doc/concepts/declarative-pipeline.md — vollständige Design-Spezifikation:
1. Kernidee: Processing Units mit expliziten require/provide-Contracts
2. Token-Vokabular: 30 Tokens in 7 Kategorien
input, setup, Gauss-Bonnet, solver, topology, layout, period/domain/output
3. YAML-Schema: Vollständige Syntax inkl. Parameterdefaults aller Units
4. Validierungsalgorithmus: monoton wachsendes provided-Set, Pre-Execution-Check
5. 5 vollständige Beispiele:
A — Euklidische Uniformisierung Torus (τ-Ausgabe)
B — Sphärische Uniformisierung (cathead.obj)
C — Hyperbolische Uniformisierung Torus (Poincaré-Disk)
D — Volle Pipeline mit Periodenmatrix + 5×5-Kachelung
E — Absichtlich fehlerhaftes Beispiel mit Validator-Fehlermeldungen
6. C++-Mapping: alle YAML-Unit-Namen → C++-Funktionen + Header
7. Implementierungsplan (Phase 8e): pipeline.hpp + CLI-App + YAML-Abhängigkeit
8. Design-Entscheidungen: YAML vs. JSON/TOML, explizit vs. auto-inference,
linear vs. DAG, eine Geometrie pro Datei
doc/api/cgal-package.md: Link zum Konzeptdokument ergänzt.
README.md: Link in Dokumentationstabelle ergänzt.
Co-Authored-By: Claude Sonnet 4.6 <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: Phase 7 complete. Newton solver for all three geometries (Euclidean / Spherical / HyperIdeal), 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. 170 CGAL tests + 36 non-CGAL tests.
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
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
| 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 24 headers with descriptions | doc/api/headers.md |
| Test suites — 28 suites, 170 tests, individual counts | 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 |
| 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 |
| 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 |
License
conformallab++ is released under the MIT License (see LICENSE).
The dissertation (Sechelmann 2016) is CC BY-SA 4.0.