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TYP: improve type annotations of arrays to also express constraints on dimensionality 1/n #469

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TYP: improve type annotations of arrays to also express constraints on dimensionality 1/n #469

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3 changes: 3 additions & 0 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -167,6 +167,9 @@ convention = "numpy"
[tool.ruff.lint.per-file-ignores]
"tests/**" = ["D"]

[tool.ty.rules]
unused-type-ignore-comment = "ignore"

[tool.mypy]
python_version = "3.11"
show_error_codes = true
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102 changes: 50 additions & 52 deletions src/gpgi/_boundaries.py
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Original file line number Diff line number Diff line change
@@ -1,25 +1,23 @@
from collections.abc import Callable
from threading import Lock
from typing import Any, Literal, cast
from typing import Any, Literal

from numpy.typing import NDArray

from gpgi._typing import FloatT
from gpgi._typing import DH, F, FArray

BoundaryRecipeT = Callable[
[
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
NDArray[FloatT],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
FArray[DH, F],
Literal["left", "right"],
dict[str, Any],
],
NDArray[FloatT],
FArray[DH, F],
]


Expand Down Expand Up @@ -125,64 +123,64 @@ def __contains__(self, key: str) -> bool:

# basic recipes
def open_boundary(
same_side_active_layer: NDArray[FloatT],
same_side_ghost_layer: NDArray[FloatT],
opposite_side_active_layer: NDArray[FloatT],
opposite_side_ghost_layer: NDArray[FloatT],
weight_same_side_active_layer: NDArray[FloatT],
weight_same_side_ghost_layer: NDArray[FloatT],
weight_opposite_side_active_layer: NDArray[FloatT],
weight_opposite_side_ghost_layer: NDArray[FloatT],
same_side_active_layer: FArray[DH, F],
same_side_ghost_layer: FArray[DH, F],
opposite_side_active_layer: FArray[DH, F],
opposite_side_ghost_layer: FArray[DH, F],
weight_same_side_active_layer: FArray[DH, F],
weight_same_side_ghost_layer: FArray[DH, F],
weight_opposite_side_active_layer: FArray[DH, F],
weight_opposite_side_ghost_layer: FArray[DH, F],
side: Literal["left", "right"],
metadata: dict[str, Any],
) -> NDArray[FloatT]:
) -> FArray[DH, F]:
# return the active layer unchanged
return same_side_active_layer


def wall_boundary(
same_side_active_layer: NDArray[FloatT],
same_side_ghost_layer: NDArray[FloatT],
opposite_side_active_layer: NDArray[FloatT],
opposite_side_ghost_layer: NDArray[FloatT],
weight_same_side_active_layer: NDArray[FloatT],
weight_same_side_ghost_layer: NDArray[FloatT],
weight_opposite_side_active_layer: NDArray[FloatT],
weight_opposite_side_ghost_layer: NDArray[FloatT],
same_side_active_layer: FArray[DH, F],
same_side_ghost_layer: FArray[DH, F],
opposite_side_active_layer: FArray[DH, F],
opposite_side_ghost_layer: FArray[DH, F],
weight_same_side_active_layer: FArray[DH, F],
weight_same_side_ghost_layer: FArray[DH, F],
weight_opposite_side_active_layer: FArray[DH, F],
weight_opposite_side_ghost_layer: FArray[DH, F],
side: Literal["left", "right"],
metadata: dict[str, Any],
) -> NDArray[FloatT]:
return cast("NDArray[FloatT]", same_side_active_layer + same_side_ghost_layer)
) -> FArray[DH, F]:
return same_side_active_layer + same_side_ghost_layer # pyright: ignore[reportReturnType]


def antisymmetric_boundary(
same_side_active_layer: NDArray[FloatT],
same_side_ghost_layer: NDArray[FloatT],
opposite_side_active_layer: NDArray[FloatT],
opposite_side_ghost_layer: NDArray[FloatT],
weight_same_side_active_layer: NDArray[FloatT],
weight_same_side_ghost_layer: NDArray[FloatT],
weight_opposite_side_active_layer: NDArray[FloatT],
weight_opposite_side_ghost_layer: NDArray[FloatT],
same_side_active_layer: FArray[DH, F],
same_side_ghost_layer: FArray[DH, F],
opposite_side_active_layer: FArray[DH, F],
opposite_side_ghost_layer: FArray[DH, F],
weight_same_side_active_layer: FArray[DH, F],
weight_same_side_ghost_layer: FArray[DH, F],
weight_opposite_side_active_layer: FArray[DH, F],
weight_opposite_side_ghost_layer: FArray[DH, F],
side: Literal["left", "right"],
metadata: dict[str, Any],
) -> NDArray[FloatT]:
return cast("NDArray[FloatT]", same_side_active_layer - same_side_ghost_layer)
) -> FArray[DH, F]:
return same_side_active_layer - same_side_ghost_layer # pyright: ignore[reportReturnType]


def periodic_boundary(
same_side_active_layer: NDArray[FloatT],
same_side_ghost_layer: NDArray[FloatT],
opposite_side_active_layer: NDArray[FloatT],
opposite_side_ghost_layer: NDArray[FloatT],
weight_same_side_active_layer: NDArray[FloatT],
weight_same_side_ghost_layer: NDArray[FloatT],
weight_opposite_side_active_layer: NDArray[FloatT],
weight_opposite_side_ghost_layer: NDArray[FloatT],
same_side_active_layer: FArray[DH, F],
same_side_ghost_layer: FArray[DH, F],
opposite_side_active_layer: FArray[DH, F],
opposite_side_ghost_layer: FArray[DH, F],
weight_same_side_active_layer: FArray[DH, F],
weight_same_side_ghost_layer: FArray[DH, F],
weight_opposite_side_active_layer: FArray[DH, F],
weight_opposite_side_ghost_layer: FArray[DH, F],
side: Literal["left", "right"],
metadata: dict[str, Any],
) -> NDArray[FloatT]:
return cast("NDArray[FloatT]", same_side_active_layer + opposite_side_ghost_layer)
) -> FArray[DH, F]:
return same_side_active_layer + opposite_side_ghost_layer # pyright: ignore[reportReturnType]


_base_registry: dict[str, BoundaryRecipeT] = {
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