32 lines
1019 B
Python
32 lines
1019 B
Python
# Author: Guillaume Lemaitre <g.lemaitre58@gmail.com>
|
|
# License: BSD 3 clause
|
|
|
|
import pytest
|
|
import numpy as np
|
|
|
|
from sklearn.mixture import GaussianMixture
|
|
from sklearn.mixture import BayesianGaussianMixture
|
|
|
|
|
|
@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)
|