def test_classify_with_ds_diff_sizes():
query = np.ones((10, 2))
predictions = np.ones((5, 3))
desknn_test = DESClustering(create_pool_classifiers())
with pytest.raises(ValueError):
desknn_test.classify_with_ds(query, predictions)
def test_classify_with_ds_diff_sizes():
query = np.ones((10, 2))
predictions = np.ones((5, 3))
des_clustering = DESClustering()
with pytest.raises(ValueError):
des_clustering.classify_with_ds(query, predictions)
def test_classify_with_ds_single_sample():
query = np.ones(2)
predictions = np.array([0, 1, 0])
desknn_test = DESClustering(create_pool_classifiers())
desknn_test.select = MagicMock(return_value=np.array([[0, 2]]))
result = desknn_test.classify_with_ds(query, predictions)
assert np.allclose(result, 0)
def test_classify_instance():
query = np.ones((1, 2))
clustering_test = DESClustering(create_pool_classifiers() * 4, k=2)
clustering_test.select = MagicMock(return_value=[0, 1, 2, 3, 5, 6, 7, 9])
predictions = []
for clf in clustering_test.pool_classifiers:
predictions.append(clf.predict(query)[0])
predicted = clustering_test.classify_with_ds(query, np.array(predictions))
assert predicted == 0