def __init__(self):
super(NeuralNetwork, self).__init__()
self.field = Field(20, 20)
self.outputs = []
self.input = []
self.target = []
b = QtGui.QPushButton("Learn!")
self.connect(b, QtCore.SIGNAL("clicked()"), self.learn)
self.outcomes_list = QtGui.QComboBox()
self._add_output("Square")
self._add_output("Triangle")
self._add_output("Line")
hpanel = QtGui.QHBoxLayout()
hpanel.addWidget(self.outcomes_list)
hpanel.addWidget(b)
btn_classify = QtGui.QPushButton("Classify")
self.connect(btn_classify, QtCore.SIGNAL("clicked()"), self.classify)
btn_clear = QtGui.QPushButton("Clear")
self.connect(btn_clear, QtCore.SIGNAL("clicked()"), self.clear)
self.label_output = QtGui.QLabel()
self.label_output.setMaximumHeight(20)
self.label_epoch = QtGui.QLabel()
self.label_epoch.setMaximumHeight(20)
vpanel = QtGui.QVBoxLayout()
vpanel.addWidget(self.field)
vpanel.addLayout(hpanel)
vpanel.addWidget(self.label_output)
vpanel.addWidget(self.label_epoch)
vpanel.addWidget(btn_classify)
vpanel.addWidget(btn_clear)
self.setLayout(vpanel)
try:
self.net, self.epoch = loadnet("netdata.dat")
except IOError:
conec = mlgraph((self.field.x * self.field.y, 10, 10, 3))
self.net = ffnet(conec)
self.epoch = 0
def __init__(self):
super(NeuralNetwork, self).__init__()
self.field = Field(20, 20)
self.outputs = []
self.input = []
self.target = []
b = QtGui.QPushButton("Learn!")
self.connect(b, QtCore.SIGNAL("clicked()"), self.learn)
self.outcomes_list = QtGui.QComboBox()
self._add_output("Square")
self._add_output("Triangle")
self._add_output("Line")
hpanel = QtGui.QHBoxLayout()
hpanel.addWidget(self.outcomes_list)
hpanel.addWidget(b)
btn_classify = QtGui.QPushButton("Classify")
self.connect(btn_classify, QtCore.SIGNAL("clicked()"), self.classify)
btn_clear = QtGui.QPushButton("Clear")
self.connect(btn_clear, QtCore.SIGNAL("clicked()"), self.clear)
self.label_output = QtGui.QLabel()
self.label_output.setMaximumHeight(20)
self.label_epoch = QtGui.QLabel()
self.label_epoch.setMaximumHeight(20)
vpanel = QtGui.QVBoxLayout()
vpanel.addWidget(self.field)
vpanel.addLayout(hpanel)
vpanel.addWidget(self.label_output)
vpanel.addWidget(self.label_epoch)
vpanel.addWidget(btn_classify)
vpanel.addWidget(btn_clear)
self.setLayout(vpanel)
try:
self.net, self.epoch = loadnet("netdata.dat")
except IOError:
conec = mlgraph((self.field.x*self.field.y, 10, 10, 3))
self.net = ffnet(conec)
self.epoch = 0
class NeuralNetwork(QtGui.QWidget):
def __init__(self):
super(NeuralNetwork, self).__init__()
self.field = Field(20, 20)
self.outputs = []
self.input = []
self.target = []
b = QtGui.QPushButton("Learn!")
