UniformSampleCone, x

Percentage Accurate: 57.7% → 99.1%
Time: 6.5s
Alternatives: 16
Speedup: 5.8×

Specification

?
\[\left(\left(2.328306437 \cdot 10^{-10} \leq ux \land ux \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq uy \land uy \leq 1\right)\right) \land \left(0 \leq maxCos \land maxCos \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) PI)) (sqrt (- 1.0 (* t_0 t_0))))))
float code(float ux, float uy, float maxCos) {
	float t_0 = (1.0f - ux) + (ux * maxCos);
	return cosf(((uy * 2.0f) * ((float) M_PI))) * sqrtf((1.0f - (t_0 * t_0)));
}
function code(ux, uy, maxCos)
	t_0 = Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))
	return Float32(cos(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0))))
end
function tmp = code(ux, uy, maxCos)
	t_0 = (single(1.0) - ux) + (ux * maxCos);
	tmp = cos(((uy * single(2.0)) * single(pi))) * sqrt((single(1.0) - (t_0 * t_0)));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\end{array}
\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 16 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 57.7% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) PI)) (sqrt (- 1.0 (* t_0 t_0))))))
float code(float ux, float uy, float maxCos) {
	float t_0 = (1.0f - ux) + (ux * maxCos);
	return cosf(((uy * 2.0f) * ((float) M_PI))) * sqrtf((1.0f - (t_0 * t_0)));
}
function code(ux, uy, maxCos)
	t_0 = Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))
	return Float32(cos(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0))))
end
function tmp = code(ux, uy, maxCos)
	t_0 = (single(1.0) - ux) + (ux * maxCos);
	tmp = cos(((uy * single(2.0)) * single(pi))) * sqrt((single(1.0) - (t_0 * t_0)));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\end{array}
\end{array}

Alternative 1: 99.1% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \sin \left(\mathsf{fma}\left(-\pi, 2 \cdot uy, \frac{\pi}{2}\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (sin (fma (- PI) (* 2.0 uy) (/ PI 2.0)))
  (sqrt
   (*
    (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
    ux))))
float code(float ux, float uy, float maxCos) {
	return sinf(fmaf(-((float) M_PI), (2.0f * uy), (((float) M_PI) / 2.0f))) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
}
function code(ux, uy, maxCos)
	return Float32(sin(fma(Float32(-Float32(pi)), Float32(Float32(2.0) * uy), Float32(Float32(pi) / Float32(2.0)))) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
end
\begin{array}{l}

\\
\sin \left(\mathsf{fma}\left(-\pi, 2 \cdot uy, \frac{\pi}{2}\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 57.7%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    7. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    8. lower-neg.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  4. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
  5. Taylor expanded in maxCos around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  6. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lower--.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  7. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Step-by-step derivation
    1. lift-cos.f32N/A

      \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lift-*.f32N/A

      \[\leadsto \cos \left(\color{blue}{\left(uy \cdot 2\right)} \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lift-PI.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lift-*.f32N/A

      \[\leadsto \cos \color{blue}{\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. cos-neg-revN/A

      \[\leadsto \color{blue}{\cos \left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. sin-+PI/2-revN/A

      \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. lower-sin.f32N/A

      \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. lower-+.f32N/A

      \[\leadsto \sin \color{blue}{\left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    9. lower-neg.f32N/A

      \[\leadsto \sin \left(\color{blue}{\left(-\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    10. *-commutativeN/A

      \[\leadsto \sin \left(\left(-\color{blue}{\mathsf{PI}\left(\right) \cdot \left(uy \cdot 2\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    11. lower-*.f32N/A

      \[\leadsto \sin \left(\left(-\color{blue}{\mathsf{PI}\left(\right) \cdot \left(uy \cdot 2\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lift-PI.f32N/A

      \[\leadsto \sin \left(\left(-\color{blue}{\pi} \cdot \left(uy \cdot 2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    13. *-commutativeN/A

      \[\leadsto \sin \left(\left(-\pi \cdot \color{blue}{\left(2 \cdot uy\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    14. lower-*.f32N/A

      \[\leadsto \sin \left(\left(-\pi \cdot \color{blue}{\left(2 \cdot uy\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    15. lower-/.f32N/A

      \[\leadsto \sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    16. lift-PI.f3299.0

      \[\leadsto \sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \frac{\color{blue}{\pi}}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  9. Applied rewrites99.0%

    \[\leadsto \color{blue}{\sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \frac{\pi}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  10. Step-by-step derivation
    1. lift-+.f32N/A

      \[\leadsto \sin \color{blue}{\left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \frac{\pi}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lift-neg.f32N/A

      \[\leadsto \sin \left(\color{blue}{\left(\mathsf{neg}\left(\pi \cdot \left(2 \cdot uy\right)\right)\right)} + \frac{\pi}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lift-PI.f32N/A

      \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\mathsf{PI}\left(\right)} \cdot \left(2 \cdot uy\right)\right)\right) + \frac{\pi}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lift-*.f32N/A

      \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\mathsf{PI}\left(\right) \cdot \left(2 \cdot uy\right)}\right)\right) + \frac{\pi}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. distribute-lft-neg-inN/A

      \[\leadsto \sin \left(\color{blue}{\left(\mathsf{neg}\left(\mathsf{PI}\left(\right)\right)\right) \cdot \left(2 \cdot uy\right)} + \frac{\pi}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. lower-fma.f32N/A

      \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{neg}\left(\mathsf{PI}\left(\right)\right), 2 \cdot uy, \frac{\pi}{2}\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. lower-neg.f32N/A

      \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{-\mathsf{PI}\left(\right)}, 2 \cdot uy, \frac{\pi}{2}\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. lift-PI.f3299.1

      \[\leadsto \sin \left(\mathsf{fma}\left(-\color{blue}{\pi}, 2 \cdot uy, \frac{\pi}{2}\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  11. Applied rewrites99.1%

    \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(-\pi, 2 \cdot uy, \frac{\pi}{2}\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  12. Add Preprocessing

Alternative 2: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (sin (fma -2.0 (* uy PI) (* 0.5 PI)))
  (sqrt
   (*
    (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
    ux))))
float code(float ux, float uy, float maxCos) {
	return sinf(fmaf(-2.0f, (uy * ((float) M_PI)), (0.5f * ((float) M_PI)))) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
}
function code(ux, uy, maxCos)
	return Float32(sin(fma(Float32(-2.0), Float32(uy * Float32(pi)), Float32(Float32(0.5) * Float32(pi)))) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
end
\begin{array}{l}

