+ iRt^RIt^RIt^RIHt.tRRltRRlt]!RRR 4]!R RR 4]!R ]!]4R 4]!4t R#)z=A module for creating docstrings for sphinx ``data`` domains.N)NDArrayc@V^8dQhR\R\R\RR/#)namevaluedocreturnNstr)formats">/usr/lib/python3/dist-packages/numpy/_typing/_add_docstring.py __annotate__r s( 0 0S 0 03 04 0c4\PWV34R#)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_listappend)rrrs&&&r add_newdocr sT#./rc$V^8dQhR\/#)rrr )r s"r r r s$$3$rc.p\EFAwrp\P!V4PRR4pVP R4p.pRpVFp\ P !RV4p V 'dV'd\P!VP44p V R8Xd)RpVPV P^4 RV 24M'R pVPV P^4 RV 24VPR4KVPV V 24K RPV4pRV R V RV 2p VPV 4EKD RPV4#) zYConvert all docstrings in ``_docstrings_list`` into a single sphinx-legible text block.  z z^(\s+)[-=]+\s*$Examplesz .. rubric:: z.. admonition:: z .. data:: z :value: z ) rtextwrapdedentreplacesplitrematchpoprgroupjoin) type_list_retrrrslines new_linesindentlinemprevs_blocks r _parse_docstringsr*sD M,,S OOC ( (x 8  D+T2AYy}}7:%F$$ |<v%FG$F$$ |3CD6%JK  $  F8D6!23 IIi  nUG6!GW%/-0 99] ##r ArrayLikeztyping.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) 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 ` 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) ra9 A `np.ndarray[tuple[Any, ...], np.dtype[ScalarT]] ` type alias :term:`generic ` w.r.t. its `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) ) __doc__rr _array_likerrrr*repr _docstringsrr r2slC   0 $B ;+ < ;+ > 9d7m @ ! r