/
test_datasets.py
57 lines (45 loc) · 1.85 KB
/
test_datasets.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
from itertools import product
import pytest
from ruptures.datasets import pw_constant, pw_linear, pw_normal, pw_wavy
@pytest.mark.parametrize("func", [pw_constant, pw_linear, pw_normal, pw_wavy])
def test_empty_arg(func):
func()
@pytest.mark.parametrize(
"func, n_samples, n_features, n_bkps, noise_std",
product([pw_constant], range(20, 1000, 200), range(1, 4), [2, 5, 3], [None, 1, 2]),
)
def test_constant(func, n_samples, n_features, n_bkps, noise_std):
signal, bkps = func(
n_samples=n_samples, n_features=n_features, n_bkps=n_bkps, noise_std=noise_std
)
assert signal.shape == (n_samples, n_features)
assert len(bkps) == n_bkps + 1
assert bkps[-1] == n_samples
@pytest.mark.parametrize(
"func, n_samples, n_features, n_bkps, noise_std",
product([pw_linear], range(20, 1000, 200), range(1, 4), [2, 5, 3], [None, 1, 2]),
)
def test_linear(func, n_samples, n_features, n_bkps, noise_std):
signal, bkps = func(
n_samples=n_samples, n_features=n_features, n_bkps=n_bkps, noise_std=noise_std
)
assert signal.shape == (n_samples, n_features + 1)
assert len(bkps) == n_bkps + 1
assert bkps[-1] == n_samples
@pytest.mark.parametrize(
"func, n_samples, n_bkps, noise_std",
product([pw_wavy], range(20, 1000, 200), [2, 5, 3], [None, 1, 2]),
)
def test_wavy(func, n_samples, n_bkps, noise_std):
signal, bkps = func(n_samples=n_samples, n_bkps=n_bkps, noise_std=noise_std)
assert signal.shape == (n_samples,)
assert len(bkps) == n_bkps + 1
assert bkps[-1] == n_samples
@pytest.mark.parametrize(
"func, n_samples, n_bkps", product([pw_normal], range(20, 1000, 200), [2, 5, 3])
)
def test_normal(func, n_samples, n_bkps):
signal, bkps = func(n_samples=n_samples, n_bkps=n_bkps)
assert signal.shape == (n_samples, 2)
assert len(bkps) == n_bkps + 1
assert bkps[-1] == n_samples