§ 1jJ/م َ@—dZddlZddlZddlmZddlmZddlmZd„Z e gd¢¦«Z d„Ze¦«\ZZ d e›d e ›d‌Zd„Zed gd¦«edgd¦«edgd¦«edgd¦«edgd¦«edgd¦«edgd¦«edgd¦«edgd¦«edgd ¦«ed!gd"¦«ed#gd$¦«ed%gd&¦«ed'd(gd)¦«ed*d+gd,¦«ed-d.gd/¦«ed0d1d2gd3¦«ed4d5d6gd7¦«ed8gd9¦«ed:d;gd<¦«ed=d>gd?¦«ed@gdA¦«edBgdC¦«edDgdE¦«edFdGdH¦«dID]>ZedFedJdK e¬L¦«f¦«edFedMdNe›dOe›dPe›dQ‌f¦«Œ?dRD]CZedFedSdNe›dTe›dU‌ee¦«j ¦«rdVe›dW‌ndXzf¦«ŒDdS)Yz¹ This file is separate from ``_add_newdocs.py`` so that it can be mocked out by our sphinx ``conf.py`` during doc builds, where we want to avoid showing platform-dependent information. éN)عdtype)عnumerictypes)ع add_newdoccَ<‡—ˆfd„}t|¦«¦«S)Nc3َv•K—‰D]2\}} tt|¦«}|||fV—Œ##t$rYŒ/wxYwdS)N)عgetattrع _numerictypesعAttributeError)عaliasعdocع alias_typeعaliasess €ْV/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/core/_add_newdocs_scalars.pyعtype_aliases_genz.numeric_type_aliases..type_aliases_gensrّèè€ط!ً /ً /‰JˆEگ3ً /ف$¥]°Eر:ش:گ ً " 5¨#ذ.ذ.ذ.ذ.ذ.ُّ "ً ً ً àگً ًّّّ /ً /sŒ)© 6µ6)عlist)rrs` rعnumeric_type_aliasesrs6ّ€ً/ً/ً/ً/ً/ُذ ذ ر"ش"ر#ش#ذ#َ))عint8z*8-bit signed integer (``-128`` to ``127``))عint16z116-bit signed integer (``-32_768`` to ``32_767``))عint32z?32-bit signed integer (``-2_147_483_648`` to ``2_147_483_647``))عint64zW64-bit signed integer (``-9_223_372_036_854_775_808`` to ``9_223_372_036_854_775_807``))عintpzJSigned integer large enough to fit pointer, compatible with C ``intptr_t``)عuint8z)8-bit unsigned integer (``0`` to ``255``))عuint16z-16-bit unsigned integer (``0`` to ``65_535``))عuint32z432-bit unsigned integer (``0`` to ``4_294_967_295``))عuint64zA64-bit unsigned integer (``0`` to ``18_446_744_073_709_551_615``))عuintpzMUnsigned integer large enough to fit pointer, compatible with C ``uintptr_t``)عfloat16zX16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa)عfloat32zX32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa)عfloat64zY64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa)عfloat96z496-bit extended-precision floating-point number type)عfloat128z5128-bit extended-precision floating-point number type)ع complex64zIComplex number type composed of 2 32-bit-precision floating-point numbers)ع complex128zIComplex number type composed of 2 64-bit-precision floating-point numbers)ع complex192zRComplex number type composed of 2 96-bit extended-precision floating-point numbers)ع complex256zSComplex number type composed of 2 128-bit extended-precision floating-point numberscَ — tj¦«\}}}}}ne#t$rXtj}|dkrAtj dd¦«ptj dd¦«}nd}YnwxYw||fS)Nعwin32عPROCESSOR_ARCHITEW6432ععPROCESSOR_ARCHITECTUREعunknown)عosعunamer عsysعplatformعenvironعget)عsystemع_عmachines rع_get_platform_and_machiner66s–€ً ف#%¤8،:¤:ر ˆگگ1گaککّفً ً ً ف”ˆطگWزذف”j—n’nذ%=¸rرBشBًDف”z—~’~ذ&>ہرCشCً ˆGً ˆGًّّ ًّّّگ7ˆ?