ai-content-maker/.venv/Lib/site-packages/numpy/lib/function_base.pyi

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2024-05-03 04:18:51 +03:00
import sys
from collections.abc import Sequence, Iterator, Callable, Iterable
from typing import (
Literal as L,
Any,
TypeVar,
overload,
Protocol,
SupportsIndex,
SupportsInt,
)
if sys.version_info >= (3, 10):
from typing import TypeGuard
else:
from typing_extensions import TypeGuard
from numpy import (
vectorize as vectorize,
ufunc,
generic,
floating,
complexfloating,
intp,
float64,
complex128,
timedelta64,
datetime64,
object_,
_OrderKACF,
)
from numpy._typing import (
NDArray,
ArrayLike,
DTypeLike,
_ShapeLike,
_ScalarLike_co,
_DTypeLike,
_ArrayLike,
_ArrayLikeInt_co,
_ArrayLikeFloat_co,
_ArrayLikeComplex_co,
_ArrayLikeTD64_co,
_ArrayLikeDT64_co,
_ArrayLikeObject_co,
_FloatLike_co,
_ComplexLike_co,
)
from numpy.core.function_base import (
add_newdoc as add_newdoc,
)
from numpy.core.multiarray import (
add_docstring as add_docstring,
bincount as bincount,
)
from numpy.core.umath import _add_newdoc_ufunc
_T = TypeVar("_T")
_T_co = TypeVar("_T_co", covariant=True)
_SCT = TypeVar("_SCT", bound=generic)
_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any])
_2Tuple = tuple[_T, _T]
class _TrimZerosSequence(Protocol[_T_co]):
def __len__(self) -> int: ...
def __getitem__(self, key: slice, /) -> _T_co: ...
def __iter__(self) -> Iterator[Any]: ...
class _SupportsWriteFlush(Protocol):
def write(self, s: str, /) -> object: ...
def flush(self) -> object: ...
__all__: list[str]
# NOTE: This is in reality a re-export of `np.core.umath._add_newdoc_ufunc`
def add_newdoc_ufunc(ufunc: ufunc, new_docstring: str, /) -> None: ...
@overload
def rot90(
m: _ArrayLike[_SCT],
k: int = ...,
axes: tuple[int, int] = ...,
) -> NDArray[_SCT]: ...
@overload
def rot90(
m: ArrayLike,
k: int = ...,
axes: tuple[int, int] = ...,
) -> NDArray[Any]: ...
@overload
def flip(m: _SCT, axis: None = ...) -> _SCT: ...
@overload
def flip(m: _ScalarLike_co, axis: None = ...) -> Any: ...
@overload
def flip(m: _ArrayLike[_SCT], axis: None | _ShapeLike = ...) -> NDArray[_SCT]: ...
@overload
def flip(m: ArrayLike, axis: None | _ShapeLike = ...) -> NDArray[Any]: ...
def iterable(y: object) -> TypeGuard[Iterable[Any]]: ...
@overload
def average(
a: _ArrayLikeFloat_co,
axis: None = ...,
weights: None | _ArrayLikeFloat_co= ...,
returned: L[False] = ...,
keepdims: L[False] = ...,
) -> floating[Any]: ...
@overload
def average(
a: _ArrayLikeComplex_co,
axis: None = ...,
weights: None | _ArrayLikeComplex_co = ...,
returned: L[False] = ...,
keepdims: L[False] = ...,
) -> complexfloating[Any, Any]: ...
@overload
def average(
a: _ArrayLikeObject_co,
axis: None = ...,
weights: None | Any = ...,
returned: L[False] = ...,
keepdims: L[False] = ...,
) -> Any: ...
@overload
def average(
a: _ArrayLikeFloat_co,
axis: None = ...,
weights: None | _ArrayLikeFloat_co= ...,
returned: L[True] = ...,
keepdims: L[False] = ...,
) -> _2Tuple[floating[Any]]: ...
@overload
def average(
a: _ArrayLikeComplex_co,
axis: None = ...,
weights: None | _ArrayLikeComplex_co = ...,
returned: L[True] = ...,
keepdims: L[False] = ...,
) -> _2Tuple[complexfloating[Any, Any]]: ...
