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: v0.10.0 — Phases 1–9b 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. 277 tests passing, 0 skipped — see doc/api/tests.md for the per-suite breakdown.

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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)

# Conformal flattening (Θ_v = 2π target). Closed meshes pin one vertex +
# enforce Gauss-Bonnet; open meshes pin the boundary and flatten the interior.
./bin/conformallab_core -i code/data/off/torus_8x8.off -g euclidean -v \
    -o layout.off -j result.json
#  topology: closed, free DOFs=63, genus=1
#  Euclidean: converged=yes  iter=3  |grad|_inf≈5e-15
./bin/conformallab_core -i code/data/obj/cathead.obj -g euclidean -v -o cat.off
#  topology: open (boundary pinned), free DOFs=119
#  Euclidean: converged=yes  iter=4

# API documentation (requires doxygen: brew/apt install doxygen)
cmake --build build --target doc
open doc/doxygen/html/index.html

Compile-time workflow modes

The default build (PCH + Unity Build + Dense→Core trims) takes ~47 s clean for the full CGAL test target. Five opt-in modes cover other iteration scenarios:

# Configure-only, no compile.  ~1 s configure, 0 s build — emits
# compile_commands.json for IDE / clangd; skips the GTest fetch.
cmake -S code -B build -DBUILD_TESTING=OFF

# Header smoke check: per-public-header isolated compile.  ~12 s full,
# ~0.1 s after touching one header.  "Does my refactor still parse?"
cmake -S code -B build -DBUILD_TESTING=OFF -DCONFORMALLAB_HEADERS_CHECK=ON
cmake --build build --target headers_check

# Dev iteration: PCH on, Unity off.  Slower full build (~75 s) but
# editing a single test rebuilds in ~16 s instead of ~46 s.
cmake -S code -B build -DWITH_CGAL_TESTS=ON -DCONFORMALLAB_DEV_BUILD=ON

# Fast CI tests: -O0 -g for the test executables only (library /
# install targets keep -O3).  Linux + g++ typically ~40 % faster
# build at the cost of 5–15× slower test RUN.  Neutral on macOS.
cmake -S code -B build -DWITH_CGAL_TESTS=ON -DCONFORMALLAB_FAST_TEST_BUILD=ON

# Low-memory build: -O0, no PCH, unity batch 1, --no-keep-memory linker.
# Drops cc1plus peak from ~700 MB to ~150 MB per TU.  Use on Raspberry Pi
# or any runner with ≤ 4 GB RAM.  Always build with -j1.
cmake -S code -B build -DWITH_CGAL_TESTS=ON -DCONFORMALLAB_LOW_MEMORY_BUILD=ON
cmake --build build --target conformallab_cgal_tests -j1

# Pristine measurement: disable both performance levers, e.g. for
# scripts/quality/coverage.sh that needs every TU compiled fresh.
cmake -S code -B build -DWITH_CGAL_TESTS=ON \
    -DCONFORMALLAB_USE_PCH=OFF -DCMAKE_UNITY_BUILD=OFF

ccache is detected automatically when present on PATH; disable with -DCONFORMALLAB_USE_CCACHE=OFF. Full mode matrix + measurements in doc/architecture/compile-time.md.

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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 as gauge fix, index the rest 0..n-1
auto gauge = *mesh.vertices().begin();
int n = assign_euclidean_vertex_dof_indices(mesh, maps, gauge);

// Natural equilibrium target: x* = 0 by construction
std::vector<double> x0(static_cast<std::size_t>(n), 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);

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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

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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

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Bugs & questions

• Bug reports / feature requests: Gitea Issues
• Code mirror (read-only): Codeberg
• Contact: Tarik Moussa · Tarik.moussa95@gmail.com

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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.