def model_simulate(model_id, method, objective_id, objective_direction, operations):
try:
model_wrapper = storage.get(model_id)
except Unauthorized as error:
abort(401, error.message)
except Forbidden as error:
abort(403, error.message)
except ModelNotFound as error:
abort(404, error.message)
model = model_wrapper.model
# Use the context manager to undo all modifications to the shared model instance on
# completion.
with model:
apply_operations(model, operations)
try:
flux_distribution, growth_rate = simulate(
model,
model_wrapper.biomass_reaction,
method,
objective_id,
objective_direction,
)
except OptimizationError:
return jsonify({"status": model.solver.status})
else:
return jsonify(
{
"status": model.solver.status,
"flux_distribution": flux_distribution,
"growth_rate": growth_rate,
}
)
def model_community_simulate(model_ids, medium, method):
try:
model_wrappers = [storage.get(model_id) for model_id in model_ids]
except Unauthorized as error:
abort(401, error.message) # noqa: B306
except Forbidden as error:
abort(403, error.message) # noqa: B306
except ModelNotFound as error:
abort(404, error.message) # noqa: B306
return community.simulate(model_wrappers, medium, method)
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 model_modify(
model_id,
medium,
genotype,
fluxomics,
metabolomics,
uptake_secretion_rates,
molar_yields,
growth_rate,
):
if not request.is_json:
abort(415, "Non-JSON request content is not supported")
try:
model_wrapper = storage.get(model_id)
except Unauthorized as error:
abort(401, error.message)
except Forbidden as error:
abort(403, error.message)
except ModelNotFound as error:
abort(404, error.message)
# Use the context manager to undo all modifications to the shared model instance on
# completion.
with model_wrapper.model as model:
# Build list of operations to perform on the model
operations = []
warnings = []
errors = []
if medium:
results = apply_medium(model, medium)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if genotype:
results = apply_genotype(model, genotype)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if (
fluxomics
or metabolomics
or uptake_secretion_rates
or molar_yields
or growth_rate
):
results = apply_measurements(
model,
model_wrapper.biomass_reaction,
fluxomics,
metabolomics,
uptake_secretion_rates,
molar_yields,
growth_rate,
)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if errors:
# If any errors occured during modifications, discard generated operations
# and return the error messages to the client for follow-up
return {"errors": errors}, 400
else:
return {"operations": operations, "warnings": warnings}
def test_get_model_unauthorized(monkeypatch, app):
monkeypatch.setattr(requests, "get",
lambda url, headers: MockResponseUnauthorized())
g.jwt_valid = False
with pytest.raises(Unauthorized):
storage.get(11)
def test_get_model_forbidden(monkeypatch, app):
monkeypatch.setattr(requests, "get",
lambda url, headers: MockResponseForbidden())
g.jwt_valid = False
with pytest.raises(Forbidden):
storage.get(11)
def test_get_model(monkeypatch, app):
monkeypatch.setattr(requests, "get",
lambda url, headers: MockResponseSuccess())
g.jwt_valid = False
assert type(storage.get(10).model) == Model
