# -*- coding: utf-8 -*- """ Created on Wed Jul 29 09:36:10 2020 @author: Rodrigo """ import sir import matplotlib.pyplot as plt #%% imax = 0.1 umax = 0.5 gamma = 0.2 beta = 0.5 #%% A = sir.SIR() A.set_params([imax, umax, gamma, beta], flag="bg") A._find_curves() P = A.add_point(0.9, 0.00001) A.find_regions() A.get_shortest() T = P.least_time print(T.segments) T.plot_time()
return foo(Is)
def final_cond(t, state, u_func, ref, crit, term_val):
out = state[0] - term_val
return out
final_cond.terminal = True
#%%
imax = 0.1
umax = 0.6
gamma = 1 / 7
beta = 0.52
A = sir.SIR()
A.set_params([imax, umax, gamma, beta], flag="bg")
sir.find_commutation_curve(A)
#%%
x0 = np.array([1 - 1e-4, 1e-4, 0, 0, 0]).reshape([
5,
])
#x0 = np.array([0.5, 0, 0.075, 0, 0]).reshape([5, ])
p = ref(0.52, 1 / 7, 1 / 7, 0.8)
sol = scipy.integrate.solve_ivp(
SEIIR,
[0, 1000],
x0,
#method = "LSODA", min_step = 1e-3,
method="RK23",
tspan = np.linspace(0, 13.178045800119373) series = scipy.integrate.odeint(sir, y0=x0, t=tspan, args=(us, )) series2 = scipy.integrate.odeint(sir, y0=x0, t=tspan, args=(umax, )) fig, ax = plt.subplots() ax.set_xlim(0.4, 1) ax.set_ylim(0, 0.1 * 1.1) ax.plot(series[:, 0], series[:, 1], color="xkcd:blue") ax.plot(series2[:, 0], series2[:, 1], color="xkcd:red") #%% ireal = 0.1 ureal = 0.5 greal = 0.1 breal = 0.3 Re = SIR.SIR() Re.set_params([ireal, ureal, greal, breal], flag="bg") SIR.find_commutation_curve(Re) iest = 0.1 uest = 0.5 gest = 0.2 best = 0.5 Est = SIR.SIR() Est.set_params([iest, uest, gest, best], flag="bg") SIR.find_commutation_curve(Est) fig, ax = plt.subplots() ax.set_xlim(min([Re.sbar, Est.sbar]), 1) ax.set_ylim(0, max([Re.imax, Est.imax]) * 1.1) ax.plot(Re.tau.s, Re.tau.i, "b:")
import matplotlib.pyplot as plt
#%%
R0 = [2.1, 2.5] # [minR0, maxR0]
imax = 0.1
umax = 0.5
disp = 1e-3
ilow = 5e-4
#%%
scenarios = {"bcs": None, "wcs": None}
for ii in range(len(R0)):
r0 = R0[ii]
key = list(scenarios.keys())[ii]
A = sir.SIR()
A.set_params([imax, umax, r0], flag = "r")
scenarios[key] = A
A._find_curves()
s0, i0 = sir.create_initial_conditions(A, disp, ilow)
for ii, jj in zip(s0, i0):
A.add_point(ii, jj)
A.find_regions()
A.get_shortest()
M = np.array([p.least_time for p in A.points])
final_point = np.array([tra.s[-1] for tra in M])
fig, ax = plt.subplots()
ax.plot(s0, final_point)
imax = 0.1
umax = 0.6
R_reals = np.array([1.73]) #2.5, 3.64])
ratios = np.linspace(0.7, 1.3, 15)
us = np.array([0.9, 1, 1.1])
overshoot = np.zeros(
[np.shape(R_reals)[0],
np.shape(ratios)[0],
np.shape(us)[0]])
sols = np.empty(np.shape(overshoot), dtype=object)
for ii in range(np.shape(R_reals)[0]):
rreal = R_reals[ii]
print("\nR_0 = {}".format(rreal))
print("Setting up real system.")
Dyn = sir.SIR()
Dyn.set_params([imax, umax, rreal], flag="r")
sir.find_commutation_curve(Dyn)
for kk in range(np.shape(us)[0]):
for jj in range(np.shape(ratios)[0]):
restim = rreal * ratios[jj]
print("\tR_e = {}".format(restim))
print("Setting up estimated system.")
Ctrol = sir.SIR()
Ctrol.set_params([imax, umax * us[kk], restim], flag="r")
sir.find_commutation_curve(Ctrol)
out = "Simulating with u = {}, R0 = {} and \\hat{{R}}0 = {}"
print(out.format(Ctrol.umax, rreal, restim))
sol = scipy.integrate.solve_ivp(F, [0, 1e5],
return foo(S)
def final_cond(t, state, u_func, evol, crit, term_val):
out = state[0] - term_val
return out
final_cond.terminal = True
#%%
imax = 0.1
umax = 0.6
rreal = 3.64
Re = sir.SIR()
Re.set_params([imax, umax, rreal], flag = "r")
sir.find_commutation_curve(Re)
Ab = sir.SIR()
Ab.set_params([imax, umax, rreal * 1.2], flag = "r")
sir.find_commutation_curve(Ab)
Be = sir.SIR()
Be.set_params([imax, umax, rreal * 0.5], flag = "r")
sir.find_commutation_curve(Be)
sbars = [Re.sbar, Ab.sbar, Be.sbar]
#%%
fig, ax = plt.subplots(figsize = (18, 12))
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 16 20:51:04 2020
@author: rmm
"""
import sir
import matplotlib.pyplot as plt
imax = 0.1
umax = 0.6
r = 1.73
Dyn = sir.SIR()
Dyn.set_params([imax, umax, r], flag = "r")
sir.find_commutation_curve(Dyn)
"""
end = Dyn.phi._curve_sol(5e-4)[0]
s0, i0 = sir.create_initial_conditions(Dyn, 1e-3, 5e-4, end = end)
for s, i in zip(s0, i0):
Dyn.add_point(s, i)
Dyn.find_regions()
regs = [p.region for p in Dyn.points]
for p in Dyn.points:
Mx = sir.MinimumTrajectory(p, Dyn)
Mx.find_commutation()
