import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
y = np.zeros(300)
y[0] = 0.5
First value is 0.5
for n in range(1,300,1):
y[n] = 3.78y[n-1](1-y[n-1])
def f():
return 3.78y[n-1](1-y[n-1])
this is y[n]'s value for each n
print(‘New y[n] value 1 until 300 for each n y:\n’,y)
This is y’ width
yy = len(y)
print(“y’s width yy:\n”,yy)
print(‘Optimalf():\n’,f())
Plot
plt.plot(y,‘ko’,label=“y[n]'s data”)
plt.legend(loc=‘best’)
plt.show()
( parametrelerini (a,b,c gibi) nasıl oluşturabilirim ve curve fittingi nasıl bulurum