flex_rf.tidy3d.SimulationData

Type: class │ Base(s): AbstractYeeGridSimulationData

Description

Stores data from a collection of Monitor objects in a Simulation.

Notes

The SimulationData objects store a copy of the original Simulation:, so it can be recovered if the SimulationData is loaded in a new session and the Simulation is no longer in memory.

More importantly, the SimulationData contains a reference to the data for each of the monitors within the original Simulation. This data can be accessed directly using the name given to the monitors initially.

Example(s)

Standalone example:

import tidy3d as td
num_modes = 5
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 = td.Grid(boundaries=td.Coords(x=x, y=y, z=z))
scalar_field = td.ScalarFieldDataArray((1+1j) * np.random.random((2,3,4,2)), coords=coords)
field_monitor = td.FieldMonitor(
    size=(2,4,6),
    freqs=[2e14, 3e14],
    name='field',
    fields=['Ex'],
    colocate=True,
)
sim = td.Simulation(
    size=(2, 4, 6),
    grid_spec=td.GridSpec(wavelength=1.0),
    monitors=[field_monitor],
    run_time=2e-12,
    sources=[
        td.UniformCurrentSource(
            size=(0, 0, 0),
            center=(0, 0.5, 0),
            polarization="Hx",
            source_time=td.GaussianPulse(
                freq0=2e14,
                fwidth=4e13,
            ),
            current_amplitude_definition="total",
        )
    ],
)
field_data = td.FieldData(monitor=field_monitor, Ex=scalar_field, grid_expanded=grid)
sim_data = td.SimulationData(simulation=sim, data=(field_data,))

To save and load the SimulationData object.

sim_data.to_file(fname='path/to/file.hdf5') # Save a SimulationData object to a HDF5 file
sim_data = SimulationData.from_file(fname='path/to/file.hdf5') # Load a SimulationData object from a HDF5 file.

Optionally, the simulation data can be loaded in a lazy mode, which only holds a reference until a field is accessed or a method is applied. This is useful to save I/O operations and memory.

sim_data = SimulationData.from_file(fname='path/to/file.hdf5', lazy=True) # Does not contain data until accessed.

Parameters

simulation [Simulation]

Original Simulation associated with the data.

data [tuple[discriminated_union(MonitorDataType), ...]]

List of MonitorData instances associated with the monitors of the original Simulation.

log [str | None] = None

A string containing the log information from the simulation run.

diverged [bool] = False

A boolean flag denoting whether the simulation run diverged.

Attributes

final_decay_value [float]

Returns value of the field decay at the final time step.

Methods

field_decay()

Returns a TimeDataArray of field decay values over time steps.

renormalize(normalize_index: int)

Return a copy of the SimulationData with a different source used for the normalization.

source_spectrum(source_index: int)

Get a spectrum normalization function for a given source index.