| # ruff: noqa: I001 |
| import builtins |
| import sys |
| import mmap |
| import ctypes as ct |
| import array as _array |
| import datetime as dt |
| 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 ( |
| # 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, |
| _NumberCodes, |
| _CharacterCodes, |
| _FlexibleCodes, |
| _GenericCodes, |
| # 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.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, |
| in1d, |
| intersect1d, |
| isin, |
| setdiff1d, |
| setxor1d, |
| union1d, |
| unique, |
| unique_all, |
| unique_counts, |
| unique_inverse, |
| unique_values, |
| ) |
|
|
| from numpy.lib._function_base_impl import ( |
| 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, |
| trapz, |
| i0, |
| meshgrid, |
| delete, |
| insert, |
| append, |
| interp, |
| quantile, |
| ) |
|
|
| 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 ( |
| 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, |
| ) |
|
|
| __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", "trapz", "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", "in1d", "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) |
| _IntegralArrayT = TypeVar("_IntegralArrayT", bound=NDArray[integer | np.bool | object_]) |
| _RealArrayT = TypeVar("_RealArrayT", bound=NDArray[floating | integer | timedelta64 | np.bool | object_]) |
| _NumericArrayT = TypeVar("_NumericArrayT", bound=NDArray[number | timedelta64 | object_]) |
|
|
| _ShapeT = TypeVar("_ShapeT", bound=_Shape) |
| _ShapeT_co = TypeVar("_ShapeT_co", bound=_Shape, default=_AnyShape, covariant=True) |
| _1DShapeT = TypeVar("_1DShapeT", bound=_1D) |
| _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) |
| _FloatingT_co = TypeVar("_FloatingT_co", bound=floating, default=floating, covariant=True) |
| _IntegerT = TypeVar("_IntegerT", bound=integer) |
| _IntegerT_co = TypeVar("_IntegerT_co", bound=integer, default=integer, covariant=True) |
| _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 |
| _NumberCType: TypeAlias = _IntegerCType |
| _GenericCType: TypeAlias = _NumberCType | type[ct.c_bool | ct.c_char | ct.py_object[Any]] |
|
|
| # 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", "unsafe"] |
|
|
| _OrderKACF: TypeAlias = L["K", "A", "C", "F"] | None |
| _OrderACF: TypeAlias = L["A", "C", "F"] | None |
| _OrderCF: TypeAlias = L["C", "F"] | None |
|
|
| _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 _SupportsItem(Protocol[_T_co]): |
| def item(self, /) -> _T_co: ... |
|
|
| @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] | None, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| 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 = ..., |
| copy: builtins.bool = ..., |
| 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], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[np.bool]: ... |
| # NOTE: `_: type[int]` also accepts `type[int | bool]` |
| @overload |
| def __new__( |
| cls, |
| dtype: type[int | int_ | np.bool], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[int_ | np.bool]: ... |
| # NOTE: `_: type[float]` also accepts `type[float | int | bool]` |
| # NOTE: `float64` inherits from `float` at runtime |
| # reflected in these stubs. So an explicit `float64` is required here. |
| @overload |
| def __new__( |
| cls, |
| dtype: type[float | float64 | int_ | np.bool] | None, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[float64 | int_ | np.bool]: ... |
| # NOTE: `_: type[complex]` also accepts `type[complex | float | int | bool]` |
| @overload |
| def __new__( |
| cls, |
| dtype: type[complex | complex128 | float64 | int_ | np.bool], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[complex128 | float64 | int_ | np.bool]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: type[bytes], # also includes `type[bytes_]` |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[bytes_]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: type[str], # also includes `type[str_]` |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| 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[memoryview | void], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| 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[_BuiltinObjectLike | object_], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[object_]: ... |
|
|
| # Unions of builtins. |
| @overload |
| def __new__( |
| cls, |
| dtype: type[bytes | str], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[character]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: type[bytes | str | memoryview], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[flexible]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: type[complex | bytes | str | memoryview | _BuiltinObjectLike], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[str, Any] = ..., |
| ) -> dtype[np.bool | int_ | float64 | complex128 | flexible | object_]: ... |
|
|
| # `unsignedinteger` string-based representations and ctypes |
| @overload |
| def __new__(cls, dtype: _UInt8Codes | type[ct.c_uint8], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint8]: ... |
| @overload |
| def __new__(cls, dtype: _UInt16Codes | type[ct.c_uint16], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint16]: ... |
| @overload |
| def __new__(cls, dtype: _UInt32Codes | type[ct.c_uint32], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint32]: ... |
| @overload |
| def __new__(cls, dtype: _UInt64Codes | type[ct.c_uint64], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint64]: ... |
| @overload |
| def __new__(cls, dtype: _UByteCodes | type[ct.c_ubyte], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ubyte]: ... |
| @overload |
| def __new__(cls, dtype: _UShortCodes | type[ct.c_ushort], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ushort]: ... |
| @overload |
| def __new__(cls, dtype: _UIntCCodes | type[ct.c_uint], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uintc]: ... |
| # NOTE: We're assuming here that `uint_ptr_t == size_t`, |
| # an assumption that does not hold in rare cases (same for `ssize_t`) |
| @overload |
| def __new__(cls, dtype: _UIntPCodes | type[ct.c_void_p] | type[ct.c_size_t], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uintp]: ... |
| @overload |
| def __new__(cls, dtype: _ULongCodes | type[ct.c_ulong], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ulong]: ... |
| @overload |
| def __new__(cls, dtype: _ULongLongCodes | type[ct.c_ulonglong], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ulonglong]: ... |
|
|
| # `signedinteger` string-based representations and ctypes |
