Remove duplicates from the solutions

This commit is contained in:
coolneng 2021-04-11 22:22:18 +02:00
parent 85e6b072c6
commit 2fe874e733
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
1 changed files with 7 additions and 5 deletions

View File

@ -27,7 +27,8 @@ def get_furthest_element(element, data):
furthest_index = element_df["distance"].idxmax() furthest_index = element_df["distance"].idxmax()
furthest_row = data.iloc[furthest_index] furthest_row = data.iloc[furthest_index]
furthest_point = get_different_element(original=element, row=furthest_row) furthest_point = get_different_element(original=element, row=furthest_row)
return {"point": furthest_point, "distance": furthest_row["distance"]} furthest_element = {"point": furthest_point, "distance": furthest_row["distance"]}
return furthest_element, furthest_index
def greedy_algorithm(n, m, data): def greedy_algorithm(n, m, data):
@ -36,10 +37,10 @@ def greedy_algorithm(n, m, data):
solutions = solutions.append(first_solution, ignore_index=True) solutions = solutions.append(first_solution, ignore_index=True)
for _ in range(m): for _ in range(m):
last_solution = solutions["point"].tail(n=1) last_solution = solutions["point"].tail(n=1)
centroid = get_furthest_element(element=int(last_solution), data=data) centroid, index = get_furthest_element(element=int(last_solution), data=data)
solutions = solutions.append(dict(centroid), ignore_index=True) solutions = solutions.append(dict(centroid), ignore_index=True)
data = data.drop(centroid["point"], columns=["source", "destination"]) data = data.drop(index)
print(solutions) return solutions
# NOTE In each step, switch to the element that gives the least amount # NOTE In each step, switch to the element that gives the least amount
@ -56,7 +57,8 @@ def main():
if len(argv) != 2: if len(argv) != 2:
usage(argv) usage(argv)
n, m, data = parse_file(argv[1]) n, m, data = parse_file(argv[1])
greedy_algorithm(n, m, data) solutions = greedy_algorithm(n, m, data)
print(solutions)
if __name__ == "__main__": if __name__ == "__main__":