Files
ConformalLabpp/code/tests/cgal/test_cgal_traits_mvp.cpp
Tarik Moussa 56f13d7c4f feat(cgal): propagate Newton status + conditioning diagnostics into CGAL results
Follow-up to S2: surface the new NewtonResult diagnostics through the public
CGAL result types so callers of the high-level API see them too.

- Add `CGAL::Newton_status` (alias of conformallab::NewtonStatus) and three
  fields — `status`, `sparse_qr_fallback_used`, `min_ldlt_pivot` — to
  Conformal_map_result, Hyper_ideal_map_result and Circle_packing_result.
  (sparse_qr_fallback_used already existed on Conformal_map_result but was never
  populated; it is now wired through.)
- Map them from NewtonResult at all five entry points (euclidean / spherical /
  hyper_ideal / inversive_distance / cp_euclidean).
- Test: SingleTriangleConverges now asserts status == Converged and the
  diagnostics propagate.

Additive only — existing `converged`/`iterations`/`gradient_norm` semantics
unchanged. 301/301 CGAL tests pass.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-05-31 19:44:50 +02:00

255 lines
12 KiB
C++

// Copyright (c) 2024-2026 Tarik Moussa.
// SPDX-License-Identifier: MIT
// test_cgal_traits_mvp.cpp
//
// Phase 8 MVP — first tests for the new CGAL-style public API.
//
// Validates:
// 1. Default_conformal_map_traits<Surface_mesh, K> compiles and
// provides all advertised types and property-map accessors.
// 2. discrete_conformal_map_euclidean() runs end-to-end on a small mesh.
// 3. Named-parameter overrides (gradient_tolerance, max_iterations)
// change the Newton behaviour as expected.
// 4. The result agrees with the legacy newton_euclidean() at the
// same DOF assignment — proving the wrapper is non-destructive.
//
// These tests are the Phase 8 MVP acceptance probe. Phase 9a
// (Inversive-Distance) will become the next, deeper validation by
// implementing a new functional against this same trait API.
#include <CGAL/Conformal_map_traits.h>
#include <CGAL/Discrete_conformal_map.h>
#include <CGAL/Kernel_traits.h>
#include "mesh_builder.hpp" // make_triangle, make_quad_strip, make_tetrahedron
#include "euclidean_functional.hpp"
#include "newton_solver.hpp"
#include <gtest/gtest.h>
#include <cmath>
using namespace conformallab;
// ════════════════════════════════════════════════════════════════════════════
// 1. Traits class: compile-time type sanity
// ════════════════════════════════════════════════════════════════════════════
TEST(CGALConformalTraits, DefaultTraitsTypes)
{
using K = CGAL::Simple_cartesian<double>;
using Mesh = CGAL::Surface_mesh<K::Point_3>;
using Tr = CGAL::Default_conformal_map_traits<Mesh, K>;
// FT comes from the kernel.
static_assert(std::is_same_v<typename Tr::FT, double>);
// Descriptors come from boost::graph_traits, not from Surface_mesh directly.
static_assert(std::is_same_v<typename Tr::Triangle_mesh, Mesh>);
static_assert(std::is_same_v<
typename Tr::Vertex_descriptor,
typename boost::graph_traits<Mesh>::vertex_descriptor>);
// Property-map types should match Surface_mesh::Property_map for the
// appropriate key.
static_assert(std::is_same_v<
typename Tr::Theta_pmap,
typename Mesh::template Property_map<typename Tr::Vertex_descriptor, double>>);
static_assert(std::is_same_v<
typename Tr::Vertex_index_pmap,
typename Mesh::template Property_map<typename Tr::Vertex_descriptor, int>>);
static_assert(std::is_same_v<
typename Tr::Lambda0_pmap,
typename Mesh::template Property_map<typename Tr::Edge_descriptor, double>>);
// Default kernel: Simple_cartesian<double>.
using TrDefault = CGAL::Default_conformal_map_traits<Mesh>;
static_assert(std::is_same_v<typename TrDefault::Kernel,
CGAL::Simple_cartesian<double>>);
}
// ════════════════════════════════════════════════════════════════════════════
// 2. Traits property-map accessors are non-destructive
//
// Setting up via the trait helpers and via setup_euclidean_maps() must yield
// the same property map (Surface_mesh deduplicates by name).
