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Add __pycache__ and .venv directories
2026-01-09 09:48:03 +08:00
# ruff: noqa: I001
import builtins
import sys
import mmap
import ctypes as ct
import array as _array
import datetime as dt
import inspect
from abc import abstractmethod
from types import EllipsisType, ModuleType, TracebackType, MappingProxyType, GenericAlias
from decimal import Decimal
from fractions import Fraction
from uuid import UUID
import numpy as np
from numpy.__config__ import show as show_config
from numpy._pytesttester import PytestTester
from numpy._core._internal import _ctypes
from numpy._typing import ( # type: ignore[deprecated]
# Arrays
ArrayLike,
NDArray,
_SupportsArray,
_NestedSequence,
_ArrayLike,
_ArrayLikeBool_co,
_ArrayLikeUInt_co,
_ArrayLikeInt,
_ArrayLikeInt_co,
_ArrayLikeFloat64_co,
_ArrayLikeFloat_co,
_ArrayLikeComplex128_co,
_ArrayLikeComplex_co,
_ArrayLikeNumber_co,
_ArrayLikeObject_co,
_ArrayLikeBytes_co,
_ArrayLikeStr_co,
_ArrayLikeString_co,
_ArrayLikeTD64_co,
_ArrayLikeDT64_co,
# DTypes
DTypeLike,
_DTypeLike,
_DTypeLikeVoid,
_VoidDTypeLike,
# Shapes
_AnyShape,
_Shape,
_ShapeLike,
# Scalars
_CharLike_co,
_IntLike_co,
_FloatLike_co,
_TD64Like_co,
_NumberLike_co,
_ScalarLike_co,
# `number` precision
NBitBase,
# NOTE: Do not remove the extended precision bit-types even if seemingly unused;
# they're used by the mypy plugin
_128Bit,
_96Bit,
_64Bit,
_32Bit,
_16Bit,
_8Bit,
_NBitByte,
_NBitShort,
_NBitIntC,
_NBitIntP,
_NBitLong,
_NBitLongLong,
_NBitHalf,
_NBitSingle,
_NBitDouble,
_NBitLongDouble,
# Character codes
_BoolCodes,
_UInt8Codes,
_UInt16Codes,
_UInt32Codes,
_UInt64Codes,
_Int8Codes,
_Int16Codes,
_Int32Codes,
_Int64Codes,
_Float16Codes,
_Float32Codes,
_Float64Codes,
_Complex64Codes,
_Complex128Codes,
_ByteCodes,
_ShortCodes,
_IntCCodes,
_IntPCodes,
_LongCodes,
_LongLongCodes,
_UByteCodes,
_UShortCodes,
_UIntCCodes,
_UIntPCodes,
_ULongCodes,
_ULongLongCodes,
_HalfCodes,
_SingleCodes,
_DoubleCodes,
_LongDoubleCodes,
_CSingleCodes,
_CDoubleCodes,
_CLongDoubleCodes,
_DT64Codes,
_TD64Codes,
_StrCodes,
_BytesCodes,
_VoidCodes,
_ObjectCodes,
_StringCodes,
_UnsignedIntegerCodes,
_SignedIntegerCodes,
_IntegerCodes,
_FloatingCodes,
_ComplexFloatingCodes,
_InexactCodes,
_CharacterCodes,
# Ufuncs
_UFunc_Nin1_Nout1,
_UFunc_Nin2_Nout1,
_UFunc_Nin1_Nout2,
_UFunc_Nin2_Nout2,
_GUFunc_Nin2_Nout1,
)
# NOTE: Numpy's mypy plugin is used for removing the types unavailable to the specific platform
from numpy._typing._extended_precision import (
float96,
float128,
complex192,
complex256,
)
from numpy._array_api_info import __array_namespace_info__
from collections.abc import (
Callable,
Iterable,
Iterator,
Mapping,
Sequence,
)
if sys.version_info >= (3, 12):
from collections.abc import Buffer as _SupportsBuffer
else:
_SupportsBuffer: TypeAlias = (
bytes
| bytearray
| memoryview
| _array.array[Any]
| mmap.mmap
| NDArray[Any]
| generic
)
from typing import (
Any,
ClassVar,
Final,
Generic,
Literal as L,
LiteralString,
Never,
NoReturn,
Protocol,
Self,
SupportsComplex,
SupportsFloat,
SupportsInt,
SupportsIndex,
TypeAlias,
TypedDict,
final,
overload,
type_check_only,
)
# NOTE: `typing_extensions` and `_typeshed` are always available in `.pyi` stubs, even
# if not available at runtime. This is because the `typeshed` stubs for the standard
# library include `typing_extensions` stubs:
# https://github.com/python/typeshed/blob/main/stdlib/typing_extensions.pyi
from _typeshed import Incomplete, StrOrBytesPath, SupportsFlush, SupportsLenAndGetItem, SupportsWrite
from typing_extensions import CapsuleType, TypeVar, deprecated, override
from numpy import (
char,
core,
ctypeslib,
dtypes,
exceptions,
f2py,
fft,
lib,
linalg,
ma,
polynomial,
random,
rec,
strings,
testing,
typing,
)
# available through `__getattr__`, but not in `__all__` or `__dir__`
from numpy import (
__config__ as __config__,
matlib as matlib,
matrixlib as matrixlib,
version as version,
)
if sys.version_info < (3, 12):
from numpy import distutils as distutils
from numpy._core.records import (
record,
recarray,
)
from numpy._core.function_base import (
linspace,
logspace,
geomspace,
)
from numpy._core.fromnumeric import (
take,
reshape,
choose,
repeat,
put,
swapaxes,
transpose,
matrix_transpose,
partition,
argpartition,
sort,
argsort,
argmax,
argmin,
searchsorted,
resize,
squeeze,
diagonal,
trace,
ravel,
nonzero,
shape,
compress,
clip,
sum,
all,
any,
cumsum,
cumulative_sum,
ptp,
max,
min,
amax,
amin,
prod,
cumprod,
cumulative_prod,
ndim,
size,
around,
round,
mean,
std,
var,
)
from numpy._core._asarray import (
require,
)
from numpy._core._type_aliases import (
sctypeDict,
)
from numpy._core._ufunc_config import (
seterr,
geterr,
setbufsize,
getbufsize,
seterrcall,
geterrcall,
errstate,
)
from numpy._core.arrayprint import (
set_printoptions,
get_printoptions,
array2string,
format_float_scientific,
format_float_positional,
array_repr,
array_str,
printoptions,
)
from numpy._core.einsumfunc import (
einsum,
einsum_path,
)
from numpy._core.getlimits import (
finfo,
iinfo,
)
from numpy._core.multiarray import (
array,
empty_like,
empty,
zeros,
concatenate,
inner,
where,
lexsort,
can_cast,
min_scalar_type,
result_type,
dot,
vdot,
bincount,
copyto,
putmask,
packbits,
unpackbits,
shares_memory,
may_share_memory,
asarray,
asanyarray,
ascontiguousarray,
asfortranarray,
arange,
busday_count,
busday_offset,
datetime_as_string,
datetime_data,
frombuffer,
fromfile,
fromiter,
is_busday,
promote_types,
fromstring,
frompyfunc,
nested_iters,
flagsobj,
)
from numpy._core.numeric import (
zeros_like,
ones,
ones_like,
full,
full_like,
count_nonzero,
isfortran,
argwhere,
flatnonzero,
correlate,
convolve,
outer,
tensordot,
roll,
rollaxis,
moveaxis,
cross,
indices,
fromfunction,
isscalar,
binary_repr,
base_repr,
identity,
allclose,
isclose,
array_equal,
array_equiv,
astype,
)
from numpy._core.numerictypes import (
isdtype,
issubdtype,
ScalarType,
typecodes,
)
from numpy._core.shape_base import (
atleast_1d,
atleast_2d,
atleast_3d,
block,
hstack,
stack,
vstack,
unstack,
)
from ._expired_attrs_2_0 import __expired_attributes__ as __expired_attributes__
from ._globals import _CopyMode as _CopyMode
from ._globals import _NoValue as _NoValue, _NoValueType
from numpy.lib import (
scimath as emath,
)
from numpy.lib._arraypad_impl import (
pad,
)
from numpy.lib._arraysetops_impl import (
ediff1d,
intersect1d,
isin,
setdiff1d,
setxor1d,
union1d,
unique,
unique_all,
unique_counts,
unique_inverse,
unique_values,
)
from numpy.lib._function_base_impl import ( # type: ignore[deprecated]
select,
piecewise,
trim_zeros,
copy,
iterable,
percentile,
diff,
gradient,
angle,
unwrap,
sort_complex,
flip,
rot90,
extract,
place,
asarray_chkfinite,
average,
digitize,
cov,
corrcoef,
median,
sinc,
hamming,
hanning,
bartlett,
blackman,
kaiser,
trapezoid,
i0,
meshgrid,
delete,
insert,
append,
interp,
quantile,
vectorize,
)
from numpy.lib._histograms_impl import (
histogram_bin_edges,
histogram,
histogramdd,
)
from numpy.lib._index_tricks_impl import (
ndenumerate,
ndindex,
ravel_multi_index,
unravel_index,
mgrid,
ogrid,
r_,
c_,
s_,
index_exp,
ix_,
fill_diagonal,
diag_indices,
diag_indices_from,
)
from numpy.lib._nanfunctions_impl import (
nansum,
nanmax,
nanmin,
nanargmax,
nanargmin,
nanmean,
nanmedian,
nanpercentile,
nanvar,
nanstd,
nanprod,
nancumsum,
nancumprod,
nanquantile,
)
from numpy.lib._npyio_impl import (
savetxt,
loadtxt,
genfromtxt,
load,
save,
savez,
savez_compressed,
fromregex,
)
from numpy.lib._polynomial_impl import (
poly,
roots,
polyint,
polyder,
polyadd,
polysub,
polymul,
polydiv,
polyval,
polyfit,
)
from numpy.lib._shape_base_impl import ( # type: ignore[deprecated]
column_stack,
row_stack,
dstack,
array_split,
split,
hsplit,
vsplit,
dsplit,
apply_over_axes,
expand_dims,
apply_along_axis,
kron,
tile,
take_along_axis,
put_along_axis,
)
from numpy.lib._stride_tricks_impl import (
broadcast_to,
broadcast_arrays,
broadcast_shapes,
)
from numpy.lib._twodim_base_impl import (
diag,
diagflat,
eye,
fliplr,
flipud,
tri,
triu,
tril,
vander,
histogram2d,
mask_indices,
tril_indices,
tril_indices_from,
triu_indices,
triu_indices_from,
)
from numpy.lib._type_check_impl import (
mintypecode,
real,
imag,
iscomplex,
isreal,
iscomplexobj,
isrealobj,
nan_to_num,
real_if_close,
typename,
common_type,
)
from numpy.lib._ufunclike_impl import (
fix,
isposinf,
isneginf,
)
from numpy.lib._utils_impl import (
get_include,
info,
show_runtime,
)
from numpy.matrixlib import (
asmatrix,
bmat,
matrix,
)
__all__ = [ # noqa: RUF022
# __numpy_submodules__
"char", "core", "ctypeslib", "dtypes", "exceptions", "f2py", "fft", "lib", "linalg",
"ma", "polynomial", "random", "rec", "strings", "test", "testing", "typing",
# _core.__all__
"abs", "acos", "acosh", "asin", "asinh", "atan", "atanh", "atan2", "bitwise_invert",
"bitwise_left_shift", "bitwise_right_shift", "concat", "pow", "permute_dims",
"memmap", "sctypeDict", "record", "recarray",
# _core.numeric.__all__
"newaxis", "ndarray", "flatiter", "nditer", "nested_iters", "ufunc", "arange",
"array", "asarray", "asanyarray", "ascontiguousarray", "asfortranarray", "zeros",
"count_nonzero", "empty", "broadcast", "dtype", "fromstring", "fromfile",
"frombuffer", "from_dlpack", "where", "argwhere", "copyto", "concatenate",
"lexsort", "astype", "can_cast", "promote_types", "min_scalar_type", "result_type",
"isfortran", "empty_like", "zeros_like", "ones_like", "correlate", "convolve",
"inner", "dot", "outer", "vdot", "roll", "rollaxis", "moveaxis", "cross",
"tensordot", "little_endian", "fromiter", "array_equal", "array_equiv", "indices",
"fromfunction", "isclose", "isscalar", "binary_repr", "base_repr", "ones",
"identity", "allclose", "putmask", "flatnonzero", "inf", "nan", "False_", "True_",
"bitwise_not", "full", "full_like", "matmul", "vecdot", "vecmat",
"shares_memory", "may_share_memory",
"all", "amax", "amin", "any", "argmax", "argmin", "argpartition", "argsort",
"around", "choose", "clip", "compress", "cumprod", "cumsum", "cumulative_prod",
"cumulative_sum", "diagonal", "mean", "max", "min", "matrix_transpose", "ndim",
"nonzero", "partition", "prod", "ptp", "put", "ravel", "repeat", "reshape",
"resize", "round", "searchsorted", "shape", "size", "sort", "squeeze", "std", "sum",
"swapaxes", "take", "trace", "transpose", "var",
"absolute", "add", "arccos", "arccosh", "arcsin", "arcsinh", "arctan", "arctan2",
"arctanh", "bitwise_and", "bitwise_or", "bitwise_xor", "cbrt", "ceil", "conj",
"conjugate", "copysign", "cos", "cosh", "bitwise_count", "deg2rad", "degrees",
"divide", "divmod", "e", "equal", "euler_gamma", "exp", "exp2", "expm1", "fabs",
"floor", "floor_divide", "float_power", "fmax", "fmin", "fmod", "frexp",
"frompyfunc", "gcd", "greater", "greater_equal", "heaviside", "hypot", "invert",
"isfinite", "isinf", "isnan", "isnat", "lcm", "ldexp", "left_shift", "less",
"less_equal", "log", "log10", "log1p", "log2", "logaddexp", "logaddexp2",
"logical_and", "logical_not", "logical_or", "logical_xor", "matvec", "maximum", "minimum",
"mod", "modf", "multiply", "negative", "nextafter", "not_equal", "pi", "positive",
"power", "rad2deg", "radians", "reciprocal", "remainder", "right_shift", "rint",
"sign", "signbit", "sin", "sinh", "spacing", "sqrt", "square", "subtract", "tan",
"tanh", "true_divide", "trunc", "ScalarType", "typecodes", "issubdtype",
"datetime_data", "datetime_as_string", "busday_offset", "busday_count", "is_busday",
"busdaycalendar", "isdtype",
"complexfloating", "character", "unsignedinteger", "inexact", "generic", "floating",
"integer", "signedinteger", "number", "flexible", "bool", "float16", "float32",
"float64", "longdouble", "complex64", "complex128", "clongdouble",
"bytes_", "str_", "void", "object_", "datetime64", "timedelta64", "int8", "byte",
"uint8", "ubyte", "int16", "short", "uint16", "ushort", "int32", "intc", "uint32",
"uintc", "int64", "long", "uint64", "ulong", "longlong", "ulonglong", "intp",
"uintp", "double", "cdouble", "single", "csingle", "half", "bool_", "int_", "uint",
"float96", "float128", "complex192", "complex256",
"array2string", "array_str", "array_repr", "set_printoptions", "get_printoptions",
"printoptions", "format_float_positional", "format_float_scientific", "require",
"seterr", "geterr", "setbufsize", "getbufsize", "seterrcall", "geterrcall",
"errstate",
# _core.function_base.__all__
"logspace", "linspace", "geomspace",
# _core.getlimits.__all__
"finfo", "iinfo",
# _core.shape_base.__all__
"atleast_1d", "atleast_2d", "atleast_3d", "block", "hstack", "stack", "unstack",
"vstack",
# _core.einsumfunc.__all__
"einsum", "einsum_path",
# matrixlib.__all__
"matrix", "bmat", "asmatrix",
# lib._histograms_impl.__all__
"histogram", "histogramdd", "histogram_bin_edges",
# lib._nanfunctions_impl.__all__
"nansum", "nanmax", "nanmin", "nanargmax", "nanargmin", "nanmean", "nanmedian",
"nanpercentile", "nanvar", "nanstd", "nanprod", "nancumsum", "nancumprod",
"nanquantile",
# lib._function_base_impl.__all__
"select", "piecewise", "trim_zeros", "copy", "iterable", "percentile", "diff",
"gradient", "angle", "unwrap", "sort_complex", "flip", "rot90", "extract", "place",
"vectorize", "asarray_chkfinite", "average", "bincount", "digitize", "cov",
"corrcoef", "median", "sinc", "hamming", "hanning", "bartlett", "blackman",
"kaiser", "trapezoid", "i0", "meshgrid", "delete", "insert", "append",
"interp", "quantile",
# lib._twodim_base_impl.__all__
"diag", "diagflat", "eye", "fliplr", "flipud", "tri", "triu", "tril", "vander",
"histogram2d", "mask_indices", "tril_indices", "tril_indices_from", "triu_indices",
"triu_indices_from",
# lib._shape_base_impl.__all__
"column_stack", "dstack", "array_split", "split", "hsplit", "vsplit", "dsplit",
"apply_over_axes", "expand_dims", "apply_along_axis", "kron", "tile",
"take_along_axis", "put_along_axis", "row_stack",
# lib._type_check_impl.__all__
"iscomplexobj", "isrealobj", "imag", "iscomplex", "isreal", "nan_to_num", "real",
"real_if_close", "typename", "mintypecode", "common_type",
# lib._arraysetops_impl.__all__
"ediff1d", "intersect1d", "isin", "setdiff1d", "setxor1d", "union1d",
"unique", "unique_all", "unique_counts", "unique_inverse", "unique_values",
# lib._ufunclike_impl.__all__
"fix", "isneginf", "isposinf",
# lib._arraypad_impl.__all__
"pad",
# lib._utils_impl.__all__
"get_include", "info", "show_runtime",
# lib._stride_tricks_impl.__all__
"broadcast_to", "broadcast_arrays", "broadcast_shapes",
# lib._polynomial_impl.__all__
"poly", "roots", "polyint", "polyder", "polyadd", "polysub", "polymul", "polydiv",
"polyval", "poly1d", "polyfit",
# lib._npyio_impl.__all__
"savetxt", "loadtxt", "genfromtxt", "load", "save", "savez", "savez_compressed",
"packbits", "unpackbits", "fromregex",
# lib._index_tricks_impl.__all__
"ravel_multi_index", "unravel_index", "mgrid", "ogrid", "r_", "c_", "s_",
"index_exp", "ix_", "ndenumerate", "ndindex", "fill_diagonal", "diag_indices",
"diag_indices_from",
# __init__.__all__
"emath", "show_config", "__version__", "__array_namespace_info__",
] # fmt: skip
### Constrained types (for internal use only)
# Only use these for functions; never as generic type parameter.
_AnyStr = TypeVar("_AnyStr", LiteralString, str, bytes)
_AnyShapeT = TypeVar(
"_AnyShapeT",
tuple[()], # 0-d
tuple[int], # 1-d
tuple[int, int], # 2-d
tuple[int, int, int], # 3-d
tuple[int, int, int, int], # 4-d
tuple[int, int, int, int, int], # 5-d
tuple[int, int, int, int, int, int], # 6-d
tuple[int, int, int, int, int, int, int], # 7-d
tuple[int, int, int, int, int, int, int, int], # 8-d
tuple[int, ...], # N-d
)
_AnyTD64Item = TypeVar("_AnyTD64Item", dt.timedelta, int, None, dt.timedelta | int | None)
_AnyDT64Arg = TypeVar("_AnyDT64Arg", dt.datetime, dt.date, None)
_AnyDT64Item = TypeVar("_AnyDT64Item", dt.datetime, dt.date, int, None, dt.date, int | None)
_AnyDate = TypeVar("_AnyDate", dt.date, dt.datetime)
_AnyDateOrTime = TypeVar("_AnyDateOrTime", dt.date, dt.datetime, dt.timedelta)
### Type parameters (for internal use only)
_T = TypeVar("_T")
_T_co = TypeVar("_T_co", covariant=True)
_T_contra = TypeVar("_T_contra", contravariant=True)
_RealT_co = TypeVar("_RealT_co", covariant=True)
_ImagT_co = TypeVar("_ImagT_co", covariant=True)
_DTypeT = TypeVar("_DTypeT", bound=dtype)
_DTypeT_co = TypeVar("_DTypeT_co", bound=dtype, default=dtype, covariant=True)
_FlexDTypeT = TypeVar("_FlexDTypeT", bound=dtype[flexible])
_ArrayT = TypeVar("_ArrayT", bound=ndarray)
_ArrayT_co = TypeVar("_ArrayT_co", bound=ndarray, default=ndarray, covariant=True)
_BoolArrayT = TypeVar("_BoolArrayT", bound=NDArray[np.bool])
_IntegerArrayT = TypeVar("_IntegerArrayT", bound=NDArray[integer])
_IntegralArrayT = TypeVar("_IntegralArrayT", bound=NDArray[np.bool | integer | object_])
_FloatingArrayT = TypeVar("_FloatingArrayT", bound=NDArray[floating])
_FloatingTimedeltaArrayT = TypeVar("_FloatingTimedeltaArrayT", bound=NDArray[floating | timedelta64])
_ComplexFloatingArrayT = TypeVar("_ComplexFloatingArrayT", bound=NDArray[complexfloating])
_InexactArrayT = TypeVar("_InexactArrayT", bound=NDArray[inexact])
_InexactTimedeltaArrayT = TypeVar("_InexactTimedeltaArrayT", bound=NDArray[inexact | timedelta64])
_NumberArrayT = TypeVar("_NumberArrayT", bound=NDArray[number])
_NumberCharacterArrayT = TypeVar("_NumberCharacterArrayT", bound=ndarray[Any, dtype[number | character] | dtypes.StringDType])
_TimedeltaArrayT = TypeVar("_TimedeltaArrayT", bound=NDArray[timedelta64])
_TimeArrayT = TypeVar("_TimeArrayT", bound=NDArray[datetime64 | timedelta64])
_ObjectArrayT = TypeVar("_ObjectArrayT", bound=NDArray[object_])
_BytesArrayT = TypeVar("_BytesArrayT", bound=NDArray[bytes_])
_StringArrayT = TypeVar("_StringArrayT", bound=ndarray[Any, dtype[str_] | dtypes.StringDType])
_RealArrayT = TypeVar("_RealArrayT", bound=NDArray[floating | integer | timedelta64 | np.bool | object_])
_NumericArrayT = TypeVar("_NumericArrayT", bound=NDArray[number | timedelta64 | object_])
_ShapeT = TypeVar("_ShapeT", bound=_Shape)
_Shape1T = TypeVar("_Shape1T", bound=tuple[int, *tuple[int, ...]])
