def confirmParameters(self):
errorMessage = ''
if not self.isNumber(self.setLossRateEdit.text()):
errorMessage = errorMessage + '缺失率无效输入\n'
elif float(self.setLossRateEdit.text()) > 1. or float(
self.setLossRateEdit.text()) < 0.:
errorMessage = errorMessage + '缺失率输入范围错误\n'
if not self.isNumber(self.setLossValueEdit.text()):
errorMessage = errorMessage + '缺失标示值无效输入\n'
if errorMessage != '':
errorMessage = errorMessage + '请重新输入参数'
reply = QMessageBox.information(self, '输入错误', errorMessage,
QMessageBox.Yes, QMessageBox.Yes)
self.setLossRateEdit.setText(
str(self.parentW.dataLossRate[self.senderName]))
self.setLossValueEdit.setText(
str(self.parentW.dataSetLossValue[self.senderName]))
return
else:
self.parentW.dataLossRate[self.senderName] = float(
self.setLossRateEdit.text())
self.parentW.dataSetLossValue[self.senderName] = float(
self.setLossValueEdit.text())
if self.parentW.fname[self.senderName] is not None:
try:
self.parentW.dataFor[
self.senderName] = myLoadData.loadData(
self.parentW.fname[self.senderName],
self.parentW.dataLossRate[self.senderName],
self.parentW.dataSetLossValue[self.senderName])
except FileNotFoundError as e:
reply = QMessageBox.information(
self, 'Message',
"Data file doesn't exist, parameters' saved",
QMessageBox.Yes, QMessageBox.Yes)
# print(self.parentW.dataFor[self.senderName].DataTrainX)
self.close()
return
# if self.parentW.dataFor['New'] is not None:
# print(self.parentW.dataFor['New'].DataTrainX, '\n', self.parentW.dataFor['New'].DataTrainY)
# else:
# print(self.parentW.dataFor['New'])
#
# if self.parentW.dataFor['Tra'] is not None:
# print(self.parentW.dataFor['Tra'].DataTrainX, '\n', self.parentW.dataFor['Tra'].DataTrainY)
# else:
# print(self.parentW.dataFor['Tra'])
reply = QMessageBox.information(self, 'Message',
"Parameters' saved successfully",
QMessageBox.Yes, QMessageBox.Yes)
self.close()
return
def loadData(self):
if self.sender() is self.dataFileChooseButton:
try:
self.dataFor['New'] = myLoadData.loadData(self.fname['New'], self.dataLossRate['New'], self.dataSetLossValue['New'])
# print(self.dataFor['New'].DataTrainX, '\n', self.dataFor['New'].DataTrainY)
except FileNotFoundError as e:
reply = QMessageBox.information(self, 'Message', "Data file not exist",
QMessageBox.Yes, QMessageBox.Yes)
return
except Exception:
reply = QMessageBox.information(self, 'Message', "Data file format error",
QMessageBox.Yes, QMessageBox.Yes)
return
dataname = self.fname['New'].split('/')[-1].split('.')[0]
# print(dataname)
self.presentDataName.setText(dataname)
self.presentDataName.resize(self.presentDataName.sizeHint())
elif self.sender() is self.dataFileChooseButtonT:
try:
self.dataFor['Tra'] = myLoadData.loadData(self.fname['Tra'], self.dataLossRate['Tra'], self.dataSetLossValue['Tra'])
# print(self.dataFor['Tra'].DataTrainX, '\n', self.dataFor['Tra'].DataTrainY)
except FileNotFoundError as e:
reply = QMessageBox.information(self, 'Message', "Data file not exist",
QMessageBox.Yes, QMessageBox.Yes)
return
except Exception:
reply = QMessageBox.information(self, 'Message', "Data file format error",
QMessageBox.Yes, QMessageBox.Yes)
return
dataname = self.fname['Tra'].split('/')[-1].split('.')[0]
# print(dataname)
self.presentDataNameT.setText(dataname)
self.presentDataNameT.resize(self.presentDataNameT.sizeHint())
return
fp.close()
except Exception:
return False
self.inputLayer = fullConnect.fullConnectInputLayer(
model['fullConnect']['inputLayer']['inputDataShape'], 0.2)
self.inputLayer.setWeight(model['fullConnect']['inputLayer']['weight'])
self.midLayer = fullConnect.fullConnectMidLayer(
model['fullConnect']['midLayer']['midInputDataShape'],
model['fullConnect']['midLayer']['yclassNum'], 0.2)
self.midLayer.setWeight(model['fullConnect']['midLayer']['weight'])
# self.forwardPropagation(self.data.DataTestX)
# print(self.predictResult)
# print(costFunc.costCal(self.predictResult, self.data.DataTestY))
# print(self.data.DataTestY)
# print(accuracyEvaluate.classifyAccuracyRate(self.predictResult, self.data.DataTestY))
return True
if __name__ == '__main__':
# irisDATA = myLoadData.loadData('iris.txt')
# traNN = traditionalNN(irisDATA)
wineData = myLoadData.loadData('wine.txt', 0.3, -1)
wineData.MeanPreProcess()
wineData.minmax_scale()
traNN = traditionalNN(wineData)
traNN.train(6000, 0.9, 2)
def setModel(self, fname):
try:
fp = open(fname, 'r')
model = json.load(fp)
fp.close()
except FileNotFoundError:
return False
self.inputLayer = fullConnect.fullConnectInputLayer(
model['fullConnect']['inputLayer']['inputDataShape'], 0.2)
self.inputLayer.setWeight(model['fullConnect']['inputLayer']['weight'])
self.midLayer = fullConnect.fullConnectMidLayer(
model['fullConnect']['midLayer']['midInputDataShape'],
model['fullConnect']['midLayer']['yclassNum'], 0.2)
self.midLayer.setWeight(model['fullConnect']['midLayer']['weight'])
# self.forwardPropagation(self.data.DataTestX)
# print(self.predictResult)
# print(costFunc.costCal(self.predictResult, self.data.DataTestY))
# print(self.data.DataTestY)
# print(accuracyEvaluate.classifyAccuracyRate(self.predictResult, self.data.DataTestY))
return True
if __name__ == '__main__':
irisDATA = myLoadData.loadData('..\\iris.txt')
traNN = traditionalNN(irisDATA)
traNN.train(500, 0.9, 2, [True], threading.Lock())
raise myException.DataValidFormatException
if self.data.DataX.shape[1] != self.combConvLayer1.getFeatureNum():
raise myException.DataModelMatchException
if setChoose == 'Train':
self.forwardPropagation()
elif setChoose == 'Test':
self.forwardPropagation(self.data.DataTestX)
elif setChoose == 'Validation':
self.forwardPropagation(self.data.DataValX)
if __name__ == '__main__':
# irisDATA = myLoadData.loadIris(0.3, -1)
# mcnn = myCombineCNN(irisDATA, 2, 5, 4)
# mcnn.trainCNN(1600,0.2, [True])
irisDATA = myLoadData.loadData('..\\iris.txt', 0.3, -1)
mcnn = myCombineCNN(irisDATA, 2, 5, 4)
mcnn.trainCNN(1600, 0.2, [True], threading.Lock())
# self.data = None
# if dataName == 'Iris':
# self.data = myLoadData.loadIris()
# else:
# print('No such data file, Waiting for new data set\n')
# exit(1) # todo throw error or set new data