14134b99ce
README.md: reduced from 703 to ~75 lines — what/why, status, quick start, minimal usage example, navigation table to doc/ files. doc/architecture/overall_pipeline.md: trimmed — roadmap, extension points, declarative pipeline YAML, and references sections removed (each now has its own dedicated file). Replaced with a link table. New files: doc/getting-started.md — build modes, single-test invocation, CLI doc/api/pipeline.md — full pipeline API with code for all 3 geometries doc/api/extending.md — new functionals, geometry modes, Java porting guide doc/api/contracts.md — processing unit preconditions/provides table doc/api/cgal-package.md — Phase 8 CGAL package design + YAML pipeline (TODO) doc/math/geometry-modes.md — Euclidean/Spherical/HyperIdeal comparison doc/math/references.md — all papers by module doc/roadmap/phases.md — Phases 1–10 with porting/research boundary doc/roadmap/java-parity.md — Java vs C++ feature parity table doc/contributing.md — language policy, test standards, release flow Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
87 lines
4.0 KiB
Markdown
87 lines
4.0 KiB
Markdown
# Java ConformalLab vs. conformallab++ — Feature Parity
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Reference: [github.com/varylab/conformallab](https://github.com/varylab/conformallab)
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Java package root: `de.varylab.discreteconformal`
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When porting a Java class, locate the original in the Java repository and use it
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as the reference implementation for expected behaviour, edge cases, and test cases.
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---
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## Algorithm parity
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| Mathematical layer | Java ConformalLab | conformallab++ | Notes |
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|---|---|---|---|
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| Euclidean functional — energy, gradient | ✅ | ✅ | |
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| Spherical functional — energy, gradient, gauge-fix | ✅ | ✅ | |
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| HyperIdeal functional — energy, gradient | ✅ | ✅ | |
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| Inversive-distance functional (Luo 2004) | ✅ | ❌ Phase 9a | `InversiveDistanceFunctional.java` |
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| Euclidean Hessian — cotangent Laplacian | ✅ analytic | ✅ analytic | Pinkall–Polthier (1993) |
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| Spherical Hessian — ∂α/∂u via law of cosines | ✅ analytic | ✅ analytic | |
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| HyperIdeal Hessian — ζ → lᵢⱼ → β/α chain | ✅ analytic | ⚠️ symmetric FD | Phase 9b |
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| Newton solver | ✅ | ✅ | |
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| SparseQR fallback for gauge modes | unknown | ✅ | New in C++ |
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| Cone metrics — prescribed Θᵥ ≠ 2π | ✅ fully | ⚠️ data structure only | |
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| Layout / embedding — ℝ² / H² / S² | ✅ | ✅ priority-BFS all three | |
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| Exact hyperbolic trilateration | ✅ Möbius | ✅ Möbius + law of cosines | |
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| halfedge_uv — seam-aware UV (texture atlas) | ✅ | ✅ | |
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| Gauss–Bonnet consistency check | ✅ | ✅ | |
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| Tree-cotree cut graph (2g edges) | ✅ | ✅ Erickson–Whittlesey (2005) | |
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| Holonomy — Euclidean (translations) | ✅ | ✅ | |
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| Holonomy — Hyperbolic (SU(1,1) Möbius maps) | ✅ | ✅ | |
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| Period matrix τ — genus 1, SL(2,ℤ)-reduced | ✅ | ✅ | |
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| Fundamental domain — genus 1 | ✅ | ✅ CCW parallelogram | |
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| 4g-polygon boundary walk — genus g > 1 | ✅ | ❌ Phase 9c | `FundamentalDomainUtility.java` |
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| Siegel period matrix Ω — genus g ≥ 2 | ✅ | ❌ Phase 10b | |
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| Global uniformization — genus g ≥ 2 | ✅ | ❌ Phase 10c | |
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| Clausen / Lobachevsky / ImLi₂ | ✅ | ✅ | |
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| Poincaré disk / Lorentz boost visualisation | ✅ | ✅ | |
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| Mesh I/O + serialisation | ✅ XML/CoHDS | ✅ OFF/OBJ/PLY + JSON/XML | |
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| Interactive viewer | ✅ jReality | ✅ libigl/GLFW | |
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---
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## Java utility classes not yet ported
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These exist in `de.varylab.discreteconformal.util` in the Java library.
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They are candidates for Phase 9 or Phase 10.
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| Java class | Description | Phase |
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| `InversiveDistanceFunctional` | Inversive-distance conformal energy | 9a |
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| `DiscreteHarmonicFormUtility` | Discrete harmonic 1-forms | 10a prerequisite |
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| `DiscreteHolomorphicFormUtility` | Holomorphic differentials on discrete surfaces | 10a |
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| `DiscreteRiemannUtility` | Discrete Riemann surfaces | 10 |
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| `CanonicalBasisUtility` | Canonical homology basis for genus g | 9c / 10 |
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| `HomologyUtility` | Homology computation | 9c |
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| `HomotopyUtility` | Homotopy generators | 9c |
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| `SpanningTreeUtility` | Spanning tree algorithms | 8 / infrastructure |
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| `SurgeryUtility` | Mesh surgery (cut/glue) | — |
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| `StitchingUtility` | Seam stitching | — |
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| `CuttingUtility` | Advanced cutting (beyond tree-cotree) | 9c |
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| `HyperellipticUtility` | Hyperelliptic surfaces | 10 |
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| `LaplaceUtility` | Discrete Laplace operators | 9 / infrastructure |
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| `ConformalStructureUtility` | Conformal structure extraction | 10 |
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---
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## HyperIdeal Hessian: FD vs. analytic
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The Java library computes the HyperIdeal Hessian analytically through the chain:
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```
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(bᵢ, aₑ) → lᵢⱼ → ζ₁₃/ζ₁₄/ζ₁₅ → αᵢⱼ / βᵢ
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```
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conformallab++ uses a **symmetric finite-difference approximation**:
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```
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H[i,j] = ( G(x + ε·eⱼ)[i] − G(x − ε·eⱼ)[i] ) / (2ε), ε = 1e-5
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```
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Accuracy: O(ε²) ≈ 10⁻¹⁰ relative error. PSD guaranteed by strict convexity (Springborn 2020).
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Cost: n extra gradient evaluations per Newton step.
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Impact: negligible for meshes < 500 DOFs; measurable for larger meshes.
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The analytic Hessian is deferred to Phase 9b.
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