fdtdx.ArrayContainer

class fdtdx.ArrayContainer(fields, alpha, kappa, sigma, inv_permittivities, inv_permeabilities, detector_states, recording_state, electric_conductivity=None, magnetic_conductivity=None, dispersive_P_curr=None, dispersive_P_prev=None, dispersive_c1=None, dispersive_c2=None, dispersive_c3=None, dispersive_inv_c2=None)

Bases: TreeClass

Container for simulation field arrays and states.

This class holds the electromagnetic field arrays and various state information needed during FDTD simulation. It includes the E and H fields, material properties, and states for boundaries, detectors and recordings.

Quick Reference

Attributes

• alpha

• detector_states

• dispersive_P_curr

• dispersive_P_prev

• dispersive_c1

• dispersive_c2

• dispersive_c3

• dispersive_inv_c2

• electric_conductivity

• fields

• inv_permeabilities

• inv_permittivities

• kappa

• magnetic_conductivity

• recording_state

• sigma

Methods

• aset

• get_class_fields

• get_public_fields

• reset

Attributes

ArrayContainer.alpha: Array

Alpha array for PML calculations.

ArrayContainer.detector_states: dict[str, dict[str, Array]]

Dictionary mapping detector names to their states.

ArrayContainer.dispersive_P_curr: Array | None

Dispersive ADE polarization state at time step n. Shape (num_poles, 3, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.dispersive_P_prev: Array | None

Dispersive ADE polarization state at time step n-1. Shape (num_poles, 3, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.dispersive_c1: Array | None

Per-cell dispersive recurrence coefficient c1. Shape (num_poles, 1, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.dispersive_c2: Array | None

Per-cell dispersive recurrence coefficient c2. Shape (num_poles, 1, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.dispersive_c3: Array | None

Per-cell dispersive recurrence coefficient c3. Shape (num_poles, 1, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.dispersive_inv_c2: Array | None

Per-cell cached 1 / c2 with non-dispersive cells set to 0. Lets the reverse-time ADE update avoid a jnp.where + division per step. Derived from dispersive_c2; never differentiated independently. Shape (num_poles, 1, Nx, Ny, Nz). None for non-dispersive simulations.

ArrayContainer.electric_conductivity: Array | None

field for electric conductivity terms. Defaults to None.

ArrayContainer.fields: FieldState

Dynamic electromagnetic fields (E, H and PML auxiliaries).

ArrayContainer.inv_permeabilities: Array | float

Inverse permeability values array.

ArrayContainer.inv_permittivities: Array

Inverse permittivity values array.

ArrayContainer.kappa: Array

Kappa array for PML calculations.

ArrayContainer.magnetic_conductivity: Array | None

field for magnetic conductivity terms. Defaults to None.

ArrayContainer.recording_state: RecordingState | None

Optional state for recording simulation data.

ArrayContainer.sigma: Array

Sigma array for PML calculations.

Methods

ArrayContainer.aset(attr_name, val, create_new_ok=False)

Sets an attribute of this class. In contrast to the classical .at[].set(), this method updates the class attribute directly and does not only operate on jax pytree leaf nodes. Instead, replaces the full attribute with the new value.

The attribute can either be the attribute name of this class, or for nested classes it can also be the attribute name of a class, which itself is an attribute of this class. The syntax for this operation could look like this: “a->b->[0]->[‘name’]”. Here, the current class has an attribute a, which has an attribute b, which is a list, which we index at index 0, which is an element of type dictionary, which we index using the dictionary key ‘name’.

Note that dictionary keys cannot contain square brackets or single quotes (even if they are escaped).

Parameters:

• attr_name (str) – Name of attribute to set

• val (Any) – Value to set the attribute to

• create_new_ok (bool, optional) – If false (default), throw an error if the attribute does not exist. If true, creates a new attribute if the attribute name does not exist yet.

Returns:

Updated instance with new attribute value

Return type:

Self

ArrayContainer.get_class_fields()

Return type:

list[TreeClassField]

ArrayContainer.get_public_fields()

Return type:

list[TreeClassField]

ArrayContainer.reset(reset_detector_states=True, reset_recording_state=False)

Return a reset copy of this array container.

Dynamic field arrays are zeroed while material arrays and conductivity arrays are preserved. Detector states are reset by default because they accumulate time-dependent measurements. Recording state is preserved by default so partial simulations can continue writing to the same buffers.

Parameters:

• reset_detector_states (bool) – Whether to zero all detector state arrays. Defaults to True.

• reset_recording_state (bool) – Whether to zero recording data and state arrays when a recording state is present. Defaults to False.

Return type:

ArrayContainer

Returns:

A new ArrayContainer with reset dynamic state.

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