added tests

This commit is contained in:
randogoth 2026-06-11 11:37:45 +03:00
parent f6d1241ecd
commit 5e3441584a

View file

@ -455,3 +455,141 @@ impl Xenobalanus {
clusters clusters
} }
} }
#[cfg(test)]
mod tests {
use super::*;
// --- Point ---
#[test]
fn point_distance_3_4_5() {
let a = Point::new(0.0, 0.0);
let b = Point::new(3.0, 4.0);
assert!((a.distance(b) - 5.0).abs() < 1e-5);
}
#[test]
fn point_bearing_east_is_zero() {
let origin = Point::new(0.0, 0.0);
let east = Point::new(1.0, 0.0);
// delta_y=0, delta_x=1 → atan2(0,1)=0° → bearing=0°
assert!((origin.bearing(east) - 0.0).abs() < 1e-4);
}
// --- random_points ---
#[test]
fn random_points_count_and_bounds() {
let mut xb = Xenobalanus::new();
xb.random_points((0.0, 0.0), 10.0, 100);
let pts = xb.points();
assert_eq!(pts.len(), 100);
for (x, y) in pts {
assert!(x >= -5.0 && x <= 5.0, "x={x} out of [-5, 5]");
assert!(y >= -5.0 && y <= 5.0, "y={y} out of [-5, 5]");
}
}
// --- delaunay ---
fn unit_square() -> Vec<Point> {
vec![
Point::new(0.0, 0.0),
Point::new(1.0, 0.0),
Point::new(1.0, 1.0),
Point::new(0.0, 1.0),
]
}
#[test]
fn delaunay_four_points_two_triangles() {
let mut xb = Xenobalanus::new();
xb.set_points(unit_square());
xb.delaunay();
// 4 convex points → 2 triangles → 6 indices
assert_eq!(xb.triangles_flat().len(), 6);
}
// --- preprocess ---
#[test]
fn preprocess_sequential_builds_edges() {
let mut xb = Xenobalanus::new();
xb.set_points(unit_square());
xb.delaunay();
xb.preprocess(0, false);
// unit square Delaunay: 4 boundary edges + 1 diagonal = 5
assert_eq!(xb.edge_lengths().len(), 5);
}
#[test]
fn preprocess_parallel_matches_sequential() {
let mut xb_seq = Xenobalanus::new();
xb_seq.set_points(unit_square());
xb_seq.delaunay();
xb_seq.preprocess(0, false);
let mut xb_par = Xenobalanus::new();
xb_par.set_points(unit_square());
xb_par.delaunay();
xb_par.preprocess(0, true);
assert_eq!(xb_seq.edge_lengths().len(), xb_par.edge_lengths().len());
}
// --- dtscan ---
#[test]
fn dtscan_finds_cluster_in_grid() {
let mut xb = Xenobalanus::new();
// 3×3 grid with spacing 1.0; diagonal ≈ 1.414
let pts: Vec<Point> = (0..3)
.flat_map(|i| (0..3).map(move |j| Point::new(i as f32, j as f32)))
.collect();
xb.set_points(pts);
xb.delaunay();
xb.preprocess(0, false);
// max_closeness=1.5 covers all edges (max diagonal ≈ 1.414)
let clusters = xb.dtscan(2, 1.5);
assert!(!clusters.is_empty());
}
// --- delfin ---
#[test]
fn delfin_smoke_test() {
let mut xb = Xenobalanus::new();
xb.random_points((0.0, 0.0), 100.0, 200);
xb.delaunay();
xb.preprocess(2, false);
// just verify it runs without panic
let _voids = xb.delfin(0.0, 0.0);
}
// --- readme example ---
#[test]
fn readme_example_pipeline() {
// Mirrors the workflow shown in the README exactly.
let dots: u32 = 10000;
let side_length: f32 = 10000.0;
let mut xeno = Xenobalanus::new();
xeno.random_points((0.0, 0.0), side_length, dots);
xeno.delaunay();
xeno.preprocess(0, false);
let min_area: f32 = 1000.0;
let min_distance: f32 = 200.0;
let void_polygons: Vec<HashSet<usize>> = xeno.delfin(min_area, min_distance);
let min_pts: usize = 5;
let max_closeness: f32 = 100.5;
let clusters: Vec<Vec<usize>> = xeno.dtscan(min_pts, max_closeness);
// With 10 000 uniform random points both algorithms should find results.
assert!(!void_polygons.is_empty(), "delfin found no voids");
assert!(!clusters.is_empty(), "dtscan found no clusters");
}
}