Finding-E from doc/reviewer/external-audit-2026-05-30.md.
Scan also uncovered the same issue in inversive_distance_functional.hpp.
Three functions used absolute error `|analytic - fd| > tol` while the
rest of the library (euclidean_functional, spherical_functional,
euclidean_hessian, hyper_ideal_functional) all use relative error
`|analytic - fd| / max(1, |analytic|) > tol`.
Absolute error is too strict for large gradients (false failures) and
too lenient for small gradients.
Fixed:
cp_euclidean_functional.hpp gradient_check_cp_euclidean()
cp_euclidean_functional.hpp hessian_check_cp_euclidean()
inversive_distance_functional.hpp gradient_check_inversive_distance()
All three now use the relative criterion and accumulate all failures
before returning (ok=false instead of early return on first mismatch).
Default tol updated from 1e-6/1e-5 to 1e-4, matching the Java
FunctionalTest convention used by all other checks in the library.
Error message updated to print rel-err instead of raw diff.
266/266 CGAL tests pass, 0 failed.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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