// ════════════════════════════════════════════════════════════════════════════
TEST(CGALConformalTraits, AccessorsReuseExistingMaps)
{
using K = CGAL::Simple_cartesian<double>;
using Mesh = CGAL::Surface_mesh<K::Point_3>;
using Tr = CGAL::Default_conformal_map_traits<Mesh, K>;
auto mesh = make_triangle();
auto maps = setup_euclidean_maps(mesh);
auto theta_via_traits = Tr::theta_map(mesh);
auto idx_via_traits = Tr::vertex_index_map(mesh);
auto lambda0_via_traits = Tr::lambda0_map(mesh);
// Surface_mesh property maps with the same key type are equality-comparable
// by name lookup — accessing through the traits class must return the
// same map that setup_euclidean_maps() created.
EXPECT_EQ(theta_via_traits, maps.theta_v);
EXPECT_EQ(idx_via_traits, maps.v_idx);
EXPECT_EQ(lambda0_via_traits, maps.lambda0);
}
// ════════════════════════════════════════════════════════════════════════════
// 3. End-to-end: discrete_conformal_map_euclidean() on a small open mesh
// ════════════════════════════════════════════════════════════════════════════
TEST(CGALDiscreteConformalMap, SingleTriangleConverges)
{
auto mesh = make_triangle();
auto result = CGAL::discrete_conformal_map_euclidean(mesh);
EXPECT_TRUE(result.converged)
<< "Newton did not converge on a single triangle";
EXPECT_LT(result.gradient_norm, 1e-8);
EXPECT_GE(result.iterations, 0);
EXPECT_EQ(result.u_per_vertex.size(), num_vertices(mesh));
// I1/N7 propagated through the CGAL layer: status enum + diagnostics.
EXPECT_EQ(result.status, CGAL::Newton_status::Converged);
EXPECT_FALSE(result.sparse_qr_fallback_used); // pinned vertex → no gauge mode
EXPECT_GE(result.min_ldlt_pivot, 0.0);
// With the default flat-disc target curvature and the first vertex pinned,
// the natural-theta equilibrium is at u = 0 — Newton should accept x0=0.
for (double u : result.u_per_vertex)
EXPECT_NEAR(u, 0.0, 1e-8);
}
TEST(CGALDiscreteConformalMap, QuadStripConverges)
{
auto mesh = make_quad_strip();
auto result = CGAL::discrete_conformal_map_euclidean(mesh);
EXPECT_TRUE(result.converged);
EXPECT_LT(result.gradient_norm, 1e-8);
EXPECT_EQ(result.u_per_vertex.size(), num_vertices(mesh));
}
// ════════════════════════════════════════════════════════════════════════════
// 4. Named-parameter overrides take effect
// ════════════════════════════════════════════════════════════════════════════
TEST(CGALDiscreteConformalMap, MaxIterationsTakesEffect)
{
auto mesh = make_triangle();
// max_iterations(0) forces Newton to give up immediately.
auto result = CGAL::discrete_conformal_map_euclidean(
mesh,
CGAL::parameters::max_iterations(0));
EXPECT_EQ(result.iterations, 0);
// Trivial natural-theta case: gradient is already zero at x=0,
// so even 0 iterations may report "converged" depending on the
// initial gradient check. The point is just that the parameter
// was *read* — verified by EXPECT_EQ on iterations above.
}
TEST(CGALDiscreteConformalMap, GradientToleranceTakesEffect)
{
auto mesh = make_quad_strip();
// Loose tolerance — must still converge, but possibly in fewer steps.
auto result_loose = CGAL::discrete_conformal_map_euclidean(
mesh,
CGAL::parameters::gradient_tolerance(1e-4));
EXPECT_TRUE(result_loose.converged);
// Strict tolerance — also must converge, gradient norm must be tighter.
auto result_strict = CGAL::discrete_conformal_map_euclidean(
mesh,
CGAL::parameters::gradient_tolerance(1e-12));
EXPECT_TRUE(result_strict.converged);
EXPECT_LT(result_strict.gradient_norm, 1e-10);
}
// ════════════════════════════════════════════════════════════════════════════
// 5. Wrapper agrees with the legacy newton_euclidean() at the same setup
//
// This is the cross-API consistency check: same mesh, same default settings
// (first vertex pinned, x0=0) — the u-vector returned by the wrapper must
// match what newton_euclidean produces directly.
