tidy3d.CustomFieldSource

class CustomFieldSource

Bases: FieldSource, PlanarSource

Implements a source corresponding to an input dataset containing E and H fields, using the equivalence principle to define the actual injected currents.

Parameters:

• name (Optional[str] = None) – Optional name for the source.

• center (Tuple[float, float, float] = (0.0, 0.0, 0.0)) – [units = um]. Center of object in x, y, and z.

• size (Tuple[NonNegativeFloat, NonNegativeFloat, NonNegativeFloat]) – [units = um]. Size in x, y, and z directions.

• source_time (Union[GaussianPulse, ContinuousWave, CustomSourceTime]) – Specification of the source time-dependence.

• field_dataset (Optional[FieldDataset]) –

  FieldDataset containing the desired frequency-domain fields patterns to inject. At least one tangential field component must be specified.

  Notes

  For the injection to work as expected (i.e. to reproduce the required E and H fields), the field data must decay by the edges of the source plane, or the source plane must span the entire simulation domain and the fields must match the simulation boundary conditions.

  The equivalent source currents are fully defined by the field components tangential to the source plane. For e.g. source normal along z, the normal components (Ez and Hz) can be provided but will have no effect on the results, and at least one of the tangential components has to be in the dataset, i.e. at least one of Ex, Ey, Hx, and Hy.

  If the data is not coming from a tidy3d simulation, the normalization is likely going to be arbitrary and the directionality of the source will likely not be perfect, even if both the E and H fields are provided. An empty normalizing run may be needed to accurately normalize results.

  The coordinates of all provided fields are assumed to be relative to the source center. If only the E or only the H fields are provided, the source will not be directional, but will inject equal power in both directions instead.

Example

>>> from tidy3d import ScalarFieldDataArray
>>> pulse = GaussianPulse(freq0=200e12, fwidth=20e12)
>>> x = np.linspace(-1, 1, 101)
>>> y = np.linspace(-1, 1, 101)
>>> z = np.array([0])
>>> f = [2e14]
>>> coords = dict(x=x, y=y, z=z, f=f)
>>> scalar_field = ScalarFieldDataArray(np.ones((101, 101, 1, 1)), coords=coords)
>>> dataset = FieldDataset(Ex=scalar_field)
>>> custom_source = CustomFieldSource(
...     center=(1, 1, 1),
...     size=(2, 2, 0),
...     source_time=pulse,
...     field_dataset=dataset)

See also

Notebooks

• Defining spatially-varying sources

Attributes

Methods

field_dataset

__hash__()

Hash method.