\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)
\begin{array}{l}
t_0 := \log \left(2 \cdot \pi\right)\\
\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\sqrt[3]{\left(\left(2 \cdot \pi\right) \cdot e^{t_0 + t_0}\right) \cdot \left(u2 \cdot \left(u2 \cdot u2\right)\right)}\right)
\end{array}
(FPCore (cosTheta_i u1 u2) :precision binary32 (* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))
(FPCore (cosTheta_i u1 u2)
:precision binary32
(let* ((t_0 (log (* 2.0 PI))))
(*
(sqrt (- (log1p (- u1))))
(sin (cbrt (* (* (* 2.0 PI) (exp (+ t_0 t_0))) (* u2 (* u2 u2))))))))float code(float cosTheta_i, float u1, float u2) {
return sqrtf(-logf(1.0f - u1)) * sinf((2.0f * ((float) M_PI)) * u2);
}
float code(float cosTheta_i, float u1, float u2) {
float t_0 = logf(2.0f * ((float) M_PI));
return sqrtf(-log1pf(-u1)) * sinf(cbrtf(((2.0f * ((float) M_PI)) * expf(t_0 + t_0)) * (u2 * (u2 * u2))));
}



Bits error versus cosTheta_i



Bits error versus u1



Bits error versus u2
Results
Initial program 13.5
Simplified0.5
Applied add-cbrt-cube_binary320.5
Applied add-cbrt-cube_binary320.5
Applied cbrt-unprod_binary320.5
Applied add-exp-log_binary320.5
Applied add-exp-log_binary320.6
Applied prod-exp_binary320.5
Final simplification0.5
herbie shell --seed 2022005
(FPCore (cosTheta_i u1 u2)
:name "Beckmann Sample, near normal, slope_y"
:precision binary32
:pre (and (and (and (> cosTheta_i 0.9999) (<= cosTheta_i 1.0)) (and (<= 2.328306437e-10 u1) (<= u1 1.0))) (and (<= 2.328306437e-10 u2) (<= u2 1.0)))
(* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))