TST replace pytest.warns(None) in test_label_propagation.py (#23010)

Ben3940 · jeremiedbb · thomasjpfan · web-flow · commit 408afccea9e3 · 2022-04-04T15:09:46.000+02:00
Co-authored-by: Jérémie du Boisberranger &lt;34657725+jeremiedbb@users.noreply.github.com&gt;
Co-authored-by: Thomas J. Fan &lt;thomasjpfan@gmail.com&gt;
diff --git a/sklearn/semi_supervised/tests/test_label_propagation.py b/sklearn/semi_supervised/tests/test_label_propagation.py
@@ -2,6 +2,7 @@
 
 import numpy as np
 import pytest
+import warnings
 
 from scipy.sparse import issparse
 from sklearn.semi_supervised import _label_propagation as label_propagation
@@ -151,14 +152,14 @@ def test_convergence_warning():
     assert mdl.n_iter_ == mdl.max_iter
 
     mdl = label_propagation.LabelSpreading(kernel="rbf", max_iter=500)
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", ConvergenceWarning)
         mdl.fit(X, y)
-    assert not [w.message for w in record]
 
     mdl = label_propagation.LabelPropagation(kernel="rbf", max_iter=500)
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", ConvergenceWarning)
         mdl.fit(X, y)
-    assert not [w.message for w in record]
 
 
 @pytest.mark.parametrize(
@@ -173,9 +174,9 @@ def test_label_propagation_non_zero_normalizer(LabelPropagationCls):
     X = np.array([[100.0, 100.0], [100.0, 100.0], [0.0, 0.0], [0.0, 0.0]])
     y = np.array([0, 1, -1, -1])
     mdl = LabelPropagationCls(kernel="knn", max_iter=100, n_neighbors=1)
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", RuntimeWarning)
         mdl.fit(X, y)
-    assert not [w.message for w in record]
 
 
 def test_predict_sparse_callable_kernel():
