2022-05-30 23:34:28 +02:00
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from dataclasses import dataclass
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2022-05-31 21:34:31 +02:00
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from const import *
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from typing import List, Dict, Tuple
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import numpy.typing as npt
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2022-05-30 23:34:28 +02:00
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@dataclass
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class Position:
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row: int
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col: int
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2022-05-31 21:34:31 +02:00
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def dfs(grid: npt.NDArray, visited: Dict[Tuple[int, int], bool], position: Position, rows: int, cols: int) -> None:
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visited[(position.row, position.col)] = True
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row_vector = [0, 0, 1, -1]
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col_vector = [-1, 1, 0, 0]
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neighbours = []
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for i in range(4):
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rr = position.row + row_vector[i]
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cc = position.col + col_vector[i]
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if rr < 0 or rr >= ROWS:
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continue
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elif cc < 0 or cc >= COLUMNS:
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continue
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else:
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p = Position(rr, cc)
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if (p.row, p.col) in visited:
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neighbours.append(p)
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for neighbour in neighbours:
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if not visited[(neighbour.row, neighbour.col)]:
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dfs(grid, visited, neighbour, rows, cols)
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def count_islands(grid: npt.NDArray, positions: List[Position], rows: int = ROWS, cols: int = COLUMNS) -> int:
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visited = {}
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for position in positions:
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visited[(position.row, position.col)] = False
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islands = 0
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for position in positions:
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if not visited[(position.row, position.col)]:
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dfs(grid, visited, position, rows, cols)
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islands += 1
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return islands
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