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 numpy.core.fromnumeric import ( amin, amax, argmin, argmax, sum, prod, cumsum, cumprod, mean, var, std ) from numpy.lib.function_base import ( median, percentile, quantile, ) __all__: list[str] # NOTE: In reaility these functions are not aliases but distinct functions # with identical signatures. nanmin = amin nanmax = amax nanargmin = argmin nanargmax = argmax nansum = sum nanprod = prod nancumsum = cumsum nancumprod = cumprod nanmean = mean nanvar = var nanstd = std nanmedian = median nanpercentile = percentile nanquantile = quantile