局所的な平均化を繰り返すことで全体の平均値に収束するかの実験 #code

average_test.py

from functools import reduce
import random
import numpy as np
import matplotlib.pyplot as plt
print(plt.style.available)
plt.style.use('fivethirtyeight')

threshold = 0.8


def local_ave(l, ind):
    # print(ind)
    ave = reduce(lambda a, b: a + l[b], ind, 0) / len(ind)
    for i in ind:
        if random.random() < threshold:
            l[i] = ave


if __name__ == '__main__':
    n = np.random.rand(20)
    iter = 30
    print(np.mean(n))
    xs = [[x] for x in n]
    indxs = range(len(n))
    t = np.arange(iter)
    for x in t:
        local_ave(n, random.sample(indxs, random.randrange(1, len(n))))
        for i in range(len(n)):
            xs[i].append(n[i])
    print(n)
    fig = plt.subplots(num=None, figsize=(10, 8), dpi=80,
                       facecolor='w', edgecolor='k')
    t = np.append(t, iter + 1)
    for i in range(len(n)):
        plt.plot(t, xs[i], label="n%d" % (i + 1))
    plt.xlabel('time')
    plt.ylabel('value')
    plt.tick_params(labelsize=18)
    plt.grid()
    plt.legend(loc="best")
    plt.show()