make check_preprocessor private (#235)

Author: wdevazelhes

metric_learn/base_metric.py

@@ -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)
@@ -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_,

test/test_utils.py

@@ -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)))
@@ -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: