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- import builtins
- import sys
- import datetime as dt
- from abc import abstractmethod
- from types import TracebackType
- from contextlib import ContextDecorator
- from numpy.core._internal import _ctypes
- from numpy.typing import (
- ArrayLike,
- DTypeLike,
- _Shape,
- _ShapeLike,
- _CharLike,
- _BoolLike,
- _IntLike,
- _FloatLike,
- _ComplexLike,
- _NumberLike,
- _SupportsDType,
- _VoidDTypeLike,
- NBitBase,
- _64Bit,
- _32Bit,
- _16Bit,
- _8Bit,
- )
- from numpy.typing._callable import (
- _BoolOp,
- _BoolBitOp,
- _BoolSub,
- _BoolTrueDiv,
- _BoolMod,
- _BoolDivMod,
- _TD64Div,
- _IntTrueDiv,
- _UnsignedIntOp,
- _UnsignedIntBitOp,
- _UnsignedIntMod,
- _UnsignedIntDivMod,
- _SignedIntOp,
- _SignedIntBitOp,
- _SignedIntMod,
- _SignedIntDivMod,
- _FloatOp,
- _FloatMod,
- _FloatDivMod,
- _ComplexOp,
- _NumberOp,
- )
- from typing import (
- Any,
- ByteString,
- Callable,
- Container,
- Callable,
- Dict,
- Generic,
- IO,
- Iterable,
- List,
- Mapping,
- Optional,
- overload,
- Sequence,
- Sized,
- SupportsComplex,
- SupportsFloat,
- SupportsInt,
- Text,
- Tuple,
- Type,
- TypeVar,
- Union,
- )
- if sys.version_info >= (3, 8):
- from typing import Literal, Protocol, SupportsIndex, Final
- else:
- from typing_extensions import Literal, Protocol, Final
- class SupportsIndex(Protocol):
- def __index__(self) -> int: ...
- # Ensures that the stubs are picked up
- from numpy import (
- char as char,
- ctypeslib as ctypeslib,
- emath as emath,
- fft as fft,
- lib as lib,
- linalg as linalg,
- ma as ma,
- matrixlib as matrixlib,
- polynomial as polynomial,
- random as random,
- rec as rec,
- testing as testing,
- version as version,
- )
- from numpy.core.function_base import (
- linspace as linspace,
- logspace as logspace,
- geomspace as geomspace,
- )
- from numpy.core.fromnumeric import (
- take as take,
- reshape as reshape,
- choose as choose,
- repeat as repeat,
- put as put,
- swapaxes as swapaxes,
- transpose as transpose,
- partition as partition,
- argpartition as argpartition,
- sort as sort,
- argsort as argsort,
- argmax as argmax,
- argmin as argmin,
- searchsorted as searchsorted,
- resize as resize,
- squeeze as squeeze,
- diagonal as diagonal,
- trace as trace,
- ravel as ravel,
- nonzero as nonzero,
- shape as shape,
- compress as compress,
- clip as clip,
- sum as sum,
- all as all,
- any as any,
- cumsum as cumsum,
- ptp as ptp,
- amax as amax,
- amin as amin,
- prod as prod,
- cumprod as cumprod,
- ndim as ndim,
- size as size,
- around as around,
- mean as mean,
- std as std,
- var as var,
- )
- from numpy.core._asarray import (
- asarray as asarray,
- asanyarray as asanyarray,
- ascontiguousarray as ascontiguousarray,
- asfortranarray as asfortranarray,
- require as require,
- )
- from numpy.core._type_aliases import (
- sctypes as sctypes,
- sctypeDict as sctypeDict,
- )
- from numpy.core._ufunc_config import (
- seterr as seterr,
- geterr as geterr,
- setbufsize as setbufsize,
- getbufsize as getbufsize,
- seterrcall as seterrcall,
- geterrcall as geterrcall,
- _SupportsWrite,
- _ErrKind,
- _ErrFunc,
- _ErrDictOptional,
- )
- from numpy.core.numeric import (
- zeros_like as zeros_like,
- ones as ones,
- ones_like as ones_like,
- empty_like as empty_like,
- full as full,
- full_like as full_like,
- count_nonzero as count_nonzero,
- isfortran as isfortran,
- argwhere as argwhere,
- flatnonzero as flatnonzero,
- correlate as correlate,
- convolve as convolve,
- outer as outer,
- tensordot as tensordot,
- roll as roll,
- rollaxis as rollaxis,
- moveaxis as moveaxis,
- cross as cross,
- indices as indices,
- fromfunction as fromfunction,
- isscalar as isscalar,
- binary_repr as binary_repr,
- base_repr as base_repr,
- identity as identity,
- allclose as allclose,
- isclose as isclose,
- array_equal as array_equal,
- array_equiv as array_equiv,
- )
- from numpy.core.numerictypes import (
- maximum_sctype as maximum_sctype,
- issctype as issctype,
- obj2sctype as obj2sctype,
- issubclass_ as issubclass_,
- issubsctype as issubsctype,
- issubdtype as issubdtype,
- sctype2char as sctype2char,
- find_common_type as find_common_type,
- )
- from numpy.core.shape_base import (
- atleast_1d as atleast_1d,
- atleast_2d as atleast_2d,
- atleast_3d as atleast_3d,
- block as block,
- hstack as hstack,
- stack as stack,
- vstack as vstack,
- )
- __all__: List[str]
- __path__: List[str]
- __version__: str
- DataSource: Any
- MachAr: Any
- ScalarType: Any
- angle: Any
- append: Any
- apply_along_axis: Any
- apply_over_axes: Any
- arange: Any
- array2string: Any
- array_repr: Any
- array_split: Any
- array_str: Any
- asarray_chkfinite: Any
- asfarray: Any
- asmatrix: Any
- asscalar: Any
- average: Any
- bartlett: Any
- bincount: Any
- bitwise_not: Any
- blackman: Any
- bmat: Any
- bool8: Any
- broadcast: Any
- broadcast_arrays: Any
- broadcast_to: Any
- busday_count: Any
- busday_offset: Any
- busdaycalendar: Any
- byte: Any
- byte_bounds: Any
- bytes0: Any
- c_: Any
- can_cast: Any
- cast: Any
- cdouble: Any
- cfloat: Any
- chararray: Any
- clongdouble: Any
- clongfloat: Any
- column_stack: Any
- common_type: Any
- compare_chararrays: Any
- complex256: Any
- complex_: Any
- concatenate: Any
- conj: Any
- copy: Any
- copyto: Any
- corrcoef: Any
- cov: Any
- csingle: Any
- cumproduct: Any
- datetime_as_string: Any
- datetime_data: Any
- delete: Any
- deprecate: Any
- deprecate_with_doc: Any
- diag: Any
- diag_indices: Any
- diag_indices_from: Any
- diagflat: Any
- diff: Any
- digitize: Any
- disp: Any
- divide: Any
- dot: Any
- double: Any
- dsplit: Any
- dstack: Any
- ediff1d: Any
- einsum: Any
- einsum_path: Any
- expand_dims: Any
- extract: Any
- eye: Any
- fill_diagonal: Any
- finfo: Any
- fix: Any
- flip: Any
- fliplr: Any
- flipud: Any
- float128: Any
- float_: Any
- format_float_positional: Any
- format_float_scientific: Any
- format_parser: Any
- frombuffer: Any
- fromfile: Any
- fromiter: Any
- frompyfunc: Any
- fromregex: Any
- fromstring: Any
- genfromtxt: Any
- get_include: Any
- get_printoptions: Any
- geterrobj: Any
- gradient: Any
- half: Any
- hamming: Any
- hanning: Any
- histogram: Any
- histogram2d: Any
- histogram_bin_edges: Any
- histogramdd: Any
- hsplit: Any
- i0: Any
- iinfo: Any
- imag: Any
- in1d: Any
- index_exp: Any
- info: Any
- inner: Any
- insert: Any
- int0: Any
- int_: Any
- intc: Any
- interp: Any
- intersect1d: Any
- intp: Any
- is_busday: Any
- iscomplex: Any
- iscomplexobj: Any
- isin: Any
- isneginf: Any
- isposinf: Any
- isreal: Any
- isrealobj: Any
- iterable: Any
- ix_: Any
- kaiser: Any
- kron: Any
- lexsort: Any
- load: Any
- loads: Any
- loadtxt: Any
- longcomplex: Any
- longdouble: Any
- longfloat: Any
- longlong: Any
- lookfor: Any
