From 60907b0104a2807667f175d9a8a328fd3f7f4ec8 Mon Sep 17 00:00:00 2001 From: ROUVREAU Vincent Date: Mon, 11 Jan 2021 16:25:18 +0100 Subject: Ignore doctest for atol doc. Rewrite unitary test for atol doc. To be synchronized --- src/python/test/test_representations.py | 26 +++++++++++++++++--------- 1 file changed, 17 insertions(+), 9 deletions(-) (limited to 'src/python/test/test_representations.py') diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py index 1c8f8cdb..cda1a15b 100755 --- a/src/python/test/test_representations.py +++ b/src/python/test/test_representations.py @@ -47,21 +47,29 @@ def test_multiple(): # Test sorted values as points order can be inverted, and sorted test is not documentation-friendly +# Note the test below must be up to date with the Atol class documentation def test_atol_doc(): a = np.array([[1, 2, 4], [1, 4, 0], [1, 0, 4]]) b = np.array([[4, 2, 0], [4, 4, 0], [4, 0, 2]]) c = np.array([[3, 2, -1], [1, 2, -1]]) atol_vectoriser = Atol(quantiser=KMeans(n_clusters=2, random_state=202006)) - assert np.sort(atol_vectoriser.fit(X=[a, b, c]).centers, axis=0) == \ - pytest.approx(np.array([[2. , 0.66666667, -0.4], \ - [2.6, 2.8 , 3.33333333]])) - assert np.sort(atol_vectoriser(a)) == pytest.approx(np.array([0.42375966, 1.18168665])) - assert np.sort(atol_vectoriser(c)) == pytest.approx(np.array([0.02062512, 1.25157463])) - assert np.sort(atol_vectoriser.transform(X=[a, b, c]), axis=0) == \ - pytest.approx(np.array([[0.02062512, 0.42375966], \ - [0.29861028, 1.06330156], \ - [1.18168665, 1.25157463]])) + # Atol will do + # X = np.concatenate([a,b,c]) + # kmeans = KMeans(n_clusters=2, random_state=202006).fit(X) + # kmeans.labels_ will be : array([1, 0, 1, 0, 0, 1, 0, 0]) + first_cluster = np.asarray([a[0], a[2], b[2]]) + second_cluster = np.asarray([a[1], b[0], b[2], c[0], c[1]]) + + # Check the center of the first_cluster and second_cluster are in Atol centers + centers = atol_vectoriser.fit(X=[a, b, c]).centers + np.isclose(centers, first_cluster.mean(axis=0)).all(1).any() + np.isclose(centers, second_cluster.mean(axis=0)).all(1).any() + + vectorization = atol_vectoriser.transform(X=[a, b, c]) + assert np.allclose(vectorization[0], atol_vectoriser(a)) + assert np.allclose(vectorization[1], atol_vectoriser(b)) + assert np.allclose(vectorization[2], atol_vectoriser(c)) def test_dummy_atol(): -- cgit v1.2.3