Warning if a nonuniform custom medium is intersecting certain sources and monitors

CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 - Support for `.gz` files in `Simulation` version updater.
+- Warning if a nonuniform custom medium is intersecting `PlaneWave`, `GaussianBeam`, `AstigmaticGaussianBeam`, `FieldProjectionCartesianMonitor`, `FieldProjectionAngleMonitor`, `FieldProjectionKSpaceMonitor`, and `DiffractionMonitor`.
 
 ### Changed
 

tests/test_components/test_custom.py

@@ -64,12 +64,16 @@ def make_custom_current_source():
     return td.CustomCurrentSource(size=SIZE, source_time=ST, current_dataset=current_dataset)
 
 
-def make_spatial_data(value=0, dx=0, unstructured=False, seed=None):
+def make_spatial_data(value=0, dx=0, unstructured=False, seed=None, uniform=False):
     """Makes a spatial data array."""
-    data = np.random.random((Nx, Ny, Nz)) + value
+    if uniform:
+        data = value * np.ones((Nx, Ny, Nz))
+    else:
+        data = np.random.random((Nx, Ny, Nz)) + value
     arr = td.SpatialDataArray(data, coords=dict(x=X + dx, y=Y, z=Z))
     if unstructured:
-        return cartesian_to_unstructured(arr, seed=seed)
+        method = "direct" if uniform else "linear"
+        return cartesian_to_unstructured(arr, seed=seed, method=method)
     return arr
 
 
@@ -634,12 +638,21 @@ def test_custom_isotropic_medium(unstructured):
         mat = CustomMedium(permittivity=permittivity, conductivity=sigmatmp)
     mat = CustomMedium(permittivity=permittivity, conductivity=sigmatmp, allow_gain=True)
     verify_custom_medium_methods(mat, ["permittivity", "conductivity"])
+    assert not mat.is_spatially_uniform
 
     # inconsistent coords
     with pytest.raises(pydantic.ValidationError):
         sigmatmp = make_spatial_data(value=0, dx=1, unstructured=unstructured, seed=seed)
         mat = CustomMedium(permittivity=permittivity, conductivity=sigmatmp)
 
+    # uniform
+    permittivity = make_spatial_data(value=1, unstructured=unstructured, seed=seed, uniform=True)
+    mat = CustomMedium(permittivity=permittivity)
+    assert mat.is_spatially_uniform
+
+    mat = CustomAnisotropicMedium(xx=mat, yy=mat, zz=mat)
+    assert mat.is_spatially_uniform
+
 
 def verify_custom_dispersive_medium_methods(mat, reduced_fields=[]):
     """Verify that the methods in custom dispersive medium is producing expected results."""
@@ -709,6 +722,7 @@ def test_custom_pole_residue(unstructured):
     mat = CustomPoleResidue(eps_inf=eps_inf, poles=((a, c),))
     verify_custom_dispersive_medium_methods(mat, ["eps_inf", "poles"])
     assert mat.n_cfl > 1
+    assert not mat.is_spatially_uniform
 
     # to custom non-dispersive medium
     # dispersive failure
@@ -775,6 +789,7 @@ def test_custom_sellmeier(unstructured):
     mat = CustomSellmeier(coeffs=((b1, c1), (b2, c2)))
     verify_custom_dispersive_medium_methods(mat, ["coeffs"])
     assert mat.n_cfl == 1
+    assert not mat.is_spatially_uniform
 
     # from dispersion
     n = make_spatial_data(value=2, unstructured=unstructured, seed=seed)
@@ -839,6 +854,7 @@ def test_custom_lorentz(unstructured):
     verify_custom_dispersive_medium_methods(mat, ["eps_inf", "coeffs"])
     assert mat.n_cfl > 1
     assert mat.pole_residue.subpixel
+    assert not mat.is_spatially_uniform
 
 
 @pytest.mark.parametrize("unstructured", [False, True])
@@ -876,6 +892,7 @@ def test_custom_drude(unstructured):
     mat = CustomDrude(eps_inf=eps_inf, coeffs=((f1, delta1), (f2, delta2)))
     verify_custom_dispersive_medium_methods(mat, ["eps_inf", "coeffs"])
     assert mat.n_cfl > 1
+    assert not mat.is_spatially_uniform
 