\\
\sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 57.7%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    7. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    8. lower-neg.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  4. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
  5. Taylor expanded in maxCos around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  6. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lower--.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  7. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Step-by-step derivation
    1. lift-cos.f32N/A

      \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lift-*.f32N/A

      \[\leadsto \cos \left(\color{blue}{\left(uy \cdot 2\right)} \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lift-PI.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lift-*.f32N/A

      \[\leadsto \cos \color{blue}{\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. cos-neg-revN/A

      \[\leadsto \color{blue}{\cos \left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. sin-+PI/2-revN/A

      \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. lower-sin.f32N/A

      \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. lower-+.f32N/A

      \[\leadsto \sin \color{blue}{\left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    9. lower-neg.f32N/A

      \[\leadsto \sin \left(\color{blue}{\left(-\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    10. *-commutativeN/A

      \[\leadsto \sin \left(\left(-\color{blue}{\mathsf{PI}\left(\right) \cdot \left(uy \cdot 2\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    11. lower-*.f32N/A

      \[\leadsto \sin \left(\left(-\color{blue}{\mathsf{PI}\left(\right) \cdot \left(uy \cdot 2\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lift-PI.f32N/A

      \[\leadsto \sin \left(\left(-\color{blue}{\pi} \cdot \left(uy \cdot 2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    13. *-commutativeN/A

      \[\leadsto \sin \left(\left(-\pi \cdot \color{blue}{\left(2 \cdot uy\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    14. lower-*.f32N/A

      \[\leadsto \sin \left(\left(-\pi \cdot \color{blue}{\left(2 \cdot uy\right)}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    15. lower-/.f32N/A

      \[\leadsto \sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    16. lift-PI.f3299.0

      \[\leadsto \sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \frac{\color{blue}{\pi}}{2}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  9. Applied rewrites99.0%

    \[\leadsto \color{blue}{\sin \left(\left(-\pi \cdot \left(2 \cdot uy\right)\right) + \frac{\pi}{2}\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  10. Taylor expanded in uy around 0

    \[\leadsto \sin \color{blue}{\left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  11. Step-by-step derivation
    1. lower-fma.f32N/A

      \[\leadsto \sin \left(\mathsf{fma}\left(-2, \color{blue}{uy \cdot \mathsf{PI}\left(\right)}, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lower-*.f32N/A

      \[\leadsto \sin \left(\mathsf{fma}\left(-2, uy \cdot \color{blue}{\mathsf{PI}\left(\right)}, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lift-PI.f32N/A

      \[\leadsto \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lower-*.f32N/A

      \[\leadsto \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. lift-PI.f3299.0

      \[\leadsto \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  12. Applied rewrites99.0%

    \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  13. Add Preprocessing

Alternative 3: 98.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), \mathsf{fma}\left(-2, maxCos, 2\right)\right) \cdot ux} \cdot \cos \left(\pi \cdot \left(2 \cdot uy\right)\right) \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (sqrt
   (* (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) (fma -2.0 maxCos 2.0)) ux))
  (cos (* PI (* 2.0 uy)))))
float code(float ux, float uy, float maxCos) {
	return sqrtf((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), fmaf(-2.0f, maxCos, 2.0f)) * ux)) * cosf((((float) M_PI) * (2.0f * uy)));
}
function code(ux, uy, maxCos)
	return Float32(sqrt(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), fma(Float32(-2.0), maxCos, Float32(2.0))) * ux)) * cos(Float32(Float32(pi) * Float32(Float32(2.0) * uy))))
end
\begin{array}{l}

\\
\sqrt{\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), \mathsf{fma}\left(-2, maxCos, 2\right)\right) \cdot ux} \cdot \cos \left(\pi \cdot \left(2 \cdot uy\right)\right)
\end{array}
Derivation
  1. Initial program 57.7%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    7. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    8. lower-neg.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  4. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
  5. Taylor expanded in maxCos around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  6. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    3. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. lower--.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  7. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Applied rewrites98.9%

    \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), \mathsf{fma}\left(-2, maxCos, 2\right)\right) \cdot ux} \cdot \cos \left(\pi \cdot \left(2 \cdot uy\right)\right)} \]
  9. Add Preprocessing

Alternative 4: 98.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -ux\right) + 2\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (cos (* (* uy 2.0) PI))
  (sqrt (* (+ (fma (- (* ux 2.0) 2.0) maxCos (- ux)) 2.0) ux))))
float code(float ux, float uy, float maxCos) {
	return cosf(((uy * 2.0f) * ((float) M_PI))) * sqrtf(((fmaf(((ux * 2.0f) - 2.0f), maxCos, -ux) + 2.0f) * ux));
}
function code(ux, uy, maxCos)
	return Float32(cos(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * sqrt(Float32(Float32(fma(Float32(Float32(ux * Float32(2.0)) - Float32(2.0)), maxCos, Float32(-ux)) + Float32(2.0)) * ux)))
end
\begin{array}{l}

\\
\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -ux\right) + 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 57.7%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    7. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    8. lower-neg.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  4. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
  5. Taylor expanded in maxCos around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(2 + \left(-1 \cdot ux + maxCos \cdot \left(2 \cdot ux - 2\right)\right)\right) \cdot ux} \]
  6. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot ux + maxCos \cdot \left(2 \cdot ux - 2\right)\right) + 2\right) \cdot ux} \]
    2. lower-+.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot ux + maxCos \cdot \left(2 \cdot ux - 2\right)\right) + 2\right) \cdot ux} \]
    3. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(maxCos \cdot \left(2 \cdot ux - 2\right) + -1 \cdot ux\right) + 2\right) \cdot ux} \]
    4. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(2 \cdot ux - 2\right) \cdot maxCos + -1 \cdot ux\right) + 2\right) \cdot ux} \]
    5. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(2 \cdot ux - 2, maxCos, -1 \cdot ux\right) + 2\right) \cdot ux} \]
    6. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(2 \cdot ux - 2, maxCos, -1 \cdot ux\right) + 2\right) \cdot ux} \]
    7. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -1 \cdot ux\right) + 2\right) \cdot ux} \]
    8. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -1 \cdot ux\right) + 2\right) \cdot ux} \]
    9. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, \mathsf{neg}\left(ux\right)\right) + 2\right) \cdot ux} \]
    10. lift-neg.f3298.2