- mafromtxt: Any
- mask_indices: Any
- mat: Any
- matrix: Any
- max: Any
- may_share_memory: Any
- median: Any
- memmap: Any
- meshgrid: Any
- mgrid: Any
- min: Any
- min_scalar_type: Any
- mintypecode: Any
- mod: Any
- msort: Any
- nan_to_num: Any
- nanargmax: Any
- nanargmin: Any
- nancumprod: Any
- nancumsum: Any
- nanmax: Any
- nanmean: Any
- nanmedian: Any
- nanmin: Any
- nanpercentile: Any
- nanprod: Any
- nanquantile: Any
- nanstd: Any
- nansum: Any
- nanvar: Any
- nbytes: Any
- ndenumerate: Any
- ndfromtxt: Any
- ndindex: Any
- nditer: Any
- nested_iters: Any
- newaxis: Any
- numarray: Any
- object0: Any
- ogrid: Any
- packbits: Any
- pad: Any
- percentile: Any
- piecewise: Any
- place: Any
- poly: Any
- poly1d: Any
- polyadd: Any
- polyder: Any
- polydiv: Any
- polyfit: Any
- polyint: Any
- polymul: Any
- polysub: Any
- polyval: Any
- printoptions: Any
- product: Any
- promote_types: Any
- put_along_axis: Any
- putmask: Any
- quantile: Any
- r_: Any
- ravel_multi_index: Any
- real: Any
- real_if_close: Any
- recarray: Any
- recfromcsv: Any
- recfromtxt: Any
- record: Any
- result_type: Any
- roots: Any
- rot90: Any
- round: Any
- round_: Any
- row_stack: Any
- s_: Any
- save: Any
- savetxt: Any
- savez: Any
- savez_compressed: Any
- select: Any
- set_printoptions: Any
- set_string_function: Any
- setdiff1d: Any
- seterrobj: Any
- setxor1d: Any
- shares_memory: Any
- short: Any
- show_config: Any
- sinc: Any
- single: Any
- singlecomplex: Any
- sort_complex: Any
- source: Any
- split: Any
- string_: Any
- take_along_axis: Any
- tile: Any
- trapz: Any
- tri: Any
- tril: Any
- tril_indices: Any
- tril_indices_from: Any
- trim_zeros: Any
- triu: Any
- triu_indices: Any
- triu_indices_from: Any
- typeDict: Any
- typecodes: Any
- typename: Any
- ubyte: Any
- uint: Any
- uint0: Any
- uintc: Any
- uintp: Any
- ulonglong: Any
- union1d: Any
- unique: Any
- unpackbits: Any
- unravel_index: Any
- unwrap: Any
- ushort: Any
- vander: Any
- vdot: Any
- vectorize: Any
- void0: Any
- vsplit: Any
- where: Any
- who: Any
- _NdArraySubClass = TypeVar("_NdArraySubClass", bound=ndarray)
- _DTypeScalar = TypeVar("_DTypeScalar", bound=generic)
- _ByteOrder = Literal["S", "<", ">", "=", "|", "L", "B", "N", "I"]
- class dtype(Generic[_DTypeScalar]):
- names: Optional[Tuple[str, ...]]
- # Overload for subclass of generic
- @overload
- def __new__(
- cls,
- dtype: Type[_DTypeScalar],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[_DTypeScalar]: ...
- # Overloads for string aliases, Python types, and some assorted
- # other special cases. Order is sometimes important because of the
- # subtype relationships
- #
- # bool < int < float < complex
- #
- # so we have to make sure the overloads for the narrowest type is
- # first.
- @overload
- def __new__(
- cls,
- dtype: Union[
- Type[bool],
- Literal[
- "?",
- "=?",
- "<?",
- ">?",
- "bool",
- "bool_",
- ],
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[bool_]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "uint8",
- "u1",
- "=u1",
- "<u1",
- ">u1",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[uint8]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "uint16",
- "u2",
- "=u2",
- "<u2",
- ">u2",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[uint16]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "uint32",
- "u4",
- "=u4",
- "<u4",
- ">u4",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[uint32]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "uint64",
- "u8",
- "=u8",
- "<u8",
- ">u8",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[uint64]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "int8",
- "i1",
- "=i1",
- "<i1",
- ">i1",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[int8]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "int16",
- "i2",
- "=i2",
- "<i2",
- ">i2",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[int16]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "int32",
- "i4",
- "=i4",
- "<i4",
- ">i4",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[int32]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "int64",
- "i8",
- "=i8",
- "<i8",
- ">i8",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[int64]: ...
- # "int"/int resolve to int_, which is system dependent and as of
- # now untyped. Long-term we'll do something fancier here.
- @overload
- def __new__(
- cls,
- dtype: Union[Type[int], Literal["int"]],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "float16",
- "f4",
- "=f4",
- "<f4",
- ">f4",
- "e",
- "=e",
- "<e",
- ">e",
- "half",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[float16]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "float32",
- "f4",
- "=f4",
- "<f4",
- ">f4",
- "f",
- "=f",
- "<f",
- ">f",
- "single",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[float32]: ...
- @overload
- def __new__(
- cls,
- dtype: Union[
- None,
- Type[float],
- Literal[
- "float64",
- "f8",
- "=f8",
- "<f8",
- ">f8",
- "d",
- "<d",
- ">d",
- "float",
- "double",
- "float_",
- ],
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[float64]: ...
- @overload
- def __new__(
- cls,
- dtype: Literal[
- "complex64",
- "c8",
- "=c8",
- "<c8",
- ">c8",
- "F",
- "=F",
- "<F",
- ">F",
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[complex64]: ...
- @overload
- def __new__(
- cls,
- dtype: Union[
- Type[complex],
- Literal[
- "complex128",
- "c16",
- "=c16",
- "<c16",
- ">c16",
- "D",
- "=D",
- "<D",
- ">D",
- ],
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[complex128]: ...
- @overload
- def __new__(
- cls,
- dtype: Union[
- Type[bytes],
- Literal[
- "S",
- "=S",
- "<S",
- ">S",
- "bytes",
- "bytes_",
- "bytes0",
- ],
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[bytes_]: ...
- @overload
- def __new__(
- cls,
- dtype: Union[
- Type[str],
- Literal[
- "U",
- "=U",
- # <U and >U intentionally not included; they are not
- # the same dtype and which one dtype("U") translates
- # to is platform-dependent.
- "str",
- "str_",
- "str0",
- ],
- ],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[str_]: ...
- # dtype of a dtype is the same dtype
- @overload
- def __new__(
- cls,
- dtype: dtype[_DTypeScalar],
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[_DTypeScalar]: ...
- # TODO: handle _SupportsDType better
- @overload
- def __new__(
- cls,
- dtype: _SupportsDType,
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[Any]: ...
- # Handle strings that can't be expressed as literals; i.e. s1, s2, ...
- @overload
- def __new__(
- cls,
- dtype: str,
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[Any]: ...
- # Catchall overload
- @overload
- def __new__(
- cls,
- dtype: _VoidDTypeLike,
- align: bool = ...,
- copy: bool = ...,
- ) -> dtype[void]: ...
