def get_medium(model, pflag=True):
'''!
Function to list the medium in a model, with Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
medium = model.medium
print('')
count = 1
result = []
if pflag:
print('Number : Component : Rate (mmol/gDW/h)')
for cpd in medium:
if pflag:
print('%s : %s : %s' % \
(count, cpd, str(medium[cpd])))
result.append([count, cpd, str(medium[cpd])])
count = count + 1
return result
def flux_balance_analysis(model,
analysis='FBA',
result_type='objective',
pflag=True):
'''!
Function to simulate a model using Flux Balance Analysis (FBA)
or FBA-related methods, with Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@analysis String: Type of FBA to perform. Allowable types are
FBA (standard flux balance analysis) and pFBA (parsimonious
FBA). Default value = FBA.
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
@result_type String: Type of result to give. Allowable types
are objective (objective value from FBA) or flux (table of
fluxes).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
result = _fba(model, analysis)
result = _fba_result(result, result_type, analysis, pflag)
return result
def get_reaction_names(model, pflag=True):
'''!
Function to list the reaction names in a model, with Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
print('')
count = 1
result = []
if pflag:
print(
'Number : Reaction ID : Upper Bound : Lower Bound : Reaction Name')
for rxn in model.reactions:
if pflag:
print('%s : %s : %s : %s : %s' % \
(count, rxn.id, rxn.upper_bound,
rxn.lower_bound, rxn.name))
result.append(
[count, rxn.id, rxn.upper_bound, rxn.lower_bound, rxn.name])
count = count + 1
return result
def mutantFBA(model,
mutation,
analysis='FBA',
result_type='objective',
pflag=True):
'''!
Function to simulate a model after adding mutation(s) using
Flux Balance Analysis (FBA) or FBA-related methods, with Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@mutation String: String to define mutation(s). Each mutation
is defined as <reaction ID>:<upper bound>:<lower bound>. For
example, RBFK,0,0 will represent a knock out. Multiple mutations
are delimited using semicolon.
@analysis String: Type of FBA to perform. Allowable types are
FBA (standard flux balance analysis) and pFBA (parsimonious
FBA). Default value = FBA.
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
@result_type String: Type of result to give. Allowable types
are objective (objective value from FBA) or flux (table of
fluxes).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
mutation = _parse_mutation(mutation)
model = _perform_mutation(model, mutation)
result = _fba(model, analysis)
result = _fba_result(result, result_type, analysis, pflag)
return result
def test_load_model_pickle_handle(self):
with open(os.path.join(TESTDIR, 'data/iJO1366.pickle'),
'rb') as handle:
model = load_model(handle, solver_interface=self.interface)
self.assertAlmostEqual(model.optimize().f,
0.9823718127269768,
places=6)
def mediumFBA(model,
change,
analysis='FBA',
result_type='objective',
pflag=True):
'''!
Function to simulate a model after changing medium conditions(s)
using Flux Balance Analysis (FBA) or FBA-related methods, with
Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@change String: String to define medium change(s). Each change
is defined as <compound ID>:<new value>. For example, EX_o2_e,0
will represent anaerobic condition. Multiple changes are delimited
using semicolon.
@analysis String: Type of FBA to perform. Allowable types are
FBA (standard flux balance analysis) and pFBA (parsimonious
FBA). Default value = FBA.
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
@result_type String: Type of result to give. Allowable types
are objective (objective value from FBA) or flux (table of
fluxes).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
change = _parse_medium_change(change)
model = _perform_medium_change(model, change)
result = _fba(model, analysis)
result = _fba_result(result, result_type, analysis, pflag)
return result
def get_reaction_compounds(model, pflag=True):
'''!
Function to list the reactants and products for each reaction
in a model, with Cameo.
@model String: Model acceptable by Cameo (see
http://cameo.bio/02-import-models.html).
@pflag Boolean: Flag to enable printing of results. Default =
True (results are printed).
