slam_shift = LightSchedule.SlamShift()
time = np.arange(0, 20*24.0, 0.10)
light_values = slam_shift(time)
act = Actogram(time, light_vals=light_values, smooth=False)
spm = Hannay19()
trajectory = spm(time, np.array([1.0, np.pi, 0.0]), light_values)
dlmo = spm.dlmos()
act.plot_phasemarker(dlmo, color='blue')
plt.show()
dlmo_experimental = np.linspace(-12, 12., 30)
dlmo_predicted = dlmo_experimental + np.random.normal(0, 2, len(dlmo_experimental))
plot_mae(dlmo_experimental, dlmo_predicted)The MAE is: 4.893222072754772
Within one hour 7/30
[-3.47328784e+00 2.29203680e+01 2.14370972e+01 2.05151476e+01
-8.28809784e-01 3.29152432e+00 -1.03521731e+00 -1.21786907e+00
6.01046181e-01 -8.64421152e-01 2.32069554e+00 -1.20140297e+00
1.11533503e+00 -1.35758354e+00 -1.13861312e+00 1.62675565e+00
1.03264169e+00 1.65883693e+00 1.66964836e+00 -2.41250659e+00
3.98410068e-01 2.24680534e+00 4.61070620e-01 -1.11127185e-02
8.78906427e-02 1.18376113e+00 1.25223210e+00 -2.07873084e+01
-2.31041479e+01 -5.54511532e+00]
phi1 = 12.0 + 5.0*np.random.randn(100)
phi2 = phi1 + 5.0*np.random.randn(100)
plot_torus(phi1, phi2, scaled_by=24.0, color='darkgreen')
plt.title("Example torus plot")
plt.xlabel("$\phi_1$")
plt.ylabel("$\phi_2$");
slam_shift = LightSchedule.SlamShift(shift=12.0, lux=500.0, before_days=2)
time = np.arange(0.0, 15*24.0, 0.10)
light_values = slam_shift(time)
# Run this for a range of period parameters
batch_dim = 50
hmodel = Hannay19({'tau': np.linspace(23.5, 24.5, batch_dim)})
initial_state = np.array([1.0, np.pi, 0.0]) + np.zeros((batch_dim, 3))
initial_state = initial_state.T
trajectory = hmodel(time, initial_state, light_values)
ax = plt.gca()
cmap = plt.get_cmap('jet')
for idx in range(trajectory.batch_size):
Stroboscopic(ax,
time,
trajectory.states[:, 0, idx],
trajectory.states[:, 1, idx],
period=24.0,
lw=0.50,
color=cmap(idx/batch_dim));
plt.title("Stroboscopic plot of the Hannay et al. 2019 model");