- @overload
- def __getitem__(self: dtype[void], key: List[str]) -> dtype[void]: ...
- @overload
- def __getitem__(self: dtype[void], key: Union[str, int]) -> dtype[Any]: ...
- # NOTE: In the future 1-based multiplications will also yield `void` dtypes
- @overload
- def __mul__(self, value: Literal[0]) -> None: ... # type: ignore[misc]
- @overload
- def __mul__(self, value: Literal[1]) -> dtype[_DTypeScalar]: ...
- @overload
- def __mul__(self, value: int) -> dtype[void]: ...
- # NOTE: `__rmul__` seems to be broken when used in combination with
- # literals as of mypy 0.800. Set the return-type to `Any` for now.
- def __rmul__(self, value: int) -> Any: ...
- def __eq__(self, other: DTypeLike) -> bool: ...
- def __ne__(self, other: DTypeLike) -> bool: ...
- def __gt__(self, other: DTypeLike) -> bool: ...
- def __ge__(self, other: DTypeLike) -> bool: ...
- def __lt__(self, other: DTypeLike) -> bool: ...
- def __le__(self, other: DTypeLike) -> bool: ...
- @property
- def alignment(self) -> int: ...
- @property
- def base(self) -> dtype: ...
- @property
- def byteorder(self) -> str: ...
- @property
- def char(self) -> str: ...
- @property
- def descr(self) -> List[Union[Tuple[str, str], Tuple[str, str, _Shape]]]: ...
- @property
- def fields(
- self,
- ) -> Optional[Mapping[str, Union[Tuple[dtype, int], Tuple[dtype, int, Any]]]]: ...
- @property
- def flags(self) -> int: ...
- @property
- def hasobject(self) -> bool: ...
- @property
- def isbuiltin(self) -> int: ...
- @property
- def isnative(self) -> bool: ...
- @property
- def isalignedstruct(self) -> bool: ...
- @property
- def itemsize(self) -> int: ...
- @property
- def kind(self) -> str: ...
- @property
- def metadata(self) -> Optional[Mapping[str, Any]]: ...
- @property
- def name(self) -> str: ...
- @property
- def names(self) -> Optional[Tuple[str, ...]]: ...
- @property
- def num(self) -> int: ...
- @property
- def shape(self) -> _Shape: ...
- @property
- def ndim(self) -> int: ...
- @property
- def subdtype(self) -> Optional[Tuple[dtype, _Shape]]: ...
- def newbyteorder(self, __new_order: _ByteOrder = ...) -> dtype: ...
- # Leave str and type for end to avoid having to use `builtins.str`
- # everywhere. See https://github.com/python/mypy/issues/3775
- @property
- def str(self) -> builtins.str: ...
- @property
- def type(self) -> Type[generic]: ...
- _DType = dtype # to avoid name conflicts with ndarray.dtype
- class _flagsobj:
- aligned: bool
- updateifcopy: bool
- writeable: bool
- writebackifcopy: bool
- @property
- def behaved(self) -> bool: ...
- @property
- def c_contiguous(self) -> bool: ...
- @property
- def carray(self) -> bool: ...
- @property
- def contiguous(self) -> bool: ...
- @property
- def f_contiguous(self) -> bool: ...
- @property
- def farray(self) -> bool: ...
- @property
- def fnc(self) -> bool: ...
- @property
- def forc(self) -> bool: ...
- @property
- def fortran(self) -> bool: ...
- @property
- def num(self) -> int: ...
- @property
- def owndata(self) -> bool: ...
- def __getitem__(self, key: str) -> bool: ...
- def __setitem__(self, key: str, value: bool) -> None: ...
- _ArrayLikeInt = Union[
- int,
- integer,
- Sequence[Union[int, integer]],
- Sequence[Sequence[Any]], # TODO: wait for support for recursive types
- ndarray
- ]
- _FlatIterSelf = TypeVar("_FlatIterSelf", bound=flatiter)
- class flatiter(Generic[_ArraySelf]):
- @property
- def base(self) -> _ArraySelf: ...
- @property
- def coords(self) -> _Shape: ...
- @property
- def index(self) -> int: ...
- def copy(self) -> _ArraySelf: ...
- def __iter__(self: _FlatIterSelf) -> _FlatIterSelf: ...
- def __next__(self) -> generic: ...
- def __len__(self) -> int: ...
- @overload
- def __getitem__(self, key: Union[int, integer]) -> generic: ...
- @overload
- def __getitem__(
- self, key: Union[_ArrayLikeInt, slice, ellipsis],
- ) -> _ArraySelf: ...
- def __array__(self, __dtype: DTypeLike = ...) -> ndarray: ...
- _OrderKACF = Optional[Literal["K", "A", "C", "F"]]
- _OrderACF = Optional[Literal["A", "C", "F"]]
- _OrderCF = Optional[Literal["C", "F"]]
- _ModeKind = Literal["raise", "wrap", "clip"]
- _PartitionKind = Literal["introselect"]
- _SortKind = Literal["quicksort", "mergesort", "heapsort", "stable"]
- _SortSide = Literal["left", "right"]
- _ArrayLikeBool = Union[_BoolLike, Sequence[_BoolLike], ndarray]
- _ArrayLikeIntOrBool = Union[
- _IntLike,
- _BoolLike,
- ndarray,
- Sequence[_IntLike],
- Sequence[_BoolLike],
- Sequence[Sequence[Any]], # TODO: wait for support for recursive types
- ]
- _ArraySelf = TypeVar("_ArraySelf", bound=_ArrayOrScalarCommon)
- class _ArrayOrScalarCommon:
- @property
- def T(self: _ArraySelf) -> _ArraySelf: ...
- @property
- def data(self) -> memoryview: ...
- @property
- def flags(self) -> _flagsobj: ...
- @property
- def itemsize(self) -> int: ...
- @property
- def nbytes(self) -> int: ...
- def __array__(self, __dtype: DTypeLike = ...) -> ndarray: ...
- def __bool__(self) -> bool: ...
- def __bytes__(self) -> bytes: ...
- def __str__(self) -> str: ...
- def __repr__(self) -> str: ...
- def __copy__(self: _ArraySelf) -> _ArraySelf: ...
- def __deepcopy__(self: _ArraySelf, __memo: Optional[dict] = ...) -> _ArraySelf: ...
- def __lt__(self, other): ...
- def __le__(self, other): ...
- def __eq__(self, other): ...
- def __ne__(self, other): ...
- def __gt__(self, other): ...
- def __ge__(self, other): ...
- def astype(
- self: _ArraySelf,
- dtype: DTypeLike,
- order: _OrderKACF = ...,
- casting: _Casting = ...,
- subok: bool = ...,
- copy: bool = ...,
- ) -> _ArraySelf: ...
- def copy(self: _ArraySelf, order: _OrderKACF = ...) -> _ArraySelf: ...
- def dump(self, file: str) -> None: ...
- def dumps(self) -> bytes: ...
- def flatten(self, order: _OrderKACF = ...) -> ndarray: ...
- def getfield(
- self: _ArraySelf, dtype: DTypeLike, offset: int = ...
- ) -> _ArraySelf: ...
- def ravel(self, order: _OrderKACF = ...) -> ndarray: ...
- @overload
- def reshape(
- self, __shape: _ShapeLike, *, order: _OrderACF = ...
- ) -> ndarray: ...
- @overload
- def reshape(
- self, *shape: SupportsIndex, order: _OrderACF = ...
- ) -> ndarray: ...
- def tobytes(self, order: _OrderKACF = ...) -> bytes: ...
- # NOTE: `tostring()` is deprecated and therefore excluded
- # def tostring(self, order=...): ...
- def tofile(
- self, fid: Union[IO[bytes], str], sep: str = ..., format: str = ...
- ) -> None: ...
- # generics and 0d arrays return builtin scalars
- def tolist(self) -> Any: ...
