Two structural compile-time optimisations on the conformallab_cgal_tests
target, both opt-out-able and verified safe (236/236 tests pass under
every configuration).
(1) Precompiled headers — option CONFORMALLAB_USE_PCH (default ON)
target_precompile_headers(conformallab_cgal_tests PRIVATE
<CGAL/Surface_mesh.h>
<CGAL/Simple_cartesian.h>
<CGAL/Kernel_traits.h>
<CGAL/boost/graph/iterator.h>
<CGAL/Polygon_mesh_processing/triangulate_faces.h>
<Eigen/Dense> <Eigen/Sparse> <Eigen/SparseCholesky> <Eigen/SparseQR>
<gtest/gtest.h>
<vector> <string> <cmath> <complex>
)
Absorbs the per-TU CGAL+Eigen template-parse cost (measured at 5.9 s
per minimal "include <CGAL/Discrete_conformal_map.h>" hello-world TU
on Apple M1).
(2) Unity Build — UNITY_BUILD ON with UNITY_BUILD_BATCH_SIZE 4
Concatenates the 22 test TUs into 5 batches of <=4 files each;
CGAL+Eigen headers parsed once per batch instead of once per TU.
Batch size 4 keeps gtest's TEST(...) macros and per-file
`using namespace ...` from colliding across batched files.
Numbers (Apple M1, Ninja, -j8, clean rebuild)
─────────────────────────────────────────────
wall CPU tests
baseline 78 s 676 s 236/236
+ PCH 66 s 474 s 236/236 (-15% wall, -30% CPU)
+ PCH + Unity 55 s 167 s 236/236 (-30% wall, -75% CPU)
Honest deferred items (documented in doc/architecture/compile-time.md):
* `extern template` (lever #2 in the analysis) — subsumed by PCH;
estimated residual gain <5%, would add Eigen-version fragility.
* Header split <CGAL/Discrete_conformal_map_{euclidean,spherical,
hyper_ideal}.h> (lever #3) — downstream-only benefit (our test
build needs all three); kept as a future cleanup once a downstream
user actually requests it.
Opt-outs: `-DCONFORMALLAB_USE_PCH=OFF` and `-DCMAKE_UNITY_BUILD=OFF`.
Detailed measurement methodology, per-TU breakdowns, clang
-ftime-trace template hot-spots, and a "what comes next" lever list
live in doc/architecture/compile-time.md.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
conformallab++
C++17 reimplementation of ConformalLab — Stefan Sechelmann's Java research library for discrete conformal geometry (TU Berlin). The long-term goal is a CGAL package for discrete conformal maps.
Algorithmic foundation:
Stefan Sechelmann — Variational Methods for Discrete Surface Parameterization: Applications and Implementation, TU Berlin 2016. DOI: 10.14279/depositonce-5415 · CC BY-SA 4.0 · Java original · sechel.de
Status: v0.9.0 — Phases 1–9a complete, Phase 8b-Lite CGAL API surface. Newton solvers for five DCE models (Euclidean / Spherical / HyperIdeal / CP-Euclidean / Inversive-Distance), priority-BFS layout in ℝ²/S²/Poincaré disk, Gauss–Bonnet, tree-cotree cut graph, Möbius holonomy, period matrix (genus 1), fundamental domain, halfedge_uv texture atlas, JSON/XML serialisation, CLI app. Full test suite passing, 0 skipped — see doc/api/tests.md for the per-suite breakdown.
