finesse.element_workspace module

class finesse.element_workspace.BaseCValues[source]

Bases: object

Base class that elements should use for storing their parameter values. This contains a generic method for storing a pointers to the double parameter values, which is intialised using setup().

Each Parameter of an element should result in a double. This won’t handle any other types of data.

class finesse.element_workspace.ElementValues[source]

Bases: object

Standard Python object which is used to store an Elements Parameter values. This is used in the default case where no optimised C class is provided.

class finesse.element_workspace.ElementWorkspace(sim, owner, values=None)[source]

Bases: object

This is the most basic workspace for a model element. It keeps track of the owner element and its parameter values in the self.values object.

compile_cy_exprs(self) → int

owner

owner_id: owner_id: ‘int’

sim

update_parameter_values(self)[source]: Updates the self.values container which holds the latest values of this elements parameters.

values

class finesse.element_workspace.RelaxingWorkspace[source]

Bases: ElementWorkspace

RelaxingWorkspace is an abstract base class that represents a workspace for relaxation processes.

This class inherits from ElementWorkspace and ABC (Abstract Base Class) and defines the following abstract methods:

status: Get the status of the relaxation process for the user
converged: Check if the relaxation process has converged.
update_step: Update the state of the model before the next solution is found
end_step: Finalizes the update of the relaxation process, to process at the end of a step

Methods

status() -> str: Abstract method to get the status of the relaxation process to show to the user regarding how close the convergence is.
converged() -> bool: Abstract method to check if the relaxation process has converged.
update_step(stepint): Abstract method to update the state of the relaxation process.
on_failed_step(stepint): Abstract method to handle a failed step of the relaxation process, this will be called if a LockLoss happens. Should revert states back to last known working point, ie the previous values.
end_step(stepint): Abstract method to finalize the this step of the relaxation process.

converged(self) → bool

end_step(self, int step)[source]

on_failed_step(self, int step)[source]

status(self) → str

update_step(self, int step)[source]

class finesse.element_workspace.TemporalQuasiStaticWorkspace[source]

Bases: ElementWorkspace

A class representing a temporal quasi-static workspace for elements. This should be used in conjunction with the analyses in finesse.analysis.actions.time.

Methods

status() -> str: Returns the status of the workspace.
time() -> float: Returns the current time of the workspace.
set_time_step(dt: float) -> float: Sets the time step for the workspace.
initialise(): Initialises the workspace.
update_before_step(): Updates the workspace before stepping forward.
step_forward(): Advances the workspace by one time step.
get_state(): Return the current time state of the element

get_state(self)[source]

initialise(self)[source]

set_time_step(self, float dt) → float

status(self) → str

step_forward(self)[source]

time(self) → float

update_before_step(self)[source]