Calculate the area of ​intersection of curves using the Monte Carlo Method in Python

I'm making a list of exercises in which I have the following exercise:

"Use the Monte Carlo method to calculate the area of ​​intersection between the curves given below. For random number generation use the Linear Congruence Method"

curves functions

I'm having trouble determining the bounds of random numbers. I already added the functions in GeoGebra

Define box which contains whole area: I would say (-0.5,-0.5) to (1.5,2.0) should do it.

Sample points in the box:

x = -0.5 + 2*np.random.random()
y = -0.5 + 2.5*np.random.random()

Check against four curves if point is inside area

def inside(x, y):
    if ... :
         return True
    return False

Count ratio of points inside vs total points and multiply by box area

N = 100000
is_inside = 0

for k in range(0, N):
    x = -0.5 + 2*np.random.random()
    y = -0.5 + 2.5*np.random.random()

    if inside(x,y):
        is_inside += 1

area = is_inside*(2.5+0.5)*(1.5+0.5)/N

UPDATE

Anyway, this is good solution, I think. Python 3.10 x64 Windows 10

import numpy as np
import matplotlib.pyplot as plt

rng = np.random.default_rng(135797531)

def inside(x: np.float64, y: np.float64) -> bool:

    if x <= 0.0:
        return False

    y1 = 4.0*x
    if y > y1:
        return False

    y2 = x*np.log(x)
    if y < y2:
        return False

    y3 = np.cosh(x)
    if y > y3:
        return False

    y4 = np.cos(x) / x
    if y > y4:
        return False

    return True

x_min: np.float64 =  0.0
y_min: np.float64 = -0.5

x_max: np.float64 = 1.5
y_max: np.float64 = 2.0

N:int = 10000

is_inside:int = 0

x_plt = []
y_plt = []

for k in range(0, N):
    
    x = x_min + (x_max - x_min)*rng.random()
    y = y_min + (y_max - y_min)*rng.random()

    if inside(x,y):
        is_inside += 1
        x_plt.append(x)
        y_plt.append(y)
    
area = (x_max - x_min)*(y_max - y_min)*is_inside/N
print(area)

plt.scatter(x_plt, y_plt, s=1)
plt.show()

that will produce output equal to 1.18275 and plot below