def optimize_removal(solver: GraphSolver, tree: Graph, orig_cost: float):
candidates = [
v for v in tree.nodes
if not solver.is_required(v) and is_leaf(tree, v)
]
while candidates:
# print(candidates)
# random.seed(0)
node = random.choice(candidates)
candidates.remove(node)
edge = (node, list(tree.neighbors(node))[0])
solver.unvisit(node)
new_cost = average_pairwise_distance(tree)
if new_cost < orig_cost:
# print('removed', node)
return optimize_removal(solver, tree, new_cost)
else:
solver.add_edge(edge)
return orig_cost
def optimize_removal_sorted(solver: GraphSolver, tree: Graph,
orig_cost: float):
candidates = [
v for v in tree.nodes
if not solver.is_required(v) and is_leaf(tree, v)
]
while candidates:
# print(candidates)
# random.seed(0)
candidates.sort(key=lambda x: closeness_centrality(solver.T, x))
node = candidates.pop(0)
edge = (node, list(tree.neighbors(node))[0])
solver.unvisit(node)
new_cost = average_pairwise_distance(tree)
if new_cost < orig_cost:
# print('removed', node)
return optimize_removal_sorted(solver, tree, new_cost)
else:
solver.add_edge(edge)
return orig_cost
def optimize_additions(solver: GraphSolver,
tree: Graph,
orig_cost: float = None):
graph = solver.G
if orig_cost is None:
orig_cost = average_pairwise_distance(tree)
# get all edges to consider
edges = []
for node in tree.nodes:
for neighbor in graph.neighbors(node):
if not edge_exists(tree.edges,
(node, neighbor)) and not edge_exists(
edges, (node, neighbor)):
edges.append((node, neighbor))
# for each edge (consider order randomly)
while edges:
# random.seed(0)
added_edge = random.choice(edges)
edges.remove(added_edge)
weight = graph[added_edge[0]][added_edge[1]]['weight']
# if added edge creates a cycle
if added_edge[1] in tree.nodes:
solver.add_edge(added_edge)
while (True):
try:
cycle: list = find_cycle(tree, added_edge[0])
except: # No cycle
break
try:
cycle.remove(added_edge)
except ValueError:
cycle.remove(added_edge[::-1])
replaced_edge, new_cost = kill_cycle(solver, cycle, orig_cost)
# print("replaced_edge:", replaced_edge)
# print("cost:", new_cost)
if replaced_edge:
orig_cost = new_cost
solver.remove_edge(replaced_edge)
else:
solver.remove_edge(added_edge)
# if other vertex not in tree
else:
v = added_edge[1]
solver.visit(v, added_edge)
# add_edge(tree, added_edge, weight)
new_cost = average_pairwise_distance(tree)
if new_cost < orig_cost:
orig_cost = new_cost
add_neighbors(solver, edges, v)
else:
solver.unvisit(v)
# remove considered edge
return orig_cost