ذs‚œAA>ء=A>z:Alias on this platform (ْ z):cَ|‡—tt|¦«ٹt‰¦«j}|‰jkrdnd|›d‌}|r d d„|D¦«¦«}nd}|d ˆfd„tD¦«¦«z }d| ¦«›d|›d|›|›d‌}td ||¦«dS) Nr*z:Canonical name: `numpy.ْ` c3َ"K—|] }d|›d‌V—ŒdS)z:Alias: `numpy.r9N©)ع.0rs rْ z-add_newdoc_for_scalar_type..OsAèè€ً8ً8ط %ً=¨eذ<ذ<ذ<ً8ً8ً8ً8ً8ً8rc3َH•K—|]\}}}|‰u¯ t›d|›d|›d‌V—ŒdS)z `numpy.z`: z. N)ع_doc_alias_string)r<r rrعos €rr=z-add_newdoc_for_scalar_type..SsXّèè€ً^ً^ظ5کj¨%°بZذ[\ب_ب_ُ.ذMذM°uذMذMہذMذMذMطM\ب_ب_ب_ً^ً^rz z :Character code: ``'z'`` ْnumpy.core.numerictypes) rr rعcharع__name__عjoinعpossible_aliasesعstripr)عobjع fixed_aliasesrعcharacter_codeعcanonical_name_docع alias_docع docstringr@s @rعadd_newdoc_for_scalar_typerMGs1ّ€ه• کsر#ش#€Aهک1‘X”X”]€Nط" a¤jز0ذ0ککط?°3ذ?ذ?ذ?ًàًط—G’Gً8ً8ط)6ً8ٌ8ô8ٌ8ô8ˆ ˆ ًˆ ط گ—’ً^ً^ً^ً^ف9Iً^ٌ^ô^ٌ^ô^ٌ^€Iًط‡Y‚Yپ[„[ًًً(ًًًً ً#ً ًً€Iُذ(¨#¨yر9ش9ذ9ذ9ذ9rعbool_aD 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`. عbytez: Signed integer type, compatible with C ``char``. عshortz; Signed integer type, compatible with C ``short``. عintcz9 Signed integer type, compatible with C ``int``. عint_zK Signed integer type, compatible with Python `int` and C ``long``. عlonglongz? Signed integer type, compatible with C ``long long``. عubytezE Unsigned integer type, compatible with C ``unsigned char``. عushortzF Unsigned integer type, compatible with C ``unsigned short``. عuintczD Unsigned integer type, compatible with C ``unsigned int``. عuintzE Unsigned integer type, compatible with C ``unsigned long``. ع ulonglongzH Signed integer type, compatible with C ``unsigned long long``. عhalfz4 Half-precision floating-point number type. عsinglezS Single-precision floating-point number type, compatible with C ``float``. عdoubleعfloat_zk Double-precision floating-point number type, compatible with Python `float` and C ``double``. ع longdoubleع longfloatz• Extended-precision floating-point number type, compatible with C ``long double`` but not necessarily with IEEE 754 quadruple-precision. عcsingleع singlecomplexzZ Complex number type composed of two single-precision floating-point numbers. عcdoubleعcfloatعcomplex_z| Complex number type composed of two double-precision floating-point numbers, compatible with Python `complex`. عclongdoubleع clongfloatعlongcomplexz\ Complex number type composed of two extended-precision floating-point numbers. عobject_z Any Python object. عstr_عunicode_au A unicode string. This type strips trailing null codepoints. >>> s = np.str_("abc\x00") >>> s 'abc' 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' عbytes_عstring_zX A byte string. When used in arrays, this type strips trailing null bytes. عvoidaُ np.void(length_or_data, /, dtype=None) Create a new structured or unstructured void scalar. Parameters ---------- length_or_data : int, array-like, bytes-like, object One of multiple meanings (see notes). The length or bytes data of an unstructured void. Or alternatively, the data to be stored in the new scalar when `dtype` is provided. This can be an array-like, in which case an array may be returned. dtype : dtype, optional If provided the dtype of the new scalar. This dtype must be "void" dtype (i.e. a structured or unstructured void, see also :ref:`defining-structured-types`). ..versionadded:: 1.24 Notes ----- For historical reasons and because void scalars can represent both arbitrary byte data and structured dtypes, the void constructor has three calling conventions: 1. ``np.void(5)`` creates a ``dtype="V5"`` scalar filled with five ``\0`` bytes. The 5 can be a Python or NumPy integer. 2. ``np.void(b"bytes-like")`` creates a void scalar from the byte string. The dtype itemsize will match the byte string length, here ``"V10"``. 3. When a ``dtype=`` is passed the call is roughly the same as an array creation. However, a void scalar rather than array is returned. Please see the examples which show all three different conventions. Examples -------- >>> np.void(5) void(b'\x00\x00\x00\x00\x00') >>> np.void(b'abcd') void(b'\x61\x62\x63\x64') >>> np.void((5, 3.2, "eggs"), dtype="i,d,S5") (5, 3.2, b'eggs') # looks like a tuple, but is `np.void` >>> np.void(3, dtype=[('x', np.int8), ('y', np.int8)]) (3, 3) # looks like a tuple, but is `np.void` ع 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. عtimedelta64zg A timedelta stored as a 64-bit integer. See :ref:`arrays.datetime` for more information. rAعinteger)ع is_integerzُ 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 )rYrZr[r]عas_integer_ratioaز {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) )عftyperpz zق.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 )rrrrrrrrrrrrع bit_countzع.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*)ع__doc__r/r-ع numpy.corerrr عnumpy.core.function_baserrrEr6ع_systemع_machiner?rMع float_nameعformatعint_namerBعislowerr;rrْr}sbًًًً € € € ط € € € طذذذذذط4ذ4ذ4ذ4ذ4ذ4ط/ذ/ذ/ذ/ذ/ذ/ً $ً $ً $ً(ذ'ً)ً)ً)ٌôذً. ً ً ً.ذ-ر/ش/ر€ˆطF°ذFذF¸(ذFذFذFذً:ً:ً:ً2ذک7 Bً ٌ ô ً ًذک6 2ًٌ ô ً ً ذک7 Bًٌ ô ً ً ذک6 2ًٌ ô ً ً ذک6 2ًٌ ô ً ً ذک: rًٌ ô ً ً ذک7 Bًٌ ô ً ً ذک8 Rًٌ ô ً ً ذک7 Bًٌ ô ً ً ذک6 2ًٌ ô ً ً ذک;¨ًٌ ô ً ً ذک6 2ًٌ ô ً ً ذک8 Rًٌ ô ً ً ذک8 h Zًٌ ô ً ًذک<¨+¨ًٌ ô ً ًذک9 ذ&7ًٌ ô ً ًذک9 x°ذ&<ًٌ ô ً ًذک=¨<¸ذ*Gًٌ ô ً ًذک9 bًٌ ô ً ً ذک6 J <ًٌ ô ً ً(ذک8 i [ًٌ ô ً ًذک6 2ً/ٌ0 ô0 ً0 ًdذک<¨ًٌ ô ً ً"ذک=¨"ًٌ ô ً ً€ ذ$ iً2 ٌ ô ً ً"=ً ً €Jط€Jذ(¨*ذ7Iً ÷ ٹFکˆFر$ش$ً7&ٌ'ô'ً'ً €Jذ(¨*°|ً ط ً ً ًً ً ًً ً ً ً7 ٌôًًً"Aً9ً9€Hً€Jذ(¨(°[ً ط ً ً ًً ً ً ًˆuگX‰Œش#×+ز+ر-ش-ً 6ً طً ً ً ً ً46ٌ 7ً58ٌ9ô9ً9ً9ً9ً9r