- @overload
- def view(self, type: Type[_NdArraySubClass]) -> _NdArraySubClass: ...
- @overload
- def view(self: _ArraySelf, dtype: DTypeLike = ...) -> _ArraySelf: ...
- @overload
- def view(
- self, dtype: DTypeLike, type: Type[_NdArraySubClass]
- ) -> _NdArraySubClass: ...
- # TODO: Add proper signatures
- def __getitem__(self, key) -> Any: ...
- @property
- def __array_interface__(self): ...
- @property
- def __array_priority__(self): ...
- @property
- def __array_struct__(self): ...
- def __array_wrap__(array, context=...): ...
- def __setstate__(self, __state): ...
- # a `bool_` is returned when `keepdims=True` and `self` is a 0d array
- @overload
- def all(
- self,
- axis: None = ...,
- out: None = ...,
- keepdims: Literal[False] = ...,
- ) -> bool_: ...
- @overload
- def all(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: None = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def all(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def any(
- self,
- axis: None = ...,
- out: None = ...,
- keepdims: Literal[False] = ...,
- ) -> bool_: ...
- @overload
- def any(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: None = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def any(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def argmax(
- self,
- axis: None = ...,
- out: None = ...,
- ) -> signedinteger[Any]: ...
- @overload
- def argmax(
- self,
- axis: _ShapeLike = ...,
- out: None = ...,
- ) -> Any: ...
- @overload
- def argmax(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def argmin(
- self,
- axis: None = ...,
- out: None = ...,
- ) -> signedinteger[Any]: ...
- @overload
- def argmin(
- self,
- axis: _ShapeLike = ...,
- out: None = ...,
- ) -> Any: ...
- @overload
- def argmin(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- def argsort(
- self,
- axis: Optional[SupportsIndex] = ...,
- kind: Optional[_SortKind] = ...,
- order: Union[None, str, Sequence[str]] = ...,
- ) -> ndarray: ...
- @overload
- def choose(
- self,
- choices: ArrayLike,
- out: None = ...,
- mode: _ModeKind = ...,
- ) -> ndarray: ...
- @overload
- def choose(
- self,
- choices: ArrayLike,
- out: _NdArraySubClass = ...,
- mode: _ModeKind = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def clip(
- self,
- min: ArrayLike = ...,
- max: Optional[ArrayLike] = ...,
- out: None = ...,
- **kwargs: Any,
- ) -> Any: ...
- @overload
- def clip(
- self,
- min: None = ...,
- max: ArrayLike = ...,
- out: None = ...,
- **kwargs: Any,
- ) -> Any: ...
- @overload
- def clip(
- self,
- min: ArrayLike = ...,
- max: Optional[ArrayLike] = ...,
- out: _NdArraySubClass = ...,
- **kwargs: Any,
- ) -> _NdArraySubClass: ...
- @overload
- def clip(
- self,
- min: None = ...,
- max: ArrayLike = ...,
- out: _NdArraySubClass = ...,
- **kwargs: Any,
- ) -> _NdArraySubClass: ...
- @overload
- def compress(
- self,
- a: ArrayLike,
- axis: Optional[SupportsIndex] = ...,
- out: None = ...,
- ) -> ndarray: ...
- @overload
- def compress(
- self,
- a: ArrayLike,
- axis: Optional[SupportsIndex] = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- def conj(self: _ArraySelf) -> _ArraySelf: ...
- def conjugate(self: _ArraySelf) -> _ArraySelf: ...
- @overload
- def cumprod(
- self,
- axis: Optional[SupportsIndex] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- ) -> ndarray: ...
- @overload
- def cumprod(
- self,
- axis: Optional[SupportsIndex] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def cumsum(
- self,
- axis: Optional[SupportsIndex] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- ) -> ndarray: ...
- @overload
- def cumsum(
- self,
- axis: Optional[SupportsIndex] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def max(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: None = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> Any: ...
- @overload
- def max(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def mean(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def mean(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def min(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: None = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> Any: ...
- @overload
- def min(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> _NdArraySubClass: ...
- def newbyteorder(
- self: _ArraySelf,
- __new_order: _ByteOrder = ...,
- ) -> _ArraySelf: ...
- @overload
- def prod(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> Any: ...
- @overload
- def prod(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def ptp(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: None = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def ptp(
- self,
- axis: Optional[_ShapeLike] = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- def repeat(
- self,
- repeats: _ArrayLikeIntOrBool,
- axis: Optional[SupportsIndex] = ...,
- ) -> ndarray: ...
- @overload
- def round(
- self: _ArraySelf,
- decimals: SupportsIndex = ...,
- out: None = ...,
- ) -> _ArraySelf: ...
- @overload
- def round(
- self,
- decimals: SupportsIndex = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def std(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- ddof: int = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def std(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- ddof: int = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def sum(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> Any: ...
- @overload
- def sum(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- keepdims: bool = ...,
- initial: _NumberLike = ...,
- where: _ArrayLikeBool = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def take(
- self,
- indices: Union[_IntLike, _BoolLike],
- axis: Optional[SupportsIndex] = ...,
- out: None = ...,
- mode: _ModeKind = ...,
- ) -> Any: ...
- @overload
- def take(
- self,
- indices: _ArrayLikeIntOrBool,
- axis: Optional[SupportsIndex] = ...,
- out: None = ...,
- mode: _ModeKind = ...,
- ) -> ndarray: ...
- @overload
- def take(
- self,
- indices: _ArrayLikeIntOrBool,
- axis: Optional[SupportsIndex] = ...,
- out: _NdArraySubClass = ...,
- mode: _ModeKind = ...,
- ) -> _NdArraySubClass: ...
- @overload
- def var(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- ddof: int = ...,
- keepdims: bool = ...,
- ) -> Any: ...
- @overload
- def var(
- self,
- axis: Optional[_ShapeLike] = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- ddof: int = ...,
- keepdims: bool = ...,
- ) -> _NdArraySubClass: ...
- _BufferType = Union[ndarray, bytes, bytearray, memoryview]
- _Casting = Literal["no", "equiv", "safe", "same_kind", "unsafe"]
- class ndarray(_ArrayOrScalarCommon, Iterable, Sized, Container):
- @property
- def base(self) -> Optional[ndarray]: ...
- @property
- def ndim(self) -> int: ...
- @property
- def size(self) -> int: ...
- @property
- def real(self: _ArraySelf) -> _ArraySelf: ...
- @real.setter
- def real(self, value: ArrayLike) -> None: ...
- @property
- def imag(self: _ArraySelf) -> _ArraySelf: ...
- @imag.setter
- def imag(self, value: ArrayLike) -> None: ...
- def __new__(
- cls: Type[_ArraySelf],
- shape: _ShapeLike,
- dtype: DTypeLike = ...,
- buffer: _BufferType = ...,
- offset: int = ...,
- strides: _ShapeLike = ...,
- order: _OrderKACF = ...,
- ) -> _ArraySelf: ...
- @property
- def dtype(self) -> _DType: ...
- @property
- def ctypes(self) -> _ctypes: ...
- @property
- def shape(self) -> _Shape: ...
- @shape.setter
- def shape(self, value: _ShapeLike): ...
- @property
- def strides(self) -> _Shape: ...
- @strides.setter
- def strides(self, value: _ShapeLike): ...
- def byteswap(self: _ArraySelf, inplace: bool = ...) -> _ArraySelf: ...
- def fill(self, value: Any) -> None: ...
- @property
- def flat(self: _ArraySelf) -> flatiter[_ArraySelf]: ...
- @overload
- def item(self, *args: SupportsIndex) -> Any: ...
- @overload
- def item(self, __args: Tuple[SupportsIndex, ...]) -> Any: ...
- @overload
- def itemset(self, __value: Any) -> None: ...
