def get_christofides_tours_edges(self, graph, weight="weight"):
""" Extract the doubletours edges from the graph """
tours = self.get_christofides_tours(graph)
edges_a = graph_utils.get_tour_edges(tours[0]).tolist()
edges_b = graph_utils.get_tour_edges(tours[1]).tolist()
return edges_a + edges_b
def extract_doubletours_edges_from_tree(self, tree, weight="weight"):
""" Extract the doubletours edges from the tree """
tours = self.get_doubletours_from_tree(tree)
edges_a = graph_utils.get_tour_edges(tours[0]).tolist()
edges_b = graph_utils.get_tour_edges(tours[1]).tolist()
return edges_a + edges_b
def compute_labels_from_solution(self, solution_fname):
""" Using the solution file, read the solution in """
tour = self._object.read_solution_from_file(solution_fname)
edges = graph_utils.get_tour_edges(tour)
min_vertex = np.min(self._graph.nodes)
order = len(self._graph.nodes)
indices = [graph_utils.compute_vector_index_symmetric(edge, order, min_vertex)
for edge in edges]
vector = np.zeros((len(self._graph.edges)))
vector[indices] = 1
return vector
def get_christofides_tour_edges(self, graph, weight="weight"):
""" Extract the doubletour edges from the graph """
tour = self.get_get_christofides_tour(graph)
return graph_utils.get_tour_edges(tour).tolist()
def extract_doubletour_edges_from_tree(self, tree, weight="weight"):
""" Extract the doubletour edges from the tree """
tour = self.get_doubletour_from_tree(tree)
return graph_utils.get_tour_edges(tour).tolist()
from optlearn.mst import mst_model
files = experiment_utils.list_files_recursive("/home/james/Data/MATHILDA/tsp/")
model = mst_model.mstSparsifier()
ones, twos, threes, fours, fives = [], [], [], [], []
for num, file in enumerate(files):
object = io_utils.optObject().read_from_file(file)
graph = object.get_graph()
graph = graph_utils.delete_self_weights(graph)
graph = graph.to_undirected()
solution = cc_solve.solution_from_path(file)
edges = graph_utils.get_tour_edges(solution.tour)
if np.min(solution.tour) < 1 and np.min(graph.nodes) > 0:
edges += 1
edges = model.tuples_to_strings(edges)
features = model.run_sparsify(graph, 15)
features = [model.tuples_to_strings(item) for item in features]
one = np.sum([edge in features[0] for edge in edges])
two = np.sum([edge in features[1] for edge in edges]) + one
three = np.sum([edge in features[2] for edge in edges]) + two
four = np.sum([edge in features[3] for edge in edges]) + three
five = np.sum([edge in features[4] for edge in edges]) + four
length = len(solution.tour)
ones.append(one / length)
def _compute_christofides_edges(self, graph):
""" Compute the Christofides edges """
tour = self._compute_christofides_tour(graph)
is_symmetric = graph_utils.check_graph(graph)
return graph_utils.get_tour_edges(tour, is_symmetric)
def _compute_doubletree_edges(self, graph):
""" Compute the doubletree edges """
tour = self._compute_doubletree_tour(graph)
is_symmetric = graph_utils.check_graph(graph)
return graph_utils.get_tour_edges(tour, is_symmetric)
def read_solution_from_file(self, fname, symmetric=True):
tour = read_solution_from_file(fname)
edges = graph_utils.get_tour_edges(tour, symmetric=symmetric)
self._solution = edges
return tour