@overload
def average(
a: _ArrayLikeObject_co,
axis: None = ...,
weights: None | Any = ...,
returned: L[True] = ...,
keepdims: L[False] = ...,
) -> _2Tuple[Any]: ...
@overload
def average(
a: _ArrayLikeComplex_co | _ArrayLikeObject_co,
axis: None | _ShapeLike = ...,
weights: None | Any = ...,
returned: L[False] = ...,
keepdims: bool = ...,
) -> Any: ...
@overload
def average(
a: _ArrayLikeComplex_co | _ArrayLikeObject_co,
axis: None | _ShapeLike = ...,
weights: None | Any = ...,
returned: L[True] = ...,
keepdims: bool = ...,
) -> _2Tuple[Any]: ...
@overload
def asarray_chkfinite(
a: _ArrayLike[_SCT],
dtype: None = ...,
order: _OrderKACF = ...,
) -> NDArray[_SCT]: ...
@overload
def asarray_chkfinite(
a: object,
dtype: None = ...,
order: _OrderKACF = ...,
) -> NDArray[Any]: ...
@overload
def asarray_chkfinite(
a: Any,
dtype: _DTypeLike[_SCT],
order: _OrderKACF = ...,
) -> NDArray[_SCT]: ...
@overload
def asarray_chkfinite(
a: Any,
dtype: DTypeLike,
order: _OrderKACF = ...,
) -> NDArray[Any]: ...
# TODO: Use PEP 612 `ParamSpec` once mypy supports `Concatenate`
# xref python/mypy#8645
@overload
def piecewise(
x: _ArrayLike[_SCT],
condlist: ArrayLike,
funclist: Sequence[Any | Callable[..., Any]],
*args: Any,
**kw: Any,
) -> NDArray[_SCT]: ...
@overload
def piecewise(
x: ArrayLike,
condlist: ArrayLike,
funclist: Sequence[Any | Callable[..., Any]],
*args: Any,
**kw: Any,
) -> NDArray[Any]: ...
def select(
condlist: Sequence[ArrayLike],
choicelist: Sequence[ArrayLike],
default: ArrayLike = ...,
) -> NDArray[Any]: ...
@overload
def copy(
a: _ArrayType,
order: _OrderKACF,
subok: L[True],
) -> _ArrayType: ...
@overload
def copy(
a: _ArrayType,
order: _OrderKACF = ...,
*,
subok: L[True],
) -> _ArrayType: ...
@overload
def copy(
a: _ArrayLike[_SCT],
order: _OrderKACF = ...,
subok: L[False] = ...,
) -> NDArray[_SCT]: ...
@overload
def copy(
a: ArrayLike,
order: _OrderKACF = ...,
subok: L[False] = ...,
) -> NDArray[Any]: ...
def gradient(
f: ArrayLike,
*varargs: ArrayLike,
axis: None | _ShapeLike = ...,
edge_order: L[1, 2] = ...,
) -> Any: ...
@overload
def diff(
a: _T,
n: L[0],
axis: SupportsIndex = ...,
prepend: ArrayLike = ...,
append: ArrayLike = ...,
) -> _T: ...
@overload
def diff(
a: ArrayLike,
n: int = ...,
axis: SupportsIndex = ...,
prepend: ArrayLike = ...,
append: ArrayLike = ...,
) -> NDArray[Any]: ...
@overload
def interp(
x: _ArrayLikeFloat_co,
xp: _ArrayLikeFloat_co,
fp: _ArrayLikeFloat_co,
left: None | _FloatLike_co = ...,
right: None | _FloatLike_co = ...,
period: None | _FloatLike_co = ...,
) -> NDArray[float64]: ...
@overload
def interp(
x: _ArrayLikeFloat_co,
xp: _ArrayLikeFloat_co,
fp: _ArrayLikeComplex_co,
left: None | _ComplexLike_co = ...,
right: None | _ComplexLike_co = ...,
period: None | _FloatLike_co = ...,
) -> NDArray[complex128]: ...
@overload
def angle(z: _ComplexLike_co, deg: bool = ...) -> floating[Any]: ...
@overload
def angle(z: object_, deg: bool = ...) -> Any: ...
@overload
def angle(z: _ArrayLikeComplex_co, deg: bool = ...) -> NDArray[floating[Any]]: ...
@overload
def angle(z: _ArrayLikeObject_co, deg: bool = ...) -> NDArray[object_]: ...
