Robert Kern wrote: >> This was not supposed to be a scientific statement -- I'm (again) >> thinking of our students that not always appreciate the full >> complexity >> of computational numerics and data types and such. > > They need to appreciate the complexity of computational numerics if > they are going to do numerical computation. Double precision does not > make it any simpler.
This is were we differ. > We haven't forgotten what newcomers will do; to the contrary, we are > quite aware > that new users need consistent behavior in order to learn how to use a > system. > Adding another special case in how dtypes implicitly convert to one > another will > impede new users being able to understand the whole system. All I'm proposing could be summarized in: mean(), sum(), var() ... produce output of dtype float64 (except for input float96 which produces float96) A comment on this is also that for these operations the input type/precision is almost not related to the resulting output precision -- the int case makes that already clear. (This is different for e.g. min() or max() ) The proposed alternative implementations seem to have one or more multiplication (or division) for each value -- this might be noticeably slower ... Regards, Sebastian ------------------------------------------------------------------------- Take Surveys. Earn Cash. Influence the Future of IT Join SourceForge.net's Techsay panel and you'll get the chance to share your opinions on IT & business topics through brief surveys -- and earn cash http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
