import numpy as np
from scipy.stats import beta
import matplotlib.pyplot as plt
import seaborn as sns

if __name__ == '__main__':
    sns.set_palette('deep', desat=.6)
    sns.set_context(rc={'figure.figsize': (8, 4)})
    x = np.linspace(0, 1, 100)
    params = [
        (0.5, 0.5),
        (1, 1),
        (4, 3),
        (2, 5),
        (6, 6)
    ]
    for p in params:
        y = beta.pdf(x, p[0], p[1])
        plt.plot(x, y, label='$\\alpha={}$, $\\beta={}$'.format(p[0], p[1]))

    plt.xlabel('$\\theta$, Fairness')
    plt.ylabel('Density')
    plt.legend(title='Parameters')
    plt.show()