_ShapeT_co = TypeVar("_ShapeT_co", bound=_Shape, default=_AnyShape, covariant=True)
_2DShapeT_co = TypeVar("_2DShapeT_co", bound=_2D, default=_2D, covariant=True)
_1NShapeT = TypeVar("_1NShapeT", bound=tuple[L[1], *tuple[L[1], ...]]) # (1,) | (1, 1) | (1, 1, 1) | ...
_ScalarT = TypeVar("_ScalarT", bound=generic)
_ScalarT_co = TypeVar("_ScalarT_co", bound=generic, default=Any, covariant=True)
_NumberT = TypeVar("_NumberT", bound=number)
_InexactT = TypeVar("_InexactT", bound=inexact)
_RealNumberT = TypeVar("_RealNumberT", bound=floating | integer)
_IntegerT = TypeVar("_IntegerT", bound=integer)
_NonObjectScalarT = TypeVar("_NonObjectScalarT", bound=np.bool | number | flexible | datetime64 | timedelta64)
_NBit = TypeVar("_NBit", bound=NBitBase, default=Any) # pyright: ignore[reportDeprecated]
_NBit1 = TypeVar("_NBit1", bound=NBitBase, default=Any) # pyright: ignore[reportDeprecated]
_NBit2 = TypeVar("_NBit2", bound=NBitBase, default=_NBit1) # pyright: ignore[reportDeprecated]
_ItemT_co = TypeVar("_ItemT_co", default=Any, covariant=True)
_BoolItemT = TypeVar("_BoolItemT", bound=builtins.bool)
_BoolItemT_co = TypeVar("_BoolItemT_co", bound=builtins.bool, default=builtins.bool, covariant=True)
_NumberItemT_co = TypeVar("_NumberItemT_co", bound=complex, default=int | float | complex, covariant=True)
_InexactItemT_co = TypeVar("_InexactItemT_co", bound=complex, default=float | complex, covariant=True)
_FlexibleItemT_co = TypeVar(
"_FlexibleItemT_co",
bound=_CharLike_co | tuple[Any, ...],
default=_CharLike_co | tuple[Any, ...],
covariant=True,
)
_CharacterItemT_co = TypeVar("_CharacterItemT_co", bound=_CharLike_co, default=_CharLike_co, covariant=True)
_TD64ItemT_co = TypeVar("_TD64ItemT_co", bound=dt.timedelta | int | None, default=dt.timedelta | int | None, covariant=True)
_DT64ItemT_co = TypeVar("_DT64ItemT_co", bound=dt.date | int | None, default=dt.date | int | None, covariant=True)
_TD64UnitT = TypeVar("_TD64UnitT", bound=_TD64Unit, default=_TD64Unit)
_BoolOrIntArrayT = TypeVar("_BoolOrIntArrayT", bound=NDArray[integer | np.bool])
### Type Aliases (for internal use only)
_Falsy: TypeAlias = L[False, 0] | np.bool[L[False]]
_Truthy: TypeAlias = L[True, 1] | np.bool[L[True]]
_1D: TypeAlias = tuple[int]
_2D: TypeAlias = tuple[int, int]
_2Tuple: TypeAlias = tuple[_T, _T]
_ArrayUInt_co: TypeAlias = NDArray[unsignedinteger | np.bool]
_ArrayInt_co: TypeAlias = NDArray[integer | np.bool]
_ArrayFloat64_co: TypeAlias = NDArray[floating[_64Bit] | float32 | float16 | integer | np.bool]
_ArrayFloat_co: TypeAlias = NDArray[floating | integer | np.bool]
_ArrayComplex128_co: TypeAlias = NDArray[number[_64Bit] | number[_32Bit] | float16 | integer | np.bool]
_ArrayComplex_co: TypeAlias = NDArray[inexact | integer | np.bool]
_ArrayNumber_co: TypeAlias = NDArray[number | np.bool]
_ArrayTD64_co: TypeAlias = NDArray[timedelta64 | integer | np.bool]
_Float64_co: TypeAlias = float | floating[_64Bit] | float32 | float16 | integer | np.bool
_Complex64_co: TypeAlias = number[_32Bit] | number[_16Bit] | number[_8Bit] | builtins.bool | np.bool
_Complex128_co: TypeAlias = complex | number[_64Bit] | _Complex64_co
_ToIndex: TypeAlias = SupportsIndex | slice | EllipsisType | _ArrayLikeInt_co | None
_ToIndices: TypeAlias = _ToIndex | tuple[_ToIndex, ...]
_UnsignedIntegerCType: TypeAlias = type[
ct.c_uint8 | ct.c_uint16 | ct.c_uint32 | ct.c_uint64
| ct.c_ushort | ct.c_uint | ct.c_ulong | ct.c_ulonglong
| ct.c_size_t | ct.c_void_p
] # fmt: skip
_SignedIntegerCType: TypeAlias = type[
ct.c_int8 | ct.c_int16 | ct.c_int32 | ct.c_int64
| ct.c_short | ct.c_int | ct.c_long | ct.c_longlong
| ct.c_ssize_t
] # fmt: skip
_FloatingCType: TypeAlias = type[ct.c_float | ct.c_double | ct.c_longdouble]
_IntegerCType: TypeAlias = _UnsignedIntegerCType | _SignedIntegerCType
# some commonly used builtin types that are known to result in a
# `dtype[object_]`, when their *type* is passed to the `dtype` constructor
# NOTE: `builtins.object` should not be included here
_BuiltinObjectLike: TypeAlias = (
slice | Decimal | Fraction | UUID
| dt.date | dt.time | dt.timedelta | dt.tzinfo
| tuple[Any, ...] | list[Any] | set[Any] | frozenset[Any] | dict[Any, Any]
) # fmt: skip
# Introduce an alias for `dtype` to avoid naming conflicts.
_dtype: TypeAlias = dtype[_ScalarT]
_ByteOrderChar: TypeAlias = L["<", ">", "=", "|"]
# can be anything, is case-insensitive, and only the first character matters
_ByteOrder: TypeAlias = L[
"S", # swap the current order (default)
"<", "L", "little", # little-endian
">", "B", "big", # big endian
"=", "N", "native", # native order
"|", "I", # ignore
] # fmt: skip
_DTypeKind: TypeAlias = L[
"b", # boolean
"i", # signed integer
"u", # unsigned integer
"f", # floating-point
"c", # complex floating-point
"m", # timedelta64
"M", # datetime64
"O", # python object
"S", # byte-string (fixed-width)
"U", # unicode-string (fixed-width)
"V", # void
"T", # unicode-string (variable-width)
]
_DTypeChar: TypeAlias = L[
"?", # bool
"b", # byte
"B", # ubyte
"h", # short
"H", # ushort
"i", # intc
"I", # uintc
"l", # long
"L", # ulong
"q", # longlong
"Q", # ulonglong
"e", # half
"f", # single
"d", # double
"g", # longdouble
"F", # csingle
"D", # cdouble
"G", # clongdouble
"O", # object
"S", # bytes_ (S0)
"a", # bytes_ (deprecated)
"U", # str_
"V", # void
"M", # datetime64
"m", # timedelta64
"c", # bytes_ (S1)
"T", # StringDType
]
_DTypeNum: TypeAlias = L[
0, # bool
1, # byte
2, # ubyte
3, # short
4, # ushort
5, # intc
6, # uintc
7, # long
8, # ulong
9, # longlong
10, # ulonglong
23, # half
11, # single
12, # double
13, # longdouble
14, # csingle
15, # cdouble
16, # clongdouble
17, # object
18, # bytes_
19, # str_
20, # void
21, # datetime64
22, # timedelta64
25, # no type
256, # user-defined
2056, # StringDType
]
_DTypeBuiltinKind: TypeAlias = L[0, 1, 2]
_ArrayAPIVersion: TypeAlias = L["2021.12", "2022.12", "2023.12", "2024.12"]
_CastingKind: TypeAlias = L["no", "equiv", "safe", "same_kind", "same_value", "unsafe"]
_OrderKACF: TypeAlias = L["K", "A", "C", "F"] | None
_OrderACF: TypeAlias = L["A", "C", "F"] | None
_OrderCF: TypeAlias = L["C", "F"] | None # noqa: PYI047
_ModeKind: TypeAlias = L["raise", "wrap", "clip"]
_PartitionKind: TypeAlias = L["introselect"]
# in practice, only the first case-insensitive character is considered (so e.g.
# "QuantumSort3000" will be interpreted as quicksort).
_SortKind: TypeAlias = L[
"Q", "quick", "quicksort",
"M", "merge", "mergesort",
"H", "heap", "heapsort",
"S", "stable", "stablesort",
]
_SortSide: TypeAlias = L["left", "right"]
_ConvertibleToInt: TypeAlias = SupportsInt | SupportsIndex | _CharLike_co
_ConvertibleToFloat: TypeAlias = SupportsFloat | SupportsIndex | _CharLike_co
_ConvertibleToComplex: TypeAlias = SupportsComplex | SupportsFloat | SupportsIndex | _CharLike_co
_ConvertibleToTD64: TypeAlias = dt.timedelta | int | _CharLike_co | character | number | timedelta64 | np.bool | None
_ConvertibleToDT64: TypeAlias = dt.date | int | _CharLike_co | character | number | datetime64 | np.bool | None
_NDIterFlagsKind: TypeAlias = L[
"buffered",
"c_index",
"copy_if_overlap",
"common_dtype",
"delay_bufalloc",
"external_loop",
"f_index",
"grow_inner", "growinner",
"multi_index",
"ranged",
"refs_ok",
"reduce_ok",
"zerosize_ok",
]
_NDIterFlagsOp: TypeAlias = L[
"aligned",
"allocate",
"arraymask",
"copy",
"config",
"nbo",
"no_subtype",
"no_broadcast",
"overlap_assume_elementwise",
"readonly",
"readwrite",
"updateifcopy",
"virtual",
"writeonly",
"writemasked",
]
_MemMapModeKind: TypeAlias = L[
"readonly", "r",
"copyonwrite", "c",
"readwrite", "r+",
"write", "w+",
]
_DT64Date: TypeAlias = _HasDateAttributes | L["TODAY", "today", b"TODAY", b"today"]
_DT64Now: TypeAlias = L["NOW", "now", b"NOW", b"now"]
_NaTValue: TypeAlias = L["NAT", "NaT", "nat", b"NAT", b"NaT", b"nat"]
_MonthUnit: TypeAlias = L["Y", "M", b"Y", b"M"]
_DayUnit: TypeAlias = L["W", "D", b"W", b"D"]
_DateUnit: TypeAlias = L[_MonthUnit, _DayUnit]
_NativeTimeUnit: TypeAlias = L["h", "m", "s", "ms", "us", "μs", b"h", b"m", b"s", b"ms", b"us"]
_IntTimeUnit: TypeAlias = L["ns", "ps", "fs", "as", b"ns", b"ps", b"fs", b"as"]
_TimeUnit: TypeAlias = L[_NativeTimeUnit, _IntTimeUnit]
_NativeTD64Unit: TypeAlias = L[_DayUnit, _NativeTimeUnit]
_IntTD64Unit: TypeAlias = L[_MonthUnit, _IntTimeUnit]
_TD64Unit: TypeAlias = L[_DateUnit, _TimeUnit]
_TimeUnitSpec: TypeAlias = _TD64UnitT | tuple[_TD64UnitT, SupportsIndex]
### TypedDict's (for internal use only)
@type_check_only
class _FormerAttrsDict(TypedDict):
object: LiteralString
float: LiteralString
complex: LiteralString
str: LiteralString
int: LiteralString
### Protocols (for internal use only)
@final
@type_check_only
class _SupportsLT(Protocol):
def __lt__(self, other: Any, /) -> Any: ...
@final
@type_check_only
class _SupportsLE(Protocol):
def __le__(self, other: Any, /) -> Any: ...
@final
@type_check_only
class _SupportsGT(Protocol):
def __gt__(self, other: Any, /) -> Any: ...
@final
@type_check_only
class _SupportsGE(Protocol):
def __ge__(self, other: Any, /) -> Any: ...
@type_check_only
class _SupportsFileMethods(SupportsFlush, Protocol):
# Protocol for representing file-like-objects accepted by `ndarray.tofile` and `fromfile`
def fileno(self) -> SupportsIndex: ...
def tell(self) -> SupportsIndex: ...
def seek(self, offset: int, whence: int, /) -> object: ...
@type_check_only
class _SupportsFileMethodsRW(SupportsWrite[bytes], _SupportsFileMethods, Protocol): ...
@type_check_only
class _SupportsDLPack(Protocol[_T_contra]):
def __dlpack__(self, /, *, stream: _T_contra | None = None) -> CapsuleType: ...
@type_check_only
class _HasDType(Protocol[_T_co]):
@property
def dtype(self, /) -> _T_co: ...
@type_check_only
class _HasRealAndImag(Protocol[_RealT_co, _ImagT_co]):
@property
def real(self, /) -> _RealT_co: ...
@property
def imag(self, /) -> _ImagT_co: ...
@type_check_only
class _HasTypeWithRealAndImag(Protocol[_RealT_co, _ImagT_co]):
@property
def type(self, /) -> type[_HasRealAndImag[_RealT_co, _ImagT_co]]: ...
@type_check_only
class _HasDTypeWithRealAndImag(Protocol[_RealT_co, _ImagT_co]):
@property
def dtype(self, /) -> _HasTypeWithRealAndImag[_RealT_co, _ImagT_co]: ...
@type_check_only
class _HasDateAttributes(Protocol):
# The `datetime64` constructors requires an object with the three attributes below,
# and thus supports datetime duck typing
@property
def day(self) -> int: ...
@property
def month(self) -> int: ...
@property
def year(self) -> int: ...
### Mixins (for internal use only)
@type_check_only
class _RealMixin:
@property
def real(self) -> Self: ...
@property
def imag(self) -> Self: ...
@type_check_only
class _RoundMixin:
@overload
def __round__(self, /, ndigits: None = None) -> int: ...
@overload
def __round__(self, /, ndigits: SupportsIndex) -> Self: ...
@type_check_only
class _IntegralMixin(_RealMixin):
@property
def numerator(self) -> Self: ...
@property
def denominator(self) -> L[1]: ...
def is_integer(self, /) -> L[True]: ...
### Public API
__version__: Final[LiteralString] = ...
e: Final[float] = ...
euler_gamma: Final[float] = ...
pi: Final[float] = ...
inf: Final[float] = ...
nan: Final[float] = ...
little_endian: Final[builtins.bool] = ...
False_: Final[np.bool[L[False]]] = ...
True_: Final[np.bool[L[True]]] = ...
newaxis: Final[None] = None
# not in __all__
__NUMPY_SETUP__: Final[L[False]] = False
__numpy_submodules__: Final[set[LiteralString]] = ...
__former_attrs__: Final[_FormerAttrsDict] = ...
__future_scalars__: Final[set[L["bytes", "str", "object"]]] = ...
__array_api_version__: Final[L["2024.12"]] = "2024.12"
test: Final[PytestTester] = ...
@type_check_only
class _DTypeMeta(type):
@property
def type(cls, /) -> type[generic] | None: ...
@property
def _abstract(cls, /) -> bool: ...
@property
def _is_numeric(cls, /) -> bool: ...
@property
def _parametric(cls, /) -> bool: ...
@property
def _legacy(cls, /) -> bool: ...
@final
class dtype(Generic[_ScalarT_co], metaclass=_DTypeMeta):
names: tuple[builtins.str, ...] | None
def __hash__(self) -> int: ...
# `None` results in the default dtype
@overload
def __new__(
cls,
dtype: type[float64 | ct.c_double] | _Float64Codes | _DoubleCodes | None,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...
) -> dtype[float64]: ...
# Overload for `dtype` instances, scalar types, and instances that have a
# `dtype: dtype[_ScalarT]` attribute
@overload
def __new__(
cls,
dtype: _DTypeLike[_ScalarT],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[_ScalarT]: ...
# Builtin types
#
# NOTE: Typecheckers act as if `bool <: int <: float <: complex <: object`,
# even though at runtime `int`, `float`, and `complex` aren't subtypes..
# This makes it impossible to express e.g. "a float that isn't an int",
# since type checkers treat `_: float` like `_: float | int`.
#
# For more details, see:
# - https://github.com/numpy/numpy/issues/27032#issuecomment-2278958251
# - https://typing.readthedocs.io/en/latest/spec/special-types.html#special-cases-for-float-and-complex
@overload
def __new__(
cls,
dtype: type[builtins.bool | np.bool | ct.c_bool] | _BoolCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[np.bool]: ...
@overload
def __new__(
cls,
dtype: type[int], # also accepts `type[builtins.bool]`
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[int_ | np.bool]: ...
@overload
def __new__(
cls,
dtype: type[float], # also accepts `type[int | bool]`
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[float64 | int_ | np.bool]: ...
@overload
def __new__(
cls,
dtype: type[complex], # also accepts `type[float | int | bool]`
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[complex128 | float64 | int_ | np.bool]: ...
@overload
def __new__(
cls,
dtype: type[bytes | ct.c_char] | _BytesCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[bytes_]: ...
@overload
def __new__(
cls,
dtype: type[str] | _StrCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[str_]: ...
# NOTE: These `memoryview` overloads assume PEP 688, which requires mypy to
# be run with the (undocumented) `--disable-memoryview-promotion` flag,
# This will be the default in a future mypy release, see:
# https://github.com/python/mypy/issues/15313
# Pyright / Pylance requires setting `disableBytesTypePromotions=true`,
# which is the default in strict mode
@overload
def __new__(
cls,
dtype: type[void | memoryview] | _VoidDTypeLike | _VoidCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[void]: ...
# NOTE: `_: type[object]` would also accept e.g. `type[object | complex]`,
# and is therefore not included here
@overload
def __new__(
cls,
dtype: type[object_ | _BuiltinObjectLike | ct.py_object[Any]] | _ObjectCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[object_]: ...
# `unsignedinteger` string-based representations and ctypes
@overload
def __new__(
cls,
dtype: _UInt8Codes | _UByteCodes | type[ct.c_uint8 | ct.c_ubyte],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[uint8]: ...
@overload
def __new__(
cls,
dtype: _UInt16Codes | _UShortCodes | type[ct.c_uint16 | ct.c_ushort],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[uint16]: ...
@overload
def __new__(
cls,
dtype: _UInt32Codes | _UIntCCodes | type[ct.c_uint32 | ct.c_uint],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[uint32]: ...
@overload
def __new__(
cls,
dtype: _UInt64Codes | _ULongLongCodes | type[ct.c_uint64 | ct.c_ulonglong],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[uint64]: ...
@overload
def __new__(
cls,
dtype: _UIntPCodes | type[ct.c_void_p | ct.c_size_t],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[uintp]: ...
@overload
def __new__(
cls,
dtype: _ULongCodes | type[ct.c_ulong],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[ulong]: ...
# `signedinteger` string-based representations and ctypes
@overload
def __new__(
cls,
dtype: _Int8Codes | _ByteCodes | type[ct.c_int8 | ct.c_byte],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[int8]: ...
@overload
def __new__(
cls,
dtype: _Int16Codes | _ShortCodes | type[ct.c_int16 | ct.c_short],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[int16]: ...
@overload
def __new__(
cls,
dtype: _Int32Codes | _IntCCodes | type[ct.c_int32 | ct.c_int],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[int32]: ...
@overload
def __new__(
cls,
dtype: _Int64Codes | _LongLongCodes | type[ct.c_int64 | ct.c_longlong],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[int64]: ...
@overload
def __new__(
cls,
dtype: _IntPCodes | type[intp | ct.c_ssize_t],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[intp]: ...
@overload
def __new__(
cls,
dtype: _LongCodes | type[ct.c_long],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[long]: ...
# `floating` string-based representations and ctypes
@overload
def __new__(
cls,
dtype: _Float16Codes | _HalfCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[float16]: ...
@overload
def __new__(
cls,
dtype: _Float32Codes | _SingleCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[float32]: ...
# float64 codes are covered by overload 1
@overload
def __new__(
cls,
dtype: _LongDoubleCodes | type[ct.c_longdouble],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[longdouble]: ...
# `complexfloating` string-based representations
@overload
def __new__(
cls,
dtype: _Complex64Codes | _CSingleCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[complex64]: ...
@overload
def __new__(
cls,
dtype: _Complex128Codes | _CDoubleCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[complex128]: ...
@overload
def __new__(
cls,
dtype: _CLongDoubleCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[clongdouble]: ...
# Miscellaneous string-based representations and ctypes
@overload
def __new__(
cls,
dtype: _TD64Codes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[timedelta64]: ...
@overload
def __new__(
cls,
dtype: _DT64Codes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[datetime64]: ...
# `StringDType` requires special treatment because it has no scalar type
@overload
def __new__(
cls,
dtype: dtypes.StringDType | _StringCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtypes.StringDType: ...
# Combined char-codes and ctypes, analogous to the scalar-type hierarchy
@overload
def __new__(
cls,
dtype: _UnsignedIntegerCodes | _UnsignedIntegerCType,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[unsignedinteger]: ...
@overload
def __new__(
cls,
dtype: _SignedIntegerCodes | _SignedIntegerCType,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[signedinteger]: ...
@overload
def __new__(
cls,
dtype: _IntegerCodes | _IntegerCType,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[integer]: ...
@overload
def __new__(
cls,
dtype: _FloatingCodes | _FloatingCType,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[floating]: ...
@overload
def __new__(
cls,
dtype: _ComplexFloatingCodes,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[complexfloating]: ...
@overload
def __new__(
cls,
dtype: _InexactCodes | _FloatingCType,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[inexact]: ...
@overload
def __new__(
cls,
dtype: _CharacterCodes | type[bytes | builtins.str | ct.c_char],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[str, Any] = ...,
) -> dtype[character]: ...
# Handle strings that can't be expressed as literals; i.e. "S1", "S2", ...
@overload
def __new__(
cls,
dtype: builtins.str,
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype: ...
# Catch-all overload for object-likes
# NOTE: `object_ | Any` is NOT equivalent to `Any`. It is specified to behave
# like a "sum type" (a.k.a. variant type, discriminated union, or tagged union).
# So the union of a type and `Any` is not the same "union type" that all other
# unions are (by definition).
# https://typing.python.org/en/latest/spec/concepts.html#union-types
@overload
def __new__(
cls,
dtype: type[object],
align: builtins.bool = False,
copy: builtins.bool = False,
*,
metadata: dict[builtins.str, Any] = ...,
) -> dtype[object_ | Any]: ...
def __class_getitem__(cls, item: Any, /) -> GenericAlias: ...
@overload
def __getitem__(self: dtype[void], key: list[builtins.str], /) -> dtype[void]: ...
@overload
def __getitem__(self: dtype[void], key: builtins.str | SupportsIndex, /) -> dtype: ...
