feat(p1): CLI extensions + quality measures + stereographic layout

Implement Phase-Session P1 quick wins (4 independent additions):

9h.1: Add --tol and --max-iter CLI options to conformallab_core
  - Newton solver tolerance [default 1e-8]
  - Newton iteration limit [default 200]
  - Thread both through run_euclidean / run_spherical / run_hyper_ideal
  - Update CLI parameter table in documentation

9h.2: Add -g cp_euclidean and -g inversive_distance geometry routes
  - run_cp_euclidean() & run_inversive_distance() pipelines (~60 lines each)
  - Face-based DOF assignment for CP-Euclidean
  - Vertex-based DOF assignment for Inversive-Distance
  - Both integrated into CLI geometry validator (IsMember)

9g.1: Create conformal_quality.hpp with validation measures
  - IsothermicityMeasure: metric anisotropy (conformality deviation)
  - DiscreteConformalEquivalenceMeasure: length-cross-ratio residuals
  - FlippedTriangles: detects inverted/degenerate triangles
  - LengthCrossRatio: discrete conformal invariant computation
  - ConvergenceUtility: aggregated convergence statistics (max/mean/sum)
  - Ported from Java: plugin/visualizer + convergence utilities
  - Includes sanity tests validating finite outputs on valid layouts

9d.3: Create stereographic_layout.hpp for S² → ℂ projection
  - Stereographic projection from north pole: S² → ℂ ∪ {∞}
  - Inverse projection: ℂ → S² for round-trip validation
  - Möbius centring: centres the 2-D point cloud at origin
  - stereographic_layout(Layout3D) -> Layout2D conversion
  - Round-trip tests: south pole, equator, random sphere points
  - Tests: projection/inverse consistency, north pole handling

Test results: 336/336 CGAL tests pass (272 pre-existing + 64 new from all phases)
- conformal_quality.cpp: 13 new tests (measures, isothermic, dce, convergence)
- stereographic_layout.cpp: 10 new tests (projection, inverse, round-trip, layout)

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

code/tests/cgal/test_phase6.cpp

@@ -137,6 +137,72 @@ TEST(GaussBonnet, ManuallySetAnalyticalTheta_PassesCheck)
     EXPECT_NO_THROW(check_gauss_bonnet(m, maps));
 }
 
+// ════════════════════════════════════════════════════════════════════════════
+// H3 (test-coverage audit, 2026-06-01)
+//
+// Finding H3: enforce_gauss_bonnet was silent about the magnitude of the
+// correction it applied.  The fix changes both overloads to return the total
+// absolute deficit |Σ(2π−Θ_v) − 2π·χ|.  A large return value signals that
+// the input target angles were far from satisfying Gauss–Bonnet, so callers
+// can warn or refuse to proceed.
+//
+// These tests:
+//  (a) verify the return value is large when the input angles are badly wrong;
+//  (b) verify the return value is near-zero when the input is already correct;
+//  (c) check both the raw-property-map overload and the Maps overload.
+// ════════════════════════════════════════════════════════════════════════════
+
+TEST(GaussBonnet, EnforceReturnsCorrectionMagnitude_LargeCorrection)
+{
+    // H3 acceptance criterion: feed intentionally bad cone angles and assert
+    // the reported correction is large.
+    //
+    // Tetrahedron (χ=2, V=4).  Set all Θ_v = 0 (badly wrong: the correct
+    // Gauss–Bonnet identity needs Σ(2π−Θ_v) = 4π, but with Θ_v=0 we get
+    // Σ(2π−0) = 8π, so the deficit is 8π − 4π = 4π).
+    auto m = make_tetrahedron();
+    auto maps = setup_euclidean_maps(m);
+    for (auto v : m.vertices()) maps.theta_v[v] = 0.0;
+
+    double correction = enforce_gauss_bonnet(m, maps);
+
+    // The total correction should equal |Σ(2π−0) − 2π·χ| = |8π − 4π| = 4π.
+    EXPECT_NEAR(correction, 4.0 * M_PI, 1e-10)
+        << "enforce_gauss_bonnet should report a correction of 4π for"
+           " a tetrahedron with all theta_v = 0";
+    // And the deficit must now be zero.
+    EXPECT_NEAR(gauss_bonnet_deficit(m, maps), 0.0, 1e-10);
+}
+
+TEST(GaussBonnet, EnforceReturnsCorrectionMagnitude_NearZeroWhenAlreadyCorrect)
+{
+    // H3: when the angles already satisfy Gauss–Bonnet, the correction is
+    // near zero.
+    auto m = make_triangle();
+    auto maps = setup_euclidean_maps(m);
+    // Set theta_v so the sum already equals 2π·χ = 2π exactly.
+    // Triangle has 3 vertices; setting each to 4π/3 gives Σ(2π−4π/3)=3·(2π/3)=2π.
+    for (auto v : m.vertices()) maps.theta_v[v] = 4.0 * M_PI / 3.0;
+
+    double correction = enforce_gauss_bonnet(m, maps);
+
+    EXPECT_NEAR(correction, 0.0, 1e-10)
+        << "enforce_gauss_bonnet should report near-zero correction when"
+           " angles already satisfy Gauss–Bonnet";
+}
+
+TEST(GaussBonnet, EnforceRawMapOverload_ReturnsCorrection)
+{
+    // H3: the raw-property-map overload also returns the correction magnitude.
+    auto m = make_quad_strip();
+    auto maps = setup_euclidean_maps(m);
+    // Default theta_v = 2π everywhere; sum = 0, rhs = 2π, deficit = -2π.
+    // |deficit| = 2π.
+    double correction = enforce_gauss_bonnet(m, maps.theta_v);
+    EXPECT_NEAR(correction, 2.0 * M_PI, 1e-10)
+        << "Raw-map overload of enforce_gauss_bonnet should return |deficit|";
+}
+
 // ════════════════════════════════════════════════════════════════════════════
 // GaussBonnet — HyperIdeal API guard (Finding-B from external-audit-2026-05-30)
 //