emulsim.actors.autonomous.box module

class BoxActor(parameters: dict[str, Any] | None = None)[source]

Bases: ActorBase

Actor containing particles in a box.

Parameters Dictionary:

bounds: The bounds of the box (default=array([], dtype=float64))
periodic: The bounds of the box (default=array(False))
point_like: When False, the radius of the object is used in the distance calculation (default=True)

Parameters:: parameters (dict) – Parameters affecting the actor. Call show_parameters() for details.

Parameters of BoxActor:

bounds: The bounds of the box (Default value: array([], dtype=float64))
periodic: The bounds of the box (Default value: array(False))
point_like: When False, the radius of the object is used in the distance calculation (Default value: True)

element_classes: tuple[type[_ElementBase] | tuple[type[_ElementBase], ...], ...] | EllipsisType = ((<class 'emulsim.elements.points.PointsElement'>, <class 'emulsim.elements.points.ArrowsElement'>, <class 'emulsim.elements.spherical_droplets.SphericalDropletsElement'>),)

defines the elements this actor handles and in what order they need to be supplied. An ellipsis (…) indicates that all elements and lists of elements are accepted. Setting this attribute allows internal consistency checks.

Type:: tuple

estimate_dt(elements: tuple[_ElementBase, ...]) → float[source]

Estimate the maximal time step for simulating this actor.

Parameters:: elements (tuple of PointsElement) – The element that is affected by the directed motion
Returns:: the maximal time step
Return type:: float

evolve(elements: tuple[_ElementBase, ...], t: float, dt: float) → None[source]

Evolve the field state from time t to t + dt

Parameters:

elements (tuple of PointsElement) – The element that is affected by this actor
t (float) – The current time point
dt (float) – The time step

classmethod from_grid(grid: CartesianGrid)[source]

Create BoxActor from a Cartesian grid.

Parameters:: grid (pde.grids.cartesian.CartesianGrid) – The Cartesian grid that defines the box

make_evolver_numba(elements: tuple[_ElementBase, ...]) → Callable[[tuple[ndarray], float, float], None][source]

Return a function evolve the field state from time t to t + dt

Parameters:

elements (tuple of PointsElement) – The element that is affected by this actor

Returns:

A function with signature: (state_data: ndarray, t: float, dt: float), evolving state_data

Return type:

callable