def loadModel_eval():
venueData = pd.read_csv("./VenueID_data.csv")
l = Localization(venueData)
trajectorydata = pd.read_csv("./trainTrajectory_final.csv")
#print(trajectorydata["VenueID"].describe())
t = Trajectory(trajectorydata)
usersgroup = l.grouping(groupNum)
models = []
models = load_models(models)
testtrajectorydata = pd.read_csv("./testTrajectory_smaller.csv")
testTrajectory = Trajectory(testtrajectorydata)
for i in range(0, len(models)):
print(str(datetime.datetime.now()) + " eval model " + str(i))
data, length, prob, dic = testTrajectory.get(usersgroup[i])
print(models[i].score(data, length) / len(length))
eval_loc_model(models, usersgroup)
def main():
venueData = pd.read_csv("./VenueID_data.csv")
l = Localization(venueData)
trajectorydata = pd.read_csv("./trainTrajectory_final.csv")
#print(trajectorydata["VenueID"].describe())
t = Trajectory(trajectorydata)
usersgroup = l.grouping(groupNum)
testtrajectorydata = pd.read_csv("./testTrajectory_final.csv")
testTrajectory = Trajectory(testtrajectorydata)
models, dics = train(usersgroup=usersgroup, trajectory=t)
for i in range(0, len(models)):
output = open(
'./LocalizationModel/' + str(groupNum) + 'model_state' +
str(states) + "_" + str(i) + '.pkl', 'wb')
s = pickle.dump(models[i], output)
output.close()
for i in range(0, len(models)):
eval_loc_model(testTrajectory=testTrajectory,
model=models[i],
users=usersgroup[i],
dic=dics[i])
