def test_RevCIAddB_revise_ignoring(self):
met1 = mnm_repr.Metabolite('met1')
met2 = mnm_repr.Metabolite('met2')
comp1 = mnm_repr.Medium()
cond_subst_1 = mnm_repr.PresentEntity(met1, comp1)
cond_subst_2 = mnm_repr.PresentEntity(met2, comp1)
a1 = mnm_repr.Reaction('act1', [], [cond_subst_1, cond_subst_2])
a1.remove_cost = None
a1.reversibility = False
a2 = mnm_repr.Reaction('act1', [], [cond_subst_1])
a2.reversibility = False
# model to be revised
mod = mnm_repr.Model('m_0', [], [a1], [])
# results
des1 = exp_repr.ExperimentDescription(exp_repr.DetectionEntity('met1'),
[])
des2 = exp_repr.ExperimentDescription(exp_repr.DetectionEntity('met2'),
[])
res1 = exp_repr.Result('res_0', des1, 'false')
res2 = exp_repr.Result('res_1', des2, 'true')
exp1 = exp_repr.Experiment('exp_0', [res1])
exp2 = exp_repr.Experiment('exp_1', [res2])
# archive with results and parts for revision
arch = Archive()
arch.known_results = [exp1, exp2]
arch.mnm_activities = [a1, a2]
arch.mnm_entities = [met1, met2]
arch.mnm_compartments = [comp1]
rev = RevCIAddB(arch)
out = rev.revise(mod)
self.assertEqual(out[0], [])
self.assertEqual(out[1], True)
def test_make_derivative_models(self):
rev = RevisionModule('archive')
cond_subst_1 = mnm_repr.PresentEntity(mnm_repr.Metabolite('met1'),
mnm_repr.Medium())
cond_subst_2 = mnm_repr.PresentEntity(mnm_repr.Metabolite('met2'),
mnm_repr.Medium())
base_model = mnm_repr.Model(
'm1', [cond_subst_1], [],
[]) #model that is compatible with interventions
second_mod = mnm_repr.Model('deriv_m1_0', [cond_subst_1, cond_subst_2],
[], [])
third_mod = mnm_repr.Model('deriv_m1_1', [], [], [])
exd1 = exp_repr.ExperimentDescription(None,
[mnm_repr.Add(cond_subst_2)])
exd2 = exp_repr.ExperimentDescription(None,
[mnm_repr.Remove(cond_subst_1)])
res1 = exp_repr.Result('r1', exd1, True)
res2 = exp_repr.Result('r2', exd2, True)
extracted_results = [res1, res2] #need interventions in description
models_results = rev.make_derivative_models(base_model,
extracted_results)
self.assertEqual(models_results, {
base_model: [],
second_mod: [res1],
third_mod: [res2]
})
def test_calculate_max_number_activities(self):
# model with activities, archive with results that have add activity in interventions
a1 = mnm_repr.Activity('act1', None, ['a'], [])
a2 = mnm_repr.Activity('act1', None, ['b'], [])
a3 = mnm_repr.Activity('act1', None, ['c'], [])
a4 = mnm_repr.Activity('act1', None, ['d'], [])
base_model = mnm_repr.Model('m1', [], [a1], [])
des1 = exp_repr.ExperimentDescription(
None, [mnm_repr.Add(a2), mnm_repr.Add(a1)])
des2 = exp_repr.ExperimentDescription(None, [mnm_repr.Add(a3)])
des3 = exp_repr.ExperimentDescription(
None, [mnm_repr.Add(a4), mnm_repr.Add(a3)])
res1 = exp_repr.Result('r1', des1, None)
res2 = exp_repr.Result('r2', des2, None)
res3 = exp_repr.Result('r3', des3, None)
exp1 = exp_repr.Experiment('exp1', [res1])
exp2 = exp_repr.Experiment('exp2', [res2])
exp3 = exp_repr.Experiment('exp3', [res3])
arch = Archive()
arch.known_results = [exp1, exp2, exp3]
rev = RevisionModule(arch)
out = rev.calculate_max_number_activities(base_model)
self.assertEqual(out, 4)
def test_export_ignore_results(self):
des = exp_repr.ExperimentDescription(exp_repr.DetectionEntity('e1'))
res1 = exp_repr.Result('res1', des, None)
res2 = exp_repr.Result('res2', des, None)
out = exporter.export_ignore_results([res1, res2])
self.assertIn('\n#modeh ignored(res1) =1 @2.', out)
self.assertIn('\n#modeh ignored(res2) =1 @2.', out)
def test_export_results(self):
