def test_cycling_states(self):
model, *_ = parse_smbionet_output_file(mucus_operon_v4_out)
operon = model.find_gene_by_name('operon')
mucuB = model.find_gene_by_name('mucuB')
self.assertEqual((State({
operon: 1,
mucuB: 0
}), ), model.available_state(State({
operon: 0,
mucuB: 0
})))
self.assertEqual((State({
operon: 2,
mucuB: 0
}), State({
operon: 1,
mucuB: 1
})), model.available_state(State({
operon: 1,
mucuB: 0
})))
self.assertEqual((State({
operon: 0,
mucuB: 1
}), ), model.available_state(State({
operon: 1,
mucuB: 1
})))
self.assertEqual((State({
operon: 0,
mucuB: 0
}), ), model.available_state(State({
operon: 0,
mucuB: 1
})))
def test_export(self):
model, *_ = parse_smbionet_output_file(model2346_out)
graph = Graph(model)
output = os.path.join(resources, 'output')
graph.export_to_dot(output)
self.assertTrue(os.path.exists(output + '.dot'))
os.remove(output + '.dot')
def test_day_night_cycle_out(self):
model1, *_ = parse_smbionet_output_file(day_night_cycle_out)
simulation = Simulation(model1)
simulation.steps = 5
simulation.random.seed(0xff)
simulation.initial_state = {'G': 0, 'P': 1}
result = simulation.run()
G = model1.find_gene_by_name('G')
P = model1.find_gene_by_name('P')
expected = [{
G: 0,
P: 1
}, {
G: 0,
P: 0
}, {
G: 1,
P: 0
}, {
G: 1,
P: 1
}, {
G: 0,
P: 1
}]
self.assertEqual(expected, result.states)
def test_available_states(self):
_, model2 = parse_smbionet_output_file(mucus_operon_v3_out)
operon = model2.find_gene_by_name('operon')
mucuB = model2.find_gene_by_name('mucuB')
self.assertEqual(
(State({
operon: 1,
mucuB: 0
}), ),
model2.available_state_for_gene(operon, State({
operon: 0,
mucuB: 0
})))
self.assertEqual(
(State({
operon: 2,
mucuB: 0
}), ),
model2.available_state_for_gene(operon, State({
operon: 1,
mucuB: 0
})))
self.assertEqual(
(State({
operon: 2,
mucuB: 0
}), ),
model2.available_state_for_gene(operon, State({
operon: 2,
mucuB: 0
})))
def test_mucus_operon_v3(self):
model1, model2 = parse_smbionet_output_file(mucus_operon_v3_out)
graph = InfluenceGraph()
operon = Gene('operon', (0, 1, 2))
graph.add_gene(operon)
mucuB = Gene('mucuB', (0, 1))
graph.add_gene(mucuB)
free = Multiplex('free', (operon, ), Expression('(not(mucuB>=1))'))
graph.add_multiplex(free)
alg = Multiplex('alg', (operon, ), Expression('(operon>=1)'))
graph.add_multiplex(alg)
prod = Multiplex('prod', (mucuB, ), Expression('(operon>=1)'))
graph.add_multiplex(prod)
expected_model1 = DiscreteModel(graph)
expected_model1.add_transition(Transition(operon, (), (0, )))
expected_model1.add_transition(Transition(operon, (alg, ), (2, )))
expected_model1.add_transition(Transition(operon, (free, ), (0, )))
expected_model1.add_transition(Transition(operon, (alg, free), (2, )))
expected_model1.add_transition(Transition(mucuB, (), (0, )))
expected_model1.add_transition(Transition(mucuB, (prod, ), (1, )))
expected_model2 = DiscreteModel(graph)
expected_model2.add_transition(Transition(operon, (), (0, )))
expected_model2.add_transition(Transition(operon, (alg, ), (2, )))
expected_model2.add_transition(Transition(operon, (free, ), (1, 2)))
expected_model2.add_transition(Transition(operon, (alg, free), (2, )))
expected_model2.add_transition(Transition(mucuB, (), (0, )))
expected_model2.add_transition(Transition(mucuB, (prod, ), (1, )))
self.assertEqual(expected_model1, model1)
self.assertEqual(expected_model2, model2)
def test_find_transition(self):
model1, model2 = parse_smbionet_output_file(mucus_operon_v3_out)
operon = model1.find_gene_by_name('operon')
free = model1.find_multiplex_by_name('free')
alg = model1.find_multiplex_by_name('alg')
transition = model1.find_transition(operon, (alg, free))
self.assertEqual((2, ), transition.states)
transition = model2.find_transition(operon, (free, ))
self.assertEqual((1, 2), transition.states)
def test_resources_table_as_data_frame(self):
model1, *_ = parse_smbionet_output_file(mucus_operon_v4_out)
rt = ResourceTable(model1.influence_graph)
df = rt.as_data_frame()
expected = pandas.DataFrame({
'operon': [0, 0, 1, 1, 2, 2],
'mucuB': [0, 1, 0, 1, 0, 1],
'active multiplex on operon': ['{free}', '{}', '{free}', '{}', '{free, alg}', '{alg}'],
'active multiplex on mucuB': ['{}', '{}', '{prod}', '{prod}', '{prod}', '{prod}']
})
pandas.testing.assert_frame_equal(expected, df)
def test_ggea_example(self):
model, *_ = parse_smbionet_output_file(model2346_out)
graph = Graph(model)
self.assertEqual(864, graph.number_of_states())
def test_model_2346(self):
model1, *_ = parse_smbionet_output_file(model2346_out)
simulation = Simulation(model1)
result = simulation.run()
self.assertEqual(100, len(result.states))
def test_process_activation(self):
model1, _ = parse_smbionet_output_file(mucus_operon_v3_out)
free = model1.find_multiplex_by_name('free')
mucuB = model1.find_gene_by_name('mucuB')
self.assertTrue(free.is_active(State({mucuB: 0})))
def test_export_model(self):
model, *_ = parse_smbionet_output_file(mucus_operon_v4_out)
json = export_model_to_json(model)
self.assertEqual(model, parse_json_model(json))