def get_model_from_bigg(id):
try:
response = requests.get('http://bigg.ucsd.edu/api/v2/models/{}/download'.format(id))
except requests.ConnectionError as e:
logger.error("Cannot reach http://bigg.ucsd.edu. Are you sure that you are connected to the internet?")
raise e
if response.ok:
with io.StringIO(response.text) as f:
return to_solver_based_model(load_json_model(f))
else:
raise Exception(
"Could not download model {}. bigg.ucsd.edu returned status code {}".format(id, response.status_code))
def load_model(path_or_handle, solver_interface=optlang, sanitize=True):
"""Read a metabolic model .
Parameters
----------
path_or_handle : path, fhandle or name.
One of:
* file path of a model file;
* file handle to a SBML or pickled model; or
* the identifier of a model in a web database (optflux.org/models)
solver_interface : solver_interface, optional
E.g. optlang.glpk_interface or any other optlang interface.
sanitize : boolean, optional
If reaction and metabolite IDs should be sanitized (works only for SBML models).
"""
solver_interface = solvers.get(solver_interface, solver_interface)
if isinstance(path_or_handle, six.string_types) and not os.path.isfile(path_or_handle):
from cameo.models.webmodels import load_webmodel
logger.debug("Given path is not a file. Trying to load from webmodels")
model = load_webmodel(path_or_handle, solver_interface)
else:
if isinstance(path_or_handle, six.string_types):
# Open the given file
path = path_or_handle
handle = open(path_or_handle, 'rb')
elif hasattr(path_or_handle, 'read'):
# Argument is already an open file
path = path_or_handle.name
handle = path_or_handle
else:
raise ValueError('Provided argument %s has to be either a string or a file handle' % path_or_handle)
model = _load_model_from_file(path, handle) # Parse model from the file
if sanitize:
sanitize_ids(model)
if not isinstance(model, SolverBasedModel):
if solver_interface is not None:
logger.debug("Changing solver interface to %s" % solver_interface)
model = to_solver_based_model(model, solver_interface=solver_interface)
else:
if solver_interface is not None and not isinstance(model.solver, solver_interface.Model):
logger.debug("Changing solver interface to %s" % solver_interface)
model.solver = solver_interface
return model
def get_model_from_uminho(index, host="http://darwin.di.uminho.pt/models"):
sbml_file = get_sbml_file(index, host)
sbml_file.close()
return to_solver_based_model(read_sbml_model(sbml_file.name))
def setUp(self):
# Make Model pickable and then load a solver based version of test_pickle
self.model = to_solver_based_model(create_test_model("textbook"))
def setUp(self):
# Make Model pickable and then load a solver based version of test_pickle
self.model = to_solver_based_model(create_test_model())
self.model_class = SolverBasedModel
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# 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 cobra.io import read_sbml_model
from optlang import glpk_interface
import inspyred
from cameo.strain_design.heuristic.multiprocess import MultiprocessReactionKnockoutOptimization
from cameo.strain_design.heuristic.objective_functions import biomass_product_coupled_yield
from cameo.flux_analysis.simulation import fba
from cameo.core.solver_based_model import to_solver_based_model
model = read_sbml_model("../tests/data/iJO1366.xml")
model = to_solver_based_model(model, solver_interface=glpk_interface)
of = biomass_product_coupled_yield("Ec_biomass_iJO1366_core_53p95M", "EX_ac_LPAREN_e_RPAREN_",
"EX_glc_LPAREN_e_RPAREN_")
mp = MultiprocessReactionKnockoutOptimization(model=model, heuristic_method=inspyred.ec.GA,
objective_function=of, simulation_method=fba)
mp.run(max_evaluations=300, n=2)
def model():
return to_solver_based_model(create_test_model("textbook"))
def load_model(path_or_handle, solver_interface=optlang.glpk_interface, sanitize=True):
"""Read a metabolic model .
Parameters
----------
path_or_handle : path, fhandle or name.
One of:
* file path of a model file;
* file handle to a SBML or pickled model; or
* the identifier of a model in a web database (optflux.org/models)
solver_interface : solver_interface, optional
E.g. optlang.glpk_interface or any other optlang interface.
sanitize : boolean, optional
If reaction and metabolite IDs should be sanitized (works only for SBML models).
"""
if isinstance(path_or_handle, str):
path = path_or_handle
try:
handle = open(path_or_handle, 'rb')
except IOError:
logger.debug('%s not a file path. Querying webmodels ... trying http://bigg.ucsd.edu first' % path)
try:
return cameo.models.webmodels.get_model_from_bigg(path)
except:
logger.debug('%s not a file path. Querying webmodels ... trying minho next' % path)
try:
df = cameo.models.webmodels.index_models_minho()
except requests.ConnectionError as e:
logger.error("You need to be connected to the internet to load an online model.")
raise e
except Exception as e:
logger.error("Something went wrong while looking up available webmodels.")
raise e
try:
index = df.query('name == "%s"' % path_or_handle).id.values[0]
handle = cameo.models.webmodels.get_sbml_file(index)
path = handle.name
except IndexError:
raise ValueError("%s is neither a file nor a model ID." % path)
elif hasattr(path_or_handle, 'read'):
path = path_or_handle.name
handle = path_or_handle
else:
raise ValueError('Provided argument %s has to be either a file path or handle' % path_or_handle)
logger.debug('Reading file from %s assuming pickled model.' % path)
try:
model = pickle.load(handle)
except Exception:
logger.debug('Cannot unpickle %s. Assuming json model next.' % path)
try:
model = load_json_model(path)
except Exception:
logger.debug("Cannot import %s as json model. Assuming sbml model next." % path)
try:
model = read_sbml_model(path)
except AttributeError as e:
logger.error("cobrapy doesn't raise a proper exception if a file does not contain an SBML model")
raise e
except Exception as e:
logger.error(
"Looks like something blow up while trying to import {} as a SBML model. Try validating the model at http://sbml.org/Facilities/Validator/ to get more information.".format(
path))
raise e
if sanitize:
sanitize_ids(model)
if not isinstance(model, SolverBasedModel):
if solver_interface is not None:
logger.debug("Changing solver interface to %s" % solver_interface)
model = to_solver_based_model(model, solver_interface=solver_interface)
else:
if model.interface is not solver_interface and solver_interface is not None:
logger.debug("Changing solver interface to %s" % solver_interface)
model.solver = solver_interface
return model
def setUp(self):
# Make Model pickable and then load a solver based version of test_pickle
self.model = to_solver_based_model(create_test_model())
self.model_class = SolverBasedModel
# http://www.apache.org/licenses/LICENSE-2.0
#
# 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 cobra.io import read_sbml_model
from optlang import glpk_interface
import inspyred
from cameo.strain_design.heuristic.multiprocess import MultiprocessReactionKnockoutOptimization
from cameo.strain_design.heuristic.objective_functions import biomass_product_coupled_yield
from cameo.flux_analysis.simulation import fba
from cameo.core.solver_based_model import to_solver_based_model
model = read_sbml_model("../tests/data/iJO1366.xml")
model = to_solver_based_model(model, solver_interface=glpk_interface)
of = biomass_product_coupled_yield("Ec_biomass_iJO1366_core_53p95M",
"EX_ac_LPAREN_e_RPAREN_",
"EX_glc_LPAREN_e_RPAREN_")
mp = MultiprocessReactionKnockoutOptimization(model=model,
heuristic_method=inspyred.ec.GA,
objective_function=of,
simulation_method=fba)
mp.run(max_evaluations=300, n=2)
