fix(notebooks): fix warnings

CHANGELOG.md

@@ -7,6 +7,21 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+### Fixed
+
+- **`nsga_walking_optimization` and `topology_walking_optimization` no
+  longer print `RuntimeWarning: invalid value encountered in subtract`.** A
+  walker that fails scores `+inf` on purpose, and pymoo's crowding distance
+  then subtracts one infinity from another. Both now run pymoo under
+  `numpy.errstate(invalid="ignore")` (the single-worker multi-objective path
+  of the former goes through `pylinkage.optimization`, which has the matching
+  fix). Such a warning names the file that
+  raised it, which is how the private path of the machine that executed
+  `examples/05_topology_co_optimization.ipynb` ended up committed with its
+  outputs; the notebook is re-executed (against pylinkage's matching fix, as
+  it calls `pylinkage.optimization.co_optimize`), and a test now refuses a
+  notebook whose outputs name a home directory.
+
 ## [0.6.1] - 2026-09-12
 
 Requires **pylinkage >= 1.2.1**.

src/leggedsnake/nsga_optimizer.py

@@ -435,14 +435,17 @@ def _run_via_parallel_problem(
     else:
         algo = NSGA2(pop_size=cfg.pop_size)
 
+    # A walker that fails scores +inf by design, and pymoo's crowding
+    # distance then computes inf - inf: expected, not a bug.
     try:
-        res = pymoo_minimize(
-            problem.problem,
-            algo,
-            ("n_gen", cfg.n_generations),
-            seed=cfg.seed,
-            verbose=cfg.verbose,
-        )
+        with np.errstate(invalid="ignore"):
+            res = pymoo_minimize(
+                problem.problem,
+                algo,
+                ("n_gen", cfg.n_generations),
+                seed=cfg.seed,
+                verbose=cfg.verbose,
+            )
     finally:
         problem.close()
 

src/leggedsnake/topology_optimization.py

@@ -1083,14 +1083,16 @@ def topology_walking_optimization(
     else:
         algo = NSGA2(pop_size=cfg.pop_size)
 
-    # Run optimization
-    res = pymoo_minimize(
-        problem.problem,
-        algo,
-        ("n_gen", cfg.n_generations),
-        seed=cfg.seed,
-        verbose=cfg.verbose,
-    )
+    # Run optimization. A candidate that fails scores +inf by design, and
+    # pymoo's crowding distance then computes inf - inf: expected, not a bug.
+    with np.errstate(invalid="ignore"):
+        res = pymoo_minimize(
+            problem.problem,
+            algo,
+            ("n_gen", cfg.n_generations),
+            seed=cfg.seed,
+            verbose=cfg.verbose,
+        )
 
     # Package results
     nsga_cfg = NsgaWalkingConfig(

tests/test_notebook_outputs.py

@@ -0,0 +1,44 @@
+"""The committed example notebooks must not carry outputs from a private machine.
+
+A warning printed while a notebook was executed embeds the path of the file
+that raised it, and a path under a home directory then ships with the
+notebook to GitHub and the rendered docs.
+"""
+
+import json
+import re
+from pathlib import Path
+
+import pytest
+
+NOTEBOOKS = sorted((Path(__file__).resolve().parents[1] / "examples").glob("*.ipynb"))
+
+# A home directory on Linux, macOS or Windows.
+LOCAL_PATH = re.compile(r"(/home/|/Users/|[A-Za-z]:\\+Users\\)")
+
+
+def _output_texts(cell: dict) -> list[str]:
+    texts = []
+    for output in cell.get("outputs", ()):
+        if "text" in output:
+            texts.append("".join(output["text"]))
+        for mime, payload in output.get("data", {}).items():
+            if mime.startswith("text/"):
+                texts.append("".join(payload))
+        if output.get("output_type") == "error":
+            texts.append("\n".join(output.get("traceback", ())))
+    return texts
+
+
+@pytest.mark.parametrize("notebook", NOTEBOOKS, ids=lambda path: path.name)
+def test_outputs_do_not_name_a_local_path(notebook: Path) -> None:
+    cells = json.loads(notebook.read_text(encoding="utf-8"))["cells"]
+    leaks = [
+        f"cell {index}: {line}"
+        for index, cell in enumerate(cells)
+        if cell["cell_type"] == "code"
+        for text in _output_texts(cell)
+        for line in text.splitlines()
+        if LOCAL_PATH.search(line)
+    ]
+    assert not leaks, "\n".join(leaks)