o 1ήc' @sdZddlmZddlmZddlmZddlZddZegdZ d d Z e d d gd e dgde dgde dgde dgde dgde dgde dgde dgde dgde d gd!e d"gd#e d$gd%e d&d'gd(e d)d*gd+e d,d-gd.e d/d0d1gd2e d3d4d5gd6e d7gd8e d9d:gd;e de d?gd@e dAgdBe dCgdDedEdFdGdHD] Z edEe dIdJj e dKfedEe dLdMe dNe dOe dPfqdQD]!Z edEe dRdMe dSe dTee jrdUe dVndWfqdS)Xz This file is separate from ``_add_newdocs.py`` so that it can be mocked out by our sphinx ``conf.py`` during doc builds, where we want to avoid showing platform-dependent information. )dtype) numerictypes) add_newdocNcsfdd}t|S)Nc 3sBD]\}}ztt|}Wn tyYqw|||fVqdS)N)getattr _numerictypesAttributeError)aliasdoc alias_typealiasesF/tmp/pip-target-vg8gfxp4/lib/python/numpy/core/_add_newdocs_scalars.pytype_aliases_gens  z.numeric_type_aliases..type_aliases_gen)list)r rr r rnumeric_type_aliasess  r))int8z*8-bit signed integer (``-128`` to ``127``))int16z116-bit signed integer (``-32_768`` to ``32_767``))int32z?32-bit signed integer (``-2_147_483_648`` to ``2_147_483_647``))int64zW64-bit signed integer (``-9_223_372_036_854_775_808`` to ``9_223_372_036_854_775_807``))intpzJSigned integer large enough to fit pointer, compatible with C ``intptr_t``)uint8z)8-bit unsigned integer (``0`` to ``255``))uint16z-16-bit unsigned integer (``0`` to ``65_535``))uint32z432-bit unsigned integer (``0`` to ``4_294_967_295``))uint64zA64-bit unsigned integer (``0`` to ``18_446_744_073_709_551_615``))uintpzMUnsigned integer large enough to fit pointer, compatible with C ``uintptr_t``)float16zX16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa)float32zX32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa)float64zY64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa)float96z496-bit extended-precision floating-point number type)float128z5128-bit extended-precision floating-point number type) complex64zIComplex number type composed of 2 32-bit-precision floating-point numbers) complex128zIComplex number type composed of 2 64-bit-precision floating-point numbers) complex192zRComplex number type composed of 2 96-bit extended-precision floating-point numbers) complex256zSComplex number type composed of 2 128-bit extended-precision floating-point numberscstt|tj}|jkrdnd|}ddd|D}|dfddtD7}dj||||d}t d||dS) Nz :Canonical name: `numpy.{}` css|]}d|VqdS)z:Alias: `numpy.{}` N)format).0rr r r =sz-add_newdoc_for_scalar_type..c3s6|]\}}}|urdtt||VqdS)z5:Alias on this platform ({} {}): `numpy.{}`: {}. N)r&platformsystemmachine)r'r rr or rr(>s"z` {doc} :Character code: ``'{character_code}'`` {canonical_name_doc}{alias_doc} )r character_codecanonical_name_doc alias_docnumpy.core.numerictypes) rrrchar__name__r&joinpossible_aliasesstripr)obj fixed_aliasesr r.r/r0 docstringr r,radd_newdoc_for_scalar_type7s    r:bool_bool8aD Boolean type (True or False), stored as a byte. .. warning:: The :class:`bool_` type is not a subclass of the :class:`int_` type (the :class:`bool_` is not even a number type). This is different than Python's default implementation of :class:`bool` as a sub-class of :class:`int`. bytez: Signed integer type, compatible with C ``char``. shortz; Signed integer type, compatible with C ``short``. intcz9 Signed integer type, compatible with C ``int``. int_zK Signed integer type, compatible with Python `int` and C ``long``. longlongz? Signed integer type, compatible with C ``long long``. ubytezE Unsigned integer type, compatible with C ``unsigned char``. ushortzF Unsigned integer type, compatible with C ``unsigned