UniformSampleCone 2

Percentage Accurate: 98.9% → 99.0%
Time: 11.1s
Alternatives: 19
Speedup: 1.0×

Specification

?
\[\left(\left(\left(\left(\left(-10000 \leq xi \land xi \leq 10000\right) \land \left(-10000 \leq yi \land yi \leq 10000\right)\right) \land \left(-10000 \leq zi \land zi \leq 10000\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq ux \land ux \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq uy \land uy \leq 1\right)\right) \land \left(0 \leq maxCos \land maxCos \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\ t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\ t_2 := \left(uy \cdot 2\right) \cdot \pi\\ \left(\left(\cos t\_2 \cdot t\_1\right) \cdot xi + \left(\sin t\_2 \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* (* (- 1.0 ux) maxCos) ux))
        (t_1 (sqrt (- 1.0 (* t_0 t_0))))
        (t_2 (* (* uy 2.0) PI)))
   (+ (+ (* (* (cos t_2) t_1) xi) (* (* (sin t_2) t_1) yi)) (* t_0 zi))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((1.0f - ux) * maxCos) * ux;
	float t_1 = sqrtf((1.0f - (t_0 * t_0)));
	float t_2 = (uy * 2.0f) * ((float) M_PI);
	return (((cosf(t_2) * t_1) * xi) + ((sinf(t_2) * t_1) * yi)) + (t_0 * zi);
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(Float32(Float32(1.0) - ux) * maxCos) * ux)
	t_1 = sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0)))
	t_2 = Float32(Float32(uy * Float32(2.0)) * Float32(pi))
	return Float32(Float32(Float32(Float32(cos(t_2) * t_1) * xi) + Float32(Float32(sin(t_2) * t_1) * yi)) + Float32(t_0 * zi))
end
function tmp = code(xi, yi, zi, ux, uy, maxCos)
	t_0 = ((single(1.0) - ux) * maxCos) * ux;
	t_1 = sqrt((single(1.0) - (t_0 * t_0)));
	t_2 = (uy * single(2.0)) * single(pi);
	tmp = (((cos(t_2) * t_1) * xi) + ((sin(t_2) * t_1) * yi)) + (t_0 * zi);
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\
t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\
t_2 := \left(uy \cdot 2\right) \cdot \pi\\
\left(\left(\cos t\_2 \cdot t\_1\right) \cdot xi + \left(\sin t\_2 \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi
\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 19 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: 98.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\ t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\ t_2 := \left(uy \cdot 2\right) \cdot \pi\\ \left(\left(\cos t\_2 \cdot t\_1\right) \cdot xi + \left(\sin t\_2 \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* (* (- 1.0 ux) maxCos) ux))
        (t_1 (sqrt (- 1.0 (* t_0 t_0))))
        (t_2 (* (* uy 2.0) PI)))
   (+ (+ (* (* (cos t_2) t_1) xi) (* (* (sin t_2) t_1) yi)) (* t_0 zi))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((1.0f - ux) * maxCos) * ux;
	float t_1 = sqrtf((1.0f - (t_0 * t_0)));
	float t_2 = (uy * 2.0f) * ((float) M_PI);
	return (((cosf(t_2) * t_1) * xi) + ((sinf(t_2) * t_1) * yi)) + (t_0 * zi);
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(Float32(Float32(1.0) - ux) * maxCos) * ux)
	t_1 = sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0)))
	t_2 = Float32(Float32(uy * Float32(2.0)) * Float32(pi))
	return Float32(Float32(Float32(Float32(cos(t_2) * t_1) * xi) + Float32(Float32(sin(t_2) * t_1) * yi)) + Float32(t_0 * zi))
end
function tmp = code(xi, yi, zi, ux, uy, maxCos)
	t_0 = ((single(1.0) - ux) * maxCos) * ux;
	t_1 = sqrt((single(1.0) - (t_0 * t_0)));
	t_2 = (uy * single(2.0)) * single(pi);
	tmp = (((cos(t_2) * t_1) * xi) + ((sin(t_2) * t_1) * yi)) + (t_0 * zi);
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\
t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\
t_2 := \left(uy \cdot 2\right) \cdot \pi\\
\left(\left(\cos t\_2 \cdot t\_1\right) \cdot xi + \left(\sin t\_2 \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi
\end{array}
\end{array}

Alternative 1: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\ t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\ \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right) \cdot t\_1\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* (* (- 1.0 ux) maxCos) ux)) (t_1 (sqrt (- 1.0 (* t_0 t_0)))))
   (+
    (+
     (* (* (sin (fma (- uy) (+ PI PI) (* PI 0.5))) t_1) xi)
     (* (* (sin (* (* uy 2.0) PI)) t_1) yi))
    (* t_0 zi))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((1.0f - ux) * maxCos) * ux;
	float t_1 = sqrtf((1.0f - (t_0 * t_0)));
	return (((sinf(fmaf(-uy, (((float) M_PI) + ((float) M_PI)), (((float) M_PI) * 0.5f))) * t_1) * xi) + ((sinf(((uy * 2.0f) * ((float) M_PI))) * t_1) * yi)) + (t_0 * zi);
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(Float32(Float32(1.0) - ux) * maxCos) * ux)
	t_1 = sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0)))
	return Float32(Float32(Float32(Float32(sin(fma(Float32(-uy), Float32(Float32(pi) + Float32(pi)), Float32(Float32(pi) * Float32(0.5)))) * t_1) * xi) + Float32(Float32(sin(Float32(Float32(uy * Float32(2.0)) * Float32(pi))) * t_1) * yi)) + Float32(t_0 * zi))
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\\
t_1 := \sqrt{1 - t\_0 \cdot t\_0}\\
\left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right) \cdot t\_1\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot t\_1\right) \cdot yi\right) + t\_0 \cdot zi
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

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

      \[\leadsto \left(\left(\color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
    2. cos-neg-revN/A

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

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

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

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

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

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

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

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

      \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \pi, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
    11. count-2-revN/A

