tidy3d.PermittivityData

class PermittivityData

Bases: PermittivityDataset, AbstractFieldData

Data for a PermittivityMonitor: diagonal components of the permittivity tensor.

Parameters:

• monitor (PermittivityMonitor) – Permittivity monitor associated with the data.

• symmetry (Tuple[Literal[0, -1, 1], Literal[0, -1, 1], Literal[0, -1, 1]] = (0, 0, 0)) – Symmetry eigenvalues of the original simulation in x, y, and z.

• symmetry_center (Optional[Tuple[float, float, float]] = None) – Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the symmetry field are non-zero.

• grid_expanded (Optional[Grid] = None) – Grid discretization of the associated monitor in the simulation which created the data. Required if symmetries are present, as well as in order to use some functionalities like getting Poynting vector and flux.

• eps_xx (ScalarFieldDataArray) – Spatial distribution of the xx-component of the relative permittivity.

• eps_yy (ScalarFieldDataArray) – Spatial distribution of the yy-component of the relative permittivity.

• eps_zz (ScalarFieldDataArray) – Spatial distribution of the zz-component of the relative permittivity.

Notes

The data is stored as a DataArray object using the xarray package.

Example

>>> from tidy3d import ScalarFieldDataArray
>>> x = [-1,1,3]
>>> y = [-2,0,2,4]
>>> z = [-3,-1,1,3,5]
>>> f = [2e14, 3e14]
>>> coords = dict(x=x[:-1], y=y[:-1], z=z[:-1], f=f)
>>> grid = Grid(boundaries=Coords(x=x, y=y, z=z))
>>> sclr_fld = ScalarFieldDataArray((1+1j) * np.random.random((2,3,4,2)), coords=coords)
>>> monitor = PermittivityMonitor(size=(2,4,6), freqs=[2e14, 3e14], name='eps')
>>> data = PermittivityData(
...     monitor=monitor, eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld, grid_expanded=grid
... )

Attributes

Methods

monitor

__hash__()

Hash method.