[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
@@ -9,24 +9,24 @@ repos:
       - id: debug-statements
       - id: check-ast
   - repo: https://github.com/psf/black
-    rev: 23.3.0
+    rev: 24.2.0
     hooks:
       - id: black-jupyter
-  - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.0.269"
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: "v0.2.1"
     hooks:
       - id: ruff
         args: ["--fix"]
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.7.0
+    rev: 1.7.1
     hooks:
       - id: nbqa-black
         additional_dependencies: [jupytext, black]
       - id: nbqa
         args: ["ruff", "--fix", "--ignore=E402,B018,F704"]
         additional_dependencies: [jupytext, ruff]
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.3.0"
+    rev: "v1.8.0"
     hooks:
       - id: mypy
         exclude: ipynb_filter.py|docs/source/conf.py

adaptive/learner/average_learner1D.py

@@ -79,8 +79,9 @@ def __init__(
         self,
         function: Callable[[tuple[int, Real]], Real],
         bounds: tuple[Real, Real],
-        loss_per_interval: None
-        | (Callable[[Sequence[Real], Sequence[Real]], float]) = None,
+        loss_per_interval: None | (
+            Callable[[Sequence[Real], Sequence[Real]], float]
+        ) = None,
         delta: float = 0.2,
         alpha: float = 0.005,
         neighbor_sampling: float = 0.3,
@@ -310,7 +311,7 @@ def _ask_for_new_point(self, n: int) -> tuple[Points, list[float]]:
         new point, since in general n << min_samples and this point will need
         to be resampled many more times"""
         points, (loss_improvement,) = self._ask_points_without_adding(1)
-        seed_points = [(seed, x) for seed, x in zip(range(n), n * points)]
+        seed_points = list(zip(range(n), n * points))
         loss_improvements = [loss_improvement / n] * n
         return seed_points, loss_improvements  # type: ignore[return-value]
 

adaptive/learner/integrator_learner.py

@@ -71,7 +71,6 @@ class DivergentIntegralError(ValueError):
 
 
 class _Interval:
-
     """
     Attributes
     ----------

adaptive/learner/learner1D.py

@@ -135,7 +135,7 @@ def triangle_loss(xs: XsType1, ys: YsType1) -> Float:
         pts = [(x, *y) for x, y in zip(xs, ys)]  # type: ignore[misc]
         vol = simplex_volume_in_embedding
     else:
-        pts = [(x, y) for x, y in zip(xs, ys)]
+        pts = list(zip(xs, ys))
         vol = volume
     return sum(vol(pts[i : i + 3]) for i in range(N)) / N
 
@@ -633,10 +633,12 @@ def tell_pending(self, x: float) -> None:
     def tell_many(
         self,
         xs: Sequence[Float] | np.ndarray,
-        ys: Sequence[Float]
-        | Sequence[Sequence[Float]]
-        | Sequence[np.ndarray]
-        | np.ndarray,
+        ys: (
+            Sequence[Float]
+            | Sequence[Sequence[Float]]
+            | Sequence[np.ndarray]
+            | np.ndarray
+        ),
         *,
         force: bool = False,
     ) -> None:

adaptive/learner/learnerND.py

@@ -987,9 +987,11 @@ def plot_slice(self, cut_mapping, n=None):
             xs = ys = np.linspace(0, 1, n)
             xys = [xs[:, None], ys[None, :]]
             values = [
-                cut_mapping[i]
-                if i in cut_mapping
-                else xys.pop(0) * (b[1] - b[0]) + b[0]
+                (
+                    cut_mapping[i]
+                    if i in cut_mapping
+                    else xys.pop(0) * (b[1] - b[0]) + b[0]
+                )
                 for i, b in enumerate(self._bbox)
             ]
 

adaptive/runner.py

@@ -470,7 +470,7 @@ def __init__(
         npoints_goal: int | None = None,
         end_time_goal: datetime | None = None,
         duration_goal: timedelta | int | float | None = None,
-        executor: (ExecutorTypes | None) = None,
+        executor: ExecutorTypes | None = None,
         ntasks: int | None = None,
         log: bool = False,
         shutdown_executor: bool = False,
@@ -629,7 +629,7 @@ def __init__(
         npoints_goal: int | None = None,
         end_time_goal: datetime | None = None,
         duration_goal: timedelta | int | float | None = None,
-        executor: (ExecutorTypes | None) = None,
+        executor: ExecutorTypes | None = None,
         ntasks: int | None = None,
         log: bool = False,
         shutdown_executor: bool = False,
@@ -956,7 +956,7 @@ def _ensure_executor(executor: ExecutorTypes | None) -> concurrent.Executor:
 
 
 def _get_ncores(
-    ex: (ExecutorTypes),
+    ex: ExecutorTypes,
 ) -> int:
     """Return the maximum  number of cores that an executor can use."""
     if with_ipyparallel:

pyproject.toml

@@ -97,6 +97,8 @@ python_version = "3.9"
 [tool.ruff]
 line-length = 150
 target-version = "py39"
+
+[tool.ruff.lint]
 select = ["B", "C", "E", "F", "W", "T", "B9", "I", "UP"]
 ignore = [
     "T20",     # flake8-print
@@ -109,14 +111,14 @@ ignore = [
     "D401",    # First line of docstring should be in imperative mood
 ]
 
+[tool.ruff.lint.mccabe]
+max-complexity = 18
+
 [tool.ruff.per-file-ignores]
 "tests/*" = ["SLF001"]
 "ci/*" = ["INP001"]
 "tests/test_examples.py" = ["E501"]
 
-[tool.ruff.mccabe]
-max-complexity = 18
-
 [tool.versioningit]
 
 [tool.versioningit.vcs]