# NOTE: In the future 1-based multiplications will also yield `flexible` dtypes
@overload
def __mul__(self: _DTypeT, value: L[1], /) -> _DTypeT: ...
@overload
def __mul__(self: _FlexDTypeT, value: SupportsIndex, /) -> _FlexDTypeT: ...
@overload
def __mul__(self, value: SupportsIndex, /) -> dtype[void]: ...
# NOTE: `__rmul__` seems to be broken when used in combination with
# literals as of mypy 0.902. Set the return-type to `dtype` for
# now for non-flexible dtypes.
@overload
def __rmul__(self: _FlexDTypeT, value: SupportsIndex, /) -> _FlexDTypeT: ...
@overload
def __rmul__(self, value: SupportsIndex, /) -> dtype: ...
def __gt__(self, other: DTypeLike | None, /) -> builtins.bool: ...
def __ge__(self, other: DTypeLike | None, /) -> builtins.bool: ...
def __lt__(self, other: DTypeLike | None, /) -> builtins.bool: ...
def __le__(self, other: DTypeLike | None, /) -> builtins.bool: ...
# Explicitly defined `__eq__` and `__ne__` to get around mypy's
# `strict_equality` option; even though their signatures are
# identical to their `object`-based counterpart
def __eq__(self, other: Any, /) -> builtins.bool: ...
def __ne__(self, other: Any, /) -> builtins.bool: ...
@property
def alignment(self) -> int: ...
@property
def base(self) -> dtype: ...
@property
def byteorder(self) -> _ByteOrderChar: ...
@property
def char(self) -> _DTypeChar: ...
@property
def descr(self) -> list[tuple[LiteralString, LiteralString] | tuple[LiteralString, LiteralString, _Shape]]: ...
@property
def fields(self,) -> MappingProxyType[LiteralString, tuple[dtype, int] | tuple[dtype, int, Any]] | None: ...
@property
def flags(self) -> int: ...
@property
def hasobject(self) -> builtins.bool: ...
@property
def isbuiltin(self) -> _DTypeBuiltinKind: ...
@property
def isnative(self) -> builtins.bool: ...
@property
def isalignedstruct(self) -> builtins.bool: ...
@property
def itemsize(self) -> int: ...
@property
def kind(self) -> _DTypeKind: ...
@property
def metadata(self) -> MappingProxyType[builtins.str, Any] | None: ...
@property
def name(self) -> LiteralString: ...
@property
def num(self) -> _DTypeNum: ...
@property
def shape(self) -> _AnyShape: ...
@property
def ndim(self) -> int: ...
@property
def subdtype(self) -> tuple[dtype, _AnyShape] | None: ...
def newbyteorder(self, new_order: _ByteOrder = ..., /) -> Self: ...
@property
def str(self) -> LiteralString: ...
@property
def type(self) -> type[_ScalarT_co]: ...
@final
class flatiter(Generic[_ArrayT_co]):
__hash__: ClassVar[None] = None # type: ignore[assignment] # pyright: ignore[reportIncompatibleMethodOverride]
@property
def base(self, /) -> _ArrayT_co: ...
@property
def coords(self: flatiter[ndarray[_ShapeT]], /) -> _ShapeT: ...
@property
def index(self, /) -> int: ...
# iteration
def __len__(self, /) -> int: ...
def __iter__(self, /) -> Self: ...
def __next__(self: flatiter[NDArray[_ScalarT]], /) -> _ScalarT: ...
# indexing
@overload # nd: _[()]
def __getitem__(self, key: tuple[()], /) -> _ArrayT_co: ...
@overload # 0d; _[<integer>]
def __getitem__(self: flatiter[NDArray[_ScalarT]], key: int | integer, /) -> _ScalarT: ...
@overload # 1d; _[[*<int>]], _[:], _[...]
def __getitem__(
self: flatiter[ndarray[Any, _DTypeT]],
key: list[int] | slice | EllipsisType | flatiter[NDArray[integer]],
/,
) -> ndarray[tuple[int], _DTypeT]: ...
@overload # 2d; _[[*[*<int>]]]
def __getitem__(
self: flatiter[ndarray[Any, _DTypeT]],
key: list[list[int]],
/,
) -> ndarray[tuple[int, int], _DTypeT]: ...
@overload # ?d
def __getitem__(
self: flatiter[ndarray[Any, _DTypeT]],
key: NDArray[integer] | _NestedSequence[int],
/,
) -> ndarray[_AnyShape, _DTypeT]: ...
# NOTE: `__setitem__` operates via `unsafe` casting rules, and can thus accept any
# type accepted by the relevant underlying `np.generic` constructor, which isn't
# known statically. So we cannot meaningfully annotate the value parameter.
def __setitem__(self, key: slice | EllipsisType | _ArrayLikeInt, val: object, /) -> None: ...
# NOTE: `dtype` and `copy` are no-ops at runtime, so we don't support them here to
# avoid confusion
def __array__(
self: flatiter[ndarray[Any, _DTypeT]],
dtype: None = None,
/,
*,
copy: None = None,
) -> ndarray[tuple[int], _DTypeT]: ...
# This returns a flat copy of the underlying array, not of the iterator itself
def copy(self: flatiter[ndarray[Any, _DTypeT]], /) -> ndarray[tuple[int], _DTypeT]: ...
@type_check_only
class _ArrayOrScalarCommon:
@property
def real(self, /) -> Any: ...
@property
def imag(self, /) -> Any: ...
@property
def T(self) -> Self: ...
@property
def mT(self) -> Self: ...
@property
def data(self) -> memoryview: ...
@property
def flags(self) -> flagsobj: ...
@property
def itemsize(self) -> int: ...
@property
def nbytes(self) -> int: ...
@property
def device(self) -> L["cpu"]: ...
def __bool__(self, /) -> builtins.bool: ...
def __int__(self, /) -> int: ...
def __float__(self, /) -> float: ...
def __copy__(self) -> Self: ...
def __deepcopy__(self, memo: dict[int, Any] | None, /) -> Self: ...
# TODO: How to deal with the non-commutative nature of `==` and `!=`?
# xref numpy/numpy#17368
def __eq__(self, other: Any, /) -> Any: ...
def __ne__(self, other: Any, /) -> Any: ...
def copy(self, order: _OrderKACF = ...) -> Self: ...
def dump(self, file: StrOrBytesPath | SupportsWrite[bytes]) -> None: ...
def dumps(self) -> bytes: ...
def tobytes(self, order: _OrderKACF = ...) -> bytes: ...
def tofile(self, fid: StrOrBytesPath | _SupportsFileMethods, /, sep: str = "", format: str = "%s") -> None: ...
# generics and 0d arrays return builtin scalars
def tolist(self) -> Any: ...
def to_device(self, device: L["cpu"], /, *, stream: int | Any | None = ...) -> Self: ...
# NOTE: for `generic`, these two methods don't do anything
def fill(self, /, value: Incomplete) -> None: ...
def put(self, indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = "raise") -> None: ...
# NOTE: even on `generic` this seems to work
def setflags(
self,
/,
*,
write: builtins.bool | None = None,
align: builtins.bool | None = None,
uic: builtins.bool | None = None,
) -> None: ...
@property
def __array_interface__(self) -> dict[str, Any]: ...
@property
def __array_priority__(self) -> float: ...
@property
def __array_struct__(self) -> CapsuleType: ... # builtins.PyCapsule
def __array_namespace__(self, /, *, api_version: _ArrayAPIVersion | None = None) -> ModuleType: ...
def __setstate__(self, state: tuple[
SupportsIndex, # version
_ShapeLike, # Shape
_DTypeT_co, # DType
np.bool, # F-continuous
bytes | list[Any], # Data
], /) -> None: ...
def conj(self) -> Self: ...
def conjugate(self) -> Self: ...
def argsort(
self,
axis: SupportsIndex | None = ...,
kind: _SortKind | None = ...,
order: str | Sequence[str] | None = ...,
*,
stable: builtins.bool | None = ...,
) -> NDArray[intp]: ...
@overload # axis=None (default), out=None (default), keepdims=False (default)
def argmax(self, /, axis: None = None, out: None = None, *, keepdims: L[False] = False) -> intp: ...
@overload # axis=index, out=None (default)
def argmax(self, /, axis: SupportsIndex, out: None = None, *, keepdims: builtins.bool = False) -> Any: ...
@overload # axis=index, out=ndarray
def argmax(self, /, axis: SupportsIndex | None, out: _BoolOrIntArrayT, *, keepdims: builtins.bool = False) -> _BoolOrIntArrayT: ...
@overload
def argmax(self, /, axis: SupportsIndex | None = None, *, out: _BoolOrIntArrayT, keepdims: builtins.bool = False) -> _BoolOrIntArrayT: ...
@overload # axis=None (default), out=None (default), keepdims=False (default)
def argmin(self, /, axis: None = None, out: None = None, *, keepdims: L[False] = False) -> intp: ...
@overload # axis=index, out=None (default)
def argmin(self, /, axis: SupportsIndex, out: None = None, *, keepdims: builtins.bool = False) -> Any: ...
@overload # axis=index, out=ndarray
def argmin(self, /, axis: SupportsIndex | None, out: _BoolOrIntArrayT, *, keepdims: builtins.bool = False) -> _BoolOrIntArrayT: ...
@overload
def argmin(self, /, axis: SupportsIndex | None = None, *, out: _BoolOrIntArrayT, keepdims: builtins.bool = False) -> _BoolOrIntArrayT: ...
# Keep in sync with `MaskedArray.round`
@overload # out=None (default)
def round(self, /, decimals: SupportsIndex = 0, out: None = None) -> Self: ...
@overload # out=ndarray
def round(self, /, decimals: SupportsIndex, out: _ArrayT) -> _ArrayT: ...
@overload
def round(self, /, decimals: SupportsIndex = 0, *, out: _ArrayT) -> _ArrayT: ...
@overload # out=None (default)
def choose(self, /, choices: ArrayLike, out: None = None, mode: _ModeKind = "raise") -> NDArray[Any]: ...
@overload # out=ndarray
def choose(self, /, choices: ArrayLike, out: _ArrayT, mode: _ModeKind = "raise") -> _ArrayT: ...
# TODO: Annotate kwargs with an unpacked `TypedDict`
@overload # out: None (default)
def clip(self, /, min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any]: ...
@overload
def clip(self, /, min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any]: ...
@overload
def clip(self, /, min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any]: ...
@overload # out: ndarray
def clip(self, /, min: ArrayLike, max: ArrayLike | None, out: _ArrayT, **kwargs: Any) -> _ArrayT: ...
@overload
def clip(self, /, min: ArrayLike, max: ArrayLike | None = None, *, out: _ArrayT, **kwargs: Any) -> _ArrayT: ...
@overload
def clip(self, /, min: None, max: ArrayLike, out: _ArrayT, **kwargs: Any) -> _ArrayT: ...
@overload
def clip(self, /, min: None = None, *, max: ArrayLike, out: _ArrayT, **kwargs: Any) -> _ArrayT: ...
@overload
def compress(self, /, condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any]: ...
@overload
def compress(self, /, condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: _ArrayT) -> _ArrayT: ...
@overload
def compress(self, /, condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: _ArrayT) -> _ArrayT: ...
# Keep in sync with `MaskedArray.cumprod`
@overload # out: None (default)
def cumprod(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None) -> NDArray[Any]: ...
@overload # out: ndarray
def cumprod(self, /, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
@overload
def cumprod(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
# Keep in sync with `MaskedArray.cumsum`
@overload # out: None (default)
def cumsum(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None) -> NDArray[Any]: ...
@overload # out: ndarray
def cumsum(self, /, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
@overload
def cumsum(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
@overload
def max(
self,
/,
axis: _ShapeLike | None = None,
out: None = None,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> Any: ...
@overload
def max(
self,
/,
axis: _ShapeLike | None,
out: _ArrayT,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def max(
self,
/,
axis: _ShapeLike | None = None,
*,
out: _ArrayT,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def min(
self,
/,
axis: _ShapeLike | None = None,
out: None = None,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> Any: ...
@overload
def min(
self,
/,
axis: _ShapeLike | None,
out: _ArrayT,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def min(
self,
/,
axis: _ShapeLike | None = None,
*,
out: _ArrayT,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def sum(
self,
/,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
out: None = None,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> Any: ...
@overload
def sum(
self,
/,
axis: _ShapeLike | None,
dtype: DTypeLike | None,
out: _ArrayT,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def sum(
self,
/,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def prod(
self,
/,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
out: None = None,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> Any: ...
@overload
def prod(
self,
/,
axis: _ShapeLike | None,
dtype: DTypeLike | None,
out: _ArrayT,
*,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def prod(
self,
/,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
keepdims: builtins.bool | _NoValueType = ...,
initial: _NumberLike_co | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def mean(
self,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
out: None = None,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> Any: ...
@overload
def mean(
self,
/,
axis: _ShapeLike | None,
dtype: DTypeLike | None,
out: _ArrayT,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def mean(
self,
/,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def std(
self,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
out: None = None,
ddof: float = 0,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> Any: ...
@overload
def std(
self,
axis: _ShapeLike | None,
dtype: DTypeLike | None,
out: _ArrayT,
ddof: float = 0,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def std(
self,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
ddof: float = 0,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def var(
self,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
out: None = None,
ddof: float = 0,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> Any: ...
@overload
def var(
self,
axis: _ShapeLike | None,
dtype: DTypeLike | None,
out: _ArrayT,
ddof: float = 0,
*,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> _ArrayT: ...
@overload
def var(
self,
axis: _ShapeLike | None = None,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
ddof: float = 0,
keepdims: builtins.bool | _NoValueType = ...,
where: _ArrayLikeBool_co | _NoValueType = ...,
mean: _ArrayLikeNumber_co | _NoValueType = ...,
correction: float | _NoValueType = ...,
) -> _ArrayT: ...
class ndarray(_ArrayOrScalarCommon, Generic[_ShapeT_co, _DTypeT_co]):
__hash__: ClassVar[None] # type: ignore[assignment] # pyright: ignore[reportIncompatibleMethodOverride]
@property
def base(self) -> NDArray[Any] | None: ...
@property
def ndim(self) -> int: ...
@property
def size(self) -> int: ...
@property
def real(self: _HasDTypeWithRealAndImag[_ScalarT, object], /) -> ndarray[_ShapeT_co, dtype[_ScalarT]]: ...
@real.setter
def real(self, value: ArrayLike, /) -> None: ...
@property
def imag(self: _HasDTypeWithRealAndImag[object, _ScalarT], /) -> ndarray[_ShapeT_co, dtype[_ScalarT]]: ...
@imag.setter
def imag(self, value: ArrayLike, /) -> None: ...
def __new__(
cls,
shape: _ShapeLike,
dtype: DTypeLike | None = ...,
buffer: _SupportsBuffer | None = ...,
offset: SupportsIndex = ...,
strides: _ShapeLike | None = ...,
order: _OrderKACF = ...,
) -> Self: ...
if sys.version_info >= (3, 12):
def __buffer__(self, flags: int, /) -> memoryview: ...
def __class_getitem__(cls, item: Any, /) -> GenericAlias: ...
@overload
def __array__(self, dtype: None = None, /, *, copy: builtins.bool | None = None) -> ndarray[_ShapeT_co, _DTypeT_co]: ...
@overload
def __array__(self, dtype: _DTypeT, /, *, copy: builtins.bool | None = None) -> ndarray[_ShapeT_co, _DTypeT]: ...
def __array_ufunc__(
self,
ufunc: ufunc,
method: L["__call__", "reduce", "reduceat", "accumulate", "outer", "at"],
*inputs: Any,
**kwargs: Any,
) -> Any: ...
def __array_function__(
self,
func: Callable[..., Any],
types: Iterable[type],
args: Iterable[Any],
kwargs: Mapping[str, Any],
) -> Any: ...
# NOTE: In practice any object is accepted by `obj`, but as `__array_finalize__`
# is a pseudo-abstract method the type has been narrowed down in order to
# grant subclasses a bit more flexibility
def __array_finalize__(self, obj: NDArray[Any] | None, /) -> None: ...
def __array_wrap__(
self,
array: ndarray[_ShapeT, _DTypeT],
context: tuple[ufunc, tuple[Any, ...], int] | None = ...,
return_scalar: builtins.bool = ...,
/,
) -> ndarray[_ShapeT, _DTypeT]: ...
# Keep in sync with `MaskedArray.__getitem__`
@overload
def __getitem__(self, key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, _DTypeT_co]: ...
@overload
def __getitem__(self, key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any: ...
@overload
def __getitem__(self, key: _ToIndices, /) -> ndarray[_AnyShape, _DTypeT_co]: ...
@overload # can be of any shape
def __getitem__(self: NDArray[void], key: str, /) -> ndarray[_ShapeT_co | _AnyShape]: ...
@overload
def __getitem__(self: NDArray[void], key: list[str], /) -> ndarray[_ShapeT_co | _AnyShape, dtype[void]]: ...
@overload # flexible | object_ | bool
def __setitem__(
self: ndarray[Any, dtype[flexible | object_ | np.bool] | dtypes.StringDType],
key: _ToIndices,
value: object,
/,
) -> None: ...
@overload # integer
def __setitem__(
self: NDArray[integer],
key: _ToIndices,
value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co,
/,
) -> None: ...
@overload # floating
def __setitem__(
self: NDArray[floating],
key: _ToIndices,
value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None,
/,
) -> None: ...
@overload # complexfloating
def __setitem__(
self: NDArray[complexfloating],
key: _ToIndices,
value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None,
/,
) -> None: ...
@overload # timedelta64
def __setitem__(
self: NDArray[timedelta64],
key: _ToIndices,
value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64],
/,
) -> None: ...
@overload # datetime64
def __setitem__(
self: NDArray[datetime64],
key: _ToIndices,
value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64],
/,
) -> None: ...
@overload # void
def __setitem__(self: NDArray[void], key: str | list[str], value: object, /) -> None: ...
@overload # catch-all
def __setitem__(self, key: _ToIndices, value: ArrayLike, /) -> None: ...
@property
def ctypes(self) -> _ctypes[int]: ...
#
@property
def shape(self) -> _ShapeT_co: ...
@shape.setter
@deprecated("In-place shape modification will be deprecated in NumPy 2.5.", category=PendingDeprecationWarning)
def shape(self, value: _ShapeLike) -> None: ...
#
@property
def strides(self) -> _Shape: ...
@strides.setter
@deprecated("Setting the strides on a NumPy array has been deprecated in NumPy 2.4")
def strides(self, value: _ShapeLike) -> None: ...
#
def byteswap(self, inplace: builtins.bool = ...) -> Self: ...
@property
def flat(self) -> flatiter[Self]: ...
@overload # use the same output type as that of the underlying `generic`
def item(self: NDArray[generic[_T]], i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> _T: ...
@overload # special casing for `StringDType`, which has no scalar type
def item(
self: ndarray[Any, dtypes.StringDType],
arg0: SupportsIndex | tuple[SupportsIndex, ...] = ...,
/,
*args: SupportsIndex,
) -> str: ...
# keep in sync with `ma.MaskedArray.tolist`
@overload # this first overload prevents mypy from over-eagerly selecting `tuple[()]` in case of `_AnyShape`
def tolist(self: ndarray[tuple[Never], dtype[generic[_T]]], /) -> Any: ...
@overload
def tolist(self: ndarray[tuple[()], dtype[generic[_T]]], /) -> _T: ...
@overload
def tolist(self: ndarray[tuple[int], dtype[generic[_T]]], /) -> list[_T]: ...
@overload
def tolist(self: ndarray[tuple[int, int], dtype[generic[_T]]], /) -> list[list[_T]]: ...
@overload
def tolist(self: ndarray[tuple[int, int, int], dtype[generic[_T]]], /) -> list[list[list[_T]]]: ...
@overload
def tolist(self, /) -> Any: ...
@overload
def resize(self, new_shape: _ShapeLike, /, *, refcheck: builtins.bool = True) -> None: ...
@overload
def resize(self, /, *new_shape: SupportsIndex, refcheck: builtins.bool = True) -> None: ...
# keep in sync with `ma.MaskedArray.squeeze`
def squeeze(
self,
/,
axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...,
) -> ndarray[_AnyShape, _DTypeT_co]: ...
def swapaxes(self, axis1: SupportsIndex, axis2: SupportsIndex, /) -> Self: ...
@overload
def transpose(self, axes: _ShapeLike | None, /) -> Self: ...
@overload
def transpose(self, /, *axes: SupportsIndex) -> Self: ...
@overload
def all(
self,
axis: None = None,
out: None = None,
keepdims: L[False, 0] = False,
*,
where: _ArrayLikeBool_co = True
) -> np.bool: ...
@overload
def all(
self,
axis: int | tuple[int, ...] | None = None,
out: None = None,
keepdims: SupportsIndex = False,
*,
where: _ArrayLikeBool_co = True,
) -> np.bool | NDArray[np.bool]: ...
@overload
def all(
self,
axis: int | tuple[int, ...] | None,
out: _ArrayT,
keepdims: SupportsIndex = False,
*,
where: _ArrayLikeBool_co = True,
) -> _ArrayT: ...
@overload
def all(
self,
axis: int | tuple[int, ...] | None = None,
*,
out: _ArrayT,
keepdims: SupportsIndex = False,
where: _ArrayLikeBool_co = True,
) -> _ArrayT: ...
@overload
def any(
self,
axis: None = None,
out: None = None,
keepdims: L[False, 0] = False,
*,
where: _ArrayLikeBool_co = True
) -> np.bool: ...
@overload
def any(
self,
axis: int | tuple[int, ...] | None = None,
out: None = None,
keepdims: SupportsIndex = False,
*,
where: _ArrayLikeBool_co = True,
) -> np.bool | NDArray[np.bool]: ...
@overload
def any(
self,
axis: int | tuple[int, ...] | None,
out: _ArrayT,
keepdims: SupportsIndex = False,
*,
where: _ArrayLikeBool_co = True,
) -> _ArrayT: ...
@overload
def any(
self,
axis: int | tuple[int, ...] | None = None,
*,
out: _ArrayT,
keepdims: SupportsIndex = False,
where: _ArrayLikeBool_co = True,
) -> _ArrayT: ...
#
@overload
def partition(
self,
kth: _ArrayLikeInt,
/,
axis: SupportsIndex = -1,
kind: _PartitionKind = "introselect",
order: None = None,
) -> None: ...
@overload
def partition(
self: NDArray[void],
kth: _ArrayLikeInt,
/,
axis: SupportsIndex = -1,
kind: _PartitionKind = "introselect",
order: str | Sequence[str] | None = None,
) -> None: ...
