def Em(name1,feature,n1,n2):
data = pd.read_csv('E:\\feature.csv', encoding='gbk')
datafeature = data[feature]
data2values = datafeature[feature].values
emval = EM()
datacompete = emval.solve(data2values)
return datacompete
def EMmake(name1, name2):
trafficflow, b, ind = share.Csvopreation(name1, name2)
datavalue = trafficflow.values
datavalue = share.Standardize(datavalue, np.nanmean(datavalue, axis=0),
np.nanstd(datavalue, axis=0))
#print(trafficflow.values.dtype)
em = EM() # EM算法
model = em.solve(datavalue)
return model