> and you want to retain as much precision as possible and still use floats They're equivalent. Both have a 23 bits (24 with implied mantissa, except for denor

> and you want to retain as much precision as possible and still use floats They're equivalent. Both have a 23 bits (24 with implied mantissa, except for denormals). Example, 2^n * (floating point here) are all exactly the same precision, since you can mult or div by 2 and not change any of the mantissa bits (untill you hit denormal or infinities). So mult or div by 100 has prettyMuch the same precision (up to 100 maybe having some off bit flip in the lowest bit). Another way to see it: IEEE 754 guarantees that A op B where x is float mult or div, is bit exact up to 1 ulp or 1/2 ulp depending on rounding mode. So by changing between these you have the exact same real number obtainiable. However, once you do what you claim is better, scaling an existing result to fit into some other range, you have potentially added a single bit flip error in the low bit, so you may be worse doing what you claim. > ou should not store them in the range [0.0,360.0), but instead store them either as radians [0-2π), or better: [-π,π), or store them as [-1.0,1.0) and use trig routines designed to work with that range. Nope, same reasons. Every elementary op you do adds max 1/2 ulp error (assuming one of the round to nearest modes). So, if you have something in radians, scale to 1.0 store/transmit whatever, and then your lib wants radians andScales back, at best you lost nothing, at worst you have added error. Trig routines in general for floating point do range reduction, and then have to do a decent amount of work to get 1/2 ulp precision (which pretty much all major C++ libs do now - it's not IEEE guaranteed!). So sure you can try to rederive a lib that works on [-bob,+bob], but you'll likley gain nothing against simply using whatever your library uses (which almost always goes into radians at some level since that is the most useful, and the lowest stacks end up there). Please don't tell people to scale numbers as if that makes them better. It makes them worse.