From 0afc650917ddf9fc4cf95fd86e0b6408f64a465d Mon Sep 17 00:00:00 2001 From: ROUVREAU Vincent Date: Mon, 11 Jan 2021 11:29:20 +0100 Subject: Remove sphinx doc test for atol as points order can be inverted and add it in a UT but sorted --- src/python/gudhi/representations/vector_methods.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'src/python/gudhi/representations/vector_methods.py') diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index cdcb1fde..d4449e7d 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -606,16 +606,16 @@ class Atol(BaseEstimator, TransformerMixin): >>> c = np.array([[3, 2, -1], [1, 2, -1]]) >>> atol_vectoriser = Atol(quantiser=KMeans(n_clusters=2, random_state=202006)) >>> atol_vectoriser.fit(X=[a, b, c]).centers - array([[ 2. , 0.66666667, 3.33333333], - [ 2.6 , 2.8 , -0.4 ]]) + >>> # array([[ 2. , 0.66666667, 3.33333333], + >>> # [ 2.6 , 2.8 , -0.4 ]]) >>> atol_vectoriser(a) - array([1.18168665, 0.42375966]) + >>> # array([1.18168665, 0.42375966]) >>> atol_vectoriser(c) - array([0.02062512, 1.25157463]) + >>> # array([0.02062512, 1.25157463]) >>> atol_vectoriser.transform(X=[a, b, c]) - array([[1.18168665, 0.42375966], - [0.29861028, 1.06330156], - [0.02062512, 1.25157463]]) + >>> # array([[1.18168665, 0.42375966], + >>> # [0.29861028, 1.06330156], + >>> # [0.02062512, 1.25157463]]) """ def __init__(self, quantiser, weighting_method="cloud", contrast="gaussian"): """ -- cgit v1.2.3 From 2a29df7cd54e9689e93bab90e3f64c84e8e8790f Mon Sep 17 00:00:00 2001 From: ROUVREAU Vincent Date: Mon, 11 Jan 2021 13:59:01 +0100 Subject: skip doctest (but run them) --- src/python/gudhi/representations/vector_methods.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'src/python/gudhi/representations/vector_methods.py') diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index d4449e7d..5ec2abd0 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -605,14 +605,14 @@ class Atol(BaseEstimator, TransformerMixin): >>> 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)) - >>> atol_vectoriser.fit(X=[a, b, c]).centers + >>> atol_vectoriser.fit(X=[a, b, c]).centers #doctest: +SKIP >>> # array([[ 2. , 0.66666667, 3.33333333], >>> # [ 2.6 , 2.8 , -0.4 ]]) >>> atol_vectoriser(a) - >>> # array([1.18168665, 0.42375966]) + >>> # array([1.18168665, 0.42375966]) #doctest: +SKIP >>> atol_vectoriser(c) - >>> # array([0.02062512, 1.25157463]) - >>> atol_vectoriser.transform(X=[a, b, c]) + >>> # array([0.02062512, 1.25157463]) #doctest: +SKIP + >>> atol_vectoriser.transform(X=[a, b, c]) #doctest: +SKIP >>> # array([[1.18168665, 0.42375966], >>> # [0.29861028, 1.06330156], >>> # [0.02062512, 1.25157463]]) -- cgit v1.2.3 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/gudhi/representations/vector_methods.py | 9 ++++---- src/python/test/test_representations.py | 26 ++++++++++++++-------- 2 files changed, 22 insertions(+), 13 deletions(-) (limited to 'src/python/gudhi/representations/vector_methods.py') diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index 5ec2abd0..84bc99a2 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -605,18 +605,19 @@ class Atol(BaseEstimator, TransformerMixin): >>> 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)) - >>> atol_vectoriser.fit(X=[a, b, c]).centers #doctest: +SKIP + >>> atol_vectoriser.fit(X=[a, b, c]).centers # doctest: +SKIP >>> # array([[ 2. , 0.66666667, 3.33333333], >>> # [ 2.6 , 2.8 , -0.4 ]]) >>> atol_vectoriser(a) - >>> # array([1.18168665, 0.42375966]) #doctest: +SKIP + >>> # array([1.18168665, 0.42375966]) # doctest: +SKIP >>> atol_vectoriser(c) - >>> # array([0.02062512, 1.25157463]) #doctest: +SKIP - >>> atol_vectoriser.transform(X=[a, b, c]) #doctest: +SKIP + >>> # array([0.02062512, 1.25157463]) # doctest: +SKIP + >>> atol_vectoriser.transform(X=[a, b, c]) # doctest: +SKIP >>> # array([[1.18168665, 0.42375966], >>> # [0.29861028, 1.06330156], >>> # [0.02062512, 1.25157463]]) """ + # Note the example above must be up to date with the one in tests called test_atol_doc def __init__(self, quantiser, weighting_method="cloud", contrast="gaussian"): """ Constructor for the Atol measure vectorisation class. 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