[pre-commit.ci] pre-commit autoupdate (#673)

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -89,7 +89,7 @@ repos:
           - --blank
         exclude: src/optimagic/optimization/algo_options.py
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.14.14
+    rev: v0.15.4
     hooks:
       # Run the linter.
       - id: ruff
@@ -130,7 +130,7 @@ repos:
         files: (docs/.)
         exclude: docs/source/how_to/how_to_specify_algorithm_and_algo_options.md
   - repo: https://github.com/kynan/nbstripout
-    rev: 0.9.0
+    rev: 0.9.1
     hooks:
       - id: nbstripout
         exclude: |

src/optimagic/optimization/internal_optimization_problem.py

@@ -898,7 +898,7 @@ def __init__(
         _fun_dict = {
             AggregationLevel.SCALAR: lambda x: ScalarFunctionValue(x @ x),
             AggregationLevel.LIKELIHOOD: lambda x: LikelihoodFunctionValue(x**2),
-            AggregationLevel.LEAST_SQUARES: lambda x: LeastSquaresFunctionValue(x),
+            AggregationLevel.LEAST_SQUARES: lambda x: LeastSquaresFunctionValue(x),  # noqa: PLW0108
         }
 
         _jac_dict = {

tests/optimagic/optimization/test_scipy_aliases.py

@@ -127,7 +127,7 @@ def test_exception_for_callback():
             fun=lambda x: x @ x,
             x0=np.arange(3),
             algorithm="scipy_lbfgsb",
-            callback=lambda x: print(x),
+            callback=print,
         )
 
 

tests/optimagic/optimization/test_with_nonlinear_constraints.py

@@ -157,7 +157,7 @@ def test_documentation_example(algorithm):
         params=np.ones(6),
         algorithm=algorithm,
         constraints=om.NonlinearConstraint(
-            func=lambda x: np.prod(x),
+            func=np.prod,
             selector=lambda x: x[:-1],
             value=1.0,
         ),

tests/optimagic/parameters/test_nonlinear_constraints.py

@@ -157,7 +157,7 @@ def test_check_validity_nonlinear_constraint(constraint, params):
 def test_check_validity_nonlinear_constraint_correct_example():
     constr = {
         "func": lambda x: x,
-        "derivative": lambda x: np.ones_like(x),
+        "derivative": np.ones_like,
         "lower_bounds": np.arange(4),
         "selector": lambda x: x[:1],
     }