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -ux\right) + 2\right) \cdot ux} \]
  7. Applied rewrites98.2%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -ux\right) + 2\right) \cdot ux} \]
  8. Add Preprocessing

Alternative 5: 97.3% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (cos (* (* uy 2.0) PI))
  (sqrt (* (- (fma -1.0 ux 2.0) (* maxCos 2.0)) ux))))
float code(float ux, float uy, float maxCos) {
	return cosf(((uy * 2.0f) * ((float) M_PI))) * sqrtf(((fmaf(-1.0f, ux, 2.0f) - (maxCos * 2.0f)) * ux));
}
function code(ux, uy, maxCos)
	return Float32(cos(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * sqrt(Float32(Float32(fma(Float32(-1.0), ux, Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
end
\begin{array}{l}

\\
\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 57.7%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    7. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    8. lower-neg.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3298.9

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  4. Applied rewrites98.9%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
  5. Taylor expanded in maxCos around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot ux\right) - maxCos \cdot 2\right) \cdot ux} \]
  6. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot ux + 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lower-fma.f3297.3

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  7. Applied rewrites97.3%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Add Preprocessing

Alternative 6: 97.9% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 0.07000000029802322:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\ \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (if (<= uy 0.07000000029802322)
   (*
    (fma
     (fma
      (* 0.6666666666666666 (* uy uy))
      (* (* PI PI) (* PI PI))
      (* (* PI PI) -2.0))
     (* uy uy)
     1.0)
    (sqrt
     (*
      (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
      ux)))
   (* (cos (* (* uy 2.0) PI)) (sqrt (* (fma -1.0 ux 2.0) ux)))))
float code(float ux, float uy, float maxCos) {
	float tmp;
	if (uy <= 0.07000000029802322f) {
		tmp = fmaf(fmaf((0.6666666666666666f * (uy * uy)), ((((float) M_PI) * ((float) M_PI)) * (((float) M_PI) * ((float) M_PI))), ((((float) M_PI) * ((float) M_PI)) * -2.0f)), (uy * uy), 1.0f) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
	} else {
		tmp = cosf(((uy * 2.0f) * ((float) M_PI))) * sqrtf((fmaf(-1.0f, ux, 2.0f) * ux));
	}
	return tmp;
}
function code(ux, uy, maxCos)
	tmp = Float32(0.0)
	if (uy <= Float32(0.07000000029802322))
		tmp = Float32(fma(fma(Float32(Float32(0.6666666666666666) * Float32(uy * uy)), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(Float32(pi) * Float32(pi))), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(-2.0))), Float32(uy * uy), Float32(1.0)) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)));
	else
		tmp = Float32(cos(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * sqrt(Float32(fma(Float32(-1.0), ux, Float32(2.0)) * ux)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;uy \leq 0.07000000029802322:\\
\;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}\\

\mathbf{else}:\\
\;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if uy < 0.0700000003

    1. Initial program 57.6%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      2. lower-*.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      3. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
      4. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      7. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      8. lower-neg.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      10. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      11. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3299.3

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. Applied rewrites99.3%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
    5. Taylor expanded in maxCos around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. lower--.f3299.3

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. Applied rewrites99.3%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. Taylor expanded in uy around 0

      \[\leadsto \color{blue}{\left(1 + {uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    9. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \left({uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) + \color{blue}{1}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \left(\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) \cdot {uy}^{2} + 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right), \color{blue}{{uy}^{2}}, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    10. Applied rewrites98.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), {\pi}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    11. Step-by-step derivation
      1. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. lift-pow.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. sqr-powN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      6. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      7. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      8. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      9. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      10. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      11. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      13. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      14. lift-PI.f3298.9

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. Applied rewrites98.9%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]

    if 0.0700000003 < uy

    1. Initial program 58.3%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      2. lower-*.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      3. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
      4. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      7. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      8. lower-neg.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      10. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      11. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3296.3

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. Applied rewrites96.3%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
    5. Taylor expanded in maxCos around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(2 + -1 \cdot ux\right) \cdot ux} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(-1 \cdot ux + 2\right) \cdot ux} \]
      2. lower-fma.f3290.8

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
    7. Applied rewrites90.8%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 7: 95.5% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 0.07999999821186066:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\sin \left(\mathsf{fma}\left(0.5, \pi, \left(\pi \cdot uy\right) \cdot 2\right)\right) \cdot \sqrt{2 \cdot ux}\\ \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (if (<= uy 0.07999999821186066)
   (*
    (fma
     (fma
      (* 0.6666666666666666 (* uy uy))
      (* (* PI PI) (* PI PI))
      (* (* PI PI) -2.0))
     (* uy uy)
     1.0)
    (sqrt
     (*
      (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
      ux)))
   (* (sin (fma 0.5 PI (* (* PI uy) 2.0))) (sqrt (* 2.0 ux)))))
float code(float ux, float uy, float maxCos) {
	float tmp;
	if (uy <= 0.07999999821186066f) {
		tmp = fmaf(fmaf((0.6666666666666666f * (uy * uy)), ((((float) M_PI) * ((float) M_PI)) * (((float) M_PI) * ((float) M_PI))), ((((float) M_PI) * ((float) M_PI)) * -2.0f)), (uy * uy), 1.0f) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
	} else {
		tmp = sinf(fmaf(0.5f, ((float) M_PI), ((((float) M_PI) * uy) * 2.0f))) * sqrtf((2.0f * ux));
	}
	return tmp;
}
function code(ux, uy, maxCos)
	tmp = Float32(0.0)
	if (uy <= Float32(0.07999999821186066))
		tmp = Float32(fma(fma(Float32(Float32(0.6666666666666666) * Float32(uy * uy)), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(Float32(pi) * Float32(pi))), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(-2.0))), Float32(uy * uy), Float32(1.0)) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)));
	else
		tmp = Float32(sin(fma(Float32(0.5), Float32(pi), Float32(Float32(Float32(pi) * uy) * Float32(2.0)))) * sqrt(Float32(Float32(2.0) * ux)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;uy \leq 0.07999999821186066:\\
\;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}\\

\mathbf{else}:\\
\;\;\;\;\sin \left(\mathsf{fma}\left(0.5, \pi, \left(\pi \cdot uy\right) \cdot 2\right)\right) \cdot \sqrt{2 \cdot ux}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if uy < 0.0799999982

