numpy2 support, drop py38 (#295)

azure-cibuildwheel.yml

@@ -2,15 +2,15 @@ jobs:
   - job: linux
     pool: { vmImage: 'Ubuntu-22.04' }
     variables:
-      CIBW_BUILD: cp3{8,9,10,11}-manylinux_x86_64
+      CIBW_BUILD: cp3{9,10,11}-manylinux_x86_64
       CIBW_BUILD_VERBOSITY: 2
     steps:
       - template: devtools/cibuildwheel.yml
 
   - job: macos
     pool: { vmImage: 'macOS-12' }
     variables:
-      CIBW_BUILD: cp3{8,9,10,11}-macosx_*
+      CIBW_BUILD: cp3{9,10,11}-macosx_*
       CIBW_ARCHS_MACOS: $(arch)
     strategy:
       matrix:
@@ -24,6 +24,6 @@ jobs:
   - job: windows
     pool: { vmImage: 'windows-2019' }
     variables:
-      CIBW_BUILD: cp3{8,9,10,11}-win_amd64
+      CIBW_BUILD: cp3{9,10,11}-win_amd64
     steps:
       - template: devtools/cibuildwheel.yml

deeptime/markov/tools/analysis/_api.py

@@ -1093,7 +1093,7 @@ def expectation(T, a, mu=None):
     >>> a = np.array([1.0, 0.0, 1.0])
     >>> m_a = expectation(T, a)
     >>> m_a # doctest: +ELLIPSIS
-    0.909090909...
+    np.float64(0.909090909...
 
     """
     # check if square matrix and remember size

deeptime/markov/tools/analysis/dense/_pcca.py

@@ -261,7 +261,7 @@ def _pcca_connected(P, n, pi=None):
     evecs[:, 0] = np.abs(evecs[:, 0])
 
     # Is there a significant complex component?
-    if not np.alltrue(np.isreal(evecs)):
+    if not np.all(np.isreal(evecs)):
         warnings.warn(
             "The given transition matrix has complex eigenvectors, so it doesn't exactly fulfill detailed balance. "
             "Forcing eigenvectors to be real and continuing. Be aware that this is not theoretically solid.")

deeptime/markov/tools/estimation/api.py

@@ -917,12 +917,12 @@ def log_likelihood(C, T):
     >>> C = np.array([[58, 7, 0], [6, 0, 4], [0, 3, 21]])
     >>> logL = log_likelihood(C, T)
     >>> logL # doctest: +ELLIPSIS
-    -38.2808034725...
+    np.float64(-38.2808034725...
 
     >>> C = np.array([[58, 20, 0], [6, 0, 4], [0, 3, 21]])
     >>> logL = log_likelihood(C, T)
     >>> logL # doctest: +ELLIPSIS
-    -68.2144096814...
+    np.float64(-68.2144096814...
 
     References
     ----------

deeptime/plots/chapman_kolmogorov.py

@@ -172,7 +172,7 @@ def plot_ck_test(data: ChapmanKolmogorovTest, height=2.5, aspect=1.,
 
     if any_complex:
         warnings.warn("Your CKtest contains imaginary components which are ignored during plotting.",
-                      category=np.ComplexWarning)
+                      category=np.exceptions.ComplexWarning)
 
     confidences = [confidences_est_l, confidences_est_r, confidences_pred_l, confidences_pred_r]
     confidences = [np.array(conf) for conf in confidences]

deeptime/plots/network.py

@@ -240,7 +240,7 @@ def state_sizes(self, value: Optional[np.ndarray]):
         if value is not None and len(value) != self.n_nodes:
             raise ValueError(f"State sizes must correspond to states (# = {self.n_nodes}) but was of "
                              f"length {len(value)}")
-        self._state_sizes = np.asfarray(value) if value is not None else np.ones(self.n_nodes)
+        self._state_sizes = np.asarray(value, dtype=float) if value is not None else np.ones(self.n_nodes)
 
     @property
     def node_sizes(self):

deeptime/util/stats.py

@@ -188,7 +188,7 @@ def evaluate_samples(samples: Iterable[Any], quantity: str, delimiter: str = '/'
     if quantity is not None:
         samples = [call_member(s, quantity, *args, **kwargs) for s in samples]
     try:
-        samples = np.asfarray(samples)
+        samples = np.asarray(samples, dtype=float)
     except:
         pass
     return samples

devtools/azure-pipelines-conda.yml

@@ -10,14 +10,12 @@ jobs:
 
   - job: 'MacOS_with_conda'
     pool:
-      vmImage: 'macOS-latest'
+      vmImage: 'macOS-12'
     steps:
       - bash: echo "##vso[task.prependpath]$CONDA/bin"
         displayName: Add conda to PATH
       - bash: sudo chown -R $USER $CONDA
         displayName: Take ownership of conda installation
-      - bash: conda install --yes --quiet libarchive sqlite -n base -c conda-forge
-        displayName: Fix missing sqlite and libarchive error
       - template: checkout.yml
       - template: conda-setup+build.yml
 

devtools/azure-pipelines-linux.yml

@@ -6,8 +6,6 @@ jobs:
 
   strategy:
     matrix:
-      Python38:
-        python.version: '3.8'
       Python39:
         python.version: '3.9'
       Python310:

devtools/azure-pipelines-osx.yml

@@ -7,8 +7,6 @@ jobs:
 
   strategy:
     matrix:
-      Python38:
-        python.version: '3.8'
       Python39:
         python.version: '3.9'
       Python310:

devtools/azure-pipelines-win.yml

@@ -6,8 +6,6 @@ jobs:
 
   strategy:
     matrix:
-      Python38:
-        python.version: '3.8'
       Python39:
         python.version: '3.9'
       Python310:

devtools/conda-setup+build.yml

@@ -10,6 +10,6 @@ steps:
   displayName: 'Update and install dependencies'
   continueOnError: false
 - bash: |
-    conda build devtools --python 3.11 --numpy 1.21
+    conda build devtools --python 3.11 --numpy 2.0.0
   displayName: 'Build and test'
   continueOnError: false

docs/source/conf.py

@@ -64,7 +64,7 @@ def filter(self, record: LogRecord) -> int:
     'sphinxcontrib.katex',
     'nbsphinx',
     'sphinx_gallery.gen_gallery',
-    'sphinx_gallery.load_style'
+    #'sphinx_gallery.load_style'
 ]
 