'''
import cameo
_cameo_header()
print('Load model: %s' % str(model))
model = cameo.load_model(model)
print('')
count = 1
result = []
if pflag:
print('Number : Reaction ID : Reactants : Products : Reaction Name')
for rxn in model.reactions:
rxn_id = rxn.id
rxn_name = rxn.name
reactants = [r.id for r in rxn.reactants]
products = [p.id for p in rxn.products]
if pflag:
print('%s : %s : %s : %s : %s' % \
(count, rxn_id, '|'.join(reactants),
'|'.join(products), rxn.name))
result.append([count, rxn_id, reactants, products, rxn.name])
count = count + 1
return result
def write_results():
"""optimize results and write out to a file"""
from cameo import load_model, fba
outF = open("KOFBAFluxes-2.txt","w")
model = load_model('KOmodel.json')
print(len(model.genes))
print(len(model.metabolites))
print(len(model.reactions))
# new_solution = model.optimize()
fba_result = fba(model)
print(fba_result)
# print(fba_result.data_frame)
print(len(fba_result.data_frame))
# print(model.reactions)
print(dir(fba_result))
print(fba_result.data_frame)
fbaD = fba_result.data_frame.T.to_dict()
fbaCorrD = {}
for keyS, valueF in fbaD.items():
fbaCorrD[keyS] = valueF["flux"]
for keyS, valueF in fbaCorrD.items():
# print(keyS, valueF)
outF.write(str(keyS) + ", " + str(valueF) + "\n")
def setUpClass(cls):
cls.model = load_model(os.path.join(TESTDIR, 'data', 'EcoliCore.xml'))
cls.cad_reaction = Reaction(id="CAD", name="Cis-Aconitate Decarboxylase")
acon_C_c = cls.model.metabolites.acon_dsh_C_c
co2_c = cls.model.metabolites.co2_c
ita_c = Metabolite(id="ita_c", name="Itaconate", compartment="c")
cls.cad_reaction.add_metabolites({acon_C_c: -1, co2_c: 1, ita_c: 1})
def test_load_model_sbml_path_set_none_interface(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'),
solver_interface=None)
self.assertAlmostEqual(model.optimize().f,
0.8739215069684306,
places=6)
self.assertTrue(isinstance(model, cobra.core.Model))
self.assertFalse(hasattr(model, 'solver'))
def find_pathway(model, product, max_prediction=4):
import cameo
_cameo_header()
model = cameo.load_model(model)
predictor = cameo.strain_design.pathway_prediction.PathwayPredictor(model)
pathways = predictor.run(product=str(product),
max_predictions=max_predictions)
for rxnID in pathways.pathways[0].data_frame['equation'].keys():
print()
def test_change_solver_to_cplex_and_check_copy_works(self):
# First, load model from scratch
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'), solver_interface='cplex')
self.assertAlmostEqual(model.optimize().f, 0.8739215069684306)
model_copy = model.copy()
self.assertAlmostEqual(model_copy.optimize().f, 0.8739215069684306)
# Second, change existing glpk based model to cplex
self.model.solver = 'cplex'
self.assertAlmostEqual(self.model.optimize().f, 0.8739215069684306)
model_copy = copy.copy(self.model)
self.assertAlmostEqual(model_copy.optimize().f, 0.8739215069684306)
def test_change_solver_to_cplex_and_check_copy_works(self):
# First, load model from scratch
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'),
solver_interface='cplex')
self.assertAlmostEqual(model.optimize().f, 0.8739215069684306)
model_copy = model.copy()
self.assertAlmostEqual(model_copy.optimize().f, 0.8739215069684306)
# Second, change existing glpk based model to cplex
self.model.solver = 'cplex'
self.assertAlmostEqual(self.model.optimize().f, 0.8739215069684306)
model_copy = copy.copy(self.model)
self.assertAlmostEqual(model_copy.optimize().f, 0.8739215069684306)
def update_local_models(model_id, model_store=None):
"""Update locally stored models.
Annotate model metabolites with CHEBI identifiers and store them locally for easy access.
:param model_id: string, model identifier
:param model_store: path to directory where to store the processed models.