- @overload
- def itemset(self, __item: _ShapeLike, __value: Any) -> None: ...
- @overload
- def resize(self, __new_shape: _ShapeLike, *, refcheck: bool = ...) -> None: ...
- @overload
- def resize(self, *new_shape: SupportsIndex, refcheck: bool = ...) -> None: ...
- def setflags(
- self, write: bool = ..., align: bool = ..., uic: bool = ...
- ) -> None: ...
- def squeeze(
- self: _ArraySelf, axis: Union[SupportsIndex, Tuple[SupportsIndex, ...]] = ...
- ) -> _ArraySelf: ...
- def swapaxes(self: _ArraySelf, axis1: SupportsIndex, axis2: SupportsIndex) -> _ArraySelf: ...
- @overload
- def transpose(self: _ArraySelf, __axes: _ShapeLike) -> _ArraySelf: ...
- @overload
- def transpose(self: _ArraySelf, *axes: SupportsIndex) -> _ArraySelf: ...
- def argpartition(
- self,
- kth: _ArrayLikeIntOrBool,
- axis: Optional[SupportsIndex] = ...,
- kind: _PartitionKind = ...,
- order: Union[None, str, Sequence[str]] = ...,
- ) -> ndarray: ...
- def diagonal(
- self: _ArraySelf,
- offset: SupportsIndex = ...,
- axis1: SupportsIndex = ...,
- axis2: SupportsIndex = ...,
- ) -> _ArraySelf: ...
- @overload
- def dot(self, b: ArrayLike, out: None = ...) -> Any: ...
- @overload
- def dot(self, b: ArrayLike, out: _NdArraySubClass = ...) -> _NdArraySubClass: ...
- # `nonzero()` is deprecated for 0d arrays/generics
- def nonzero(self) -> Tuple[ndarray, ...]: ...
- def partition(
- self,
- kth: _ArrayLikeIntOrBool,
- axis: SupportsIndex = ...,
- kind: _PartitionKind = ...,
- order: Union[None, str, Sequence[str]] = ...,
- ) -> None: ...
- # `put` is technically available to `generic`,
- # but is pointless as `generic`s are immutable
- def put(
- self, ind: _ArrayLikeIntOrBool, v: ArrayLike, mode: _ModeKind = ...
- ) -> None: ...
- def searchsorted(
- self, # >= 1D array
- v: ArrayLike,
- side: _SortSide = ...,
- sorter: Optional[_ArrayLikeIntOrBool] = ..., # 1D int array
- ) -> ndarray: ...
- def setfield(
- self, val: ArrayLike, dtype: DTypeLike, offset: SupportsIndex = ...
- ) -> None: ...
- def sort(
- self,
- axis: SupportsIndex = ...,
- kind: Optional[_SortKind] = ...,
- order: Union[None, str, Sequence[str]] = ...,
- ) -> None: ...
- @overload
- def trace(
- self, # >= 2D array
- offset: SupportsIndex = ...,
- axis1: SupportsIndex = ...,
- axis2: SupportsIndex = ...,
- dtype: DTypeLike = ...,
- out: None = ...,
- ) -> Any: ...
- @overload
- def trace(
- self, # >= 2D array
- offset: SupportsIndex = ...,
- axis1: SupportsIndex = ...,
- axis2: SupportsIndex = ...,
- dtype: DTypeLike = ...,
- out: _NdArraySubClass = ...,
- ) -> _NdArraySubClass: ...
- # Many of these special methods are irrelevant currently, since protocols
- # aren't supported yet. That said, I'm adding them for completeness.
- # https://docs.python.org/3/reference/datamodel.html
- def __int__(self) -> int: ...
- def __float__(self) -> float: ...
- def __complex__(self) -> complex: ...
- def __len__(self) -> int: ...
- def __setitem__(self, key, value): ...
- def __iter__(self) -> Any: ...
- def __contains__(self, key) -> bool: ...
- def __index__(self) -> int: ...
- def __matmul__(self, other: ArrayLike) -> Any: ...
- # NOTE: `ndarray` does not implement `__imatmul__`
- def __rmatmul__(self, other: ArrayLike) -> Any: ...
- def __neg__(self: _ArraySelf) -> Any: ...
- def __pos__(self: _ArraySelf) -> Any: ...
- def __abs__(self: _ArraySelf) -> Any: ...
- def __mod__(self, other: ArrayLike) -> Any: ...
- def __rmod__(self, other: ArrayLike) -> Any: ...
- def __divmod__(self, other: ArrayLike) -> Tuple[Any, Any]: ...
- def __rdivmod__(self, other: ArrayLike) -> Tuple[Any, Any]: ...
- def __add__(self, other: ArrayLike) -> Any: ...
- def __radd__(self, other: ArrayLike) -> Any: ...
- def __sub__(self, other: ArrayLike) -> Any: ...
- def __rsub__(self, other: ArrayLike) -> Any: ...
- def __mul__(self, other: ArrayLike) -> Any: ...
- def __rmul__(self, other: ArrayLike) -> Any: ...
- def __floordiv__(self, other: ArrayLike) -> Any: ...
- def __rfloordiv__(self, other: ArrayLike) -> Any: ...
- def __pow__(self, other: ArrayLike) -> Any: ...
- def __rpow__(self, other: ArrayLike) -> Any: ...
- def __truediv__(self, other: ArrayLike) -> Any: ...
- def __rtruediv__(self, other: ArrayLike) -> Any: ...
- def __invert__(self: _ArraySelf) -> Any: ...
- def __lshift__(self, other: ArrayLike) -> Any: ...
- def __rlshift__(self, other: ArrayLike) -> Any: ...
- def __rshift__(self, other: ArrayLike) -> Any: ...
- def __rrshift__(self, other: ArrayLike) -> Any: ...
- def __and__(self, other: ArrayLike) -> Any: ...
- def __rand__(self, other: ArrayLike) -> Any: ...
- def __xor__(self, other: ArrayLike) -> Any: ...
- def __rxor__(self, other: ArrayLike) -> Any: ...
- def __or__(self, other: ArrayLike) -> Any: ...
- def __ror__(self, other: ArrayLike) -> Any: ...
- # `np.generic` does not support inplace operations
- def __iadd__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __isub__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __imul__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __itruediv__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __ifloordiv__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __ipow__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __imod__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __ilshift__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __irshift__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __iand__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __ixor__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- def __ior__(self: _ArraySelf, other: ArrayLike) -> _ArraySelf: ...
- # NOTE: while `np.generic` is not technically an instance of `ABCMeta`,
- # the `@abstractmethod` decorator is herein used to (forcefully) deny
- # the creation of `np.generic` instances.
- # The `# type: ignore` comments are necessary to silence mypy errors regarding
- # the missing `ABCMeta` metaclass.
- # See https://github.com/numpy/numpy-stubs/pull/80 for more details.
- _ScalarType = TypeVar("_ScalarType", bound=generic)
- _NBit_co = TypeVar("_NBit_co", covariant=True, bound=NBitBase)
- _NBit_co2 = TypeVar("_NBit_co2", covariant=True, bound=NBitBase)
- class generic(_ArrayOrScalarCommon):
- @abstractmethod
- def __init__(self, *args: Any, **kwargs: Any) -> None: ...
- @property
- def base(self) -> None: ...
- @property
- def dtype(self: _ScalarType) -> _DType[_ScalarType]: ...
- @property
- def ndim(self) -> Literal[0]: ...
- @property
- def size(self) -> Literal[1]: ...
- @property
- def shape(self) -> Tuple[()]: ...
- @property
- def strides(self) -> Tuple[()]: ...
- def byteswap(self: _ScalarType, inplace: Literal[False] = ...) -> _ScalarType: ...
- @property
- def flat(self) -> flatiter[ndarray]: ...
