#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter


def function_pdf(element: list[int]):
    plt.hist(element, bins=500, histtype='step')
    plt.show()


def function_cdf(element: list[int]):
    plt.hist(element, bins=500, cumulative=True, histtype='step')
    plt.show()


def function_1000_cdf(element: list[int]):
    plt.hist(element, bins=250, histtype='step', label='x', cumulative=True,
             weights=np.ones(len(element)) / len(element))
    plt.hist(element[:1000], bins=100, histtype='step', label='y', cumulative=True, weights=np.ones(1000) / 1000)
    plt.gca().yaxis.set_major_formatter(PercentFormatter(1))
    plt.show()


def normal_distribution() -> list[int]:
    with open('normal_distribution.txt') as fin:
        context = fin.read()
    return list(map(int, context.splitlines()))


if __name__ == '__main__':
    elements = normal_distribution()
    function_pdf(elements)
    function_cdf(elements)
    function_1000_cdf(elements)