Update to skmatter 1.8

.github/workflows/build.yml

@@ -15,7 +15,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v6
       with:
-        python-version: "3.13"
+        python-version: "3.14"
 
     - name: install tests dependencies
       run: python -m pip install tox

.github/workflows/docs.yml

@@ -16,7 +16,7 @@ jobs:
       - name: setup Python
         uses: actions/setup-python@v6
         with:
-          python-version: "3.13"
+          python-version: "3.14"
 
       - name: install tests dependencies
         run: python -m pip install tox

.github/workflows/lint.yml

@@ -14,7 +14,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v6
       with:
-        python-version: "3.13"
+        python-version: "3.14"
 
     - name: install tests dependencies
       run: python -m pip install tox

.github/workflows/release.yml

@@ -22,7 +22,7 @@ jobs:
     - name: setup Python
       uses: actions/setup-python@v6
       with:
-        python-version: "3.13"
+        python-version: "3.14"
     - run: python -m pip install tox
     - name: Build package
       run: tox -e build

.github/workflows/tests-dev.yml

@@ -11,8 +11,8 @@ jobs:
     strategy:
       matrix:
         python-version: 
-          - "3.10"
-          - "3.13"
+          - "3.11"
+          - "3.14"
 
     steps:
       - uses: actions/checkout@v6

.github/workflows/tests.yml

@@ -16,8 +16,8 @@ jobs:
           - macos-latest
           - windows-latest
         python-version: 
-          - "3.10"
-          - "3.13"
+          - "3.11"
+          - "3.14"
 
     steps:
     - uses: actions/checkout@v6

CHANGELOG

@@ -13,6 +13,11 @@ The rules for CHANGELOG file:
 
 Unreleased
 ----------
+- Fix PCovC scaling (#270)
+- Refactor of reconstruction measures(#275)
+- Code cleanup of Base classes (#264)
+- Update ``sklearn`` dependency to `>=1.8.0` (#278)
+- Bump minimal Python version to 3.11 (#278)
 
 0.3.2 (2025/07/15)
 ------------------

README.rst

@@ -34,7 +34,7 @@ You can then ``import skmatter`` and use scikit-matter in your projects!
 
 Tests
 -----
-We are testing our code for Python 3.10 and 3.13 on the latest versions of Ubuntu,
+We are testing our code for Python 3.11 and 3.14 on the latest versions of Ubuntu,
 macOS and Windows.
 
 .. marker-issues

docs/requirements.txt

@@ -2,4 +2,3 @@ sphinx
 sphinx-gallery
 sphinx-toggleprompt
 pydata-sphinx-theme
-tomli

docs/src/conf.py

@@ -10,12 +10,11 @@
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 
+import tomllib
 import os
 import sys
 from datetime import datetime
 
-import tomli  # Replace by tomllib from std library once docs are build with Python 3.11
-
 import skmatter
 
 
@@ -28,7 +27,7 @@
 master_doc = "index"
 
 with open(os.path.join(ROOT, "pyproject.toml"), "rb") as fp:
-    project_dict = tomli.load(fp)["project"]
+    project_dict = tomllib.load(fp)["project"]
 
 project = project_dict["name"]
 author = ", ".join(a["name"] for a in project_dict["authors"])

pyproject.toml

@@ -20,7 +20,7 @@ authors = [
     {name = "Michele Ceriotti"}
 ]
 readme = "README.rst"
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 license = {text = "BSD-3-Clause"}
 classifiers = [
     "Development Status :: 4 - Beta",
@@ -32,14 +32,14 @@ classifiers = [
     "Operating System :: MacOS :: MacOS X",
     "Operating System :: Microsoft :: Windows",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
     "Topic :: Scientific/Engineering",
 ]
 dependencies = [
-    "scikit-learn >= 1.7, < 1.8",
+    "scikit-learn >= 1.8, < 1.9",
     "scipy >= 1.15",  # explicit to adhere to scikit-learn dependencies
 ]
 dynamic = ["version"]

src/skmatter/metrics/_prediction_rigidities.py

@@ -74,7 +74,7 @@ def local_prediction_rigidity(X_train, X_test, alpha):
 
     for ai in range(atom_count):
         Xi = X_test[ai].reshape(1, -1) / sfactor
-        LPR_np[ai] = 1 / (Xi @ Xinv @ Xi.T)
+        LPR_np[ai] = 1 / (Xi @ Xinv @ Xi.T).item()
 
     # separately store LPR by test struc
     LPR = []
@@ -180,11 +180,11 @@ def componentwise_prediction_rigidity(X_train, X_test, alpha, comp_dims):
 
         for ai in range(atom_count):
             Xic = np.multiply(X_test[ai].reshape(1, -1) / sfactor, mask)
-            LCPR_np[ai, ci] = 1 / (Xic @ Xinv @ Xic.T)
+            LCPR_np[ai, ci] = 1 / (Xic @ Xinv @ Xic.T).item()
 
         for si in range(len(X_struc_test)):
             XAc = np.multiply(X_struc_test[si].reshape(1, -1), mask)
-            CPR[si, ci] = 1 / (XAc @ Xinv @ XAc.T)
+            CPR[si, ci] = 1 / (XAc @ Xinv @ XAc.T).item()
 
     # separately store LCPR by test struc
     LCPR = []