 
 @pytest.mark.parametrize("unstructured", [False, True])
@@ -926,6 +943,7 @@ def test_custom_debye(unstructured):
     mat = CustomDebye(eps_inf=eps_inf, coeffs=((eps1, tau1), (eps2, tau2)))
     verify_custom_dispersive_medium_methods(mat, ["eps_inf", "coeffs"])
     assert mat.n_cfl > 1
+    assert not mat.is_spatially_uniform
 
 
 @pytest.mark.parametrize("unstructured", [True])
@@ -957,6 +975,7 @@ def test_custom_anisotropic_medium(log_capture, unstructured):
     # anisotropic
     mat = CustomAnisotropicMedium(xx=mat_xx, yy=mat_yy, zz=mat_zz)
     verify_custom_medium_methods(mat)
+    assert not mat.is_spatially_uniform
 
     mat = CustomAnisotropicMedium(xx=mat_xx, yy=mat_yy, zz=mat_zz, subpixel=True)
     assert_log_level(log_capture, "WARNING")
@@ -1075,3 +1094,86 @@ def test_io_dispersive(tmp_path, unstructured, z_custom):
     sim_load = td.Simulation.from_file(filename)
 
     assert sim_load == sim
+
+
+def test_warn_planewave_intersection(log_capture):
+    """Warn that if a nonuniform custom medium is intersecting PlaneWave source."""
+    src = td.PlaneWave(
+        source_time=td.GaussianPulse(freq0=3e14, fwidth=1e13),
+        center=(0, 0, 0),
+        size=(td.inf, td.inf, 0),
+        direction="+",
+    )
+
+    # uniform custom medium
+    permittivity = make_spatial_data(value=1, unstructured=False, seed=0, uniform=True)
+    mat = CustomMedium(permittivity=permittivity)
+    box = td.Structure(
+        geometry=td.Box(size=(td.inf, td.inf, 1)),
+        medium=mat,
+    )
+
+    sim = td.Simulation(
+        size=(1, 1, 2),
+        structures=[box],
+        grid_spec=td.GridSpec.auto(wavelength=1),
+        sources=[src],
+        run_time=1e-12,
+        boundary_spec=td.BoundarySpec.all_sides(boundary=td.Periodic()),
+    )
+    assert_log_level(log_capture, None)
+
+    # nonuniform custom medium
+    permittivity = make_spatial_data(value=1, unstructured=False, seed=0, uniform=False)
+    mat = CustomMedium(permittivity=permittivity)
+    box = td.Structure(
+        geometry=td.Box(size=(td.inf, td.inf, 1)),
+        medium=mat,
+    )
+    sim.updated_copy(structures=[box])
+    assert_log_level(log_capture, "WARNING")
+
+
+def test_warn_diffraction_monitor_intersection(log_capture):
+    """Warn that if a nonuniform custom medium is intersecting Diffraction Monitor."""
+    src = td.PointDipole(
+        source_time=td.GaussianPulse(freq0=2.5e14, fwidth=1e13),
+        center=(0, 0, 0.6),
+        polarization="Ex",
+    )
+    monitor = td.DiffractionMonitor(
+        center=(0, 0, 0),
+        size=(td.inf, td.inf, 0),
+        freqs=[250e12],
+        name="monitor_diffraction",
+        normal_dir="+",
+    )
+
+    # uniform custom medium
+    permittivity = make_spatial_data(value=1, unstructured=False, seed=0, uniform=True)
+    mat = CustomMedium(permittivity=permittivity)
+    box = td.Structure(
+        geometry=td.Box(size=(td.inf, td.inf, 1)),
+        medium=mat,
+    )
+
+    sim = td.Simulation(
+        size=(1, 1, 2),
+        structures=[box],
+        grid_spec=td.GridSpec.auto(wavelength=1),
+        monitors=[monitor],
+        sources=[src],
+        run_time=1e-12,
+        boundary_spec=td.BoundarySpec.all_sides(boundary=td.Periodic()),
+    )
+    assert_log_level(log_capture, None)
+
+    # nonuniform custom medium
+    permittivity = make_spatial_data(value=1, unstructured=False, seed=0, uniform=False)
+    mat = CustomMedium(permittivity=permittivity)
+    box = td.Structure(
+        geometry=td.Box(size=(td.inf, td.inf, 1)),
+        medium=mat,
+    )
+    sim.updated_copy(structures=[box])
+    assert_log_level(log_capture, "WARNING")

