Merge pull request 'feat(geometry): pn_geometry.hpp — Pn projective-metric substrate (jReality port)' (#31) from feat/pn-geometry-substrate into main
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code/include/pn_geometry.hpp
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156
code/include/pn_geometry.hpp
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#pragma once
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// Copyright (c) 2024-2026 Tarik Moussa.
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// SPDX-License-Identifier: MIT
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// pn_geometry.hpp
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//
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// Projective-metric geometry substrate — faithful port of the
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// `de.jreality.math.Pn` surface that the Java algorithmic core
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// uses pervasively:
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// HyperbolicLayout, SphericalLayout, FundamentalPolygon,
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// KoebePolyhedron, quasi-isothermic utilities, hyperelliptic θ.
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//
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// Porting this ~30-function surface once unblocks every downstream
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// geometric phase (9c / 10c' / 10e / 11c) instead of re-deriving the
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// metric ad hoc per phase.
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//
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// ┌──────────────────────────────────────────────────────────────────┐
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// │ Metric signature convention (matches jReality exactly) │
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// │ │
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// │ EUCLIDEAN = 0 ⟨u,v⟩ = Σ_{i<last} uᵢvᵢ (spatial) │
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// │ ELLIPTIC = +1 ⟨u,v⟩ = Σ_{all} uᵢvᵢ (S^n) │
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// │ HYPERBOLIC = -1 ⟨u,v⟩ = u_last·v_last − Σ_{i<last} uᵢvᵢ │
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// │ (Minkowski; last coord = timelike) │
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// │ │
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// │ HYPERBOLIC uses the timelike-positive ("upper sheet") convention│
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// │ so a normalised hyperbolic point satisfies ⟨p,p⟩ = +1 and │
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// │ ⟨p,q⟩ ≥ 1 → d(p,q) = acosh(⟨p,q⟩) directly. │
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// │ This is identical to projective_math.hpp::hyperbolicDistance, │
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// │ against which pn_distance_between(..., HYPERBOLIC) is anchored. │
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// └──────────────────────────────────────────────────────────────────┘
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//
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// Vectors are Eigen column vectors (homogeneous, length = dim+1).
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#include <Eigen/Core>
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#include <cmath>
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#include <algorithm>
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namespace conformallab {
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/// Metric signatures matching `de.jreality.math.Pn`.
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enum PnMetric : int {
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PN_EUCLIDEAN = 0,
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PN_ELLIPTIC = +1,
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PN_HYPERBOLIC = -1
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};
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// ── Inner product ─────────────────────────────────────────────────────────────
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/// Bilinear form ⟨u,v⟩ for the given metric.
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/// Spatial part = all but the last coordinate; the last coord is the
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/// homogeneous/timelike one.
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inline double pn_inner_product(const Eigen::VectorXd& u,
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const Eigen::VectorXd& v,
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int metric)
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{
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const int n = static_cast<int>(u.size());
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const double spat = u.head(n - 1).dot(v.head(n - 1));
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const double last = u(n - 1) * v(n - 1);
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switch (metric) {
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case PN_HYPERBOLIC: return last - spat;
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case PN_ELLIPTIC: return last + spat;
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case PN_EUCLIDEAN:
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default: return spat;
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}
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}
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// ── Norm / scale ──────────────────────────────────────────────────────────────
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/// Metric norm √|⟨p,p⟩|. Absolute value guards against tiny negative
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/// round-off in the Euclidean / hyperbolic degenerate cases.
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inline double pn_norm(const Eigen::VectorXd& p, int metric)
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{
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return std::sqrt(std::abs(pn_inner_product(p, p, metric)));
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}
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/// Dehomogenise: divide by the last component (jReality `Pn.dehomogenize`).
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inline Eigen::VectorXd pn_dehomogenize(const Eigen::VectorXd& p)
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{
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return p / p(p.size() - 1);
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}
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/// Scale `p` to metric norm `length` (jReality `Pn.setToLength`).
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/// Returns `p` unchanged when its norm is numerically zero.
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inline Eigen::VectorXd pn_set_to_length(const Eigen::VectorXd& p,
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double length, int metric)
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{
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const double nrm = pn_norm(p, metric);
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if (nrm < 1e-300) return p;
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return p * (length / nrm);
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}
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/// Normalise to unit metric norm (jReality `Pn.normalize`).
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inline Eigen::VectorXd pn_normalize(const Eigen::VectorXd& p, int metric)
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{
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return pn_set_to_length(p, 1.0, metric);
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}
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// ── Distance ──────────────────────────────────────────────────────────────────
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/// Geodesic distance between two points (jReality `Pn.distanceBetween`).
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/// EUCLIDEAN: ‖p̂_spatial − q̂_spatial‖ (dehomogenised)
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/// ELLIPTIC: acos(⟨p̂,q̂⟩) (spherical angle, clamped to [−1,1])
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/// HYPERBOLIC: acosh(⟨p̂,q̂⟩) (clamped ≥ 1)
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inline double pn_distance_between(const Eigen::VectorXd& p,
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const Eigen::VectorXd& q,
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int metric)
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{
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if (metric == PN_EUCLIDEAN) {
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const auto pd = pn_dehomogenize(p);
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const auto qd = pn_dehomogenize(q);
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const int n = static_cast<int>(pd.size());
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return (pd.head(n - 1) - qd.head(n - 1)).norm();
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}
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const double np = pn_norm(p, metric);
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const double nq = pn_norm(q, metric);
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double c = pn_inner_product(p, q, metric) / (np * nq);
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if (metric == PN_HYPERBOLIC)
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return std::acosh(std::max(1.0, c));
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// ELLIPTIC
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c = std::clamp(c, -1.0, 1.0);
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return std::acos(c);
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}
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// ── Geodesic interpolation ────────────────────────────────────────────────────
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/// Constant-speed geodesic interpolation at parameter t ∈ [0,1]
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/// (jReality `Pn.linearInterpolation`).
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/// EUCLIDEAN: affine blend of the dehomogenised points.
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/// ELLIPTIC: spherical slerp:
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/// r(t) = (sin((1−t)d)·p̂ + sin(td)·q̂) / sin(d)
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/// HYPERBOLIC: hyperbolic slerp:
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/// r(t) = (sinh((1−t)d)·p̂ + sinh(td)·q̂) / sinh(d)
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/// where d = pn_distance_between(p,q,metric) and p̂,q̂ are unit vectors.
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inline Eigen::VectorXd pn_linear_interpolation(const Eigen::VectorXd& p,
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const Eigen::VectorXd& q,
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double t, int metric)
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{
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if (metric == PN_EUCLIDEAN) {
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const auto pd = pn_dehomogenize(p);
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const auto qd = pn_dehomogenize(q);
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return (1.0 - t) * pd + t * qd;
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}
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const auto ph = pn_normalize(p, metric);
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const auto qh = pn_normalize(q, metric);
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const double d = pn_distance_between(ph, qh, metric);
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if (d < 1e-12) return ph; // coincident — return either endpoint
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if (metric == PN_ELLIPTIC) {
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const double s = std::sin(d);
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return (std::sin((1.0 - t) * d) * ph + std::sin(t * d) * qh) / s;
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}
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// HYPERBOLIC
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const double s = std::sinh(d);
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return (std::sinh((1.0 - t) * d) * ph + std::sinh(t * d) * qh) / s;
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}
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} // namespace conformallab
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