def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
start = g.find_leaf_path()
T = g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
optimize_sorted(g, T)
rebuilder = Rebuilder(g)
min_T = T.copy()
min_cost = average_pairwise_distance(T)
# print('*', min_cost)
for _ in range(50):
if rebuilder.rebuild():
g = GraphSolver(G)
for v in min_T.nodes:
g.visit(v)
for e in min_T.edges:
g.add_edge(e)
# print('reset')
g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
optimize_sorted(g, g.T)
cost = average_pairwise_distance(g.T)
# print(cost)
if cost < min_cost:
min_cost = cost
min_T = g.T.copy()
return min_T
def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
# TODO: your code here!
g = GraphSolver(G)
T = g.dijkstra_solve_graph()
return T
def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
start = g.find_leaf_path()
T = g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
return T
def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
start = g.find_leaf_path()
T = g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
optimize_sorted(g, T, kill_cycle_all_paths)
return T
def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
T = g.dijkstra_solve_graph(None, calculate_heuristic, first_heuristic)
if average_pairwise_distance(T) == 0:
return T
optimize_sorted(g, T, cycle_killer_fn=kill_cycle)
return T
def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
start = g.find_leaf_path()
T = g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
if average_pairwise_distance(T) == 0:
return T
optimize(g, T)
return T