| @overload |
| def __new__(cls, dtype: _Int8Codes | type[ct.c_int8], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int8]: ... |
| @overload |
| def __new__(cls, dtype: _Int16Codes | type[ct.c_int16], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int16]: ... |
| @overload |
| def __new__(cls, dtype: _Int32Codes | type[ct.c_int32], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int32]: ... |
| @overload |
| def __new__(cls, dtype: _Int64Codes | type[ct.c_int64], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int64]: ... |
| @overload |
| def __new__(cls, dtype: _ByteCodes | type[ct.c_byte], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[byte]: ... |
| @overload |
| def __new__(cls, dtype: _ShortCodes | type[ct.c_short], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[short]: ... |
| @overload |
| def __new__(cls, dtype: _IntCCodes | type[ct.c_int], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[intc]: ... |
| @overload |
| def __new__(cls, dtype: _IntPCodes | type[ct.c_ssize_t], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[intp]: ... |
| @overload |
| def __new__(cls, dtype: _LongCodes | type[ct.c_long], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[long]: ... |
| @overload |
| def __new__(cls, dtype: _LongLongCodes | type[ct.c_longlong], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[longlong]: ... |
|
|
| # `floating` string-based representations and ctypes |
| @overload |
| def __new__(cls, dtype: _Float16Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float16]: ... |
| @overload |
| def __new__(cls, dtype: _Float32Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float32]: ... |
| @overload |
| def __new__(cls, dtype: _Float64Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float64]: ... |
| @overload |
| def __new__(cls, dtype: _HalfCodes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[half]: ... |
| @overload |
| def __new__(cls, dtype: _SingleCodes | type[ct.c_float], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[single]: ... |
| @overload |
| def __new__(cls, dtype: _DoubleCodes | type[ct.c_double], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[double]: ... |
| @overload |
| def __new__(cls, dtype: _LongDoubleCodes | type[ct.c_longdouble], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[longdouble]: ... |
|
|
| # `complexfloating` string-based representations |
| @overload |
| def __new__(cls, dtype: _Complex64Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[complex64]: ... |
| @overload |
| def __new__(cls, dtype: _Complex128Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[complex128]: ... |
| @overload |
| def __new__(cls, dtype: _CSingleCodes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[csingle]: ... |
| @overload |
| def __new__(cls, dtype: _CDoubleCodes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[cdouble]: ... |
| @overload |
| def __new__(cls, dtype: _CLongDoubleCodes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[clongdouble]: ... |
|
|
| # Miscellaneous string-based representations and ctypes |
| @overload |
| def __new__(cls, dtype: _BoolCodes | type[ct.c_bool], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[np.bool]: ... |
| @overload |
| def __new__(cls, dtype: _TD64Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[timedelta64]: ... |
| @overload |
| def __new__(cls, dtype: _DT64Codes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[datetime64]: ... |
| @overload |
| def __new__(cls, dtype: _StrCodes, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[str_]: ... |
| @overload |
| def __new__(cls, dtype: _BytesCodes | type[ct.c_char], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[bytes_]: ... |
| @overload |
| def __new__(cls, dtype: _VoidCodes | _VoidDTypeLike, align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[void]: ... |
| @overload |
| def __new__(cls, dtype: _ObjectCodes | type[ct.py_object[Any]], align: builtins.bool = ..., copy: builtins.bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[object_]: ... |
|
|
| # `StringDType` requires special treatment because it has no scalar type |
| @overload |
| def __new__( |
| cls, |
| dtype: dtypes.StringDType | _StringCodes, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| 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 = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[unsignedinteger]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _SignedIntegerCodes | _SignedIntegerCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[signedinteger]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _IntegerCodes | _IntegerCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[integer]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _FloatingCodes | _FloatingCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[floating]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _ComplexFloatingCodes, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[complexfloating]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _InexactCodes | _FloatingCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[inexact]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _NumberCodes | _NumberCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[number]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _CharacterCodes | type[ct.c_char], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[character]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _FlexibleCodes | type[ct.c_char], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[flexible]: ... |
| @overload |
| def __new__( |
| cls, |
| dtype: _GenericCodes | _GenericCType, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype[generic]: ... |
|
|
| # Handle strings that can't be expressed as literals |
| @overload |
| def __new__( |
| cls, |
| dtype: builtins.str, |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| metadata: dict[builtins.str, Any] = ..., |
| ) -> dtype: ... |
|
|
| # Catch-all overload for object-likes |
| # NOTE: `object_ | Any` is *not* equivalent to `Any` -- it describes some |
| # (static) type `T` s.t. `object_ <: T <: builtins.object` (`<:` denotes |
| # the subtyping relation, the (gradual) typing analogue of `issubclass()`). |
| # https://typing.readthedocs.io/en/latest/spec/concepts.html#union-types |
| @overload |
| def __new__( |
| cls, |
| dtype: type[object], |
| align: builtins.bool = ..., |
| copy: builtins.bool = ..., |
| 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, /) -> builtins.bool: ... |
