tyler fixes

gradcheck_nb.py

@@ -127,8 +127,8 @@ def make_structures(params, apply_symmetry: bool = True):
             if apply_symmetry and symmetry[1] != 0 and y0 < -S / 2:
                 continue
 
-            # geometry = td.Box(center=(x0, y0, center_z), size=(size, size, H))
-            geometry = td.Cylinder(center=(x0, y0, center_z), length=H, radius=size / 2)
+            geometry = td.Box(center=(x0, y0, center_z), size=(size, size, H))
+            # geometry = td.Cylinder(center=(x0, y0, center_z), length=H, radius=size / 2)
 
             geometries.append(geometry)
     geo_group = td.GeometryGroup(geometries=geometries)
@@ -235,14 +235,17 @@ def measure_focal_intensity(sim_data: td.SimulationData) -> float:
 
     far_fields = n2f.project_fields(monitor_far)
     # return anp.sum(anp.abs(far_fields.Etheta.values))
-    return abs(far_fields.power.values.item())
+    return far_fields.power.values.item()
 
 
 def J(params) -> float:
     """Objective function, returns intensity at focal point as a function of params."""
     sim = make_sim(params)
+    # sim.plot(z=0)
+    # plt.show()
+    # exit()
     # sim = make_sim(np.zeros(x_centers.shape))
-    sim_data = run_adj(sim, task_name="metalens_invdes", verbose=True)
+    sim_data = run_adj(sim, task_name="metalens_invdes_dbg", verbose=True)
     # sim_data = make_sim_data(params, fp="simulation_data.hdf5")
     # sim_data = td.SimulationData.from_file("simulation_data.hdf5")
     return measure_focal_intensity(sim_data)
@@ -255,7 +258,9 @@ def J(params) -> float:
 # # print(J(params0))
 dJ = ag.value_and_grad(J)
 val, grad = dJ(params0)
-print(val, grad)
+print("val: ", val)
+print("grad: ", grad)
+print("|grad|: ", np.linalg.norm(grad))
 # exit()
 
 # check_grads(J, modes=["rev"], order=1)(params0)
@@ -296,7 +301,7 @@ def J_normalized(params):
     print(f"\tgrad_norm = {np.linalg.norm(gradient):.4e}")
 
     # compute and apply updates to the optimizer based on gradient (-1 sign to maximize obj_fn)
-    updates, opt_state = optimizer.update(gradient, opt_state, params)
+    updates, opt_state = optimizer.update(-gradient, opt_state, params)
     params = optax.apply_updates(params, updates)
     params = np.array(params)
 

tidy3d/components/data/monitor_data.py

@@ -1098,7 +1098,7 @@ def shift_value(coords) -> float:
             for name, field_component in self.field_components.items():
                 field_component = field_component.sel(f=freq0)
                 forward_amps = field_component.values
-                values = -1j * forward_amps
+                values = np.conj(forward_amps)
                 if "H" in name:
                     values *= -1
                 coords = dict(field_component.coords.copy())

tidy3d/web/api/autograd/autograd.py

@@ -732,9 +732,6 @@ def setup_adj(
     td.log.info("Running custom vjp (adjoint) pipeline.")
 
     # immediately filter out any data_vjps with all 0's in the data
-    # data_fields_vjp = {
-    #     key: get_static(value) for key, value in data_fields_vjp.items() if not np.all(value == 0.0)
-    # }
     data_fields_vjp = {key: get_static(value) for key, value in data_fields_vjp.items()}
 
     # insert the raw VJP data into the .data of the original SimulationData