Implement furthest element computation
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from preprocessing import parse_file
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from pandas import DataFrame
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from secrets import randbelow
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from sys import argv
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def get_furthest_element(element, data):
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element_df = data.query(f"source == {element} or destination == {element}")
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furthest_index = element_df["distance"].idxmax()
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furthest_row = data.iloc[furthest_index]
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return furthest_row
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def greedy_algorithm(n, m, data):
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solutions = DataFrame(columns=["source", "destination", "distance"])
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for _ in range(m):
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centroid = get_furthest_element(element=randbelow(n), data=data)
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solutions = solutions.append(centroid)
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def usage(argv):
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print(f"Usage: python {argv[0]} <file>")
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exit(1)
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def main():
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if len(argv) != 2:
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usage(argv)
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n, m, data = parse_file(argv[1])
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if __name__ == "__main__":
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main()
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