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from collections import Counter
from statistics import fmean, pstdev
from matplotlib import pyplot as plt
from bitarray.util import random_k, sum_indices
from sample import SampleMeanDist
# The code will also work, if you change these parameters here:
SMD = SampleMeanDist(n=1_000, k=600)
M = 100_000 # number of trails
DX = 2.5 # width used for counting trail outcomes
def plot_pdf(plt, xmin, xmax):
X = []
Y = []
n = 2_000
for i in range(n + 1):
x = xmin + i * (xmax - xmin) / n
X.append(x)
Y.append(SMD.pdf(x) * DX)
plt.plot(X, Y)
def plot_count(plt, C):
X = []
Y = []
for i in range(min(C), max(C) + 1):
x = i * DX
X.append(x)
Y.append(C[i] / M)
plt.scatter(X, Y, color='red')
if __name__ == '__main__':
SMD.print()
C = Counter()
values = []
for _ in range(M):
x = sum_indices(random_k(SMD.n, SMD.k)) / SMD.k
C[round(x / DX)] += 1
values.append(x)
assert C.total() == M
print("mean", fmean(values))
print("stdev", pstdev(values, SMD.mu))
plot_count(plt, C)
plot_pdf(plt, min(C) * DX, max(C) * DX)
plt.show()
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