1import numpy as np
4def create_bernoulli(*, n_samples: int, p: float, seed: int) -> np.ndarray:
5 rng = np.random.default_rng(seed)
6 x = rng.binomial(1, p, n_samples).astype(np.uint8)
7 return x
10datasets = [
11 {
12 "name": "bernoulli-0.1",
13 "version": "1",
14 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.1, seed=0),
15 "description": "Binary sequence with 10% probability of ones.",
16 "tags": ["binary"],
17 },
18 {
19 "name": "bernoulli-0.2",
20 "version": "1",
21 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.2, seed=0),
22 "description": "Binary sequence with 20% probability of ones.",
23 "tags": ["binary"],
24 },
25 {
26 "name": "bernoulli-0.3",
27 "version": "1",
28 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.3, seed=0),
29 "description": "Binary sequence with 30% probability of ones.",
30 "tags": ["binary"],
31 },
32 {
33 "name": "bernoulli-0.4",
34 "version": "1",
35 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.4, seed=0),
36 "description": "Binary sequence with 40% probability of ones.",
37 "tags": ["binary"],
38 },
39 {
40 "name": "bernoulli-0.5",
41 "version": "1",
42 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.5, seed=0),
43 "description": "Binary sequence with 50% probability of ones and 50% probability of zeros.",
44 "tags": ["binary"],
45 },
46]