pl.figure(figsize=bp.golden_ratio(5))
x = np.linspace(0,5*np.pi,100)
for i in range(n):
pl.plot(x, 1-np.sin(x[::-1]/np.sqrt(i+1)), marker=bp.markers[i],mfc='w',label='$i=%d$'%i)
bp.strip_axis(pl.gca())
leg = pl.legend()
bp.align_legend_right(leg)
bp.arrow(pl.gca(), r'$i$', (14, 0.8), (10, 0.15), text_position=text_position, rad=0.3)
pl.xlabel('this is the x-label')
pl.ylabel('this is the y-label')
pl.gcf().tight_layout()
sin_test(n=4,text_position='start')
pl.savefig('one.png',dpi=150)
bp.set_color_cycle(bp.new_colors)
sin_test(n=4,text_position='end')
pl.savefig('two.png',dpi=150)
pl.show()
(E, symptomatic_rate, I),
(I, recovery_rate, R),
(I, quarantine_rate, Q),
])
model.set_initial_conditions({S: N - I0, I: I0})
t, result = model.simulate(100)
plt.figure()
for compartment, incidence in result.items():
plt.plot(t, incidence, label=compartment)
plt.xlabel('time [days]')
plt.ylabel('incidence')
plt.legend()
bp.strip_axis(plt.gca())
plt.gcf().tight_layout()
plt.savefig('SEIRQ_sim.png', dpi=300)
tt = np.linspace(0, max(t), 1000)
result_int = model.integrate(tt)
for compartment, incidence in result_int.items():
plt.plot(tt, incidence)
#plt.gcf().tight_layout()
plt.savefig('SEIRQ_sim_compare_int.png', dpi=300)
plt.show()