def process_emg(self, emg): emgDict = dict() self.emgData.append(list(emg[0])) self.emgData.append(list(emg[1])) self.emgDataCounter += 1 if self.emgDataCounter == self.model.mFeatures[ 'LW'] / 2 + self.numberVoter - 1: #投票数为其加1 # print("a sample is over!!!!") self.emgDataCounter = 0 self.emgData = np.array(self.emgData, dtype=np.int64) self.emgData = self.emgData.T emgDict['one'] = self.emgData self.sample = FeatureSpace( rawDict=emgDict, moveNames=[ 'one', ], #动作类别 ChList=[0, 1, 2, 3, 4, 5, 6, 7], #传感器的通道数目 features=self.model.mFeatures, one_hot=False, trainPercent=[1, 0, 0] #是否进行onehot处理 ) self.getTrainData() actionList = self.model.mModel.predict(self.trainX) print("the action is :", self.getTheAction(actionList)) self.emgData = [] emgDict.clear()
def getFeature(self): #Splicing all the action data into a large dictionary self.model.readDataFile() emgDict = dict() for i in self.model.actionNames: temp = self.model.emgData[self.model.emgData['action']==i] emgDict[i] = temp[['ch0' , 'ch1' ,'ch2' , 'ch3' ,'ch4' , 'ch5' ,'ch6' , 'ch7' ]].values.T self.Sample = FeatureSpace(rawDict = emgDict, moveNames = self.model.actionNames, #动作类别 ChList = [0,1,2,3,4,5,6,7], #传感器的通道数目 features = self.model.mFeatures, #定义的窗滑动的步长 one_hot = False #是否进行onehot处理 ) self.model.getTrainData(self.Sample)