def setUp(self):
# load a rpSBML file
self.rpsbml = rpSBML(
os_path.join(os_path.dirname(__file__), 'data', 'rpsbml.xml'))
self.gem = rpSBML(
os_path.join(os_path.dirname(__file__), 'data', 'gem.xml'))
self.rpsbml_name = 'RetroPath_Pathway_1_1'
self.rpsbml_score = 0.5684564101634014
with open(os_path.join(os_path.dirname(__file__), 'data', 'data.json'),
'r') as f:
self.data = json_load(f)
def test_pfba(self):
rpsbml = rpSBML(os_path.join('data', 'merged.xml'))
obj_value, rpsbml = rp_pfba(rpsbml, 'RP1_sink')
self.assertTrue(rpsbml)
self.assertAlmostEqual(obj_value, 859.3846153846168)
# make sure that the results are written to the file
all_json = rpsbml.genJSON()
self.assertAlmostEqual(all_json['pathway']['brsynth']['fba_obj_RP1_sink']['value'], 859.3846153846168)
def test_fraction(self):
rpsbml = rpSBML(os_path.join('data', 'merged.xml'))
obj_value, rpsbml = rp_fraction(rpsbml, 'biomass', 1.0, 'RP1_sink', 1.0)
self.assertTrue(rpsbml)
self.assertAlmostEqual(obj_value, 2.3076923076923888)
# make sure that the results are written to the file
all_json = rpsbml.genJSON()
self.assertAlmostEqual(all_json['pathway']['brsynth']['fba_obj_RP1_sink__restricted_biomass']['value'], 2.3076923076923888)
self.assertAlmostEqual(all_json['pathway']['brsynth']['fba_obj_biomass']['value'], 3.6794124272706443)
def test_print_rpSBML(self):
rpsbml = rpSBML(name='rpSBML_test')
rpsbml.genericModel('RetroPath_Pathway_test', 'RP_model_test',
self.comp_xref, 'MNXC3', 999999, 0)
rpsbml.createPathway('rp_pathway')
rpsbml.createPathway('central_species')
with NamedTemporaryFile() as tempf:
rpsbml.writeSBML(tempf.name)
self.assertListEqual(
list(io_open(tempf.name)),
list(io_open(os_path.join('data', 'rpSBML_test_sbml.xml'))))
def addInChiKey(self, input_sbml, output_sbml):
"""Check the MIRIAM annotation for MetaNetX or CHEBI id's and try to recover the inchikey from cache and add it to MIRIAM
:param input_sbml: SBML file input
:param output_sbml: Output SBML file
:type input_sbml: str
:type output_sbml: str
:rtype: bool
:return: Success or failure of the function
"""
filename = input_sbml.split('/')[-1].replace('.rpsbml', '').replace(
'.sbml', '').replace('.xml', '')
self.logger.debug(filename)
rpsbml = rpSBML(inFile=input_sbml)
for spe in rpsbml.getModel().getListOfSpecies():
inchikey = None
miriam_dict = rpsbml.readMIRIAMAnnotation(spe.getAnnotation())
if 'inchikey' in miriam_dict:
self.logger.info('The species ' + str(spe.id) +
' already has an inchikey... skipping')
continue
try:
for mnx in miriam_dict['metanetx']:
inchikey = self.cid_strc[self.rpcache._checkCIDdeprecated(
mnx, self.deprecatedCID_cid)]['inchikey']
if inchikey:
rpsbml.addUpdateMIRIAM(spe, 'species',
{'inchikey': [inchikey]})
else:
self.logger.warning('The inchikey is empty for: ' +
str(spe.id))
continue
except KeyError:
try:
for chebi in miriam_dict['chebi']:
inchikey = self.cid_strc[
self.rpcache._checkCIDdeprecated(
self.chebi_cid[chebi],
self.deprecatedCID_cid)]['inchikey']
if inchikey:
rpsbml.addUpdateMIRIAM(spe, 'species',
{'inchikey': [inchikey]})
else:
self.logger.warning('The inchikey is empty for: ' +
str(spe.id))
continue
except KeyError:
self.logger.warning('Cannot find the inchikey for: ' +
str(spe.id))
writeSBMLToFile(rpsbml.document, output_sbml)
return True
def test_createReturnFluxParameter(self):
#return feature
param = self.rpsbml.createReturnFluxParameter(None,
parameter_id='B_999999')
self.assertEqual(param.id, 'B_999999')
self.assertEqual(param.value, 999999.0)
#create feature
new = rpSBML('test')
new.createModel('test_name', 'test_id')
param = new.createReturnFluxParameter(8888.0)
self.assertEqual(param.id, 'B_8888_0')
self.assertEqual(param.value, 8888.0)
def runFBA(
sbml_path,
gem_sbml,
outFile,
sim_type,
source_reaction,
target_reaction,
source_coefficient,
target_coefficient,
is_max,
fraction_of,
dont_merge=True,
pathway_id='rp_pathway',
objective_id=None,
compartment_id='MNXC3',
# fill_orphan_species=False,
species_group_id='central_species',
sink_species_group_id='rp_sink_species',
logger=None):
"""Single rpSBML simulation
:param file_name: The name of the model
:param sbml_path: Path to the rpSBML file
:param gem_sbml: Path to the GEM file
:param sim_type: The type of simulation to use. Available simulation types include: fraction, fba, rpfba
:param source_reaction: The reaction id of the source reaction.
