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)