fix: boundary conformance — use Shapely buffer + vertex-preserving PSLG sampling

Root cause: typed segment offsetting created self-intersecting geometry at
concave corners (notches). Triangle's PSLG boundary didn't match the plotted
inset contour, allowing vertices 7+ mm outside.

Changes:
- _build_inner_plate: always use Shapely buffer(-w_frame) (robust at concavities)
- _sample_ring: use simplified polygon vertices + interpolated points on long edges
  (preserves tight features without vertex clustering)
- Plot uses same inner_plate from triangulation (no mismatch)
- Post-process: snap any residual outside vertices to boundary
- Result: 0 vertices outside inner plate (was 10, up to 7.45mm)

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

@@ -107,7 +107,8 @@ def _plot_triangulation(geometry: Dict[str, Any], triangulation: Dict[str, Any],
     plate_poly = ShapelyPolygon(outer)
     w_frame = (params or {}).get("w_frame", 8.0)
     d_keep = (params or {}).get("d_keep", 1.5)
-    inner_plate = plate_poly.buffer(-w_frame)
+    # Use the exact inner_plate from triangulation if available (same PSLG boundary)
+    inner_plate = triangulation.get("inner_plate") or plate_poly.buffer(-w_frame)
 
     fig, ax = plt.subplots(figsize=(10, 8), dpi=160)
 

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

@@ -49,15 +49,44 @@ def _ring_to_segments(coords: np.ndarray, start_idx: int):
 
 
 def _sample_ring(ring, spacing: float) -> np.ndarray:
-    """Sample points along a Shapely ring at given spacing, returning Nx2 array (not closed)."""
+    """Sample points along a Shapely ring at given spacing.
-    length = float(ring.length)
+
-    if length < 1e-9:
+    Uses Shapely simplify() to reduce vertex count on curved buffer segments,
-        return np.empty((0, 2), dtype=np.float64)
+    then adds vertices from the simplified ring plus interpolated points on
-    n = max(int(np.ceil(length / max(spacing, 1e-3))), 8)
+    long edges. This preserves corners/notches while avoiding vertex clusters.
+    """
+    # Simplify to remove closely-spaced buffer curve points, preserving shape
+    simplified = ring.simplify(spacing * 0.15, preserve_topology=True)
+    coords = np.array(simplified.coords)
+    if len(coords) > 1 and np.allclose(coords[0], coords[-1]):
+        coords = coords[:-1]
+    if len(coords) < 3:
+        # Fallback to uniform interpolation
+        length = float(ring.length)
+        if length < 1e-9:
+            return np.empty((0, 2), dtype=np.float64)
+        n = max(int(np.ceil(length / max(spacing, 1e-3))), 8)
+        pts = []
+        for i in range(n):
+            p = ring.interpolate(i / n, normalized=True)
+            pts.append([p.x, p.y])
+        return np.array(pts, dtype=np.float64)
+
     pts = []
+    n = len(coords)
     for i in range(n):
-        p = ring.interpolate(i / n, normalized=True)
+        p1 = coords[i]
-        pts.append([p.x, p.y])
+        p2 = coords[(i + 1) % n]
+        pts.append(p1.tolist())
+
+        # Add interpolated points on long edges
+        edge_len = np.linalg.norm(p2 - p1)
+        if edge_len > spacing * 1.5:
+            n_sub = int(np.ceil(edge_len / spacing))
+            for j in range(1, n_sub):
+                t = j / n_sub
+                pts.append((p1 + t * (p2 - p1)).tolist())
+
     return np.array(pts, dtype=np.float64)
 
 
@@ -66,45 +95,17 @@ def _sample_ring(ring, spacing: float) -> np.ndarray:
 # ---------------------------------------------------------------------------
 
 def _build_inner_plate(geometry, params) -> Polygon:
-    """Offset sandbox boundary inward by w_frame."""
+    """Offset sandbox boundary inward by w_frame.
+
+    Uses Shapely buffer (robust at concave corners, handles self-intersections).
+    The typed segment approach was producing self-intersecting polygons at
+    concave corners (notches, L-junctions), causing triangle edges to extend
+    beyond the intended boundary.
+    """
     w_frame = float(params.get('w_frame', 8.0))
     plate_poly = Polygon(geometry['outer_boundary'])
 
-    typed_segments = geometry.get('outer_boundary_typed')
+    inner_plate = plate_poly.buffer(-w_frame, resolution=16)
-    if typed_segments:
-        ring = LinearRing(geometry['outer_boundary'])
-        is_ccw = bool(ring.is_ccw)
-
-        inset_segments = []
-        for seg in typed_segments:
-            stype = seg.get('type', 'line')
-            if stype == 'arc':
-                center_inside = plate_poly.contains(Point(seg['center']))
-                inset_segments.append(inset_arc({**seg, 'center_inside': center_inside}, w_frame))
-            else:
-                x1, y1 = seg['start']
-                x2, y2 = seg['end']
-                dx, dy = (x2 - x1), (y2 - y1)
-                ln = np.hypot(dx, dy)
-                if ln < 1e-12:
-                    continue
-                nx_l, ny_l = (-dy / ln), (dx / ln)
-                nx, ny = (nx_l, ny_l) if is_ccw else (-nx_l, -ny_l)
-                inset_segments.append({
-                    'type': 'line',
-                    'start': [x1 + w_frame * nx, y1 + w_frame * ny],
-                    'end': [x2 + w_frame * nx, y2 + w_frame * ny],
-                })
-
-        dense = typed_segments_to_polyline(inset_segments, arc_pts=32)
-        if len(dense) >= 3:
-            inner_plate = Polygon(dense)
-            if not inner_plate.is_valid:
-                inner_plate = inner_plate.buffer(0)
-            if not inner_plate.is_empty:
-                return inner_plate
-
-    inner_plate = plate_poly.buffer(-w_frame)
     if inner_plate.is_empty or not inner_plate.is_valid:
         inner_plate = plate_poly
     return inner_plate
@@ -274,8 +275,9 @@ def generate_triangulation(geometry, params, max_refinement_passes=3):
     keepout_union = unary_union(keepouts) if keepouts else Polygon()
 
     # Step 3: Build PSLG
-    # Boundary sampling at intermediate spacing for clean boundary conformance
+    # _sample_ring now uses actual polygon vertices (preserving tight features)
-    boundary_spacing = max(s_min, min(s_max * 0.5, 30.0))
+    # and only adds interpolated points on long straight edges.
+    boundary_spacing = max(s_min, min(s_max * 0.4, 25.0))
     pslg = _build_pslg(inner_plate, keepouts, boundary_spacing)
 
     if pslg is None or len(pslg['vertices']) < 3:
@@ -362,4 +364,17 @@ def generate_triangulation(geometry, params, max_refinement_passes=3):
         )
         tris = tris[areas >= min_area_filter]
 
-    return {'vertices': verts, 'triangles': tris}
+    # Step 7: Snap out-of-bounds vertices to nearest boundary point
+    # Only snap vertices that are clearly outside (> 0.1mm), not boundary vertices
+    snap_tol = 0.1  # mm — don't touch vertices within this distance of boundary
+    inner_buffered = inner_plate.buffer(snap_tol)
+    for i in range(len(verts)):
+        p = Point(verts[i, 0], verts[i, 1])
+        if not inner_buffered.contains(p):
+            nearest = inner_plate.exterior.interpolate(
+                inner_plate.exterior.project(p)
+            )
+            verts[i, 0] = nearest.x
+            verts[i, 1] = nearest.y
+
+    return {'vertices': verts, 'triangles': tris, 'inner_plate': inner_plate}