:param target_reaction: The reaction id of the target reaction. Note that if fba or rpfba options are used, then these are ignored
:param source_coefficient: The source coefficient
:param target_coefficient: The target coefficient
:param is_max: Maximise or minimise the objective
:param fraction_of: The fraction of the optimum. Note that this value is ignored is fba is used
:param tmpOutputFolder: The path to the output document
:param dont_merge: Output the merged model (Default: True)
:param pathway_id: The id of the heterologous pathway (Default: rp_pathway)
:param objective_id: Overwrite the auto-generated id of the results (Default: None)
:param compartment_id: The SBML compartment id (Default: MNXC3)
:param fill_orphan_species: Add pseudo reactions that consume/produce single parent species. Note in development
:param species_group_id: The id of the central species (Default: central_species)
:param sink_species_group_id: The id of the sink species (Default: rp_sink_species)
:type inputTar: str
:type gem_sbml: str
:type sim_type: str
:type source_reaction: str
:type target_reaction: str
:type source_coefficient: float
:type target_coefficient: float
:type is_max: bool
:type fraction_of: float
:type tmpOutputFolder: str
:type dont_merge: bool
:type num_workers: int
:type pathway_id: str
:type objective_id: str
:type compartment_id: str
:type fill_orphan_species: bool
:type species_group_id: str
:type sink_species_group_id: str
:return: Succcess or failure of the function
:rtype: bool
"""
logger = logger or logging.getLogger(__name__)
logger.info('--------- ' + str(outFile) + ' ------------')
rpsbml = rpSBML(sbml_path, logger=logger)
# Save the central species
groups = rpsbml.getModel().getPlugin('groups')
central = groups.getGroup(species_group_id)
sink_group = groups.getGroup(sink_species_group_id)
rp_group = groups.getGroup(pathway_id)
cent_spe = [str(i.getIdRef()) for i in central.getListOfMembers()]
sink_spe = [str(i.getIdRef()) for i in sink_group.getListOfMembers()]
rp_reac = [str(i.getIdRef()) for i in rp_group.getListOfMembers()]
logger.debug('old central species: ' + str(cent_spe))
logger.debug('old sink species: ' + str(sink_spe))
logger.debug('old rp reactions: ' + str(rp_reac))
rpsbml_gem = rpSBML(gem_sbml, logger=logger)
species_source_target, reactions_convert = rpSBML.mergeModels(
rpsbml, rpsbml_gem, logger)
# NOTE: reactions_convert is organised with key being the rpsbml reaction and value being the rpsbml_gem value`
# BUG: when merging the RP1_sink (very rare cases) can be recognised if another reaction contains the same species as a reactant
## under such as scenario the algorithm will consider that they are the same -- TODO: overwrite it
if target_reaction in reactions_convert:
logger.warning('The target_reaction (' + str(target_reaction) +
') has been detected in model ' + str(outFile) +
', ignoring this model...')
return False
rev_reactions_convert = {v: k for k, v in reactions_convert.items()}
logger.debug('species_source_target: ' + str(species_source_target))
logger.debug('reactions_convert: ' + str(reactions_convert))
logger.debug('rev_reactions_convert: ' + str(rev_reactions_convert))
# TO TEST MERGE: TO REMOVE
# rpsbml_gem.modelName = 'test'
# rpsbml_gem.writeSBML('/home/mdulac/workspace/Galaxy-SynBioCAD/rpFBA/rpFBA_image/tmp_out/')
####### fraction of reaction ######
# Choose the good function according to 'sim_type' argument
sim_func = globals()['rp_' + sim_type]
obj_val, rpsbml_gem = sim_func(rpsbml_gem, source_reaction,
source_coefficient, target_reaction,
target_coefficient, fraction_of, is_max,
pathway_id, objective_id, logger)
# ####### FBA ########
# elif sim_type=='fba':
# obj_val,rpsbml_gem = fba(rpsbml_gem,
# source_reaction, source_coefficient,
# target_reaction, target_coefficient,
# fraction_of,
# is_max,
# pathway_id, objective_id)
# ####### pFBA #######
# elif sim_type=='pfba':
# obj_val,rpsbml_gem = pfba(rpsbml_gem,
# source_reaction, source_coefficient,
# target_reaction, target_coefficient,
# fraction_of,
# is_max,
# pathway_id, objective_id)
# else:
# logger.error('Cannot recognise sim_type: '+str(sim_type))
'''
###### multi objective #####
elif sim_type=='multi_fba':
rpfba.runMultiObjective(reactions, coefficients, is_max, pathway_id)