#
@overload
def argpartition(
self,
kth: _ArrayLikeInt,
/,
axis: SupportsIndex | None = -1,
kind: _PartitionKind = "introselect",
order: None = None,
) -> NDArray[intp]: ...
@overload
def argpartition(
self: NDArray[void],
kth: _ArrayLikeInt,
/,
axis: SupportsIndex | None = -1,
kind: _PartitionKind = "introselect",
order: str | Sequence[str] | None = None,
) -> NDArray[intp]: ...
# keep in sync with `ma.MaskedArray.diagonal`
def diagonal(
self,
offset: SupportsIndex = 0,
axis1: SupportsIndex = 0,
axis2: SupportsIndex = 1,
) -> ndarray[_AnyShape, _DTypeT_co]: ...
# 1D + 1D returns a scalar;
# all other with at least 1 non-0D array return an ndarray.
@overload
def dot(self, b: _ScalarLike_co, /, out: None = None) -> NDArray[Any]: ...
@overload
def dot(self, b: ArrayLike, /, out: None = None) -> Any: ...
@overload
def dot(self, b: ArrayLike, /, out: _ArrayT) -> _ArrayT: ...
# `nonzero()` raises for 0d arrays/generics
def nonzero(self) -> tuple[ndarray[tuple[int], np.dtype[intp]], ...]: ...
@overload
def searchsorted(
self, # >= 1D array
v: _ScalarLike_co, # 0D array-like
/,
side: _SortSide = "left",
sorter: _ArrayLikeInt_co | None = None,
) -> intp: ...
@overload
def searchsorted(
self, # >= 1D array
v: ArrayLike,
/,
side: _SortSide = "left",
sorter: _ArrayLikeInt_co | None = None,
) -> NDArray[intp]: ...
def sort(
self,
/,
axis: SupportsIndex = -1,
kind: _SortKind | None = None,
order: str | Sequence[str] | None = None,
*,
stable: builtins.bool | None = None,
) -> None: ...
# Keep in sync with `MaskedArray.trace`
@overload
def trace(
self, # >= 2D array
/,
offset: SupportsIndex = 0,
axis1: SupportsIndex = 0,
axis2: SupportsIndex = 1,
dtype: DTypeLike | None = None,
out: None = None,
) -> Any: ...
@overload
def trace(
self, # >= 2D array
/,
offset: SupportsIndex = 0,
axis1: SupportsIndex = 0,
axis2: SupportsIndex = 1,
dtype: DTypeLike | None = None,
*,
out: _ArrayT,
) -> _ArrayT: ...
@overload
def trace(
self, # >= 2D array
/,
offset: SupportsIndex,
axis1: SupportsIndex,
axis2: SupportsIndex,
dtype: DTypeLike | None,
out: _ArrayT,
) -> _ArrayT: ...
@overload
def take(
self: NDArray[_ScalarT],
indices: _IntLike_co,
/,
axis: SupportsIndex | None = ...,
out: None = None,
mode: _ModeKind = ...,
) -> _ScalarT: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None = ...,
out: None = None,
mode: _ModeKind = ...,
) -> ndarray[_AnyShape, _DTypeT_co]: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None = ...,
*,
out: _ArrayT,
mode: _ModeKind = ...,
) -> _ArrayT: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None,
out: _ArrayT,
mode: _ModeKind = ...,
) -> _ArrayT: ...
# keep in sync with `ma.MaskedArray.repeat`
@overload
def repeat(self, repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], _DTypeT_co]: ...
@overload
def repeat(self, repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, _DTypeT_co]: ...
# keep in sync with `ma.MaskedArray.flatten` and `ma.MaskedArray.ravel`
def flatten(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], _DTypeT_co]: ...
def ravel(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], _DTypeT_co]: ...
# Keep in sync with `MaskedArray.reshape`
# NOTE: reshape also accepts negative integers, so we can't use integer literals
@overload # (None)
def reshape(self, shape: None, /, *, order: _OrderACF = "C", copy: builtins.bool | None = None) -> Self: ...
@overload # (empty_sequence)
def reshape( # type: ignore[overload-overlap] # mypy false positive
self,
shape: Sequence[Never],
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[()], _DTypeT_co]: ...
@overload # (() | (int) | (int, int) | ....) # up to 8-d
def reshape(
self,
shape: _AnyShapeT,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[_AnyShapeT, _DTypeT_co]: ...
@overload # (index)
def reshape(
self,
size1: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[int], _DTypeT_co]: ...
@overload # (index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[int, int], _DTypeT_co]: ...
@overload # (index, index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
size3: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[int, int, int], _DTypeT_co]: ...
@overload # (index, index, index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
size3: SupportsIndex,
size4: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[int, int, int, int], _DTypeT_co]: ...
@overload # (int, *(index, ...))
def reshape(
self,
size0: SupportsIndex,
/,
*shape: SupportsIndex,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[_AnyShape, _DTypeT_co]: ...
@overload # (sequence[index])
def reshape(
self,
shape: Sequence[SupportsIndex],
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[_AnyShape, _DTypeT_co]: ...
@overload
def astype(
self,
dtype: _DTypeLike[_ScalarT],
order: _OrderKACF = ...,
casting: _CastingKind = ...,
subok: builtins.bool = ...,
copy: builtins.bool | _CopyMode = ...,
) -> ndarray[_ShapeT_co, dtype[_ScalarT]]: ...
@overload
def astype(
self,
dtype: DTypeLike | None,
order: _OrderKACF = ...,
casting: _CastingKind = ...,
subok: builtins.bool = ...,
copy: builtins.bool | _CopyMode = ...,
) -> ndarray[_ShapeT_co, dtype]: ...
#
@overload # ()
def view(self, /) -> Self: ...
@overload # (dtype: T)
def view(self, /, dtype: _DTypeT | _HasDType[_DTypeT]) -> ndarray[_ShapeT_co, _DTypeT]: ...
@overload # (dtype: dtype[T])
def view(self, /, dtype: _DTypeLike[_ScalarT]) -> ndarray[_ShapeT_co, dtype[_ScalarT]]: ...
@overload # (type: T)
def view(self, /, *, type: type[_ArrayT]) -> _ArrayT: ...
@overload # (_: T)
def view(self, /, dtype: type[_ArrayT]) -> _ArrayT: ...
@overload # (dtype: ?)
def view(self, /, dtype: DTypeLike) -> ndarray[_ShapeT_co, dtype]: ...
@overload # (dtype: ?, type: T)
def view(self, /, dtype: DTypeLike, type: type[_ArrayT]) -> _ArrayT: ...
def setfield(self, val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None: ...
@overload
def getfield(self, /, dtype: _DTypeLike[_ScalarT], offset: SupportsIndex = 0) -> NDArray[_ScalarT]: ...
@overload
def getfield(self, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]: ...
def __index__(self: NDArray[integer], /) -> int: ...
def __complex__(self: NDArray[number | np.bool | object_], /) -> complex: ...
def __len__(self) -> int: ...
def __contains__(self, value: object, /) -> builtins.bool: ...
# NOTE: This weird `Never` tuple works around a strange mypy issue where it assigns
# `tuple[int]` to `tuple[Never]` or `tuple[int, int]` to `tuple[Never, Never]`.
# This way the bug only occurs for 9-D arrays, which are probably not very common.
@overload
def __iter__(
self: ndarray[tuple[Never, Never, Never, Never, Never, Never, Never, Never, Never], Any], /
) -> Iterator[Any]: ...
@overload # == 1-d & dtype[T \ object_]
def __iter__(self: ndarray[tuple[int], dtype[_NonObjectScalarT]], /) -> Iterator[_NonObjectScalarT]: ...
@overload # == 1-d & StringDType
def __iter__(self: ndarray[tuple[int], dtypes.StringDType], /) -> Iterator[str]: ...
@overload # >= 2-d
def __iter__(self: ndarray[tuple[int, int, *tuple[int, ...]], _DTypeT], /) -> Iterator[ndarray[_AnyShape, _DTypeT]]: ...
@overload # ?-d
def __iter__(self, /) -> Iterator[Any]: ...
#
@overload
def __lt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co, /) -> NDArray[np.bool]: ...
@overload
def __lt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[np.bool]: ...
@overload
def __lt__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[np.bool]: ...
@overload
def __lt__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[np.bool]: ...
@overload
def __lt__(
self: ndarray[Any, dtype[str_] | dtypes.StringDType], other: _ArrayLikeStr_co | _ArrayLikeString_co, /
) -> NDArray[np.bool]: ...
@overload
def __lt__(self: NDArray[object_], other: object, /) -> NDArray[np.bool]: ...
@overload
def __lt__(self, other: _ArrayLikeObject_co, /) -> NDArray[np.bool]: ...
#
@overload
def __le__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co, /) -> NDArray[np.bool]: ...
@overload
def __le__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[np.bool]: ...
@overload
def __le__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[np.bool]: ...
@overload
def __le__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[np.bool]: ...
@overload
def __le__(
self: ndarray[Any, dtype[str_] | dtypes.StringDType], other: _ArrayLikeStr_co | _ArrayLikeString_co, /
) -> NDArray[np.bool]: ...
@overload
def __le__(self: NDArray[object_], other: object, /) -> NDArray[np.bool]: ...
@overload
def __le__(self, other: _ArrayLikeObject_co, /) -> NDArray[np.bool]: ...
#
@overload
def __gt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co, /) -> NDArray[np.bool]: ...
@overload
def __gt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[np.bool]: ...
@overload
def __gt__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[np.bool]: ...
@overload
def __gt__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[np.bool]: ...
@overload
def __gt__(
self: ndarray[Any, dtype[str_] | dtypes.StringDType], other: _ArrayLikeStr_co | _ArrayLikeString_co, /
) -> NDArray[np.bool]: ...
@overload
def __gt__(self: NDArray[object_], other: object, /) -> NDArray[np.bool]: ...
@overload
def __gt__(self, other: _ArrayLikeObject_co, /) -> NDArray[np.bool]: ...
#
@overload
def __ge__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co, /) -> NDArray[np.bool]: ...
@overload
def __ge__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[np.bool]: ...
@overload
def __ge__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[np.bool]: ...
@overload
def __ge__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[np.bool]: ...
@overload
def __ge__(
self: ndarray[Any, dtype[str_] | dtypes.StringDType], other: _ArrayLikeStr_co | _ArrayLikeString_co, /
) -> NDArray[np.bool]: ...
@overload
def __ge__(self: NDArray[object_], other: object, /) -> NDArray[np.bool]: ...
@overload
def __ge__(self, other: _ArrayLikeObject_co, /) -> NDArray[np.bool]: ...
# Unary ops
# TODO: Uncomment once https://github.com/python/mypy/issues/14070 is fixed
# @overload
# def __abs__(self: ndarray[_ShapeT, dtypes.Complex64DType], /) -> ndarray[_ShapeT, dtypes.Float32DType]: ...
# @overload
# def __abs__(self: ndarray[_ShapeT, dtypes.Complex128DType], /) -> ndarray[_ShapeT, dtypes.Float64DType]: ...
# @overload
# def __abs__(self: ndarray[_ShapeT, dtypes.CLongDoubleDType], /) -> ndarray[_ShapeT, dtypes.LongDoubleDType]: ...
# @overload
# def __abs__(self: ndarray[_ShapeT, dtype[complex128]], /) -> ndarray[_ShapeT, dtype[float64]]: ...
@overload
def __abs__(self: ndarray[_ShapeT, dtype[complexfloating[_NBit]]], /) -> ndarray[_ShapeT, dtype[floating[_NBit]]]: ...
@overload
def __abs__(self: _RealArrayT, /) -> _RealArrayT: ...
def __invert__(self: _IntegralArrayT, /) -> _IntegralArrayT: ... # noqa: PYI019
def __neg__(self: _NumericArrayT, /) -> _NumericArrayT: ... # noqa: PYI019
def __pos__(self: _NumericArrayT, /) -> _NumericArrayT: ... # noqa: PYI019
# Binary ops
# TODO: Support the "1d @ 1d -> scalar" case
@overload
def __matmul__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ...
@overload
def __matmul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __matmul__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __matmul__(self: NDArray[floating[_64Bit]], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __matmul__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __matmul__(self: NDArray[complexfloating[_64Bit]], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __matmul__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __matmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __matmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __matmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __matmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
@overload
def __matmul__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __matmul__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __matmul__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload # signature equivalent to __matmul__
def __rmatmul__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ...
@overload
def __rmatmul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __rmatmul__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rmatmul__(self: NDArray[floating[_64Bit]], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rmatmul__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rmatmul__(self: NDArray[complexfloating[_64Bit]], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __rmatmul__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __rmatmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmatmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmatmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __rmatmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
@overload
def __rmatmul__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __rmatmul__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rmatmul__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __mod__(self: NDArray[_RealNumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_RealNumberT]]: ...
@overload
def __mod__(self: NDArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __mod__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __mod__(self: NDArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __mod__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __mod__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __mod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __mod__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __mod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __mod__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __mod__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __mod__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload # signature equivalent to __mod__
def __rmod__(self: NDArray[_RealNumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_RealNumberT]]: ...
@overload
def __rmod__(self: NDArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __rmod__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __rmod__(self: NDArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __rmod__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rmod__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __rmod__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __rmod__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rmod__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __divmod__(self: NDArray[_RealNumberT], rhs: int | np.bool, /) -> _2Tuple[ndarray[_ShapeT_co, dtype[_RealNumberT]]]: ...
@overload
def __divmod__(self: NDArray[_RealNumberT], rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[_RealNumberT]]: ... # type: ignore[overload-overlap]
@overload
def __divmod__(self: NDArray[np.bool], rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[int8]]: ... # type: ignore[overload-overlap]
@overload
def __divmod__(self: NDArray[np.bool], rhs: _ArrayLike[_RealNumberT], /) -> _2Tuple[NDArray[_RealNumberT]]: ... # type: ignore[overload-overlap]
@overload
def __divmod__(self: NDArray[float64], rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]]: ...
@overload
def __divmod__(self: _ArrayFloat64_co, rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]]: ...
@overload
def __divmod__(self: _ArrayUInt_co, rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger]]: ... # type: ignore[overload-overlap]
@overload
def __divmod__(self: _ArrayInt_co, rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger]]: ... # type: ignore[overload-overlap]
@overload
def __divmod__(self: _ArrayFloat_co, rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating]]: ...
@overload
def __divmod__(self: NDArray[timedelta64], rhs: _ArrayLike[timedelta64], /) -> tuple[NDArray[int64], NDArray[timedelta64]]: ...
@overload # signature equivalent to __divmod__
def __rdivmod__(self: NDArray[_RealNumberT], lhs: int | np.bool, /) -> _2Tuple[ndarray[_ShapeT_co, dtype[_RealNumberT]]]: ...
@overload
def __rdivmod__(self: NDArray[_RealNumberT], lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[_RealNumberT]]: ... # type: ignore[overload-overlap]
@overload
def __rdivmod__(self: NDArray[np.bool], lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[int8]]: ... # type: ignore[overload-overlap]
@overload
def __rdivmod__(self: NDArray[np.bool], lhs: _ArrayLike[_RealNumberT], /) -> _2Tuple[NDArray[_RealNumberT]]: ... # type: ignore[overload-overlap]
@overload
def __rdivmod__(self: NDArray[float64], lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]]: ...
@overload
def __rdivmod__(self: _ArrayFloat64_co, lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]]: ...
@overload
def __rdivmod__(self: _ArrayUInt_co, lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger]]: ... # type: ignore[overload-overlap]
@overload
def __rdivmod__(self: _ArrayInt_co, lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger]]: ... # type: ignore[overload-overlap]
@overload
def __rdivmod__(self: _ArrayFloat_co, lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating]]: ...
@overload
def __rdivmod__(self: NDArray[timedelta64], lhs: _ArrayLike[timedelta64], /) -> tuple[NDArray[int64], NDArray[timedelta64]]: ...
# Keep in sync with `MaskedArray.__add__`
@overload
def __add__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __add__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __add__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __add__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __add__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __add__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ... # type: ignore[overload-overlap]
@overload
def __add__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
@overload
def __add__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co, /) -> NDArray[datetime64]: ...
@overload
def __add__(self: NDArray[datetime64], other: _ArrayLikeTD64_co, /) -> NDArray[datetime64]: ...
@overload
def __add__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[bytes_]: ...
@overload
def __add__(self: NDArray[str_], other: _ArrayLikeStr_co, /) -> NDArray[str_]: ...
@overload
def __add__(
self: ndarray[Any, dtypes.StringDType],
other: _ArrayLikeStr_co | _ArrayLikeString_co,
/,
) -> ndarray[tuple[Any, ...], dtypes.StringDType]: ...
@overload
def __add__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __add__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__radd__`
@overload # signature equivalent to __add__
def __radd__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __radd__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __radd__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __radd__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __radd__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __radd__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ... # type: ignore[overload-overlap]
@overload
def __radd__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
@overload
def __radd__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co, /) -> NDArray[datetime64]: ...
@overload
def __radd__(self: NDArray[datetime64], other: _ArrayLikeTD64_co, /) -> NDArray[datetime64]: ...
@overload
def __radd__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> NDArray[bytes_]: ...
@overload
def __radd__(self: NDArray[str_], other: _ArrayLikeStr_co, /) -> NDArray[str_]: ...
@overload
def __radd__(
self: ndarray[Any, dtypes.StringDType],
other: _ArrayLikeStr_co | _ArrayLikeString_co,
/,
) -> ndarray[tuple[Any, ...], dtypes.StringDType]: ...
@overload
def __radd__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __radd__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__sub__`
@overload
def __sub__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __sub__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NoReturn: ...
@overload
def __sub__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __sub__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __sub__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __sub__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __sub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ... # type: ignore[overload-overlap]
@overload
def __sub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
@overload
def __sub__(self: NDArray[datetime64], other: _ArrayLikeTD64_co, /) -> NDArray[datetime64]: ...
@overload
def __sub__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64]: ...
@overload
def __sub__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __sub__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__rsub__`
@overload
def __rsub__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __rsub__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NoReturn: ...
@overload
def __rsub__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rsub__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rsub__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __rsub__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __rsub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ... # type: ignore[overload-overlap]
@overload
def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
@overload
def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co, /) -> NDArray[datetime64]: ...
@overload
def __rsub__(self: NDArray[datetime64], other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64]: ...
@overload
def __rsub__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rsub__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__mul__`
@overload
def __mul__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __mul__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __mul__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __mul__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __mul__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __mul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __mul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
@overload
def __mul__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __mul__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64]: ...
@overload
def __mul__(self: _ArrayFloat_co, other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __mul__(
self: ndarray[Any, dtype[character] | dtypes.StringDType],
other: _ArrayLikeInt,
/,
) -> ndarray[tuple[Any, ...], _DTypeT_co]: ...
@overload
def __mul__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __mul__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__rmul__`
@overload # signature equivalent to __mul__
def __rmul__(self: NDArray[_NumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __rmul__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rmul__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rmul__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __rmul__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __rmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __rmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
@overload
def __rmul__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __rmul__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64]: ...
@overload
def __rmul__(self: _ArrayFloat_co, other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __rmul__(
self: ndarray[Any, dtype[character] | dtypes.StringDType],
other: _ArrayLikeInt,
/,
) -> ndarray[tuple[Any, ...], _DTypeT_co]: ...
@overload
def __rmul__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rmul__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__truediv__`
@overload
def __truediv__(self: _ArrayInt_co | NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __truediv__(self: _ArrayFloat64_co, other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __truediv__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __truediv__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __truediv__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __truediv__(self: _ArrayFloat_co, other: _ArrayLike[floating], /) -> NDArray[floating]: ...
@overload
def __truediv__(self: NDArray[complexfloating], other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating]: ...
@overload
def __truediv__(self: _ArrayNumber_co, other: _ArrayLike[complexfloating], /) -> NDArray[complexfloating]: ...
@overload
def __truediv__(self: NDArray[inexact], other: _ArrayLikeNumber_co, /) -> NDArray[inexact]: ...
@overload
def __truediv__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __truediv__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[float64]: ...
@overload
def __truediv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co, /) -> NoReturn: ...
@overload
def __truediv__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64]: ...
@overload
def __truediv__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __truediv__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__rtruediv__`
@overload
def __rtruediv__(self: _ArrayInt_co | NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rtruediv__(self: _ArrayFloat64_co, other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rtruediv__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, /) -> NDArray[complex128]: ...
@overload
def __rtruediv__(self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> NDArray[complex128]: ...
@overload
def __rtruediv__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLike[floating], /) -> NDArray[floating]: ...
@overload
def __rtruediv__(self: NDArray[complexfloating], other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating]: ...
@overload
def __rtruediv__(self: _ArrayNumber_co, other: _ArrayLike[complexfloating], /) -> NDArray[complexfloating]: ...
@overload
def __rtruediv__(self: NDArray[inexact], other: _ArrayLikeNumber_co, /) -> NDArray[inexact]: ...
@overload
def __rtruediv__(self: NDArray[number], other: _ArrayLikeNumber_co, /) -> NDArray[number]: ...
@overload
def __rtruediv__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[float64]: ...
@overload
def __rtruediv__(self: NDArray[integer | floating], other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __rtruediv__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rtruediv__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__floordiv__`
@overload
def __floordiv__(self: NDArray[_RealNumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_RealNumberT]]: ...
@overload
def __floordiv__(self: NDArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __floordiv__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __floordiv__(self: NDArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __floordiv__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __floordiv__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __floordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __floordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __floordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __floordiv__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[int64]: ...
@overload
def __floordiv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co, /) -> NoReturn: ...
@overload
def __floordiv__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64]: ...
@overload
def __floordiv__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __floordiv__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__rfloordiv__`
@overload
def __rfloordiv__(self: NDArray[_RealNumberT], other: int | np.bool, /) -> ndarray[_ShapeT_co, dtype[_RealNumberT]]: ...
@overload
def __rfloordiv__(self: NDArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __rfloordiv__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __rfloordiv__(self: NDArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> NDArray[_RealNumberT]: ... # type: ignore[overload-overlap]
@overload
def __rfloordiv__(self: NDArray[float64], other: _ArrayLikeFloat64_co, /) -> NDArray[float64]: ...
@overload
def __rfloordiv__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64]: ...
@overload
def __rfloordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rfloordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def __rfloordiv__(self: NDArray[timedelta64], other: _ArrayLike[timedelta64], /) -> NDArray[int64]: ...
@overload
def __rfloordiv__(self: NDArray[floating | integer], other: _ArrayLike[timedelta64], /) -> NDArray[timedelta64]: ...
@overload
def __rfloordiv__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rfloordiv__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# Keep in sync with `MaskedArray.__pow__`
@overload
def __pow__(self: NDArray[_NumberT], other: int | np.bool, mod: None = None, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __pow__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: NDArray[np.bool], other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], mod: None = None, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: NDArray[float64], other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64]: ...