    1. Initial program 57.6%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      2. lower-*.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      3. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
      4. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      7. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      8. lower-neg.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      10. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      11. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3299.3

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. Applied rewrites99.3%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
    5. Taylor expanded in maxCos around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. lower--.f3299.3

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. Applied rewrites99.3%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. Taylor expanded in uy around 0

      \[\leadsto \color{blue}{\left(1 + {uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    9. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \left({uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) + \color{blue}{1}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \left(\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) \cdot {uy}^{2} + 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right), \color{blue}{{uy}^{2}}, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    10. Applied rewrites98.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), {\pi}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    11. Step-by-step derivation
      1. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. lift-pow.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. sqr-powN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      6. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      7. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      8. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      9. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      10. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      11. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      13. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      14. lift-PI.f3298.7

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. Applied rewrites98.7%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]

    if 0.0799999982 < uy

    1. Initial program 58.3%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Step-by-step derivation
      1. lift-cos.f32N/A

        \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      2. lift-*.f32N/A

        \[\leadsto \cos \left(\color{blue}{\left(uy \cdot 2\right)} \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      3. lift-PI.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      4. lift-*.f32N/A

        \[\leadsto \cos \color{blue}{\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      5. sin-+PI/2-revN/A

        \[\leadsto \color{blue}{\sin \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      6. lower-sin.f32N/A

        \[\leadsto \color{blue}{\sin \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      7. *-commutativeN/A

        \[\leadsto \sin \left(\color{blue}{\left(2 \cdot uy\right)} \cdot \mathsf{PI}\left(\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      8. associate-*r*N/A

        \[\leadsto \sin \left(\color{blue}{2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      9. *-commutativeN/A

        \[\leadsto \sin \left(\color{blue}{\left(uy \cdot \mathsf{PI}\left(\right)\right) \cdot 2} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      10. lower-fma.f32N/A

        \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(uy \cdot \mathsf{PI}\left(\right), 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      11. *-commutativeN/A

        \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{\mathsf{PI}\left(\right) \cdot uy}, 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      12. lower-*.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{\mathsf{PI}\left(\right) \cdot uy}, 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      13. lift-PI.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{\pi} \cdot uy, 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      14. lower-/.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(\pi \cdot uy, 2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      15. lift-PI.f3258.1

        \[\leadsto \sin \left(\mathsf{fma}\left(\pi \cdot uy, 2, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    3. Applied rewrites58.1%

      \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(\pi \cdot uy, 2, \frac{\pi}{2}\right)\right)} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    4. Taylor expanded in ux around 0

      \[\leadsto \color{blue}{\sqrt{ux \cdot \left(2 - 2 \cdot maxCos\right)} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)} \]
    5. Step-by-step derivation
      1. sin-+PI/2N/A

        \[\leadsto \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \]
      2. associate-*l*N/A

        \[\leadsto \sqrt{\color{blue}{ux} \cdot \left(2 - 2 \cdot maxCos\right)} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \]
      3. lift-*.f32N/A

        \[\leadsto \sqrt{ux \cdot \left(2 - 2 \cdot maxCos\right)} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\color{blue}{ux} \cdot \left(2 - 2 \cdot maxCos\right)} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \]
      5. lift-*.f32N/A

        \[\leadsto \sqrt{ux \cdot \left(2 - 2 \cdot maxCos\right)} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \]
      6. *-commutativeN/A

        \[\leadsto \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \color{blue}{\sqrt{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
      7. lower-*.f32N/A

        \[\leadsto \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + 2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \color{blue}{\sqrt{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
    6. Applied rewrites74.3%

      \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(0.5, \pi, \left(\pi \cdot uy\right) \cdot 2\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]
    7. Taylor expanded in maxCos around 0

      \[\leadsto \sin \left(\mathsf{fma}\left(\frac{1}{2}, \pi, \left(\pi \cdot uy\right) \cdot 2\right)\right) \cdot \sqrt{2 \cdot ux} \]
    8. Step-by-step derivation
      1. Applied rewrites71.4%

        \[\leadsto \sin \left(\mathsf{fma}\left(0.5, \pi, \left(\pi \cdot uy\right) \cdot 2\right)\right) \cdot \sqrt{2 \cdot ux} \]
    9. Recombined 2 regimes into one program.
    10. Add Preprocessing

    Alternative 8: 91.4% accurate, 1.6× speedup?

    \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (*
      (fma
       (fma
        (* 0.6666666666666666 (* uy uy))
        (* (* PI PI) (* PI PI))
        (* (* PI PI) -2.0))
       (* uy uy)
       1.0)
      (sqrt
       (*
        (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
        ux))))
    float code(float ux, float uy, float maxCos) {
    	return fmaf(fmaf((0.6666666666666666f * (uy * uy)), ((((float) M_PI) * ((float) M_PI)) * (((float) M_PI) * ((float) M_PI))), ((((float) M_PI) * ((float) M_PI)) * -2.0f)), (uy * uy), 1.0f) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
    }
    
    function code(ux, uy, maxCos)
    	return Float32(fma(fma(Float32(Float32(0.6666666666666666) * Float32(uy * uy)), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(Float32(pi) * Float32(pi))), Float32(Float32(Float32(pi) * Float32(pi)) * Float32(-2.0))), Float32(uy * uy), Float32(1.0)) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
    end
    
    \begin{array}{l}
    
    \\
    \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
    \end{array}
    
    Derivation
    1. Initial program 57.7%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      2. lower-*.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      3. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
      4. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      7. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      8. lower-neg.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      10. lower--.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      11. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3298.9

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    4. Applied rewrites98.9%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
    5. Taylor expanded in maxCos around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. lower--.f3298.9

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. Applied rewrites98.9%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. Taylor expanded in uy around 0

      \[\leadsto \color{blue}{\left(1 + {uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    9. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \left({uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) + \color{blue}{1}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. *-commutativeN/A

        \[\leadsto \left(\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) \cdot {uy}^{2} + 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right), \color{blue}{{uy}^{2}}, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    10. Applied rewrites91.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), {\pi}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    11. Step-by-step derivation
      1. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. lift-pow.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      3. sqr-powN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      4. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{4}{2}\right)}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      6. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      7. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      8. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      9. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \mathsf{PI}\left(\right)\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      10. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot {\mathsf{PI}\left(\right)}^{2}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      11. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      13. lift-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{2}{3} \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \mathsf{PI}\left(\right)\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      14. lift-PI.f3291.4

