def status_init(self):
super(SignatureShowOption, self).init()
self.build_gui()
try:
with open(self.signature_file, 'r') as f:
file_content = json.loads(f.read())
except (IOError, ValueError):
file_content = {}
for k, v in file_content.iteritems():
print k
states = v["states"]
for n, pos in states.iteritems():
if n.lower() == "off":
continue
self.power_scatter.addPoints(
brush=qt.brush(255, 255, 255, 255),
pos=[pos], size=10)
text = qt.text(k+'/'+n, anchor=(0.5, 0))
text.setPos(pos[0], pos[1]-0.5)
self.power_plot.addItem(text)
self.status = self.STATUS.WAIT
def build_gui(self):
self.sign_plot = self.build_plot("VAr", "W",
title=u"Possíveis transições")
self.sign_scatter = qt.scatter(unicolor=True)
self.sign_plot.addItem(self.sign_scatter)
self.next_row()
self.power_plot = self.build_plot("VAr", "W",
title=u"Tempo real")
self.power_scatter = qt.scatter(unicolor=True)
self.power_plot.addItem(self.power_scatter)
self.reac_power_data = deque(maxlen=self.POWER_SIZE_LEN)
self.real_power_data = deque(maxlen=self.POWER_SIZE_LEN)
self.power_scatter_brushes = qt.mk_brushes(
self.POWER_SIZE_LEN, 255, 255, 255)
self.status_text = qt.text("", anchor=(0.0, 1.0))
self.status_text.setPos(0, 0)
self.power_plot.addItem(self.status_text)
def update_classifier(self):
self.classifier_instances = []
self.classifier_labels = []
self.classifier_texts = []
for appliance, data in self.signatures.iteritems():
self.classifier_instances.extend([
t[2] if t[0] == self.current_status[appliance]
else [-t[2][0], -t[2][1]]
for t in data["transitions"]
if t[0] == self.current_status[appliance]
or t[1] == self.current_status[appliance]
])
self.classifier_labels.extend([
(appliance,
t[0] if t[1] == self.current_status[appliance]
else t[1])
for t in data["transitions"]
if t[0] == self.current_status[appliance]
or t[1] == self.current_status[appliance]
])
self.classifier_texts.extend([
qt.text(appliance + '/' + label, anchor=(0, 0.5))
for app, label in self.classifier_labels
if app == appliance
])
for i, text in enumerate(self.classifier_texts):
text.setPos(*self.classifier_instances[i])
self.classifier_classes = range(
len(self.classifier_instances))
self.classifier = KNeighborsClassifier(n_neighbors=1)
self.classifier.fit(self.classifier_instances,
self.classifier_classes)
def button_tag_clicked(self):
self.labels = []
arrow = qt.arrow(angle=-160, tipAngle=60,
headLen=40, tailLen=40, tailWidth=20,
pen={'color': 'w', 'width': 3})
self.power_plot.addItem(arrow)
try:
for i, prototype in enumerate(self.prototypes):
arrow.setPos(prototype[0]-0.2, prototype[1]+0.2)
qt.update_gui()
current_state = qt.input_dialog("Nome do estado", "")
self.labels.append(current_state)
text = qt.text(current_state, anchor=(0.5, 0))
text.setPos(prototype[0], prototype[1]-0.5)
self.power_plot.addItem(text)
except qt.UserCancelError:
return
self.power_plot.removeItem(arrow)
self.transitions = []
l = len(self.prototypes)
for i in xrange(l):
for j in xrange(i+1, l):
self.transitions.append((
self.labels[j], self.labels[i], (
self.prototypes[i][0] - self.prototypes[j][0],
self.prototypes[i][1] - self.prototypes[j][1]
)))
self.button_cluster.setEnabled(False)
self.button_tag.setEnabled(False)
self.button_save.setEnabled(True)