def test_construct_distance_graph(self):
b_s = BaseSolution()
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.relax_network()
b_s.construct_distance_graph()
b_s.display_graph("test_construct_distance_graph")
self.assertTrue(False)
def test_model_network(self):
b_s = BaseSolution()
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.display_graph("test_model_network")
self.assertTrue(False)
def test_backpropagate_task_assign(self):
b_s = BaseSolution()
s_o_d = SetOfDifferences()
policy = Policy()
# Create plan
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.relax_network()
b_s.construct_distance_graph()
b_s.all_pairs_shortest_paths()
b_s.prune_redundant_constraints()
# Evaluate policies
print("Evaluating: {}".format(b_s._graph.nodes.data()))
policy.evaluate(b_s)
print("Policy results")
print(policy.valid_assignments)
print(policy.data)
# Build set of differences
s_o_d.initialize_set_of_differences(b_s, policy)
print(s_o_d.self.valid_assignments)
for full_assignment in s_o_d.valid_assignments:
constraints = [asg[0] for asg in full_assignment.task_assignments]
temporally_consistent = s_o_d.backpropagate_task_assign(
constraints, self.base_solution, full_assignment)
if not temporally_consistent:
full_assignment.feasible = False
self.assertTrue(False)
def test_create_component_solution(self):
b_s = BaseSolution()
s_o_d = SetOfDifferences()
policy = Policy()
# Create plan
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.relax_network()
b_s.construct_distance_graph()
b_s.all_pairs_shortest_paths()
b_s.prune_redundant_constraints()
# Evaluate policies
print("Evaluating: {}".format(b_s._graph.nodes.data()))
policy.evaluate(b_s)
print("Policy results")
print(policy.valid_assignments)
print(policy.data)
# Build set of differences
s_o_d.initialize_set_of_differences(b_s, policy)
self.assertTrue(False)
def test_policy_evaluate(self):
b_s = BaseSolution()
policy = Policy()
# Create plan
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.relax_network()
b_s.construct_distance_graph()
b_s.all_pairs_shortest_paths()
b_s.prune_redundant_constraints()
#
print("Evaluating: {}".format(b_s._graph.nodes.data()))
policy.evaluate(b_s)
print("Policy results")
print(policy.valid_assignments)
print(policy.data)
self.assertTrue(False)
def test_prune_redundant_constraints(self):
b_s = BaseSolution()
b_s.model_temporal_problem("Cranfield_Assembly")
b_s.relax_network()
b_s.construct_distance_graph()
b_s.all_pairs_shortest_paths()
b_s.prune_redundant_constraints()
b_s.display_graph("test_prune_redundant_constraints")
self.assertTrue(False)