short``. uintczD Unsigned integer type, compatible with C ``unsigned int``. uintzE Unsigned integer type, compatible with C ``unsigned long``. ulonglongzH Signed integer type, compatible with C ``unsigned long long``. halfz4 Half-precision floating-point number type. singlezS Single-precision floating-point number type, compatible with C ``float``. doublefloat_zk Double-precision floating-point number type, compatible with Python `float` and C ``double``. longdouble longfloatz Extended-precision floating-point number type, compatible with C ``long double`` but not necessarily with IEEE 754 quadruple-precision. csingle singlecomplexzZ Complex number type composed of two single-precision floating-point numbers. cdoublecfloatcomplex_z| Complex number type composed of two double-precision floating-point numbers, compatible with Python `complex`. clongdouble clongfloat longcomplexz\ Complex number type composed of two extended-precision floating-point numbers. object_z Any Python object. str_unicode_aV A unicode string. When used in arrays, this type strips trailing null codepoints. Unlike the builtin `str`, this supports the :ref:`python:bufferobjects`, exposing its contents as UCS4: >>> m = memoryview(np.str_("abc")) >>> m.format '3w' >>> m.tobytes() b'a\x00\x00\x00b\x00\x00\x00c\x00\x00\x00' bytes_string_zX A byte string. When used in arrays, this type strips trailing null bytes. voidae Either an opaque sequence of bytes, or a structure. >>> np.void(b'abcd') void(b'\x61\x62\x63\x64') Structured `void` scalars can only be constructed via extraction from :ref:`structured_arrays`: >>> arr = np.array((1, 2), dtype=[('x', np.int8), ('y', np.int8)]) >>> arr[()] (1, 2) # looks like a tuple, but is `np.void` datetime64a If created from a 64-bit integer, it represents an offset from ``1970-01-01T00:00:00``. If created from string, the string can be in ISO 8601 date or datetime format. >>> np.datetime64(10, 'Y') numpy.datetime64('1980') >>> np.datetime64('1980', 'Y') numpy.datetime64('1980') >>> np.datetime64(10, 'D') numpy.datetime64('1970-01-11') See :ref:`arrays.datetime` for more information. timedelta64zg A timedelta stored as a 64-bit integer. See :ref:`arrays.datetime` for more information. r1integer) is_integerz integer.is_integer() -> bool Return ``True`` if the number is finite with integral value. .. versionadded:: 1.22 Examples -------- >>> np.int64(-2).is_integer() True >>> np.uint32(5).is_integer() True )rGrHrIrKas_integer_ratioa {ftype}.as_integer_ratio() -> (int, int) Return a pair of integers, whose ratio is exactly equal to the original floating point number, and with a positive denominator. Raise `OverflowError` on infinities and a `ValueError` on NaNs. >>> np.{ftype}(10.0).as_integer_ratio() (10, 1) >>> np.{ftype}(0.0).as_integer_ratio() (0, 1) >>> np.{ftype}(-.25).as_integer_ratio() (-1, 4) )ftyper^z z.is_integer() -> bool Return ``True`` if the floating point number is finite with integral value, and ``False`` otherwise. .. versionadded:: 1.22 Examples -------- >>> np.z0(-2.0).is_integer() True >>> np.z)(3.2).is_integer() False ) rrrrrrrrrrrr bit_countz.bit_count() -> int Computes the number of 1-bits in the absolute value of the input. Analogous to the builtin `int.bit_count` or ``popcount`` in C++. Examples -------- >>> np.z(127).bit_count() 7z >>> np.z%(-127).bit_count() 7 r%)__doc__ numpy.corerrrnumpy.core.function_baserr)rr5r: float_namer&int_namer2islowerr r r rs