Another implementation of assert raises from numpy

.github/workflows/build-code.yml

@@ -38,7 +38,7 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
-    - uses: actions/cache@v3
+    - uses: actions/cache@v4
       with:
         path: ${{ matrix.path }}
         key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}

msmbuilder/tests/test_dataset.py

@@ -33,14 +33,8 @@ def test_1():
         assert set(os.listdir(path)) == set(('PROVENANCE.txt', '00000000.npy'))
         np.testing.assert_array_equal(ds[0], X)
 
-
-        try:
+        with np.testing.assert_raises(IndexError):
             _ = ds[1]
-        except IndexError:
-            pass
-        else:
-            assert False
-        assert len(ds) == 1
 
         Y = np.zeros((10, 1))
         Z = np.ones((2, 2))
@@ -173,12 +167,8 @@ def test_hdf5_3():
 
 
 def test_union_no_longer_exists():
-    try:
+    with np.testing.assert_raises_regex(ValueError, r".*[Uu]se msmbuilder\.featurizer\.FeatureUnion.*"):
         mds = dataset(['ds1.h5', 'ds2.h5'], fmt='hdf5-union')
-    except ValueError as e:
-        assert re.match(r".*[Uu]se msmbuilder\.featurizer\.FeatureUnion.*", repr(e))
-    else:
-        assert False
 
 
 

msmbuilder/tests/test_featureunion.py

@@ -78,13 +78,8 @@ def test_uneven_n():
             # Uneven number of trajs!
 
             fu = FeatureUnion(normalize=False)
-            try:
+            with np.testing.assert_raises(ValueError):
                 fu.fit((ds1, ds2))
-            except ValueError:
-                pass
-            else:
-                assert False
-
 
 def test_uneven_len():
     with tempdir():
@@ -99,12 +94,8 @@ def test_uneven_len():
             # Uneven length!
 
             fu = FeatureUnion(normalize=False)
-            try:
+            with np.testing.assert_raises(ValueError):
                 fu.fit_transform((ds1, ds2))
-            except ValueError:
-                pass
-            else:
-                assert False
 
 
 def test_uneven_width():
@@ -116,9 +107,5 @@ def test_uneven_width():
     ds2[1] = np.random.randn(5, 3)
 
     fu = FeatureUnion(normalize=True)
-    try:
+    with np.testing.assert_raises(ValueError):
         fu.fit_transform((ds1, ds2))
-    except ValueError:
-        pass
-    else:
-        assert False