// ════════════════════════════════════════════════════════════════════════════
// ════════════════════════════════════════════════════════════════════════════
// 6. Kernel deduction: the wrapper must NOT hard-code Simple_cartesian
//
// Regression guard: the wrapper deduces its kernel from the mesh point type
// via `CGAL::Kernel_traits`. If anyone re-introduces a hard-coded
// `Simple_cartesian<double>` in the wrapper, the static_asserts here still
// pass (the legacy ConformalMesh uses that kernel) — but Phase 9a or any
// user with a different kernel-backed Surface_mesh would fail to compile.
// This test pins the deduction *contract* explicitly.
// ════════════════════════════════════════════════════════════════════════════
TEST(CGALDiscreteConformalMap, KernelIsDeducedFromMeshPointType)
{
using Mesh = ConformalMesh;
using P = typename Mesh::Point;
using DeducedKernel = typename CGAL::Kernel_traits<P>::Kernel;
using DeducedTraits = CGAL::Default_conformal_map_traits<Mesh, DeducedKernel>;
static_assert(std::is_same_v<DeducedKernel, CGAL::Simple_cartesian<double>>,
"ConformalMesh point type must deduce to Simple_cartesian<double>");
static_assert(std::is_same_v<typename DeducedTraits::FT, double>);
static_assert(std::is_same_v<typename DeducedTraits::Triangle_mesh, Mesh>);
// Run-time sanity: the wrapper accepts the deduced-kernel mesh end-to-end.
auto mesh = make_quad_strip();
auto result = CGAL::discrete_conformal_map_euclidean(mesh);
EXPECT_TRUE(result.converged);
}
TEST(CGALDiscreteConformalMap, WrapperMatchesLegacyAPI)
{
auto mesh = make_quad_strip();
// ── New API: applies natural-theta automatically ───────────────────────
auto result_new = CGAL::discrete_conformal_map_euclidean(mesh);
// ── Legacy API on a fresh mesh — must replicate the *same* preparation
// that the wrapper performs internally (pin first vertex, assign
// DOFs, apply natural-theta). Otherwise the comparison is unfair
// (Newton would diverge without natural-theta on these meshes). ────
auto mesh_legacy = make_quad_strip();
auto maps = setup_euclidean_maps(mesh_legacy);
compute_euclidean_lambda0_from_mesh(mesh_legacy, maps);
// Pin first vertex (gauge), assign sequential DOFs to the rest.
auto vit = mesh_legacy.vertices().begin();
maps.v_idx[*vit++] = -1;
int idx = 0;
for (; vit != mesh_legacy.vertices().end(); ++vit)
maps.v_idx[*vit] = idx++;
// Natural-theta: shift Θ so that x = 0 is the natural equilibrium.
std::vector<double> x0(idx, 0.0);
auto G0 = euclidean_gradient(mesh_legacy, x0, maps);
for (auto v : mesh_legacy.vertices()) {
int j = maps.v_idx[v];
if (j >= 0) maps.theta_v[v] -= G0[static_cast<std::size_t>(j)];
}
auto nr = newton_euclidean(mesh_legacy, x0, maps, 1e-10, 200);
// ── Compare ────────────────────────────────────────────────────────────
EXPECT_EQ(result_new.converged, nr.converged);
EXPECT_NEAR(result_new.gradient_norm, nr.grad_inf_norm, 1e-12);
// Pinned vertex u is 0 in both; for the rest the values agree.
for (auto v : mesh_legacy.vertices()) {
int j = maps.v_idx[v];
double u_legacy = (j >= 0) ? nr.x[static_cast<std::size_t>(j)] : 0.0;
EXPECT_NEAR(result_new.u_per_vertex[v.idx()], u_legacy, 1e-10)
<< "Wrapper diverges from legacy for vertex " << v.idx();
}
}