知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
146 lines
4.2 KiB
Python
146 lines
4.2 KiB
Python
from typing import Any, Final, Literal as L, overload
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import numpy as np
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from numpy._typing import ArrayLike, NDArray, _ArrayLike, _Shape, _ShapeLike
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__all__ = ["fftfreq", "fftshift", "ifftshift", "rfftfreq"]
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###
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type _Device = L["cpu"]
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type _IntLike = int | np.integer
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type _AsFloat64 = np.float64 | np.float32 | np.float16 | np.integer | np.bool
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type _AsComplex128 = np.complex128 | np.complex64
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type _Inexact80 = np.longdouble | np.clongdouble
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type _Array[ShapeT: _Shape, ScalarT: np.generic] = np.ndarray[ShapeT, np.dtype[ScalarT]]
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type _1D = tuple[int]
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###
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integer_types: Final[tuple[type[int], type[np.integer]]] = ...
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# keep in sync with `ifftshift` below
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@overload
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def fftshift[ShapeT: _Shape, DTypeT: np.dtype](
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x: np.ndarray[ShapeT, DTypeT],
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axes: _ShapeLike | None = None,
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) -> np.ndarray[ShapeT, DTypeT]: ...
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@overload
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def fftshift[ScalarT: np.generic](x: _ArrayLike[ScalarT], axes: _ShapeLike | None = None) -> NDArray[ScalarT]: ...
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@overload
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def fftshift(x: ArrayLike, axes: _ShapeLike | None = None) -> NDArray[Any]: ...
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# keep in sync with `fftshift` above
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@overload
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def ifftshift[ShapeT: _Shape, DTypeT: np.dtype](
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x: np.ndarray[ShapeT, DTypeT],
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axes: _ShapeLike | None = None,
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) -> np.ndarray[ShapeT, DTypeT]: ...
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@overload
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def ifftshift[ScalarT: np.generic](x: _ArrayLike[ScalarT], axes: _ShapeLike | None = None) -> NDArray[ScalarT]: ...
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@overload
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def ifftshift(x: ArrayLike, axes: _ShapeLike | None = None) -> NDArray[Any]: ...
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# keep in sync with `rfftfreq` below
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@overload # 0d +f64 (default)
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def fftfreq(
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n: _IntLike,
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d: _AsFloat64 | float = 1.0,
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device: _Device | None = None,
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) -> _Array[_1D, np.float64]: ...
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@overload # 0d c64 | c128
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def fftfreq(
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n: _IntLike,
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d: _AsComplex128,
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device: _Device | None = None,
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) -> _Array[_1D, np.complex128]: ...
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@overload # 0d +complex
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def fftfreq(
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n: _IntLike,
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d: complex,
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device: _Device | None = None,
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) -> _Array[_1D, np.complex128 | Any]: ...
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@overload # 0d T: f80 | c160
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def fftfreq[ScalarT: _Inexact80](
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n: _IntLike,
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d: ScalarT,
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device: _Device | None = None,
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) -> _Array[_1D, ScalarT]: ...
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@overload # nd +f64
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def fftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, _AsFloat64],
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device: _Device | None = None,
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) -> _Array[ShapeT, np.float64]: ...
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@overload # nd c64 | c128
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def fftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, _AsComplex128],
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device: _Device | None = None,
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) -> _Array[ShapeT, np.complex128]: ...
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@overload # nd T: f80 | c160
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def fftfreq[ShapeT: _Shape, LongDoubleT: _Inexact80](
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n: _IntLike,
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d: _Array[ShapeT, LongDoubleT],
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device: _Device | None = None,
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) -> _Array[ShapeT, LongDoubleT]: ...
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@overload # nd +complex (fallback)
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def fftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, np.number | np.bool],
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device: _Device | None = None,
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) -> _Array[ShapeT, Any]: ...
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# keep in sync with `fftfreq` above
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@overload # 0d +f64 (default)
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def rfftfreq(
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n: _IntLike,
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d: _AsFloat64 | float = 1.0,
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device: _Device | None = None,
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) -> _Array[_1D, np.float64]: ...
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@overload # 0d c64 | c128
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def rfftfreq(
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n: _IntLike,
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d: _AsComplex128,
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device: _Device | None = None,
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) -> _Array[_1D, np.complex128]: ...
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@overload # 0d +complex
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def rfftfreq(
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n: _IntLike,
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d: complex,
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device: _Device | None = None,
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) -> _Array[_1D, np.complex128 | Any]: ...
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@overload # 0d T: f80 | c160
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def rfftfreq[LongDoubleT: _Inexact80](
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n: _IntLike,
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d: LongDoubleT,
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device: _Device | None = None,
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) -> _Array[_1D, LongDoubleT]: ...
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@overload # nd +f64
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def rfftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, _AsFloat64],
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device: _Device | None = None,
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) -> _Array[ShapeT, np.float64]: ...
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@overload # nd c64 | c128
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def rfftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, _AsComplex128],
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device: _Device | None = None,
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) -> _Array[ShapeT, np.complex128]: ...
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@overload # nd T: f80 | c160
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def rfftfreq[ShapeT: _Shape, LongDoubleT: _Inexact80](
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n: _IntLike,
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d: _Array[ShapeT, LongDoubleT],
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device: _Device | None = None,
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) -> _Array[ShapeT, LongDoubleT]: ...
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@overload # nd +complex (fallback)
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def rfftfreq[ShapeT: _Shape](
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n: _IntLike,
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d: _Array[ShapeT, np.number | np.bool],
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device: _Device | None = None,
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) -> _Array[ShapeT, Any]: ...
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