def test_set_model_params(mock_kmeans):
model = Mock()
mock_kmeans.return_value = model
n_clusters = 5
n_features = 5
init = 'k-means++'
n_init = 1 # Explicit initial center position passed: performing only one init
kmm = KMeansModel(n_clusters, n_features, init, n_init)
params = np.random.rand(10).reshape((5, 2))
kmm.set_model_params(params)
assert model == kmm._model
assert np.array_equal(params, kmm._init)
assert n_init == kmm._n_init
assert n_features == kmm._n_features
assert np.array_equal(params, kmm._model.cluster_centers_)
def test_set_model_params_zeros_array(mock_kmeans):
model = Mock()
mock_kmeans.return_value = model
n_clusters = 5
n_features = 5
init = 'k-means++'
n_init = 10
kmm = KMeansModel(n_clusters, n_features, init, n_init)
params = np.zeros(10).reshape((5, 2))
kmm.set_model_params(params)
assert model == kmm._model
assert init == kmm._init
assert n_init == kmm._n_init
assert n_features == kmm._n_features
assert np.array_equal(np.zeros((params.shape[0], n_features)),
kmm._model.cluster_centers_)