tests/test_data/test_data_arrays.py

@@ -381,3 +381,25 @@ def test_sel_inside(nx):
 
     with pytest.raises(DataError):
         _ = arr.does_cover([[0.1, 3, 2], [1, 2.5, 2]])
+
+
+def test_uniform_check():
+    """check if each element in the array is of equal value."""
+    arr = td.SpatialDataArray(
+        np.ones((2, 2, 2), dtype=np.complex128),
+        coords=dict(x=[0, 1], y=[1, 2], z=[2, 3]),
+    )
+    assert arr.is_uniform
+
+    # small variation is still considered as uniform
+    arr = td.SpatialDataArray(
+        np.ones((2, 2, 2)) + np.random.random((2, 2, 2)) * 1e-6,
+        coords=dict(x=[0, 1], y=[1, 2], z=[2, 3]),
+    )
+    assert arr.is_uniform
+
+    arr = td.SpatialDataArray(
+        np.ones((2, 2, 2)) + np.random.random((2, 2, 2)) * 1e-4,
+        coords=dict(x=[0, 1], y=[1, 2], z=[2, 3]),
+    )
+    assert not arr.is_uniform

tests/test_data/test_datasets.py

@@ -39,7 +39,7 @@ def test_triangular_dataset(log_capture, tmp_path, ds_name, no_vtk=False):
         cells=tri_grid_cells,
         values=tri_grid_values,
     )
-
+    assert not tri_grid.is_uniform
     # test name redirect
     assert tri_grid.name == ds_name
 
@@ -594,3 +594,32 @@ def test_cartesian_to_unstructured(nz, use_vtk, fill_value):
         assert sample_outside.values.item() == values[0, 0, 0]
     else:
         assert sample_outside.values.item() == fill_value
+
+
+def test_triangular_dataset_uniform():
+    import tidy3d as td
+
+    # basic create
+    tri_grid_points = td.PointDataArray(
+        [[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]],
+        dims=("index", "axis"),
+    )
+
+    tri_grid_cells = td.CellDataArray(
+        [[0, 1, 2], [1, 2, 3]],
+        dims=("cell_index", "vertex_index"),
+    )
+
+    tri_grid_values = td.IndexedDataArray(
+        [1.0, 1.0, 1.0, 1.0],
+        dims=("index"),
+    )
+
+    tri_grid = td.TriangularGridDataset(
+        normal_axis=1,
+        normal_pos=0,
+        points=tri_grid_points,
+        cells=tri_grid_cells,
+        values=tri_grid_values,
+    )
+    assert tri_grid.is_uniform

tidy3d/components/data/data_array.py

@@ -144,6 +144,12 @@ def abs(self):
         """Absolute value of data array."""
         return abs(self)
 
+    @property
+    def is_uniform(self):
+        """Whether each element is of equal value in the data array"""
+        raw_data = self.data.ravel()
+        return np.allclose(raw_data, raw_data[0])
+
     def to_hdf5(self, fname: Union[str, h5py.File], group_path: str) -> None:
         """Save an xr.DataArray to the hdf5 file or file handle with a given path to the group."""
 

tidy3d/components/data/dataset.py

@@ -563,6 +563,11 @@ def points_right_dims(cls, val):
             )
         return val
 
+    @property
+    def is_uniform(self):
+        """Whether each element is of equal value in ``values``."""
+        return self.values.is_uniform
+
     @pd.validator("points", always=True)
     def points_right_indexing(cls, val):
         """Check that points are indexed corrrectly."""