optimisation.objective.objective module

Define a class to hold optimisation objective with its ideal value.

class Objective(name: str, weight: float, descriptor: str | None = None, ideal_value: tuple[float] | float | None = None)

Bases: ABC

Hold an objective and methods to evaluate it.

Parameters:

• name (str) – A short string to describe the objective and access to it.

• weight (float) – A scaling constant to set the weight of current objective.

• descriptor (str | None, optional) – A longer string to explain the objective. The default is None.

• ideal_value (float | tuple[float], optional) – The ideal value or range of values that we should tend to.

__init__(name: str, weight: float, descriptor: str | None = None, ideal_value: tuple[float] | float | None = None) → None

__post_init__() → None

Avoid line jumps in the descriptor.

_abc_impl = <_abc._abc_data object>

abstract current_value(simulation_output: SimulationOutput | float) → str

Give value of current objective and residue.

static current_value_header() → str

Give a header to explain what current_value() returns.

descriptor: str | None = None

abstract evaluate(simulation_output: SimulationOutput | float) → float

Compute residue of this objective.

Parameters:

simulation_output (SimulationOutput | float) – Object containing simulation results of the broken linac.

Returns:

residue – Difference between current evaluation and ideal_value value for self.name, scaled by self.weight.

Return type:

float

ideal_value: tuple[float] | float | None = None

name: str

static str_header() → str

Give a header to explain what __str__() returns.

weight: float