self.connect(b, QtCore.SIGNAL("clicked()"), self.learn)
self.outcomes_list = QtGui.QComboBox()
self._add_output("Square")
self._add_output("Triangle")
self._add_output("Line")
hpanel = QtGui.QHBoxLayout()
hpanel.addWidget(self.outcomes_list)
hpanel.addWidget(b)
btn_classify = QtGui.QPushButton("Classify")
self.connect(btn_classify, QtCore.SIGNAL("clicked()"), self.classify)
btn_clear = QtGui.QPushButton("Clear")
self.connect(btn_clear, QtCore.SIGNAL("clicked()"), self.clear)
self.label_output = QtGui.QLabel()
self.label_output.setMaximumHeight(20)
self.label_epoch = QtGui.QLabel()
self.label_epoch.setMaximumHeight(20)
vpanel = QtGui.QVBoxLayout()
vpanel.addWidget(self.field)
vpanel.addLayout(hpanel)
vpanel.addWidget(self.label_output)
vpanel.addWidget(self.label_epoch)
vpanel.addWidget(btn_classify)
vpanel.addWidget(btn_clear)
self.setLayout(vpanel)
try:
self.net, self.epoch = loadnet("netdata.dat")
except IOError:
conec = mlgraph((self.field.x * self.field.y, 10, 10, 3))
self.net = ffnet(conec)
self.epoch = 0
def _add_output(self, output):
self.outputs.append(output)
self.outcomes_list.addItem(output)
def closeEvent(self, close_event):
self.save_net()
def learn(self):
self.epoch += 1
self.input.append(self.field.get_values())
a = [0.0] * 3
a[self.outcomes_list.currentIndex()] = 1.0
self.target.append(a)
self.net.train_tnc(numpy.array(self.input),
numpy.array(self.target),
maxfun=2000,
messages=1)
def save_net(self):
savenet((self.net, self.epoch), "netdata.dat")
def classify(self):
res_array = self.net.call(numpy.array(self.field.get_values()))
print(res_array)
res_arg = res_array.argmax()
res_value = res_array[res_arg]
self.label_output.setText("%s (%s)" %
(self.outputs[res_arg], res_value))
self.label_epoch.setText("Epoch: %s" % self.epoch)
def clear(self):
self.field.clear()
class NeuralNetwork(QtGui.QWidget):
def __init__(self):
super(NeuralNetwork, self).__init__()
self.field = Field(20, 20)
self.outputs = []
self.input = []
self.target = []
b = QtGui.QPushButton("Learn!")
self.connect(b, QtCore.SIGNAL("clicked()"), self.learn)
self.outcomes_list = QtGui.QComboBox()
self._add_output("Square")
self._add_output("Triangle")
self._add_output("Line")
hpanel = QtGui.QHBoxLayout()
hpanel.addWidget(self.outcomes_list)
hpanel.addWidget(b)
btn_classify = QtGui.QPushButton("Classify")
self.connect(btn_classify, QtCore.SIGNAL("clicked()"), self.classify)
btn_clear = QtGui.QPushButton("Clear")
self.connect(btn_clear, QtCore.SIGNAL("clicked()"), self.clear)
self.label_output = QtGui.QLabel()
self.label_output.setMaximumHeight(20)
self.label_epoch = QtGui.QLabel()
self.label_epoch.setMaximumHeight(20)
vpanel = QtGui.QVBoxLayout()
vpanel.addWidget(self.field)
vpanel.addLayout(hpanel)
vpanel.addWidget(self.label_output)
vpanel.addWidget(self.label_epoch)
vpanel.addWidget(btn_classify)
vpanel.addWidget(btn_clear)
self.setLayout(vpanel)
try:
self.net, self.epoch = loadnet("netdata.dat")
except IOError:
conec = mlgraph((self.field.x*self.field.y, 10, 10, 3))
self.net = ffnet(conec)
self.epoch = 0
def _add_output(self, output):
self.outputs.append(output)
self.outcomes_list.addItem(output)
def closeEvent(self, close_event):
self.save_net()
def learn(self):
self.epoch += 1
self.input.append(self.field.get_values())
a = [0.0]*3; a[self.outcomes_list.currentIndex()] = 1.0
self.target.append(a)
self.net.train_tnc(numpy.array(self.input), numpy.array(self.target), maxfun = 2000, messages=1)
def save_net(self):
savenet((self.net, self.epoch), "netdata.dat")
def classify(self):
res_array = self.net.call(numpy.array(self.field.get_values()))
print (res_array)
res_arg = res_array.argmax()
res_value = res_array[res_arg]
self.label_output.setText("%s (%s)" % (self.outputs[res_arg], res_value) )
self.label_epoch.setText("Epoch: %s" % self.epoch)
def clear(self):
self.field.clear()