"""
model_store = model_store or 'data/models'
if model_id in LOCAL_MODELS:
sbml_file = os.path.join(model_store, 'original',
model_id + '.sbml.gz')
model = read_sbml_model(sbml_file)
else:
model = load_model(model_id)
# annotate metabolites
namespace = storage.get(model_id).namespace
metabolite_namespace = MODEL_METABOLITE_NAMESPACE[model_id]
db_name = 'CHEBI'
metabolites_missing_annotation = [
m.id for m in model.metabolites
if len(m.annotation.get(db_name, [])) < 1
]
model_xref = sync_query_identifiers([
strip_compartment[namespace](mid)
for mid in metabolites_missing_annotation
], namespace, db_name)
for metabolite_id in metabolites_missing_annotation:
compound_id = strip_compartment[namespace](metabolite_id)
if compound_id in model_xref:
metabolite = model.metabolites.get_by_id(metabolite_id)
if db_name not in metabolite.annotation:
metabolite.annotation[db_name] = []
metabolite.annotation[db_name].extend([
f'{db_name}:{i}' if not i.startswith(f"{db_name}:") else i
for i in model_xref[compound_id]
])
# TODO: For some reason, id-mapper doesn't make this link, add manually for now
if compound_id in GLUCOSE and db_name == 'CHEBI':
metabolite.annotation[db_name].append('CHEBI:42758')
if metabolite_namespace not in metabolite.annotation:
metabolite.annotation[metabolite_namespace] = []
metabolite.annotation[metabolite_namespace].append(compound_id)
# gecko protein exchanges
db_name = 'uniprot'
protein_exchanges = model.reactions.query(
lambda rxn: re.match(r'^prot_.*_exchange$', rxn.id))
for rxn in protein_exchanges:
rxn.annotation[db_name] = [
re.findall('^prot_(.*)_exchange$', rxn.id)[0]
]
write_sbml_model(model, os.path.join(model_store, model_id + '.sbml.gz'))
def test_all_objects_point_to_all_other_correct_objects(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
for reaction in model.reactions:
self.assertEqual(reaction.model, model)
for gene in reaction.genes:
self.assertEqual(gene, model.genes.get_by_id(gene.id))
self.assertEqual(gene.model, model)
for reaction2 in gene.reactions:
self.assertEqual(reaction2.model, model)
self.assertEqual(reaction2, model.reactions.get_by_id(reaction2.id))
for metabolite in reaction.metabolites:
self.assertEqual(metabolite.model, model)
self.assertEqual(metabolite, model.metabolites.get_by_id(metabolite.id))
for reaction2 in metabolite.reactions:
self.assertEqual(reaction2.model, model)
self.assertEqual(reaction2, model.reactions.get_by_id(reaction2.id))
def test_all_objects_point_to_all_other_correct_objects(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
for reaction in model.reactions:
self.assertEqual(reaction.model, model)
for gene in reaction.genes:
self.assertEqual(gene, model.genes.get_by_id(gene.id))
self.assertEqual(gene.model, model)
for reaction2 in gene.reactions:
self.assertEqual(reaction2.model, model)
self.assertEqual(
reaction2, model.reactions.get_by_id(reaction2.id))
for metabolite in reaction.metabolites:
self.assertEqual(metabolite.model, model)
self.assertEqual(
metabolite, model.metabolites.get_by_id(metabolite.id))
for reaction2 in metabolite.reactions:
self.assertEqual(reaction2.model, model)
self.assertEqual(
reaction2, model.reactions.get_by_id(reaction2.id))
def find_gene():
"""create optimized model from json file and find genes and reactions in it"""
from cameo import load_model
# [('HGNC:1093', 0.8281729165648598), ('HGNC:8889', 0.8281729165648598), ('HGNC:8888', 0.8281729165648598), ('HGNC:8898', 0.8281729165648598), ('HGNC:8896', 0.8281729165648598),
# ('HGNC:16270', 0.6949058320029933), ('HGNC:8124', 0.6), ('HGNC:3700', 0.6), ('HGNC:4336', 0.6), ('HGNC:4335', 0.6)]
model = load_model('WTmodel.json')
print(len(model.genes))
print(len(model.metabolites))
print(len(model.reactions))
model.optimize()
for modelO in model.reactions:
# print(dir(modelO))
# print(modelO.name, modelO.reaction, modelO.nice_id, modelO.annotation)
if str(modelO.nice_id) == "PGK":
print(modelO.name, modelO.reaction, modelO.nice_id, modelO.annotation, modelO.flux)
elif str(modelO.nice_id) == "O2t":
print(modelO.name, modelO.reaction, modelO.nice_id, modelO.annotation, modelO.flux)
def test_iMM904_4HGLSDm_problem(self):
