def load(self, arg, namespaces=[None], profile_memory=0, report_timing=None):
"""
Load the model with data from a file, dictionary or DataPortal object.
"""
if report_timing is not None:
deprecation_warning(
"The report_timing argument to Model.load() is deprecated. "
"Use pyomo.util.timing.report_timing() to enable reporting "
"construction timing")
if arg is None or isinstance(arg, basestring):
dp = DataPortal(filename=arg, model=self)
elif type(arg) is DataPortal:
dp = arg
elif type(arg) is dict:
dp = DataPortal(data_dict=arg, model=self)
elif isinstance(arg, SolverResults):
if len(arg.solution):
logger.warning(
"""DEPRECATION WARNING: the Model.load() method is deprecated for
loading solutions stored in SolverResults objects. Call
Model.solutions.load_from().""")
self.solutions.load_from(arg)
else:
logger.warning(
"""DEPRECATION WARNING: the Model.load() method is deprecated for
loading solutions stored in SolverResults objects. By default, results
from solvers are immediately loaded into the original model instance.""")
return
else:
msg = "Cannot load model model data from with object of type '%s'"
raise ValueError(msg % str( type(arg) ))
self._load_model_data(dp,
namespaces,
profile_memory=profile_memory)
def create_instance(self,
filename=None,
data=None,
name=None,
namespace=None,
namespaces=None,
profile_memory=0,
report_timing=False,
**kwds):
"""
Create a concrete instance of an abstract model, possibly using data
read in from a file.
Optional:
filename: The name of a Pyomo Data File that will be used
to load data into the model.
data: A dictionary containing initialization data for
the model to be used if there is no filename
name: The name given to the model.
namespace: A namespace used to select data.
namespaces: A list of namespaces used to select data.
profile_memory: A number that indicates the profiling level.
report_timing: Report timing statistics during construction.
"""
#
# Generate a warning if this is a concrete model but the
# filename is specified. A concrete model is already
# constructed, so passing in a data file is a waste of time.
#
if self.is_constructed() and isinstance(filename, string_types):
msg = "The filename=%s will not be loaded - supplied as an " \
"argument to the create_instance() method of a "\
"concrete instance with name=%s." % (filename, name)
logger.warning(msg)
if 'clone' in kwds:
kwds.pop('clone')
deprecation_warning(
"Model.create_instance() no longer accepts the 'clone' "
"argument: the base abstract model is always cloned.")
if 'preprocess' in kwds:
kwds.pop('preprocess')
deprecation_warning(
"Model.create_instance() no longer accepts the preprocess' "
"argument: preprocessing is always deferred to when the "
"model is sent to the solver")
if kwds:
msg = \
"""Model.create_instance() passed the following unrecognized keyword
arguments (which have been ignored):"""
for k in kwds:
msg = msg + "\n '%s'" % (k, )
logger.error(msg)
if self.is_constructed():
deprecation_warning(
"Cannot call Model.create_instance() on a constructed "
"model; returning a clone of the current model instance.")
return self.clone()
if report_timing:
pyomo.util.timing.report_timing()
if name is None:
name = self.name
if filename is not None:
if data is not None:
logger.warning(
"Model.create_instance() passed both 'filename' "
"and 'data' keyword arguments. Ignoring the "
"'data' argument")
data = filename
if data is None:
data = {}
#
# Clone the model and load the data
#
instance = self.clone()
if name is not None:
instance._name = name
# If someone passed a rule for creating the instance, fire the
# rule before constructing the components.
if instance._rule is not None:
instance._rule(instance)
if namespaces:
_namespaces = list(namespaces)
else:
_namespaces = []
if namespace is not None:
_namespaces.append(namespace)
if None not in _namespaces:
_namespaces.append(None)
instance.load(data,
namespaces=_namespaces,
profile_memory=profile_memory)
#
# Preprocess the new model
#
if False and preprocess is True:
if report_timing is True:
start_time = time.time()
instance.preprocess()
if report_timing is True:
total_time = time.time() - start_time
print(" %6.2f seconds required for preprocessing" %
total_time)
if (pympler_available is True) and (profile_memory >= 2):
mem_used = muppy.get_size(muppy.get_objects())
print(
" Total memory = %d bytes following instance preprocessing"
% mem_used)
print("")
if (pympler_available is True) and (profile_memory >= 2):
print("")
print(
" Summary of objects following instance preprocessing"
)
post_preprocessing_summary = summary.summarize(
muppy.get_objects())
summary.print_(post_preprocessing_summary, limit=100)
#
# Indicate that the model is concrete/constructed
#
instance._constructed = True
#
# Change this class from "Abstract" to "Concrete". It is
# absolutely crazy that this is allowed in Python, but since the
# AbstractModel and ConcreteModel are basically identical, we
# can "reassign" the new concrete instance to be an instance of
# ConcreteModel
#
instance.__class__ = ConcreteModel
return instance
def xsequence(*args):
from pyomo.util.deprecation import deprecation_warning
deprecation_warning("The xsequence function is deprecated. Use the sequence() function, which returns a generator.") # Remove in Pyomo 6.0
return sequence(*args)