import DataPrepare as DP
import NN
import matplotlib.pyplot as plt
import numpy as np
import spliner as sp
data = DP.LoadData('data.csv')
data = sp.SplineData(data, 3)
size = 700
confirmed = np.array(DP.GetConfirmed(data, size))
#confirmed = np.array(DP.GetDeath(data, size))
confirmedRate = DP.GetRate(confirmed, size)
plt.plot(confirmed[800])
plt.plot(np.array(confirmedRate[800]) * 50)
plt.show()
confirmedNN = NN.NN(confirmedRate, Units=256)
#confirmedNN.load('Deathmodel.300-0.01.h5')
confirmedNN.load('model.300-0.03.h5')
#confirmedNN.train()
confirmedRate = np.array(confirmedRate)
ncovdata = DP.LoadData('datancov.csv')
ncovdata = sp.SplineData(ncovdata, 1)
ncovconfirmed = np.array(DP.GetDeath(ncovdata, size))
ncovRate = np.array(DP.GetRate(ncovconfirmed, size))
validation = np.array([ncovRate[0, :-1]])
result = validation
curve = np.array([ncovconfirmed[660, :-1]])[-1]
def SplineData(DiltedData, times=2) -> list:
res = []
for i in range(DiltedData.__len__()):
conf = GetCF(DiltedData[i])
rec = GetRe(DiltedData[i])
dea = GetDe(DiltedData[i])
datal = conf.__len__()
base = np.linspace(0, datal + 1, datal + 2)
splc = BSpline(base, conf, times)
splr = BSpline(base, rec, times)
spld = BSpline(base, dea, times)
base2 = np.linspace(1, datal - 1, datal * 10)
conf_, rec_, dea_ = splc(base2), splr(base2), spld(base2)
ret = []
for j in range(0, conf_.__len__()):
x = DP.Data()
x.ConfirmedData = conf_[j]
x.RecoverData = rec_[j]
x.DeathData = dea_[j]
x.AreaName = DiltedData[i][0].AreaName
ret.append(x)
res.append(ret)
return res
if __name__ == '__main__':
data = DP.LoadData('data.csv')
data = FiltData(data)
Sdata = SplineData(data)
print(Sdata[0][1040].RecoverData)
