plot runtimes for different big oh notation

runtime plotting for different big o-complexity

import matplotlib.pyplot as plt
import numpy as np
import math 

n = range(1,9) # input range
lgn = [math.log(x,2) for x in n] #logn
l = [x for x in n]  # linear
nlgn = [x*math.log(x,2) for x in n] # nlogn
q = [x**2 for x in n] # quadratic
p = [2**i for i in n] # polynomial

plt.plot(n, lgn, label="logn")
plt.plot(n, l, label="linear")
plt.plot(n,nlgn, label="nlogn")
plt.plot(n,q, label="quadratic")
plt.plot(n,p, label='polynomial')

plt.legend(loc='upper left')
plt.xlabel('input range values (n)')
plt.ylabel('time range on different runtimes')
plt.title('runtime complexity')
plt.grid(True)
plt.show()