'''
if dont_merge:
logger.info('Returning model with heterologous pathway only')
groups = rpsbml_gem.getModel().getPlugin('groups')
rp_pathway = groups.getGroup(pathway_id)
logger.debug('---- Reactions ----')
for member in rp_pathway.getListOfMembers():
#### reaction annotation
logger.debug(member.getIdRef())
reacFBA = rpsbml_gem.getModel().getReaction(member.getIdRef())
logger.debug(reacFBA)
try:
#reacIN = rpsbml.model.getReaction(reactions_convert[member.getIdRef()])
reacIN = rpsbml.getModel().getReaction(
rev_reactions_convert[member.getIdRef()])
except KeyError:
reacIN = rpsbml.getModel().getReaction(member.getIdRef())
logger.debug(reacIN)
logger.debug(reacFBA.getAnnotation())
reacIN.setAnnotation(reacFBA.getAnnotation())
#### species TODO: only for shadow price
#### add groups ####
source_groups = rpsbml_gem.getModel().getPlugin('groups')
target_groups = rpsbml.getModel().getPlugin('groups')
target_groupsID = [i.getId() for i in target_groups.getListOfGroups()]
for source_group in source_groups.getListOfGroups():
logger.info('Replacing group id: ' + str(source_group.getId()))
if source_group.getId() == species_group_id:
target_group = target_groups.getGroup(source_group.getId())
# TODO: #### replace the new potentially incorect central species with the normal ones #####
# delete all the previous members
logger.info('Removing central_species')
for i in range(target_group.getNumMembers()):
logger.debug('Deleting group member: ' +
str(target_group.getMember(0).getIdRef()))
target_group.removeMember(0)
# add the new ones
for cs in cent_spe:
logger.info('Creating new member: ' + str(cs))
newM = target_group.createMember()
newM.setIdRef(cs)
elif source_group.getId() == sink_species_group_id:
target_group = target_groups.getGroup(source_group.getId())
logger.info('Removing sink species')
for i in range(target_group.getNumMembers()):
logger.info('Deleting group member: ' +
str(target_group.getMember(0).getIdRef()))
target_group.removeMember(0)
#add the new ones
for cs in sink_spe:
logger.info('Creating new member: ' + str(cs))
newM = target_group.createMember()
newM.setIdRef(cs)
elif source_group.getId() in target_groupsID:
target_group = target_groups.getGroup(source_group.getId())
target_group.setAnnotation(source_group.getAnnotation())
'''
elif source_group.getId()==pathway_id:
target_group = target_groups.getGroup(source_group.getId())
logger.debug('Removing rp ractions')
for i in range(target_group.getNumMembers()):
logger.debug('Deleting group member: '+str(target_group.getMember(0).getIdRef()))
target_group.removeMember(0)
#add the new ones
for cs in rp_reac:
logger.debug('Creating new member: '+str(cs))
newM = target_group.createMember()
newM.setIdRef(cs)
'''
#### add objectives ####
source_fbc = rpsbml_gem.getModel().getPlugin('fbc')
target_fbc = rpsbml.getModel().getPlugin('fbc')
target_objID = [i.getId() for i in target_fbc.getListOfObjectives()]
for source_obj in source_fbc.getListOfObjectives():
source_obj_id = source_obj.getId()
if source_obj.getId() in target_objID:
target_obj = target_fbc.getObjective(source_obj.getId())
target_obj.setAnnotation(source_obj.getAnnotation())
for target_fluxObj in target_obj.getListOfFluxObjectives():
for source_fluxObj in source_obj.getListOfFluxObjectives():
if target_fluxObj.getReaction(
) == source_fluxObj.getReaction():
target_fluxObj.setAnnotation(
source_fluxObj.getAnnotation())
else:
target_fbc.addObjective(source_obj)
#rpsbml.createMultiFluxObj('obj_RP1_sink', ['RP1_sink'], [1])
target_fbc.setActiveObjectiveId(
source_obj_id) #tmp random assigenement of objective
rpsbml.writeSBML(outFile)
else:
logger.info('Returning the full model')
rpsbml_gem.writeSBML(outFile)
return True
def test_initWithNothing(self):
rpsbml = rpSBML()
self.assertEqual(rpsbml.getName(), 'dummy')
def test_initWithModelName(self):
rpsbml = rpSBML(name=self.rpsbml.getName())
self.assertEqual(rpsbml.getName(), self.rpsbml_name)
def test_initWithDocument(self):
rpsbml = rpSBML(document=self.rpsbml.getDocument())
self.assertEqual(rpsbml.getName(), self.rpsbml_name)
def test_initEmpty(self):
rpSBML('rpSBML_test')
def setUp(self):
# load a rpSBML file
rpsbml = rpSBML(
os_path.join(os_path.dirname(__file__), 'data', 'rpsbml.xml'))
self.rpgraph = rpGraph(rpsbml)