Test with numpy 2.0 rc1 (#1114)

* Test with numpy 2.0 rc1

* Remove Python 3.8 from numpy 2.0 tests

* specify dtype

* fix new style np.unique output with squeeze

* fix doctest failures due to np.float64(...) print

* add separate numpy2 workflow

.github/workflows/main.yml

@@ -38,4 +38,4 @@ jobs:
         mypy skfem
     - name: Run pytest
       run: |
-        pytest
+        pytest

.github/workflows/numpy2.yml

@@ -0,0 +1,42 @@
+name: tests with numpy 2
+
+on:
+  pull_request:
+  push:
+    branches: master
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.9, '3.10', 3.11, 3.12]
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+        pip install --pre numpy==2.0.0rc1
+        pip install .
+    - name: Run flake8
+      run: |
+        flake8 skfem
+    - name: Run sphinx build
+      run: |
+        sphinx-build -W -a -b html docs docs/_build
+    - name: Run sphinx doctests
+      run: |
+        sphinx-build -W -a -b doctest docs docs/_build
+    - name: Run mypy
+      run: |
+        mypy skfem
+    - name: Run pytest
+      run: |
+        pytest -k 'not TestEx09 and not TestEx32 and not TestEx49'

docs/examples/ex41.py

@@ -19,6 +19,7 @@
 on mixed meshes is work-in-progress.
 
 """
+import numpy as np
 from pathlib import Path
 from skfem import *
 from skfem.models import laplace, unit_load
@@ -35,7 +36,7 @@
 A = asm(laplace, basis)
 f = asm(unit_load, basis)
 
-y = solve(*condense(A, f, D=out[0]['boundary']['line']))
+y = solve(*condense(A, f, D=out[0]['boundary']['line'].astype(np.int64)))
 
 def visualize():
     from skfem.visuals.matplotlib import plot, draw

docs/gettingstarted.rst

@@ -193,5 +193,5 @@ Thus, it makes sense to verify that the error is small.
    ...     uh = w['uh']
    ...     u = np.sin(np.pi * x) * np.sin(np.pi * y) / (2. * np.pi ** 2)
    ...     return (uh - u) ** 2
-   >>> round(error.assemble(Vh, uh=Vh.interpolate(x)), 9)
-   1.069e-06
+   >>> str(round(error.assemble(Vh, uh=Vh.interpolate(x)), 9))
+   '1.069e-06'

skfem/mesh/mesh.py

@@ -588,7 +588,16 @@ def _remove_duplicate_nodes(p, t):
         tmp = np.ascontiguousarray(p.T)
         tmp, ixa, ixb = np.unique(tmp.view([('', tmp.dtype)] * tmp.shape[1]),
                                   return_index=True, return_inverse=True)
-        return p[:, ixa], ixb[t]
+        return p[:, ixa], Mesh._squeeze_if(ixb[t])
+
+    @staticmethod
+    def _squeeze_if(arr):
+        # Workaround for the additional dimension introduced in
+        # numpy 2.0 for the output of np.unique when using
+        # return_index=True
+        if len(arr.shape) > 2:
+            return arr.squeeze(axis=2)
+        return arr
 
     def __iter__(self):
         return iter((self.doflocs, self.t))
@@ -609,8 +618,8 @@ def __matmul__(self, other):
                                     return_index=True, return_inverse=True)
             p = p[:, ixa]
             return [
-                cls(p, ixb[self.t]),
-                *[type(m)(p, ixb[m.t + self.p.shape[1]])
+                cls(p, self._squeeze_if(ixb[self.t])),
+                *[type(m)(p, self._squeeze_if(ixb[m.t + self.p.shape[1]]))
                   for i, m in enumerate(other)],
             ]
         raise NotImplementedError

skfem/utils.py

@@ -307,9 +307,9 @@ def _init_bc(A: spmatrix,
     if I is None and D is None:
         raise Exception("Either I or D must be given!")
     elif I is None and D is not None:
-        I = np.setdiff1d(np.arange(A.shape[0]), D)
+        I = np.setdiff1d(np.arange(A.shape[0], dtype=np.int64), D)
     elif D is None and I is not None:
-        D = np.setdiff1d(np.arange(A.shape[0]), I)
+        D = np.setdiff1d(np.arange(A.shape[0], dtype=np.int64), I)
     else:
         raise Exception("Give only I or only D!")