tidy3d.FieldTimeData#
- class FieldTimeData[source]#
Bases:
FieldTimeDataset,ElectromagneticFieldDataData associated with a
FieldTimeMonitor: scalar components of E and H fields.- Parameters:
Ex (Attribute:
Ex) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the x-component of the electric field.
Ey (Attribute:
Ey) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the y-component of the electric field.
Ez (Attribute:
Ez) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the z-component of the electric field.
Hx (Attribute:
Hx) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the x-component of the magnetic field.
Hy (Attribute:
Hy) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the y-component of the magnetic field.
Hz (Attribute:
Hz) βTypeOptional[ScalarFieldTimeDataArray]
Default= None
DescriptionSpatial distribution of the z-component of the magnetic field.
monitor (Attribute:
monitor) βTypeFieldTimeMonitor
DefaultDescriptionTime-domain field monitor associated with the data.
symmetry (Attribute:
symmetry) βTypeTuple[Literal[0, -1, 1], Literal[0, -1, 1], Literal[0, -1, 1]]
Default= (0, 0, 0)
DescriptionSymmetry eigenvalues of the original simulation in x, y, and z.
symmetry_center (Attribute:
symmetry_center) βTypeOptional[Tuple[float, float, float]]
Default= None
DescriptionCenter of the symmetry planes of the original simulation in x, y, and z. Required only if any of the
symmetryfield are non-zero.grid_expanded (Attribute:
grid_expanded) βTypeOptional[Grid]
Default= None
DescriptionGriddiscretization 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 and flux.grid_primal_correction (Attribute:
grid_primal_correction) βTypeUnion[float, FreqDataArray, TimeDataArray, FreqModeDataArray]
Default= 1.0
DescriptionCorrection factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the primal grid locations along the normal direction.
grid_dual_correction (Attribute:
grid_dual_correction) βTypeUnion[float, FreqDataArray, TimeDataArray, FreqModeDataArray]
Default= 1.0
DescriptionCorrection factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the dual grid locations along the normal direction.
Notes
The data is stored as a DataArray object using the xarray package.
Example
>>> from tidy3d import ScalarFieldTimeDataArray >>> x = [-1,1,3] >>> y = [-2,0,2,4] >>> z = [-3,-1,1,3,5] >>> t = [0, 1e-12, 2e-12] >>> coords = dict(x=x[:-1], y=y[:-1], z=z[:-1], t=t) >>> grid = Grid(boundaries=Coords(x=x, y=y, z=z)) >>> scalar_field = ScalarFieldTimeDataArray(np.random.random((2,3,4,3)), coords=coords) >>> monitor = FieldTimeMonitor( ... size=(2,4,6), interval=100, name='field', fields=['Ex', 'Hz'], colocate=True ... ) >>> data = FieldTimeData(monitor=monitor, Ex=scalar_field, Hz=scalar_field, grid_expanded=grid)
Attributes
Flux for data corresponding to a 2D monitor.
Instantaneous Poynting vector for time-domain data associated to a 2D monitor, projected to the direction normal to the monitor plane.
Make a copy of the data with time-reversed fields.
Methods
dot(field_data[,Β conjugate])Inner product is not defined for time-domain data.
- monitor#
- property poynting#
Instantaneous Poynting vector for time-domain data associated to a 2D monitor, projected to the direction normal to the monitor plane.
- property flux#
Flux for data corresponding to a 2D monitor.
- property time_reversed_copy#
Make a copy of the data with time-reversed fields. The sign of the magnetic fields is flipped, and the data is reversed along the
tdimension, such that for a given field,field[t_beg + t] -> field[t_end - t], wheret_begandt_endare the first and last coordinates along thetdimension.
- __hash__()#
Hash method.