"Greg Ewing" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > I don't think you're doing anyone any favours by trying to protect > them from having to know about these things, because they *need* to > know about them if they're not to write algorithms that seem to > work fine on tests but mysteriously start producing garbage when > run on real data,
I agree. Here was my 'kick-in-the-butt' lesson (from 20+ years ago): the 'simplified for computation' formula for standard deviation, found in too many statistics books without a warning as to its danger, and specialized for three data points, is sqrt( ((a*a+b*b+c*c)-(a+b+c)**2/3.0) /2.0). After 1000s of ok calculations, the data were something like a,b,c = 10005,10006,10007. The correct answer is 1.0 but with numbers rounded to 7 digits, the computed answer is sqrt(-.5) == CRASH. I was aware that subtraction lost precision but not how rounding could make a theoretically guaranteed non-negative difference negative. Of course, Python floats being C doubles makes such glitches much rarer. Not exposing C floats is a major newbie (and journeyman) protection feature. Terry Jan Reedy _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