model = load_model(os.path.join(TESTDIR, 'data/iMM904.xml'))
# set upper bound before lower bound after knockout
cp = model.copy()
rxn = cp.reactions.get_by_id('4HGLSDm')
prev_lb, prev_ub = rxn.lower_bound, rxn.upper_bound
rxn.lower_bound = 0
rxn.upper_bound = 0
rxn.upper_bound = prev_ub
rxn.lower_bound = prev_lb
self.assertEquals(rxn.lower_bound, prev_lb)
self.assertEquals(rxn.upper_bound, prev_ub)
# set lower bound before upper bound after knockout
cp = model.copy()
rxn = cp.reactions.get_by_id('4HGLSDm')
prev_lb, prev_ub = rxn.lower_bound, rxn.upper_bound
rxn.lower_bound = 0
rxn.upper_bound = 0
rxn.lower_bound = prev_lb
rxn.upper_bound = prev_ub
self.assertEquals(rxn.lower_bound, prev_lb)
self.assertEquals(rxn.upper_bound, prev_ub)
def test_iMM904_4HGLSDm_problem(self):
model = load_model(os.path.join(TESTDIR, 'data/iMM904.xml'))
# set upper bound before lower bound after knockout
cp = model.copy()
rxn = cp.reactions.get_by_id('4HGLSDm')
prev_lb, prev_ub = rxn.lower_bound, rxn.upper_bound
rxn.lower_bound = 0
rxn.upper_bound = 0
rxn.upper_bound = prev_ub
rxn.lower_bound = prev_lb
self.assertEquals(rxn.lower_bound, prev_lb)
self.assertEquals(rxn.upper_bound, prev_ub)
# set lower bound before upper bound after knockout
cp = model.copy()
rxn = cp.reactions.get_by_id('4HGLSDm')
prev_lb, prev_ub = rxn.lower_bound, rxn.upper_bound
rxn.lower_bound = 0
rxn.upper_bound = 0
rxn.lower_bound = prev_lb
rxn.upper_bound = prev_ub
self.assertEquals(rxn.lower_bound, prev_lb)
self.assertEquals(rxn.upper_bound, prev_ub)
def test_load_model_sbml_path_set_none_interface(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'),
solver_interface=None)
assert abs(model.optimize().f - 0.8739215069684306) < 10e-6
assert isinstance(model, cobra.core.Model)
assert not hasattr(model, 'solver')
def test_load_model_sbml_path(self, solver_interface):
model = load_model(os.path.join(TESTDIR, 'data/iJO1366.xml'),
solver_interface=solver_interface)
assert abs(model.optimize().f - 0.9823718127269768) < 10e-6
from cameo import load_model
from cameo.flux_analysis import phenotypic_phase_plane
import os
TESTDIR = os.path.dirname(__file__)
CORE_MODEL = load_model(os.path.join(TESTDIR, 'EcoliCore.xml'), sanitize=False)
model = CORE_MODEL.copy()
model.solver = 'glpk'
ppp = phenotypic_phase_plane(model, ['EX_o2_LPAREN_e_RPAREN_'])
ppp.data_frame.to_csv(os.path.join(TESTDIR, 'REFERENCE_PPP_o2_EcoliCore.csv'),
float_format='%.3f')
model = CORE_MODEL.copy()
model.solver = 'glpk'
ppp2d = phenotypic_phase_plane(
model, ['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'])
ppp2d.data_frame.to_csv(os.path.join(TESTDIR,
'REFERENCE_PPP_o2_glc_EcoliCore.csv'),
float_format='%.3f')
model = CORE_MODEL.copy()
model.solver = 'glpk'
objective = model.add_boundary(model.metabolites.ac_c, type='demand')
model.objective = objective
ppp = phenotypic_phase_plane(model, ['EX_o2_LPAREN_e_RPAREN_'])
ppp.data_frame.to_csv(os.path.join(TESTDIR,
'REFERENCE_PPP_o2_EcoliCore_ac.csv'),
float_format='%.3f')
def core_model(request, data_directory):
ecoli_core = load_model(join(data_directory, 'EcoliCore.xml'), sanitize=False)
ecoli_core.solver = request.param
return ecoli_core
def imm904(request, data_directory):
imm = load_model(join(data_directory, 'iMM904.xml'))
imm.solver = request.param
return imm.copy()
def iaf1260(data_directory):
return load_model(join(data_directory, 'iAF1260.xml'))
def test_load_model_pickle_path(self, solver_interface):
model = load_model(os.path.join(TESTDIR, 'data/iJO1366.pickle'), solver_interface=solver_interface)
assert abs(model.optimize().objective_value - 0.9823718127269768) < 10e-6
def test_load_model_sbml_handle(self, solver_interface):
with open(os.path.join(TESTDIR, 'data/iJO1366.xml')) as handle:
model = load_model(handle, solver_interface=solver_interface)
assert abs(model.slim_optimize() - 0.9823718127269768) < 10e-6
def test_load_model_sbml_path_set_none_interface(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'), solver_interface=None)
assert abs(model.slim_optimize() - 0.8739215069684306) < 10e-6
assert isinstance(model, cobra.Model)
def test_invalid_path(self):
with pytest.raises(Exception):
load_model("blablabla_model")
