ENH: install TensorBoard in tf extras

.github/dependabot.yml

@@ -12,6 +12,11 @@ updates:
     labels: [⬆️ Lock]
     multi-ecosystem-group: lock
     patterns: ["*"]
+  - package-ecosystem: pre-commit
+    directory: "/"
+    labels: [⬆️ Lock]
+    multi-ecosystem-group: lock
+    patterns: ["*"]
   - package-ecosystem: uv
     directory: "/"
     labels: [⬆️ Lock]

.github/workflows/release-drafter.yml

@@ -11,6 +11,6 @@ jobs:
   update_release_draft:
     runs-on: ubuntu-slim
     steps:
-      - uses: release-drafter/release-drafter@v6
+      - uses: release-drafter/release-drafter@v7
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.pre-commit-config.yaml

@@ -14,7 +14,7 @@ repos:
       - id: check-useless-excludes
 
   - repo: https://github.com/ComPWA/policy
-    rev: 0.8.7
+    rev: 0.8.9
     hooks:
       - id: check-dev-files
         args:
@@ -61,7 +61,7 @@ repos:
             metadata.vscode
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.15.2
+    rev: v0.15.10
     hooks:
       - id: ruff-check
         args: [--fix]
@@ -107,14 +107,14 @@ repos:
       - id: taplo-format
 
   - repo: https://github.com/pappasam/toml-sort
-    rev: v0.24.3
+    rev: v0.24.4
     hooks:
       - id: toml-sort
         args:
           - --in-place
 
   - repo: https://github.com/python-jsonschema/check-jsonschema
-    rev: 0.36.2
+    rev: 0.37.1
     hooks:
       - id: check-jsonschema
         name: Check CITATION.cff
@@ -127,12 +127,13 @@ repos:
         pass_filenames: false
 
   - repo: https://github.com/streetsidesoftware/cspell-cli
-    rev: v9.7.0
+    rev: v10.0.0
     hooks:
       - id: cspell
+        language_version: 25.9.0
 
   - repo: https://github.com/editorconfig-checker/editorconfig-checker.python
-    rev: 3.6.0
+    rev: 3.6.1
     hooks:
       - id: editorconfig-checker
         name: editorconfig
@@ -153,6 +154,6 @@ repos:
         types_or: [python, pyi, jupyter]
 
   - repo: https://github.com/astral-sh/uv-pre-commit
-    rev: 0.10.5
+    rev: 0.11.6
     hooks:
       - id: uv-lock

docs/amplitude-analysis/analytic-continuation.ipynb

@@ -131,7 +131,7 @@
     "analytic_breit_wigner_builder = RelativisticBreitWignerBuilder(\n",
     "    form_factor=True,\n",
     "    energy_dependent_width=True,\n",
-    "    phsp_factor=PhaseSpaceFactorSWave,\n",
+    "    phsp_factor=PhaseSpaceFactorSWave,  # ty:ignore[invalid-argument-type]\n",
     ")\n",
     "model_builder.dynamics.assign(\"D0\", create_non_dynamic_with_ff)\n",
     "model_builder.dynamics.assign(\"a(0)(980)0\", analytic_breit_wigner_builder)\n",
@@ -236,7 +236,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.12"
+   "version": "3.13.13"
   }
  },
  "nbformat": 4,

docs/conf.py

@@ -22,7 +22,7 @@ def create_tensorflow_inventory() -> None:
     if os.path.exists("tensorflow.inv"):
         return
     subprocess.check_call(
-        ("sphobjinv", "convert", "-o", "zlib", "tensorflow.txt"),
+        ("sphobjinv", "convert", "-o", "zlib", "tensorflow.txt"),  # noqa: S607
     )
 
 
@@ -45,6 +45,7 @@ def get_tensorflow_url() -> str:
 create_tensorflow_inventory()
 set_intersphinx_version_remapping({
     "matplotlib": {"3.5.1": "3.5.0"},
+    "pandas": {"3.0.2": "3.0.1"},
     "scipy": {"1.7.3": "1.7.1"},
 })
 

docs/usage/caching.ipynb

@@ -381,7 +381,7 @@
     "    \"x\": (-1, +1),\n",
     "    \"y\": (-1, +1),\n",
     "}\n",
-    "domain_generator = NumpyDomainGenerator(boundaries)\n",
+    "domain_generator = NumpyDomainGenerator(boundaries)  # ty:ignore[invalid-argument-type]\n",
     "rng = NumpyUniformRNG()\n",
     "domain = domain_generator.generate(10_000, rng)"
    ]
@@ -486,7 +486,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.12"
+   "version": "3.13.13"
   }
  },
  "nbformat": 4,

pyproject.toml

@@ -63,7 +63,10 @@ pwa = [
     "tensorwaves[phsp]",
 ]
 scipy = ["scipy >=1"]
-tf = ["tensorflow >=2.12"]
+tf = [
+    "tensorboard",
+    "tensorflow >=2.12",
+]
 
