import numpy as np
import matplotlib.pyplot as plt
import math
from IPython.display import clear_output
print("Utilize Which Growth Model of Population? (Type A or B)")
print()
print("A Exponential Growth Model")
print("B Logistic Growth Model")
print()
A = int(1)
# Exponential Growth Model
B = int(2)
# Logistic Growth Model
C = input("Growth Model of choice : ")
print()
if C == "A":
# Definition of Parameters
print("The Differential Equation of your chosen growth model is P'(t) = r*P(t)")
print()
print("Where r = growth parameter")
print("Where P(t) = total population at a certain time t")
print("Where t = time")
print()
# Explanation of Differential Equation
print("This equation can be considered as the exponential differential equation")
print("because its solution is P(t) = P(0)*e^r*t ; where P(0) = Initial Population")
print()
print("This equation can be portrayed by using this graph : ")
# Graph Code
x, y = np.meshgrid(np.linspace(-50, 50, 10), np.linspace(-50, 50, 10))
r = float(input("Encode Growth Parameter :"))
t = float(input("At how many years do you want to solve? :"))
P = float(input("Encode Population Count :"))
P = y
t = x
x = np.asarray(x, dtype="float64")
Un = u / P * (math.exp ** (r * t))
Vn = u / P * (math.exp ** (r * t))
plt.quiver(x, y, Un, Vn)
plt.plot([8, 12, 25, 31], [1, 16, 20, 40])
plt.show()
if C == "B":
print("The Differential Equation of your chosen growth model is y' = k*y*(M-y)")
print()
print("Where k = slope of the function")
print("Where y = y-value at the specific point")
print("Where M = limit of y as x approaches infinity")
print()
print("This equation is derived using *** ")