!pip install --upgrade quantecon

import quantecon as qe
import numpy as np
import scipy.linalg as la
import matplotlib.pyplot as plt
%matplotlib inline
from quantecon import DLE

np.set_printoptions(suppress=True, precision=4)

α, β, ρ_1, ρ_2, σ = 10, 0.95, 0.9, 0, 1

γ = np.array([[-1], [0]])
ϕ_c = np.array([[1], [0]])
ϕ_g = np.array([[0], [1]])
ϕ_1 = 1e-5
ϕ_i = np.array([[-1], [-ϕ_1]])
δ_k = np.array([[0]])
θ_k = np.array([[1 / β]])
β = np.array([[β]])
l_λ = np.array([[0]])
π_h = np.array([[1]])
δ_h = np.array([[0]])
θ_h = np.array([[0]])

a22 = np.array([[1,   0,   0],
                [α, ρ_1, ρ_2],
                [0, 1, 0]])

c2 = np.array([[0], [σ], [0]])
ud = np.array([[0, 1, 0],
               [0, 0, 0]])
ub = np.array([[100, 0, 0]])

x0 = np.array([[0], [0], [1], [0], [0]])

info1 = (a22, c2, ub, ud)
tech1 = (ϕ_c, ϕ_g, ϕ_i, γ, δ_k, θ_k)
pref1 = (β, l_λ, π_h, δ_h, θ_h)
econ1 = DLE(info1, tech1, pref1)

econ1.Sc

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 5))

for i in range(25):
    econ1.compute_sequence(x0, ts_length=150)
    ax1.plot(econ1.c[0], c='g')
    ax1.plot(econ1.d[0], c='b')
ax1.plot(econ1.c[0], label='Consumption', c='g')
ax1.plot(econ1.d[0], label='Income', c='b')
ax1.legend()

for i in range(25):
    econ1.compute_sequence(x0, ts_length=150)
    ax2.plot(econ1.k[0], color='r')
ax2.plot(econ1.k[0], label='Debt', c='r')
ax2.legend()
plt.show()