# limitations under the License.
import os
import pickle
import re
import pytest
from cameo import api, load_model
from cameo import models, config
from cameo.api.hosts import Host
from cameo.api.products import Compound
MODELS = os.path.dirname(models.__file__)
UNIVERSALMODEL = load_model(os.path.join(MODELS, 'json/iJO1366.json'))
UNIVERSALMODEL.remove_reactions(UNIVERSALMODEL.boundary)
def test_api():
mock_host = Host('core',
models=['e_coli_core'],
biomass=['BIOMASS_Ecoli_core_w_GAM'],
carbon_sources=['EX_glc__D_e'])
api.design.debug = True
pathways = api.design.predict_pathways(
product=UNIVERSALMODEL.metabolites.ser__L_c,
hosts=[mock_host],
database=UNIVERSALMODEL,
aerobic=True)
# If single knockout causes the constrained model to become infeasible, then no superset
# of knockouts can be feasible either.
with TimeMachine() as tm:
reaction.knock_out(tm)
try:
self._primal_model.solve()
except Infeasible:
illegal_knockouts.append(reaction.id)
self._illegal_knockouts = illegal_knockouts
return cloned_constraints
if __name__ == '__main__':
from cameo import load_model
model = load_model("e_coli_core")
# model = load_model('../../tests/data/EcoliCore.xml')
model.reactions.ATPM.lower_bound, model.reactions.ATPM.upper_bound = 0, 1000.
model.reactions.BIOMASS_Ecoli_core_w_GAM.lower_bound = 1
model.solver = 'cplex'
shortest_emo = ShortestElementaryFluxModes(model)
# s.model.solver.configuration.verbosity = 3
count = 0
for emo in shortest_emo:
if count == 1000:
break
count += 1
print(str(count) + " " + 80 * "#")
print(len(emo))
for reaction in emo:
print(reaction, reaction.lower_bound, reaction.upper_bound)
# Smoketest for Docker images
# Execute few commands to see if cameo images function somehow
from aiozmq import rpc # included because on Alpine Linux it leads to segfault
from cameo import models, load_model
model = load_model('iJO1366') # does not rely on connection to BIGG database
model.solve()
print('Test OK')
def pathway_predictor(request, data_directory, universal_model):
core_model = load_model(join(data_directory, 'EcoliCore.xml'), sanitize=False)
core_model.solver = request.param
predictor = PathwayPredictor(core_model, universal_model=universal_model)
return core_model, predictor
# If single knockout causes the constrained model to become infeasible, then no superset
# of knockouts can be feasible either.
with TimeMachine() as tm:
reaction.knock_out(tm)
try:
self._primal_model.solve()
except Infeasible:
illegal_knockouts.append(reaction.id)
self._illegal_knockouts = illegal_knockouts
return cloned_constraints
if __name__ == '__main__':
from cameo import load_model
model = load_model("e_coli_core")
# model = load_model('../../tests/data/EcoliCore.xml')
model.reactions.ATPM.lower_bound, model.reactions.ATPM.upper_bound = 0, 1000.
model.reactions.BIOMASS_Ecoli_core_w_GAM.lower_bound = 1
model.solver = 'cplex'
shortest_emo = ShortestElementaryFluxModes(model)
# s.model.solver.configuration.verbosity = 3
count = 0
for emo in shortest_emo:
if count == 1000:
break
count += 1
print(str(count) + " " + 80 * "#")
print(len(emo))
for reaction in emo:
print(reaction, reaction.lower_bound, reaction.upper_bound)
def universal_model(data_directory):
universal = load_model(join(data_directory, 'iJO1366.xml'), sanitize=False)
universal.remove_reactions(universal.boundary)
return universal
# limitations under the License.
import os
import pickle
import re
import pytest
from cameo import api, load_model
from cameo import models, config
from cameo.api.hosts import Host
from cameo.api.products import Compound
MODELS = os.path.dirname(models.__file__)
UNIVERSALMODEL = load_model(os.path.join(MODELS, 'json/iJO1366.json'))
UNIVERSALMODEL.remove_reactions(UNIVERSALMODEL.boundary)
def test_api():
mock_host = Host('core',
models=['e_coli_core'],
biomass=['BIOMASS_Ecoli_core_w_GAM'],
carbon_sources=['EX_glc__D_e'])
api.design.debug = True
pathways = api.design.predict_pathways(product=UNIVERSALMODEL.metabolites.ser__L_c, hosts=[mock_host],
database=UNIVERSALMODEL, aerobic=True)
optimization_reports = api.design.optimize_strains(pathways, config.default_view, aerobic=True)
pickle.loads(pickle.dumps(optimization_reports))
assert len(optimization_reports) > 0
def toy_model(request, data_directory):
toy = load_model(join(data_directory, "toy_model_Papin_2003.xml"))
toy.solver = request.param
return toy
def test_load_model_pickle_handle(self):
with open(os.path.join(TESTDIR, 'data/iJO1366.pickle'), 'rb') as handle:
model = load_model(handle, solver_interface=self.interface)
self.assertAlmostEqual(model.optimize().f, 0.9823718127269768)
def lazy_model_init(path):
model = load_model(path)
setattr(model, "biomass", biomass)
setattr(model, "carbon_source", carbon_source)
return model
except requests.ConnectionError:
bigg.no_models_available = "Cameo couldn't reach http://bigg.ucsd.edu at initialization time. Are you connected to the internet?"
except Exception as e:
bigg.no_models_available = "Cameo could reach http://bigg.ucsd.edu at initialization time but something went wrong while decoding the server response."
logger.debug(e)
else:
for id in model_ids:
setattr(bigg, str_to_valid_variable_name(id), lazy_object_proxy.Proxy(partial(get_model_from_bigg, id)))
minho = ModelDB()
try:
minho_models = index_models_minho()
except requests.ConnectionError as e:
minho.no_models_available = "Cameo couldn't reach http://darwin.di.uminho.pt/models at initialization time. Are you connected to the internet?"
logger.debug(e)
except Exception as e:
minho.no_models_available = "Cameo could reach http://darwin.di.uminho.pt/models at initialization time but something went wrong while decoding the server response."
logger.debug(e)
else:
model_indices = minho_models.id
model_ids = minho_models.name
for index, id in zip(model_indices, model_ids):
setattr(minho, str_to_valid_variable_name(id), lazy_object_proxy.Proxy(partial(get_model_from_uminho, index)))
if __name__ == "__main__":
print(index_models_minho())
from cameo import load_model
model = load_model(get_sbml_file(2))
print(model.objective)
set_mutation, set_indel, multiple_chromosome_set_mutation, multiple_chromosome_set_indel
from cameo.util import RandomGenerator as Random
TRAVIS = os.getenv('TRAVIS', False)
if os.getenv('REDIS_PORT_6379_TCP_ADDR'):
REDIS_HOST = os.getenv('REDIS_PORT_6379_TCP_ADDR') # wercker
else:
REDIS_HOST = 'localhost'
SEED = 1234
CURRENT_PATH = os.path.dirname(__file__)
MODEL_PATH = os.path.join(CURRENT_PATH, "data/EcoliCore.xml")
TEST_MODEL = load_model(MODEL_PATH, sanitize=False)
SOLUTIONS = [
[[1, 2, 3], 0.1],
[[1, 3, 2, 4], 0.1],
[[2, 3, 4], 0.45],
[[62, 51, 4], 0.2],
[[5, 3, 4, 51], 0.9],
[[5, 23, 41, 51], 0.9],
[[5, 3, 4, 51, 31], 0.9],
[[5, 3, 4, 51], 0.9],
[[44, 12, 42, 51], 0.0],
[[52, 22, 4, 11], 0.0]
]
def pathway_predictor(request, data_directory, universal_model):
core_model = load_model(join(data_directory, 'EcoliCore.xml'), sanitize=False)
core_model.solver = request.param
predictor = PathwayPredictor(core_model, universal_model=universal_model)
return core_model, predictor
