Add v2 geometry normalization and boundary-layer seed points

tools/adaptive-isogrid/src/brain/triangulation.py

@@ -21,6 +21,71 @@ from src.shared.arc_utils import inset_arc, typed_segments_to_polyline, typed_se
 from .density_field import evaluate_density, density_to_spacing
 
 
+def _boundary_layer_offset_for_segment(mid_pt, geometry, params):
+    """Choose inward offset for boundary seed row."""
+    explicit = params.get('boundary_layer_offset', None)
+    if explicit is not None:
+        return max(float(explicit), 0.0)
+    eta = evaluate_density(mid_pt[0], mid_pt[1], geometry, params)
+    return max(float(density_to_spacing(eta, params)), 1e-3)
+
+
+def _add_boundary_layer_seed_points(points, geometry, params, plate_poly, keepout_union):
+    """Add a structured point row offset inward from each straight outer edge."""
+    boundary_pts = []
+    ring = LinearRing(geometry['outer_boundary'])
+    is_ccw = bool(ring.is_ccw)
+
+    # Prefer typed segments to avoid treating discretized arcs as straight edges
+    typed = geometry.get('outer_boundary_typed')
+    if typed:
+        segments = [seg for seg in typed if seg.get('type', 'line') == 'line']
+        edge_pairs = [(_np(seg['start']), _np(seg['end'])) for seg in segments]
+    else:
+        coords = np.asarray(geometry['outer_boundary'], dtype=float)
+        if len(coords) >= 2 and np.allclose(coords[0], coords[-1]):
+            coords = coords[:-1]
+        edge_pairs = []
+        for i in range(len(coords)):
+            edge_pairs.append((coords[i], coords[(i + 1) % len(coords)]))
+
+    for a, b in edge_pairs:
+        dx, dy = b[0] - a[0], b[1] - a[1]
+        edge_len = float(np.hypot(dx, dy))
+        if edge_len < 1e-9:
+            continue
+
+        mid = np.array([(a[0] + b[0]) * 0.5, (a[1] + b[1]) * 0.5], dtype=float)
+        spacing = float(density_to_spacing(evaluate_density(mid[0], mid[1], geometry, params), params))
+        spacing = max(spacing, 1e-3)
+        offset = _boundary_layer_offset_for_segment(mid, geometry, params)
+
+        nx_l, ny_l = (-dy / edge_len), (dx / edge_len)
+        nx, ny = (nx_l, ny_l) if is_ccw else (-nx_l, -ny_l)
+
+        n_pts = max(int(np.floor(edge_len / spacing)), 1)
+        for k in range(1, n_pts + 1):
+            t = k / (n_pts + 1)
+            bx = a[0] + t * dx
+            by = a[1] + t * dy
+            px = bx + offset * nx
+            py = by + offset * ny
+            p = Point(px, py)
+            if not plate_poly.buffer(1e-6).contains(p):
+                continue
+            if not keepout_union.is_empty and keepout_union.contains(p):
+                continue
+            boundary_pts.append([px, py])
+
+    if boundary_pts:
+        return np.vstack([points, np.asarray(boundary_pts, dtype=np.float64)])
+    return points
+
+
+def _np(pt):
+    return np.asarray([float(pt[0]), float(pt[1])], dtype=float)
+
+
 def _generate_hex_grid(bbox, base_spacing):
     """
     Generate a regular hexagonal-packed point grid.
@@ -267,6 +332,10 @@ def generate_triangulation(geometry, params, max_refinement_passes=3):
     # Add boundary-conforming vertices and get inset plate polygon for clipping
     all_pts, inner_plate = _add_boundary_vertices(grid_pts, geometry, params, keepout_union)
 
+    # Add structured boundary-layer seed row along straight edges
+    plate_poly = Polygon(geometry['outer_boundary'])
+    all_pts = _add_boundary_layer_seed_points(all_pts, geometry, params, plate_poly, keepout_union)
+
     # Deduplicate close points
     all_pts = np.unique(np.round(all_pts, 4), axis=0)