[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: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
@@ -9,21 +9,21 @@ repos:
       - id: debug-statements
       - id: check-ast
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.3.5"
+    rev: "v0.11.5"
     hooks:
       - id: ruff
         args: ["--fix"]
       - id: ruff-format
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.8.5
+    rev: 1.9.1
     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: "v1.9.0"
+    rev: "v1.15.0"
     hooks:
       - id: mypy
         exclude: ipynb_filter.py|docs/source/conf.py

adaptive/learner/average_learner1D.py

@@ -500,8 +500,7 @@ def tell_many(  # type: ignore[override]
         # but ignore it going forward.
         if not np.prod([x >= self.bounds[0] and x <= self.bounds[1] for _, x in xs]):
             raise ValueError(
-                "x value out of bounds, "
-                "remove x or enlarge the bounds of the learner"
+                "x value out of bounds, remove x or enlarge the bounds of the learner"
             )
 
         # Create a mapping of points to a list of samples
@@ -534,8 +533,7 @@ def tell_many_at_point(self, x: Real, seed_y_mapping: dict[int, Real]) -> None:
         # Check x is within the bounds
         if not np.prod(x >= self.bounds[0] and x <= self.bounds[1]):
             raise ValueError(
-                "x value out of bounds, "
-                "remove x or enlarge the bounds of the learner"
+                "x value out of bounds, remove x or enlarge the bounds of the learner"
             )
 
         # If x is a new point:

adaptive/learner/balancing_learner.py

@@ -116,9 +116,7 @@ def __init__(
         self._cdims_default = cdims
 
         if len({learner.__class__ for learner in self.learners}) > 1:
-            raise TypeError(
-                "A BalacingLearner can handle only one type" " of learners."
-            )
+            raise TypeError("A BalacingLearner can handle only one type of learners.")
 
         self.strategy: STRATEGY_TYPE = strategy
 

adaptive/learner/learner2D.py

@@ -451,7 +451,7 @@ def __init__(
         self.aspect_ratio = 1
 
         self._bounds_points = list(itertools.product(*bounds))
-        self._stack.update({p: np.inf for p in self._bounds_points})
+        self._stack.update(dict.fromkeys(self._bounds_points, np.inf))
         self.function = function  # type: ignore
         self._ip = self._ip_combined = None
 

adaptive/learner/learnerND.py

@@ -1098,8 +1098,7 @@ def _get_iso(self, level=0.0, which="surface"):
         if which == "surface":
             if self.ndim != 3 or self.vdim != 1:
                 raise Exception(
-                    "Isosurface plotting is only supported"
-                    " for a 3D input and 1D output"
+                    "Isosurface plotting is only supported for a 3D input and 1D output"
                 )
             get_surface = True
             get_line = False

adaptive/learner/triangulation.py

@@ -336,8 +336,7 @@ def __init__(self, coords):
         vectors = subtract(coords[1:], coords[0])
         if matrix_rank(vectors) < dim:
             raise ValueError(
-                "Initial simplex has zero volumes "
-                "(the points are linearly dependent)"
+                "Initial simplex has zero volumes (the points are linearly dependent)"
             )
 
         self.vertices = list(coords)

adaptive/notebook_integration.py

@@ -16,8 +16,7 @@ def notebook_extension(*, _inline_js=True):
     """Enable ipywidgets, holoviews, and asyncio notebook integration."""
     if not in_ipynb():
         raise RuntimeError(
-            '"adaptive.notebook_extension()" may only be run '
-            "from a Jupyter notebook."
+            '"adaptive.notebook_extension()" may only be run from a Jupyter notebook.'
         )
 
     global _holoviews_enabled, _ipywidgets_enabled
@@ -116,8 +115,7 @@ def live_plot(runner, *, plotter=None, update_interval=2, name=None, normalize=T
     """
     if not _holoviews_enabled:
         raise RuntimeError(
-            "Live plotting is not enabled; did you run "
-            "'adaptive.notebook_extension()'?"
+            "Live plotting is not enabled; did you run 'adaptive.notebook_extension()'?"
         )
 
     import holoviews as hv
@@ -202,8 +200,7 @@ def live_info(runner, *, update_interval=0.5):
     """
     if not _holoviews_enabled:
         raise RuntimeError(
-            "Live plotting is not enabled; did you run "
-            "'adaptive.notebook_extension()'?"
+            "Live plotting is not enabled; did you run 'adaptive.notebook_extension()'?"
         )
 
     import ipywidgets
@@ -268,7 +265,7 @@ def _info_html(runner):
         info.append(("# of samples", runner.learner.nsamples))
 
     with suppress(Exception):
-        info.append(("latest loss", f'{runner.learner._cache["loss"]:.3f}'))
+        info.append(("latest loss", f"{runner.learner._cache['loss']:.3f}"))
 
     table = "\n".join(_table_row(i, k, v) for i, (k, v) in enumerate(info))
 

adaptive/runner.py

@@ -935,7 +935,7 @@ def _info_text(runner, separator: str = "\n"):
         info.append(("# of samples", runner.learner.nsamples))
 
     with suppress(Exception):
-        info.append(("latest loss", f'{runner.learner._cache["loss"]:.3f}'))
+        info.append(("latest loss", f"{runner.learner._cache['loss']:.3f}"))
 
     width = 30
     formatted_info = [f"{k}: {v}".ljust(width) for i, (k, v) in enumerate(info)]

example-notebook.ipynb

@@ -489,8 +489,7 @@
     "    print(\"WARINING: The runner hasn't reached it goal yet!\")\n",
     "\n",
     "print(\n",
-    "    f\"The integral value is {learner.igral} \"\n",
-    "    f\"with a corresponding error of {learner.err}\"\n",
+    "    f\"The integral value is {learner.igral} with a corresponding error of {learner.err}\"\n",
     ")\n",
     "learner.plot()"
    ]