def test_load_model_sbml_handle(self, solver_interface):
with open(os.path.join(TESTDIR, 'data/iJO1366.xml')) as handle:
model = load_model(handle, solver_interface=solver_interface)
assert abs(model.optimize().f - 0.9823718127269768) < 10e-6
import pickle
import cobra.test
import optlang
from cameo import load_model
ijo = load_model('iJO1366.xml', solver_interface=optlang.glpk_interface)
with open('iJO1366.pickle', 'wb') as out:
pickle.dump(ijo, out, protocol=2)
salmonella = cobra.test.create_test_model('salmonella')
salmonella.solver = 'glpk'
with open('salmonella.pickle', 'wb') as out:
pickle.dump(salmonella, out, protocol=2)
def test_invalid_path(self):
with pytest.raises(Exception):
load_model("blablabla_model")
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import, print_function
import os
import unittest
from cameo import load_model
from cameo.strain_design.pathway_prediction import PathwayPredictor
from cameo.models import universal
TESTDIR = os.path.dirname(__file__)
TESTMODEL = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
UNIVERSALMODEL = load_model(os.path.join(TESTDIR, 'data/iJO1366.xml'))
TRAVIS = os.getenv('TRAVIS', False)
PATHWAYPREDICTOR = PathwayPredictor(TESTMODEL, universal_model=UNIVERSALMODEL)
class TestPathwayPredictor(unittest.TestCase):
def setUp(self):
self.pathway_predictor = PATHWAYPREDICTOR
def test_setting_incorrect_universal_model_raises(self):
with self.assertRaisesRegexp(ValueError, 'Provided universal_model.*'):
PathwayPredictor(TESTMODEL, universal_model='Mickey_Mouse')
import copy
from cameo import load_model
from cameo.methods import DifferentialFVA
from cameo.basics import production_envelope
model = load_model('../tests/data/EcoliCore.xml')
solution = model.optimize()
surrogate_experimental_fluxes = dict([(key, (val * .8, val * 1.2)) for key, val in solution.x_dict.iteritems()])
constraint_model = copy.copy(model)
for reaction_id, (lb, ub) in surrogate_experimental_fluxes.iteritems():
reaction = constraint_model.reactions.get_by_id(reaction_id)
reaction.lower_bound = lb
reaction.upper_bound = ub
diffFVA = DifferentialFVA(design_space_model=model,
reference_model=constraint_model,
target='EX_succ_LPAREN_e_RPAREN_',
variables=[model.reactions.Biomass_Ecoli_core_N_LPAREN_w_FSLASH_GAM_RPAREN__Nmet2])
print diffFVA.run()
def model(data_directory):
return load_model(join(data_directory, 'EcoliCore.xml'))
import optlang
import pandas
from sympy import Eq
from cameo import load_model, Reaction, Model
from cameo.config import solvers
from cameo.exceptions import UndefinedSolution
from cameo.core.solver_based_model import Reaction
from cameo.util import TimeMachine
import six
TRAVIS = os.getenv('TRAVIS', False)
TESTDIR = os.path.dirname(__file__)
REFERENCE_FVA_SOLUTION_ECOLI_CORE = pandas.read_csv(os.path.join(TESTDIR, 'data/REFERENCE_flux_ranges_EcoliCore.csv'),
index_col=0)
TESTMODEL = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'), sanitize=False)
COBRAPYTESTMODEL = read_sbml_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
ESSENTIAL_GENES = ['b2779', 'b1779', 'b0720', 'b0451', 'b2416', 'b2926', 'b1136', 'b2415']
ESSENTIAL_REACTIONS = ['GLNS', 'Biomass_Ecoli_core_N_LPAREN_w_FSLASH_GAM_RPAREN__Nmet2', 'PIt2r', 'GAPD', 'ACONTb',
'EX_nh4_LPAREN_e_RPAREN_', 'ENO', 'EX_h_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_', 'ICDHyr',
'CS', 'NH4t', 'GLCpts', 'PGM', 'EX_pi_LPAREN_e_RPAREN_', 'PGK', 'RPI', 'ACONTa']
class WrappedCommonGround:
class CommonGround(unittest.TestCase):
def setUp(self):
self.model = TESTMODEL.copy()
self.model.optimize()
class AbstractTestLazySolution(WrappedCommonGround.CommonGround):
def ijo1366(request, data_directory):
ijo = load_model(join(data_directory, 'iJO1366.xml'), sanitize=False)
