| | # 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 |
| |
|
| | _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 |
| | @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 |
| | # 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 |
| | def __getitem__(self: flatiter[NDArray[_ScalarT]], key: int | integer, /) -> _ScalarT: ... |
| | @overload # 1d |
| | def __getitem__( |
| | self: flatiter[ndarray[Any, _DTypeT]], |
| | key: list[int] | slice | EllipsisType | flatiter[NDArray[integer]], |
| | /, |
| | ) -> ndarray[tuple[int], _DTypeT]: ... |
| | @overload # 2d |
| | 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]: ... |
| |
|
