fix: don't initialize eigsh with vector in null(L); break: numpy >= 2.0

.github/workflows/build.yaml

@@ -11,12 +11,12 @@ jobs:
         os: [ubuntu-latest, macos-11, windows-latest]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
 
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v5
         name: Install Python
         with:
-          python-version: '3.8'
+          python-version: '3.10'
 
       - name: Install dependencies
         run: |
@@ -26,26 +26,26 @@ jobs:
           pip install -r requirements.txt
 
       - name: Build wheels
-        uses: pypa/cibuildwheel@v2.11.2
+        uses: pypa/cibuildwheel@v2.23.3
         env:
-          CIBW_BUILD: "cp38* cp39* cp310* cp311*"
+          CIBW_BUILD: "cp310* cp311* cp312* cp313"
           CIBW_SKIP: "*-win32 *-manylinux_i686 *-musllinux*"
           CIBW_ARCHS_MACOS: x86_64 arm64
 
-      - uses: actions/upload-artifact@v2
+      - uses: actions/upload-artifact@v4
         with:
           path: ./wheelhouse/*.whl
 
   build_sdist:
     name: Build source distribution
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
 
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v5
         name: Install Python
         with:
-          python-version: '3.8'
+          python-version: '3.10'
 
       - name: Install dependencies
         run: |
@@ -57,7 +57,7 @@ jobs:
       - name: Build sdist
         run: python setup.py sdist
 
-      - uses: actions/upload-artifact@v2
+      - uses: actions/upload-artifact@v4
         with:
           path: dist/*.tar.gz
 
@@ -69,7 +69,7 @@ jobs:
     # alternatively, to publish when a GitHub Release is created, use the following rule:
     #if: github.event_name == 'release' && github.event.action == 'published'
     steps:
-      - uses: actions/download-artifact@v2
+      - uses: actions/download-artifact@v4
         with:
           name: artifact
           path: dist

.github/workflows/run_tests.yaml

@@ -9,37 +9,27 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
-        python-version: ${{ matrix.python-version }}
+        python-version: '${{ matrix.python-version }}'
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
         pip install setuptools wheel
         pip install flake8 pytest
-    - if: matrix.python-version == '3.7'
-      run: pip install numpy==1.17.5
-
-    - if: matrix.python-version == '3.8'
-      run: pip install numpy==1.17.5
-
-    - if: matrix.python-version == '3.9'
-      run: pip install numpy==1.21.0
+        pip install numpy==2.2.5
 
       # install cpu versions of torch for CI
     - if: matrix.os == 'macos-latest'
-      run: pip install torch==1.8.0 torchvision==0.9.0
+      run: pip install torch==2.7.0 torchvision==0.22.0
 
     - if: matrix.os == 'ubuntu-latest'
-      run: pip install --find-links https://download.pytorch.org/whl/torch_stable.html torch==1.8.0+cpu torchvision==0.9.0+cpu
-
-    - if: matrix.os == 'windows-latest'
-      run: pip install --find-links https://download.pytorch.org/whl/torch_stable.html torch==1.8.0+cpu torchvision==0.9.0+cpu
+      run: pip install torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/cpu
 
     - name: Lint with flake8
       run: |

pymde/experiment_utils.py

@@ -139,8 +139,8 @@ def _is_discrete(dtype):
             for other in (
                 np.integer,
                 np.bool_,
-                np.string_,
-                np.unicode_,
+                np.bytes_,
+                np.str_,
                 np.object_,
             )
         ]

pymde/functions/losses.py

@@ -5,7 +5,7 @@
 
 .. math::
 
-    f_k(d_k) = \\ell(d_k, \delta_k), \\quad k=1, \\ldots, p,
+    f_k(d_k) = \\ell(d_k, \\delta_k), \\quad k=1, \\ldots, p,
 
 where
 :math:`\\ell` is a loss function, :math:`\\delta_k` is a nonnegative deviation
@@ -102,7 +102,7 @@ class Huber(Function):
     """
     .. math::
 
-        \ell(d, \\delta) = \\begin{cases}
+        \\ell(d, \\delta) = \\begin{cases}
             \\cdot (d - \\delta)^2 & d < \\text{threshold} \\\\
             \\text{threshold}(2(d - \\delta) - \\cdot \\text{threshold})
             & d \\geq \\text{threshold}

pymde/functions/penalties.py

@@ -308,7 +308,7 @@ def forward(self, distances):
 
 
 class Log1p(Function):
-    """:math:`p(d) = \log(1 + d^{\\text{exponent}})`"""
+    """:math:`p(d) = \\log(1 + d^{\\text{exponent}})`"""
 
     def __init__(self, weights, exponent=1.5):
         super(Log1p, self).__init__()
@@ -322,7 +322,7 @@ def forward(self, distances):
 
 
 class Log(Function):
-    """:math:`p(d) = \log(1 - \\exp(-d^\\text{exponent}))`"""
+    """:math:`p(d) = \\log(1 - \\exp(-d^\\text{exponent}))`"""
 
     def __init__(self, weights, exponent=1.0):
         super(Log, self).__init__()

pymde/preprocess/graph.py

@@ -336,7 +336,7 @@ def _shortest_paths(shape, node, max_length, unweighted, sample_prob):
 
 
 def __init_process(data, indptr, indices):
-    global __this_module
+    global __this_module  # noqa: F824
     __this_module.__data = data
     __this_module.__indptr = indptr
     __this_module.__indices = indices
@@ -395,7 +395,7 @@ def shortest_paths(
     if verbose:
         LOGGER.info(
             f"Computing shortest path distances (retaining "
-            f"{100*retain_fraction:.2f} percent with "
+            f"{100 * retain_fraction:.2f} percent with "
             f"max_distance={max_length}) ..."
         )
 
