def test_case(filename):
data = get_input(filename)
output = get_output(filename.replace("input", "output"))
shortest = clustering(data)
assert shortest == output
if not detect_cycle(bfs_graph_addition, u) and tuple(sorted(
[u, v])) not in t:
t = t.union([tuple(sorted([u, v]))])
cost += w
bfs_graph[u].add(v)
bfs_graph[v].add(u)
return cost
def kruskal_uf(graph):
uf = UF(len(graph))
t = set()
cost = 0
edges = []
for u in graph.keys():
for v, w in graph[u]:
edges.append((u, v, w))
edges = sorted(edges, key=lambda x: x[2])
for u, v, w in edges:
if uf.find(u - 1) != uf.find(v - 1):
t = t.union([tuple(sorted([u, v]))])
uf.union(u - 1, v - 1)
cost += w
return cost
if __name__ == "__main__":
data = get_input("test.txt")
# print(data)
# print(len(data))
print(kruskal_uf(data))
from algorithms.mst_prim import get_input
from algorithms.single_link_clustering import clustering
import pytest
import glob
filename = "input_completeRandom_*.txt"
all_files = glob.glob(filename)
def get_output(filename):
with open(filename, 'r') as f:
line = f.readline()
return int(line)
@pytest.mark.parametrize("filename", all_files)
def test_case(filename):
data = get_input(filename)
output = get_output(filename.replace("input", "output"))
shortest = clustering(data)
assert shortest == output
if __name__ == "__main__":
data = get_input("challenge.txt")
shortest = clustering(data)
print(shortest)
def test_case(filename):
data = get_input(filename)
output = get_output(filename.replace("input", "output"))
shortest = kruskal_uf(data)
assert shortest == output