 [project.readme]
 content-type = "text/markdown"

src/tensorwaves/function/__init__.py

@@ -103,7 +103,7 @@ def __init__(
         argument_order: Iterable[str],
         parameters: Mapping[str, ParameterValue],
     ) -> None:
-        self.__function = PositionalArgumentFunction(function, argument_order)  # ty:ignore[invalid-argument-type]
+        self.__function = PositionalArgumentFunction(function, argument_order)
         self.__parameters = dict(parameters)
 
     def __call__(self, data: DataSample) -> np.ndarray:

src/tensorwaves/function/sympy/__init__.py

@@ -356,9 +356,13 @@ def fast_lambdify(  # noqa: PLR0913
             top_expression, symbols, backend, use_cse=use_cse, use_jit=use_jit
         )
 
-    sorted_top_symbols = sorted(sub_expressions, key=str)  # ty:ignore[no-matching-overload]
+    sorted_top_symbols = sorted(sub_expressions, key=str)
     top_function = lambdify(
-        top_expression, sorted_top_symbols, backend, use_cse=use_cse, use_jit=use_jit
+        top_expression,
+        sorted_top_symbols,  # ty:ignore[invalid-argument-type]
+        backend,
+        use_cse=use_cse,
+        use_jit=use_jit,
     )
     sub_functions: list[Callable] = []
     for symbol in tqdm(
@@ -367,7 +371,7 @@ def fast_lambdify(  # noqa: PLR0913
         unit="expr",
         disable=not _use_progress_bar(),
     ):
-        sub_expression = sub_expressions[symbol]
+        sub_expression = sub_expressions[symbol]  # ty:ignore[invalid-argument-type]
         sub_function = lambdify(
             sub_expression, symbols, backend, use_cse=use_cse, use_jit=use_jit
         )
@@ -384,7 +388,7 @@ def recombined_function(*args: Any) -> Any:
 
 def _collect_constant_sub_expressions(
     expression: sp.Basic, free_symbols: Iterable[sp.Basic]
-) -> set[sp.Expr]:
+) -> set[sp.Basic]:
     import sympy as sp
 
     free_symbol_set = set(free_symbols)
@@ -393,7 +397,7 @@ def _collect_constant_sub_expressions(
 
     def iterate_constant_sub_expressions(
         expression: sp.Basic,
-    ) -> Generator[sp.Expr, None, None]:
+    ) -> Generator[sp.Basic, None, None]:
         if isinstance(expression, sp.Atom):
             return
         if _get_free_symbols(expression) & free_symbol_set:
@@ -438,7 +442,7 @@ def extract_constant_sub_expressions(
     free_symbols = set(free_symbols)
     over_defined = free_symbols - _get_free_symbols(expression)
     if over_defined:
-        over_defined_symbols = sorted(over_defined, key=str)  # ty:ignore[no-matching-overload]
+        over_defined_symbols = sorted(over_defined, key=str)
         symbol_names = ", ".join(map(str, over_defined_symbols))
         if len(over_defined) == 1:
             text = f"Symbol {symbol_names} does"

tests/data/test_transform.py

@@ -18,7 +18,7 @@ def test_identity_chain(self, extend: bool):
         x, y, v, w = sp.symbols("x y v w")
         transform1 = _create_transformer({v: 2 * x - 5, w: -0.2 * y + 3})
         transform2 = _create_transformer({x: 0.5 * (v + 5), y: 5 * (3 - w)})
-        chained_transform = ChainedDataTransformer([transform1, transform2], extend)  # ty:ignore[invalid-argument-type]
+        chained_transform = ChainedDataTransformer([transform1, transform2], extend)
         rng = np.random.default_rng(seed=0)
         data = {"x": rng.uniform(size=100), "y": rng.uniform(size=100)}
         transformed_data = chained_transform(data)
@@ -35,7 +35,7 @@ def test_identity_chain(self, extend: bool):
 
     def test_single_chain(self):
         transform = IdentityTransformer()
-        chained_transform = ChainedDataTransformer([transform])  # ty:ignore[invalid-argument-type]
+        chained_transform = ChainedDataTransformer([transform])
         data = {
             "x": np.ones(5),
             "y": np.ones(5),

tests/optimizer/test_fit_simple_model.py

@@ -9,6 +9,7 @@
 from tensorwaves.estimator import UnbinnedNLL
 from tensorwaves.function.sympy import create_parametrized_function
 from tensorwaves.optimizer.callbacks import (
+    Callback,
     CallbackList,
     CSVSummary,
     TFSummary,
@@ -132,7 +133,7 @@ def test_optimize_all_parameters(
     original_nll = estimator(function.parameters)
 
     callback_file = output_dir / f"simple_fit_{backend}_{optimizer_type.__name__}"
-    callbacks = [
+    callbacks: list[Callback] = [
         CSVSummary(f"{callback_file}.csv"),
         YAMLSummary(f"{callback_file}.yml"),
     ]