Average Error: 13.6 → 0.5
Time: 14.1s
Precision: binary32
\[\left(\left(cosTheta_i > 0.9999 \land cosTheta_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
\[\mathsf{expm1}\left(\mathsf{log1p}\left(\sin \left(\pi \cdot \left(u2 \cdot 2\right)\right) \cdot \sqrt{-\mathsf{log1p}\left(-u1\right)}\right)\right) \]
\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)
\mathsf{expm1}\left(\mathsf{log1p}\left(\sin \left(\pi \cdot \left(u2 \cdot 2\right)\right) \cdot \sqrt{-\mathsf{log1p}\left(-u1\right)}\right)\right)
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (expm1 (log1p (* (sin (* PI (* u2 2.0))) (sqrt (- (log1p (- u1))))))))
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) {
	return expm1f(log1pf(sinf(((float) M_PI) * (u2 * 2.0f)) * sqrtf(-log1pf(-u1))));
}

Error

Bits error versus cosTheta_i

Bits error versus u1

Bits error versus u2

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 13.6

    \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  2. Simplified0.5

    \[\leadsto \color{blue}{\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)} \]
  3. Applied add-sqr-sqrt_binary320.8

    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \color{blue}{\left(\sqrt{\left(2 \cdot \pi\right) \cdot u2} \cdot \sqrt{\left(2 \cdot \pi\right) \cdot u2}\right)} \]
  4. Applied expm1-log1p-u_binary320.8

    \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\sqrt{\left(2 \cdot \pi\right) \cdot u2} \cdot \sqrt{\left(2 \cdot \pi\right) \cdot u2}\right)\right)\right)} \]
  5. Simplified0.5

    \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(\sin \left(\pi \cdot \left(u2 \cdot 2\right)\right) \cdot \sqrt{-\mathsf{log1p}\left(-u1\right)}\right)}\right) \]
  6. Final simplification0.5

    \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\sin \left(\pi \cdot \left(u2 \cdot 2\right)\right) \cdot \sqrt{-\mathsf{log1p}\left(-u1\right)}\right)\right) \]

Reproduce

herbie shell --seed 2021280 
(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))))