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[MRG] make check_preprocessor private #235

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Merged
merged 1 commit into from
Jul 6, 2019
Merged

[MRG] make check_preprocessor private #235

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4 changes: 2 additions & 2 deletions metric_learn/base_metric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ def score_pairs(self, pairs):
learner is.
"""

def check_preprocessor(self):
def _check_preprocessor(self):
"""Initializes the preprocessor"""
if _is_arraylike(self.preprocessor):
self.preprocessor_ = ArrayIndexer(self.preprocessor)
Expand Down Expand Up @@ -92,7 +92,7 @@ def _prepare_inputs(self, X, y=None, type_of_inputs='classic',
y: `numpy.ndarray` (optional)
The checked input labels array.
"""
self.check_preprocessor()
self._check_preprocessor()
return check_input(X, y,
type_of_inputs=type_of_inputs,
preprocessor=self.preprocessor_,
Expand Down
4 changes: 2 additions & 2 deletions test/test_utils.py
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Expand Up @@ -779,7 +779,7 @@ class MockMetricLearner(MahalanobisMixin):

mock_algo = MockMetricLearner(preprocessor=preprocessor)
with pytest.raises(ValueError) as e:
mock_algo.check_preprocessor()
mock_algo._check_preprocessor()
assert str(e.value) == ("Invalid type for the preprocessor: {}. You should "
"provide either None, an array-like object, "
"or a callable.".format(type(preprocessor)))
Expand Down Expand Up @@ -812,7 +812,7 @@ def test_error_message_t_score_pairs(estimator, _):
"""
estimator = clone(estimator)
set_random_state(estimator)
estimator.check_preprocessor()
estimator._check_preprocessor()
triplets = np.array([[[1.3, 6.3], [3., 6.8], [6.5, 4.4]],
[[1.9, 5.3], [1., 7.8], [3.2, 1.2]]])
with pytest.raises(ValueError) as raised_err:
Expand Down