@overload
def __pow__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64]: ...
@overload
def __pow__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128]: ...
@overload
def __pow__(
self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], mod: None = None, /
) -> NDArray[complex128]: ...
@overload
def __pow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: _ArrayInt_co, other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __pow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating]: ...
@overload
def __pow__(self: NDArray[number], other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number]: ...
@overload
def __pow__(self: NDArray[object_], other: Any, mod: None = None, /) -> Any: ...
@overload
def __pow__(self: NDArray[Any], other: _ArrayLikeObject_co, mod: None = None, /) -> Any: ...
# Keep in sync with `MaskedArray.__rpow__`
@overload
def __rpow__(self: NDArray[_NumberT], other: int | np.bool, mod: None = None, /) -> ndarray[_ShapeT_co, dtype[_NumberT]]: ...
@overload
def __rpow__(self: NDArray[_NumberT], other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: NDArray[np.bool], other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[int8]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: NDArray[np.bool], other: _ArrayLike[_NumberT], mod: None = None, /) -> NDArray[_NumberT]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: NDArray[float64], other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64]: ...
@overload
def __rpow__(self: _ArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64]: ...
@overload
def __rpow__(self: NDArray[complex128], other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128]: ...
@overload
def __rpow__(
self: _ArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], mod: None = None, /
) -> NDArray[complex128]: ...
@overload
def __rpow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: _ArrayInt_co, other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating]: ... # type: ignore[overload-overlap]
@overload
def __rpow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating]: ...
@overload
def __rpow__(self: NDArray[number], other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number]: ...
@overload
def __rpow__(self: NDArray[object_], other: Any, mod: None = None, /) -> Any: ...
@overload
def __rpow__(self: NDArray[Any], other: _ArrayLikeObject_co, mod: None = None, /) -> Any: ...
@overload
def __lshift__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ...
@overload
def __lshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __lshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __lshift__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __lshift__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __rlshift__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ...
@overload
def __rlshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rlshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __rlshift__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rlshift__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __rshift__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ...
@overload
def __rshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __rshift__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rshift__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __rrshift__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[int8]: ...
@overload
def __rrshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rrshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __rrshift__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rrshift__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __and__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __and__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __and__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __and__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __and__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __rand__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __rand__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rand__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __rand__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rand__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __xor__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __xor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __xor__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __xor__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __xor__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __rxor__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __rxor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __rxor__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __rxor__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __rxor__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __or__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __or__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __or__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __or__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __or__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
@overload
def __ror__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def __ror__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[overload-overlap]
@overload
def __ror__(self: _ArrayInt_co, other: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def __ror__(self: NDArray[object_], other: Any, /) -> Any: ...
@overload
def __ror__(self: NDArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
# `np.generic` does not support inplace operations
# NOTE: Inplace ops generally use "same_kind" casting w.r.t. to the left
# operand. An exception to this rule are unsigned integers though, which
# also accepts a signed integer for the right operand as long it is a 0D
# object and its value is >= 0
# NOTE: Due to a mypy bug, overloading on e.g. `self: NDArray[SCT_floating]` won't
# work, as this will lead to `false negatives` when using these inplace ops.
# +=
@overload # type: ignore[misc]
def __iadd__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __iadd__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __iadd__(self: _InexactArrayT, other: _ArrayLikeFloat_co, /) -> _InexactArrayT: ...
@overload
def __iadd__(self: _NumberArrayT, other: _ArrayLikeInt_co, /) -> _NumberArrayT: ...
@overload
def __iadd__(self: _TimeArrayT, other: _ArrayLikeTD64_co, /) -> _TimeArrayT: ...
@overload
def __iadd__(self: _BytesArrayT, other: _ArrayLikeBytes_co, /) -> _BytesArrayT: ...
@overload
def __iadd__(self: _StringArrayT, other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> _StringArrayT: ...
@overload
def __iadd__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# -=
@overload # type: ignore[misc]
def __isub__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __isub__(self: _InexactArrayT, other: _ArrayLikeFloat_co, /) -> _InexactArrayT: ...
@overload
def __isub__(self: _NumberArrayT, other: _ArrayLikeInt_co, /) -> _NumberArrayT: ...
@overload
def __isub__(self: _TimeArrayT, other: _ArrayLikeTD64_co, /) -> _TimeArrayT: ...
@overload
def __isub__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# *=
@overload # type: ignore[misc]
def __imul__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __imul__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __imul__(self: _InexactTimedeltaArrayT, other: _ArrayLikeFloat_co, /) -> _InexactTimedeltaArrayT: ...
@overload
def __imul__(self: _NumberCharacterArrayT, other: _ArrayLikeInt_co, /) -> _NumberCharacterArrayT: ...
@overload
def __imul__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# @=
@overload # type: ignore[misc]
def __imatmul__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __imatmul__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __imatmul__(self: _InexactArrayT, other: _ArrayLikeFloat_co, /) -> _InexactArrayT: ...
@overload
def __imatmul__(self: _NumberArrayT, other: _ArrayLikeInt_co, /) -> _NumberArrayT: ...
@overload
def __imatmul__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# **=
@overload # type: ignore[misc]
def __ipow__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __ipow__(self: _InexactArrayT, other: _ArrayLikeFloat_co, /) -> _InexactArrayT: ...
@overload
def __ipow__(self: _NumberArrayT, other: _ArrayLikeInt_co, /) -> _NumberArrayT: ...
@overload
def __ipow__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# /=
@overload # type: ignore[misc]
def __itruediv__(self: _ComplexFloatingArrayT, other: _ArrayLikeComplex_co, /) -> _ComplexFloatingArrayT: ...
@overload
def __itruediv__(self: _InexactTimedeltaArrayT, other: _ArrayLikeFloat_co, /) -> _InexactTimedeltaArrayT: ...
@overload
def __itruediv__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# //=
# keep in sync with `__imod__`
@overload # type: ignore[misc]
def __ifloordiv__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __ifloordiv__(self: _FloatingTimedeltaArrayT, other: _ArrayLikeFloat_co, /) -> _FloatingTimedeltaArrayT: ...
@overload
def __ifloordiv__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# %=
# keep in sync with `__ifloordiv__`
@overload # type: ignore[misc]
def __imod__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __imod__(self: _FloatingArrayT, other: _ArrayLikeFloat_co, /) -> _FloatingArrayT: ...
@overload
def __imod__(self: _TimedeltaArrayT, other: _ArrayLike[timedelta64], /) -> _TimedeltaArrayT: ...
@overload
def __imod__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# <<=
# keep in sync with `__irshift__`
@overload # type: ignore[misc]
def __ilshift__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __ilshift__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# >>=
# keep in sync with `__ilshift__`
@overload # type: ignore[misc]
def __irshift__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __irshift__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# &=
# keep in sync with `__ixor__` and `__ior__`
@overload # type: ignore[misc]
def __iand__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __iand__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __iand__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# ^=
# keep in sync with `__iand__` and `__ior__`
@overload # type: ignore[misc]
def __ixor__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __ixor__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __ixor__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
# |=
# keep in sync with `__iand__` and `__ixor__`
@overload # type: ignore[misc]
def __ior__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
@overload
def __ior__(self: _IntegerArrayT, other: _ArrayLikeInt_co, /) -> _IntegerArrayT: ...
@overload
def __ior__(self: _ObjectArrayT, other: object, /) -> _ObjectArrayT: ...
#
def __dlpack__(
self: NDArray[number],
/,
*,
stream: int | Any | None = None,
max_version: tuple[int, int] | None = None,
dl_device: tuple[int, int] | None = None,
copy: builtins.bool | None = None,
) -> CapsuleType: ...
def __dlpack_device__(self, /) -> tuple[L[1], L[0]]: ...
# Keep `dtype` at the bottom to avoid name conflicts with `np.dtype`
@property
def dtype(self) -> _DTypeT_co: ...
# 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.
class generic(_ArrayOrScalarCommon, Generic[_ItemT_co]):
@abstractmethod
def __new__(cls, /, *args: Any, **kwargs: Any) -> Self: ...
# NOTE: Technically this doesn't exist at runtime, but it is unlikely to lead to
# type-unsafe situations (the abstract scalar types cannot be instantiated
# themselves) and is convenient to have, so we include it regardless. See
# https://github.com/numpy/numpy/issues/30445 for use-cases and discussion.
def __hash__(self, /) -> int: ...
if sys.version_info >= (3, 12):
def __buffer__(self, flags: int, /) -> memoryview: ...
@overload
def __array__(self, dtype: None = None, /) -> ndarray[tuple[()], dtype[Self]]: ...
@overload
def __array__(self, dtype: _DTypeT, /) -> ndarray[tuple[()], _DTypeT]: ...
@overload
def __array_wrap__(
self,
array: ndarray[_ShapeT, _DTypeT],
context: tuple[ufunc, tuple[object, ...], int] | None,
return_scalar: L[False],
/,
) -> ndarray[_ShapeT, _DTypeT]: ...
@overload
def __array_wrap__(
self,
array: ndarray[tuple[()], dtype[_ScalarT]],
context: tuple[ufunc, tuple[object, ...], int] | None = None,
return_scalar: L[True] = True,
/,
) -> _ScalarT: ...
@overload
def __array_wrap__(
self,
array: ndarray[_Shape1T, _DTypeT],
context: tuple[ufunc, tuple[object, ...], int] | None = None,
return_scalar: L[True] = True,
/,
) -> ndarray[_Shape1T, _DTypeT]: ...
@overload
def __array_wrap__(
self,
array: ndarray[_ShapeT, dtype[_ScalarT]],
context: tuple[ufunc, tuple[object, ...], int] | None = None,
return_scalar: L[True] = True,
/,
) -> _ScalarT | ndarray[_ShapeT, dtype[_ScalarT]]: ...
@property
def base(self) -> None: ...
@property
def ndim(self) -> L[0]: ...
@property
def size(self) -> L[1]: ...
@property
def shape(self) -> tuple[()]: ...
@property
def strides(self) -> tuple[()]: ...
@property
def flat(self) -> flatiter[ndarray[tuple[int], dtype[Self]]]: ...
@overload
def item(self, /) -> _ItemT_co: ...
@overload
def item(self, arg0: L[0, -1] | tuple[L[0, -1]] | tuple[()] = ..., /) -> _ItemT_co: ...
@override
def tolist(self, /) -> _ItemT_co: ...
# NOTE: these technically exist, but will always raise when called
def trace( # type: ignore[misc]
self: Never,
/,
offset: L[0] = 0,
axis1: L[0] = 0,
axis2: L[1] = 1,
dtype: None = None,
out: None = None,
) -> Never: ...
def diagonal(self: Never, /, offset: L[0] = 0, axis1: L[0] = 0, axis2: L[1] = 1) -> Never: ... # type: ignore[misc]
def swapaxes(self: Never, axis1: Never, axis2: Never, /) -> Never: ... # type: ignore[misc]
def sort(self: Never, /, axis: L[-1] = -1, kind: None = None, order: None = None, *, stable: None = None) -> Never: ... # type: ignore[misc]
def nonzero(self: Never, /) -> Never: ... # type: ignore[misc]
def setfield(self: Never, val: Never, /, dtype: Never, offset: L[0] = 0) -> None: ... # type: ignore[misc]
def searchsorted(self: Never, v: Never, /, side: L["left"] = "left", sorter: None = None) -> Never: ... # type: ignore[misc]
# NOTE: this wont't raise, but won't do anything either
@overload
def resize(self, /, *, refcheck: builtins.bool = True) -> None: ...
@overload
def resize(self, new_shape: L[0, -1] | tuple[L[0, -1]] | tuple[()], /, *, refcheck: builtins.bool = True) -> None: ...
#
def byteswap(self, /, inplace: L[False] = False) -> Self: ...
#
@overload
def astype(
self,
/,
dtype: _DTypeLike[_ScalarT],
order: _OrderKACF = "K",
casting: _CastingKind = "unsafe",
subok: builtins.bool = True,
copy: builtins.bool | _CopyMode = True,
) -> _ScalarT: ...
@overload
def astype(
self,
/,
dtype: DTypeLike | None,
order: _OrderKACF = "K",
casting: _CastingKind = "unsafe",
subok: builtins.bool = True,
copy: builtins.bool | _CopyMode = True,
) -> Incomplete: ...
# NOTE: `view` will perform a 0D->scalar cast,
# thus the array `type` is irrelevant to the output type
@overload
def view(self, type: type[ndarray] = ...) -> Self: ...
@overload
def view(self, /, dtype: _DTypeLike[_ScalarT], type: type[ndarray] = ...) -> _ScalarT: ...
@overload
def view(self, /, dtype: DTypeLike, type: type[ndarray] = ...) -> Incomplete: ...
@overload
def getfield(self, /, dtype: _DTypeLike[_ScalarT], offset: SupportsIndex = 0) -> _ScalarT: ...
@overload
def getfield(self, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> Incomplete: ...
@overload
def take(
self,
indices: _IntLike_co,
/,
axis: SupportsIndex | None = None,
out: None = None,
mode: _ModeKind = "raise",
) -> Self: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None = None,
out: None = None,
mode: _ModeKind = "raise",
) -> NDArray[Self]: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None = None,
*,
out: _ArrayT,
mode: _ModeKind = "raise",
) -> _ArrayT: ...
@overload
def take(
self,
indices: _ArrayLikeInt_co,
/,
axis: SupportsIndex | None,
out: _ArrayT,
mode: _ModeKind = "raise",
) -> _ArrayT: ...
def repeat(self, repeats: _ArrayLikeInt_co, /, axis: SupportsIndex | None = None) -> ndarray[tuple[int], dtype[Self]]: ...
def flatten(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], dtype[Self]]: ...
def ravel(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], dtype[Self]]: ...
@overload # (() | [])
def reshape(
self,
shape: tuple[()] | list[Never],
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> Self: ...
@overload # ((1, *(1, ...))@_ShapeT)
def reshape(
self,
shape: _1NShapeT,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[_1NShapeT, dtype[Self]]: ...
@overload # (Sequence[index, ...]) # not recommended
def reshape(
self,
shape: Sequence[SupportsIndex],
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> Self | ndarray[tuple[L[1], ...], dtype[Self]]: ...
@overload # _(index)
def reshape(
self,
size1: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[L[1]], dtype[Self]]: ...
@overload # _(index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[L[1], L[1]], dtype[Self]]: ...
@overload # _(index, index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
size3: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[L[1], L[1], L[1]], dtype[Self]]: ...
@overload # _(index, index, index, index)
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
size3: SupportsIndex,
size4: SupportsIndex,
/,
*,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[L[1], L[1], L[1], L[1]], dtype[Self]]: ...
@overload # _(index, index, index, index, index, *index) # ndim >= 5
def reshape(
self,
size1: SupportsIndex,
size2: SupportsIndex,
size3: SupportsIndex,
size4: SupportsIndex,
size5: SupportsIndex,
/,
*sizes6_: SupportsIndex,
order: _OrderACF = "C",
copy: builtins.bool | None = None,
) -> ndarray[tuple[L[1], L[1], L[1], L[1], L[1], *tuple[L[1], ...]], dtype[Self]]: ...
def squeeze(self, axis: L[0] | tuple[()] | None = ...) -> Self: ...
def transpose(self, axes: tuple[()] | None = ..., /) -> Self: ...
@overload
def all(
self,
/,
axis: L[0, -1] | tuple[()] | None = None,
out: None = None,
keepdims: SupportsIndex = False,
*,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True
) -> np.bool: ...
@overload
def all(
self,
/,
axis: L[0, -1] | tuple[()] | None,
out: ndarray[tuple[()], dtype[_ScalarT]],
keepdims: SupportsIndex = False,
*,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True,
) -> _ScalarT: ...
@overload
def all(
self,
/,
axis: L[0, -1] | tuple[()] | None = None,
*,
out: ndarray[tuple[()], dtype[_ScalarT]],
keepdims: SupportsIndex = False,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True,
) -> _ScalarT: ...
@overload
def any(
self,
/,
axis: L[0, -1] | tuple[()] | None = None,
out: None = None,
keepdims: SupportsIndex = False,
*,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True
) -> np.bool: ...
@overload
def any(
self,
/,
axis: L[0, -1] | tuple[()] | None,
out: ndarray[tuple[()], dtype[_ScalarT]],
keepdims: SupportsIndex = False,
*,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True,
) -> _ScalarT: ...
@overload
def any(
self,
/,
axis: L[0, -1] | tuple[()] | None = None,
*,
out: ndarray[tuple[()], dtype[_ScalarT]],
keepdims: SupportsIndex = False,
where: builtins.bool | np.bool | ndarray[tuple[()], dtype[np.bool]] = True,
) -> _ScalarT: ...
# Keep `dtype` at the bottom to avoid name conflicts with `np.dtype`
@property
def dtype(self) -> _dtype[Self]: ...
class number(generic[_NumberItemT_co], Generic[_NBit, _NumberItemT_co]):
@abstractmethod # `SupportsIndex | str | bytes` equivs `_ConvertibleToInt & _ConvertibleToFloat`
def __new__(cls, value: SupportsIndex | str | bytes = 0, /) -> Self: ...
def __class_getitem__(cls, item: Any, /) -> GenericAlias: ...
def __neg__(self) -> Self: ...
def __pos__(self) -> Self: ...
def __abs__(self) -> Self: ...
def __add__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __radd__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __sub__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __rsub__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __mul__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __rmul__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __pow__(self, other: _NumberLike_co, mod: None = None, /) -> Incomplete: ...
def __rpow__(self, other: _NumberLike_co, mod: None = None, /) -> Incomplete: ...
def __truediv__(self, other: _NumberLike_co, /) -> Incomplete: ...
def __rtruediv__(self, other: _NumberLike_co, /) -> Incomplete: ...
@overload
def __lt__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __lt__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsGT], /) -> NDArray[bool_]: ...
@overload
def __lt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __le__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __le__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsGE], /) -> NDArray[bool_]: ...
@overload
def __le__(self, other: _SupportsGE, /) -> bool_: ...
@overload
def __gt__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __gt__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsLT], /) -> NDArray[bool_]: ...
@overload
def __gt__(self, other: _SupportsLT, /) -> bool_: ...
@overload
def __ge__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __ge__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsLE], /) -> NDArray[bool_]: ...
@overload
def __ge__(self, other: _SupportsLE, /) -> bool_: ...
class bool(generic[_BoolItemT_co], Generic[_BoolItemT_co]):
@property
def itemsize(self) -> L[1]: ...
@property
def nbytes(self) -> L[1]: ...
@property
def real(self) -> Self: ...
@property
def imag(self) -> np.bool[L[False]]: ...
@overload # mypy bug workaround: https://github.com/numpy/numpy/issues/29245
def __new__(cls, value: Never, /) -> np.bool[builtins.bool]: ...
@overload
def __new__(cls, value: _Falsy = ..., /) -> np.bool[L[False]]: ...
@overload
def __new__(cls, value: _Truthy, /) -> np.bool[L[True]]: ...
@overload
def __new__(cls, value: object, /) -> np.bool[builtins.bool]: ...
def __class_getitem__(cls, type_arg: type | object, /) -> GenericAlias: ...
def __bool__(self, /) -> _BoolItemT_co: ...
@overload
def __int__(self: np.bool[L[False]], /) -> L[0]: ...
@overload
def __int__(self: np.bool[L[True]], /) -> L[1]: ...
@overload
def __int__(self, /) -> L[0, 1]: ...
def __abs__(self) -> Self: ...
@overload
def __invert__(self: np.bool[L[False]], /) -> np.bool[L[True]]: ...
@overload
def __invert__(self: np.bool[L[True]], /) -> np.bool[L[False]]: ...
@overload
def __invert__(self, /) -> np.bool: ...
@overload
def __add__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __add__(self, other: builtins.bool | bool_, /) -> bool_: ...
@overload
def __add__(self, other: int, /) -> int_: ...
@overload
def __add__(self, other: float, /) -> float64: ...
@overload
def __add__(self, other: complex, /) -> complex128: ...
@overload
def __radd__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __radd__(self, other: builtins.bool, /) -> bool_: ...
@overload
def __radd__(self, other: int, /) -> int_: ...
@overload
def __radd__(self, other: float, /) -> float64: ...
@overload
def __radd__(self, other: complex, /) -> complex128: ...
@overload
def __sub__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __sub__(self, other: int, /) -> int_: ...
@overload
def __sub__(self, other: float, /) -> float64: ...
@overload
def __sub__(self, other: complex, /) -> complex128: ...
@overload
def __rsub__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __rsub__(self, other: int, /) -> int_: ...
@overload
def __rsub__(self, other: float, /) -> float64: ...
@overload
def __rsub__(self, other: complex, /) -> complex128: ...
@overload
def __mul__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __mul__(self, other: builtins.bool | bool_, /) -> bool_: ...
@overload
def __mul__(self, other: int, /) -> int_: ...
@overload
def __mul__(self, other: float, /) -> float64: ...
@overload
def __mul__(self, other: complex, /) -> complex128: ...
@overload
def __rmul__(self, other: _NumberT, /) -> _NumberT: ...
@overload
def __rmul__(self, other: builtins.bool, /) -> bool_: ...
@overload
def __rmul__(self, other: int, /) -> int_: ...
@overload
def __rmul__(self, other: float, /) -> float64: ...
@overload
def __rmul__(self, other: complex, /) -> complex128: ...
@overload
def __pow__(self, other: _NumberT, mod: None = None, /) -> _NumberT: ...
@overload
def __pow__(self, other: builtins.bool | bool_, mod: None = None, /) -> int8: ...
@overload
def __pow__(self, other: int, mod: None = None, /) -> int_: ...
@overload
def __pow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __pow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __rpow__(self, other: _NumberT, mod: None = None, /) -> _NumberT: ...
@overload
def __rpow__(self, other: builtins.bool, mod: None = None, /) -> int8: ...
@overload
def __rpow__(self, other: int, mod: None = None, /) -> int_: ...
@overload
def __rpow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __truediv__(self, other: _InexactT, /) -> _InexactT: ...
@overload
def __truediv__(self, other: float | integer | bool_, /) -> float64: ...
@overload
def __truediv__(self, other: complex, /) -> complex128: ...
@overload
def __rtruediv__(self, other: _InexactT, /) -> _InexactT: ...
@overload
def __rtruediv__(self, other: float | integer, /) -> float64: ...
@overload
def __rtruediv__(self, other: complex, /) -> complex128: ...
@overload
def __floordiv__(self, other: _RealNumberT, /) -> _RealNumberT: ...
@overload
def __floordiv__(self, other: builtins.bool | bool_, /) -> int8: ...
@overload
def __floordiv__(self, other: int, /) -> int_: ...
@overload
def __floordiv__(self, other: float, /) -> float64: ...
