"""
Provides support for mypy type checking of the package
.. codeauthor:: David Zwicker <david.zwicker@ds.mpg.de>
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Literal, Protocol, Union
import numpy as np
from numpy.typing import ArrayLike # @UnusedImport
if TYPE_CHECKING:
from ..grids.base import GridBase
Real = Union[int, float]
Number = Union[Real, complex]
NumberOrArray = Union[Number, np.ndarray]
FloatNumerical = Union[float, np.ndarray]
BackendType = Literal["auto", "numpy", "numba"]
[docs]
class OperatorType(Protocol):
"""an operator that acts on an array"""
def __call__(self, arr: np.ndarray, out: np.ndarray) -> None:
"""evaluate the operator"""
[docs]
class OperatorFactory(Protocol):
"""a factory function that creates an operator for a particular grid"""
def __call__(self, grid: GridBase, **kwargs) -> OperatorType:
"""create the operator"""
[docs]
class CellVolume(Protocol):
def __call__(self, *args: int) -> float:
"""calculate the volume of the cell at the given position"""
[docs]
class VirtualPointEvaluator(Protocol):
def __call__(self, arr: np.ndarray, idx: tuple[int, ...], args=None) -> float:
"""evaluate the virtual point at the given position"""
[docs]
class AdjacentEvaluator(Protocol):
def __call__(
self, arr_1d: np.ndarray, i_point: int, bc_idx: tuple[int, ...]
) -> float:
"""evaluate the values at adjecent points"""
[docs]
class GhostCellSetter(Protocol):
def __call__(self, data_full: np.ndarray, args=None) -> None:
"""set the ghost cells"""