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

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

      \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
    14. mult-flipN/A

      \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot \frac{1}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
    15. metadata-evalN/A

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

      \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot 0.5}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
  3. Applied rewrites99.0%

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

Alternative 2: 98.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(uy + uy\right)\\ t_1 := \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}\\ \mathsf{fma}\left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux, zi, \mathsf{fma}\left(yi \cdot \sin t\_0, t\_1, \left(xi \cdot t\_1\right) \cdot \cos t\_0\right)\right) \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* PI (+ uy uy)))
        (t_1
         (sqrt
          (fma
           (* (* (- ux 1.0) (* maxCos ux)) (- 1.0 ux))
           (* maxCos ux)
           1.0))))
   (fma
    (* (* maxCos (- 1.0 ux)) ux)
    zi
    (fma (* yi (sin t_0)) t_1 (* (* xi t_1) (cos t_0))))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((float) M_PI) * (uy + uy);
	float t_1 = sqrtf(fmaf((((ux - 1.0f) * (maxCos * ux)) * (1.0f - ux)), (maxCos * ux), 1.0f));
	return fmaf(((maxCos * (1.0f - ux)) * ux), zi, fmaf((yi * sinf(t_0)), t_1, ((xi * t_1) * cosf(t_0))));
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(pi) * Float32(uy + uy))
	t_1 = sqrt(fma(Float32(Float32(Float32(ux - Float32(1.0)) * Float32(maxCos * ux)) * Float32(Float32(1.0) - ux)), Float32(maxCos * ux), Float32(1.0)))
	return fma(Float32(Float32(maxCos * Float32(Float32(1.0) - ux)) * ux), zi, fma(Float32(yi * sin(t_0)), t_1, Float32(Float32(xi * t_1) * cos(t_0))))
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \pi \cdot \left(uy + uy\right)\\
t_1 := \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}\\
\mathsf{fma}\left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux, zi, \mathsf{fma}\left(yi \cdot \sin t\_0, t\_1, \left(xi \cdot t\_1\right) \cdot \cos t\_0\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(\left(\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
  2. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux, zi, \mathsf{fma}\left(yi \cdot \sin \left(\pi \cdot \left(uy + uy\right)\right), \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \left(xi \cdot \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}\right) \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right)\right)\right)} \]
  3. Add Preprocessing

Alternative 3: 98.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(uy + uy\right)\\ t_1 := \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}\\ \mathsf{fma}\left(xi \cdot \cos t\_0, t\_1, \mathsf{fma}\left(yi \cdot t\_1, \sin t\_0, zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right) \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* PI (+ uy uy)))
        (t_1
         (sqrt
          (fma
           (* (* (- ux 1.0) (* maxCos ux)) (- 1.0 ux))
           (* maxCos ux)
           1.0))))
   (fma
    (* xi (cos t_0))
    t_1
    (fma (* yi t_1) (sin t_0) (* zi (* (* maxCos (- 1.0 ux)) ux))))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((float) M_PI) * (uy + uy);
	float t_1 = sqrtf(fmaf((((ux - 1.0f) * (maxCos * ux)) * (1.0f - ux)), (maxCos * ux), 1.0f));
	return fmaf((xi * cosf(t_0)), t_1, fmaf((yi * t_1), sinf(t_0), (zi * ((maxCos * (1.0f - ux)) * ux))));
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(pi) * Float32(uy + uy))
	t_1 = sqrt(fma(Float32(Float32(Float32(ux - Float32(1.0)) * Float32(maxCos * ux)) * Float32(Float32(1.0) - ux)), Float32(maxCos * ux), Float32(1.0)))
	return fma(Float32(xi * cos(t_0)), t_1, fma(Float32(yi * t_1), sin(t_0), Float32(zi * Float32(Float32(maxCos * Float32(Float32(1.0) - ux)) * ux))))
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \pi \cdot \left(uy + uy\right)\\
t_1 := \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}\\
\mathsf{fma}\left(xi \cdot \cos t\_0, t\_1, \mathsf{fma}\left(yi \cdot t\_1, \sin t\_0, zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(\left(\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
  2. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(xi \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right), \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \mathsf{fma}\left(yi \cdot \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \sin \left(\pi \cdot \left(uy + uy\right)\right), zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right)} \]
  3. Add Preprocessing

Alternative 4: 98.7% accurate, 1.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(uy + uy\right)\\ \mathsf{fma}\left(xi \cdot \cos t\_0, 1, \mathsf{fma}\left(yi \cdot 1, \sin t\_0, zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right) \end{array} \end{array} \]
(FPCore (xi yi zi ux uy maxCos)
 :precision binary32
 (let* ((t_0 (* PI (+ uy uy))))
   (fma
    (* xi (cos t_0))
    1.0
    (fma (* yi 1.0) (sin t_0) (* zi (* (* maxCos (- 1.0 ux)) ux))))))
float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
	float t_0 = ((float) M_PI) * (uy + uy);
	return fmaf((xi * cosf(t_0)), 1.0f, fmaf((yi * 1.0f), sinf(t_0), (zi * ((maxCos * (1.0f - ux)) * ux))));
}
function code(xi, yi, zi, ux, uy, maxCos)
	t_0 = Float32(Float32(pi) * Float32(uy + uy))
	return fma(Float32(xi * cos(t_0)), Float32(1.0), fma(Float32(yi * Float32(1.0)), sin(t_0), Float32(zi * Float32(Float32(maxCos * Float32(Float32(1.0) - ux)) * ux))))
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \pi \cdot \left(uy + uy\right)\\
\mathsf{fma}\left(xi \cdot \cos t\_0, 1, \mathsf{fma}\left(yi \cdot 1, \sin t\_0, zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(\left(\cos \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
  2. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(xi \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right), \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \mathsf{fma}\left(yi \cdot \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \sin \left(\pi \cdot \left(uy + uy\right)\right), zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right)} \]
  3. Taylor expanded in ux around 0

    \[\leadsto \mathsf{fma}\left(xi \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right), \color{blue}{1}, \mathsf{fma}\left(yi \cdot \sqrt{\mathsf{fma}\left(\left(\left(ux - 1\right) \cdot \left(maxCos \cdot ux\right)\right) \cdot \left(1 - ux\right), maxCos \cdot ux, 1\right)}, \sin \left(\pi \cdot \left(uy + uy\right)\right), zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right) \]
  4. Step-by-step derivation
    1. Applied rewrites98.8%