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. Applied rewrites91.4%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), \left(\pi \cdot \pi\right) \cdot \left(\pi \cdot \pi\right), \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    13. Add Preprocessing

    Alternative 9: 73.7% accurate, 2.2× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;t\_0 \cdot t\_0 \leq 0.9995999932289124:\\ \;\;\;\;1 \cdot \sqrt{1 - t\_0 \cdot \left(1 - ux\right)}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\ \end{array} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
       (if (<= (* t_0 t_0) 0.9995999932289124)
         (* 1.0 (sqrt (- 1.0 (* t_0 (- 1.0 ux)))))
         (* 1.0 (sqrt (* ux (fma -2.0 maxCos 2.0)))))))
    float code(float ux, float uy, float maxCos) {
    	float t_0 = (1.0f - ux) + (ux * maxCos);
    	float tmp;
    	if ((t_0 * t_0) <= 0.9995999932289124f) {
    		tmp = 1.0f * sqrtf((1.0f - (t_0 * (1.0f - ux))));
    	} else {
    		tmp = 1.0f * sqrtf((ux * fmaf(-2.0f, maxCos, 2.0f)));
    	}
    	return tmp;
    }
    
    function code(ux, uy, maxCos)
    	t_0 = Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))
    	tmp = Float32(0.0)
    	if (Float32(t_0 * t_0) <= Float32(0.9995999932289124))
    		tmp = Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(t_0 * Float32(Float32(1.0) - ux)))));
    	else
    		tmp = Float32(Float32(1.0) * sqrt(Float32(ux * fma(Float32(-2.0), maxCos, Float32(2.0)))));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
    \mathbf{if}\;t\_0 \cdot t\_0 \leq 0.9995999932289124:\\
    \;\;\;\;1 \cdot \sqrt{1 - t\_0 \cdot \left(1 - ux\right)}\\
    
    \mathbf{else}:\\
    \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))) < 0.999599993

      1. Initial program 89.8%

        \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      2. Taylor expanded in uy around 0

        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      3. Step-by-step derivation
        1. Applied rewrites73.6%

          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Taylor expanded in maxCos around 0

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(1 - ux\right)}} \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)} \]
          2. +-commutativeN/A

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{1} - ux\right)} \]
          3. lift--.f3270.5

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - \color{blue}{ux}\right)} \]
        4. Applied rewrites70.5%

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(1 - ux\right)}} \]

        if 0.999599993 < (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))

        1. Initial program 37.4%

          \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Taylor expanded in uy around 0

          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        3. Step-by-step derivation
          1. Applied rewrites34.2%

            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          2. Taylor expanded in ux around inf

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)}} \]
          3. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
            2. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{ux} \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
            3. *-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
            4. lower-*.f32N/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
            5. lower--.f32N/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot ux\right)} \]
            6. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
            7. lower-+.f32N/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
            8. lower-/.f3235.3

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
          4. Applied rewrites35.3%

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}} \]
          5. Taylor expanded in ux around 0

            \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
          6. Step-by-step derivation
            1. metadata-evalN/A

              \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
            2. fp-cancel-sign-sub-invN/A

              \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
            3. lower-*.f32N/A

              \[\leadsto 1 \cdot \sqrt{ux \cdot \color{blue}{\left(2 + -2 \cdot maxCos\right)}} \]
            4. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{ux \cdot \left(-2 \cdot maxCos + \color{blue}{2}\right)} \]
            5. lift-fma.f3275.7

              \[\leadsto 1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, \color{blue}{maxCos}, 2\right)} \]
          7. Applied rewrites75.7%

            \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}} \]
        4. Recombined 2 regimes into one program.
        5. Add Preprocessing

        Alternative 10: 88.1% accurate, 2.3× speedup?

        \[\begin{array}{l} \\ \mathsf{fma}\left(-2 \cdot \left(\pi \cdot \pi\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
        (FPCore (ux uy maxCos)
         :precision binary32
         (*
          (fma (* -2.0 (* PI PI)) (* uy uy) 1.0)
          (sqrt
           (*
            (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
            ux))))
        float code(float ux, float uy, float maxCos) {
        	return fmaf((-2.0f * (((float) M_PI) * ((float) M_PI))), (uy * uy), 1.0f) * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
        }
        
        function code(ux, uy, maxCos)
        	return Float32(fma(Float32(Float32(-2.0) * Float32(Float32(pi) * Float32(pi))), Float32(uy * uy), Float32(1.0)) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
        end
        
        \begin{array}{l}
        
        \\
        \mathsf{fma}\left(-2 \cdot \left(\pi \cdot \pi\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
        \end{array}
        
        Derivation
        1. Initial program 57.7%

          \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Taylor expanded in ux around 0

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
          2. lower-*.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
          3. lower--.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
          4. +-commutativeN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          5. associate-*r*N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          6. mul-1-negN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          7. lower-fma.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          8. lower-neg.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          9. lower-pow.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          10. lower--.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
          11. *-commutativeN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          12. lower-*.f3298.9

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        4. Applied rewrites98.9%

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
        5. Taylor expanded in maxCos around 0

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        6. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          2. *-commutativeN/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          3. lower-fma.f32N/A

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          4. lower--.f3298.9

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        7. Applied rewrites98.9%

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        8. Taylor expanded in uy around 0

          \[\leadsto \color{blue}{\left(1 + {uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        9. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \left({uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) + \color{blue}{1}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          2. *-commutativeN/A

            \[\leadsto \left(\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) \cdot {uy}^{2} + 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          3. lower-fma.f32N/A

            \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right), \color{blue}{{uy}^{2}}, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        10. Applied rewrites91.4%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), {\pi}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        11. Taylor expanded in uy around 0

          \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}, \color{blue}{uy} \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        12. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}, uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          2. pow2N/A

            \[\leadsto \mathsf{fma}\left(-2 \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          3. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(-2 \cdot \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          4. lift-PI.f32N/A

            \[\leadsto \mathsf{fma}\left(-2 \cdot \left(\pi \cdot \mathsf{PI}\left(\right)\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
          5. lift-PI.f3288.1

            \[\leadsto \mathsf{fma}\left(-2 \cdot \left(\pi \cdot \pi\right), uy \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        13. Applied rewrites88.1%

