port MatrixUtility and SurfaceCurveUtility tests to C++

- include/matrix_utility.hpp: 4x4 mapping matrix R·from=to (Eigen)
- include/projective_math.hpp: dehomogenize, hyperbolicDistance,
  isOnSegment (collinearity + betweenness via 3D cross/dot),
  getPointOnCorrespondingSegment (parameter by arc-length ratio)
- test_matrix_utility.cpp: port of MatrixUtilityTest (1 test)
- test_surface_curve_utility.cpp: port of SurfaceCurveUtilityTest
  testIsBetween and testGetPointOnSegment_SegmentEdge (2 tests)
- tolerance adjusted to 1e-12 for matrix inversion (2.7e-15 rounding
  from Eigen vs jReality's LU; both well within meaningful accuracy)

Total: 16/16 tests pass

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Tarik Moussa
2026-05-09 01:15:35 +02:00
parent c30d540521
commit a2876b9cbf
5 changed files with 207 additions and 0 deletions

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#pragma once
// 4x4 mapping matrix from corresponding point pairs.
// Ported from de.varylab.discreteconformal.math.MatrixUtility (Java).
#include <Eigen/Dense>
namespace conformallab {
// Find the 4×4 matrix R that maps source points to target points.
// Each row of `from` / `to` is a homogeneous 4-vector (one point per row).
// Post-condition: R * from.row(i).T == to.row(i).T for all i.
//
// Implementation: R = to^T * (from^T)^{-1}
// Corresponds to Java MatrixUtility.makeMappingMatrix().
inline Eigen::Matrix4d makeMappingMatrix(const Eigen::Matrix4d& from,
const Eigen::Matrix4d& to) {
return to.transpose() * from.transpose().inverse();
}
} // namespace conformallab

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#pragma once
// Projective and hyperbolic geometry utilities.
// Ported from de.jreality.math.Pn / Rn and
// de.varylab.discreteconformal.uniformization.SurfaceCurveUtility (Java).
#include <Eigen/Dense>
#include <cmath>
#include <algorithm>
#include <array>
#include <cassert>
namespace conformallab {
// Divide a homogeneous vector by its last component.
// Corresponds to Java Pn.dehomogenize().
inline Eigen::VectorXd dehomogenize(const Eigen::VectorXd& p) {
return p / p(p.size() - 1);
}
// Hyperbolic distance between two homogeneous vectors of the same dimension.
// The last component is the "timelike" coordinate (jReality convention).
// Inner product: <p,q> = -sum_i p_i*q_i + p_last * q_last
// Distance: arcosh(<p̂, q̂>) where p̂ normalises to the hyperboloid.
// Corresponds to Java Pn.distanceBetween(p, q, Pn.HYPERBOLIC).
inline double hyperbolicDistance(const Eigen::VectorXd& p,
const Eigen::VectorXd& q) {
int n = static_cast<int>(p.size());
double normP = std::sqrt(p(n-1)*p(n-1) - p.head(n-1).squaredNorm());
double normQ = std::sqrt(q(n-1)*q(n-1) - q.head(n-1).squaredNorm());
double inner = (-p.head(n-1).dot(q.head(n-1)) + p(n-1)*q(n-1))
/ (normP * normQ);
// clamp to [1, inf) to guard against floating-point rounding below 1
return std::acosh(std::max(1.0, inner));
}
// Check whether a homogeneous point p lies on the segment [s[0], s[1]].
// Works for n-dimensional homogeneous coords; cross product uses the first
// 3 spatial components after dehomogenization (matching jReality's Rn behaviour).
// Corresponds to Java SurfaceCurveUtility.isOnSegment().
inline bool isOnSegment(const Eigen::VectorXd& p_h,
const Eigen::VectorXd& s0_h,
const Eigen::VectorXd& s1_h) {
// Dehomogenize all points.
Eigen::VectorXd p = dehomogenize(p_h);
Eigen::VectorXd s0 = dehomogenize(s0_h);
Eigen::VectorXd s1 = dehomogenize(s1_h);
// Vectors from p to each endpoint.
Eigen::VectorXd ps0 = s0 - p;
Eigen::VectorXd ps1 = s1 - p;
// Collinearity check: 3D cross product of first 3 spatial components
// (after dehomogenize the w-component differences cancel to 0).
// head<3>() gives compile-time size needed by Eigen's cross().
Eigen::Vector3d cross = ps0.head<3>().cross(ps1.head<3>());
if (cross.norm() > 1e-7) return false;
// Betweenness check: dot product of the two direction vectors must be ≤ 0.
double dot = ps0.dot(ps1);
if (dot > 0.0) return false;
return true;
}
// Find the point on `target` that corresponds to `p` on `source`.
// The parameter t is determined by hyperbolic distance ratios on `source`,
// then applied as a linear interpolation on the dehomogenized `target`.
// Corresponds to Java SurfaceCurveUtility.getPointOnCorrespondingSegment().
inline Eigen::VectorXd getPointOnCorrespondingSegment(
const Eigen::VectorXd& p,
const Eigen::VectorXd& src0,
const Eigen::VectorXd& src1,
const Eigen::VectorXd& tgt0,
const Eigen::VectorXd& tgt1)
{
double l = hyperbolicDistance(src0, src1);
double l1 = hyperbolicDistance(src0, p) / l; // weight for tgt1
double l2 = hyperbolicDistance(src1, p) / l; // weight for tgt0
if (std::isnan(l1)) return dehomogenize(tgt0);
if (std::isnan(l2)) return dehomogenize(tgt1);
Eigen::VectorXd t0d = dehomogenize(tgt0);
Eigen::VectorXd t1d = dehomogenize(tgt1);
return l1 * t1d + l2 * t0d;
}
} // namespace conformallab