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

      \[\leadsto \mathsf{fma}\left(xi \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right), 1, \mathsf{fma}\left(yi \cdot \color{blue}{1}, \sin \left(\pi \cdot \left(uy + uy\right)\right), zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right) \]
    3. Step-by-step derivation
      1. Applied rewrites98.7%

        \[\leadsto \mathsf{fma}\left(xi \cdot \cos \left(\pi \cdot \left(uy + uy\right)\right), 1, \mathsf{fma}\left(yi \cdot \color{blue}{1}, \sin \left(\pi \cdot \left(uy + uy\right)\right), zi \cdot \left(\left(maxCos \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right) \]
      2. Add Preprocessing

      Alternative 5: 98.7% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \left(uy \cdot \pi\right)\\ \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), \mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\right) \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (let* ((t_0 (* 2.0 (* uy PI))))
         (fma maxCos (* ux (* zi (- 1.0 ux))) (fma xi (cos t_0) (* yi (sin t_0))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float t_0 = 2.0f * (uy * ((float) M_PI));
      	return fmaf(maxCos, (ux * (zi * (1.0f - ux))), fmaf(xi, cosf(t_0), (yi * sinf(t_0))));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	t_0 = Float32(Float32(2.0) * Float32(uy * Float32(pi)))
      	return fma(maxCos, Float32(ux * Float32(zi * Float32(Float32(1.0) - ux))), fma(xi, cos(t_0), Float32(yi * sin(t_0))))
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := 2 \cdot \left(uy \cdot \pi\right)\\
      \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), \mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\right)
      \end{array}
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

        \[\leadsto \color{blue}{maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + \left(xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)} \]
      3. Step-by-step derivation
        1. lower-fma.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \color{blue}{\left(zi \cdot \left(1 - ux\right)\right)}, xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \color{blue}{\left(1 - ux\right)}\right), xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        4. lower--.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - \color{blue}{ux}\right)\right), xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
      4. Applied rewrites98.7%

        \[\leadsto \color{blue}{\mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right)} \]
      5. Add Preprocessing

      Alternative 6: 96.0% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 0.00039999998989515007:\\ \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\\ \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (if (<= uy 0.00039999998989515007)
         (+ xi (fma 2.0 (* uy (* yi PI)) (* maxCos (* (* zi ux) (- 1.0 ux)))))
         (fma
          xi
          (sin (fma -2.0 (* uy PI) (* 0.5 PI)))
          (* yi (sin (* 2.0 (* uy PI)))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float tmp;
      	if (uy <= 0.00039999998989515007f) {
      		tmp = xi + fmaf(2.0f, (uy * (yi * ((float) M_PI))), (maxCos * ((zi * ux) * (1.0f - ux))));
      	} else {
      		tmp = fmaf(xi, sinf(fmaf(-2.0f, (uy * ((float) M_PI)), (0.5f * ((float) M_PI)))), (yi * sinf((2.0f * (uy * ((float) M_PI))))));
      	}
      	return tmp;
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	tmp = Float32(0.0)
      	if (uy <= Float32(0.00039999998989515007))
      		tmp = Float32(xi + fma(Float32(2.0), Float32(uy * Float32(yi * Float32(pi))), Float32(maxCos * Float32(Float32(zi * ux) * Float32(Float32(1.0) - ux)))));
      	else
      		tmp = fma(xi, sin(fma(Float32(-2.0), Float32(uy * Float32(pi)), Float32(Float32(0.5) * Float32(pi)))), Float32(yi * sin(Float32(Float32(2.0) * Float32(uy * Float32(pi))))));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;uy \leq 0.00039999998989515007:\\
      \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if uy < 3.9999999e-4

        1. Initial program 98.9%

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

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

            \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        4. Applied rewrites81.6%

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

          \[\leadsto xi + \color{blue}{\left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        6. Step-by-step derivation
          1. lower-+.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          4. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          5. lower-PI.f32N/A

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

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

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          9. lower--.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        7. Applied rewrites81.5%

          \[\leadsto xi + \color{blue}{\mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        8. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          2. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          3. associate-*r*N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          4. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          5. lower-*.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          6. lift-*.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]
          8. lower-*.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]
        9. Applied rewrites81.5%

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]

        if 3.9999999e-4 < uy

        1. Initial program 98.9%

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

            \[\leadsto \left(\left(\color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
          2. cos-neg-revN/A

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

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

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

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

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

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

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

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

            \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \pi, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
          11. count-2-revN/A

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

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

            \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
          14. mult-flipN/A

            \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot \frac{1}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
          15. metadata-evalN/A

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

            \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot 0.5}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        3. Applied rewrites99.0%

          \[\leadsto \left(\left(\color{blue}{\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        4. Taylor expanded in ux around 0

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

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

            \[\leadsto \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          3. lower-fma.f32N/A

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

            \[\leadsto \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \mathsf{PI}\left(\right), \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          5. lower-PI.f32N/A

