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Remove selected solution from dataset properly

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coolneng 2021-04-12 12:58:23 +02:00
parent 04c92add44
commit a81756e93b
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
1 changed files with 11 additions and 7 deletions
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src/processing.py
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@ -29,20 +29,22 @@ def get_furthest_element(element, data):
furthest_index = element_df["distance"].astype(float).idxmax()
furthest_row = data.iloc[furthest_index]
furthest_point = get_different_element(original=element, row=furthest_row)
furthest_element = {"point": furthest_point, "distance": furthest_row["distance"]}
return furthest_element, furthest_index
return {"point": furthest_point, "distance": furthest_row["distance"]}
def remove_solution_dataset(data, solution):
return data.query(f"source != {solution} and destination != {solution}")
# FIXME Remove duplicated elements properly
def greedy_algorithm(n, m, data):
solutions = DataFrame(columns=["point", "distance"])
first_solution = get_first_solution(n, data)
solutions = solutions.append(first_solution, ignore_index=True)
for _ in range(m):
last_solution = solutions["point"].tail(n=1)
centroid, index = get_furthest_element(element=int(last_solution), data=data)
last_solution = int(solutions["point"].tail(n=1))
centroid = get_furthest_element(element=last_solution, data=data)
solutions = solutions.append(dict(centroid), ignore_index=True)
data = data.drop(index)
data = remove_solution_dataset(data=data, solution=last_solution)
return solutions
@ -72,9 +74,11 @@ def execute_algorithm(choice, n, m, data):
def show_results(solutions):
distance_sum = solutions["distance"].sum()
duplicates = solutions.duplicated()
print(solutions)
print("Total distance: " + str(distance_sum))
print(solutions.duplicated())
if solutions[duplicates].empty:
print("No duplicates found")
def usage(argv):