From 5e3441584aa30a6438d964388d73de328e3dbe37 Mon Sep 17 00:00:00 2001
From: randogoth <kflux@posteo.de>
Date: Thu, 11 Jun 2026 11:37:45 +0300
Subject: [PATCH] added tests

---
 src/lib.rs | 138 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 138 insertions(+)

diff --git a/src/lib.rs b/src/lib.rs
index 3af0075..d9b71a1 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -454,4 +454,142 @@ impl Xenobalanus {
     
         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");
+    }
 }
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