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| author | blackhao <13851610112@163.com> | 2025-08-22 02:51:50 -0500 |
|---|---|---|
| committer | blackhao <13851610112@163.com> | 2025-08-22 02:51:50 -0500 |
| commit | 4aab4087dc97906d0b9890035401175cdaab32d4 (patch) | |
| tree | 4e2e9d88a711ec5b1cfa02e8ac72a55183b99123 /.venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi | |
| parent | afa8f50d1d21c721dabcb31ad244610946ab65a3 (diff) | |
2.0
Diffstat (limited to '.venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi')
| -rw-r--r-- | .venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi | 124 |
1 files changed, 124 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi b/.venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi new file mode 100644 index 0000000..6ce4f4b --- /dev/null +++ b/.venv/lib/python3.12/site-packages/numpy/random/bit_generator.pyi @@ -0,0 +1,124 @@ +import abc +from collections.abc import Callable, Mapping, Sequence +from threading import Lock +from typing import ( + Any, + ClassVar, + Literal, + NamedTuple, + Self, + TypeAlias, + TypedDict, + overload, + type_check_only, +) + +from _typeshed import Incomplete +from typing_extensions import CapsuleType + +import numpy as np +from numpy._typing import ( + NDArray, + _ArrayLikeInt_co, + _DTypeLike, + _ShapeLike, + _UInt32Codes, + _UInt64Codes, +) + +__all__ = ["BitGenerator", "SeedSequence"] + +### + +_DTypeLikeUint_: TypeAlias = _DTypeLike[np.uint32 | np.uint64] | _UInt32Codes | _UInt64Codes + +@type_check_only +class _SeedSeqState(TypedDict): + entropy: int | Sequence[int] | None + spawn_key: tuple[int, ...] + pool_size: int + n_children_spawned: int + +@type_check_only +class _Interface(NamedTuple): + state_address: Incomplete + state: Incomplete + next_uint64: Incomplete + next_uint32: Incomplete + next_double: Incomplete + bit_generator: Incomplete + +@type_check_only +class _CythonMixin: + def __setstate_cython__(self, pyx_state: object, /) -> None: ... + def __reduce_cython__(self) -> Any: ... # noqa: ANN401 + +@type_check_only +class _GenerateStateMixin(_CythonMixin): + def generate_state(self, /, n_words: int, dtype: _DTypeLikeUint_ = ...) -> NDArray[np.uint32 | np.uint64]: ... + +### + +class ISeedSequence(abc.ABC): + @abc.abstractmethod + def generate_state(self, /, n_words: int, dtype: _DTypeLikeUint_ = ...) -> NDArray[np.uint32 | np.uint64]: ... + +class ISpawnableSeedSequence(ISeedSequence, abc.ABC): + @abc.abstractmethod + def spawn(self, /, n_children: int) -> list[Self]: ... + +class SeedlessSeedSequence(_GenerateStateMixin, ISpawnableSeedSequence): + def spawn(self, /, n_children: int) -> list[Self]: ... + +class SeedSequence(_GenerateStateMixin, ISpawnableSeedSequence): + __pyx_vtable__: ClassVar[CapsuleType] = ... + + entropy: int | Sequence[int] | None + spawn_key: tuple[int, ...] + pool_size: int + n_children_spawned: int + pool: NDArray[np.uint32] + + def __init__( + self, + /, + entropy: _ArrayLikeInt_co | None = None, + *, + spawn_key: Sequence[int] = (), + pool_size: int = 4, + n_children_spawned: int = ..., + ) -> None: ... + def spawn(self, /, n_children: int) -> list[Self]: ... + @property + def state(self) -> _SeedSeqState: ... + +class BitGenerator(_CythonMixin, abc.ABC): + lock: Lock + @property + def state(self) -> Mapping[str, Any]: ... + @state.setter + def state(self, value: Mapping[str, Any], /) -> None: ... + @property + def seed_seq(self) -> ISeedSequence: ... + @property + def ctypes(self) -> _Interface: ... + @property + def cffi(self) -> _Interface: ... + @property + def capsule(self) -> CapsuleType: ... + + # + def __init__(self, /, seed: _ArrayLikeInt_co | SeedSequence | None = None) -> None: ... + def __reduce__(self) -> tuple[Callable[[str], Self], tuple[str], tuple[Mapping[str, Any], ISeedSequence]]: ... + def spawn(self, /, n_children: int) -> list[Self]: ... + def _benchmark(self, /, cnt: int, method: str = "uint64") -> None: ... + + # + @overload + def random_raw(self, /, size: None = None, output: Literal[True] = True) -> int: ... + @overload + def random_raw(self, /, size: _ShapeLike, output: Literal[True] = True) -> NDArray[np.uint64]: ... + @overload + def random_raw(self, /, size: _ShapeLike | None, output: Literal[False]) -> None: ... + @overload + def random_raw(self, /, size: _ShapeLike | None = None, *, output: Literal[False]) -> None: ... |
