The most precise way with floats is likely to compute both sin and cos using a single x87 instruction, fsincos.
However, if you need to do the computation manually, it's best to group arguments with similar magnitudes. This means the second option is more precise, especially when cos_theta
is close to 0, where precision matters the most.
As the article What Every Computer Scientist Should Know About Floating-Point Arithmetic notes:
The expression x2 - y2 is another formula that exhibits catastrophic cancellation. It is more accurate to evaluate it as (x - y)(x + y).
Edit: it's more complicated than this. Although the above is generally true, (x - y)(x + y) is slightly less accurate when x and y are of very different magnitudes, as the footnote to the statement explains:
In this case, (x - y)(x + y) has three rounding errors, but x2 - y2 has only two since the rounding error committed when computing the smaller of x2 and y2 does not affect the final subtraction.
In other words, taking x - y, x + y, and the product (x - y)(x + y) each introduce rounding errors (3 steps of rounding error). x2, y2, and the subtraction x2 - y2 also each introduce rounding errors, but the rounding error obtained by squaring a relatively small number (the smaller of x and y) is so negligible that there are effectively only two steps of rounding error, making the difference of squares more precise.
So option 1 is actually going to be more precise. This is confirmed by dev.brutus's Java test.