Fix 5 test regarding make_spd_matrix usage from sklearn (#321)

* Add venv to gitignore

* Fix 5 test regarding make_spd_matrix usage from sklearn

Author: mvargas33

.gitignore

@@ -7,4 +7,5 @@ htmlcov/
 .cache/
 .pytest_cache/
 doc/auto_examples/*
-doc/generated/*
+doc/generated/*
+venv/

test/metric_learn_test.py

@@ -929,7 +929,7 @@ def test_singleton_class(self):
       X = X[[ind_0[0], ind_1[0], ind_2[0]]]
       y = y[[ind_0[0], ind_1[0], ind_2[0]]]
 
-      A = make_spd_matrix(X.shape[1], X.shape[1])
+      A = make_spd_matrix(n_dim=X.shape[1], random_state=X.shape[1])
       nca = NCA(init=A, max_iter=30, n_components=X.shape[1])
       nca.fit(X, y)
       assert_array_equal(nca.components_, A)
@@ -940,7 +940,7 @@ def test_one_class(self):
       X = self.iris_points[self.iris_labels == 0]
       y = self.iris_labels[self.iris_labels == 0]
 
-      A = make_spd_matrix(X.shape[1], X.shape[1])
+      A = make_spd_matrix(n_dim=X.shape[1], random_state=X.shape[1])
       nca = NCA(init=A, max_iter=30, n_components=X.shape[1])
       nca.fit(X, y)
       assert_array_equal(nca.components_, A)

test/test_mahalanobis_mixin.py

@@ -503,12 +503,12 @@ def test_init_mahalanobis(estimator, build_dataset):
       model.fit(input_data, labels)
 
       # Initialize with a random spd matrix
-      init = make_spd_matrix(X.shape[1], random_state=rng)
+      init = make_spd_matrix(n_dim=X.shape[1], random_state=rng)
       model.set_params(**{param: init})
       model.fit(input_data, labels)
 
       # init.shape[1] must match X.shape[1]
-      init = make_spd_matrix(X.shape[1] + 1, X.shape[1] + 1)
+      init = make_spd_matrix(n_dim=X.shape[1] + 1, random_state=rng)
       model.set_params(**{param: init})
       msg = ('The input dimensionality {} of the given '
              'mahalanobis matrix `{}` must match the '