"""Contains the implementations for the quadrature methods
Implements the supported quadrature methods.
"""
from collections.abc import Callable
from pydantic import Field
from ..base import CalibrationMethodBase, CalibrationWorkflowBase
from ..data_model import CalibrationModel
TASK = "quadrature"
BASE_IMPLEMENTATIONS: dict[str, str] = dict(
emukit=f"calisim.{TASK}.emukit_wrapper:EmukitQuadrature",
)
[docs]
def get_implementations() -> dict[str, str]:
"""Get the calibration implementations for quadrature.
Returns:
Dict[str, str]: The dictionary
of calibration implementations for quadrature.
"""
implementations = dict(BASE_IMPLEMENTATIONS)
implementations.update(CalibrationMethodBase.load_external_implementations(TASK))
return implementations
[docs]
class QuadratureMethodModel(CalibrationModel):
"""The quadrature method data model.
Args:
BaseModel (CalibrationModel): The calibration base model class.
"""
kernel: str | None = Field(
description="The Kernel embeddings for Bayesian quadrature",
default="QuadratureRBFLebesgueMeasure",
)
measure: str | None = Field(
description="The Integration measures", default="LebesgueMeasure"
)
[docs]
class QuadratureMethod(CalibrationMethodBase):
"""The quadrature method class."""
def __init__(
self,
calibration_func: Callable,
specification: QuadratureMethodModel,
engine: str = "emukit",
implementation: type[CalibrationWorkflowBase]
| CalibrationWorkflowBase
| None = None,
) -> None:
"""QuadratureMethod constructor.
Args:
calibration_func (Callable): The calibration function.
For example, a simulation function or objective function.
specification (QuadratureMethodModel): The calibration
specification.
engine (str, optional): The Quadrature backend.
Defaults to "emukit".
implementation (type[CalibrationWorkflowBase] | CalibrationWorkflowBase
| None): The calibration workflow implementation.
"""
super().__init__(
calibration_func,
specification,
TASK,
engine,
get_implementations(),
implementation,
)