def newModel(self, event):
'''Callback for creating a new (meta-, view-) model.'''
self.clearModels()
self.clearViewer()
root = None
if self.editor_mode == 'Model':
fname = QtGui.QFileDialog.getOpenFileName(
self,
'Select Meta Model',
'',
'Meta Model Files (*.meta)',
options=QtGui.QFileDialog.Options()
)
if fname:
self.open_meta(fname)
uuid_dict = OrderedDict()
base = MetaModel.fromMeta(self.META['__ROOT__'][0], uuid_dict)
roots = [
MetaModel.fromMeta(r, uuid_dict)()
for r in self.META['__ROOT__']
]
elif self.editor_mode == 'Meta Model':
self.open_meta('MetaMetaModel.meta')
roots = [MetaModel()]
elif self.editor_mode == 'View Model':
# TODO: Replace this with view_model code
self.open_meta('MetaViewModel.meta')
roots = [ViewModel()]
if roots:
self.load_model(roots)
def summary(self) -> None:
for island in self.islands:
print(f"{island.name}")
print('-' * len(island.model_group))
print('')
island.model_group.report()
print('')
archipelago = MetaModel(-1, self.groups)
archipelago.summary()
print('-' * 80)
def test_ridge(data):
model = MetaModel().readCSV(data)
model.setResponse("Electricity:Facility [J](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Humidity Ratio [kgWater/kgDryAir](Hourly)")
model.bayesRidge().getScores()
print(model.scores)
def saveModel(self, event):
'''Saves a model according to the current mode of the editor.'''
ftype = '{}'.format(self.editor_mode.lower().split()[0])
fname = QtGui.QFileDialog.getSaveFileName(
self,
'Save {}'.format(self.editor_mode),
'',
'{} Files (*.{})'.format(self.editor_mode, ftype),
options=QtGui.QFileDialog.Options()
)
fname = str(fname)
if fname:
if fname[-len(ftype):] != ftype:
fname += '.{}'.format(ftype)
root = self.model.getModel(QtCore.QModelIndex())
# the actual root is not displayed and is always a Model()
rootDict = [MetaModel.toDict(c) for c in root.children]
modelDict = OrderedDict()
modelDict['Name'] = fname.split('/')[-1].split('.')[-2]
modelDict['MD5'] = hashlib.md5(str(rootDict)).hexdigest()
modelDict['__META__'] = {
'Name': self.META['Name'],
'MD5': self.META['MD5']
}
modelDict['__ROOT__'] = rootDict
dictStr = json.dumps(modelDict, indent=4)
with open(fname, 'w') as f:
f.write(dictStr)
return 0
def load_model(self, roots):
'''
:param in model: the root object of a model, which is loaded into
the tree-viewer and proxy models
'''
# Set up the hidden Root model, with the 'model' object as its
# only child
# TODO: Figure out how to allow different roots and multiple
# child objects.
root = MetaModel()
for r in roots:
root.children.set_cardinality({r.__class__: '1..*'})
root.add_child(r)
# Set up the proxy model for sorting/filtering
self.proxy_model = SortFilterProxyModel(self)
self.proxy_model.setDynamicSortFilter(True)
self.proxy_model.setFilterCaseSensitivity(QtCore.Qt.CaseInsensitive)
self.proxy_model.setSortRole(ItemModel.sort_role)
self.proxy_model.setFilterRole(self.filter_role)
self.proxy_model.setFilterKeyColumn(0)
# the model stores the reference to the model that is
# currently being edited/viewed; this can be a regular model,
# a view model, or even a meta-model. All these models
# inherit from the meta-metamodel so have the same interfaces
# and can be interacted with in the same way
self.model = ItemModel(root)
self.model.setMeta(self.META)
self.model.rowsAboutToBeRemoved.connect(self.modelRowsAboutToBeRemoved)
# Link the actual model and the proxy model
self.proxy_model.setSourceModel(self.model)
self.filter_edit.textChanged.connect(self.proxy_model.setFilterRegExp)
self.tree_view.setModel(self.proxy_model)
self.tree_view.expandAll()
def open_meta(self, fname):
'''Decodes a saved meta-model file and loads it into the editor.'''
with open(fname, 'r') as f:
meta_dict = json.loads(f.read())
print 'Loaded meta-model {}'.format(fname)
# uuid_dict = {}
# base = MetaModel.fromMeta(meta_dict['__ROOT__'], uuid_dict)
# TODO: create meta_dict from loaded meta-model
# TODO: Probably will need to resolve UUID referencce problems here
uuid_dict = {}
unresolved_keys = {}
for r in meta_dict['__ROOT__']:
a = MetaModel.fromDict(r, uuid_dict, unresolved_keys)
buildMeta(meta_dict, r, uuid_dict)
self.META = meta_dict
def process(self) -> None:
logging.info(f" == {self.name} island == ")
base = self._data.base_price
self._models = MetaModel.blank(base)
logging.info(f" (%d models) ", len(self._models))
for time, price in self._data.timeline.items():
if price is None:
continue
if time.value < TimePeriod.Monday_AM.value:
continue
logging.info(f"[{time.name}]: fixing price @ {price}")
self._models.fix_price(time, price)
def test_addPredictor():
model = MetaModel()
model.addPredictor("temperature")
print(model.predictors)
def test_all(data):
model = MetaModel().readCSV(data)
model.setResponse("Electricity:Facility [J](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Humidity Ratio [kgWater/kgDryAir](Hourly)")
model.addPredictor("BASEMENT:Zone Thermostat Heating Setpoint Temperature [C](Hourly)")
model.addPredictor("CORE_MID:Zone Thermostat Heating Setpoint Temperature [C](Hourly)")
model.addPredictor("CORE_TOP:Zone Thermostat Cooling Setpoint Temperature [C](Hourly)")
model.bayesRidge().fitSVR(cost=10, epsilon=0.2).trees(numberOfTrees=300).getScores()
print(model.scores)
model.fit(model.SVR)
model.persistMeta('../../data/demoMeta.p')
def test_readCSV(data):
model = MetaModel()
model.readCSV(data)
print(model.dataBox[:3])
def test_persist(data):
model = MetaModel().readCSV(data)
model.setResponse("Electricity:Facility [J](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)")
model.addPredictor("Environment:Site Outdoor Air Humidity Ratio [kgWater/kgDryAir](Hourly)")
model.fitSVR(cost=10, epsilon=0.2).getScores()
model.persistMeta('testPickle.p')
newModel = pickle.load(open('testPickle.p', 'rb'))
print(newModel.scores)
def test_setResponse():
model = MetaModel()
model.setResponse("energy")
print (model.response)