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add_executable(conformallab_tests
test_clausen.cpp
test_hyper_ideal_utility.cpp
test_matrix_utility.cpp
test_surface_curve_utility.cpp
)
target_include_directories(conformallab_tests SYSTEM PRIVATE

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// Port of de.varylab.discreteconformal.math.MatrixUtilityTest (Java/JUnit).
#include "matrix_utility.hpp"
#include <gtest/gtest.h>
#include <Eigen/Dense>
using Eigen::Matrix4d;
using Eigen::Vector4d;
using conformallab::makeMappingMatrix;
TEST(MatrixUtilityTest, MakeMappingMatrix) {
// Source points (rows = homogeneous 4-vectors).
Matrix4d from;
from.row(0) = Vector4d(2, 0, 2, 1);
from.row(1) = Vector4d(1, 1, 0, 0);
from.row(2) = Vector4d(1, 0, 8, 0);
from.row(3) = Vector4d(3, 4, 0, 1);
// Target points.
Matrix4d to;
to.row(0) = Vector4d(2, 0, 1, 0);
to.row(1) = Vector4d(0, 3, 0, 2);
to.row(2) = Vector4d(1, 0, 4, 0);
to.row(3) = Vector4d(0, 3, 0, 5);
Matrix4d R = makeMappingMatrix(from, to);
// R must map each source column to the corresponding target column.
for (int i = 0; i < 4; i++) {
Vector4d result = R * from.row(i).transpose();
Vector4d expected = to.row(i).transpose();
for (int k = 0; k < 4; k++) {
// Java original uses 1e-15; double-precision matrix inversion gives ~2e-15
// rounding, so we use 1e-12 (still far below any meaningful error).
EXPECT_NEAR(expected(k), result(k), 1e-12)
<< "Row " << i << ", component " << k;
}
}
}

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// Port of de.varylab.discreteconformal.uniformization.SurfaceCurveUtilityTest
// (Java/JUnit) — the two pure-math tests that don't need the HDS.
#include "projective_math.hpp"
#include <gtest/gtest.h>
#include <Eigen/Dense>
using Eigen::VectorXd;
using conformallab::isOnSegment;
using conformallab::getPointOnCorrespondingSegment;
using conformallab::dehomogenize;
// Helper: make VectorXd from initializer list.
static VectorXd V(std::initializer_list<double> vals) {
VectorXd v(vals.size());
int i = 0;
for (double x : vals) v(i++) = x;
return v;
}
// A point exactly at the midpoint of segment lies on it; a slightly perturbed
// point perpendicular to the segment does not.
TEST(SurfaceCurveUtilityTest, IsOnSegment) {
VectorXd x1 = V({1, 1, 1, 1});
VectorXd x2 = V({1 + 1e-5, 1, 1, 1});
VectorXd s0 = V({0, 0, 0, 1});
VectorXd s1 = V({2, 2, 2, 1});
EXPECT_TRUE(isOnSegment(x1, s0, s1));
EXPECT_FALSE(isOnSegment(x2, s0, s1));
}
// The edge point coincides (within floating-point) with the END of the edge
// segment, so the corresponding point on the target segment must be its end.
TEST(SurfaceCurveUtilityTest, GetPointOnCorrespondingSegment_SegmentEdge) {
VectorXd edgePoint = V({0.352392439203295, 0.9123804930829212, 1.0});
VectorXd edgeSrc0 = V({0.34745306897719913, 0.912568467121888, 1.0});
VectorXd edgeSrc1 = V({0.35239243920431296, 0.912380493082885, 1.0});
VectorXd tgt0 = V({-0.2896352574166635, 0.03146361746587523,
0.10643898885661185, 0.44373020886051084});
VectorXd tgt1 = V({-0.2666822290964323, 0.019034256494171405,
0.10525293907970201, 0.44373020886051084});
VectorXd result = getPointOnCorrespondingSegment(
edgePoint, edgeSrc0, edgeSrc1, tgt0, tgt1);
// Expected: dehomogenized tgt1 (edgePoint is at the end of the source segment).
VectorXd expected = dehomogenize(tgt1);
ASSERT_EQ(expected.size(), result.size());
for (int i = 0; i < result.size(); i++) {
EXPECT_NEAR(expected(i), result(i), 1e-9) << "component " << i;
}
}