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
|
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
import numpy as np
import pytest
from sklearn.mixture import BayesianGaussianMixture, GaussianMixture
@pytest.mark.parametrize("estimator", [GaussianMixture(), BayesianGaussianMixture()])
def test_gaussian_mixture_n_iter(estimator):
# check that n_iter is the number of iteration performed.
rng = np.random.RandomState(0)
X = rng.rand(10, 5)
max_iter = 1
estimator.set_params(max_iter=max_iter)
estimator.fit(X)
assert estimator.n_iter_ == max_iter
@pytest.mark.parametrize("estimator", [GaussianMixture(), BayesianGaussianMixture()])
def test_mixture_n_components_greater_than_n_samples_error(estimator):
"""Check error when n_components <= n_samples"""
rng = np.random.RandomState(0)
X = rng.rand(10, 5)
estimator.set_params(n_components=12)
msg = "Expected n_samples >= n_components"
with pytest.raises(ValueError, match=msg):
estimator.fit(X)
|