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(\pi \cdot \pi\right), \color{blue}{uy} \cdot uy, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        14. Add Preprocessing

        Alternative 11: 74.9% accurate, 3.1× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;ux \leq 9.999999747378752 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \mathsf{fma}\left(maxCos - 1, ux, 1\right)}\\ \end{array} \end{array} \]
        (FPCore (ux uy maxCos)
         :precision binary32
         (if (<= ux 9.999999747378752e-5)
           (* 1.0 (sqrt (* ux (fma -2.0 maxCos 2.0))))
           (*
            1.0
            (sqrt
             (- 1.0 (* (+ (- 1.0 ux) (* ux maxCos)) (fma (- maxCos 1.0) ux 1.0)))))))
        float code(float ux, float uy, float maxCos) {
        	float tmp;
        	if (ux <= 9.999999747378752e-5f) {
        		tmp = 1.0f * sqrtf((ux * fmaf(-2.0f, maxCos, 2.0f)));
        	} else {
        		tmp = 1.0f * sqrtf((1.0f - (((1.0f - ux) + (ux * maxCos)) * fmaf((maxCos - 1.0f), ux, 1.0f))));
        	}
        	return tmp;
        }
        
        function code(ux, uy, maxCos)
        	tmp = Float32(0.0)
        	if (ux <= Float32(9.999999747378752e-5))
        		tmp = Float32(Float32(1.0) * sqrt(Float32(ux * fma(Float32(-2.0), maxCos, Float32(2.0)))));
        	else
        		tmp = Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos)) * fma(Float32(maxCos - Float32(1.0)), ux, Float32(1.0))))));
        	end
        	return tmp
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;ux \leq 9.999999747378752 \cdot 10^{-5}:\\
        \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\
        
        \mathbf{else}:\\
        \;\;\;\;1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \mathsf{fma}\left(maxCos - 1, ux, 1\right)}\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if ux < 9.99999975e-5

          1. Initial program 35.8%

            \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          2. Taylor expanded in uy around 0

            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          3. Step-by-step derivation
            1. Applied rewrites32.8%

              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            2. Taylor expanded in ux around inf

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)}} \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
              2. +-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{ux} \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
              3. *-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
              4. lower-*.f32N/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
              5. lower--.f32N/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot ux\right)} \]
              6. +-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
              7. lower-+.f32N/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
              8. lower-/.f3233.9

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
            4. Applied rewrites33.9%

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}} \]
            5. Taylor expanded in ux around 0

              \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
            6. Step-by-step derivation
              1. metadata-evalN/A

                \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
              2. fp-cancel-sign-sub-invN/A

                \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
              3. lower-*.f32N/A

                \[\leadsto 1 \cdot \sqrt{ux \cdot \color{blue}{\left(2 + -2 \cdot maxCos\right)}} \]
              4. +-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{ux \cdot \left(-2 \cdot maxCos + \color{blue}{2}\right)} \]
              5. lift-fma.f3276.2

                \[\leadsto 1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, \color{blue}{maxCos}, 2\right)} \]
            7. Applied rewrites76.2%

              \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}} \]

            if 9.99999975e-5 < ux

            1. Initial program 88.6%

              \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            2. Taylor expanded in uy around 0

              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            3. Step-by-step derivation
              1. Applied rewrites73.0%

                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Taylor expanded in ux around 0

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(1 + ux \cdot \left(maxCos - 1\right)\right)}} \]
              3. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 + ux \cdot \left(maxCos - 1\right)\right)} \]
                2. +-commutativeN/A

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{1} + ux \cdot \left(maxCos - 1\right)\right)} \]
                3. +-commutativeN/A

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot \left(maxCos - 1\right) + \color{blue}{1}\right)} \]
                4. *-commutativeN/A

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(maxCos - 1\right) \cdot ux + 1\right)} \]
                5. lower-fma.f32N/A

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \mathsf{fma}\left(maxCos - 1, \color{blue}{ux}, 1\right)} \]
                6. lift--.f3273.1

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \mathsf{fma}\left(maxCos - 1, ux, 1\right)} \]
              4. Applied rewrites73.1%

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\mathsf{fma}\left(maxCos - 1, ux, 1\right)}} \]
            4. Recombined 2 regimes into one program.
            5. Add Preprocessing

            Alternative 12: 74.8% accurate, 3.2× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\ \mathbf{if}\;ux \leq 9.999999747378752 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{1 - t\_0 \cdot t\_0}\\ \end{array} \end{array} \]
            (FPCore (ux uy maxCos)
             :precision binary32
             (let* ((t_0 (fma maxCos ux (- 1.0 ux))))
               (if (<= ux 9.999999747378752e-5)
                 (* 1.0 (sqrt (* ux (fma -2.0 maxCos 2.0))))
                 (* 1.0 (sqrt (- 1.0 (* t_0 t_0)))))))
            float code(float ux, float uy, float maxCos) {
            	float t_0 = fmaf(maxCos, ux, (1.0f - ux));
            	float tmp;
            	if (ux <= 9.999999747378752e-5f) {
            		tmp = 1.0f * sqrtf((ux * fmaf(-2.0f, maxCos, 2.0f)));
            	} else {
            		tmp = 1.0f * sqrtf((1.0f - (t_0 * t_0)));
            	}
            	return tmp;
            }
            
            function code(ux, uy, maxCos)
            	t_0 = fma(maxCos, ux, Float32(Float32(1.0) - ux))
            	tmp = Float32(0.0)
            	if (ux <= Float32(9.999999747378752e-5))
            		tmp = Float32(Float32(1.0) * sqrt(Float32(ux * fma(Float32(-2.0), maxCos, Float32(2.0)))));
            	else
            		tmp = Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0))));
            	end
            	return tmp
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\
            \mathbf{if}\;ux \leq 9.999999747378752 \cdot 10^{-5}:\\
            \;\;\;\;1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}\\
            
            \mathbf{else}:\\
            \;\;\;\;1 \cdot \sqrt{1 - t\_0 \cdot t\_0}\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if ux < 9.99999975e-5

              1. Initial program 35.8%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Taylor expanded in uy around 0

                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              3. Step-by-step derivation
                1. Applied rewrites32.8%

                  \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Taylor expanded in ux around inf

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)}} \]
                3. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
                  2. +-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{ux} \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
                  3. *-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
                  4. lower-*.f32N/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
                  5. lower--.f32N/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot ux\right)} \]
                  6. +-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                  7. lower-+.f32N/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                  8. lower-/.f3233.9