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

            \[\leadsto \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          7. lower-PI.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        6. Applied rewrites90.7%

          \[\leadsto \color{blue}{\mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 7: 95.9% accurate, 1.7× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \left(uy \cdot \pi\right)\\ \mathbf{if}\;uy \leq 0.00039999998989515007:\\ \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\\ \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (let* ((t_0 (* 2.0 (* uy PI))))
         (if (<= uy 0.00039999998989515007)
           (+ xi (fma 2.0 (* uy (* yi PI)) (* maxCos (* (* zi ux) (- 1.0 ux)))))
           (fma xi (cos t_0) (* yi (sin t_0))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float t_0 = 2.0f * (uy * ((float) M_PI));
      	float tmp;
      	if (uy <= 0.00039999998989515007f) {
      		tmp = xi + fmaf(2.0f, (uy * (yi * ((float) M_PI))), (maxCos * ((zi * ux) * (1.0f - ux))));
      	} else {
      		tmp = fmaf(xi, cosf(t_0), (yi * sinf(t_0)));
      	}
      	return tmp;
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	t_0 = Float32(Float32(2.0) * Float32(uy * Float32(pi)))
      	tmp = Float32(0.0)
      	if (uy <= Float32(0.00039999998989515007))
      		tmp = Float32(xi + fma(Float32(2.0), Float32(uy * Float32(yi * Float32(pi))), Float32(maxCos * Float32(Float32(zi * ux) * Float32(Float32(1.0) - ux)))));
      	else
      		tmp = fma(xi, cos(t_0), Float32(yi * sin(t_0)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := 2 \cdot \left(uy \cdot \pi\right)\\
      \mathbf{if}\;uy \leq 0.00039999998989515007:\\
      \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if uy < 3.9999999e-4

        1. Initial program 98.9%

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

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

            \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        4. Applied rewrites81.6%

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

          \[\leadsto xi + \color{blue}{\left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        6. Step-by-step derivation
          1. lower-+.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          4. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          5. lower-PI.f32N/A

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

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

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          9. lower--.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        7. Applied rewrites81.5%

          \[\leadsto xi + \color{blue}{\mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        8. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          2. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          3. associate-*r*N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          4. lift-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          5. lower-*.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(ux \cdot zi\right) \cdot \left(1 - ux\right)\right)\right) \]
          6. lift-*.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]
          8. lower-*.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]
        9. Applied rewrites81.5%

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(\left(zi \cdot ux\right) \cdot \left(1 - ux\right)\right)\right) \]

        if 3.9999999e-4 < uy

        1. Initial program 98.9%

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

          \[\leadsto \color{blue}{xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)} \]
        3. Step-by-step derivation
          1. lower-fma.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \color{blue}{\cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)}, yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          2. lower-cos.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          4. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          5. lower-PI.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          6. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          7. lower-sin.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          8. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          9. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          10. lower-PI.f3290.7

            \[\leadsto \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right) \]
        4. Applied rewrites90.7%

          \[\leadsto \color{blue}{\mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 8: 95.9% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2 \cdot uy, \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (fma
        maxCos
        (* ux zi)
        (fma
         xi
         (sin (fma (* -2.0 uy) PI (* 0.5 PI)))
         (* yi (sin (* 2.0 (* uy PI)))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return fmaf(maxCos, (ux * zi), fmaf(xi, sinf(fmaf((-2.0f * uy), ((float) M_PI), (0.5f * ((float) M_PI)))), (yi * sinf((2.0f * (uy * ((float) M_PI)))))));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return fma(maxCos, Float32(ux * zi), fma(xi, sin(fma(Float32(Float32(-2.0) * uy), Float32(pi), Float32(Float32(0.5) * Float32(pi)))), Float32(yi * sin(Float32(Float32(2.0) * Float32(uy * Float32(pi)))))))
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2 \cdot uy, \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

          \[\leadsto \left(\left(\color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        2. cos-neg-revN/A

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

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

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

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

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

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

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \pi, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        11. count-2-revN/A

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        14. mult-flipN/A

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot \frac{1}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        15. metadata-evalN/A

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot 0.5}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      3. Applied rewrites99.0%

        \[\leadsto \left(\left(\color{blue}{\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      4. Taylor expanded in ux around 0

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
      6. Applied rewrites95.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right)} \]
      7. Step-by-step derivation
        1. lift-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \pi\right) + \frac{1}{2} \cdot \pi\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
        2. lift-PI.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \pi\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
        4. associate-*r*N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\left(-2 \cdot uy\right) \cdot \mathsf{PI}\left(\right) + \frac{1}{2} \cdot \pi\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
        5. lower-fma.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2 \cdot uy, \mathsf{PI}\left(\right), \frac{1}{2} \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
        7. lift-PI.f3296.0

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2 \cdot uy, \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
      8. Applied rewrites96.0%

        \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2 \cdot uy, \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right) \]
      9. Add Preprocessing

      Alternative 9: 95.7% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(\sin \left(\pi \cdot \left(uy + uy\right)\right), yi, \sin \left(\mathsf{fma}\left(\pi \cdot uy, -2, 0.5 \cdot \pi\right)\right) \cdot xi\right)\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (fma
        maxCos
        (* ux zi)
        (fma
         (sin (* PI (+ uy uy)))
         yi
         (* (sin (fma (* PI uy) -2.0 (* 0.5 PI))) xi))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return fmaf(maxCos, (ux * zi), fmaf(sinf((((float) M_PI) * (uy + uy))), yi, (sinf(fmaf((((float) M_PI) * uy), -2.0f, (0.5f * ((float) M_PI)))) * xi)));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return fma(maxCos, Float32(ux * zi), fma(sin(Float32(Float32(pi) * Float32(uy + uy))), yi, Float32(sin(fma(Float32(Float32(pi) * uy), Float32(-2.0), Float32(Float32(0.5) * Float32(pi)))) * xi)))
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(\sin \left(\pi \cdot \left(uy + uy\right)\right), yi, \sin \left(\mathsf{fma}\left(\pi \cdot uy, -2, 0.5 \cdot \pi\right)\right) \cdot xi\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

          \[\leadsto \left(\left(\color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        2. cos-neg-revN/A

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

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

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

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

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

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

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \pi, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        11. count-2-revN/A

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        14. mult-flipN/A

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot \frac{1}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        15. metadata-evalN/A

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot 0.5}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      3. Applied rewrites99.0%

        \[\leadsto \left(\left(\color{blue}{\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      4. Taylor expanded in ux around 0

