remove usage of nose.tools

- They aren't supported by Python 3.12 due to their usage on imp library

.gitignore

@@ -18,6 +18,8 @@ develop-eggs
 lib
 lib64
 __pycache__
+Scripts/*
+pyvenv.cfg
 
 # Installer logs
 pip-log.txt

msmbuilder/tests/test_dataset.py

@@ -3,10 +3,9 @@
 import os
 import shutil
 import tempfile
-
+import re
 import numpy as np
 from mdtraj.testing import get_fn
-from nose.tools import assert_raises, assert_raises_regexp
 # sklearn.externals.joblib is removed in scikit-learn v0.23
 try:
     from joblib import Parallel, delayed
@@ -34,7 +33,13 @@ def test_1():
         assert set(os.listdir(path)) == set(('PROVENANCE.txt', '00000000.npy'))
         np.testing.assert_array_equal(ds[0], X)
 
-        assert_raises(IndexError, lambda: ds[1])
+
+        try:
+            _ = ds[1]
+        except IndexError:
+            pass
+        else:
+            assert False
         assert len(ds) == 1
 
         Y = np.zeros((10, 1))
@@ -168,9 +173,13 @@ def test_hdf5_3():
 
 
 def test_union_no_longer_exists():
-    with assert_raises_regexp(ValueError,
-                              r".*[Uu]se msmbuilder\.featurizer\.FeatureUnion.*"):
+    try:
         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
+
 
 
 def test_order_1():

msmbuilder/tests/test_featureunion.py

@@ -1,7 +1,6 @@
 from __future__ import print_function, absolute_import, division
 
 import numpy as np
-from nose.tools import assert_raises
 
 from msmbuilder.dataset import dataset
 from msmbuilder.featurizer import FeatureUnion
@@ -29,14 +28,8 @@ def test_union():
 
 
 def test_normalize():
-    ds1 = [
-        np.random.randn(10, 2),
-        np.random.randn(5, 2)
-    ]
-    ds2 = [
-        100 * np.random.randn(10, 3),
-        100 * np.random.randn(5, 3)
-    ]
+    ds1 = [np.random.randn(10, 2), np.random.randn(5, 2)]
+    ds2 = [100 * np.random.randn(10, 3), 100 * np.random.randn(5, 3)]
 
     fu = FeatureUnion(normalize=True)
     mds = fu.fit_transform((ds1, ds2))
@@ -51,8 +44,9 @@ def test_normalize():
 def test_dataset():
     with tempdir():
         # This doesn't work with py2.6
-        with dataset('ds1.h5', 'w', 'hdf5') as ds1, \
-                dataset('ds2.h5', 'w', 'hdf5') as ds2:
+        with dataset("ds1.h5", "w", "hdf5") as ds1, dataset(
+            "ds2.h5", "w", "hdf5"
+        ) as ds2:
             ds1[0] = np.random.randn(10, 2)
             ds1[1] = np.random.randn(5, 2)
             ds2[0] = np.random.randn(10, 4)
@@ -75,32 +69,42 @@ def test_dataset():
 def test_uneven_n():
     with tempdir():
         # This doesn't work with py2.6
-        with dataset('ds1/', 'w', 'dir-npy') as ds1, \
-                dataset('ds2/', 'w', 'dir-npy') as ds2:
+        with dataset("ds1/", "w", "dir-npy") as ds1, dataset(
+            "ds2/", "w", "dir-npy"
+        ) as ds2:
             ds1[0] = np.random.randn(10, 2)
             ds1[1] = np.random.randn(5, 2)
             ds2[0] = np.random.randn(10, 4)
             # Uneven number of trajs!
 
             fu = FeatureUnion(normalize=False)
-            with assert_raises(ValueError):
+            try:
                 fu.fit((ds1, ds2))
+            except ValueError:
+                pass
+            else:
+                assert False
 
 
 def test_uneven_len():
     with tempdir():
         # This doesn't work with py2.6
-        with dataset('ds1/', 'w', 'dir-npy') as ds1, \
-                dataset('ds2/', 'w', 'dir-npy') as ds2:
+        with dataset("ds1/", "w", "dir-npy") as ds1, dataset(
+            "ds2/", "w", "dir-npy"
+        ) as ds2:
             ds1[0] = np.random.randn(10, 2)
             ds1[1] = np.random.randn(5, 2)
             ds2[0] = np.random.randn(10, 4)
             ds2[1] = np.random.randn(10, 4)
             # Uneven length!
 
             fu = FeatureUnion(normalize=False)
-            with assert_raises(ValueError):
+            try:
                 fu.fit_transform((ds1, ds2))
+            except ValueError:
+                pass
+            else:
+                assert False
 
 
 def test_uneven_width():
@@ -112,5 +116,9 @@ def test_uneven_width():
     ds2[1] = np.random.randn(5, 3)
 
     fu = FeatureUnion(normalize=True)
-    with assert_raises(ValueError):
+    try:
         fu.fit_transform((ds1, ds2))
+    except ValueError:
+        pass
+    else:
+        assert False