| def __ge__(self, other: DTypeLike, /) -> builtins.bool: ... |
| def __lt__(self, other: DTypeLike, /) -> builtins.bool: ... |
| def __le__(self, other: DTypeLike, /) -> 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] |
| @property |
| def base(self) -> _ArrayT_co: ... |
| @property |
| def coords(self) -> _Shape: ... |
| @property |
| def index(self) -> int: ... |
| def copy(self) -> _ArrayT_co: ... |
| def __iter__(self) -> Self: ... |
| def __next__(self: flatiter[NDArray[_ScalarT]]) -> _ScalarT: ... |
| def __len__(self) -> int: ... |
| @overload |
| def __getitem__( |
| self: flatiter[NDArray[_ScalarT]], |
| key: int | integer | tuple[int | integer], |
| ) -> _ScalarT: ... |
| @overload |
| def __getitem__( |
| self, |
| key: _ArrayLikeInt | slice | EllipsisType | tuple[_ArrayLikeInt | slice | EllipsisType], |
| ) -> _ArrayT_co: ... |
| # TODO: `__setitem__` operates via `unsafe` casting rules, and can |
| # thus accept any type accepted by the relevant underlying `np.generic` |
| # constructor. |
| # This means that `value` must in reality be a supertype of `npt.ArrayLike`. |
| def __setitem__( |
| self, |
| key: _ArrayLikeInt | slice | EllipsisType | tuple[_ArrayLikeInt | slice | EllipsisType], |
| value: Any, |
| ) -> None: ... |
| @overload |
| def __array__(self: flatiter[ndarray[_1DShapeT, _DTypeT]], dtype: None = ..., /) -> ndarray[_1DShapeT, _DTypeT]: ... |
| @overload |
| def __array__(self: flatiter[ndarray[_1DShapeT, Any]], dtype: _DTypeT, /) -> ndarray[_1DShapeT, _DTypeT]: ... |
| @overload |
| def __array__(self: flatiter[ndarray[Any, _DTypeT]], dtype: None = ..., /) -> ndarray[_AnyShape, _DTypeT]: ... |
| @overload |
| def __array__(self, dtype: _DTypeT, /) -> ndarray[_AnyShape, _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 = ...) -> None: ... |
| # generics and 0d arrays return builtin scalars |
| def tolist(self) -> Any: ... |
| def to_device(self, device: L["cpu"], /, *, stream: int | Any | None = ...) -> Self: ... |
|
|
| @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[Any]: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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 = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> Any: ... |
| @overload |
| def max( |
| self, |
| /, |
| axis: _ShapeLike | None, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
| @overload |
| def max( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| *, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def min( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| out: None = None, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> Any: ... |
| @overload |
| def min( |
| self, |
| /, |
| axis: _ShapeLike | None, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
| @overload |
| def min( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| *, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = ..., |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def sum( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| out: None = None, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 0, |
| where: _ArrayLikeBool_co = True, |
| ) -> Any: ... |
| @overload |
| def sum( |
| self, |
| /, |
| axis: _ShapeLike | None, |
| dtype: DTypeLike | None, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 0, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
| @overload |
| def sum( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| *, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 0, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def prod( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| out: None = None, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 1, |
| where: _ArrayLikeBool_co = True, |
| ) -> Any: ... |
| @overload |
| def prod( |
| self, |
| /, |
| axis: _ShapeLike | None, |
| dtype: DTypeLike | None, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 1, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
| @overload |
| def prod( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| *, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| initial: _NumberLike_co = 1, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def mean( |
| self, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| out: None = None, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| ) -> Any: ... |
| @overload |
| def mean( |
| self, |
| /, |
| axis: _ShapeLike | None, |
| dtype: DTypeLike | None, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
| @overload |
| def mean( |
| self, |
| /, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| *, |
| out: _ArrayT, |
| keepdims: builtins.bool = False, |
| where: _ArrayLikeBool_co = True, |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def std( |
| self, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| out: None = None, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> Any: ... |
| @overload |
| def std( |
| self, |
| axis: _ShapeLike | None, |
| dtype: DTypeLike | None, |
| out: _ArrayT, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> _ArrayT: ... |
| @overload |
| def std( |
| self, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| *, |
| out: _ArrayT, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def var( |
| self, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| out: None = None, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> Any: ... |
| @overload |
| def var( |
| self, |
| axis: _ShapeLike | None, |
| dtype: DTypeLike | None, |
| out: _ArrayT, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| *, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> _ArrayT: ... |
| @overload |
| def var( |
| self, |
| axis: _ShapeLike | None = None, |
| dtype: DTypeLike | None = None, |
| *, |
| out: _ArrayT, |
| ddof: float = 0, |
| keepdims: builtins.bool = False, |
| where: _ArrayLikeBool_co = True, |
| mean: _ArrayLikeNumber_co = ..., |
| correction: float = ..., |
| ) -> _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 = ..., |
| 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]: ... |
|
|
| @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 |
| def __getitem__(self: NDArray[void], key: str, /) -> ndarray[_ShapeT_co, np.dtype]: ... |
| @overload |
| def __getitem__(self: NDArray[void], key: list[str], /) -> ndarray[_ShapeT_co, _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 |
| def shape(self, value: _ShapeLike) -> None: ... |
| @property |
| def strides(self) -> _Shape: ... |
| @strides.setter |
| def strides(self, value: _ShapeLike) -> None: ... |
| def byteswap(self, inplace: builtins.bool = ...) -> Self: ... |
