增加环绕侦察场景适配
This commit is contained in:
@@ -1,5 +1,3 @@
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from numpy import matrix
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from .defmatrix import asmatrix, bmat
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from .defmatrix import asmatrix, bmat, matrix
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__all__ = ["matrix", "bmat", "asmatrix"]
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@@ -1,17 +1,218 @@
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from _typeshed import Incomplete
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from collections.abc import Mapping, Sequence
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from typing import Any
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from types import EllipsisType
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from typing import Any, ClassVar, Literal as L, Self, SupportsIndex, TypeAlias, overload
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from typing_extensions import TypeVar
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from numpy import matrix
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from numpy._typing import ArrayLike, DTypeLike, NDArray
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import numpy as np
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from numpy._typing import (
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ArrayLike,
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DTypeLike,
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NDArray,
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_AnyShape,
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_ArrayLikeInt_co,
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_NestedSequence,
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_ShapeLike,
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)
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__all__ = ["asmatrix", "bmat", "matrix"]
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_T = TypeVar("_T")
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_ArrayT = TypeVar("_ArrayT", bound=np.ndarray)
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_BoolOrIntArrayT = TypeVar("_BoolOrIntArrayT", bound=NDArray[np.integer | np.bool])
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_ScalarT = TypeVar("_ScalarT", bound=np.generic)
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_ShapeT_co = TypeVar("_ShapeT_co", bound=_2D, default=_2D, covariant=True)
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_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
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_2D: TypeAlias = tuple[int, int]
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_Matrix: TypeAlias = matrix[_2D, np.dtype[_ScalarT]]
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_ToIndex1: TypeAlias = slice | EllipsisType | NDArray[np.integer | np.bool] | _NestedSequence[int] | None
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_ToIndex2: TypeAlias = tuple[_ToIndex1, _ToIndex1 | SupportsIndex] | tuple[_ToIndex1 | SupportsIndex, _ToIndex1]
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class matrix(np.ndarray[_ShapeT_co, _DTypeT_co]):
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__array_priority__: ClassVar[float] = 10.0 # pyright: ignore[reportIncompatibleMethodOverride]
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def __new__(
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subtype, # pyright: ignore[reportSelfClsParameterName]
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data: ArrayLike,
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dtype: DTypeLike | None = None,
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copy: bool = True,
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) -> _Matrix[Incomplete]: ...
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#
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@overload # type: ignore[override]
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def __getitem__(
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self, key: SupportsIndex | _ArrayLikeInt_co | tuple[SupportsIndex | _ArrayLikeInt_co, ...], /
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) -> Incomplete: ...
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@overload
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def __getitem__(self, key: _ToIndex1 | _ToIndex2, /) -> matrix[_2D, _DTypeT_co]: ...
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@overload
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def __getitem__(self: _Matrix[np.void], key: str, /) -> _Matrix[Incomplete]: ...
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@overload
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def __getitem__(self: _Matrix[np.void], key: list[str], /) -> matrix[_2D, _DTypeT_co]: ... # pyright: ignore[reportIncompatibleMethodOverride]
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#
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def __mul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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def __rmul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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#
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def __pow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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def __rpow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `prod` and `mean`
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@overload # type: ignore[override]
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def sum(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
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@overload
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def sum(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
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@overload
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def sum(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def sum(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `sum` and `mean`
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@overload # type: ignore[override]
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def prod(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
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@overload
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def prod(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
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@overload
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def prod(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def prod(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `sum` and `prod`
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@overload # type: ignore[override]
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def mean(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
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@overload
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def mean(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
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@overload
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def mean(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def mean(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `var`
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@overload # type: ignore[override]
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def std(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
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@overload
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def std(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
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@overload
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def std(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ...
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@overload
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def std( # pyright: ignore[reportIncompatibleMethodOverride]
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self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0
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) -> _ArrayT: ...
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# keep in sync with `std`
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@overload # type: ignore[override]
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def var(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
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@overload
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def var(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
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@overload
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def var(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ...
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@overload
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def var( # pyright: ignore[reportIncompatibleMethodOverride]
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self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0
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) -> _ArrayT: ...
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# keep in sync with `all`
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@overload # type: ignore[override]
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def any(self, axis: None = None, out: None = None) -> np.bool: ...
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@overload
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def any(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
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@overload
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def any(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def any(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `any`
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@overload # type: ignore[override]
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def all(self, axis: None = None, out: None = None) -> np.bool: ...
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@overload
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def all(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
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@overload
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def all(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def all(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `min` and `ptp`
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@overload # type: ignore[override]
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def max(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
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@overload
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def max(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
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@overload
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def max(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def max(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `max` and `ptp`
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@overload # type: ignore[override]
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def min(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
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@overload
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def min(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
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@overload
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def min(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def min(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `max` and `min`
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@overload
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def ptp(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
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@overload
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def ptp(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
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@overload
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def ptp(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
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@overload
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def ptp(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `argmin`
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@overload # type: ignore[override]
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def argmax(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> np.intp: ...
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@overload
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def argmax(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
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@overload
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def argmax(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...
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@overload
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def argmax(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# keep in sync with `argmax`
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@overload # type: ignore[override]
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def argmin(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> np.intp: ...
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@overload
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def argmin(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
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@overload
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def argmin(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...