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
      6. Applied rewrites95.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right)} \]
      7. Step-by-step derivation
        1. lift-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right) \]
        2. +-commutativeN/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right) + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        3. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right) + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        4. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(2 \cdot \left(uy \cdot \pi\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        5. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(2 \cdot \left(uy \cdot \pi\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        6. lift-PI.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        7. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        8. associate-*r*N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(\left(2 \cdot uy\right) \cdot \mathsf{PI}\left(\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        9. count-2N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \sin \left(\left(uy + uy\right) \cdot \mathsf{PI}\left(\right)\right) \cdot yi + xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right) \]
        10. lift-+.f32N/A

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

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(\sin \left(\pi \cdot \left(uy + uy\right)\right), yi, xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)\right)\right) \]
      8. Applied rewrites95.9%

        \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(\sin \left(\pi \cdot \left(uy + uy\right)\right), yi, \sin \left(\mathsf{fma}\left(\pi \cdot uy, -2, 0.5 \cdot \pi\right)\right) \cdot xi\right)\right) \]
      9. Add Preprocessing

      Alternative 10: 95.7% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \left(uy \cdot \pi\right)\\ \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\right) \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (let* ((t_0 (* 2.0 (* uy PI))))
         (fma maxCos (* ux zi) (fma xi (cos t_0) (* yi (sin t_0))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float t_0 = 2.0f * (uy * ((float) M_PI));
      	return fmaf(maxCos, (ux * zi), fmaf(xi, cosf(t_0), (yi * sinf(t_0))));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	t_0 = Float32(Float32(2.0) * Float32(uy * Float32(pi)))
      	return fma(maxCos, Float32(ux * zi), fma(xi, cos(t_0), Float32(yi * sin(t_0))))
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := 2 \cdot \left(uy \cdot \pi\right)\\
      \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos t\_0, yi \cdot \sin t\_0\right)\right)
      \end{array}
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

        \[\leadsto \color{blue}{maxCos \cdot \left(ux \cdot zi\right) + \left(xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)} \]
      3. Step-by-step derivation
        1. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, \color{blue}{ux \cdot zi}, xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        2. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \color{blue}{zi}, xi \cdot \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) + yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
        3. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
        4. lower-cos.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
        5. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
        6. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
        7. lower-PI.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
        8. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
      4. Applied rewrites95.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \cos \left(2 \cdot \left(uy \cdot \pi\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\right)} \]
      5. Add Preprocessing

      Alternative 11: 86.6% accurate, 2.1× speedup?

      \[\begin{array}{l} \\ zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)}{zi} + 2 \cdot \frac{uy \cdot \left(yi \cdot \pi\right)}{zi}\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (*
        zi
        (fma
         maxCos
         ux
         (+
          (/ (* xi (sin (fma -2.0 (* uy PI) (* 0.5 PI)))) zi)
          (* 2.0 (/ (* uy (* yi PI)) zi))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return zi * fmaf(maxCos, ux, (((xi * sinf(fmaf(-2.0f, (uy * ((float) M_PI)), (0.5f * ((float) M_PI))))) / zi) + (2.0f * ((uy * (yi * ((float) M_PI))) / zi))));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return Float32(zi * fma(maxCos, ux, Float32(Float32(Float32(xi * sin(fma(Float32(-2.0), Float32(uy * Float32(pi)), Float32(Float32(0.5) * Float32(pi))))) / zi) + Float32(Float32(2.0) * Float32(Float32(uy * Float32(yi * Float32(pi))) / zi)))))
      end
      
      \begin{array}{l}
      
      \\
      zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)}{zi} + 2 \cdot \frac{uy \cdot \left(yi \cdot \pi\right)}{zi}\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

          \[\leadsto \left(\left(\color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \pi\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        2. cos-neg-revN/A

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

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

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

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

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

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

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \pi, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        11. count-2-revN/A

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

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \frac{\color{blue}{\pi}}{2}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        14. mult-flipN/A

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot \frac{1}{2}}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
        15. metadata-evalN/A

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

          \[\leadsto \left(\left(\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \color{blue}{\pi \cdot 0.5}\right)\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      3. Applied rewrites99.0%

        \[\leadsto \left(\left(\color{blue}{\sin \left(\mathsf{fma}\left(-uy, \pi + \pi, \pi \cdot 0.5\right)\right)} \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot xi + \left(\sin \left(\left(uy \cdot 2\right) \cdot \pi\right) \cdot \sqrt{1 - \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right)}\right) \cdot yi\right) + \left(\left(\left(1 - ux\right) \cdot maxCos\right) \cdot ux\right) \cdot zi \]
      4. Taylor expanded in ux around 0

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot zi, \mathsf{fma}\left(xi, \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right)\right) \]
      6. Applied rewrites95.9%

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

        \[\leadsto zi \cdot \color{blue}{\left(maxCos \cdot ux + \left(\frac{xi \cdot \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)}{zi} + \frac{yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)}{zi}\right)\right)} \]
      8. Step-by-step derivation
        1. lower-*.f32N/A

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

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

          \[\leadsto zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)}{zi} + \frac{yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)}{zi}\right) \]
      9. Applied rewrites95.2%

        \[\leadsto zi \cdot \color{blue}{\mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)}{zi} + \frac{yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)}{zi}\right)} \]
      10. Taylor expanded in uy around 0

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

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

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

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

          \[\leadsto zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, \frac{1}{2} \cdot \pi\right)\right)}{zi} + 2 \cdot \frac{uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)}{zi}\right) \]
        5. lower-PI.f3286.6

          \[\leadsto zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)}{zi} + 2 \cdot \frac{uy \cdot \left(yi \cdot \pi\right)}{zi}\right) \]
      12. Applied rewrites86.6%

        \[\leadsto zi \cdot \mathsf{fma}\left(maxCos, ux, \frac{xi \cdot \sin \left(\mathsf{fma}\left(-2, uy \cdot \pi, 0.5 \cdot \pi\right)\right)}{zi} + 2 \cdot \frac{uy \cdot \left(yi \cdot \pi\right)}{zi}\right) \]
      13. Add Preprocessing