Quick start
git clone https://codeberg.org/TMoussa/ConformalLabpp && cd ConformalLabpp
# Fast tests — no system dependencies
cmake -S code -B build && cmake --build build --target conformallab_tests -j$(nproc)
ctest --test-dir build --output-on-failure
# CGAL tests headless (apt install libboost-dev / brew install boost)
cmake -S code -B build -DWITH_CGAL_TESTS=ON
cmake --build build --target conformallab_cgal_tests -j$(nproc)
ctest --test-dir build -R "^cgal\." --output-on-failure
# Full build with CLI + viewer (requires Wayland/X11 dev headers)
cmake -S code -B build -DWITH_CGAL=ON && cmake --build build -j$(nproc)
./bin/conformallab_core -i input.off -g euclidean -o layout.off -j result.json
# API documentation (requires doxygen: brew/apt install doxygen)
cmake --build build --target doc
open doc/doxygen/html/index.html
Minimal usage
#include "conformal_mesh.hpp"
#include "mesh_io.hpp"
#include "euclidean_functional.hpp"
#include "gauss_bonnet.hpp"
#include "newton_solver.hpp"
#include "layout.hpp"
using namespace conformallab;
ConformalMesh mesh = load_mesh("input.off");
EuclideanMaps maps = setup_euclidean_maps(mesh);
compute_euclidean_lambda0_from_mesh(mesh, maps);
// Assign DOFs — pin first vertex (gauge fix)
auto vit = mesh.vertices().begin();
maps.v_idx[*vit++] = -1;
int idx = 0;
for (; vit != mesh.vertices().end(); ++vit) maps.v_idx[*vit] = idx++;
// Natural equilibrium target: x* = 0 by construction
std::vector<double> x0(idx, 0.0);
auto G0 = euclidean_gradient(mesh, x0, maps);
for (auto v : mesh.vertices())
if (maps.v_idx[v] >= 0) maps.theta_v[v] -= G0[maps.v_idx[v]];
check_gauss_bonnet(mesh, maps);
NewtonResult res = newton_euclidean(mesh, x0, maps);
Layout2D layout = euclidean_layout(mesh, res.x, maps);
Documentation
| API reference (Doxygen HTML) — every public class, function and named-parameter helper | https://tmoussa.codeberg.page/ConformalLabpp/ |
| Getting started — build modes, single-test invocation, CLI, Docker | doc/getting-started.md |
| Pipeline API — all three geometries, holonomy, serialisation | doc/api/pipeline.md |
| Public headers — all public headers with descriptions | doc/api/headers.md |
| Test suites — per-suite breakdown and counts (single source of truth) | doc/api/tests.md |
| Extending — new functionals, geometry modes, porting from Java | doc/api/extending.md |
| Processing unit contracts — preconditions / provides table | doc/api/contracts.md |
| CGAL package design — Phase 8 target, YAML pipeline | doc/api/cgal-package.md |
| Architecture & pipeline diagram | doc/architecture/overall_pipeline.md |
| geometry-central comparison — shared core, demarcation, adoption candidates, scientific added value | doc/architecture/geometry-central-comparison.md |
| Design decisions — key architectural choices + rationale | doc/architecture/design-decisions.md |
| Project structure — directory tree + build targets | doc/architecture/project-structure.md |
| Discrete conformal theory — mathematical background for collaborators | doc/math/discrete-conformal-theory.md |
| Validation — known analytic results + how to verify them | doc/math/validation.md |
| Validation protocol — concrete commands with expected outputs | doc/math/validation-protocol.md |
| Tutorial: add a new functional — step-by-step Inversive-Distance port | doc/tutorials/add-inversive-distance.md |
| Declarative YAML pipeline — concept, token vocabulary, 5 examples | doc/concepts/declarative-pipeline.md |
| Geometry modes — Euclidean / Spherical / HyperIdeal comparison | doc/math/geometry-modes.md |
| References — all papers by module | doc/math/references.md |
| Software landscape — how conformallab++ relates to libigl, CGAL, geometry-central | doc/math/software-landscape.md |
| Novelty statement — unique features, target audience, what this is not | doc/math/novelty-statement.md |
| Complexity & scalability — O() analysis, measured timings on real meshes, HyperIdeal bottleneck | doc/math/complexity.md |
| Roadmap — Phases 1–10 | doc/roadmap/phases.md |
| Java parity table — what is ported, what is planned | doc/roadmap/java-parity.md |
| Contributing — language policy, test standards, release flow | doc/contributing.md |
| Claude Code context | CLAUDE.md |
Citing
If you use conformallab++ in your research, please cite it using the metadata
in CITATION.cff. GitHub and Codeberg show a "Cite this repository"
button that generates BibTeX and APA automatically.
The primary algorithmic source is:
Stefan Sechelmann — Variational Methods for Discrete Surface Parameterization: Applications and Implementation, TU Berlin 2016. DOI: 10.14279/depositonce-5415
Bugs & questions
- Bug reports / feature requests: Gitea Issues
- Code mirror (read-only): Codeberg
- Contact: Tarik Moussa · Tarik.moussa95@gmail.com
License
conformallab++ is released under the MIT License (see LICENSE).
Copyright © 2024–2026 Tarik Moussa.
The dissertation (Sechelmann 2016) is CC BY-SA 4.0.