optimisation.objective.minimize_mismatch module

This module is specific to hold mismatches.

It has its own module as this quantity is pretty specific.

class MinimizeMismatch(name: str, weight: float, get_key: str, get_kwargs: dict[str, Element | str | bool], reference: SimulationOutput, descriptor: str | None = None)

Bases: Objective

Minimize a mismatch factor.

__init__(name: str, weight: float, get_key: str, get_kwargs: dict[str, Element | str | bool], reference: SimulationOutput, descriptor: str | None = None) → None

Set complementary get() flags, reference value.

Parameters:

• get_key (str) – Must contain ‘twiss’ plus the name of a phase-space, or simply ‘twiss’ and the phase-space is defined in get_kwargs.

• get_kwargs (dict[str, Element | str | bool]) – Keyword arguments for the get() method. We do not check its validity, but in general you will want to define the keys elt and pos. You should also define the phase_space_name key if it is not defined in the get_key.

• reference (SimulationOutput) – The reference simulation output from which the Twiss parameters will be taken.

_abc_impl = <_abc._abc_data object>

_base_str() → str

Return a base text for output.

_compute_residues(twiss_fix: ndarray) → float

Compute the residues.

_twiss_getter(simulation_output: SimulationOutput) → ndarray

Get desired value using SimulationOutput.get() method.

current_value(simulation_output: SimulationOutput) → str

Give value of current objective and residue.

evaluate(simulation_output: SimulationOutput) → 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