60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
import shared
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import matrix
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from dijkstar import Graph, find_path, algorithm
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criteria = lambda _cur, _neighbor: _neighbor - _cur <= 1
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def build_graph(mx):
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graph = Graph()
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for y, row in enumerate(mx):
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for x, _ in enumerate(row):
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neighbors = matrix.valid_neighbors(mx, x=x, y=y, criteria=criteria)
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for neighbor in neighbors:
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graph.add_edge((y, x), (neighbor["y"], neighbor["x"]), 1)
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return graph
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def part1(mx):
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start = matrix.find_in_matrix(mx, "S")
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end = matrix.find_in_matrix(mx, "E")
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mx[start[0]][start[1]] = "a"
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mx[end[0]][end[1]] = "z"
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matrix.apply_to_all(mx, lambda x: ord(x) - ord("a"))
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graph = build_graph(mx)
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path = find_path(graph, start, end)
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print(len(path.nodes))
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def part2(mx):
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end = matrix.find_in_matrix(mx, "E")
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s = matrix.find_in_matrix(mx, "S")
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mx[s[0]][s[1]] = "a"
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mx[end[0]][end[1]] = "z"
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starts = matrix.find_in_matrix(mx, "a", one=False)
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matrix.apply_to_all(mx, lambda x: ord(x) - ord("a"))
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graph = build_graph(mx)
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n_counts = []
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for start in starts:
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try:
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path = find_path(graph, start, end)
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n_counts.append(len(path.nodes) - 1)
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except algorithm.NoPathError:
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pass
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print(n_counts)
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print(min(n_counts))
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def main():
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mx = matrix.load_matrix_file(shared.get_fname(12), matrix.split_word_to_chr_list)
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# part1(mx)
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part2(mx)
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if __name__ == "__main__":
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main()
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