@overload
def unwrap(
p: _ArrayLikeFloat_co,
discont: None | float = ...,
axis: int = ...,
*,
period: float = ...,
) -> NDArray[floating[Any]]: ...
@overload
def unwrap(
p: _ArrayLikeObject_co,
discont: None | float = ...,
axis: int = ...,
*,
period: float = ...,
) -> NDArray[object_]: ...
def sort_complex(a: ArrayLike) -> NDArray[complexfloating[Any, Any]]: ...
def trim_zeros(
filt: _TrimZerosSequence[_T],
trim: L["f", "b", "fb", "bf"] = ...,
) -> _T: ...
@overload
def extract(condition: ArrayLike, arr: _ArrayLike[_SCT]) -> NDArray[_SCT]: ...
@overload
def extract(condition: ArrayLike, arr: ArrayLike) -> NDArray[Any]: ...
def place(arr: NDArray[Any], mask: ArrayLike, vals: Any) -> None: ...
def disp(
mesg: object,
device: None | _SupportsWriteFlush = ...,
linefeed: bool = ...,
) -> None: ...
@overload
def cov(
m: _ArrayLikeFloat_co,
y: None | _ArrayLikeFloat_co = ...,
rowvar: bool = ...,
bias: bool = ...,
ddof: None | SupportsIndex | SupportsInt = ...,
fweights: None | ArrayLike = ...,
aweights: None | ArrayLike = ...,
*,
dtype: None = ...,
) -> NDArray[floating[Any]]: ...
@overload
def cov(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
bias: bool = ...,
ddof: None | SupportsIndex | SupportsInt = ...,
fweights: None | ArrayLike = ...,
aweights: None | ArrayLike = ...,
*,
dtype: None = ...,
) -> NDArray[complexfloating[Any, Any]]: ...
@overload
def cov(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
bias: bool = ...,
ddof: None | SupportsIndex | SupportsInt = ...,
fweights: None | ArrayLike = ...,
aweights: None | ArrayLike = ...,
*,
dtype: _DTypeLike[_SCT],
) -> NDArray[_SCT]: ...
@overload
def cov(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
bias: bool = ...,
ddof: None | SupportsIndex | SupportsInt = ...,
fweights: None | ArrayLike = ...,
aweights: None | ArrayLike = ...,
*,
dtype: DTypeLike,
) -> NDArray[Any]: ...
# NOTE `bias` and `ddof` have been deprecated
@overload
def corrcoef(
m: _ArrayLikeFloat_co,
y: None | _ArrayLikeFloat_co = ...,
rowvar: bool = ...,
*,
dtype: None = ...,
) -> NDArray[floating[Any]]: ...
@overload
def corrcoef(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
*,
dtype: None = ...,
) -> NDArray[complexfloating[Any, Any]]: ...
@overload
def corrcoef(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
*,
dtype: _DTypeLike[_SCT],
) -> NDArray[_SCT]: ...
@overload
def corrcoef(
m: _ArrayLikeComplex_co,
y: None | _ArrayLikeComplex_co = ...,
rowvar: bool = ...,
*,
dtype: DTypeLike,
) -> NDArray[Any]: ...
def blackman(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
def bartlett(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
def hanning(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
def hamming(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
def i0(x: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ...
def kaiser(
M: _FloatLike_co,
beta: _FloatLike_co,
) -> NDArray[floating[Any]]: ...
@overload
def sinc(x: _FloatLike_co) -> floating[Any]: ...
@overload
def sinc(x: _ComplexLike_co) -> complexfloating[Any, Any]: ...
@overload
def sinc(x: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ...
@overload
def sinc(x: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ...
# NOTE: Deprecated
# def msort(a: ArrayLike) -> NDArray[Any]: ...
@overload
def median(
a: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
keepdims: L[False] = ...,
) -> floating[Any]: ...
@overload
def median(
a: _ArrayLikeComplex_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
keepdims: L[False] = ...,
) -> complexfloating[Any, Any]: ...
@overload
def median(
a: _ArrayLikeTD64_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
keepdims: L[False] = ...,
) -> timedelta64: ...
@overload
def median(
a: _ArrayLikeObject_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
keepdims: L[False] = ...,
) -> Any: ...