| def fill(self, value: Any, /) -> None: ... |
| @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: ... |
|
|
| @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 = ...) -> None: ... |
| @overload |
| def resize(self, /, *new_shape: SupportsIndex, refcheck: builtins.bool = ...) -> None: ... |
|
|
| def setflags(self, write: builtins.bool = ..., align: builtins.bool = ..., uic: builtins.bool = ...) -> None: ... |
|
|
| def squeeze( |
| self, |
| axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ..., |
| ) -> ndarray[_AnyShape, _DTypeT_co]: ... |
|
|
| def swapaxes( |
| self, |
| axis1: SupportsIndex, |
| axis2: SupportsIndex, |
| ) -> ndarray[_AnyShape, _DTypeT_co]: ... |
|
|
| @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]: ... |
|
|
| # |
| def diagonal( |
| self, |
| offset: SupportsIndex = ..., |
| axis1: SupportsIndex = ..., |
| axis2: SupportsIndex = ..., |
| ) -> 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 = ...) -> NDArray[Any]: ... |
| @overload |
| def dot(self, b: ArrayLike, out: None = ...) -> Any: ... # type: ignore[misc] |
| @overload |
| def dot(self, b: ArrayLike, out: _ArrayT) -> _ArrayT: ... |
|
|
| # `nonzero()` is deprecated for 0d arrays/generics |
| def nonzero(self) -> tuple[NDArray[intp], ...]: ... |
|
|
| # `put` is technically available to `generic`, |
| # but is pointless as `generic`s are immutable |
| def put(self, /, indices: _ArrayLikeInt_co, values: ArrayLike, mode: _ModeKind = "raise") -> None: ... |
|
|
| @overload |
| def searchsorted( # type: ignore[misc] |
| self, # >= 1D array |
| v: _ScalarLike_co, # 0D array-like |
| side: _SortSide = ..., |
| sorter: _ArrayLikeInt_co | None = ..., |
| ) -> intp: ... |
| @overload |
| def searchsorted( |
| self, # >= 1D array |
| v: ArrayLike, |
| side: _SortSide = ..., |
| sorter: _ArrayLikeInt_co | None = ..., |
| ) -> NDArray[intp]: ... |
|
|
| def sort( |
| self, |
| axis: SupportsIndex = ..., |
| kind: _SortKind | None = ..., |
| order: str | Sequence[str] | None = ..., |
| *, |
| stable: builtins.bool | None = ..., |
| ) -> None: ... |
|
|
| @overload |
| def trace( |
| self, # >= 2D array |
| offset: SupportsIndex = ..., |
| axis1: SupportsIndex = ..., |
| axis2: SupportsIndex = ..., |
| dtype: DTypeLike = ..., |
| out: None = ..., |
| ) -> Any: ... |
| @overload |
| def trace( |
| self, # >= 2D array |
| offset: SupportsIndex = ..., |
| axis1: SupportsIndex = ..., |
| axis2: SupportsIndex = ..., |
| dtype: DTypeLike = ..., |
| out: _ArrayT = ..., |
| ) -> _ArrayT: ... |
|
|
| @overload |
| def take( # type: ignore[misc] |
| self: NDArray[_ScalarT], |
| indices: _IntLike_co, |
| axis: SupportsIndex | None = ..., |
| out: None = ..., |
| mode: _ModeKind = ..., |
| ) -> _ScalarT: ... |
| @overload |
| def take( # type: ignore[misc] |
| self, |
| indices: _ArrayLikeInt_co, |
| axis: SupportsIndex | None = ..., |
| out: None = ..., |
| mode: _ModeKind = ..., |
| ) -> ndarray[_AnyShape, _DTypeT_co]: ... |
| @overload |
| def take( |
| self, |
| indices: _ArrayLikeInt_co, |
| axis: SupportsIndex | None = ..., |
| out: _ArrayT = ..., |
| mode: _ModeKind = ..., |
| ) -> _ArrayT: ... |
|
|
| @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]: ... |
|
|
| def flatten(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], _DTypeT_co]: ... |
| def ravel(self, /, order: _OrderKACF = "C") -> ndarray[tuple[int], _DTypeT_co]: ... |
|
|
| # 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, |
| 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[_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: 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]], /) -> Iterator[Any]: ... |
| @overload # == 1-d & dtype[T \ object_] |
| def __iter__(self: ndarray[tuple[int], dtype[_NonObjectScalarT]], /) -> Iterator[_NonObjectScalarT]: ... |
| @overload # >= 2-d |
| def __iter__(self: ndarray[tuple[int, int, *tuple[int, ...]], dtype[_ScalarT]], /) -> Iterator[NDArray[_ScalarT]]: ... |
| @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]]: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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]: ... # type: ignore[overload-overlap] |
| @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: ... |
|
|
| @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]: ... # type: ignore[overload-overlap] |
| @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: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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]: ... # type: ignore[overload-overlap] |
| @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: ... |
|
|
| @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: ... |
|
|
| @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]: ... # type: ignore[misc] |
| @overload |
| def __lshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __rlshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __rshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __rrshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __and__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __rand__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __xor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __rxor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __or__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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]: ... # type: ignore[misc] |
| @overload |
| def __ror__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ... # type: ignore[misc] |
| @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 |
| def __iadd__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[timedelta64 | datetime64], other: _ArrayLikeTD64_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[bytes_], other: _ArrayLikeBytes_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__( |
| self: ndarray[Any, dtype[str_] | dtypes.StringDType], |
| other: _ArrayLikeStr_co | _ArrayLikeString_co, |
| /, |
| ) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iadd__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # |
| @overload |
| def __isub__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __isub__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __isub__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __isub__(self: NDArray[timedelta64 | datetime64], other: _ArrayLikeTD64_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __isub__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # |
| @overload |
| def __imul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imul__( |
| self: ndarray[Any, dtype[integer | character] | dtypes.StringDType], other: _ArrayLikeInt_co, / |
| ) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imul__(self: NDArray[floating | timedelta64], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imul__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imul__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| @overload |
| def __ipow__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ipow__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ipow__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ipow__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # |
| @overload |
| def __itruediv__(self: NDArray[floating | timedelta64], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __itruediv__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __itruediv__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__imod__` |
| @overload |
| def __ifloordiv__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ifloordiv__(self: NDArray[floating | timedelta64], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ifloordiv__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__ifloordiv__` |
| @overload |
| def __imod__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imod__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imod__( |
| self: NDArray[timedelta64], |
| other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]], |
| /, |
| ) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imod__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__irshift__` |
| @overload |
| def __ilshift__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ilshift__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__ilshift__` |
| @overload |
| def __irshift__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __irshift__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__ixor__` and `__ior__` |
| @overload |
| def __iand__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iand__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __iand__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__iand__` and `__ior__` |
| @overload |
| def __ixor__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ixor__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ixor__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # keep in sync with `__iand__` and `__ixor__` |
| @overload |
| def __ior__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ior__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __ior__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # |
| @overload |
| def __imatmul__(self: NDArray[np.bool], other: _ArrayLikeBool_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imatmul__(self: NDArray[integer], other: _ArrayLikeInt_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imatmul__(self: NDArray[floating], other: _ArrayLikeFloat_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imatmul__(self: NDArray[complexfloating], other: _ArrayLikeComplex_co, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
| @overload |
| def __imatmul__(self: NDArray[object_], other: Any, /) -> ndarray[_ShapeT_co, _DTypeT_co]: ... |
|
|
| # |
| 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: ... |
| def __hash__(self) -> int: ... |
| @overload |
| def __array__(self, dtype: None = None, /) -> ndarray[tuple[()], dtype[Self]]: ... |
| @overload |
| def __array__(self, dtype: _DTypeT, /) -> ndarray[tuple[()], _DTypeT]: ... |
| if sys.version_info >= (3, 12): |
| def __buffer__(self, flags: int, /) -> memoryview: ... |
|
|
| @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: ... |
| def tolist(self, /) -> _ItemT_co: ... |
|
|
| def byteswap(self, inplace: L[False] = ...) -> Self: ... |
|
|
| @overload |
| def astype( |
| self, |
| dtype: _DTypeLike[_ScalarT], |
| order: _OrderKACF = ..., |
| casting: _CastingKind = ..., |
| subok: builtins.bool = ..., |
| copy: builtins.bool | _CopyMode = ..., |
| ) -> _ScalarT: ... |
| @overload |
| def astype( |
| self, |
| dtype: DTypeLike, |
| order: _OrderKACF = ..., |
| casting: _CastingKind = ..., |
| subok: builtins.bool = ..., |
| copy: builtins.bool | _CopyMode = ..., |
| ) -> Any: ... |
|
|
| # 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[Any]] = ...) -> Self: ... |
| @overload |
| def view( |
| self, |
| dtype: _DTypeLike[_ScalarT], |
| type: type[NDArray[Any]] = ..., |
| ) -> _ScalarT: ... |
| @overload |
| def view( |
| self, |
| dtype: DTypeLike, |
| type: type[NDArray[Any]] = ..., |
| ) -> Any: ... |
|
|
| @overload |
| def getfield( |
| self, |
| dtype: _DTypeLike[_ScalarT], |
| offset: SupportsIndex = ... |
| ) -> _ScalarT: ... |
| @overload |
| def getfield( |
| self, |
| dtype: DTypeLike, |
| offset: SupportsIndex = ... |
| ) -> Any: ... |
|
|
| @overload |
| def take( # type: ignore[misc] |
| self, |
| indices: _IntLike_co, |
| axis: SupportsIndex | None = ..., |
| out: None = ..., |
| mode: _ModeKind = ..., |
| ) -> Self: ... |
| @overload |
| def take( # type: ignore[misc] |
| self, |
| indices: _ArrayLikeInt_co, |
| axis: SupportsIndex | None = ..., |
| out: None = ..., |
| mode: _ModeKind = ..., |
| ) -> NDArray[Self]: ... |
| @overload |
| def take( |
| self, |
| indices: _ArrayLikeInt_co, |
| axis: SupportsIndex | None = ..., |
| out: _ArrayT = ..., |
| mode: _ModeKind = ..., |
| ) -> _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, /) -> Incomplete: ... |
| def __rpow__(self, other: _NumberLike_co, /) -> 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 __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, nothing_to_see_here: None = None, /) -> None: ... # type: ignore[misc] |
| @overload |
| def __new__(cls, stringy: _AnyStr, /) -> _AnyStr: ... # type: ignore[misc] |
| @overload |
| def __new__(cls, array: ndarray[_ShapeT, Any], /) -> ndarray[_ShapeT, dtype[Self]]: ... # type: ignore[misc] |
| @overload |
| def __new__(cls, sequence: 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 __getformat__(self, typestr: L["double", "float"], /) -> str: ... |
| def __getnewargs__(self, /) -> tuple[float]: ... |
|
|
| # float64-specific operator overrides |
| @overload |
| 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 |
| def __radd__(self, other: _Float64_co, /) -> float64: ... |
| @overload |
| def __radd__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... |
| @overload |
| def __radd__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ... |
| @overload |
| def __radd__(self, other: complex, /) -> float64 | complex128: ... |
|
|
| @overload |
| 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 |
| def __rsub__(self, other: _Float64_co, /) -> float64: ... |
