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
212 lines
11 KiB
Python
212 lines
11 KiB
Python
from _typeshed import Incomplete
|
|
from collections.abc import Mapping, Sequence
|
|
from types import EllipsisType
|
|
from typing import Any, ClassVar, Literal as L, Self, SupportsIndex, overload
|
|
from typing_extensions import TypeVar
|
|
|
|
import numpy as np
|
|
from numpy._typing import (
|
|
ArrayLike,
|
|
DTypeLike,
|
|
NDArray,
|
|
_AnyShape,
|
|
_ArrayLikeInt_co,
|
|
_NestedSequence,
|
|
_ShapeLike,
|
|
)
|
|
|
|
__all__ = ["asmatrix", "bmat", "matrix"]
|
|
|
|
_ShapeT_co = TypeVar("_ShapeT_co", bound=_2D, default=_2D, covariant=True)
|
|
_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
|
|
|
|
type _2D = tuple[int, int]
|
|
type _Matrix[ScalarT: np.generic] = matrix[_2D, np.dtype[ScalarT]]
|
|
type _ToIndex1 = slice | EllipsisType | NDArray[np.integer | np.bool] | _NestedSequence[int] | None
|
|
type _ToIndex2 = tuple[_ToIndex1, _ToIndex1 | SupportsIndex] | tuple[_ToIndex1 | SupportsIndex, _ToIndex1]
|
|
|
|
###
|
|
|
|
class matrix(np.ndarray[_ShapeT_co, _DTypeT_co]):
|
|
__array_priority__: ClassVar[float] = 10.0 # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
def __new__(cls, data: ArrayLike, dtype: DTypeLike | None = None, copy: bool = True) -> _Matrix[Incomplete]: ...
|
|
|
|
#
|
|
@overload # type: ignore[override]
|
|
def __getitem__(
|
|
self, key: SupportsIndex | _ArrayLikeInt_co | tuple[SupportsIndex | _ArrayLikeInt_co, ...], /
|
|
) -> Incomplete: ...
|
|
@overload
|
|
def __getitem__(self, key: _ToIndex1 | _ToIndex2, /) -> matrix[_2D, _DTypeT_co]: ...
|
|
@overload
|
|
def __getitem__(self: _Matrix[np.void], key: str, /) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def __getitem__(self: _Matrix[np.void], key: list[str], /) -> matrix[_2D, _DTypeT_co]: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
#
|
|
def __mul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
|
|
def __rmul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
#
|
|
def __pow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
|
|
def __rpow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override]
|
|
|
|
# keep in sync with `prod` and `mean`
|
|
@overload # type: ignore[override]
|
|
def sum(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
|
|
@overload
|
|
def sum(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def sum[OutT: np.ndarray](self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def sum[OutT: np.ndarray](self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `sum` and `mean`
|
|
@overload # type: ignore[override]
|
|
def prod(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
|
|
@overload
|
|
def prod(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def prod[OutT: np.ndarray](self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def prod[OutT: np.ndarray](self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `sum` and `prod`
|
|
@overload # type: ignore[override]
|
|
def mean(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
|
|
@overload
|
|
def mean(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def mean[OutT: np.ndarray](self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def mean[OutT: np.ndarray](self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `var`
|
|
@overload # type: ignore[override]
|
|
def std(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
|
|
@overload
|
|
def std(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def std[OutT: np.ndarray](self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: OutT, ddof: float = 0) -> OutT: ...
|
|
@overload
|
|
def std[OutT: np.ndarray]( # pyright: ignore[reportIncompatibleMethodOverride]
|
|
self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: OutT, ddof: float = 0
|
|
) -> OutT: ...
|
|
|
|
# keep in sync with `std`
|
|
@overload # type: ignore[override]
|
|
def var(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
|
|
@overload
|
|
def var(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
|
|
@overload
|
|
def var[OutT: np.ndarray](self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: OutT, ddof: float = 0) -> OutT: ...
|
|
@overload
|
|
def var[OutT: np.ndarray]( # pyright: ignore[reportIncompatibleMethodOverride]
|
|
self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: OutT, ddof: float = 0
|
|
) -> OutT: ...
|
|
|
|
# keep in sync with `all`
|
|
@overload # type: ignore[override]
|
|
def any(self, axis: None = None, out: None = None) -> np.bool: ...
