def test_number_of_knockouts(self):
of_max = number_of_knockouts(sense='max')
of_min = number_of_knockouts(sense='min')
f1 = of_max(None, None, [['a', 'b'], ['a', 'b']])
f2 = of_max(None, None, [['a', 'b'], ['a', 'b', 'c']])
self.assertGreater(f2, f1)
f1 = of_min(None, None, [['a', 'b'], ['a', 'b']])
f2 = of_min(None, None, [['a', 'b'], ['a', 'b', 'c']])
self.assertGreater(f1, f2)
def test_run_multiobjective(self):
result_file = os.path.join(CURRENT_PATH, "data", "reaction_knockout_multi_objective.pkl")
objective1 = biomass_product_coupled_yield(
"Biomass_Ecoli_core_N_LPAREN_w_FSLASH_GAM_RPAREN__Nmet2",
"EX_ac_LPAREN_e_RPAREN_",
"EX_glc_LPAREN_e_RPAREN_")
objective2 = number_of_knockouts()
objective = [objective1, objective2]
rko = ReactionKnockoutOptimization(model=self.model,
simulation_method=fba,
objective_function=objective,
heuristic_method=inspyred.ec.emo.NSGA2,
seed=SEED)
# self.assertEqual(rko.random.random(), 0.1915194503788923)
results = rko.run(max_evaluations=3000, pop_size=10, view=SequentialView())
# print(rko.random.random(), 0.545818634701)
with open(result_file, 'rb') as in_file:
if six.PY3:
expected_results = pickle.load(in_file, encoding="latin1")
else:
expected_results = pickle.load(in_file)
assert_frame_equal(results.solutions, expected_results.solutions)
def test_change_objective_function(self):
single_objective_heuristic = HeuristicOptimization(
model=self.model,
objective_function=self.single_objective_function,
)
nok = number_of_knockouts()
single_objective_heuristic.objective_function = nok
self.assertEqual(nok, single_objective_heuristic.objective_function)
self.assertFalse(single_objective_heuristic.is_mo())
self.assertRaises(TypeError,
single_objective_heuristic.objective_function,
self.multiobjective_function)
single_objective_heuristic.objective_function = [nok]
self.assertEqual(nok, single_objective_heuristic.objective_function)
self.assertFalse(single_objective_heuristic.is_mo())
self.assertRaises(TypeError, single_objective_heuristic.objective_function, self.multiobjective_function)
multiobjective_heuristic = HeuristicOptimization(
model=self.model,
objective_function=self.multiobjective_function,
heuristic_method=inspyred.ec.emo.NSGA2
)
multiobjective_heuristic.objective_function = nok
self.assertEqual(len(multiobjective_heuristic.objective_function), 1)
self.assertEqual(multiobjective_heuristic.objective_function[0], nok)
self.assertTrue(multiobjective_heuristic.is_mo())
def setUp(self):
self.model = TEST_MODEL
self.single_objective_function = product_yield('product', 'substrate')
self.multiobjective_function = [
product_yield('product', 'substrate'),
number_of_knockouts()
]
