+
    ei  c                   s    R t ^ RIt^ RIt^RIHt . tR R ltR R lt]! RRR	4       ]! R
RR4       ]! R]! ]4      R4       ]! 4       t	R# )z=A module for creating docstrings for sphinx ``data`` domains.N)NDArrayc                s@    V ^8  d   QhR\         R\         R\         RR/# )   namevaluedocreturnNZstrZformat   "C/usr/lib64/python3.14/site-packages/numpy/_typing/_add_docstring.py__annotate__r
      s(     0 0S 0 03 04 0    c                s4    \         P                  WV34       R# )zAppend ``_docstrings_list`` with a docstring for `name`.

Parameters
----------
name : str
    The name of the object.
value : str
    A string-representation of the object.
doc : str
    The docstring of the object.

N)_docstrings_listappend)r   r   r   s   &&&r	   
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   r
      s     $ $3 $r   c                 s   . p \          EFA  w  rp\        P                  ! V4      P                  RR4      pVP	                  R4      p. pRpV F  p\
        P                  ! RV4      p	V	'       d   V'       d   \        P                  ! VP                  4       4      p
V
R8X  d)   RpVP                  V	P                  ^4       RV
 24       M'R
pVP                  V	P                  ^4       RV
 24       VP                  R4       K  VP                  V V 24       K  	  RP                  V4      pRV R	V RV 2pV P                  V4       EKD  	  RP                  V 4      # )zYConvert all docstrings in ``_docstrings_list`` into a single
sphinx-legible text block.

Z
z
    Z z^(\s+)[-=]+\s*$ZExamplesz.. rubric:: z.. admonition:: z
.. data:: z
    :value: z    )r   textwrapZdedentZreplaceZsplitreZmatchZpopr   ZgroupZjoin)Ztype_list_retr   r   r   ZsZlinesZ	new_linesZindentZlineZmZprevZs_blocks               r	   _parse_docstringsr      sD   
 M,,SOOC ((x8 	D+T2AYy}}7:%F$$
|<v%FG$F$$
|3CD6%JK  $  F8D6!23  IIi  nUG6!GW%/ -0 99]##r   Z	ArrayLikeztyping.Union[...]ag  
    A `~typing.Union` representing objects that can be coerced
    into an `~numpy.ndarray`.

    Among others this includes the likes of:

    * Scalars.
    * (Nested) sequences.
    * Objects implementing the `~class.__array__` protocol.

    .. versionadded:: 1.20

    See Also
    --------
    :term:`array_like`:
        Any scalar or sequence that can be interpreted as an ndarray.

    Examples
    --------
    .. code-block:: python

        >>> import numpy as np
        >>> import numpy.typing as npt

        >>> def as_array(a: npt.ArrayLike) -> np.ndarray:
        ...     return np.array(a)

    Z	DTypeLikea  
    A `~typing.Union` representing objects that can be coerced
    into a `~numpy.dtype`.

    Among others this includes the likes of:

    * :class:`type` objects.
    * Character codes or the names of :class:`type` objects.
    * Objects with the ``.dtype`` attribute.

    .. versionadded:: 1.20

    See Also
    --------
    :ref:`Specifying and constructing data types <arrays.dtypes.constructing>`
        A comprehensive overview of all objects that can be coerced
        into data types.

    Examples
    --------
    .. code-block:: python

        >>> import numpy as np
        >>> import numpy.typing as npt

        >>> def as_dtype(d: npt.DTypeLike) -> np.dtype:
        ...     return np.dtype(d)

    r    a9  
    A `np.ndarray[tuple[Any, ...], np.dtype[ScalarT]] <numpy.ndarray>`
    type alias :term:`generic <generic type>` w.r.t. its
    `dtype.type <numpy.dtype.type>`.

    Can be used during runtime for typing arrays with a given dtype
    and unspecified shape.

    .. versionadded:: 1.21

    Examples
    --------
    .. code-block:: python

        >>> import numpy as np
        >>> import numpy.typing as npt

        >>> print(npt.NDArray)
        numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~_ScalarT]]

        >>> print(npt.NDArray[np.float64])
        numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.float64]]

        >>> NDArrayInt = npt.NDArray[np.int_]
        >>> a: NDArrayInt = np.arange(10)

        >>> def func(a: npt.ArrayLike) -> npt.NDArray[Any]:
        ...     return np.array(a)

    )
Z__doc__r   r   Z_array_liker    r   r   r   ZreprZ_docstrings) r   r	   <module>r      sl    C 	    0 $B ;+	< ;+	> 9d7m	@  !r   