      Alternative 12: 84.8% accurate, 2.6× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 0.028999999165534973:\\ \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\\ \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (if (<= uy 0.028999999165534973)
         (+
          xi
          (fma 2.0 (* uy (* yi PI)) (* maxCos (* ux (+ zi (* -1.0 (* ux zi)))))))
         (fma maxCos (* ux (* zi (- 1.0 ux))) (* yi (sin (* 2.0 (* uy PI)))))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float tmp;
      	if (uy <= 0.028999999165534973f) {
      		tmp = xi + fmaf(2.0f, (uy * (yi * ((float) M_PI))), (maxCos * (ux * (zi + (-1.0f * (ux * zi))))));
      	} else {
      		tmp = fmaf(maxCos, (ux * (zi * (1.0f - ux))), (yi * sinf((2.0f * (uy * ((float) M_PI))))));
      	}
      	return tmp;
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	tmp = Float32(0.0)
      	if (uy <= Float32(0.028999999165534973))
      		tmp = Float32(xi + fma(Float32(2.0), Float32(uy * Float32(yi * Float32(pi))), Float32(maxCos * Float32(ux * Float32(zi + Float32(Float32(-1.0) * Float32(ux * zi)))))));
      	else
      		tmp = fma(maxCos, Float32(ux * Float32(zi * Float32(Float32(1.0) - ux))), Float32(yi * sin(Float32(Float32(2.0) * Float32(uy * Float32(pi))))));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;uy \leq 0.028999999165534973:\\
      \;\;\;\;xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if uy < 0.0289999992

        1. Initial program 98.9%

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

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

            \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        4. Applied rewrites81.6%

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

          \[\leadsto xi + \color{blue}{\left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        6. Step-by-step derivation
          1. lower-+.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          4. lower-*.f32N/A

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          5. lower-PI.f32N/A

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

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

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
          9. lower--.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        7. Applied rewrites81.5%

          \[\leadsto xi + \color{blue}{\mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
        8. Taylor expanded in ux around 0

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right) \]
        9. Step-by-step derivation
          1. lower-+.f32N/A

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

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right) \]
          3. lower-*.f3281.5

            \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right) \]
        10. Applied rewrites81.5%

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi + -1 \cdot \left(ux \cdot zi\right)\right)\right)\right) \]

        if 0.0289999992 < uy

        1. Initial program 98.9%

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

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

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

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

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

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

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \left(\sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right) \]
        4. Applied rewrites44.2%

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

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

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

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

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

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

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          6. lower-sin.f32N/A

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

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

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right)\right)\right) \]
          9. lower-PI.f3244.1

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right) \]
        7. Applied rewrites44.1%

          \[\leadsto \mathsf{fma}\left(maxCos, \color{blue}{ux \cdot \left(zi \cdot \left(1 - ux\right)\right)}, yi \cdot \sin \left(2 \cdot \left(uy \cdot \pi\right)\right)\right) \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 13: 81.5% accurate, 6.1× speedup?

      \[\begin{array}{l} \\ xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(\pi \cdot yi\right)\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (+ xi (fma (* zi (- 1.0 ux)) (* maxCos ux) (* (+ uy uy) (* PI yi)))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return xi + fmaf((zi * (1.0f - ux)), (maxCos * ux), ((uy + uy) * (((float) M_PI) * yi)));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return Float32(xi + fma(Float32(zi * Float32(Float32(1.0) - ux)), Float32(maxCos * ux), Float32(Float32(uy + uy) * Float32(Float32(pi) * yi))))
      end
      
      \begin{array}{l}
      
      \\
      xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(\pi \cdot yi\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

          \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites81.6%

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

        \[\leadsto xi + \color{blue}{\left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

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

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        4. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        5. lower-PI.f32N/A

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

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

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

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
        9. lower--.f3281.5

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)\right) \]
      7. Applied rewrites81.5%

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

          \[\leadsto xi + \left(2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right) + maxCos \cdot \color{blue}{\left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right)}\right) \]
        2. +-commutativeN/A

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

          \[\leadsto xi + \left(maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + 2 \cdot \left(\color{blue}{uy} \cdot \left(yi \cdot \pi\right)\right)\right) \]
        4. *-commutativeN/A

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

          \[\leadsto xi + \left(\left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) \cdot maxCos + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\right) \]
        6. *-commutativeN/A

          \[\leadsto xi + \left(\left(\left(zi \cdot \left(1 - ux\right)\right) \cdot ux\right) \cdot maxCos + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\right) \]
        7. associate-*l*N/A

          \[\leadsto xi + \left(\left(zi \cdot \left(1 - ux\right)\right) \cdot \left(ux \cdot maxCos\right) + 2 \cdot \left(\color{blue}{uy} \cdot \left(yi \cdot \pi\right)\right)\right) \]
        8. *-commutativeN/A

          \[\leadsto xi + \left(\left(zi \cdot \left(1 - ux\right)\right) \cdot \left(maxCos \cdot ux\right) + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\right) \]
        9. lift-*.f32N/A

          \[\leadsto xi + \left(\left(zi \cdot \left(1 - ux\right)\right) \cdot \left(maxCos \cdot ux\right) + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\right) \]
        10. lower-fma.f32N/A

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

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\right) \]
        12. associate-*r*N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(2 \cdot uy\right) \cdot \left(yi \cdot \pi\right)\right) \]
        13. count-2N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(yi \cdot \pi\right)\right) \]
        14. lift-+.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(yi \cdot \pi\right)\right) \]
        15. lower-*.f3281.5

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(yi \cdot \pi\right)\right) \]
        16. lift-PI.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) \]
        17. lift-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) \]
        18. *-commutativeN/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(\mathsf{PI}\left(\right) \cdot yi\right)\right) \]
        19. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(\mathsf{PI}\left(\right) \cdot yi\right)\right) \]
        20. lift-PI.f3281.5