| @overload |
| def __rsub__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... |
| @overload |
| def __rsub__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ... |
| @overload |
| def __rsub__(self, other: complex, /) -> float64 | complex128: ... |
|
|
| @overload |
| 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 |
| def __rmul__(self, other: _Float64_co, /) -> float64: ... |
| @overload |
| def __rmul__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... |
| @overload |
| def __rmul__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ... |
| @overload |
| def __rmul__(self, other: complex, /) -> float64 | complex128: ... |
|
|
| @overload |
| 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 |
| def __rtruediv__(self, other: _Float64_co, /) -> float64: ... |
| @overload |
| def __rtruediv__(self, other: complexfloating[_64Bit, _64Bit], /) -> complex128: ... |
| @overload |
| def __rtruediv__(self, other: complexfloating[_NBit1, _NBit2], /) -> complexfloating[_NBit1 | _64Bit, _NBit2 | _64Bit]: ... |
| @overload |
| def __rtruediv__(self, other: complex, /) -> float64 | complex128: ... |
|
|
| @overload |
| 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: ... |
| @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 |
| 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 |
| def __rpow__(self, other: _Float64_co, mod: None = None, /) -> float64: ... |
| @overload |
| def __rpow__(self, other: complexfloating[_64Bit, _64Bit], mod: None = None, /) -> complex128: ... |
| @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: ... # type: ignore[override] |
| def __rmod__(self, other: _Float64_co, /) -> float64: ... # type: ignore[override] |
|
|
| def __divmod__(self, other: _Float64_co, /) -> _2Tuple[float64]: ... # type: ignore[override] |
| def __rdivmod__(self, other: _Float64_co, /) -> _2Tuple[float64]: ... # type: ignore[override] |
|
|
| half: TypeAlias = floating[_NBitHalf] |
| single: TypeAlias = floating[_NBitSingle] |
| double: TypeAlias = floating[_NBitDouble] |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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, _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 |
| 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: ... |
|
|
| @overload |
| 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: ... |
|
|
| @overload |
| 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: ... |
|
|
| @overload |
| 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: ... |
|
|
| @overload |
| 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: ... |
|
|
| csingle: TypeAlias = complexfloating[_NBitSingle, _NBitSingle] |
| cdouble: TypeAlias = complexfloating[_NBitDouble, _NBitDouble] |
| clongdouble: TypeAlias = complexfloating[_NBitLongDouble, _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]: ... |
| __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: ... |
|
|
| # the L[0] makes __mod__ non-commutative, which the first two overloads reflect |
| @overload |
| def __rmod__(self, x: timedelta64[None], /) -> timedelta64[None]: ... |
| @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]: ... |
| @overload |
| def __rmod__(self: timedelta64[dt.timedelta], x: timedelta64[_AnyTD64Item], /) -> timedelta64[_AnyTD64Item | None]: ... |
| @overload |
| def __rmod__(self: timedelta64[dt.timedelta], x: dt.timedelta, /) -> dt.timedelta: ... |
| @overload |
| def __rmod__(self, x: timedelta64[int], /) -> timedelta64[int | None]: ... |
| @overload |
| def __rmod__(self, x: timedelta64, /) -> timedelta64: ... |
|
|
| # 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]]: ... |
| @overload |
| def __rdivmod__(self: timedelta64[L[0] | None], x: timedelta64, /) -> tuple[int64, timedelta64[None]]: ... |
| @overload |
| def __rdivmod__(self: timedelta64[int], x: timedelta64[int | dt.timedelta], /) -> tuple[int64, timedelta64[int | None]]: ... |
| @overload |
| def __rdivmod__(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]]: ... |
| @overload |
| def __rdivmod__(self, x: timedelta64, /) -> tuple[int64, timedelta64]: ... |
|
|
| @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]: ... |
|
|
| @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]: ... |
| @overload |
| def __rsub__(self: timedelta64[_AnyTD64Item], a: timedelta64[_AnyTD64Item] | _IntLike_co, /) -> timedelta64[_AnyTD64Item]: ... |
| @overload |
| def __rsub__(self, a: timedelta64[None], /) -> timedelta64[None]: ... |
| @overload |
| def __rsub__(self, a: datetime64[None], /) -> datetime64[None]: ... |
|
|
| @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: ... |
|
|
| @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: ... |
|
|
| @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]: ... |
| @overload |
| def __rsub__(self: datetime64[dt.datetime], x: datetime64[dt.date], /) -> timedelta64[dt.timedelta]: ... |
| @overload |
| def __rsub__(self, x: datetime64[None], /) -> timedelta64[None]: ... |
| @overload |
| def __rsub__(self, x: datetime64, /) -> timedelta64: ... |
|
|
| @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_: ... |
|
|
| class flexible(_RealMixin, generic[_FlexibleItemT_co], Generic[_FlexibleItemT_co]): ... # type: ignore[misc] |
|
|
| class void(flexible[bytes | tuple[Any, ...]]): |
| @overload |
| def __new__(cls, value: _IntLike_co | bytes, /, dtype: None = None) -> Self: ... |
| @overload |
| def __new__(cls, value: Any, /, 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]): |
| @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): |
| @overload |
| def __new__(cls, o: object = ..., /) -> Self: ... |
| @overload |
| def __new__(cls, s: str, /, encoding: str, errors: str = ...) -> Self: ... |
|
|
| # |
| def __bytes__(self, /) -> bytes: ... |
|
|
| class str_(character[str], str): |
| @overload |
| def __new__(cls, value: object = ..., /) -> Self: ... |
| @overload |
| def __new__(cls, value: bytes, /, encoding: str = ..., errors: str = ...) -> Self: ... |
|
|
| # See `numpy._typing._ufunc` for more concrete nin-/nout-specific stubs |
| @final |
| class ufunc: |
| @property |
| def __name__(self) -> LiteralString: ... |
| @property |
| def __qualname__(self) -> LiteralString: ... |
| @property |
| def __doc__(self) -> str: ... |
| @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 reduce(self, /, *args: Any, **kwargs: Any) -> Any: ... |
| def accumulate(self, /, *args: Any, **kwargs: Any) -> NDArray[Any]: ... |
| def reduceat(self, /, *args: Any, **kwargs: Any) -> NDArray[Any]: ... |
| def outer(self, *args: Any, **kwargs: Any) -> Any: ... |
