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  ã                   ó   — d Z ddlZdgZdd„Zy)z!
Introspection helper functions.
é    NÚopt_func_infoc                 ó¦  ‡
‡— ddl m}mŠ
 | �Jt        j                  | «      }|j                  «       D ��ci c]  \  }}|j                  |«      r||“Œ }}}n|}|�nt        j                  |«      Ši }|j                  «       D ]B  \  }}i }|j                  «       D ]   \  }	}t        ˆ
ˆfd„|	D «       «      sŒ|||	<   Œ" |sŒ>|||<   ŒD |S |}|S c c}}w )am  
    Returns a dictionary containing the currently supported CPU dispatched
    features for all optimized functions.

    Parameters
    ----------
    func_name : str (optional)
        Regular expression to filter by function name.

    signature : str (optional)
        Regular expression to filter by data type.

    Returns
    -------
    dict
        A dictionary where keys are optimized function names and values are
        nested dictionaries indicating supported targets based on data types.

    Examples
    --------
    Retrieve dispatch information for functions named 'add' or 'sub' and
    data types 'float64' or 'float32':

    >>> import numpy as np
    >>> dict = np.lib.introspect.opt_func_info(
    ...     func_name="add|abs", signature="float64|complex64"
    ... )
    >>> import json
    >>> print(json.dumps(dict, indent=2))
        {
          "absolute": {
            "dd": {
              "current": "SSE41",
              "available": "SSE41 baseline(SSE SSE2 SSE3)"
            },
            "Ff": {
              "current": "FMA3__AVX2",
              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
            },
            "Dd": {
              "current": "FMA3__AVX2",
              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
            }
          },
          "add": {
            "ddd": {
              "current": "FMA3__AVX2",
              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
            },
            "FFF": {
              "current": "FMA3__AVX2",
              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
            }
          }
        }

    r   )Ú__cpu_targets_info__Údtypec              3   ó†   •K  — | ]8  }‰j                  |«      xs! ‰j                   ‰|«      j                  «      –— Œ: y ­w)N)ÚsearchÚname)Ú.0Úcr   Úsig_patterns     €€úVC:\xampp\htdocs\tradingbinance\backend\.venv\Lib\site-packages\numpy/lib/introspect.pyÚ	<genexpr>z opt_func_info.<locals>.<genexpr>V   s?   øè ø€ ð á"˜ð  ×&Ñ& qÓ)ÒN¨[×-?Ñ-?ÁÀaÃÇÁÓ-NÓNÙ"ùs   ƒ>A)Únumpy._core._multiarray_umathr   r   ÚreÚcompileÚitemsr   Úany)Ú	func_nameÚ	signatureÚtargetsÚfunc_patternÚkÚvÚmatching_funcsÚmatching_sigsÚmatching_charsÚcharsr   r   s             @@r   r   r   	   sô   ù€ ÷tð ÐÜ—z‘z )Ó,ˆà$Ÿ]™]œ_ô
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ð
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s   µC)NN)Ú__doc__r   Ú__all__r   © ó    r   Ú<module>r"      s   ðñó 
àÐ
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