a_w = 2.0
# Initial conditions
s_zero = 1000.0
e_zero = 100.0
i_zero = 50.0
r_zero = 15.0
n_zero = s_zero + e_zero + i_zero + r_zero
fbsm = ForwardBackwardSweep()
fbsm.set_parameters(t_0, t_f, b, d, c, e, g, a, a_w, s_zero, e_zero, i_zero,
r_zero, n_zero)
t = fbsm.t
n_max = fbsm.n_max
u = np.zeros(n_max)
x_wc = fbsm.runge_kutta_forward(u)
[x, lambda_, u] = fbsm.forward_backward_sweep()
# plotting
name_file_1 = 'epidemics_lenhart_lab7.eps'
mpl.style.use('ggplot')
# plt.ion()
plt.show()
ax1 = plt.subplot2grid((2, 2), (0, 0), rowspan=2)
ax2 = plt.subplot2grid((2, 2), (0, 1))
ax3 = plt.subplot2grid((2, 2), (1, 1))
ax1.plot(t,
x_wc[:, 2],
'-',
ms=3,
c_3 = 1.2
c_4 = 1.3
name_file_1 = 'New_System_four_control.pdf'
#
fbsm = ForwardBackwardSweep()
fbsm.set_parameters(beta_y_p, r_y_1, r_y_2, r_a, alpha, beta_a_p, b_y,
b_a, beta_y_v, beta_a_v, gamma, theta, mu,
A_1, A_2, A_3, A_4, c_1, c_2, c_3, c_4,
s_y_p_zero, s_a_p_zero, l_y_p_zero, l_a_p_zero, i_y_p_zero, i_a_p_zero, s_v_zero, i_v_zero)
t = fbsm.t
x_wc_1 = fbsm.runge_kutta_forward(fbsm.u)
#
[x, lambda_, u] = fbsm.forward_backward_sweep()
cost = fbsm.control_cost(fbsm.x,u)
########################################################################################################################
############################################## R_0 Computation #######################################################
########################################################################################################################
R_0 = np.sqrt((beta_y_p* N_p) / gamma) * np.sqrt((beta_y_v * mu * b_y) / (gamma * (b_y * r_y_2 + r_y_1 * r_y_2)))
print('R_0 = ',R_0)
########################################################################################################################
############################################# ODEINT SOLVER ########################################################
########################################################################################################################
b_3 = 1.0
b_4 = 1.0
c_1 = 300.0
c_2 = 600.0
name_file_1 = 'figure_1_sars.eps'
name_file_2 = 'figure_2_sars.eps'
name_file_3 = 'figure_3_sars.eps'
#
fbsm = ForwardBackwardSweep()
fbsm.set_parameters(beta, e_e, e_q, e_j, mu, p, k_1, k_2, d_1, d_2, sigma_1,
sigma_2, n_whole, b_1, b_2, b_3, b_4, c_1, c_2, s_zero,
e_zero, q_zero, i_zero, j_zero, r_zero)
#
t = fbsm.t
x_wcc = fbsm.runge_kutta_forward(fbsm.u)
constant_cost = fbsm.control_cost(x_wcc, fbsm.u)
#
[x, lambda_, u] = fbsm.forward_backward_sweep()
optimal_cost = fbsm.control_cost(x, u)
#
mpl.style.use('ggplot')
# plt.ion()
n_whole = fbsm.n_whole
ax1 = plt.subplot2grid((2, 2), (0, 0), rowspan=2)
ax2 = plt.subplot2grid((2, 2), (0, 1))
ax3 = plt.subplot2grid((2, 2), (1, 1))
#
infected_wcc = x_wcc[:, 1] + x_wcc[:, 2] + x_wcc[:, 3] + x_wcc[:, 4]
infected = x[:, 1] + x[:, 2] + x[:, 3] + x[:, 4]
# saving data:
