bigO.py

"""

Big-O notation image generator. Code which generated the Big-O
growth graph (order) in the book.

"""
import numpy as np
import math
import matplotlib.pyplot as plt
from functools import reduce

def f(t):
    return np.exp(-t) * np.cos(2*np.pi*t)

def k(t):
    return [0]

def l(t):
    return list(map(math.log, t))

def x(t):
    return list(map(lambda x: x, t))

def xl(t):
    return list(map(lambda x: math.log(x)*x, t))

def sq(t):
    return list(map(lambda x: x*x, t))

def p2(t):
    return list(map(lambda x: pow(2,x), t))

def fact(n):
    return reduce(lambda x,y : x*y, range(1, n+1))

def facn(t):
    return list(map(lambda x: fact(x), t))
                    
t = range(1, 101)

plt.axis([0, 50, 0, 50])
line1=plt.plot(t, [1]*100, '#00ee00')
print(line1)
plt.text(45, 1.5, r'O(1)')

line2=plt.plot(t, l(t), color='#00bb00')
plt.text(40, 4.8, r'O(log(n))')

line3=plt.plot(t, x(t), color='#008800')
plt.text(42, 40, r'O((n))')

line4=plt.plot(t, xl(t), color='#eeee00')
plt.text(18, 45, r'O(nlog(n))')

line5=plt.plot(t, sq(t), color='#440000')
plt.text(8, 44, r'O(n^2)')

line6=plt.plot(t, p2(t), color='#bb0000')
plt.text(2, 35, r'O(2^n)')

line7=plt.plot(t, facn(t), color='#ff0000')
plt.text(0, 45, r'O(n!)')

plt.show()