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                4. Applied rewrites33.9%

                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}} \]
                5. Taylor expanded in ux around 0

                  \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
                6. Step-by-step derivation
                  1. metadata-evalN/A

                    \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
                  2. fp-cancel-sign-sub-invN/A

                    \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
                  3. lower-*.f32N/A

                    \[\leadsto 1 \cdot \sqrt{ux \cdot \color{blue}{\left(2 + -2 \cdot maxCos\right)}} \]
                  4. +-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{ux \cdot \left(-2 \cdot maxCos + \color{blue}{2}\right)} \]
                  5. lift-fma.f3276.2

                    \[\leadsto 1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, \color{blue}{maxCos}, 2\right)} \]
                7. Applied rewrites76.2%

                  \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}} \]

                if 9.99999975e-5 < ux

                1. Initial program 88.6%

                  \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Taylor expanded in uy around 0

                  \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                3. Step-by-step derivation
                  1. Applied rewrites73.0%

                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  2. Step-by-step derivation
                    1. lift-+.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. lift--.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{\left(1 - ux\right)} + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    3. +-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    4. lift-*.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    5. *-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    6. lift-+.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \left(1 - ux\right)\right) \cdot \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                    7. lift--.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \left(1 - ux\right)\right) \cdot \left(\color{blue}{\left(1 - ux\right)} + ux \cdot maxCos\right)} \]
                    8. +-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \left(1 - ux\right)\right) \cdot \color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}} \]
                    9. lift-*.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \left(1 - ux\right)\right) \cdot \left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right)} \]
                    10. *-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \left(1 - ux\right)\right) \cdot \left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right)} \]
                    11. lift-fma.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(maxCos \cdot ux + \left(1 - ux\right)\right)} \]
                    12. lift--.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, \color{blue}{1 - ux}\right) \cdot \left(maxCos \cdot ux + \left(1 - ux\right)\right)} \]
                    13. lift-fma.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}} \]
                    14. lift--.f3273.0

                      \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, \color{blue}{1 - ux}\right)} \]
                  3. Applied rewrites73.0%

                    \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)}} \]
                4. Recombined 2 regimes into one program.
                5. Add Preprocessing

                Alternative 13: 79.7% accurate, 3.4× speedup?

                \[\begin{array}{l} \\ 1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \end{array} \]
                (FPCore (ux uy maxCos)
                 :precision binary32
                 (*
                  1.0
                  (sqrt
                   (*
                    (- (fma (- ux) (fma (- maxCos 2.0) maxCos 1.0) 2.0) (* maxCos 2.0))
                    ux))))
                float code(float ux, float uy, float maxCos) {
                	return 1.0f * sqrtf(((fmaf(-ux, fmaf((maxCos - 2.0f), maxCos, 1.0f), 2.0f) - (maxCos * 2.0f)) * ux));
                }
                
                function code(ux, uy, maxCos)
                	return Float32(Float32(1.0) * sqrt(Float32(Float32(fma(Float32(-ux), fma(Float32(maxCos - Float32(2.0)), maxCos, Float32(1.0)), Float32(2.0)) - Float32(maxCos * Float32(2.0))) * ux)))
                end
                
                \begin{array}{l}
                
                \\
                1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
                \end{array}
                
                Derivation
                1. Initial program 57.7%

                  \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Taylor expanded in ux around 0

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                3. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                  2. lower-*.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                  3. lower--.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  4. +-commutativeN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  5. associate-*r*N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  6. mul-1-negN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\left(\left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  7. lower-fma.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{neg}\left(ux\right), {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  8. lower-neg.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  9. lower-pow.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  10. lower--.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
                  11. *-commutativeN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  12. lower-*.f3298.9

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                4. Applied rewrites98.9%

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}} \]
                5. Taylor expanded in maxCos around 0

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, 1 + maxCos \cdot \left(maxCos - 2\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                6. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, maxCos \cdot \left(maxCos - 2\right) + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  2. *-commutativeN/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 2\right) \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  3. lower-fma.f32N/A

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  4. lower--.f3298.9

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                7. Applied rewrites98.9%

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                8. Taylor expanded in uy around 0

                  \[\leadsto \color{blue}{\left(1 + {uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right)\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                9. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto \left({uy}^{2} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) + \color{blue}{1}\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  2. *-commutativeN/A

                    \[\leadsto \left(\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right)\right) \cdot {uy}^{2} + 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  3. lower-fma.f32N/A

                    \[\leadsto \mathsf{fma}\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2} + \frac{2}{3} \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{4}\right), \color{blue}{{uy}^{2}}, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                10. Applied rewrites91.4%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.6666666666666666 \cdot \left(uy \cdot uy\right), {\pi}^{4}, \left(\pi \cdot \pi\right) \cdot -2\right), uy \cdot uy, 1\right)} \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                11. Taylor expanded in uy around 0

                  \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                12. Step-by-step derivation
                  1. Applied rewrites79.7%

                    \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(maxCos - 2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
                  2. Add Preprocessing

                  Alternative 14: 64.3% accurate, 5.8× speedup?

                  \[\begin{array}{l} \\ 1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)} \end{array} \]
                  (FPCore (ux uy maxCos)
                   :precision binary32
                   (* 1.0 (sqrt (* ux (fma -2.0 maxCos 2.0)))))
                  float code(float ux, float uy, float maxCos) {
                  	return 1.0f * sqrtf((ux * fmaf(-2.0f, maxCos, 2.0f)));
                  }
                  
                  function code(ux, uy, maxCos)
                  	return Float32(Float32(1.0) * sqrt(Float32(ux * fma(Float32(-2.0), maxCos, Float32(2.0)))))
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}
                  \end{array}
                  
                  Derivation
                  1. Initial program 57.7%

                    \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  2. Taylor expanded in uy around 0

                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  3. Step-by-step derivation
                    1. Applied rewrites49.5%

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Taylor expanded in ux around inf

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)}} \]
                    3. Step-by-step derivation
                      1. *-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
                      2. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{ux} \cdot \left(\left(maxCos + \frac{1}{ux}\right) - 1\right)\right)} \]
                      3. *-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
                      4. lower-*.f32N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot \color{blue}{ux}\right)} \]
                      5. lower--.f32N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(maxCos + \frac{1}{ux}\right) - 1\right) \cdot ux\right)} \]
                      6. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                      7. lower-+.f32N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                      8. lower-/.f3250.1

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
                    4. Applied rewrites50.1%

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}} \]
                    5. Taylor expanded in ux around 0

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
                    6. Step-by-step derivation
                      1. metadata-evalN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
                      2. fp-cancel-sign-sub-invN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
                      3. lower-*.f32N/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \color{blue}{\left(2 + -2 \cdot maxCos\right)}} \]
                      4. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(-2 \cdot maxCos + \color{blue}{2}\right)} \]
                      5. lift-fma.f3264.3

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \mathsf{fma}\left(-2, \color{blue}{maxCos}, 2\right)} \]
                    7. Applied rewrites64.3%

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \mathsf{fma}\left(-2, maxCos, 2\right)}} \]
                    8. Add Preprocessing

                    Alternative 15: 39.9% accurate, 6.2× speedup?