@@ -419,7 +419,7 @@ def to_shared_memory(array):
         array = np.ctypeslib.as_ctypes(array)
         return sharedctypes.RawArray(array._type_, array)
 
-    global __this_module
+    global __this_module  # noqa: F824
     data = __this_module.__data = to_shared_memory(graph.A.data)
     indptr = __this_module.__indptr = to_shared_memory(graph.A.indptr)
     indices = __this_module.__indices = to_shared_memory(graph.A.indices)

pymde/quadratic.py

@@ -88,7 +88,6 @@ def _spectral(
             which="SM",
             ncv=num_lanczos_vectors,
             tol=1e-4,
-            v0=np.ones(L.shape[0]),
             maxiter=L.shape[0] * 5,
         )
         order = np.argsort(eigenvalues)[1:k]
@@ -123,17 +122,17 @@ def _spectral(
 def spectral(
     n_items, embedding_dim, edges, weights, cg=False, max_iter=40, device="cpu"
 ):
-    """Compute a spectral embedding
+    r"""Compute a spectral embedding
 
 
     Solves the quadratic MDE problem
 
     .. math::
 
-        \\begin{array}{ll}
-        \\mbox{minimize} & \\sum_{(i, j) in \\text{edges}} w_{ij} d_{ij}^2 \\\\
-        \\mbox{subject to} & (1/n) X^T X = I, \quad d_{ij} = |x_i - x_j|_2.
-        \\end{array}
+        \begin{array}{ll}
+        \mbox{minimize} & \sum_{(i, j) in \text{edges}} w_{ij} d_{ij}^2 \\
+        \mbox{subject to} & (1/n) X^T X = I, \quad d_{ij} = |x_i - x_j|_2.
+        \end{array}
 
     By default, the problem is solved using a Lanczos method. If cg=True,
     LOBPCG is used; LOBPCG is warm-started by running a projected quasi-newton

pyproject.toml

@@ -1,45 +1,14 @@
 [build-system]
 requires = [
   # NumPy dependencies copied from SciPy:
-  # https://github.com/scipy/scipy/blob/3df34d96123678e4b1b03aba83b84d8ff08817e5/pyproject.toml
-  # NumPy dependencies - to update these, sync from
-  # https://github.com/scipy/oldest-supported-numpy/, and then
-  # update minimum version to match our install_requires min version
-  # ----------------------------------------------------------------
-
-  # now matches minimum supported version, keep here as separate requirement
-  # to be able to sync more easily with oldest-supported-numpy
-  "numpy==1.19.5; python_version=='3.8' and platform_machine=='aarch64' and platform_python_implementation != 'PyPy'",
-
-  # arm64 on Darwin supports Python 3.8 and above requires numpy>=1.21.0
-  # (first version with arm64 wheels available)
-  "numpy==1.21.0; python_version=='3.8' and platform_machine=='arm64' and platform_system=='Darwin'",
-  "numpy==1.21.0; python_version=='3.9' and platform_machine=='arm64' and platform_system=='Darwin'",
-
-  # loongarch64 requires numpy>=1.22.0
-  "numpy==1.22.0; platform_machine=='loongarch64'",
-
-  # On Windows we need to avoid 1.21.6, 1.22.0 and 1.22.1 because they were
-  # built with vc142. 1.22.3 is the first version that has 32-bit Windows
-  # wheels *and* was built with vc141. So use that:
-  "numpy==1.22.3; python_version=='3.10' and platform_system=='Windows' and platform_python_implementation != 'PyPy'",
-
-  # default numpy requirements
-  "numpy==1.19.5; python_version=='3.8' and (platform_machine!='arm64' or platform_system!='Darwin') and platform_machine!='aarch64' and platform_machine!='loongarch64' and platform_python_implementation != 'PyPy'",
-  "numpy==1.19.5; python_version=='3.9' and (platform_machine!='arm64' or platform_system!='Darwin') and platform_machine!='loongarch64' and platform_python_implementation != 'PyPy'",
-  # Note that 1.21.3 was the first version with a complete set of 3.10 wheels,
-  # however macOS was broken and it's safe C API/ABI-wise to build against 1.21.6
-  # (see oldest-supported-numpy issues gh-28 and gh-45)
-  "numpy==1.21.6; python_version=='3.10' and (platform_system!='Windows' and platform_machine!='loongarch64') and platform_python_implementation != 'PyPy'",
-  "numpy==1.23.2; python_version=='3.11' and platform_python_implementation != 'PyPy'",
-
-  # For Python versions which aren't yet officially supported,
-  # we specify an unpinned NumPy which allows source distributions
-  # to be used and allows wheels to be used as soon as they
-  # become available.
-  "numpy; python_version>='3.12'",
-  "numpy; python_version>='3.8' and platform_python_implementation=='PyPy'",
-
+  # https://github.com/scipy/scipy/blob/55cae814e23208354bf16b84be47b5070b4c1c89/pyproject.toml#L25-L31
+  # numpy requirement for wheel builds for distribution on PyPI - building
+  # against 2.x yields wheels that are also compatible with numpy 1.x at
+  # runtime.
+  # Note that building against numpy 1.x works fine too - users and
+  # redistributors can do this by installing the numpy version they like and
+  # disabling build isolation.
+  "numpy>=2.0.0",
   "scipy >= 1.6",
   "setuptools",
   "wheel",

setup.py

@@ -45,7 +45,7 @@ def get_version(rel_path):
     setup_requires=["setuptools>=18.0", "cython"],
     install_requires=[
         "matplotlib",
-        "numpy >= 1.17.5",
+        "numpy >= 2.0",
         "pynndescent",
         "scipy",
         "torch >= 1.7.1",