@overload
def __rfloordiv__(self, other: _RealNumberT, /) -> _RealNumberT: ...
@overload
def __rfloordiv__(self, other: builtins.bool, /) -> int8: ...
@overload
def __rfloordiv__(self, other: int, /) -> int_: ...
@overload
def __rfloordiv__(self, other: float, /) -> float64: ...
# keep in sync with __floordiv__
@overload
def __mod__(self, other: _RealNumberT, /) -> _RealNumberT: ...
@overload
def __mod__(self, other: builtins.bool | bool_, /) -> int8: ...
@overload
def __mod__(self, other: int, /) -> int_: ...
@overload
def __mod__(self, other: float, /) -> float64: ...
# keep in sync with __rfloordiv__
@overload
def __rmod__(self, other: _RealNumberT, /) -> _RealNumberT: ...
@overload
def __rmod__(self, other: builtins.bool, /) -> int8: ...
@overload
def __rmod__(self, other: int, /) -> int_: ...
@overload
def __rmod__(self, other: float, /) -> float64: ...
# keep in sync with __mod__
@overload
def __divmod__(self, other: _RealNumberT, /) -> _2Tuple[_RealNumberT]: ...
@overload
def __divmod__(self, other: builtins.bool | bool_, /) -> _2Tuple[int8]: ...
@overload
def __divmod__(self, other: int, /) -> _2Tuple[int_]: ...
@overload
def __divmod__(self, other: float, /) -> _2Tuple[float64]: ...
# keep in sync with __rmod__
@overload
def __rdivmod__(self, other: _RealNumberT, /) -> _2Tuple[_RealNumberT]: ...
@overload
def __rdivmod__(self, other: builtins.bool, /) -> _2Tuple[int8]: ...
@overload
def __rdivmod__(self, other: int, /) -> _2Tuple[int_]: ...
@overload
def __rdivmod__(self, other: float, /) -> _2Tuple[float64]: ...
@overload
def __lshift__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __lshift__(self, other: builtins.bool | bool_, /) -> int8: ...
@overload
def __lshift__(self, other: int, /) -> int_: ...
@overload
def __rlshift__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __rlshift__(self, other: builtins.bool, /) -> int8: ...
@overload
def __rlshift__(self, other: int, /) -> int_: ...
# keep in sync with __lshift__
@overload
def __rshift__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __rshift__(self, other: builtins.bool | bool_, /) -> int8: ...
@overload
def __rshift__(self, other: int, /) -> int_: ...
# keep in sync with __rlshift__
@overload
def __rrshift__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __rrshift__(self, other: builtins.bool, /) -> int8: ...
@overload
def __rrshift__(self, other: int, /) -> int_: ...
@overload
def __and__(self: np.bool[L[False]], other: builtins.bool | np.bool, /) -> np.bool[L[False]]: ...
@overload
def __and__(self, other: L[False] | np.bool[L[False]], /) -> np.bool[L[False]]: ...
@overload
def __and__(self, other: L[True] | np.bool[L[True]], /) -> Self: ...
@overload
def __and__(self, other: builtins.bool | np.bool, /) -> np.bool: ...
@overload
def __and__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __and__(self, other: int, /) -> np.bool | intp: ...
__rand__ = __and__
@overload
def __xor__(self: np.bool[L[False]], other: _BoolItemT | np.bool[_BoolItemT], /) -> np.bool[_BoolItemT]: ...
@overload
def __xor__(self: np.bool[L[True]], other: L[True] | np.bool[L[True]], /) -> np.bool[L[False]]: ...
@overload
def __xor__(self, other: L[False] | np.bool[L[False]], /) -> Self: ...
@overload
def __xor__(self, other: builtins.bool | np.bool, /) -> np.bool: ...
@overload
def __xor__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __xor__(self, other: int, /) -> np.bool | intp: ...
__rxor__ = __xor__
@overload
def __or__(self: np.bool[L[True]], other: builtins.bool | np.bool, /) -> np.bool[L[True]]: ...
@overload
def __or__(self, other: L[False] | np.bool[L[False]], /) -> Self: ...
@overload
def __or__(self, other: L[True] | np.bool[L[True]], /) -> np.bool[L[True]]: ...
@overload
def __or__(self, other: builtins.bool | np.bool, /) -> np.bool: ...
@overload
def __or__(self, other: _IntegerT, /) -> _IntegerT: ...
@overload
def __or__(self, other: int, /) -> np.bool | intp: ...
__ror__ = __or__
@overload
def __lt__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __lt__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsGT], /) -> NDArray[bool_]: ...
@overload
def __lt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __le__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __le__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsGE], /) -> NDArray[bool_]: ...
@overload
def __le__(self, other: _SupportsGE, /) -> bool_: ...
@overload
def __gt__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __gt__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsLT], /) -> NDArray[bool_]: ...
@overload
def __gt__(self, other: _SupportsLT, /) -> bool_: ...
@overload
def __ge__(self, other: _NumberLike_co, /) -> bool_: ...
@overload
def __ge__(self, other: _ArrayLikeNumber_co | _NestedSequence[_SupportsLE], /) -> NDArray[bool_]: ...
@overload
def __ge__(self, other: _SupportsLE, /) -> bool_: ...
# NOTE: This should _not_ be `Final` or a `TypeAlias`
bool_ = bool
# NOTE: The `object_` constructor returns the passed object, so instances with type
# `object_` cannot exists (at runtime).
# NOTE: Because mypy has some long-standing bugs related to `__new__`, `object_` can't
# be made generic.
@final
class object_(_RealMixin, generic):
@overload
def __new__(cls, value: None = None, /) -> None: ... # type: ignore[misc]
@overload
def __new__(cls, value: _AnyStr, /) -> _AnyStr: ... # type: ignore[misc]
@overload
def __new__(cls, value: ndarray[_ShapeT, Any], /) -> ndarray[_ShapeT, dtype[Self]]: ... # type: ignore[misc]
@overload
def __new__(cls, value: SupportsLenAndGetItem[object], /) -> NDArray[Self]: ... # type: ignore[misc]
@overload
def __new__(cls, value: _T, /) -> _T: ... # type: ignore[misc]
@overload # catch-all
def __new__(cls, value: Any = ..., /) -> object | NDArray[Self]: ... # type: ignore[misc]
def __hash__(self, /) -> int: ...
def __abs__(self, /) -> object_: ... # this affects NDArray[object_].__abs__
def __call__(self, /, *args: object, **kwargs: object) -> Any: ...
if sys.version_info >= (3, 12):
def __release_buffer__(self, buffer: memoryview, /) -> None: ...
class integer(_IntegralMixin, _RoundMixin, number[_NBit, int]):
@abstractmethod
def __new__(cls, value: _ConvertibleToInt = 0, /) -> Self: ...
# NOTE: `bit_count` and `__index__` are technically defined in the concrete subtypes
def bit_count(self, /) -> int: ...
def __index__(self, /) -> int: ...
def __invert__(self, /) -> Self: ...
@override # type: ignore[override]
@overload
def __truediv__(self, other: float | integer, /) -> float64: ...
@overload
def __truediv__(self, other: complex, /) -> complex128: ...
@override # type: ignore[override]
@overload
def __rtruediv__(self, other: float | integer, /) -> float64: ...
@overload
def __rtruediv__(self, other: complex, /) -> complex128: ...
def __floordiv__(self, value: _IntLike_co, /) -> integer: ...
def __rfloordiv__(self, value: _IntLike_co, /) -> integer: ...
def __mod__(self, value: _IntLike_co, /) -> integer: ...
def __rmod__(self, value: _IntLike_co, /) -> integer: ...
def __divmod__(self, value: _IntLike_co, /) -> _2Tuple[integer]: ...
def __rdivmod__(self, value: _IntLike_co, /) -> _2Tuple[integer]: ...
# Ensure that objects annotated as `integer` support bit-wise operations
def __lshift__(self, other: _IntLike_co, /) -> integer: ...
def __rlshift__(self, other: _IntLike_co, /) -> integer: ...
def __rshift__(self, other: _IntLike_co, /) -> integer: ...
def __rrshift__(self, other: _IntLike_co, /) -> integer: ...
def __and__(self, other: _IntLike_co, /) -> integer: ...
def __rand__(self, other: _IntLike_co, /) -> integer: ...
def __or__(self, other: _IntLike_co, /) -> integer: ...
def __ror__(self, other: _IntLike_co, /) -> integer: ...
def __xor__(self, other: _IntLike_co, /) -> integer: ...
def __rxor__(self, other: _IntLike_co, /) -> integer: ...
class signedinteger(integer[_NBit]):
def __new__(cls, value: _ConvertibleToInt = 0, /) -> Self: ...
# arithmetic ops
@override # type: ignore[override]
@overload
def __add__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __add__(self, other: float, /) -> float64: ...
@overload
def __add__(self, other: complex, /) -> complex128: ...
@overload
def __add__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __add__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __radd__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __radd__(self, other: float, /) -> float64: ...
@overload
def __radd__(self, other: complex, /) -> complex128: ...
@overload
def __radd__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __radd__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __sub__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __sub__(self, other: float, /) -> float64: ...
@overload
def __sub__(self, other: complex, /) -> complex128: ...
@overload
def __sub__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __sub__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rsub__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rsub__(self, other: float, /) -> float64: ...
@overload
def __rsub__(self, other: complex, /) -> complex128: ...
@overload
def __rsub__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __rsub__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __mul__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __mul__(self, other: float, /) -> float64: ...
@overload
def __mul__(self, other: complex, /) -> complex128: ...
@overload
def __mul__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __mul__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rmul__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rmul__(self, other: float, /) -> float64: ...
@overload
def __rmul__(self, other: complex, /) -> complex128: ...
@overload
def __rmul__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __rmul__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __pow__(self, other: int | int8 | bool_ | Self, mod: None = None, /) -> Self: ...
@overload
def __pow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __pow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __pow__(self, other: signedinteger, mod: None = None, /) -> signedinteger: ...
@overload
def __pow__(self, other: integer, mod: None = None, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rpow__(self, other: int | int8 | bool_, mod: None = None, /) -> Self: ...
@overload
def __rpow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __rpow__(self, other: signedinteger, mod: None = None, /) -> signedinteger: ...
@overload
def __rpow__(self, other: integer, mod: None = None, /) -> Incomplete: ...
# modular division ops
@override # type: ignore[override]
@overload
def __floordiv__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __floordiv__(self, other: float, /) -> float64: ...
@overload
def __floordiv__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __floordiv__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rfloordiv__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rfloordiv__(self, other: float, /) -> float64: ...
@overload
def __rfloordiv__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __rfloordiv__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __mod__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __mod__(self, other: float, /) -> float64: ...
@overload
def __mod__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __mod__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rmod__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rmod__(self, other: float, /) -> float64: ...
@overload
def __rmod__(self, other: signedinteger, /) -> signedinteger: ...
@overload
def __rmod__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __divmod__(self, other: int | int8 | bool_ | Self, /) -> _2Tuple[Self]: ...
@overload
def __divmod__(self, other: float, /) -> _2Tuple[float64]: ...
@overload
def __divmod__(self, other: signedinteger, /) -> _2Tuple[signedinteger]: ...
@overload
def __divmod__(self, other: integer, /) -> _2Tuple[Incomplete]: ...
@override # type: ignore[override]
@overload
def __rdivmod__(self, other: int | int8 | bool_, /) -> _2Tuple[Self]: ...
@overload
def __rdivmod__(self, other: float, /) -> _2Tuple[float64]: ...
@overload
def __rdivmod__(self, other: signedinteger, /) -> _2Tuple[signedinteger]: ...
@overload
def __rdivmod__(self, other: integer, /) -> _2Tuple[Incomplete]: ...
# bitwise ops
@override # type: ignore[override]
@overload
def __lshift__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __lshift__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rlshift__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rlshift__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rshift__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __rshift__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rrshift__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rrshift__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __and__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __and__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rand__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rand__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __xor__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __xor__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rxor__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rxor__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __or__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __or__(self, other: integer, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __ror__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __ror__(self, other: integer, /) -> signedinteger: ...
int8 = signedinteger[_8Bit]
int16 = signedinteger[_16Bit]
int32 = signedinteger[_32Bit]
int64 = signedinteger[_64Bit]
byte = signedinteger[_NBitByte]
short = signedinteger[_NBitShort]
intc = signedinteger[_NBitIntC]
intp = signedinteger[_NBitIntP]
int_ = intp
long = signedinteger[_NBitLong]
longlong = signedinteger[_NBitLongLong]
class unsignedinteger(integer[_NBit1]):
def __new__(cls, value: _ConvertibleToInt = 0, /) -> Self: ...
# arithmetic ops
@override # type: ignore[override]
@overload
def __add__(self, other: int | uint8 | bool_ | Self, /) -> Self: ...
@overload
def __add__(self, other: float, /) -> float64: ...
@overload
def __add__(self, other: complex, /) -> complex128: ...
@overload
def __add__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __add__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __radd__(self, other: int | uint8 | bool_, /) -> Self: ...
@overload
def __radd__(self, other: float, /) -> float64: ...
@overload
def __radd__(self, other: complex, /) -> complex128: ...
@overload
def __radd__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __radd__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __sub__(self, other: int | uint8 | bool_ | Self, /) -> Self: ...
@overload
def __sub__(self, other: float, /) -> float64: ...
@overload
def __sub__(self, other: complex, /) -> complex128: ...
@overload
def __sub__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __sub__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rsub__(self, other: int | uint8 | bool_, /) -> Self: ...
@overload
def __rsub__(self, other: float, /) -> float64: ...
@overload
def __rsub__(self, other: complex, /) -> complex128: ...
@overload
def __rsub__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rsub__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __mul__(self, other: int | uint8 | bool_ | Self, /) -> Self: ...
@overload
def __mul__(self, other: float, /) -> float64: ...
@overload
def __mul__(self, other: complex, /) -> complex128: ...
@overload
def __mul__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __mul__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rmul__(self, other: int | uint8 | bool_, /) -> Self: ...
@overload
def __rmul__(self, other: float, /) -> float64: ...
@overload
def __rmul__(self, other: complex, /) -> complex128: ...
@overload
def __rmul__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rmul__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __pow__(self, other: int | uint8 | bool_ | Self, mod: None = None, /) -> Self: ...
@overload
def __pow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __pow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __pow__(self, other: unsignedinteger, mod: None = None, /) -> unsignedinteger: ...
@overload
def __pow__(self, other: integer, mod: None = None, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rpow__(self, other: int | uint8 | bool_, mod: None = None, /) -> Self: ...
@overload
def __rpow__(self, other: float, mod: None = None, /) -> float64: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> complex128: ...
@overload
def __rpow__(self, other: unsignedinteger, mod: None = None, /) -> unsignedinteger: ...
@overload
def __rpow__(self, other: integer, mod: None = None, /) -> Incomplete: ...
# modular division ops
@override # type: ignore[override]
@overload
def __floordiv__(self, other: int | uint8 | bool_ | Self, /) -> Self: ...
@overload
def __floordiv__(self, other: float, /) -> float64: ...
@overload
def __floordiv__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __floordiv__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rfloordiv__(self, other: int | uint8 | bool_, /) -> Self: ...
@overload
def __rfloordiv__(self, other: float, /) -> float64: ...
@overload
def __rfloordiv__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rfloordiv__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __mod__(self, other: int | uint8 | bool_ | Self, /) -> Self: ...
@overload
def __mod__(self, other: float, /) -> float64: ...
@overload
def __mod__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __mod__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __rmod__(self, other: int | uint8 | bool_, /) -> Self: ...
@overload
def __rmod__(self, other: float, /) -> float64: ...
@overload
def __rmod__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rmod__(self, other: integer, /) -> Incomplete: ...
@override # type: ignore[override]
@overload
def __divmod__(self, other: int | uint8 | bool_ | Self, /) -> _2Tuple[Self]: ...
@overload
def __divmod__(self, other: float, /) -> _2Tuple[float64]: ...
@overload
def __divmod__(self, other: unsignedinteger, /) -> _2Tuple[unsignedinteger]: ...
@overload
def __divmod__(self, other: integer, /) -> _2Tuple[Incomplete]: ...
@override # type: ignore[override]
@overload
def __rdivmod__(self, other: int | uint8 | bool_, /) -> _2Tuple[Self]: ...
@overload
def __rdivmod__(self, other: float, /) -> _2Tuple[float64]: ...
@overload
def __rdivmod__(self, other: unsignedinteger, /) -> _2Tuple[unsignedinteger]: ...
@overload
def __rdivmod__(self, other: integer, /) -> _2Tuple[Incomplete]: ...
# bitwise ops
@override # type: ignore[override]
@overload
def __lshift__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __lshift__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __lshift__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rlshift__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rlshift__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rlshift__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rshift__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __rshift__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rshift__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rrshift__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rrshift__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rrshift__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __and__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __and__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __and__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rand__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rand__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rand__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __xor__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __xor__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __xor__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __rxor__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __rxor__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __rxor__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __or__(self, other: int | int8 | bool_ | Self, /) -> Self: ...
@overload
def __or__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __or__(self, other: signedinteger, /) -> signedinteger: ...
@override # type: ignore[override]
@overload
def __ror__(self, other: int | int8 | bool_, /) -> Self: ...
@overload
def __ror__(self, other: unsignedinteger, /) -> unsignedinteger: ...
@overload
def __ror__(self, other: signedinteger, /) -> signedinteger: ...
uint8: TypeAlias = unsignedinteger[_8Bit]
uint16: TypeAlias = unsignedinteger[_16Bit]
uint32: TypeAlias = unsignedinteger[_32Bit]
uint64: TypeAlias = unsignedinteger[_64Bit]
ubyte: TypeAlias = unsignedinteger[_NBitByte]
ushort: TypeAlias = unsignedinteger[_NBitShort]
uintc: TypeAlias = unsignedinteger[_NBitIntC]
uintp: TypeAlias = unsignedinteger[_NBitIntP]
uint: TypeAlias = uintp
ulong: TypeAlias = unsignedinteger[_NBitLong]
ulonglong: TypeAlias = unsignedinteger[_NBitLongLong]
class inexact(number[_NBit, _InexactItemT_co], Generic[_NBit, _InexactItemT_co]):
@abstractmethod
def __new__(cls, value: _ConvertibleToFloat | None = 0, /) -> Self: ...
class floating(_RealMixin, _RoundMixin, inexact[_NBit1, float]):
def __new__(cls, value: _ConvertibleToFloat | None = 0, /) -> Self: ...
# arithmetic ops
@override # type: ignore[override]
@overload
def __add__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __add__(self, other: integer | floating, /) -> floating: ...
@overload
def __add__(self, other: float, /) -> Self: ...
@overload
def __add__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __radd__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __radd__(self, other: integer | floating, /) -> floating: ...
@overload
def __radd__(self, other: float, /) -> Self: ...
@overload
def __radd__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __sub__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __sub__(self, other: integer | floating, /) -> floating: ...
@overload
def __sub__(self, other: float, /) -> Self: ...
@overload
def __sub__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __rsub__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __rsub__(self, other: integer | floating, /) -> floating: ...
@overload
def __rsub__(self, other: float, /) -> Self: ...
@overload
def __rsub__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __mul__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __mul__(self, other: integer | floating, /) -> floating: ...
@overload
def __mul__(self, other: float, /) -> Self: ...
@overload
def __mul__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __rmul__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __rmul__(self, other: integer | floating, /) -> floating: ...
@overload
def __rmul__(self, other: float, /) -> Self: ...
@overload
def __rmul__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __pow__(self, other: int | float16 | uint8 | int8 | bool_ | Self, mod: None = None, /) -> Self: ...
@overload
def __pow__(self, other: integer | floating, mod: None = None, /) -> floating: ...
@overload
def __pow__(self, other: float, mod: None = None, /) -> Self: ...
@overload
def __pow__(self, other: complex, mod: None = None, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __rpow__(self, other: int | float16 | uint8 | int8 | bool_, mod: None = None, /) -> Self: ...
@overload
def __rpow__(self, other: integer | floating, mod: None = None, /) -> floating: ...
@overload
def __rpow__(self, other: float, mod: None = None, /) -> Self: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __truediv__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __truediv__(self, other: integer | floating, /) -> floating: ...
@overload
def __truediv__(self, other: float, /) -> Self: ...
@overload
def __truediv__(self, other: complex, /) -> complexfloating: ...
@override # type: ignore[override]
@overload
def __rtruediv__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __rtruediv__(self, other: integer | floating, /) -> floating: ...
@overload
def __rtruediv__(self, other: float, /) -> Self: ...
@overload
def __rtruediv__(self, other: complex, /) -> complexfloating: ...
# modular division ops
@overload
def __floordiv__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __floordiv__(self, other: integer | floating, /) -> floating: ...
@overload
def __floordiv__(self, other: float, /) -> Self: ...
@overload
def __rfloordiv__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __rfloordiv__(self, other: integer | floating, /) -> floating: ...
@overload
def __rfloordiv__(self, other: float, /) -> Self: ...
@overload
def __mod__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> Self: ...
@overload
def __mod__(self, other: integer | floating, /) -> floating: ...
@overload
def __mod__(self, other: float, /) -> Self: ...
@overload
def __rmod__(self, other: int | float16 | uint8 | int8 | bool_, /) -> Self: ...
@overload
def __rmod__(self, other: integer | floating, /) -> floating: ...
@overload
def __rmod__(self, other: float, /) -> Self: ...
@overload
def __divmod__(self, other: int | float16 | uint8 | int8 | bool_ | Self, /) -> _2Tuple[Self]: ...
@overload
def __divmod__(self, other: integer | floating, /) -> _2Tuple[floating]: ...
@overload
def __divmod__(self, other: float, /) -> _2Tuple[Self]: ...
@overload
def __rdivmod__(self, other: int | float16 | uint8 | int8 | bool_, /) -> _2Tuple[Self]: ...
@overload
def __rdivmod__(self, other: integer | floating, /) -> _2Tuple[floating]: ...
@overload
def __rdivmod__(self, other: float, /) -> _2Tuple[Self]: ...
# NOTE: `is_integer` and `as_integer_ratio` are technically defined in the concrete subtypes
def is_integer(self, /) -> builtins.bool: ...
def as_integer_ratio(self, /) -> tuple[int, int]: ...
float16: TypeAlias = floating[_16Bit]
float32: TypeAlias = floating[_32Bit]
# either a C `double`, `float`, or `longdouble`
class float64(floating[_64Bit], float): # type: ignore[misc]
@property
def itemsize(self) -> L[8]: ...
@property
def nbytes(self) -> L[8]: ...
# overrides for `floating` and `builtins.float` compatibility (`_RealMixin` doesn't work)
@property
def real(self) -> Self: ...