|
|
@overload
|
|
def any(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
|
|
@overload
|
|
def any[OutT: np.ndarray](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def any[OutT: np.ndarray](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `any`
|
|
@overload # type: ignore[override]
|
|
def all(self, axis: None = None, out: None = None) -> np.bool: ...
|
|
@overload
|
|
def all(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
|
|
@overload
|
|
def all[OutT: np.ndarray](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def all[OutT: np.ndarray](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `min` and `ptp`
|
|
@overload # type: ignore[override]
|
|
def max[ScalarT: np.generic](self: NDArray[ScalarT], axis: None = None, out: None = None) -> ScalarT: ...
|
|
@overload
|
|
def max(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
|
|
@overload
|
|
def max[OutT: np.ndarray](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def max[OutT: np.ndarray](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `max` and `ptp`
|
|
@overload # type: ignore[override]
|
|
def min[ScalarT: np.generic](self: NDArray[ScalarT], axis: None = None, out: None = None) -> ScalarT: ...
|
|
@overload
|
|
def min(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
|
|
@overload
|
|
def min[OutT: np.ndarray](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def min[OutT: np.ndarray](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `max` and `min`
|
|
@overload
|
|
def ptp[ScalarT: np.generic](self: NDArray[ScalarT], axis: None = None, out: None = None) -> ScalarT: ...
|
|
@overload
|
|
def ptp(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
|
|
@overload
|
|
def ptp[OutT: np.ndarray](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def ptp[OutT: np.ndarray](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `argmin`
|
|
@overload # type: ignore[override]
|
|
def argmax[ScalarT: np.generic](self: NDArray[ScalarT], axis: None = None, out: None = None) -> np.intp: ...
|
|
@overload
|
|
def argmax(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
|
|
@overload
|
|
def argmax[OutT: NDArray[np.integer | np.bool]](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def argmax[OutT: NDArray[np.integer | np.bool]](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# keep in sync with `argmax`
|
|
@overload # type: ignore[override]
|
|
def argmin[ScalarT: np.generic](self: NDArray[ScalarT], axis: None = None, out: None = None) -> np.intp: ...
|
|
@overload
|
|
def argmin(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
|
|
@overload
|
|
def argmin[OutT: NDArray[np.integer | np.bool]](self, axis: _ShapeLike | None, out: OutT) -> OutT: ...
|
|
@overload
|
|
def argmin[OutT: NDArray[np.integer | np.bool]](self, axis: _ShapeLike | None = None, *, out: OutT) -> OutT: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# the second overload handles the (rare) case that the matrix is not 2-d
|
|
@overload
|
|
def tolist[T](self: _Matrix[np.generic[T]]) -> list[list[T]]: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
@overload
|
|
def tolist(self) -> Incomplete: ... # pyright: ignore[reportIncompatibleMethodOverride]
|
|
|
|
# these three methods will at least return a `2-d` array of shape (1, n)
|
|
def squeeze(self, /, axis: _ShapeLike | None = None) -> matrix[_2D, _DTypeT_co]: ...
|
|
def ravel(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override]
|
|
def flatten(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override]
|
|
|
|
# matrix.T is inherited from _ScalarOrArrayCommon
|
|
def getT(self) -> Self: ...
|
|
@property
|
|
def I(self) -> _Matrix[Incomplete]: ... # noqa: E743
|
|
def getI(self) -> _Matrix[Incomplete]: ...
|
|
@property
|
|
def A(self) -> np.ndarray[_2D, _DTypeT_co]: ...
|
|
def getA(self) -> np.ndarray[_2D, _DTypeT_co]: ...
|
|
@property
|
|
def A1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
|
|
def getA1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
|
|
@property
|
|
def H(self) -> matrix[_2D, _DTypeT_co]: ...
|
|
def getH(self) -> matrix[_2D, _DTypeT_co]: ...
|
|
|
|
def bmat(
|
|
obj: str | Sequence[ArrayLike] | NDArray[Any],
|
|
ldict: Mapping[str, Any] | None = None,
|
|
gdict: Mapping[str, Any] | None = None,
|
|
) -> _Matrix[Incomplete]: ...
|
|
|
|
def asmatrix(data: ArrayLike, dtype: DTypeLike | None = None) -> _Matrix[Incomplete]: ...
|