TimeDomainModel¶

class photonforge.TimeDomainModel(pole_residue_matrix, time_step)¶

Time-domain model based on a pole-residue representation of an S matrix.

Parameters:

pole_residue_matrix (PoleResidueMatrix) – Underlying pole-residue matrix.
time_step (float) – Time step to be used for this model.

Example

>>> pole_res = pf.PoleResidueMatrix(
...     poles=[-pf.C_0 / 1.0],
...     residues={("P0", "P0"): [2.0 * pf.C_0, 0.0]},
... )
>>> time_domain = pf.TimeDomainModel(pole_res, time_step=0.001)

Note

Time-domain models cannot be added to components at the moment. Component models are only those used to compute frequency-domain S parameters.

Methods

`copy`()	Create a copy of this time-domain model.
`reset`()	Reset the internal model state.
`step`([inputs, steps, time_step, show_progress])	Compute the outputs for multiple time steps.
`step_single`(inputs, outputs[, time_index, ...])	Compute the output for a single time step using array-based API.

Attributes

`keys`	input/output array keys (read only).
`pole_residue_matrix`	Underlying pole-residue matrix (read only).
`properties`	Object properties.
`time_step`	Time step.

copy()¶

Create a copy of this time-domain model.

Returns:: New copy.
Return type:: TimeDomainModel

keys¶

input/output array keys (read only).

Type:: tuple[str]

pole_residue_matrix¶

Underlying pole-residue matrix (read only).

Type:: PoleResidueMatrix

properties¶

Object properties.

Type:: Properties

reset()¶

Reset the internal model state.

Returns:: This object.
Return type:: TimeDomainModel

step(inputs=None, steps=0, time_step=0, show_progress=True)¶

Compute the outputs for multiple time steps.

Note

This method is not thread-safe. Do not call step concurrently from multiple threads on the same TimeDomainModel instance. For parallel simulations, create separate model instances (e.g., via copy()) for each thread.

Parameters:

inputs (TimeSeries | None) – Inputs to the time domain model. If None, uses zero inputs for steps time steps.
steps (int) – The number of time steps to execute. Only used if inputs is None.
time_step (float) – The interval between time steps (in seconds). Only used if inputs is None. Must match the model’s time_step attribute.
show_progress (bool) – If True, show computation progress.

Returns:

Computed outputs.

Return type:

TimeSeries

step_single(inputs, outputs, time_index=0, update_state=True, shutdown=False)¶

Compute the output for a single time step using array-based API.

Note

This method is not thread-safe. Do not call it concurrently from multiple threads on the same TimeDomainModel instance, even with update_state=False. For parallel simulations, create a separate model instance (e.g., via copy()) for each thread.

Parameters:

inputs (ndarray) – Input values at the current time step. Must be a contiguous 1D array of complex values ordered according to keys.
outputs (ndarray) – Pre-allocated output array where results will be stored. Same size and type as inputs.
time_index (int) – Time series index for the current input. Not used.
update_state (bool) – Whether to update the internal model state.
shutdown (bool) – Whether this is the last call. Not used.

Returns:

None. Results are written in-place to the outputs array.

time_step¶

Time step.

Type:: float