@property
def imag(self) -> Self: ...
def conjugate(self) -> Self: ...
def __getnewargs__(self, /) -> tuple[float]: ...
@classmethod
def __getformat__(cls, typestr: L["double", "float"], /) -> str: ... # undocumented
# float64-specific operator overrides
# NOTE: Mypy reports [misc] errors about "unsafely overlapping signatures" for the
# reflected methods. But since they are identical to the non-reflected versions,
# these errors appear to be false positives.
@overload # type: ignore[override]
def __add__(self, other: _Float64_co, /) -> float64: ...
@overload
def __add__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __add__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __add__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __radd__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
@overload
def __radd__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... # type: ignore[misc]
@overload
def __radd__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __radd__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __sub__(self, other: _Float64_co, /) -> float64: ...
@overload
def __sub__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __sub__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __sub__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __rsub__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
@overload
def __rsub__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... # type: ignore[misc]
@overload
def __rsub__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __rsub__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __mul__(self, other: _Float64_co, /) -> float64: ...
@overload
def __mul__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __mul__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __mul__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __rmul__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
@overload
def __rmul__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... # type: ignore[misc]
@overload
def __rmul__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __rmul__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __truediv__(self, other: _Float64_co, /) -> float64: ...
@overload
def __truediv__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __truediv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __truediv__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __rtruediv__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
@overload
def __rtruediv__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... # type: ignore[misc]
@overload
def __rtruediv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __rtruediv__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __floordiv__(self, other: _Float64_co, /) -> float64: ...
@overload
def __floordiv__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __floordiv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __floordiv__(self, other: complex, /) -> float64 | complex128: ...
@overload
def __rfloordiv__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
@overload
def __rfloordiv__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ...
@overload
def __rfloordiv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __rfloordiv__(self, other: complex, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __pow__(self, other: _Float64_co, mod: None = None, /) -> float64: ...
@overload
def __pow__(self, other: complexfloating[_64Bit, _64Bit], mod: None = None, /) -> complex128: ...
@overload
def __pow__(
self, other: complexfloating[_NBit1, _NBit2], mod: None = None, /
) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __pow__(self, other: complex, mod: None = None, /) -> float64 | complex128: ...
@overload # type: ignore[override]
def __rpow__(self, other: _Float64_co, mod: None = None, /) -> float64: ... # type: ignore[misc]
@overload
def __rpow__(self, other: complexfloating[_64Bit, _64Bit], mod: None = None, /) -> complex128: ... # type: ignore[misc]
@overload
def __rpow__(
self, other: complexfloating[_NBit1, _NBit2], mod: None = None, /
) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> float64 | complex128: ...
def __mod__(self, other: _Float64_co, /) -> float64: ...
def __rmod__(self, other: _Float64_co, /) -> float64: ... # type: ignore[misc]
def __divmod__(self, other: _Float64_co, /) -> _2Tuple[float64]: ...
def __rdivmod__(self, other: _Float64_co, /) -> _2Tuple[float64]: ... # type: ignore[misc]
half: TypeAlias = float16
single: TypeAlias = float32
double: TypeAlias = float64
longdouble: TypeAlias = floating[_NBitLongDouble]
# 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[_NBit1, complex], Generic[_NBit1, _NBit2]):
@overload
def __new__(
cls,
real: complex | SupportsComplex | SupportsFloat | SupportsIndex = 0,
imag: complex | SupportsFloat | SupportsIndex = 0,
/,
) -> Self: ...
@overload
def __new__(cls, real: _ConvertibleToComplex | None = 0, /) -> Self: ...
@property
def real(self) -> floating[_NBit1]: ...
@property
def imag(self) -> floating[_NBit2]: ...
# NOTE: `__complex__` is technically defined in the concrete subtypes
def __complex__(self, /) -> complex: ...
def __abs__(self, /) -> floating[_NBit1 | _NBit2]: ... # type: ignore[override]
@overload # type: ignore[override]
def __add__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __add__(self, other: complex | float64 | complex128, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __add__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __radd__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __radd__(self, other: complex, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __radd__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __sub__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __sub__(self, other: complex | float64 | complex128, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __sub__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __rsub__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __rsub__(self, other: complex, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __rsub__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __mul__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __mul__(self, other: complex | float64 | complex128, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __mul__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __rmul__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __rmul__(self, other: complex, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __rmul__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __truediv__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __truediv__(self, other: complex | float64 | complex128, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __truediv__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __rtruediv__(self, other: _Complex64_co, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __rtruediv__(self, other: complex, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __rtruediv__(self, other: number[_NBit], /) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __pow__(self, other: _Complex64_co, mod: None = None, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __pow__(
self, other: complex | float64 | complex128, mod: None = None, /
) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __pow__(
self, other: number[_NBit], mod: None = None, /
) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
@overload # type: ignore[override]
def __rpow__(self, other: _Complex64_co, mod: None = None, /) -> complexfloating[_NBit1, _NBit2]: ...
@overload
def __rpow__(self, other: complex, mod: None = None, /) -> complexfloating[_NBit1, _NBit2] | complex128: ...
@overload
def __rpow__(
self, other: number[_NBit], mod: None = None, /
) -> complexfloating[_NBit1, _NBit2] | complexfloating[_NBit, _NBit]: ...
complex64: TypeAlias = complexfloating[_32Bit]
class complex128(complexfloating[_64Bit, _64Bit], complex):
@property
def itemsize(self) -> L[16]: ...
@property
def nbytes(self) -> L[16]: ...
# overrides for `floating` and `builtins.float` compatibility
@property
def real(self) -> float64: ...
@property
def imag(self) -> float64: ...
def conjugate(self) -> Self: ...
def __abs__(self) -> float64: ... # type: ignore[override]
def __getnewargs__(self, /) -> tuple[float, float]: ...
# complex128-specific operator overrides
@overload # type: ignore[override]
def __add__(self, other: _Complex128_co, /) -> complex128: ...
@overload
def __add__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
def __radd__(self, other: _Complex128_co, /) -> complex128: ... # type: ignore[override]
@overload # type: ignore[override]
def __sub__(self, other: _Complex128_co, /) -> complex128: ...
@overload
def __sub__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
def __rsub__(self, other: _Complex128_co, /) -> complex128: ... # type: ignore[override]
@overload # type: ignore[override]
def __mul__(self, other: _Complex128_co, /) -> complex128: ...
@overload
def __mul__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
def __rmul__(self, other: _Complex128_co, /) -> complex128: ... # type: ignore[override]
@overload # type: ignore[override]
def __truediv__(self, other: _Complex128_co, /) -> complex128: ...
@overload
def __truediv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
def __rtruediv__(self, other: _Complex128_co, /) -> complex128: ... # type: ignore[override]
@overload # type: ignore[override]
def __pow__(self, other: _Complex128_co, mod: None = None, /) -> complex128: ...
@overload
def __pow__(
self, other: complexfloating[_NBit1, _NBit2], mod: None = None, /
) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ...
def __rpow__(self, other: _Complex128_co, mod: None = None, /) -> complex128: ... # type: ignore[override]
csingle: TypeAlias = complex64
cdouble: TypeAlias = complex128
clongdouble: TypeAlias = complexfloating[_NBitLongDouble]
class timedelta64(_IntegralMixin, generic[_TD64ItemT_co], Generic[_TD64ItemT_co]):
@property
def itemsize(self) -> L[8]: ...
@property
def nbytes(self) -> L[8]: ...
@overload
def __new__(cls, value: _TD64ItemT_co | timedelta64[_TD64ItemT_co], /) -> Self: ...
@overload
def __new__(cls, /) -> timedelta64[L[0]]: ...
@overload
def __new__(cls, value: _NaTValue | None, format: _TimeUnitSpec, /) -> timedelta64[None]: ...
@overload
def __new__(cls, value: L[0], format: _TimeUnitSpec[_IntTD64Unit] = ..., /) -> timedelta64[L[0]]: ...
@overload
def __new__(cls, value: _IntLike_co, format: _TimeUnitSpec[_IntTD64Unit] = ..., /) -> timedelta64[int]: ...
@overload
def __new__(cls, value: dt.timedelta, format: _TimeUnitSpec[_IntTimeUnit], /) -> timedelta64[int]: ...
@overload
def __new__(
cls,
value: dt.timedelta | _IntLike_co,
format: _TimeUnitSpec[_NativeTD64Unit] = ...,
/,
) -> timedelta64[dt.timedelta]: ...
@overload
def __new__(cls, value: _ConvertibleToTD64, format: _TimeUnitSpec = ..., /) -> Self: ...
# inherited at runtime from `signedinteger`
def __class_getitem__(cls, type_arg: type | object, /) -> GenericAlias: ...
# NOTE: Only a limited number of units support conversion
# to builtin scalar types: `Y`, `M`, `ns`, `ps`, `fs`, `as`
def __int__(self: timedelta64[int], /) -> int: ...
def __float__(self: timedelta64[int], /) -> float: ...
def __neg__(self, /) -> Self: ...
def __pos__(self, /) -> Self: ...
def __abs__(self, /) -> Self: ...
@overload
def __add__(self: timedelta64[None], x: _TD64Like_co, /) -> timedelta64[None]: ...
@overload
def __add__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> timedelta64[int]: ...
@overload
def __add__(self: timedelta64[int], x: timedelta64, /) -> timedelta64[int | None]: ...
@overload
def __add__(self: timedelta64[dt.timedelta], x: _AnyDateOrTime, /) -> _AnyDateOrTime: ...
@overload
def __add__(self: timedelta64[_AnyTD64Item], x: timedelta64[_AnyTD64Item] | _IntLike_co, /) -> timedelta64[_AnyTD64Item]: ...
@overload
def __add__(self, x: timedelta64[None], /) -> timedelta64[None]: ... # type: ignore[overload-cannot-match]
__radd__ = __add__
@overload
def __mul__(self: timedelta64[_AnyTD64Item], x: int | np.integer | np.bool, /) -> timedelta64[_AnyTD64Item]: ...
@overload
def __mul__(self: timedelta64[_AnyTD64Item], x: float | np.floating, /) -> timedelta64[_AnyTD64Item | None]: ...
@overload
def __mul__(self, x: float | np.floating | np.integer | np.bool, /) -> timedelta64: ...
__rmul__ = __mul__
@overload
def __mod__(self, x: timedelta64[L[0] | None], /) -> timedelta64[None]: ...
@overload
def __mod__(self: timedelta64[None], x: timedelta64, /) -> timedelta64[None]: ...
@overload
def __mod__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> timedelta64[int | None]: ...
@overload
def __mod__(self: timedelta64[dt.timedelta], x: timedelta64[_AnyTD64Item], /) -> timedelta64[_AnyTD64Item | None]: ...
@overload
def __mod__(self: timedelta64[dt.timedelta], x: dt.timedelta, /) -> dt.timedelta: ...
@overload
def __mod__(self, x: timedelta64[int], /) -> timedelta64[int | None]: ...
@overload
def __mod__(self, x: timedelta64, /) -> timedelta64: ...
# NOTE: The L[0] makes __mod__ non-commutative, which the first two overloads
# reflect. However, mypy does not seem to like this, so we ignore the errors.
@overload
def __rmod__(self, x: timedelta64[None], /) -> timedelta64[None]: ... # type: ignore[misc]
@overload
def __rmod__(self: timedelta64[L[0] | None], x: timedelta64, /) -> timedelta64[None]: ...
@overload
def __rmod__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> timedelta64[int | None]: ... # type: ignore[misc]
@overload
def __rmod__(self: timedelta64[dt.timedelta], x: timedelta64[_AnyTD64Item], /) -> timedelta64[_AnyTD64Item | None]: ... # type: ignore[misc]
@overload
def __rmod__(self: timedelta64[dt.timedelta], x: dt.timedelta, /) -> dt.timedelta: ...
@overload
def __rmod__(self, x: timedelta64[int], /) -> timedelta64[int | None]: ... # type: ignore[misc]
@overload
def __rmod__(self, x: timedelta64, /) -> timedelta64: ... # type: ignore[misc]
# keep in sync with __mod__
@overload
def __divmod__(self, x: timedelta64[L[0] | None], /) -> tuple[int64, timedelta64[None]]: ...
@overload
def __divmod__(self: timedelta64[None], x: timedelta64, /) -> tuple[int64, timedelta64[None]]: ...
@overload
def __divmod__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> tuple[int64, timedelta64[int | None]]: ...
@overload
def __divmod__(
self: timedelta64[dt.timedelta], x: timedelta64[_AnyTD64Item], /
) -> tuple[int64, timedelta64[_AnyTD64Item | None]]: ...
@overload
def __divmod__(self: timedelta64[dt.timedelta], x: dt.timedelta, /) -> tuple[int, dt.timedelta]: ...
@overload
def __divmod__(self, x: timedelta64[int], /) -> tuple[int64, timedelta64[int | None]]: ...
@overload
def __divmod__(self, x: timedelta64, /) -> tuple[int64, timedelta64]: ...
# keep in sync with __rmod__
@overload
def __rdivmod__(self, x: timedelta64[None], /) -> tuple[int64, timedelta64[None]]: ... # type: ignore[misc]
@overload
def __rdivmod__(self: timedelta64[L[0] | None], x: timedelta64, /) -> tuple[int64, timedelta64[None]]: ... # type: ignore[misc]
@overload
def __rdivmod__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> tuple[int64, timedelta64[int | None]]: ... # type: ignore[misc]
@overload
def __rdivmod__( # type: ignore[misc]
self: timedelta64[dt.timedelta], x: timedelta64[_AnyTD64Item], /
) -> tuple[int64, timedelta64[_AnyTD64Item | None]]: ...
@overload
def __rdivmod__(self: timedelta64[dt.timedelta], x: dt.timedelta, /) -> tuple[int, dt.timedelta]: ...
@overload
def __rdivmod__(self, x: timedelta64[int], /) -> tuple[int64, timedelta64[int | None]]: ... # type: ignore[misc]
@overload
def __rdivmod__(self, x: timedelta64, /) -> tuple[int64, timedelta64]: ... # type: ignore[misc]
@overload
def __sub__(self: timedelta64[None], b: _TD64Like_co, /) -> timedelta64[None]: ...
@overload
def __sub__(self: timedelta64[int], b: timedelta64[int | dt.timedelta], /) -> timedelta64[int]: ...
@overload
def __sub__(self: timedelta64[int], b: timedelta64, /) -> timedelta64[int | None]: ...
@overload
def __sub__(self: timedelta64[dt.timedelta], b: dt.timedelta, /) -> dt.timedelta: ...
@overload
def __sub__(self: timedelta64[_AnyTD64Item], b: timedelta64[_AnyTD64Item] | _IntLike_co, /) -> timedelta64[_AnyTD64Item]: ...
@overload
def __sub__(self, b: timedelta64[None], /) -> timedelta64[None]: ... # type: ignore[overload-cannot-match]
# NOTE: subtraction is not commutative, so __rsub__ differs from __sub__.
# This confuses mypy, so we ignore the [misc] errors it reports.
@overload
def __rsub__(self: timedelta64[None], a: _TD64Like_co, /) -> timedelta64[None]: ...
@overload
def __rsub__(self: timedelta64[dt.timedelta], a: _AnyDateOrTime, /) -> _AnyDateOrTime: ...
@overload
def __rsub__(self: timedelta64[dt.timedelta], a: timedelta64[_AnyTD64Item], /) -> timedelta64[_AnyTD64Item]: ... # type: ignore[misc]
@overload
def __rsub__(self: timedelta64[_AnyTD64Item], a: timedelta64[_AnyTD64Item] | _IntLike_co, /) -> timedelta64[_AnyTD64Item]: ... # type: ignore[misc]
@overload
def __rsub__(self, a: timedelta64[None], /) -> timedelta64[None]: ... # type: ignore[overload-cannot-match]
@overload
def __rsub__(self, a: datetime64[None], /) -> datetime64[None]: ... # type: ignore[misc]
@overload
def __truediv__(self: timedelta64[dt.timedelta], b: dt.timedelta, /) -> float: ...
@overload
def __truediv__(self, b: timedelta64, /) -> float64: ...
@overload
def __truediv__(self: timedelta64[_AnyTD64Item], b: int | integer, /) -> timedelta64[_AnyTD64Item]: ...
@overload
def __truediv__(self: timedelta64[_AnyTD64Item], b: float | floating, /) -> timedelta64[_AnyTD64Item | None]: ...
@overload
def __truediv__(self, b: float | floating | integer, /) -> timedelta64: ...
@overload
def __rtruediv__(self: timedelta64[dt.timedelta], a: dt.timedelta, /) -> float: ...
@overload
def __rtruediv__(self, a: timedelta64, /) -> float64: ...
@overload
def __floordiv__(self: timedelta64[dt.timedelta], b: dt.timedelta, /) -> int: ...
@overload
def __floordiv__(self, b: timedelta64, /) -> int64: ...
@overload
def __floordiv__(self: timedelta64[_AnyTD64Item], b: int | integer, /) -> timedelta64[_AnyTD64Item]: ...
@overload
def __floordiv__(self: timedelta64[_AnyTD64Item], b: float | floating, /) -> timedelta64[_AnyTD64Item | None]: ...
@overload
def __rfloordiv__(self: timedelta64[dt.timedelta], a: dt.timedelta, /) -> int: ...
@overload
def __rfloordiv__(self, a: timedelta64, /) -> int64: ...
# comparison ops
@overload
def __lt__(self, other: _TD64Like_co, /) -> bool_: ...
@overload
def __lt__(self, other: _ArrayLikeTD64_co | _NestedSequence[_SupportsGT], /) -> NDArray[bool_]: ...
@overload
def __lt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __le__(self, other: _TD64Like_co, /) -> bool_: ...
@overload
def __le__(self, other: _ArrayLikeTD64_co | _NestedSequence[_SupportsGE], /) -> NDArray[bool_]: ...
@overload
def __le__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __gt__(self, other: _TD64Like_co, /) -> bool_: ...
@overload
def __gt__(self, other: _ArrayLikeTD64_co | _NestedSequence[_SupportsLT], /) -> NDArray[bool_]: ...
@overload
def __gt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __ge__(self, other: _TD64Like_co, /) -> bool_: ...
@overload
def __ge__(self, other: _ArrayLikeTD64_co | _NestedSequence[_SupportsLE], /) -> NDArray[bool_]: ...
@overload
def __ge__(self, other: _SupportsGT, /) -> bool_: ...
class datetime64(_RealMixin, generic[_DT64ItemT_co], Generic[_DT64ItemT_co]):
@property
def itemsize(self) -> L[8]: ...
@property
def nbytes(self) -> L[8]: ...
@overload
def __new__(cls, value: datetime64[_DT64ItemT_co], /) -> Self: ...
@overload
def __new__(cls, value: _AnyDT64Arg, /) -> datetime64[_AnyDT64Arg]: ...
@overload
def __new__(cls, value: _NaTValue | None = ..., format: _TimeUnitSpec = ..., /) -> datetime64[None]: ...
@overload
def __new__(cls, value: _DT64Now, format: _TimeUnitSpec[_NativeTimeUnit] = ..., /) -> datetime64[dt.datetime]: ...
@overload
def __new__(cls, value: _DT64Date, format: _TimeUnitSpec[_DateUnit] = ..., /) -> datetime64[dt.date]: ...
@overload
def __new__(cls, value: int | bytes | str | dt.date, format: _TimeUnitSpec[_IntTimeUnit], /) -> datetime64[int]: ...
@overload
def __new__(
cls, value: int | bytes | str | dt.date, format: _TimeUnitSpec[_NativeTimeUnit], /
) -> datetime64[dt.datetime]: ...
@overload
def __new__(cls, value: int | bytes | str | dt.date, format: _TimeUnitSpec[_DateUnit], /) -> datetime64[dt.date]: ...
@overload
def __new__(cls, value: bytes | str | dt.date | None, format: _TimeUnitSpec = ..., /) -> Self: ...
def __class_getitem__(cls, type_arg: type | object, /) -> GenericAlias: ...
@overload
def __add__(self: datetime64[_AnyDT64Item], x: int | integer | np.bool, /) -> datetime64[_AnyDT64Item]: ...
@overload
def __add__(self: datetime64[None], x: _TD64Like_co, /) -> datetime64[None]: ...
@overload
def __add__(self: datetime64[int], x: timedelta64[int | dt.timedelta], /) -> datetime64[int]: ...
@overload
def __add__(self: datetime64[dt.datetime], x: timedelta64[dt.timedelta], /) -> datetime64[dt.datetime]: ...
@overload
def __add__(self: datetime64[dt.date], x: timedelta64[dt.timedelta], /) -> datetime64[dt.date]: ...
@overload
def __add__(self: datetime64[dt.date], x: timedelta64[int], /) -> datetime64[int]: ...
@overload
def __add__(self, x: datetime64[None], /) -> datetime64[None]: ...
@overload
def __add__(self, x: _TD64Like_co, /) -> datetime64: ...
__radd__ = __add__
@overload
def __sub__(self: datetime64[_AnyDT64Item], x: int | integer | np.bool, /) -> datetime64[_AnyDT64Item]: ...
@overload
def __sub__(self: datetime64[_AnyDate], x: _AnyDate, /) -> dt.timedelta: ...
@overload
def __sub__(self: datetime64[None], x: timedelta64, /) -> datetime64[None]: ...
@overload
def __sub__(self: datetime64[None], x: datetime64, /) -> timedelta64[None]: ...
@overload
def __sub__(self: datetime64[int], x: timedelta64, /) -> datetime64[int]: ...
@overload
def __sub__(self: datetime64[int], x: datetime64, /) -> timedelta64[int]: ...
@overload
def __sub__(self: datetime64[dt.datetime], x: timedelta64[int], /) -> datetime64[int]: ...
@overload
def __sub__(self: datetime64[dt.datetime], x: timedelta64[dt.timedelta], /) -> datetime64[dt.datetime]: ...
@overload
def __sub__(self: datetime64[dt.datetime], x: datetime64[int], /) -> timedelta64[int]: ...
@overload
def __sub__(self: datetime64[dt.date], x: timedelta64[int], /) -> datetime64[dt.date | int]: ...
@overload
def __sub__(self: datetime64[dt.date], x: timedelta64[dt.timedelta], /) -> datetime64[dt.date]: ...
@overload
def __sub__(self: datetime64[dt.date], x: datetime64[dt.date], /) -> timedelta64[dt.timedelta]: ...
@overload
def __sub__(self, x: timedelta64[None], /) -> datetime64[None]: ...
@overload
def __sub__(self, x: datetime64[None], /) -> timedelta64[None]: ...
@overload
def __sub__(self, x: _TD64Like_co, /) -> datetime64: ...
@overload
def __sub__(self, x: datetime64, /) -> timedelta64: ...