@overload
def median(
a: _ArrayLikeFloat_co | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
axis: None | _ShapeLike = ...,
out: None = ...,
overwrite_input: bool = ...,
keepdims: bool = ...,
) -> Any: ...
@overload
def median(
a: _ArrayLikeFloat_co | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
axis: None | _ShapeLike = ...,
out: _ArrayType = ...,
overwrite_input: bool = ...,
keepdims: bool = ...,
) -> _ArrayType: ...
_MethodKind = L[
"inverted_cdf",
"averaged_inverted_cdf",
"closest_observation",
"interpolated_inverted_cdf",
"hazen",
"weibull",
"linear",
"median_unbiased",
"normal_unbiased",
"lower",
"higher",
"midpoint",
"nearest",
]
@overload
def percentile(
a: _ArrayLikeFloat_co,
q: _FloatLike_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> floating[Any]: ...
@overload
def percentile(
a: _ArrayLikeComplex_co,
q: _FloatLike_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> complexfloating[Any, Any]: ...
@overload
def percentile(
a: _ArrayLikeTD64_co,
q: _FloatLike_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> timedelta64: ...
@overload
def percentile(
a: _ArrayLikeDT64_co,
q: _FloatLike_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> datetime64: ...
@overload
def percentile(
a: _ArrayLikeObject_co,
q: _FloatLike_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> Any: ...
@overload
def percentile(
a: _ArrayLikeFloat_co,
q: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> NDArray[floating[Any]]: ...
@overload
def percentile(
a: _ArrayLikeComplex_co,
q: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> NDArray[complexfloating[Any, Any]]: ...
@overload
def percentile(
a: _ArrayLikeTD64_co,
q: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> NDArray[timedelta64]: ...
@overload
def percentile(
a: _ArrayLikeDT64_co,
q: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> NDArray[datetime64]: ...
@overload
def percentile(
a: _ArrayLikeObject_co,
q: _ArrayLikeFloat_co,
axis: None = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: L[False] = ...,
) -> NDArray[object_]: ...
@overload
def percentile(
a: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
q: _ArrayLikeFloat_co,
axis: None | _ShapeLike = ...,
out: None = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: bool = ...,
) -> Any: ...
@overload
def percentile(
a: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
q: _ArrayLikeFloat_co,
axis: None | _ShapeLike = ...,
out: _ArrayType = ...,
overwrite_input: bool = ...,
method: _MethodKind = ...,
keepdims: bool = ...,
) -> _ArrayType: ...
# NOTE: Not an alias, but they do have identical signatures
# (that we can reuse)
quantile = percentile
# TODO: Returns a scalar for <= 1D array-likes; returns an ndarray otherwise
def trapz(
y: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
x: None | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co = ...,
dx: float = ...,
axis: SupportsIndex = ...,
) -> Any: ...
def meshgrid(
*xi: ArrayLike,
copy: bool = ...,
sparse: bool = ...,
indexing: L["xy", "ij"] = ...,
) -> list[NDArray[Any]]: ...
@overload
def delete(
arr: _ArrayLike[_SCT],
obj: slice | _ArrayLikeInt_co,
axis: None | SupportsIndex = ...,
) -> NDArray[_SCT]: ...
@overload
def delete(
arr: ArrayLike,
obj: slice | _ArrayLikeInt_co,
axis: None | SupportsIndex = ...,
) -> NDArray[Any]: ...
@overload
def insert(
arr: _ArrayLike[_SCT],
obj: slice | _ArrayLikeInt_co,
values: ArrayLike,
axis: None | SupportsIndex = ...,
) -> NDArray[_SCT]: ...
@overload
def insert(
arr: ArrayLike,
obj: slice | _ArrayLikeInt_co,
values: ArrayLike,
axis: None | SupportsIndex = ...,
) -> NDArray[Any]: ...
def append(
arr: ArrayLike,
values: ArrayLike,
axis: None | SupportsIndex = ...,
) -> NDArray[Any]: ...
@overload
def digitize(
x: _FloatLike_co,
bins: _ArrayLikeFloat_co,
right: bool = ...,
) -> intp: ...
@overload
def digitize(
x: _ArrayLikeFloat_co,
bins: _ArrayLikeFloat_co,
right: bool = ...,
) -> NDArray[intp]: ...