- def item(
- self: _ScalarType,
- __args: Union[Literal[0], Tuple[()], Tuple[Literal[0]]] = ...,
- ) -> Any: ...
- def squeeze(
- self: _ScalarType, axis: Union[Literal[0], Tuple[()]] = ...
- ) -> _ScalarType: ...
- def transpose(self: _ScalarType, __axes: Tuple[()] = ...) -> _ScalarType: ...
- class number(generic, Generic[_NBit_co]): # type: ignore
- @property
- def real(self: _ArraySelf) -> _ArraySelf: ...
- @property
- def imag(self: _ArraySelf) -> _ArraySelf: ...
- def __int__(self) -> int: ...
- def __float__(self) -> float: ...
- def __complex__(self) -> complex: ...
- def __neg__(self: _ArraySelf) -> _ArraySelf: ...
- def __pos__(self: _ArraySelf) -> _ArraySelf: ...
- def __abs__(self: _ArraySelf) -> _ArraySelf: ...
- # Ensure that objects annotated as `number` support arithmetic operations
- __add__: _NumberOp
- __radd__: _NumberOp
- __sub__: _NumberOp
- __rsub__: _NumberOp
- __mul__: _NumberOp
- __rmul__: _NumberOp
- __floordiv__: _NumberOp
- __rfloordiv__: _NumberOp
- __pow__: _NumberOp
- __rpow__: _NumberOp
- __truediv__: _NumberOp
- __rtruediv__: _NumberOp
- class bool_(generic):
- def __init__(self, __value: object = ...) -> None: ...
- @property
- def real(self: _ArraySelf) -> _ArraySelf: ...
- @property
- def imag(self: _ArraySelf) -> _ArraySelf: ...
- def __int__(self) -> int: ...
- def __float__(self) -> float: ...
- def __complex__(self) -> complex: ...
- def __abs__(self: _ArraySelf) -> _ArraySelf: ...
- __add__: _BoolOp[bool_]
- __radd__: _BoolOp[bool_]
- __sub__: _BoolSub
- __rsub__: _BoolSub
- __mul__: _BoolOp[bool_]
- __rmul__: _BoolOp[bool_]
- __floordiv__: _BoolOp[int8]
- __rfloordiv__: _BoolOp[int8]
- __pow__: _BoolOp[int8]
- __rpow__: _BoolOp[int8]
- __truediv__: _BoolTrueDiv
- __rtruediv__: _BoolTrueDiv
- def __invert__(self) -> bool_: ...
- __lshift__: _BoolBitOp[int8]
- __rlshift__: _BoolBitOp[int8]
- __rshift__: _BoolBitOp[int8]
- __rrshift__: _BoolBitOp[int8]
- __and__: _BoolBitOp[bool_]
- __rand__: _BoolBitOp[bool_]
- __xor__: _BoolBitOp[bool_]
- __rxor__: _BoolBitOp[bool_]
- __or__: _BoolBitOp[bool_]
- __ror__: _BoolBitOp[bool_]
- __mod__: _BoolMod
- __rmod__: _BoolMod
- __divmod__: _BoolDivMod
- __rdivmod__: _BoolDivMod
- class object_(generic):
- def __init__(self, __value: object = ...) -> None: ...
- @property
- def real(self: _ArraySelf) -> _ArraySelf: ...
- @property
- def imag(self: _ArraySelf) -> _ArraySelf: ...
- # The `datetime64` constructors requires an object with the three attributes below,
- # and thus supports datetime duck typing
- class _DatetimeScalar(Protocol):
- @property
- def day(self) -> int: ...
- @property
- def month(self) -> int: ...
- @property
- def year(self) -> int: ...
- class datetime64(generic):
- @overload
- def __init__(
- self,
- __value: Union[None, datetime64, _CharLike, _DatetimeScalar] = ...,
- __format: Union[_CharLike, Tuple[_CharLike, _IntLike]] = ...,
- ) -> None: ...
- @overload
- def __init__(
- self,
- __value: int,
- __format: Union[_CharLike, Tuple[_CharLike, _IntLike]]
- ) -> None: ...
- def __add__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> datetime64: ...
- def __radd__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> datetime64: ...
- @overload
- def __sub__(self, other: datetime64) -> timedelta64: ...
- @overload
- def __sub__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> datetime64: ...
- def __rsub__(self, other: datetime64) -> timedelta64: ...
- # Support for `__index__` was added in python 3.8 (bpo-20092)
- if sys.version_info >= (3, 8):
- _IntValue = Union[SupportsInt, _CharLike, SupportsIndex]
- _FloatValue = Union[None, _CharLike, SupportsFloat, SupportsIndex]
- _ComplexValue = Union[None, _CharLike, SupportsFloat, SupportsComplex, SupportsIndex]
- else:
- _IntValue = Union[SupportsInt, _CharLike]
- _FloatValue = Union[None, _CharLike, SupportsFloat]
- _ComplexValue = Union[None, _CharLike, SupportsFloat, SupportsComplex]
- class integer(number[_NBit_co]): # type: ignore
- # NOTE: `__index__` is technically defined in the bottom-most
- # sub-classes (`int64`, `uint32`, etc)
- def __index__(self) -> int: ...
- __truediv__: _IntTrueDiv[_NBit_co]
- __rtruediv__: _IntTrueDiv[_NBit_co]
- def __mod__(self, value: Union[_IntLike, integer]) -> integer: ...
- def __rmod__(self, value: Union[_IntLike, integer]) -> integer: ...
- def __invert__(self: _IntType) -> _IntType: ...
- # Ensure that objects annotated as `integer` support bit-wise operations
- def __lshift__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __rlshift__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __rshift__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __rrshift__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __and__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __rand__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __or__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __ror__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __xor__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- def __rxor__(self, other: Union[_IntLike, _BoolLike]) -> integer: ...
- class signedinteger(integer[_NBit_co]):
- def __init__(self, __value: _IntValue = ...) -> None: ...
- __add__: _SignedIntOp[_NBit_co]
- __radd__: _SignedIntOp[_NBit_co]
- __sub__: _SignedIntOp[_NBit_co]
- __rsub__: _SignedIntOp[_NBit_co]
- __mul__: _SignedIntOp[_NBit_co]
- __rmul__: _SignedIntOp[_NBit_co]
- __floordiv__: _SignedIntOp[_NBit_co]
- __rfloordiv__: _SignedIntOp[_NBit_co]
- __pow__: _SignedIntOp[_NBit_co]
- __rpow__: _SignedIntOp[_NBit_co]
- __lshift__: _SignedIntBitOp[_NBit_co]
- __rlshift__: _SignedIntBitOp[_NBit_co]
- __rshift__: _SignedIntBitOp[_NBit_co]
- __rrshift__: _SignedIntBitOp[_NBit_co]
- __and__: _SignedIntBitOp[_NBit_co]
- __rand__: _SignedIntBitOp[_NBit_co]
- __xor__: _SignedIntBitOp[_NBit_co]
- __rxor__: _SignedIntBitOp[_NBit_co]
- __or__: _SignedIntBitOp[_NBit_co]
- __ror__: _SignedIntBitOp[_NBit_co]
- __mod__: _SignedIntMod[_NBit_co]
- __rmod__: _SignedIntMod[_NBit_co]
- __divmod__: _SignedIntDivMod[_NBit_co]
- __rdivmod__: _SignedIntDivMod[_NBit_co]
- int8 = signedinteger[_8Bit]
- int16 = signedinteger[_16Bit]
- int32 = signedinteger[_32Bit]
- int64 = signedinteger[_64Bit]
- class timedelta64(generic):
- def __init__(
- self,
- __value: Union[None, int, _CharLike, dt.timedelta, timedelta64] = ...,
- __format: Union[_CharLike, Tuple[_CharLike, _IntLike]] = ...,
- ) -> None: ...
- def __int__(self) -> int: ...
