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 "tags": ["binary"],
16 },
17 {
18 "name": "bernoulli-0.2",
19 "version": "1",
20 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.2, seed=0),
21 "tags": ["binary"],
22 },
23 {
24 "name": "bernoulli-0.3",
25 "version": "1",
26 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.3, seed=0),
27 "tags": ["binary"],
28 },
29 {
30 "name": "bernoulli-0.4",
31 "version": "1",
32 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.4, seed=0),
33 "tags": ["binary"],
34 },
35 {
36 "name": "bernoulli-0.5",
37 "version": "1",
38 "create": lambda: create_bernoulli(n_samples=1_000_000, p=0.5, seed=0),
39 "tags": ["binary"],
40 },
41]