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cloudlinux
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venv
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lib
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python3.11
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numpy
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Editing: _add_newdocs_scalars.cpython-311.pyc
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N)�_doc_alias_string)r< r r r �os �r r= z-add_newdoc_for_scalar_type.<locals>.<genexpr>S sX �� � � � ^� ^� 5�j�%��Z�[\�_�_� .�M�M�u�M�M��M�M�M�M\�_�_�_�^� ^r z z :Character code: ``'z'`` �numpy.core.numerictypes) r r r �char�__name__�join�possible_aliases�stripr )�obj� fixed_aliasesr �character_code�canonical_name_doc� alias_doc� docstringr@ s @r �add_newdoc_for_scalar_typerM G s1 �� �� �s�#�#�A��1�X�X�]�N� "�a�j� 0� 0���?�3�?�?�?� �� ��G�G� 8� 8�)6� 8� 8� 8� 8� 8� � � � � ���� ^� ^� ^� ^�9I�^� ^� ^� ^� ^� ^�I���Y�Y�[�[�� � (�� � � � #� � � �I� �(�#�y�9�9�9�9�9r �bool_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`. �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``. �double�float_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. �cdouble�cfloat�complex_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_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' �bytes_�string_zX A byte string. When used in arrays, this type strips trailing null bytes. �voida� 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` � 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. rA �integer)� 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 )rY rZ r[ r] �as_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) )�ftyperp 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 ) r r r r r r r r r r r r � 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++. 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