#!/usr/bin/python3
"""
When s = 1,
this would add up to the cumulative probability of the linear_rank_simple.py
"""

import numpy as np
import matplotlib.pyplot as plt

u = 10
ui = range(u)
s_values = np.arange(1, 2.1, 0.1)
for s in s_values:
    print(f"\nS value of {s}")
    fitnesses = []
    for i in range(u):
        fitness_i = ((2 - s) / u) + ((2 * i) * (s - 1)) / (u * (u - 1))
        fitnesses.append(fitness_i)
        print(f"fitness of {i} is {fitness_i}")
    plt.plot(ui, fitnesses, label=f"{s}")
plt.legend()
plt.show()