- def __float__(self) -> float: ...
- def __complex__(self) -> complex: ...
- def __neg__(self: _ArraySelf) -> _ArraySelf: ...
- def __pos__(self: _ArraySelf) -> _ArraySelf: ...
- def __abs__(self: _ArraySelf) -> _ArraySelf: ...
- def __add__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> timedelta64: ...
- def __radd__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> timedelta64: ...
- def __sub__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> timedelta64: ...
- def __rsub__(self, other: Union[timedelta64, _IntLike, _BoolLike]) -> timedelta64: ...
- def __mul__(self, other: Union[_FloatLike, _BoolLike]) -> timedelta64: ...
- def __rmul__(self, other: Union[_FloatLike, _BoolLike]) -> timedelta64: ...
- __truediv__: _TD64Div[float64]
- __floordiv__: _TD64Div[int64]
- def __rtruediv__(self, other: timedelta64) -> float64: ...
- def __rfloordiv__(self, other: timedelta64) -> int64: ...
- def __mod__(self, other: timedelta64) -> timedelta64: ...
- def __rmod__(self, other: timedelta64) -> timedelta64: ...
- def __divmod__(self, other: timedelta64) -> Tuple[int64, timedelta64]: ...
- def __rdivmod__(self, other: timedelta64) -> Tuple[int64, timedelta64]: ...
- class unsignedinteger(integer[_NBit_co]):
- # NOTE: `uint64 + signedinteger -> float64`
- def __init__(self, __value: _IntValue = ...) -> None: ...
- __add__: _UnsignedIntOp[_NBit_co]
- __radd__: _UnsignedIntOp[_NBit_co]
- __sub__: _UnsignedIntOp[_NBit_co]
- __rsub__: _UnsignedIntOp[_NBit_co]
- __mul__: _UnsignedIntOp[_NBit_co]
- __rmul__: _UnsignedIntOp[_NBit_co]
- __floordiv__: _UnsignedIntOp[_NBit_co]
- __rfloordiv__: _UnsignedIntOp[_NBit_co]
- __pow__: _UnsignedIntOp[_NBit_co]
- __rpow__: _UnsignedIntOp[_NBit_co]
- __lshift__: _UnsignedIntBitOp[_NBit_co]
- __rlshift__: _UnsignedIntBitOp[_NBit_co]
- __rshift__: _UnsignedIntBitOp[_NBit_co]
- __rrshift__: _UnsignedIntBitOp[_NBit_co]
- __and__: _UnsignedIntBitOp[_NBit_co]
- __rand__: _UnsignedIntBitOp[_NBit_co]
- __xor__: _UnsignedIntBitOp[_NBit_co]
- __rxor__: _UnsignedIntBitOp[_NBit_co]
- __or__: _UnsignedIntBitOp[_NBit_co]
- __ror__: _UnsignedIntBitOp[_NBit_co]
- __mod__: _UnsignedIntMod[_NBit_co]
- __rmod__: _UnsignedIntMod[_NBit_co]
- __divmod__: _UnsignedIntDivMod[_NBit_co]
- __rdivmod__: _UnsignedIntDivMod[_NBit_co]
- uint8 = unsignedinteger[_8Bit]
- uint16 = unsignedinteger[_16Bit]
- uint32 = unsignedinteger[_32Bit]
- uint64 = unsignedinteger[_64Bit]
- class inexact(number[_NBit_co]): ... # type: ignore
- _IntType = TypeVar("_IntType", bound=integer)
- _FloatType = TypeVar('_FloatType', bound=floating)
- class floating(inexact[_NBit_co]):
- def __init__(self, __value: _FloatValue = ...) -> None: ...
- __add__: _FloatOp[_NBit_co]
- __radd__: _FloatOp[_NBit_co]
- __sub__: _FloatOp[_NBit_co]
- __rsub__: _FloatOp[_NBit_co]
- __mul__: _FloatOp[_NBit_co]
- __rmul__: _FloatOp[_NBit_co]
- __truediv__: _FloatOp[_NBit_co]
- __rtruediv__: _FloatOp[_NBit_co]
- __floordiv__: _FloatOp[_NBit_co]
- __rfloordiv__: _FloatOp[_NBit_co]
- __pow__: _FloatOp[_NBit_co]
- __rpow__: _FloatOp[_NBit_co]
- __mod__: _FloatMod[_NBit_co]
- __rmod__: _FloatMod[_NBit_co]
- __divmod__: _FloatDivMod[_NBit_co]
- __rdivmod__: _FloatDivMod[_NBit_co]
- float16 = floating[_16Bit]
- float32 = floating[_32Bit]
- float64 = floating[_64Bit]
- # The main reason for `complexfloating` having two typevars is cosmetic.
- # It is used to clarify why `complex128`s precision is `_64Bit`, the latter
- # describing the two 64 bit floats representing its real and imaginary component
- class complexfloating(inexact[_NBit_co], Generic[_NBit_co, _NBit_co2]):
- def __init__(self, __value: _ComplexValue = ...) -> None: ...
- @property
- def real(self) -> floating[_NBit_co]: ... # type: ignore[override]
- @property
- def imag(self) -> floating[_NBit_co2]: ... # type: ignore[override]
- def __abs__(self) -> floating[_NBit_co]: ... # type: ignore[override]
- __add__: _ComplexOp[_NBit_co]
- __radd__: _ComplexOp[_NBit_co]
- __sub__: _ComplexOp[_NBit_co]
- __rsub__: _ComplexOp[_NBit_co]
- __mul__: _ComplexOp[_NBit_co]
- __rmul__: _ComplexOp[_NBit_co]
- __truediv__: _ComplexOp[_NBit_co]
- __rtruediv__: _ComplexOp[_NBit_co]
- __floordiv__: _ComplexOp[_NBit_co]
- __rfloordiv__: _ComplexOp[_NBit_co]
- __pow__: _ComplexOp[_NBit_co]
- __rpow__: _ComplexOp[_NBit_co]
- complex64 = complexfloating[_32Bit, _32Bit]
- complex128 = complexfloating[_64Bit, _64Bit]
- class flexible(generic): ... # type: ignore
- class void(flexible):
- def __init__(self, __value: Union[_IntLike, _BoolLike, bytes]): ...
- @property
- def real(self: _ArraySelf) -> _ArraySelf: ...
- @property
- def imag(self: _ArraySelf) -> _ArraySelf: ...
- def setfield(
- self, val: ArrayLike, dtype: DTypeLike, offset: int = ...
- ) -> None: ...
- class character(flexible): # type: ignore
- def __int__(self) -> int: ...
- def __float__(self) -> float: ...
- # NOTE: Most `np.bytes_` / `np.str_` methods return their
- # builtin `bytes` / `str` counterpart
- class bytes_(character, bytes):
- @overload
- def __init__(self, __value: object = ...) -> None: ...
- @overload
- def __init__(
- self, __value: str, encoding: str = ..., errors: str = ...
- ) -> None: ...
- class str_(character, str):
- @overload
- def __init__(self, __value: object = ...) -> None: ...
- @overload
- def __init__(
- self, __value: bytes, encoding: str = ..., errors: str = ...
- ) -> None: ...
- unicode_ = str0 = str_
- # TODO(alan): Platform dependent types
- # longcomplex, longdouble, longfloat
- # bytes, short, intc, intp, longlong
- # half, single, double, longdouble
- # uint_, int_, float_, complex_
- # float128, complex256
- # float96
- def array(
- object: object,
- dtype: DTypeLike = ...,
- *,
- copy: bool = ...,
- order: _OrderKACF = ...,
- subok: bool = ...,
- ndmin: int = ...,
- like: ArrayLike = ...,
- ) -> ndarray: ...
- def zeros(
- shape: _ShapeLike,
- dtype: DTypeLike = ...,
- order: _OrderCF = ...,
- *,
- like: ArrayLike = ...,
- ) -> ndarray: ...