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@overload
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def argmin(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# the second overload handles the (rare) case that the matrix is not 2-d
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@overload
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def tolist(self: _Matrix[np.generic[_T]]) -> list[list[_T]]: ... # pyright: ignore[reportIncompatibleMethodOverride]
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@overload
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def tolist(self) -> Incomplete: ... # pyright: ignore[reportIncompatibleMethodOverride]
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# these three methods will at least return a `2-d` array of shape (1, n)
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def squeeze(self, /, axis: _ShapeLike | None = None) -> matrix[_2D, _DTypeT_co]: ...
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def ravel(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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def flatten(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
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# matrix.T is inherited from _ScalarOrArrayCommon
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def getT(self) -> Self: ...
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@property
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def I(self) -> _Matrix[Incomplete]: ... # noqa: E743
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def getI(self) -> _Matrix[Incomplete]: ...
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@property
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def A(self) -> np.ndarray[_2D, _DTypeT_co]: ...
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def getA(self) -> np.ndarray[_2D, _DTypeT_co]: ...
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@property
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def A1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
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def getA1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
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@property
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def H(self) -> matrix[_2D, _DTypeT_co]: ...
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def getH(self) -> matrix[_2D, _DTypeT_co]: ...
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def bmat(
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obj: str | Sequence[ArrayLike] | NDArray[Any],
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ldict: Mapping[str, Any] | None = ...,
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gdict: Mapping[str, Any] | None = ...,
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) -> matrix[tuple[int, int], Any]: ...
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ldict: Mapping[str, Any] | None = None,
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gdict: Mapping[str, Any] | None = None,
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) -> _Matrix[Incomplete]: ...
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def asmatrix(
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data: ArrayLike, dtype: DTypeLike = ...
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) -> matrix[tuple[int, int], Any]: ...
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def asmatrix(data: ArrayLike, dtype: DTypeLike | None = None) -> _Matrix[Incomplete]: ...
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@@ -288,10 +288,10 @@ class TestMatrixReturn:
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'argmin', 'choose', 'dump', 'dumps', 'fill', 'getfield',
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'getA', 'getA1', 'item', 'nonzero', 'put', 'putmask', 'resize',
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'searchsorted', 'setflags', 'setfield', 'sort',
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'partition', 'argpartition', 'newbyteorder', 'to_device',
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'partition', 'argpartition', 'to_device',
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'take', 'tofile', 'tolist', 'tobytes', 'all', 'any',
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'sum', 'argmax', 'argmin', 'min', 'max', 'mean', 'var', 'ptp',
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'prod', 'std', 'ctypes', 'itemset', 'bitwise_count',
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'prod', 'std', 'ctypes', 'bitwise_count',
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]
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for attrib in dir(a):
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if attrib.startswith('_') or attrib in excluded_methods:
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@@ -116,7 +116,7 @@ class TestMaskedMatrix:
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# Test setting
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test = masked_array(np.matrix([[1, 2, 3]]), mask=[0, 0, 1])
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testflat = test.flat
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testflat[:] = testflat[[2, 1, 0]]
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testflat[:] = testflat[np.array([2, 1, 0])]
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assert_equal(test, control)
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testflat[0] = 9
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# test that matrices keep the correct shape (#4615)
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@@ -182,26 +182,26 @@ class TestMaskedMatrix:
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class TestSubclassing:
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# Test suite for masked subclasses of ndarray.
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def setup_method(self):
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def _create_data(self):
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x = np.arange(5, dtype='float')
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mx = MMatrix(x, mask=[0, 1, 0, 0, 0])
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self.data = (x, mx)
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return x, mx
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def test_maskedarray_subclassing(self):
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# Tests subclassing MaskedArray
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(x, mx) = self.data
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mx = self._create_data()[1]
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assert_(isinstance(mx._data, np.matrix))
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def test_masked_unary_operations(self):
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# Tests masked_unary_operation
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(x, mx) = self.data
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x, mx = self._create_data()
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with np.errstate(divide='ignore'):
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assert_(isinstance(log(mx), MMatrix))
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assert_equal(log(x), np.log(x))
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def test_masked_binary_operations(self):
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# Tests masked_binary_operation
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(x, mx) = self.data
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x, mx = self._create_data()
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# Result should be a MMatrix
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assert_(isinstance(add(mx, mx), MMatrix))
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assert_(isinstance(add(mx, x), MMatrix))
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@@ -215,7 +215,7 @@ class TestSubclassing:
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def test_masked_binary_operations2(self):
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# Tests domained_masked_binary_operation
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(x, mx) = self.data
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x, mx = self._create_data()
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xmx = masked_array(mx.data.__array__(), mask=mx.mask)
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assert_(isinstance(divide(mx, mx), MMatrix))
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assert_(isinstance(divide(mx, x), MMatrix))
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@@ -1,4 +1,6 @@
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""" Test functions for linalg module using the matrix class."""
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import pytest
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import numpy as np
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from numpy.linalg.tests.test_linalg import (
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CondCases,
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@@ -12,13 +14,13 @@ from numpy.linalg.tests.test_linalg import (
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PinvCases,
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SolveCases,
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SVDCases,
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TestQR as _TestQR,
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_TestNorm2D,
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_TestNormDoubleBase,
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_TestNormInt64Base,
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_TestNormSingleBase,
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apply_tag,
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)
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from numpy.linalg.tests.test_linalg import TestQR as _TestQR
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CASES = []
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@@ -81,6 +83,9 @@ class TestDetMatrix(DetCases, MatrixTestCase):
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pass
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@pytest.mark.thread_unsafe(
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reason="residuals not calculated properly for square tests (gh-29851)"
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)
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class TestLstsqMatrix(LstsqCases, MatrixTestCase):
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pass
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