                    \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \end{array} \]
                    (FPCore (ux uy maxCos)
                     :precision binary32
                     (* 1.0 (sqrt (- 1.0 (fma -2.0 ux 1.0)))))
                    float code(float ux, float uy, float maxCos) {
                    	return 1.0f * sqrtf((1.0f - fmaf(-2.0f, ux, 1.0f)));
                    }
                    
                    function code(ux, uy, maxCos)
                    	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - fma(Float32(-2.0), ux, Float32(1.0)))))
                    end
                    
                    \begin{array}{l}
                    
                    \\
                    1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)}
                    \end{array}
                    
                    Derivation
                    1. Initial program 57.7%

                      \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Taylor expanded in uy around 0

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    3. Step-by-step derivation
                      1. Applied rewrites49.5%

                        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                      2. Taylor expanded in ux around 0

                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)}} \]
                      3. Step-by-step derivation
                        1. pow2N/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{1} + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        2. *-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        3. +-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        4. pow2N/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{1} + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        5. +-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(ux \cdot \left(2 \cdot maxCos - 2\right) + \color{blue}{1}\right)} \]
                        6. *-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(2 \cdot maxCos - 2\right) \cdot ux + 1\right)} \]
                        7. lower-fma.f32N/A

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(2 \cdot maxCos - 2, \color{blue}{ux}, 1\right)} \]
                        8. lower--.f32N/A

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(2 \cdot maxCos - 2, ux, 1\right)} \]
                        9. *-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                        10. lift-*.f3240.6

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                      4. Applied rewrites40.6%

                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)}} \]
                      5. Taylor expanded in maxCos around 0

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \]
                      6. Step-by-step derivation
                        1. Applied rewrites39.9%

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \]
                        2. Add Preprocessing

                        Alternative 16: 6.6% accurate, 8.2× speedup?

                        \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - 1} \end{array} \]
                        (FPCore (ux uy maxCos) :precision binary32 (* 1.0 (sqrt (- 1.0 1.0))))
                        float code(float ux, float uy, float maxCos) {
                        	return 1.0f * sqrtf((1.0f - 1.0f));
                        }
                        
                        module fmin_fmax_functions
                            implicit none
                            private
                            public fmax
                            public fmin
                        
                            interface fmax
                                module procedure fmax88
                                module procedure fmax44
                                module procedure fmax84
                                module procedure fmax48
                            end interface
                            interface fmin
                                module procedure fmin88
                                module procedure fmin44
                                module procedure fmin84
                                module procedure fmin48
                            end interface
                        contains
                            real(8) function fmax88(x, y) result (res)
                                real(8), intent (in) :: x
                                real(8), intent (in) :: y
                                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                            end function
                            real(4) function fmax44(x, y) result (res)
                                real(4), intent (in) :: x
                                real(4), intent (in) :: y
                                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                            end function
                            real(8) function fmax84(x, y) result(res)
                                real(8), intent (in) :: x
                                real(4), intent (in) :: y
                                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                            end function
                            real(8) function fmax48(x, y) result(res)
                                real(4), intent (in) :: x
                                real(8), intent (in) :: y
                                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                            end function
                            real(8) function fmin88(x, y) result (res)
                                real(8), intent (in) :: x
                                real(8), intent (in) :: y
                                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                            end function
                            real(4) function fmin44(x, y) result (res)
                                real(4), intent (in) :: x
                                real(4), intent (in) :: y
                                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                            end function
                            real(8) function fmin84(x, y) result(res)
                                real(8), intent (in) :: x
                                real(4), intent (in) :: y
                                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                            end function
                            real(8) function fmin48(x, y) result(res)
                                real(4), intent (in) :: x
                                real(8), intent (in) :: y
                                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                            end function
                        end module
                        
                        real(4) function code(ux, uy, maxcos)
                        use fmin_fmax_functions
                            real(4), intent (in) :: ux
                            real(4), intent (in) :: uy
                            real(4), intent (in) :: maxcos
                            code = 1.0e0 * sqrt((1.0e0 - 1.0e0))
                        end function
                        
                        function code(ux, uy, maxCos)
                        	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(1.0))))
                        end
                        
                        function tmp = code(ux, uy, maxCos)
                        	tmp = single(1.0) * sqrt((single(1.0) - single(1.0)));
                        end
                        
                        \begin{array}{l}
                        
                        \\
                        1 \cdot \sqrt{1 - 1}
                        \end{array}
                        
                        Derivation
                        1. Initial program 57.7%

                          \[\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                        2. Taylor expanded in uy around 0

                          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                        3. Step-by-step derivation
                          1. Applied rewrites49.5%

                            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                          2. Taylor expanded in ux around 0

                            \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                          3. Step-by-step derivation
                            1. pow26.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            2. *-commutative6.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            3. +-commutative6.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            4. pow26.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                          4. Applied rewrites6.6%

                            \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                          5. Add Preprocessing

                          Reproduce

                          ?
                          herbie shell --seed 2025093 
                          (FPCore (ux uy maxCos)
                            :name "UniformSampleCone, x"
                            :precision binary32
                            :pre (and (and (and (<= 2.328306437e-10 ux) (<= ux 1.0)) (and (<= 2.328306437e-10 uy) (<= uy 1.0))) (and (<= 0.0 maxCos) (<= maxCos 1.0)))
                            (* (cos (* (* uy 2.0) PI)) (sqrt (- 1.0 (* (+ (- 1.0 ux) (* ux maxCos)) (+ (- 1.0 ux) (* ux maxCos)))))))