def toEnzymeStructure_b(data_dict):
'''Converts dictionary structure to DataTreatment.Enzyme based
structure to be able to test data selection functions.'''
organized_data = {}
for enzyme in data_dict:
organized_data[enzyme] = Enzyme(enzyme, '1.1.1.1')
for metabolite in data_dict[enzyme]:
organized_data[enzyme].backward[metabolite] = []
data = getData(data_dict[enzyme], metabolite,
DataType.turnover)
for index, entry in enumerate(data_dict[enzyme][metabolite]):
organized_data[enzyme].backward[metabolite].append(
MetaboliteCandidate(metabolite, **data[index]))
return organized_data
def test_buildExpectedEnzyme(self):
new_enzyme = Enzyme('biggly', '2.2.2.2b')
self.assertEqual('biggly', new_enzyme.bigg)
self.assertEqual('2.2.2.2b', new_enzyme.EC)
self.assertEqual({}, new_enzyme.forward)
self.assertEqual({}, new_enzyme.backward)
self.assertEqual({}, new_enzyme.with_kegg)
self.assertEqual(None, new_enzyme.forward_turnover)
self.assertEqual(None, new_enzyme.backward_turnover)
self.assertEqual(None, new_enzyme.has_f_wild_type)
self.assertEqual(None, new_enzyme.has_b_wild_type)
def loadMadeUpModel(path):
'''Load a cobra model using a structure based on Enzymes and Metabolite
Candidates
Args:
path: filepath to made up mode.
Note:
This function, based on DataTreatment.storeBiGGRepresentation is
for testing purposes, and allows to load a made up model.
'''
made_up_model = cobra.io.load_json_model(path)
local_repr = {}
for reaction in made_up_model.reactions:
if reaction.id == 'CSND' or reaction.id == 'DHPM1':
local_repr[reaction.id] = Enzyme(reaction.id)
for reactant in reaction.reactants:
local_repr[reaction.id].forward[reactant.name] = \
Metabolite(reactant.name, bigg=reactant.id)
for product in reaction.products:
local_repr[reaction.id].backward[product.name] = \
Metabolite(product.name, bigg=product.id)
return local_repr
class MatchById(unittest.TestCase):
'''Contains functions to test Match By Id
Note:
openJson already checked in TestFileIO.py
'''
def loadMadeUpModel(path):
'''Load a cobra model using a structure based on Enzymes and Metabolite
Candidates
Args:
path: filepath to made up mode.
Note:
This function, based on DataTreatment.storeBiGGRepresentation is
for testing purposes, and allows to load a made up model.
'''
made_up_model = cobra.io.load_json_model(path)
local_repr = {}
for reaction in made_up_model.reactions:
if reaction.id == 'CSND' or reaction.id == 'DHPM1':
local_repr[reaction.id] = Enzyme(reaction.id)
for reactant in reaction.reactants:
local_repr[reaction.id].forward[reactant.name] = \
Metabolite(reactant.name, bigg=reactant.id)
for product in reaction.products:
local_repr[reaction.id].backward[product.name] = \
Metabolite(product.name, bigg=product.id)
return local_repr
brenda_keggs = openJson('Unit Tests/sample_brenda_keggs.json')
treated_brenda_output = openJson(
'Unit Tests/sample_simple_brenda_output.json')
data_type = DataType.turnover
potential_updates_dict = openJson(
'Unit Tests/correct_potential_updates.json')
simple_test_model = loadMadeUpModel('Unit Tests/simple_test_model.json')
simple_test_model['CSND'].with_kegg['C00380'] = 'cyt'
simple_test_model['CSND'].with_kegg['D00323'] = '5-fluorocyt'
simple_test_model['DHPM1'].with_kegg['C00148'] = 'DL-p'
correct_potential_updates = {}
for reaction in potential_updates_dict:
correct_potential_updates.update({reaction: Enzyme(reaction)})
if reaction in brenda_keggs:
for kegg in brenda_keggs[reaction]:
brenda_name = brenda_keggs[reaction][kegg]
if kegg in simple_test_model[reaction].with_kegg:
if simple_test_model[reaction].with_kegg[kegg] in\
simple_test_model[reaction].forward:
if treated_brenda_output[reaction][
brenda_keggs[reaction][kegg]] != []:
name = simple_test_model[reaction].with_kegg[kegg]
correct_potential_updates[reaction].forward[
name] = []
for entry in treated_brenda_output[reaction][
brenda_name]:
data = {
'organism': entry['organism'],
'wild-type': entry['wild-type'],
'turnover': entry['turnoverNumber']
}
correct_potential_updates[reaction].forward[
name].append(MetaboliteCandidate(
brenda_name, data))
elif simple_test_model[reaction].with_kegg[kegg] in\
simple_test_model[reaction].backward:
name = simple_test_model[reaction].with_kegg[kegg]
correct_potential_updates[reaction].backward[name] = []
for entry in treated_brenda_output[reaction][brenda_name]:
data = {
'organism': entry['organism'],
'wild-type': entry['wild-type'],
'turnover': entry['turnoverNumber']
}
correct_potential_updates[reaction].backward[
name].append(MetaboliteCandidate(
brenda_name, data))
correct_unmatched = openJson('Unit Tests/correct_unmatched.json')
def test_matchById_potential_updates(self):
'''matchByName should match BiGG metabolites with BRENDA metabolites
given a file containing their respective KEGG Ids.
'''
potential_updates = {}
matchById(potential_updates, MatchById.brenda_keggs,
MatchById.treated_brenda_output, MatchById.data_type,
MatchById.simple_test_model)
writeEnzymes('Unit Tests/return_matchById_potential_updates.json',
potential_updates)
potential_updates_as_dict = {}
correct_potential_updates_as_dict = {}
for enzyme in potential_updates:
potential_updates_as_dict[enzyme] = \
potential_updates[enzyme].getDict()
for enzyme in MatchById.correct_potential_updates:
correct_potential_updates_as_dict[enzyme] = \
MatchById.correct_potential_updates[enzyme].getDict()
self.assertDictEqual(potential_updates_as_dict,
correct_potential_updates_as_dict,
msg='Potential updates incorrect.')