# one of exp types; no need to test all (they do the same thing)
exp_type = exp_repr.LocalisationEntity('p1', 'c_02')
res = exp_repr.Result('res1',
exp_repr.ExperimentDescription(exp_type, []),
True)
exported = exporter.export_results([res])
self.assertIn(
'\nresult(res1, experiment(localisation_entity_exp, p1, c_02), True).',
exported)
def setUp(self):
# models:
self.g1 = Gene('g1')
self.p1 = Protein('p1')
self.met1 = Metabolite('met1')
self.met2 = Metabolite('met2')
self.cplx1 = Complex('cplx1')
self.cytosol = Cytosol()
self.cond1 = PresentEntity(self.met1, self.cytosol)
self.cond2 = PresentEntity(self.met2, self.cytosol)
self.cond3 = PresentEntity(self.p1, self.cytosol)
self.cond4 = PresentEntity(self.cplx1, self.cytosol)
self.growth = Growth('growth', [self.cond2])
self.growth.reversibility = False
self.r1 = Reaction('r1', [self.cond1], [self.cond2])
self.r2 = Reaction('r2', [self.cond3], [self.cond4])
self.r1.reversibility = False
self.r2.reversibility = False
self.entities = [self.g1, self.p1, self.met1, self.met2, self.cplx1]
self.compartments = [self.cytosol]
self.activities = [self.growth, self.r1, self.r2]
self.setup_conds = [self.cond1, self.cond3]
self.mod1 = Model('m0', self.setup_conds, [self.growth, self.r1], [])
self.mod2 = Model('m1', self.setup_conds, [self.growth, self.r2], [])
# cost_module:
self.cost_model = CostModel(self.entities, self.compartments,
self.activities, self.setup_conds)
self.cost_model.set_all_basic_costs_to_1()
self.cost_model.calculate_derived_costs(self.activities)
self.cost_model.remove_None_valued_elements()
# known results (one exp, both models consistent)
self.exd = exp_repr.ExperimentDescription(
exp_repr.DetectionEntity('met1'), [])
self.res = exp_repr.Result('res1', self.exd, 'true')
self.exp = exp_repr.Experiment('exp1', [self.res])
# archive
self.arch = Archive()
self.arch.working_models = [self.mod1, self.mod2]
self.arch.known_results = [self.exp]
self.arch.mnm_compartments = self.compartments
self.arch.mnm_entities = self.entities
self.arch.mnm_activities = self.activities
# exp module
self.exp_module = ExperimentModule(self.arch, self.cost_model, False)
def test_ban_experiment(self):
comp = mnm_repr.Medium()
ent1 = mnm_repr.Metabolite('m1')
cond1 = mnm_repr.PresentEntity(ent1, comp)
inter1 = mnm_repr.Add(cond1)
ent2 = mnm_repr.Metabolite('m2')
cond2 = mnm_repr.PresentEntity(ent2, comp)
inter2 = mnm_repr.Remove(cond2)
exp_description = exp_repr.ExperimentDescription(
exp_repr.DetectionEntity('ent1'), [inter1, inter2])
out = exporter.ban_experiment(exp_description)
# print([out])
self.assertIn('\n:- designed(experiment(detection_entity_exp, ent1))',
out)
self.assertIn(',remove(setup_present(m2, none, c_01))', out)
self.assertIn(',add(setup_present(m1, none, c_01))', out)
def test_check_consistency_negative(self):
met1 = mnm_repr.Metabolite('met1')
met2 = mnm_repr.Metabolite('met2')
comp1 = mnm_repr.Medium()
cond_subst_1 = mnm_repr.PresentEntity(met1, comp1)
cond_subst_2 = mnm_repr.PresentEntity(met2, comp1)
base_model = mnm_repr.Model('m1', [cond_subst_1, cond_subst_2], [], [])
exd = exp_repr.ExperimentDescription(exp_repr.DetectionEntity('met1'),
[])
res = exp_repr.Result('r1', exd, 'false')
exp = exp_repr.Experiment('exp1', [res])
arch = Archive()
arch.mnm_entities = [met1, met2]
arch.mnm_compartments = [comp1]
ev1 = AdditionalModels([base_model])
ev2 = AcceptedResults(exp)
arch.record(ev1)
arch.record(ev2)
rev = RevisionModule(arch)
out = rev.check_consistency(base_model)
self.assertEqual(False, out)