| # Similarly at won't be defined for ufuncs that return multiple |
| # outputs, so we can't type it very precisely. |
| def at(self, /, *args: Any, **kwargs: Any) -> 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_not: _UFunc_Nin1_Nout1[L['invert'], L[12], 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] |
| conj: _UFunc_Nin1_Nout1[L['conjugate'], L[18], 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['true_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] |
| mod: _UFunc_Nin2_Nout1[L['remainder'], L[16], 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] |
| true_divide: _UFunc_Nin2_Nout1[L['true_divide'], L[11], 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_invert = invert |
| bitwise_right_shift = right_shift |
| permute_dims = transpose |
| pow = power |
|
|
| # 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 __new__( |
| cls, |
| weekmask: ArrayLike = ..., |
| holidays: ArrayLike | dt.date | _NestedSequence[dt.date] = ..., |
| ) -> busdaycalendar: ... |
| @property |
| def weekmask(self) -> NDArray[np.bool]: ... |
| @property |
| def holidays(self) -> NDArray[datetime64]: ... |
|
|
| class finfo(Generic[_FloatingT_co]): |
| dtype: Final[dtype[_FloatingT_co]] |
| bits: Final[int] |
| eps: Final[_FloatingT_co] |
| epsneg: Final[_FloatingT_co] |
| iexp: Final[int] |
| machep: Final[int] |
| max: Final[_FloatingT_co] |
| maxexp: Final[int] |
| min: Final[_FloatingT_co] |
| minexp: Final[int] |
| negep: Final[int] |
| nexp: Final[int] |
| nmant: Final[int] |
| precision: Final[int] |
| resolution: Final[_FloatingT_co] |
| smallest_subnormal: Final[_FloatingT_co] |
| @property |
| def smallest_normal(self) -> _FloatingT_co: ... |
| @property |
| def tiny(self) -> _FloatingT_co: ... |
| @overload |
| def __new__(cls, dtype: inexact[_NBit1] | _DTypeLike[inexact[_NBit1]]) -> finfo[floating[_NBit1]]: ... |
| @overload |
| def __new__(cls, dtype: complex | type[complex]) -> finfo[float64]: ... |
| @overload |
| def __new__(cls, dtype: str) -> finfo[floating]: ... |
|
|
| class iinfo(Generic[_IntegerT_co]): |
| dtype: Final[dtype[_IntegerT_co]] |
| kind: Final[LiteralString] |
| bits: Final[int] |
| key: Final[LiteralString] |
| @property |
| def min(self) -> int: ... |
| @property |
| def max(self) -> int: ... |
|
|
| @overload |
| def __new__( |
| cls, dtype: _IntegerT_co | _DTypeLike[_IntegerT_co] |
| ) -> iinfo[_IntegerT_co]: ... |
| @overload |
| def __new__(cls, dtype: int | type[int]) -> iinfo[int_]: ... |
| @overload |
| def __new__(cls, dtype: str) -> iinfo[Any]: ... |
|
|
| @final |
| class nditer: |
| def __new__( |
| cls, |
| op: ArrayLike | Sequence[ArrayLike | None], |
| flags: Sequence[_NDIterFlagsKind] | None = ..., |
| op_flags: Sequence[Sequence[_NDIterFlagsOp]] | None = ..., |
| op_dtypes: DTypeLike | Sequence[DTypeLike] = ..., |
| order: _OrderKACF = ..., |
| casting: _CastingKind = ..., |
| op_axes: Sequence[Sequence[SupportsIndex]] | None = ..., |
| itershape: _ShapeLike | None = ..., |
| buffersize: SupportsIndex = ..., |
| ) -> nditer: ... |
| 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 = ..., |
| offset: int = ..., |
| shape: int | tuple[int, ...] | None = ..., |
| order: _OrderKACF = ..., |
| ) -> memmap[Any, dtype[uint8]]: ... |
| @overload |
| def __new__( |
| subtype, |
| filename: StrOrBytesPath | _SupportsFileMethodsRW, |
| dtype: _DTypeLike[_ScalarT], |
| mode: _MemMapModeKind = ..., |
| offset: int = ..., |
| shape: int | tuple[int, ...] | None = ..., |
| order: _OrderKACF = ..., |
| ) -> memmap[Any, dtype[_ScalarT]]: ... |
| @overload |
| def __new__( |
| subtype, |
| filename: StrOrBytesPath | _SupportsFileMethodsRW, |
| dtype: DTypeLike, |
| mode: _MemMapModeKind = ..., |
| offset: int = ..., |
| shape: int | tuple[int, ...] | None = ..., |
| order: _OrderKACF = ..., |
| ) -> memmap[Any, dtype]: ... |
| def __array_finalize__(self, obj: object) -> None: ... |
| def __array_wrap__( |
| self, |
| array: memmap[_ShapeT_co, _DTypeT_co], |
| context: tuple[ufunc, tuple[Any, ...], int] | None = ..., |
| return_scalar: builtins.bool = ..., |
| ) -> Any: ... |
| def flush(self) -> None: ... |
|
|
| # TODO: Add a mypy plugin for managing functions whose output type is dependent |
| # on the literal value of some sort of signature (e.g. `einsum` and `vectorize`) |
| class vectorize: |
| pyfunc: Callable[..., Any] |
| cache: builtins.bool |
| signature: LiteralString | None |
| otypes: LiteralString | None |
| excluded: set[int | str] |
| __doc__: str | None |
| def __init__( |
| self, |
| /, |
| pyfunc: Callable[..., Any] | _NoValueType = ..., # = _NoValue |
| otypes: str | Iterable[DTypeLike] | None = None, |
| doc: str | None = None, |
| excluded: Iterable[int | str] | None = None, |
| cache: builtins.bool = False, |
| signature: str | None = None, |
| ) -> None: ... |
| def __call__(self, *args: Any, **kwargs: Any) -> Any: ... |
|
|
| 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 = ..., |
| variable: str | 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 = ...) -> poly1d: ... |
| def integ( |
| self, |
| m: SupportsInt | SupportsIndex = ..., |
| k: _ArrayLikeComplex_co | _ArrayLikeObject_co | None = ..., |
| ) -> poly1d: ... |
|
|
| class matrix(ndarray[_2DShapeT_co, _DTypeT_co]): |
| __array_priority__: ClassVar[float] = 10.0 # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| def __new__( |
| subtype, # pyright: ignore[reportSelfClsParameterName] |
| data: ArrayLike, |
| dtype: DTypeLike = ..., |
| copy: builtins.bool = ..., |
| ) -> matrix[_2D, Incomplete]: ... |
| def __array_finalize__(self, obj: object) -> None: ... |
|
|
| @overload # type: ignore[override] |
| def __getitem__( |
| self, key: SupportsIndex | _ArrayLikeInt_co | tuple[SupportsIndex | _ArrayLikeInt_co, ...], / |
| ) -> Incomplete: ... |
| @overload |
| def __getitem__(self, key: _ToIndices, /) -> matrix[_2D, _DTypeT_co]: ... |
| @overload |
| def __getitem__(self: matrix[Any, dtype[void]], key: str, /) -> matrix[_2D, dtype]: ... |
| @overload |
| def __getitem__(self: matrix[Any, dtype[void]], key: list[str], /) -> matrix[_2DShapeT_co, _DTypeT_co]: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # |
| def __mul__(self, other: ArrayLike, /) -> matrix[_2D, Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
| def __rmul__(self, other: ArrayLike, /) -> matrix[_2D, Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
| def __imul__(self, other: ArrayLike, /) -> Self: ... |
|
|
| # |
| def __pow__(self, other: ArrayLike, mod: None = None, /) -> matrix[_2D, Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