          \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot ux, \left(uy + uy\right) \cdot \left(\pi \cdot yi\right)\right) \]
      9. Applied rewrites81.5%

        \[\leadsto xi + \mathsf{fma}\left(zi \cdot \left(1 - ux\right), maxCos \cdot \color{blue}{ux}, \left(uy + uy\right) \cdot \left(\pi \cdot yi\right)\right) \]
      10. Add Preprocessing

      Alternative 14: 79.0% accurate, 7.6× speedup?

      \[\begin{array}{l} \\ xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (+ xi (fma 2.0 (* uy (* yi PI)) (* maxCos (* ux zi)))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return xi + fmaf(2.0f, (uy * (yi * ((float) M_PI))), (maxCos * (ux * zi)));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return Float32(xi + fma(Float32(2.0), Float32(uy * Float32(yi * Float32(pi))), Float32(maxCos * Float32(ux * zi))))
      end
      
      \begin{array}{l}
      
      \\
      xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

          \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites81.6%

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

        \[\leadsto xi + \color{blue}{\left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + maxCos \cdot \left(ux \cdot zi\right)\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

          \[\leadsto xi + \left(2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)}\right) \]
        2. lower-fma.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}, maxCos \cdot \left(ux \cdot zi\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right), maxCos \cdot \left(ux \cdot zi\right)\right) \]
        4. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right), maxCos \cdot \left(ux \cdot zi\right)\right) \]
        5. lower-PI.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right) \]
        6. lower-*.f32N/A

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right) \]
        7. lower-*.f3279.0

          \[\leadsto xi + \mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right) \]
      7. Applied rewrites79.0%

        \[\leadsto xi + \color{blue}{\mathsf{fma}\left(2, uy \cdot \left(yi \cdot \pi\right), maxCos \cdot \left(ux \cdot zi\right)\right)} \]
      8. Add Preprocessing

      Alternative 15: 74.3% accurate, 12.4× speedup?

      \[\begin{array}{l} \\ xi + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (+ xi (* 2.0 (* uy (* yi PI)))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return xi + (2.0f * (uy * (yi * ((float) M_PI))));
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return Float32(xi + Float32(Float32(2.0) * Float32(uy * Float32(yi * Float32(pi)))))
      end
      
      function tmp = code(xi, yi, zi, ux, uy, maxCos)
      	tmp = xi + (single(2.0) * (uy * (yi * single(pi))));
      end
      
      \begin{array}{l}
      
      \\
      xi + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

          \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites81.6%

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

        \[\leadsto xi + \color{blue}{2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

          \[\leadsto xi + 2 \cdot \color{blue}{\left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right)} \]
        2. lower-*.f32N/A

          \[\leadsto xi + 2 \cdot \left(uy \cdot \color{blue}{\left(yi \cdot \mathsf{PI}\left(\right)\right)}\right) \]
        3. lower-*.f32N/A

          \[\leadsto xi + 2 \cdot \left(uy \cdot \left(yi \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        4. lower-*.f32N/A

          \[\leadsto xi + 2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) \]
        5. lower-PI.f3274.3

          \[\leadsto xi + 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right) \]
      7. Applied rewrites74.3%

        \[\leadsto xi + \color{blue}{2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)} \]
      8. Add Preprocessing

      Alternative 16: 58.6% accurate, 8.9× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\\ \mathbf{if}\;yi \leq -1.9999999949504854 \cdot 10^{-6}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;yi \leq 2.7999999474559445 \cdot 10^{-6}:\\ \;\;\;\;\mathsf{fma}\left(zi \cdot ux, maxCos, xi\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
      (FPCore (xi yi zi ux uy maxCos)
       :precision binary32
       (let* ((t_0 (* 2.0 (* uy (* yi PI)))))
         (if (<= yi -1.9999999949504854e-6)
           t_0
           (if (<= yi 2.7999999474559445e-6) (fma (* zi ux) maxCos xi) t_0))))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	float t_0 = 2.0f * (uy * (yi * ((float) M_PI)));
      	float tmp;
      	if (yi <= -1.9999999949504854e-6f) {
      		tmp = t_0;
      	} else if (yi <= 2.7999999474559445e-6f) {
      		tmp = fmaf((zi * ux), maxCos, xi);
      	} else {
      		tmp = t_0;
      	}
      	return tmp;
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	t_0 = Float32(Float32(2.0) * Float32(uy * Float32(yi * Float32(pi))))
      	tmp = Float32(0.0)
      	if (yi <= Float32(-1.9999999949504854e-6))
      		tmp = t_0;
      	elseif (yi <= Float32(2.7999999474559445e-6))
      		tmp = fma(Float32(zi * ux), maxCos, xi);
      	else
      		tmp = t_0;
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right)\\
      \mathbf{if}\;yi \leq -1.9999999949504854 \cdot 10^{-6}:\\
      \;\;\;\;t\_0\\
      
      \mathbf{elif}\;yi \leq 2.7999999474559445 \cdot 10^{-6}:\\
      \;\;\;\;\mathsf{fma}\left(zi \cdot ux, maxCos, xi\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;t\_0\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if yi < -1.99999999e-6 or 2.79999995e-6 < yi

        1. Initial program 98.9%

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

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

            \[\leadsto \mathsf{fma}\left(2, \color{blue}{uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)}, maxCos \cdot \left(ux \cdot \left(zi \cdot \left(1 - ux\right)\right)\right) + xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        4. Applied rewrites81.6%

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

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

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

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

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

            \[\leadsto 2 \cdot \left(uy \cdot \left(yi \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)\right) \]
          5. lower-PI.f32N/A

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

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

            \[\leadsto 2 \cdot \left(uy \cdot \left(yi \cdot \left(\pi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right)\right)\right) \]
        7. Applied rewrites32.2%

