CI: Update dependencies and add minimal-dependency CI

.github/workflows/install.yml

@@ -22,7 +22,7 @@ jobs:
       uses: conda-incubator/setup-miniconda@v3
       with:
         auto-update-conda: true
-        python-version: "3.10"
+        python-version: "3.11"
     - name: Install py4vasp and testing tools
       shell: bash -el {0}
       run: |

.github/workflows/publish_full.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
 
     steps:
     - uses: actions/checkout@v5

.github/workflows/test_core.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
 
     steps:
     - uses: actions/checkout@v5

.github/workflows/test_full.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
 
     steps:
     - uses: actions/checkout@v5

.github/workflows/test_minimal.yml

@@ -0,0 +1,37 @@
+name: test-minimal
+
+# Verify that the minimum dependency versions declared in pyproject.toml actually
+# install and pass the test suite. Uses uv's `lowest-direct` resolution to pin every
+# direct dependency to its lowest declared version (transitive deps resolve normally)
+# on the oldest supported Python. If this job fails, a declared lower bound is too low
+# and should be raised (see https://scientific-python.org/specs/spec-0000/ for guidance).
+
+on:
+  push:
+    branches: [master]
+  pull_request:
+    branches: [master]
+  schedule:
+    - cron: "0 2 * * 6"
+
+jobs:
+  test-minimal:
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v5
+    - name: Install uv and set the Python version
+      uses: astral-sh/setup-uv@v7
+      with:
+        python-version: "3.11"
+    - name: Install py4vasp with lowest-direct dependency versions
+      run: |
+        uv --version
+        python --version
+        uv lock --resolution lowest-direct
+        uv sync --no-group doc
+        uv version
+    - name: Test with pytest
+      run: |
+        uv run pytest --version
+        uv run pytest

README.md

@@ -18,7 +18,7 @@ We recommend installing py4vasp in a conda environment to resolve issues related
 installing `mdtraj` with pip. To do this please use the following steps. The last step
 will test whether everything worked
 ~~~shell
-conda create --name py4vasp-env python=3.10
+conda create --name py4vasp-env python=3.11
 conda activate py4vasp-env
 conda install conda-forge::uv
 git clone git@github.com:vasp-dev/py4vasp.git

core/pyproject.toml

@@ -17,7 +17,7 @@ authors = [
     { name = "Tomáš Bučko", email = "tomas.bucko@uniba.sk" },
     { name = "Max Liebetreu", email = "max.liebetreu@vasp.at" },
 ]
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 readme = "README.md"
 license = "Apache-2.0"
 dependencies = [

pyproject.toml

@@ -17,7 +17,7 @@ authors = [
     { name = "Tomáš Bučko", email = "tomas.bucko@uniba.sk" },
     { name = "Max Liebetreu", email = "max.liebetreu@vasp.at" },
 ]
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 readme = "README.md"
 license = "Apache-2.0"
 dependencies = [

src/py4vasp/_third_party/graph/contour.py

@@ -18,6 +18,11 @@
 interpolate = import_.optional("scipy.interpolate")
 
 
+def _cross_2d(a, b):
+    # numpy removed the cross product of 2d vectors, so compute the scalar directly
+    return a[0] * b[1] - a[1] * b[0]
+
+
 @dataclasses.dataclass
 class Contour(trace.Trace):
     """Represents data on a 2d slice through the unit cell.
@@ -406,7 +411,7 @@ def _interpolation_required(self):
         return not np.allclose((y_position_first_vector, x_position_second_vector), 0)
 
     def _interpolate_data(self, lattice, data):
-        area_cell = abs(np.cross(lattice[0], lattice[1]))
+        area_cell = abs(_cross_2d(lattice[0], lattice[1]))
         points_per_area = data.size / area_cell
         points_per_line = np.sqrt(points_per_area) * self._interpolation_factor
         lengths = np.sum(np.abs(lattice), axis=0)
@@ -649,7 +654,7 @@ def _label_unit_cell_vectors(self):
         ]
 
     def _shift_label(self, current_vector, other_vector):
-        invert = np.cross(current_vector, other_vector) < 0
+        invert = _cross_2d(current_vector, other_vector) < 0
         norm = np.linalg.norm(current_vector)
         shifts = self._shift_label_pixels * current_vector[::-1] / norm
         if invert:

tests/third_party/graph/test_graph.py

@@ -839,7 +839,8 @@ def check_unit_cell(unit_cell, x, y, zero):
 
 def check_annotations(lattice, annotations, Assert):
     assert len(lattice.vectors) == len(annotations)
-    sign = np.sign(np.cross(*lattice.vectors))
+    first, second = lattice.vectors
+    sign = np.sign(first[0] * second[1] - first[1] * second[0])
     labels = "abc".replace(lattice.cut, "")
     for vector, label, annotation in zip(lattice.vectors, labels, annotations):
         assert annotation.showarrow == False
@@ -882,7 +883,8 @@ def check_basic_tilted_contour(
     graph = Graph(curr_contour)
     fig = graph.to_plotly()
     if not with_periodic_traces:
-        area_cell = np.linalg.norm(np.cross(*curr_contour.lattice.vectors))
+        first, second = curr_contour.lattice.vectors
+        area_cell = abs(first[0] * second[1] - first[1] * second[0])
         points_per_area = curr_contour.data.size / area_cell
         points_per_line = np.sqrt(points_per_area) * curr_contour._interpolation_factor
         lengths = np.array(expected_lengths)