On Nov 26, 2:11 pm, Steven D'Aprano <steve +comp.lang.pyt...@pearwood.info> wrote: > On Fri, 26 Nov 2010 12:54:12 -0800, John Nagle wrote: > > For ordinary number crunching, > > rational arithmetic is completely inappropriate. > > Why? > > -- > Steven As you perform repeated calculations with rationals, the size of the values (usually) keep growing. (Where size is measured as the length of numerator and denominator.) The speed and memory requirements are no longer constant.
I coded a quick matrix inversion function and measured running times using GMPY2 rational and floating point types. For the floating point tests, I used a precision of 1000 bits. With floating point values, the running time grew as n^3. With rational values, the running time grew as n^4*ln(n). On my system, inverting a 1000x1000 matrix with 1000-bit precision floating point would take about 30 minutes. Inverting the same matrix using rationals would take a month or longer and require much more memory. But the rational solution would be exact. casevh -- http://mail.python.org/mailman/listinfo/python-list