52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
import numpy as np
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from day11.common import char_to_int
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seats = np.array([[char_to_int(x) for x in line.strip()] for line in open("input.txt")], dtype=np.byte)
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neighbors = np.zeros_like(seats, dtype=np.byte)
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next_neighbors = np.zeros_like(seats, dtype=np.byte)
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RAYS = [(1, 0), (-1, 1), (0, 1), (1, 1)]
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occupied = -1
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def find_neighbor(idx, ray):
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idx = tuple(map(sum, zip(idx, ray)))
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while 0 <= idx[0] < seats.shape[0] and 0 <= idx[1] < seats.shape[1]:
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if seats[idx] == -1:
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return 0, idx
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elif seats[idx] == 0:
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idx = tuple(map(sum, zip(idx, ray)))
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continue
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else:
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return 1, idx
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else:
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return None
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while True:
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new_occupied = np.count_nonzero(seats == 1)
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if occupied == new_occupied:
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break
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occupied = new_occupied
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result = np.zeros_like(seats)
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for idx, val in np.ndenumerate(seats):
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if val == 0:
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continue
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findings = (find_neighbor(idx, ray) for ray in RAYS)
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findings = [f for f in findings if f is not None]
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neighbors[idx] += sum(occ for occ, f in findings)
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if val == -1 and neighbors[idx] == 0:
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result[idx] = 1
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elif val == 1 and neighbors[idx] >= 5:
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result[idx] = -1
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else:
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result[idx] = seats[idx]
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if result[idx] == 1:
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for occ, f in findings:
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next_neighbors[f] += 1
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seats = result
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neighbors = next_neighbors
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next_neighbors = np.zeros_like(seats, dtype=np.byte)
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print(occupied)
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print(occupied)
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