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-rw-r--r--src/python/gudhi/representations/vector_methods.py19
1 files changed, 10 insertions, 9 deletions
diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py
index cdcb1fde..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
- array([[ 2. , 0.66666667, 3.33333333],
- [ 2.6 , 2.8 , -0.4 ]])
+ >>> 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([[1.18168665, 0.42375966],
- [0.29861028, 1.06330156],
- [0.02062512, 1.25157463]])
+ >>> # 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.