- def empty(
- shape: _ShapeLike,
- dtype: DTypeLike = ...,
- order: _OrderCF = ...,
- *,
- like: ArrayLike = ...,
- ) -> ndarray: ...
- def broadcast_shapes(*args: _ShapeLike) -> _Shape: ...
- #
- # Constants
- #
- Inf: Final[float]
- Infinity: Final[float]
- NAN: Final[float]
- NINF: Final[float]
- NZERO: Final[float]
- NaN: Final[float]
- PINF: Final[float]
- PZERO: Final[float]
- e: Final[float]
- euler_gamma: Final[float]
- inf: Final[float]
- infty: Final[float]
- nan: Final[float]
- pi: Final[float]
- ALLOW_THREADS: Final[int]
- BUFSIZE: Final[int]
- CLIP: Final[int]
- ERR_CALL: Final[int]
- ERR_DEFAULT: Final[int]
- ERR_IGNORE: Final[int]
- ERR_LOG: Final[int]
- ERR_PRINT: Final[int]
- ERR_RAISE: Final[int]
- ERR_WARN: Final[int]
- FLOATING_POINT_SUPPORT: Final[int]
- FPE_DIVIDEBYZERO: Final[int]
- FPE_INVALID: Final[int]
- FPE_OVERFLOW: Final[int]
- FPE_UNDERFLOW: Final[int]
- MAXDIMS: Final[int]
- MAY_SHARE_BOUNDS: Final[int]
- MAY_SHARE_EXACT: Final[int]
- RAISE: Final[int]
- SHIFT_DIVIDEBYZERO: Final[int]
- SHIFT_INVALID: Final[int]
- SHIFT_OVERFLOW: Final[int]
- SHIFT_UNDERFLOW: Final[int]
- UFUNC_BUFSIZE_DEFAULT: Final[int]
- WRAP: Final[int]
- tracemalloc_domain: Final[int]
- little_endian: Final[bool]
- True_: Final[bool_]
- False_: Final[bool_]
- UFUNC_PYVALS_NAME: Final[str]
- class ufunc:
- @property
- def __name__(self) -> str: ...
- def __call__(
- self,
- *args: ArrayLike,
- out: Optional[Union[ndarray, Tuple[ndarray, ...]]] = ...,
- where: Optional[ndarray] = ...,
- # The list should be a list of tuples of ints, but since we
- # don't know the signature it would need to be
- # Tuple[int, ...]. But, since List is invariant something like
- # e.g. List[Tuple[int, int]] isn't a subtype of
- # List[Tuple[int, ...]], so we can't type precisely here.
- axes: List[Any] = ...,
- axis: int = ...,
- keepdims: bool = ...,
- casting: _Casting = ...,
- order: _OrderKACF = ...,
- dtype: DTypeLike = ...,
- subok: bool = ...,
- signature: Union[str, Tuple[str]] = ...,
- # In reality this should be a length of list 3 containing an
- # int, an int, and a callable, but there's no way to express
- # that.
- extobj: List[Union[int, Callable]] = ...,
- ) -> Any: ...
- @property
- def nin(self) -> int: ...
- @property
- def nout(self) -> int: ...
- @property
- def nargs(self) -> int: ...
- @property
- def ntypes(self) -> int: ...
- @property
- def types(self) -> List[str]: ...
- # Broad return type because it has to encompass things like
- #
- # >>> np.logical_and.identity is True
- # True
- # >>> np.add.identity is 0
- # True
- # >>> np.sin.identity is None
- # True
- #
- # and any user-defined ufuncs.
- @property
- def identity(self) -> Any: ...
- # This is None for ufuncs and a string for gufuncs.
- @property
- def signature(self) -> Optional[str]: ...
- # The next four methods will always exist, but they will just
- # raise a ValueError ufuncs with that don't accept two input
- # arguments and return one output argument. Because of that we
- # can't type them very precisely.
- @property
- def reduce(self) -> Any: ...
- @property
- def accumulate(self) -> Any: ...
- @property
- def reduceat(self) -> Any: ...
- @property
- def outer(self) -> Any: ...
- # Similarly at won't be defined for ufuncs that return multiple
- # outputs, so we can't type it very precisely.
- @property
- def at(self) -> Any: ...
- absolute: ufunc
- add: ufunc
- arccos: ufunc
- arccosh: ufunc
- arcsin: ufunc
- arcsinh: ufunc
- arctan2: ufunc
- arctan: ufunc
- arctanh: ufunc
- bitwise_and: ufunc
- bitwise_or: ufunc
- bitwise_xor: ufunc
- cbrt: ufunc
- ceil: ufunc
- conjugate: ufunc
- copysign: ufunc
- cos: ufunc
- cosh: ufunc
- deg2rad: ufunc
- degrees: ufunc
- divmod: ufunc
- equal: ufunc
- exp2: ufunc
- exp: ufunc
- expm1: ufunc
- fabs: ufunc
- float_power: ufunc
- floor: ufunc
- floor_divide: ufunc
- fmax: ufunc
- fmin: ufunc
- fmod: ufunc
- frexp: ufunc
- gcd: ufunc
- greater: ufunc
- greater_equal: ufunc
- heaviside: ufunc
- hypot: ufunc
- invert: ufunc
- isfinite: ufunc
- isinf: ufunc
- isnan: ufunc
- isnat: ufunc
- lcm: ufunc
- ldexp: ufunc
- left_shift: ufunc
- less: ufunc
- less_equal: ufunc
- log10: ufunc
- log1p: ufunc
- log2: ufunc
- log: ufunc
- logaddexp2: ufunc
- logaddexp: ufunc
- logical_and: ufunc
- logical_not: ufunc
- logical_or: ufunc
- logical_xor: ufunc
- matmul: ufunc
- maximum: ufunc
- minimum: ufunc
- modf: ufunc
- multiply: ufunc
- negative: ufunc
- nextafter: ufunc
- not_equal: ufunc
- positive: ufunc
- power: ufunc
- rad2deg: ufunc
- radians: ufunc
- reciprocal: ufunc
- remainder: ufunc
- right_shift: ufunc
- rint: ufunc
- sign: ufunc
- signbit: ufunc
- sin: ufunc
- sinh: ufunc
- spacing: ufunc
- sqrt: ufunc
- square: ufunc
- subtract: ufunc
- tan: ufunc
- tanh: ufunc
- true_divide: ufunc
- trunc: ufunc
- abs = absolute
- # Warnings
- class ModuleDeprecationWarning(DeprecationWarning): ...
- class VisibleDeprecationWarning(UserWarning): ...
- class ComplexWarning(RuntimeWarning): ...
- class RankWarning(UserWarning): ...
- # Errors
- class TooHardError(RuntimeError): ...
- class AxisError(ValueError, IndexError):
- def __init__(
- self, axis: int, ndim: Optional[int] = ..., msg_prefix: Optional[str] = ...
- ) -> None: ...
- _CallType = TypeVar("_CallType", bound=Union[_ErrFunc, _SupportsWrite])
- class errstate(Generic[_CallType], ContextDecorator):
- call: _CallType
- kwargs: _ErrDictOptional
- # Expand `**kwargs` into explicit keyword-only arguments
- def __init__(
- self,
- *,
- call: _CallType = ...,
- all: Optional[_ErrKind] = ...,
- divide: Optional[_ErrKind] = ...,
- over: Optional[_ErrKind] = ...,
- under: Optional[_ErrKind] = ...,
- invalid: Optional[_ErrKind] = ...,
- ) -> None: ...
- def __enter__(self) -> None: ...
- def __exit__(
- self,
- __exc_type: Optional[Type[BaseException]],
- __exc_value: Optional[BaseException],
- __traceback: Optional[TracebackType],
- ) -> None: ...
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