ÿØÿàJFIFÿþ ÿÛC       ÿÛC ÿÀÿÄÿÄ"#QrÿÄÿÄ&1!A"2qQaáÿÚ ?Øy,æ/3JæݹÈ߲؋5êXw²±ÉyˆR”¾I0ó2—PI¾IÌÚiMö¯–þrìN&"KgX:Šíµ•nTJnLK„…@!‰-ý ùúmë;ºgµŒ&ó±hw’¯Õ@”Ü— 9ñ-ë.²1<yà‚¹ïQÐU„ہ?.’¦èûbß±©Ö«Âw*VŒ) `$‰bØԟ’ëXÖ-ËTÜíGÚ3ð«g Ÿ§¯—Jx„–’U/ÂÅv_s(Hÿ@TñJÑãõçn­‚!ÈgfbÓc­:él[ðQe 9ÀPLbÃãCµm[5¿ç'ªjglå‡Ûí_§Úõl-;"PkÞÞÁQâ¼_Ñ^¢SŸx?"¸¦ùY騐ÒOÈ q’`~~ÚtËU¹CڒêV  I1Áß_ÿÙfrom collections.abc import Sequence from typing import ( Literal as L, Any, SupportsIndex, ) from numpy._typing import ( NDArray, ArrayLike, ) _BinKind = L[ "stone", "auto", "doane", "fd", "rice", "scott", "sqrt", "sturges", ] __all__: list[str] def histogram_bin_edges( a: ArrayLike, bins: _BinKind | SupportsIndex | ArrayLike = ..., range: None | tuple[float, float] = ..., weights: None | ArrayLike = ..., ) -> NDArray[Any]: ... def histogram( a: ArrayLike, bins: _BinKind | SupportsIndex | ArrayLike = ..., range: None | tuple[float, float] = ..., density: bool = ..., weights: None | ArrayLike = ..., ) -> tuple[NDArray[Any], NDArray[Any]]: ... def histogramdd( sample: ArrayLike, bins: SupportsIndex | ArrayLike = ..., range: Sequence[tuple[float, float]] = ..., density: None | bool = ..., weights: None | ArrayLike = ..., ) -> tuple[NDArray[Any], list[NDArray[Any]]]: ...