# NOTE: mypy gets confused by the non-commutativity of subtraction here
@overload
def __rsub__(self: datetime64[_AnyDT64Item], x: int | integer | np.bool, /) -> datetime64[_AnyDT64Item]: ...
@overload
def __rsub__(self: datetime64[_AnyDate], x: _AnyDate, /) -> dt.timedelta: ...
@overload
def __rsub__(self: datetime64[None], x: datetime64, /) -> timedelta64[None]: ...
@overload
def __rsub__(self: datetime64[int], x: datetime64, /) -> timedelta64[int]: ...
@overload
def __rsub__(self: datetime64[dt.datetime], x: datetime64[int], /) -> timedelta64[int]: ... # type: ignore[misc]
@overload
def __rsub__(self: datetime64[dt.datetime], x: datetime64[dt.date], /) -> timedelta64[dt.timedelta]: ... # type: ignore[misc]
@overload
def __rsub__(self, x: datetime64[None], /) -> timedelta64[None]: ... # type: ignore[misc]
@overload
def __rsub__(self, x: datetime64, /) -> timedelta64: ... # type: ignore[misc]
@overload
def __lt__(self, other: datetime64, /) -> bool_: ...
@overload
def __lt__(self, other: _ArrayLikeDT64_co | _NestedSequence[_SupportsGT], /) -> NDArray[bool_]: ...
@overload
def __lt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __le__(self, other: datetime64, /) -> bool_: ...
@overload
def __le__(self, other: _ArrayLikeDT64_co | _NestedSequence[_SupportsGE], /) -> NDArray[bool_]: ...
@overload
def __le__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __gt__(self, other: datetime64, /) -> bool_: ...
@overload
def __gt__(self, other: _ArrayLikeDT64_co | _NestedSequence[_SupportsLT], /) -> NDArray[bool_]: ...
@overload
def __gt__(self, other: _SupportsGT, /) -> bool_: ...
@overload
def __ge__(self, other: datetime64, /) -> bool_: ...
@overload
def __ge__(self, other: _ArrayLikeDT64_co | _NestedSequence[_SupportsLE], /) -> NDArray[bool_]: ...
@overload
def __ge__(self, other: _SupportsGT, /) -> bool_: ...
@final # cannot be subclassed at runtime
class flexible(_RealMixin, generic[_FlexibleItemT_co], Generic[_FlexibleItemT_co]): ... # type: ignore[misc]
class void(flexible[bytes | tuple[Any, ...]]): # type: ignore[misc]
@overload
def __new__(cls, length_or_data: _IntLike_co | bytes, /, dtype: None = None) -> Self: ...
@overload
def __new__(cls, length_or_data: object, /, dtype: _DTypeLikeVoid) -> Self: ...
@overload
def __getitem__(self, key: str | SupportsIndex, /) -> Any: ...
@overload
def __getitem__(self, key: list[str], /) -> void: ...
def __setitem__(self, key: str | list[str] | SupportsIndex, value: ArrayLike, /) -> None: ...
def setfield(self, val: ArrayLike, dtype: DTypeLike, offset: int = ...) -> None: ...
class character(flexible[_CharacterItemT_co], Generic[_CharacterItemT_co]): # type: ignore[misc]
@abstractmethod
def __new__(cls, value: object = ..., /) -> Self: ...
# NOTE: Most `np.bytes_` / `np.str_` methods return their builtin `bytes` / `str` counterpart
class bytes_(character[bytes], bytes): # type: ignore[misc]
@overload
def __new__(cls, value: object = b"", /) -> Self: ...
@overload
def __new__(cls, value: str, /, encoding: str, errors: str = "strict") -> Self: ...
#
@override
def __hash__(self, /) -> int: ...
#
def __bytes__(self, /) -> bytes: ...
class str_(character[str], str): # type: ignore[misc]
@overload
def __new__(cls, value: object = "", /) -> Self: ...
@overload
def __new__(cls, value: bytes, /, encoding: str, errors: str = "strict") -> Self: ...
#
@override
def __hash__(self, /) -> int: ...
# See `numpy._typing._ufunc` for more concrete nin-/nout-specific stubs
@final
class ufunc:
__signature__: Final[inspect.Signature]
@property
def __name__(self) -> LiteralString: ...
@property
def __qualname__(self) -> LiteralString: ... # pyright: ignore[reportIncompatibleVariableOverride]
@property
def __doc__(self) -> str: ... # type: ignore[override]
@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[LiteralString]: ...
# 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) -> LiteralString | None: ...
def __call__(self, /, *args: Any, **kwargs: Any) -> Any: ...
# 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.
def accumulate(
self,
array: ArrayLike,
/,
axis: SupportsIndex = 0,
dtype: DTypeLike | None = None,
out: ndarray | EllipsisType | None = None,
) -> NDArray[Incomplete]: ...
def reduce(
self,
array: ArrayLike,
/,
axis: _ShapeLike | None = 0,
dtype: DTypeLike | None = None,
out: ndarray | EllipsisType | None = None,
**kwargs: Incomplete,
) -> Incomplete: ...
def reduceat(
self,
array: ArrayLike,
/,
indices: _ArrayLikeInt_co,
axis: SupportsIndex = 0,
dtype: DTypeLike | None = None,
out: ndarray | EllipsisType | None = None,
) -> NDArray[Incomplete]: ...
def outer(self, A: ArrayLike, B: ArrayLike, /, **kwargs: Incomplete) -> NDArray[Incomplete]: ...
# Similarly `at` won't be defined for ufuncs that return multiple
# outputs, so we can't type it very precisely.
def at(self, a: ndarray, indices: _ArrayLikeInt_co, b: ArrayLike | None = None, /) -> None: ...
#
def resolve_dtypes(
self,
/,
dtypes: tuple[dtype | type | None, ...],
*,
signature: tuple[dtype | None, ...] | None = None,
casting: _CastingKind | None = None,
reduction: builtins.bool = False,
) -> tuple[dtype, ...]: ...
# Parameters: `__name__`, `ntypes` and `identity`
absolute: _UFunc_Nin1_Nout1[L["absolute"], L[20], None]
add: _UFunc_Nin2_Nout1[L["add"], L[22], L[0]]
arccos: _UFunc_Nin1_Nout1[L["arccos"], L[8], None]
arccosh: _UFunc_Nin1_Nout1[L["arccosh"], L[8], None]
arcsin: _UFunc_Nin1_Nout1[L["arcsin"], L[8], None]
arcsinh: _UFunc_Nin1_Nout1[L["arcsinh"], L[8], None]
arctan2: _UFunc_Nin2_Nout1[L["arctan2"], L[5], None]
arctan: _UFunc_Nin1_Nout1[L["arctan"], L[8], None]
arctanh: _UFunc_Nin1_Nout1[L["arctanh"], L[8], None]
bitwise_and: _UFunc_Nin2_Nout1[L["bitwise_and"], L[12], L[-1]]
bitwise_count: _UFunc_Nin1_Nout1[L["bitwise_count"], L[11], None]
bitwise_or: _UFunc_Nin2_Nout1[L["bitwise_or"], L[12], L[0]]
bitwise_xor: _UFunc_Nin2_Nout1[L["bitwise_xor"], L[12], L[0]]
cbrt: _UFunc_Nin1_Nout1[L["cbrt"], L[5], None]
ceil: _UFunc_Nin1_Nout1[L["ceil"], L[7], None]
conjugate: _UFunc_Nin1_Nout1[L["conjugate"], L[18], None]
copysign: _UFunc_Nin2_Nout1[L["copysign"], L[4], None]
cos: _UFunc_Nin1_Nout1[L["cos"], L[9], None]
cosh: _UFunc_Nin1_Nout1[L["cosh"], L[8], None]
deg2rad: _UFunc_Nin1_Nout1[L["deg2rad"], L[5], None]
degrees: _UFunc_Nin1_Nout1[L["degrees"], L[5], None]
divide: _UFunc_Nin2_Nout1[L["divide"], L[11], None]
divmod: _UFunc_Nin2_Nout2[L["divmod"], L[15], None]
equal: _UFunc_Nin2_Nout1[L["equal"], L[23], None]
exp2: _UFunc_Nin1_Nout1[L["exp2"], L[8], None]
exp: _UFunc_Nin1_Nout1[L["exp"], L[10], None]
expm1: _UFunc_Nin1_Nout1[L["expm1"], L[8], None]
fabs: _UFunc_Nin1_Nout1[L["fabs"], L[5], None]
float_power: _UFunc_Nin2_Nout1[L["float_power"], L[4], None]
floor: _UFunc_Nin1_Nout1[L["floor"], L[7], None]
floor_divide: _UFunc_Nin2_Nout1[L["floor_divide"], L[21], None]
fmax: _UFunc_Nin2_Nout1[L["fmax"], L[21], None]
fmin: _UFunc_Nin2_Nout1[L["fmin"], L[21], None]
fmod: _UFunc_Nin2_Nout1[L["fmod"], L[15], None]
frexp: _UFunc_Nin1_Nout2[L["frexp"], L[4], None]
gcd: _UFunc_Nin2_Nout1[L["gcd"], L[11], L[0]]
greater: _UFunc_Nin2_Nout1[L["greater"], L[23], None]
greater_equal: _UFunc_Nin2_Nout1[L["greater_equal"], L[23], None]
heaviside: _UFunc_Nin2_Nout1[L["heaviside"], L[4], None]
hypot: _UFunc_Nin2_Nout1[L["hypot"], L[5], L[0]]
invert: _UFunc_Nin1_Nout1[L["invert"], L[12], None]
isfinite: _UFunc_Nin1_Nout1[L["isfinite"], L[20], None]
isinf: _UFunc_Nin1_Nout1[L["isinf"], L[20], None]
isnan: _UFunc_Nin1_Nout1[L["isnan"], L[20], None]
isnat: _UFunc_Nin1_Nout1[L["isnat"], L[2], None]
lcm: _UFunc_Nin2_Nout1[L["lcm"], L[11], None]
ldexp: _UFunc_Nin2_Nout1[L["ldexp"], L[8], None]
left_shift: _UFunc_Nin2_Nout1[L["left_shift"], L[11], None]
less: _UFunc_Nin2_Nout1[L["less"], L[23], None]
less_equal: _UFunc_Nin2_Nout1[L["less_equal"], L[23], None]
log10: _UFunc_Nin1_Nout1[L["log10"], L[8], None]
log1p: _UFunc_Nin1_Nout1[L["log1p"], L[8], None]
log2: _UFunc_Nin1_Nout1[L["log2"], L[8], None]
log: _UFunc_Nin1_Nout1[L["log"], L[10], None]
logaddexp2: _UFunc_Nin2_Nout1[L["logaddexp2"], L[4], float]
logaddexp: _UFunc_Nin2_Nout1[L["logaddexp"], L[4], float]
logical_and: _UFunc_Nin2_Nout1[L["logical_and"], L[20], L[True]]
logical_not: _UFunc_Nin1_Nout1[L["logical_not"], L[20], None]
logical_or: _UFunc_Nin2_Nout1[L["logical_or"], L[20], L[False]]
logical_xor: _UFunc_Nin2_Nout1[L["logical_xor"], L[19], L[False]]
matmul: _GUFunc_Nin2_Nout1[L["matmul"], L[19], None, L["(n?,k),(k,m?)->(n?,m?)"]]
matvec: _GUFunc_Nin2_Nout1[L["matvec"], L[19], None, L["(m,n),(n)->(m)"]]
maximum: _UFunc_Nin2_Nout1[L["maximum"], L[21], None]
minimum: _UFunc_Nin2_Nout1[L["minimum"], L[21], None]
modf: _UFunc_Nin1_Nout2[L["modf"], L[4], None]
multiply: _UFunc_Nin2_Nout1[L["multiply"], L[23], L[1]]
negative: _UFunc_Nin1_Nout1[L["negative"], L[19], None]
nextafter: _UFunc_Nin2_Nout1[L["nextafter"], L[4], None]
not_equal: _UFunc_Nin2_Nout1[L["not_equal"], L[23], None]
positive: _UFunc_Nin1_Nout1[L["positive"], L[19], None]
power: _UFunc_Nin2_Nout1[L["power"], L[18], None]
rad2deg: _UFunc_Nin1_Nout1[L["rad2deg"], L[5], None]
radians: _UFunc_Nin1_Nout1[L["radians"], L[5], None]
reciprocal: _UFunc_Nin1_Nout1[L["reciprocal"], L[18], None]
remainder: _UFunc_Nin2_Nout1[L["remainder"], L[16], None]
right_shift: _UFunc_Nin2_Nout1[L["right_shift"], L[11], None]
rint: _UFunc_Nin1_Nout1[L["rint"], L[10], None]
sign: _UFunc_Nin1_Nout1[L["sign"], L[19], None]
signbit: _UFunc_Nin1_Nout1[L["signbit"], L[4], None]
sin: _UFunc_Nin1_Nout1[L["sin"], L[9], None]
sinh: _UFunc_Nin1_Nout1[L["sinh"], L[8], None]
spacing: _UFunc_Nin1_Nout1[L["spacing"], L[4], None]
sqrt: _UFunc_Nin1_Nout1[L["sqrt"], L[10], None]
square: _UFunc_Nin1_Nout1[L["square"], L[18], None]
subtract: _UFunc_Nin2_Nout1[L["subtract"], L[21], None]
tan: _UFunc_Nin1_Nout1[L["tan"], L[8], None]
tanh: _UFunc_Nin1_Nout1[L["tanh"], L[8], None]
trunc: _UFunc_Nin1_Nout1[L["trunc"], L[7], None]
vecdot: _GUFunc_Nin2_Nout1[L["vecdot"], L[19], None, L["(n),(n)->()"]]
vecmat: _GUFunc_Nin2_Nout1[L["vecmat"], L[19], None, L["(n),(n,m)->(m)"]]
abs = absolute
acos = arccos
acosh = arccosh
asin = arcsin
asinh = arcsinh
atan = arctan
atanh = arctanh
atan2 = arctan2
concat = concatenate
bitwise_left_shift = left_shift
bitwise_not = invert
bitwise_invert = invert
bitwise_right_shift = right_shift
conj = conjugate
mod = remainder
permute_dims = transpose
pow = power
true_divide = divide
# TODO: The type of each `__next__` and `iters` return-type depends
# on the length and dtype of `args`; we can't describe this behavior yet
# as we lack variadics (PEP 646).
@final
class broadcast:
def __new__(cls, *args: ArrayLike) -> broadcast: ...
@property
def index(self) -> int: ...
@property
def iters(self) -> tuple[flatiter[Any], ...]: ...
@property
def nd(self) -> int: ...
@property
def ndim(self) -> int: ...
@property
def numiter(self) -> int: ...
@property
def shape(self) -> _AnyShape: ...
@property
def size(self) -> int: ...
def __next__(self) -> tuple[Any, ...]: ...
def __iter__(self) -> Self: ...
def reset(self) -> None: ...
@final
class busdaycalendar:
def __init__(
self,
/,
weekmask: str | Sequence[int | bool_ | integer] | _SupportsArray[dtype[bool_ | integer]] = "1111100",
holidays: Sequence[dt.date | datetime64] | _SupportsArray[dtype[datetime64]] | None = None,
) -> None: ...
@property
def weekmask(self) -> ndarray[tuple[int], dtype[bool_]]: ...
@property
def holidays(self) -> ndarray[tuple[int], dtype[datetime64[dt.date]]]: ...
@final
class nditer:
@overload
def __init__(
self,
/,
op: ArrayLike,
flags: Sequence[_NDIterFlagsKind] | None = None,
op_flags: Sequence[_NDIterFlagsOp] | None = None,
op_dtypes: DTypeLike | None = None,
order: _OrderKACF = "K",
casting: _CastingKind = "safe",
op_axes: Sequence[SupportsIndex] | None = None,
itershape: _ShapeLike | None = None,
buffersize: SupportsIndex = 0,
) -> None: ...
@overload
def __init__(
self,
/,
op: Sequence[ArrayLike | None],
flags: Sequence[_NDIterFlagsKind] | None = None,
op_flags: Sequence[Sequence[_NDIterFlagsOp]] | None = None,
op_dtypes: Sequence[DTypeLike | None] | None = None,
order: _OrderKACF = "K",
casting: _CastingKind = "safe",
op_axes: Sequence[Sequence[SupportsIndex]] | None = None,
itershape: _ShapeLike | None = None,
buffersize: SupportsIndex = 0,
) -> None: ...
def __enter__(self) -> nditer: ...
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_value: BaseException | None,
traceback: TracebackType | None,
) -> None: ...
def __iter__(self) -> nditer: ...
def __next__(self) -> tuple[NDArray[Any], ...]: ...
def __len__(self) -> int: ...
def __copy__(self) -> nditer: ...
@overload
def __getitem__(self, index: SupportsIndex) -> NDArray[Any]: ...
@overload
def __getitem__(self, index: slice) -> tuple[NDArray[Any], ...]: ...
def __setitem__(self, index: slice | SupportsIndex, value: ArrayLike) -> None: ...
def close(self) -> None: ...
def copy(self) -> nditer: ...
def debug_print(self) -> None: ...
def enable_external_loop(self) -> None: ...
def iternext(self) -> builtins.bool: ...
def remove_axis(self, i: SupportsIndex, /) -> None: ...
def remove_multi_index(self) -> None: ...
def reset(self) -> None: ...
@property
def dtypes(self) -> tuple[dtype, ...]: ...
@property
def finished(self) -> builtins.bool: ...
@property
def has_delayed_bufalloc(self) -> builtins.bool: ...
@property
def has_index(self) -> builtins.bool: ...
@property
def has_multi_index(self) -> builtins.bool: ...
@property
def index(self) -> int: ...
@property
def iterationneedsapi(self) -> builtins.bool: ...
@property
def iterindex(self) -> int: ...
@property
def iterrange(self) -> tuple[int, ...]: ...
@property
def itersize(self) -> int: ...
@property
def itviews(self) -> tuple[NDArray[Any], ...]: ...
@property
def multi_index(self) -> tuple[int, ...]: ...
@property
def ndim(self) -> int: ...
@property
def nop(self) -> int: ...
@property
def operands(self) -> tuple[NDArray[Any], ...]: ...
@property
def shape(self) -> tuple[int, ...]: ...
@property
def value(self) -> tuple[NDArray[Any], ...]: ...
class memmap(ndarray[_ShapeT_co, _DTypeT_co]):
__array_priority__: ClassVar[float]
filename: str | None
offset: int
mode: str
@overload
def __new__(
subtype,
filename: StrOrBytesPath | _SupportsFileMethodsRW,
dtype: type[uint8] = ...,
mode: _MemMapModeKind = "r+",
offset: int = 0,
shape: int | tuple[int, ...] | None = None,
order: _OrderKACF = "C",
) -> memmap[Any, dtype[uint8]]: ...
@overload
def __new__(
subtype,
filename: StrOrBytesPath | _SupportsFileMethodsRW,
dtype: _DTypeLike[_ScalarT],
mode: _MemMapModeKind = "r+",
offset: int = 0,
shape: int | tuple[int, ...] | None = None,
order: _OrderKACF = "C",
) -> memmap[Any, dtype[_ScalarT]]: ...
@overload
def __new__(
subtype,
filename: StrOrBytesPath | _SupportsFileMethodsRW,
dtype: DTypeLike,
mode: _MemMapModeKind = "r+",
offset: int = 0,
shape: int | tuple[int, ...] | None = None,
order: _OrderKACF = "C",
) -> memmap[Any, dtype]: ...
def __array_finalize__(self, obj: object) -> None: ...
def __array_wrap__(
self,
array: memmap[_ShapeT_co, _DTypeT_co], # type: ignore[override]
context: tuple[ufunc, tuple[Any, ...], int] | None = None,
return_scalar: builtins.bool = False,
) -> Any: ...
def flush(self) -> None: ...
class poly1d:
@property
def variable(self) -> LiteralString: ...
@property
def order(self) -> int: ...
@property
def o(self) -> int: ...
@property
def roots(self) -> NDArray[Any]: ...
@property
def r(self) -> NDArray[Any]: ...
@property
def coeffs(self) -> NDArray[Any]: ...
@coeffs.setter
def coeffs(self, value: NDArray[Any]) -> None: ...
@property
def c(self) -> NDArray[Any]: ...
@c.setter
def c(self, value: NDArray[Any]) -> None: ...
@property
def coef(self) -> NDArray[Any]: ...
@coef.setter
def coef(self, value: NDArray[Any]) -> None: ...
@property
def coefficients(self) -> NDArray[Any]: ...
@coefficients.setter
def coefficients(self, value: NDArray[Any]) -> None: ...
__hash__: ClassVar[None] # type: ignore[assignment] # pyright: ignore[reportIncompatibleMethodOverride]
@overload
def __array__(self, /, t: None = None, copy: builtins.bool | None = None) -> ndarray[tuple[int], dtype]: ...
@overload
def __array__(self, /, t: _DTypeT, copy: builtins.bool | None = None) -> ndarray[tuple[int], _DTypeT]: ...
@overload
def __call__(self, val: _ScalarLike_co) -> Any: ...
@overload
def __call__(self, val: poly1d) -> poly1d: ...
@overload
def __call__(self, val: ArrayLike) -> NDArray[Any]: ...
def __init__(
self,
c_or_r: ArrayLike,
r: builtins.bool = False,
variable: str | None = None,
) -> None: ...
def __len__(self) -> int: ...
def __neg__(self) -> poly1d: ...
def __pos__(self) -> poly1d: ...
def __mul__(self, other: ArrayLike, /) -> poly1d: ...
def __rmul__(self, other: ArrayLike, /) -> poly1d: ...
def __add__(self, other: ArrayLike, /) -> poly1d: ...
def __radd__(self, other: ArrayLike, /) -> poly1d: ...
def __pow__(self, val: _FloatLike_co, /) -> poly1d: ... # Integral floats are accepted
def __sub__(self, other: ArrayLike, /) -> poly1d: ...
def __rsub__(self, other: ArrayLike, /) -> poly1d: ...
def __truediv__(self, other: ArrayLike, /) -> poly1d: ...
def __rtruediv__(self, other: ArrayLike, /) -> poly1d: ...
def __getitem__(self, val: int, /) -> Any: ...
def __setitem__(self, key: int, val: Any, /) -> None: ...
def __iter__(self) -> Iterator[Any]: ...
def deriv(self, m: SupportsInt | SupportsIndex = 1) -> poly1d: ...
def integ(
self,
m: SupportsInt | SupportsIndex = 1,
k: _ArrayLikeComplex_co | _ArrayLikeObject_co | None = 0,
) -> poly1d: ...
def from_dlpack(
x: _SupportsDLPack[None],
/,
*,
device: L["cpu"] | None = None,
copy: builtins.bool | None = None,
) -> NDArray[number | np.bool]: ...
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