fix polyslab autograd when sidewall_angle or dilation

CHANGELOG.md

@@ -17,6 +17,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Bug where boundary layers would be plotted too small in 2D simulations.
 - Bug when plotting transformed geometries.
 - Bug when snapping `CoaxialLumpedPort` to grid cell boundaries.
+- Errors in `PolySlab` when using autograd differentiation with `sidewall_angle` and `dilation`.
 
 ## [2.7.0] - 2024-06-17
 

tests/test_components/test_autograd.py

@@ -239,6 +239,8 @@ def make_structures(params: anp.ndarray) -> dict[str, td.Structure]:
             vertices=vertices,
             slab_bounds=(-0.5, 0.5),
             axis=1,
+            sidewall_angle=0.01,
+            dilation=0.01,
         ),
         medium=med,
     )

tidy3d/components/geometry/polyslab.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+from copy import copy
 from math import isclose
 from typing import List, Tuple
 
@@ -1249,9 +1250,9 @@ def cross(u, v):
         def normalize(v):
             return v / np.linalg.norm(v, axis=0)
 
-        vs_orig = vertices.T.copy()
-        vs_next = np.roll(vs_orig.copy(), axis=-1, shift=-1)
-        vs_previous = np.roll(vs_orig.copy(), axis=-1, shift=+1)
+        vs_orig = copy(vertices.T)
+        vs_next = np.roll(copy(vs_orig), axis=-1, shift=-1)
+        vs_previous = np.roll(copy(vs_orig), axis=-1, shift=+1)
 
         asp = normalize(vs_next - vs_orig)
         asm = normalize(vs_orig - vs_previous)
@@ -1289,14 +1290,14 @@ def _edge_length_and_reduction_rate(vertices: np.ndarray) -> Tuple[np.ndarray, n
         """
 
         # edge length
-        vs_orig = vertices.T.copy()
-        vs_next = np.roll(vs_orig.copy(), axis=-1, shift=-1)
+        vs_orig = copy(vertices.T)
+        vs_next = np.roll(copy(vs_orig), axis=-1, shift=-1)
         edge_length = np.linalg.norm(vs_next - vs_orig, axis=0)
 
         # edge length remaining
         dist = 1
         parallel_shift = PolySlab._shift_vertices(vertices, dist)[1]
-        parallel_shift_p = np.roll(parallel_shift.copy(), shift=-1)
+        parallel_shift_p = np.roll(copy(parallel_shift), shift=-1)
         edge_reduction = -(parallel_shift + parallel_shift_p)
         return edge_length, edge_reduction