2023-06-09 01:12:07 +00:00
|
|
|
import squigglepy as sq
|
|
|
|
import numpy as np
|
|
|
|
|
|
|
|
p_a = 0.8
|
|
|
|
p_b = 0.5
|
|
|
|
p_c = p_a * p_b
|
|
|
|
|
2023-06-09 21:00:20 +00:00
|
|
|
dist_0 = 0
|
|
|
|
dist_1 = 1
|
2023-06-09 01:12:07 +00:00
|
|
|
dist_some = sq.to(1, 3)
|
|
|
|
dist_many = sq.to(2, 10)
|
|
|
|
|
|
|
|
dists = [dist_0, dist_1, dist_some, dist_many]
|
|
|
|
weights = [(1 - p_c), p_c/2, p_c/4, p_c/4 ]
|
|
|
|
|
|
|
|
result = sq.mixture(dists, weights)
|
|
|
|
result_samples = sq.sample(result, 1000000)
|
|
|
|
print(np.mean(result_samples))
|