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_)