def kalman():
filter = KalmanFilter(dim_x=2, dim_z=1)
x = array([0., 1.])
P = eye(2) * 100.
enf = EnsembleKalmanFilter(x=x, P=P, dim_z=1, dt=1., N=20, hx=hx, fx=fx)
measurements = []
results = []
ps = []
kf_results = []
for i in range(len(data)):
z = data.iloc[i].as_array()
enf.predict()
enf.update(asarray([z]))
filter.predict()
filter.update(asarray([[z]]))
results.append (enf.x[0])
kf_results.append (kf.x[0,0])
measurements.append(z)
ps.append(3*(enf.P[0,0]**.5))
results = asarray(results)
ps = asarray(ps)
