Fast Math.exp

I started on a FastMath class and then caved and started playing with this one. Just thought I'd offer up a fast Math.exp I found from this blog (via StackOverflow):

public static double exp(double val) {
    final long tmp = (long) (1512775 * val + 1072632447);
    return Double.longBitsToDouble(tmp << 32);
}

Probably doesn't matter to most of you, but if you're doing DC with gaussians it might. I actually use a different kernel density in my main gun because 20,000 Math.exp's each time I aim would be pretty slow. (Not sure the above would solve that, but anyway...)

Didn't I post that just above?

FYI - testing for values between -20 and 0, which would be the range if you're doing gaussians with bandwidth = 1/2 bot width and up to 40 bot widths.

Math.exp() time: 0.30864 seconds
FastMath.exp() time: 0.06371 seconds
FastMath.exp() worst error: 0.02899
FastMath.exp() avg error: 0.00073

Or for -3 to 0:

== exp Test ==
Math.exp() time: 0.38425 seconds
FastMath.exp() time: 0.07076 seconds
FastMath.exp() worst error: 0.02899
FastMath.exp() avg error: 0.00464

Oh, haha - sorry, I didn't see it in the file...

Yeah, I didn't update the main page, didn't want to overwrite others' functions. Try the atan/atan2 I posted, they're much more accurate I think.

Yep - already tested them, using them, and running a long benchmark with a FastMath Diamond. =) I actually haven't noticed any huge speed increase in Diamond, so I'm hesitant to keep all this FastMath stuff. But it is faster and the error rate looks pretty low, so if I don't take any score hit I'll definitely keep it.