ijo.solver = request.param
return ijo
# limitations under the License.
from __future__ import absolute_import, print_function
import os
import unittest
from cameo import load_model
from cameo.core.pathway import Pathway
from cameo.flux_analysis.analysis import PhenotypicPhasePlaneResult
from cameo.strain_design.pathway_prediction import PathwayPredictor
from cameo.strain_design.pathway_prediction.pathway_predictor import PathwayResult
from cameo.util import TimeMachine
TESTDIR = os.path.dirname(__file__)
TESTMODEL = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
UNIVERSALMODEL = load_model(os.path.join(TESTDIR, 'data/iJO1366.xml'))
UNIVERSALMODEL.remove_reactions(UNIVERSALMODEL.exchanges)
TRAVIS = os.getenv('TRAVIS', False)
PATHWAYPREDICTOR = PathwayPredictor(TESTMODEL, universal_model=UNIVERSALMODEL)
class Wrapper:
class AbstractPathwayPredictorTestCase(unittest.TestCase):
def test_setting_incorrect_universal_model_raises(self):
with self.assertRaisesRegexp(ValueError, 'Provided universal_model.*'):
PathwayPredictor(TESTMODEL, universal_model='Mickey_Mouse')
import os
import unittest
import pandas
import six
from pandas import DataFrame
from pandas.util.testing import assert_frame_equal
import cameo
from cameo import load_model
from cameo.strain_design.deterministic.flux_variability_based import FSEOF, FSEOFResult, DifferentialFVA
from cameo.strain_design.deterministic.linear_programming import OptKnock
TRAVIS = os.getenv('TRAVIS', False)
TESTDIR = os.path.dirname(__file__)
ECOLICORE = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'))
def assert_dataframes_equal(df, expected):
try:
assert_frame_equal(df, expected, check_names=False)
return True
except AssertionError:
return False
class TestFSEOF(unittest.TestCase):
def setUp(self):
self.model = ECOLICORE.copy()
self.model.solver = 'glpk'
import pickle
import cobra
from cobra.test import create_test_model
from optlang import glpk_interface
from cameo import load_model
config = cobra.Configuration()
config.solver = "glpk"
ijo = load_model('iJO1366.xml', glpk_interface)
with open('iJO1366.pickle', 'wb') as out:
pickle.dump(ijo, out, protocol=2)
salmonella = create_test_model('salmonella')
with open('salmonella.pickle', 'wb') as out:
pickle.dump(salmonella, out, protocol=2)
def test_load_model_pickle_path(self):
model = load_model(os.path.join(TESTDIR, 'data/iJO1366.pickle'), solver_interface=self.interface)
self.assertAlmostEqual(model.optimize().f, 0.9823718127269768, places=6)
builder.display_in_browser()
except ImportError:
print("Escher must be installed in order to visualize maps")
if __name__ == '__main__':
import time
from cobra.io import read_sbml_model
from cameo import load_model
# sbml_path = '../../tests/data/EcoliCore.xml'
sbml_path = '../../tests/data/iJO1366.xml'
cb_model = read_sbml_model(sbml_path)
model = load_model(sbml_path)
# model.solver = 'glpk'
# print("cobra fba")
# tic = time.time()
# cb_model.optimize(solver='cglpk')
# print("flux sum:", sum([abs(val) for val in list(cb_model.solution.x_dict.values())]))
# print("cobra fba runtime:", time.time() - tic)
# print("cobra pfba")
# tic = time.time()
# optimize_minimal_flux(cb_model, solver='cglpk')
# print("flux sum:", sum([abs(val) for val in list(cb_model.solution.x_dict.values())]))
# print("cobra pfba runtime:", time.time() - tic)
def test_load_model_sbml_handle(self):
with open(os.path.join(TESTDIR, 'data/iJO1366.xml')) as handle:
model = load_model(handle, solver_interface=self.interface)
self.assertAlmostEqual(model.optimize().f, 0.9823718127269768, places=6)
builder.display_in_browser()
except ImportError:
print("Escher must be installed in order to visualize maps")
if __name__ == '__main__':
import time
from cobra.io import read_sbml_model
from cameo import load_model
# sbml_path = '../../tests/data/EcoliCore.xml'
sbml_path = '../../tests/data/iJO1366.xml'
cb_model = read_sbml_model(sbml_path)
model = load_model(sbml_path)
# model.solver = 'glpk'
# print("cobra fba")
# tic = time.time()
# cb_model.optimize(solver='cglpk')
# print("flux sum:", sum([abs(val) for val in list(cb_model.solution.fluxes.values())]))
# print("cobra fba runtime:", time.time() - tic)
# print("cobra pfba")
# tic = time.time()
# optimize_minimal_flux(cb_model, solver='cglpk')
# print("flux sum:", sum([abs(val) for val in list(cb_model.solution.fluxes.values())]))
# print("cobra pfba runtime:", time.time() - tic)
def test_load_model_sbml_path_set_none_interface(self):
model = load_model(os.path.join(TESTDIR, 'data/EcoliCore.xml'), solver_interface=None)
self.assertAlmostEqual(model.optimize().f, 0.8739215069684306, places=6)
self.assertTrue(isinstance(model, cobra.core.Model))
self.assertFalse(hasattr(model, 'solver'))