in sensor_to_beacon.items():
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d = abs(sx - bx) + abs(sy - by)
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m.add_constraint(m.abs(x - sx) + m.abs(y - sy) >= d + 1, ctname=f"ct_{sx}_{sy}")
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m.set_objective("min", x + y)
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s = m.solve()
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vx = int(s.get_value(x))
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vy = int(s.get_value(y))
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return vx, vy, 4_000_000 * vx + vy
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lines = sys.stdin.read().splitlines()
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lines = sys.stdin.read().splitlines()
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sensor_to_beacon: dict[tuple[int, int], tuple[int, int]] = {}
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sensor_to_beacon: dict[tuple[int, int], tuple[int, int]] = {}
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@ -19,33 +83,8 @@ for line in lines:
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xy_max = 4_000_000 if max(sensor_to_beacon) > (1_000, 0) else 20
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xy_max = 4_000_000 if max(sensor_to_beacon) > (1_000, 0) else 20
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row = 2_000_000 if max(sensor_to_beacon) > (1_000, 0) else 10
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row = 2_000_000 if max(sensor_to_beacon) > (1_000, 0) else 10
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no_beacons_row_l: list[np.ndarray] = []
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print(f"answer 1 is {part1(sensor_to_beacon, row)}")
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for (sx, sy), (bx, by) in sensor_to_beacon.items():
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# x, y, a2 = part2_cplex(sensor_to_beacon, xy_max)
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d = abs(sx - bx) + abs(sy - by) # closest
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x, y, a2 = part2_intervals(sensor_to_beacon, xy_max)
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print(f"answer 2 is {a2} (x={x}, y={y})")
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no_beacons_row_l.append(sx - np.arange(0, d - abs(sy - row) + 1))
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no_beacons_row_l.append(sx + np.arange(0, d - abs(sy - row) + 1))
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beacons_at_row = set(bx for (bx, by) in sensor_to_beacon.values() if by == row)
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no_beacons_row = set(np.concatenate(no_beacons_row_l)).difference(beacons_at_row)
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print(f"answer 1 is {len(no_beacons_row)}")
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# === part 2 ===
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m = Model()
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x, y = m.continuous_var_list(2, ub=xy_max, name=["x", "y"])
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for (sx, sy), (bx, by) in sensor_to_beacon.items():
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d = abs(sx - bx) + abs(sy - by)
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m.add_constraint(m.abs(x - sx) + m.abs(y - sy) >= d + 1, ctname=f"ct_{sx}_{sy}")
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m.set_objective("min", x + y)
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s = m.solve()
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# 10621647166538
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answer_2 = 4_000_000 * int(s.get_value(x)) + int(s.get_value(y))
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print(f"answer 2 is {answer_2}")
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