def update_model(self, oldmodel, newmodel):
"""called whenever the model variable is set."""
# TODO: check for pre-connected traits on the new model
# TODO: disconnect traits corresponding to old model (or leave them if the new model has the same ones?)
# TODO: check for nested MMs? Is this a problem?
# TODO: check for name collisions between MetaModel class traits and traits from model
if newmodel is not None and not has_interface(newmodel, IComponent):
self.raise_exception('model of type %s does not implement the IComponent interface' % type(newmodel).__name__,
TypeError)
if not self.surrogate:
self.raise_exception("surrogate must be set before the model or any includes/excludes of variables", RuntimeError)
new_model_traitnames = set()
self._surrogate_input_names = []
self._taining_input_history = []
self._surrogate_info = {}
# remove traits promoted from the old model
for name in self._current_model_traitnames:
if self.parent:
self.parent.disconnect('.'.join([self.name,name]))
self.remove_trait(name)
if newmodel:
# query for inputs
traitdict = newmodel._alltraits(iotype='in')
for name,trait in traitdict.items():
if self._eligible(name):
self._surrogate_input_names.append(name)
if name not in self._mm_class_traitnames:
self.add_trait(name, _clone_trait(trait))
new_model_traitnames.add(name)
setattr(self, name, getattr(newmodel, name))
# now outputs
traitdict = newmodel._alltraits(iotype='out')
for name,trait in traitdict.items():
if self._eligible(name):
try:
surrogate = self.surrogate[name]
except KeyError:
try:
surrogate = self.surrogate['default']
except KeyError:
self.raise_exception("No default surrogate model was"
" specified. Either specify a default, or specify a "
"surrogate model for all outputs",ValueError)
trait_type = surrogate.get_uncertain_value(1.0).__class__()
self.add(name, Slot(trait_type, iotype='out', desc=trait.desc))
self._surrogate_info[name] = (surrogate.__class__(), []) # (surrogate,output_history)
new_model_traitnames.add(name)
setattr(self, name, surrogate.get_uncertain_value(getattr(newmodel,name)))
newmodel.parent = self
newmodel.name = 'model'
self._current_model_traitnames = new_model_traitnames
def _add_output(self, name):
"""Adds the specified output variable and its associated surrogate Slot."""
sur_name = __surrogate_prefix__+name
self.add_trait(sur_name, Slot(ISurrogate, allow_none=True))
self.on_trait_change(self._surrogate_updated, sur_name)
if self.default_surrogate is not None:
surrogate = deepcopy(self.default_surrogate)
self._default_surrogate_copies[sur_name] = surrogate
self._add_var_for_surrogate(surrogate, name)
else:
self.add_trait(name, _clone_trait(self.model.trait(name)))
self._training_data[name] = []
def _add_output(self, name):
"""Adds the specified output variable and its associated surrogate Slot."""
sur_name = __surrogate_prefix__ + name
self.add_trait(sur_name, Slot(ISurrogate, allow_none=True))
self.on_trait_change(self._surrogate_updated, sur_name)
if self.default_surrogate is not None:
surrogate = deepcopy(self.default_surrogate)
self._default_surrogate_copies[sur_name] = surrogate
self._add_var_for_surrogate(surrogate, name)
else:
self.add_trait(name, _clone_trait(self.model.trait(name)))
self._training_data[name] = []
def update_model(self, oldmodel, newmodel):
"""called whenever the model variable is set or when includes/excludes change."""
# TODO: check for pre-connected traits on the new model
# TODO: disconnect traits corresponding to old model (or leave them if the new model has the same ones?)
# TODO: check for nested MMs? Is this a problem?
# TODO: check for name collisions between MetaModel class traits and traits from model
if newmodel is not None and not has_interface(newmodel, IComponent):
self.raise_exception(
'model of type %s does not implement the IComponent interface'
% type(newmodel).__name__, TypeError)
if not self.surrogate:
self.raise_exception(
"surrogate must be set before the model or any includes/excludes of variables",
RuntimeError)
new_model_traitnames = set()
self._surrogate_input_names = []
self._training_input_history = []
self._surrogate_info = {}
self._failed_training_msgs = []
# remove traits promoted from the old model
for name in self._current_model_traitnames:
if self.parent:
self.parent.disconnect('.'.join([self.name, name]))
self.remove_trait(name)
if newmodel:
# query for inputs
traitdict = newmodel._alltraits(iotype='in')
for name, trait in traitdict.items():
if self._eligible(name):
self._surrogate_input_names.append(name)
if name not in self._mm_class_traitnames:
self.add_trait(name, _clone_trait(trait))
new_model_traitnames.add(name)
setattr(self, name, getattr(newmodel, name))
# now outputs
traitdict = newmodel._alltraits(iotype='out')
for name, trait in traitdict.items():
if self._eligible(name):
try:
surrogate = self.surrogate[name]
args = self.surrogate_args.get(name, [])
except KeyError:
try:
surrogate = self.surrogate['default']
args = self.surrogate_args.get('default', [])
except KeyError:
self.raise_exception(
"No default surrogate model was"
" specified. Either specify a default, or specify a "
"surrogate model for all outputs", ValueError)
if isinstance(args, dict):
kwargs = args
args = []
elif isinstance(args, tuple):
args = args[0]
kwargs = args[1]
else:
kwargs = {}
trait_type = surrogate.get_uncertain_value(1.0).__class__()
self.add(name,
Slot(trait_type, iotype='out', desc=trait.desc))
self._surrogate_info[name] = (surrogate.__class__(
*args, **kwargs), []) # (surrogate,output_history)
new_model_traitnames.add(name)
setattr(
self, name,
surrogate.get_uncertain_value(getattr(newmodel, name)))
newmodel.parent = self
newmodel.name = 'model'
self._current_model_traitnames = new_model_traitnames
def _add_input(self, name):
"""Adds the specified input variable."""
self.add_trait(name, _clone_trait(self.model.trait(name)))
setattr(self, name, getattr(self.model, name))
def _add_input(self, name):
"""Adds the specified input variable."""
self.add_trait(name, _clone_trait(self.model.trait(name)))
setattr(self, name, getattr(self.model, name))