 # Add any paths that contain templates here, relative to this directory.

pyproject.toml

@@ -22,9 +22,9 @@ authors = [
 ]
 requires-python = ">= 3.8"
 dependencies = [
-    'numpy>=1.20',
+    'numpy',
     'scipy>=1.9.0',
-    'scikit-learn>=1.2.2',
+    'scikit-learn>=1.5.0',
     'threadpoolctl>=3.1.0'
 ]
 dynamic = ['version']
@@ -40,13 +40,13 @@ deep-learning = ['torch']
 plotting = ['matplotlib', 'networkx']
 units = ['pint>=0.20']
 tests = [
-    'torch>=1.12.0; platform_system!="Darwin" and python_version<"3.11"',
-    'pytest==7.1.2',
-    'pytest-cov==3.0.0',
+    'torch>=1.12.0; platform_system!="Darwin" and platform_system!="Windows"',
+    'pytest>=7.1.2',
+    'pytest-cov>=3.0.0',
     'coverage[toml]',
-    'pytest-xdist==2.5.0',
-    'flaky==3.7.0',
-    'tqdm==4.64.0',
+    'pytest-xdist>=2.5.0',
+    'flaky>=3.7.0',
+    'tqdm>=4.64.0',
     "cython>=0.29.30",
     "pybind11>=2.10.1",
     "networkx",
@@ -77,10 +77,10 @@ requires = [
     "scikit-build>=0.16",
     "cython>=0.29.30",
     "pybind11>=2.10.1",
-    "numpy>=1.20",
+    "numpy",
     "cmake>=3.24",
     "tomli; python_version < '3.11'",
-    "scipy==1.9.3",
+    "scipy>=1.9.3",
     "ninja; platform_system!='Windows'",
     "versioneer[toml]==0.28"
 ]

tests/markov/test_sample.py

@@ -35,7 +35,7 @@ def test_onetraj():
     assert (len(res) == len(expected))
     for i in range(len(res)):
         assert (res[i].shape == expected[i].shape)
-        assert (np.alltrue(res[i] == expected[i]))
+        assert (np.all(res[i] == expected[i]))
 
 
 def test_onetraj_sub():
@@ -46,7 +46,7 @@ def test_onetraj_sub():
     assert (len(res) == len(expected))
     for i in range(len(res)):
         assert (res[i].shape == expected[i].shape)
-        assert (np.alltrue(res[i] == expected[i]))
+        assert (np.all(res[i] == expected[i]))
 
 
 def test_twotraj():
@@ -58,15 +58,15 @@ def test_twotraj():
     assert (len(res) == len(expected))
     for i in range(len(res)):
         assert (res[i].shape == expected[i].shape)
-        assert (np.alltrue(res[i] == expected[i]))
+        assert (np.all(res[i] == expected[i]))
 
 
 def test_sample_by_sequence():
     dtraj = [0, 1, 2, 3, 2, 1, 0]
     idx = sample.compute_index_states(dtraj)
     seq = [0, 1, 1, 1, 0, 0, 0, 0, 1, 1]
     sidx = sample.indices_by_sequence(idx, seq)
-    assert (np.alltrue(sidx.shape == (len(seq), 2)))
+    assert (np.all(sidx.shape == (len(seq), 2)))
     for t in range(sidx.shape[0]):
         assert (sidx[t, 0] == 0)  # did we pick the right traj?
         assert (dtraj[sidx[t, 1]] == seq[t])  # did we pick the right states?

tests/markov/tools/analysis/impl/dense/pcca_test.py

@@ -117,16 +117,16 @@ def test_pcca_large(self):
         P = np.loadtxt(os.path.split(__file__)[0] + '/../../P_rev_251x251.dat')
         # n=2
         chi = pcca(P, 2)
-        assert (np.alltrue(chi >= 0))
-        assert (np.alltrue(chi <= 1))
+        assert (np.all(chi >= 0))
+        assert (np.all(chi <= 1))
         # n=3
         chi = pcca(P, 3)
-        assert (np.alltrue(chi >= 0))
-        assert (np.alltrue(chi <= 1))
+        assert (np.all(chi >= 0))
+        assert (np.all(chi <= 1))
         # n=4
         chi = pcca(P, 4)
-        assert (np.alltrue(chi >= 0))
-        assert (np.alltrue(chi <= 1))
+        assert (np.all(chi >= 0))
+        assert (np.all(chi <= 1))
 
     def test_pcca_coarsegrain(self):
         # fine-grained transition matrix

tests/plots/test_ck_test.py

@@ -43,7 +43,7 @@ def test_sanity_vamp(fractional):
 
     if fractional:
         with warnings.catch_warnings():
-            warnings.simplefilter("ignore", np.ComplexWarning)
+            warnings.simplefilter("ignore", np.exceptions.ComplexWarning)
             plot_ck_test(models[0].ck_test(models))
     else:
         plot_ck_test(models[0].ck_test(models))