def solve(G):
"""
Args:
G: networkx.Graph
Returns:
T: networkx.Graph
"""
g = GraphSolver(G)
start = g.find_leaf_path()
if start is None:
start = first_heuristic(g)
graph_choices = []
for v in g.neighbors(start):
newG = G.copy()
new_g = GraphSolver(newG)
new_g.visit(start)
new_g.visit(v, (start, v))
graph_choices.append(new_g)
minT = G
minCost = float('inf')
for g_option in graph_choices:
g_option.dijkstra_solve_graph(start, calculate_heuristic,
first_heuristic)
optimize_sorted(g_option, g_option.T, cycle_killer_fn=kill_cycle)
cost = average_pairwise_distance(g_option.T)
if cost < minCost:
minCost = cost
minT = g_option.T
return minT
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
"""
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)
start = g.find_leaf_path()
T = g.dijkstra_solve_graph(start, calculate_heuristic, first_heuristic)
if average_pairwise_distance(T) == 0:
return T
optimize_sorted(g, T, cycle_killer_fn=kill_cycle)
return T