"""Define :class:`Variable`, which stores an optimisation variable.
It keeps it's name, bounds, initial value, etc.
"""
import logging
from dataclasses import dataclass
from typing import Self
import numpy as np
import pandas as pd
from lightwin.optimisation.design_space.design_space_parameter import (
DesignSpaceParameter,
)
IMPLEMENTED_VARIABLES = ("k_e", "phi_0_abs", "phi_0_rel", "phi_s") #:
[docs]
@dataclass
class Variable(DesignSpaceParameter):
"""A single variable.
It can be a cavity amplitude, absolute phase, relative phase or synchronous
phase with an initial value and limits.
Parameters
----------
name : str
Name of the parameter. Must be compatible with the
:meth:`.SimulationOutput.get` method, and be in
:data:`.IMPLEMENTED_VARIABLES`.
element_name : str
Name of the element concerned by the parameter.
limits : tuple[float, float]
Lower and upper bound for the variable. ``np.nan`` deactivates a bound.
x_0 : float
Initial value.
"""
x_0: float
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@classmethod
def from_floats(
cls,
name: str,
element_name: str,
x_min: float,
x_max: float,
x_0: float = np.nan,
) -> Self:
"""Initialize object with ``x_min``, ``x_max`` instead of ``limits``.
Parameters
----------
name : str
Name of the parameter. Must be compatible with the
:meth:`.SimulationOutput.get` method, and be in
:data:`.IMPLEMENTED_VARIABLES`.
element_name : str
Name of the element concerned by the parameter.
x_min : float
Lower limit. ``np.nan`` to deactivate lower bound.
x_max : float
Upper limit. ``np.nan`` to deactivate lower bound.
x_0: float
Initial value.
Returns
-------
Self
A Variable with limits = (x_min, x_max).
"""
return cls(name, element_name, (x_min, x_max), x_0)
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@classmethod
def from_pd_series(
cls, name: str, element_name: str, pd_series: pd.Series
) -> Self:
"""Init object from a pd series (file import)."""
x_min = pd_series.loc[f"{name}: x_min"]
x_max = pd_series.loc[f"{name}: x_max"]
x_0 = pd_series.loc[f"{name}: x_0"]
return cls.from_floats(name, element_name, x_min, x_max, x_0)
[docs]
def __post_init__(self):
"""Convert values in deg for output if it is angle."""
if self.name not in IMPLEMENTED_VARIABLES:
logging.warning(f"Variable {self.name} not tested.")
super().__post_init__()