Лабораторная 1 / Фибоначчи с запаздываниями / Lab1

import matplotlib.pyplot as plt
import numpy as np
import random
import time


class MyRandom:
    def __init__(self, m, debug=False):
        self.m = m
        if debug:
            random.seed(0)
            self.seed = [random.randint(0, 2**m) for _ in range(55)]
        else:
            random.seed(time.time())
            self.seed = [random.randint(0, 2**m) for _ in range(55)]

    def next(self):
        x = (self.seed[-55] + self.seed[-24]) % 2**self.m
        self.seed.pop(0)
        self.seed.append(x)

        return x / 2**self.m


rand = MyRandom(16)
rand_list = []
for i in range(5000):
    rand_list.append(rand.next())


N = len(rand_list)
M = sum(rand_list) / N
D = (sum(z * z for z in rand_list) - (M * M) * N) / N
print(f"Моменты: M = {M}; D = {D}")

base = np.linspace(0, 1, N)
plt.hist([rand_list, base],
         bins=10,
         weights=[np.ones_like(rand_list) / len(rand_list),
         np.ones_like(base) / base.size],
         label=['Эмпирическое', 'Теоретическое'])
plt.legend(loc='lower right')
plt.savefig("Vasilisa/ms1.1.svg")
plt.show()


S_list = (2, 5, 10)
for S in S_list:
    targetNs = [x*200 for x in range(1, 40)]
    Rs = []
    for targetN in targetNs:
        rand = MyRandom(16)
        rand_list.clear()
        for k in range(targetN):
            rand_list.append(rand.next())
        N = len(rand_list)
        randX = rand_list[:N-S]
        randY = rand_list[S:]
        R = np.corrcoef(randX, randY)[0, 1]
        Rs.append(R)
    if S == S_list[0]:
        plt.plot(targetNs, Rs, color='r', label='s = 2')
    if S == S_list[1]:
        plt.plot(targetNs, Rs, color='b', label='s = 5')
    if S == S_list[2]:
        plt.plot(targetNs, Rs, color='g', label='s = 10')
plt.title("Коэффициент корреляции при s = 2, 5, 10")
plt.legend()
plt.xlabel("N")
plt.ylabel("R")
plt.grid(True)
plt.axhline(y=0, color='k')
plt.axvline(x=0, color='k')
plt.savefig("Vasilisa/ms1.s.svg")
plt.show()