| def __rpow__(self, other: ArrayLike, mod: None = None, /) -> matrix[_2D, Incomplete]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
| def __ipow__(self, other: ArrayLike, /) -> Self: ... # type: ignore[misc, override] |
|
|
| # keep in sync with `prod` and `mean` |
| @overload # type: ignore[override] |
| def sum(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ... |
| @overload |
| def sum(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> matrix[_2D, Incomplete]: ... |
| @overload |
| def sum(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def sum(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `sum` and `mean` |
| @overload # type: ignore[override] |
| def prod(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ... |
| @overload |
| def prod(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> matrix[_2D, Incomplete]: ... |
| @overload |
| def prod(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def prod(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `sum` and `prod` |
| @overload # type: ignore[override] |
| def mean(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ... |
| @overload |
| def mean(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> matrix[_2D, Incomplete]: ... |
| @overload |
| def mean(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def mean(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `var` |
| @overload # type: ignore[override] |
| def std(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ... |
| @overload |
| def std( |
| self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0 |
| ) -> matrix[_2D, Incomplete]: ... |
| @overload |
| def std(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ... |
| @overload |
| def std( # pyright: ignore[reportIncompatibleMethodOverride] |
| self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0 |
| ) -> _ArrayT: ... |
|
|
| # keep in sync with `std` |
| @overload # type: ignore[override] |
| def var(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ... |
| @overload |
| def var( |
| self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0 |
| ) -> matrix[_2D, Incomplete]: ... |
| @overload |
| def var(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ... |
| @overload |
| def var( # pyright: ignore[reportIncompatibleMethodOverride] |
| self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0 |
| ) -> _ArrayT: ... |
|
|
| # keep in sync with `all` |
| @overload # type: ignore[override] |
| def any(self, axis: None = None, out: None = None) -> np.bool: ... |
| @overload |
| def any(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, dtype[np.bool]]: ... |
| @overload |
| def any(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def any(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `any` |
| @overload # type: ignore[override] |
| def all(self, axis: None = None, out: None = None) -> np.bool: ... |
| @overload |
| def all(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, dtype[np.bool]]: ... |
| @overload |
| def all(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def all(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `min` and `ptp` |
| @overload # type: ignore[override] |
| def max(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ... |
| @overload |
| def max(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ... |
| @overload |
| def max(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def max(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `max` and `ptp` |
| @overload # type: ignore[override] |
| def min(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ... |
| @overload |
| def min(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ... |
| @overload |
| def min(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def min(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `max` and `min` |
| @overload |
| def ptp(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ... |
| @overload |
| def ptp(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ... |
| @overload |
| def ptp(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ... |
| @overload |
| def ptp(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `argmin` |
| @overload # type: ignore[override] |
| def argmax(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> intp: ... |
| @overload |
| def argmax(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, dtype[intp]]: ... |
| @overload |
| def argmax(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... |
| @overload |
| def argmax(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # keep in sync with `argmax` |
| @overload # type: ignore[override] |
| def argmin(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> intp: ... |
| @overload |
| def argmin(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, dtype[intp]]: ... |
| @overload |
| def argmin(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... |
| @overload |
| def argmin(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ... # pyright: ignore[reportIncompatibleMethodOverride] |
| |
| #the second overload handles the (rare) case that the matrix is not 2-d |
| @overload |
| def tolist(self: matrix[_2D, dtype[generic[_T]]]) -> list[list[_T]]: ... # pyright: ignore[reportIncompatibleMethodOverride] |
| @overload |
| def tolist(self) -> Incomplete: ... # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # these three methods will at least return a `2-d` array of shape (1, n) |
| def squeeze(self, axis: _ShapeLike | None = None) -> matrix[_2D, _DTypeT_co]: ... |
| def ravel(self, /, order: _OrderKACF = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
| def flatten(self, /, order: _OrderKACF = "C") -> matrix[_2D, _DTypeT_co]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] |
|
|
| # matrix.T is inherited from _ScalarOrArrayCommon |
| def getT(self) -> Self: ... |
| @property |
| def I(self) -> matrix[_2D, Incomplete]: ... # noqa: E743 |
| def getI(self) -> matrix[_2D, Incomplete]: ... |
| @property |
| def A(self) -> ndarray[_2DShapeT_co, _DTypeT_co]: ... |
| def getA(self) -> ndarray[_2DShapeT_co, _DTypeT_co]: ... |
| @property |
| def A1(self) -> ndarray[_AnyShape, _DTypeT_co]: ... |
| def getA1(self) -> ndarray[_AnyShape, _DTypeT_co]: ... |
| @property |
| def H(self) -> matrix[_2D, _DTypeT_co]: ... |
| def getH(self) -> matrix[_2D, _DTypeT_co]: ... |
|
|
| def from_dlpack( |
| x: _SupportsDLPack[None], |
| /, |
| *, |
| device: L["cpu"] | None = None, |
| copy: builtins.bool | None = None, |
| ) -> NDArray[number | np.bool]: ... |
|
|