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

          \[\leadsto 2 \cdot \left(uy \cdot \left(yi \cdot \mathsf{PI}\left(\right)\right)\right) \]
        9. Step-by-step derivation
          1. lower-PI.f3232.1

            \[\leadsto 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right) \]
        10. Applied rewrites32.1%

          \[\leadsto 2 \cdot \left(uy \cdot \left(yi \cdot \pi\right)\right) \]

        if -1.99999999e-6 < yi < 2.79999995e-6

        1. Initial program 98.9%

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

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

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

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

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

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

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
          6. lower-sqrt.f32N/A

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

            \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        4. Applied rewrites51.7%

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

          \[\leadsto xi + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)} \]
        6. Step-by-step derivation
          1. lower-+.f32N/A

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

            \[\leadsto xi + maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
          3. lower-*.f3249.7

            \[\leadsto xi + maxCos \cdot \left(ux \cdot zi\right) \]
        7. Applied rewrites49.7%

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

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

            \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
          3. lift-*.f32N/A

            \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
          4. *-commutativeN/A

            \[\leadsto \left(ux \cdot zi\right) \cdot maxCos + xi \]
          5. lower-fma.f3249.7

            \[\leadsto \mathsf{fma}\left(ux \cdot zi, maxCos, xi\right) \]
          6. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(ux \cdot zi, maxCos, xi\right) \]
          7. *-commutativeN/A

            \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
          8. lower-*.f3249.7

            \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
        9. Applied rewrites49.7%

          \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 17: 49.7% accurate, 17.3× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos) :precision binary32 (fma (* zi ux) maxCos xi))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return fmaf((zi * ux), maxCos, xi);
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return fma(Float32(zi * ux), maxCos, xi)
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

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

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        6. lower-sqrt.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites51.7%

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

        \[\leadsto xi + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

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

          \[\leadsto xi + maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
        3. lower-*.f3249.7

          \[\leadsto xi + maxCos \cdot \left(ux \cdot zi\right) \]
      7. Applied rewrites49.7%

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

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

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
        3. lift-*.f32N/A

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
        4. *-commutativeN/A

          \[\leadsto \left(ux \cdot zi\right) \cdot maxCos + xi \]
        5. lower-fma.f3249.7

          \[\leadsto \mathsf{fma}\left(ux \cdot zi, maxCos, xi\right) \]
        6. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(ux \cdot zi, maxCos, xi\right) \]
        7. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
        8. lower-*.f3249.7

          \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
      9. Applied rewrites49.7%

        \[\leadsto \mathsf{fma}\left(zi \cdot ux, maxCos, xi\right) \]
      10. Add Preprocessing

      Alternative 18: 49.7% accurate, 17.3× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(maxCos \cdot ux, zi, xi\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos) :precision binary32 (fma (* maxCos ux) zi xi))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return fmaf((maxCos * ux), zi, xi);
      }
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return fma(Float32(maxCos * ux), zi, xi)
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(maxCos \cdot ux, zi, xi\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

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

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        6. lower-sqrt.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites51.7%

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

        \[\leadsto xi + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

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

          \[\leadsto xi + maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
        3. lower-*.f3249.7

          \[\leadsto xi + maxCos \cdot \left(ux \cdot zi\right) \]
      7. Applied rewrites49.7%

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

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

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
        3. lift-*.f32N/A

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
        4. lift-*.f32N/A

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) + xi \]
        5. associate-*r*N/A

          \[\leadsto \left(maxCos \cdot ux\right) \cdot zi + xi \]
        6. lift-*.f32N/A

          \[\leadsto \left(maxCos \cdot ux\right) \cdot zi + xi \]
        7. lower-fma.f3249.7

          \[\leadsto \mathsf{fma}\left(maxCos \cdot ux, zi, xi\right) \]
      9. Applied rewrites49.7%

        \[\leadsto \mathsf{fma}\left(maxCos \cdot ux, zi, xi\right) \]
      10. Add Preprocessing

      Alternative 19: 11.8% accurate, 22.3× speedup?

      \[\begin{array}{l} \\ maxCos \cdot \left(ux \cdot zi\right) \end{array} \]
      (FPCore (xi yi zi ux uy maxCos) :precision binary32 (* maxCos (* ux zi)))
      float code(float xi, float yi, float zi, float ux, float uy, float maxCos) {
      	return maxCos * (ux * zi);
      }
      
      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(xi, yi, zi, ux, uy, maxcos)
      use fmin_fmax_functions
          real(4), intent (in) :: xi
          real(4), intent (in) :: yi
          real(4), intent (in) :: zi
          real(4), intent (in) :: ux
          real(4), intent (in) :: uy
          real(4), intent (in) :: maxcos
          code = maxcos * (ux * zi)
      end function
      
      function code(xi, yi, zi, ux, uy, maxCos)
      	return Float32(maxCos * Float32(ux * zi))
      end
      
      function tmp = code(xi, yi, zi, ux, uy, maxCos)
      	tmp = maxCos * (ux * zi);
      end
      
      \begin{array}{l}
      
      \\
      maxCos \cdot \left(ux \cdot zi\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

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

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

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

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
        6. lower-sqrt.f32N/A

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

          \[\leadsto \mathsf{fma}\left(maxCos, ux \cdot \left(zi \cdot \left(1 - ux\right)\right), xi \cdot \sqrt{1 - {maxCos}^{2} \cdot \left({ux}^{2} \cdot {\left(1 - ux\right)}^{2}\right)}\right) \]
      4. Applied rewrites51.7%

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

        \[\leadsto xi + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)} \]
      6. Step-by-step derivation
        1. lower-+.f32N/A

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

          \[\leadsto xi + maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
        3. lower-*.f3249.7

          \[\leadsto xi + maxCos \cdot \left(ux \cdot zi\right) \]
      7. Applied rewrites49.7%

        \[\leadsto xi + \color{blue}{maxCos \cdot \left(ux \cdot zi\right)} \]
      8. Taylor expanded in xi around 0

        \[\leadsto maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
      9. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) \]
        2. lower-*.f3211.8

          \[\leadsto maxCos \cdot \left(ux \cdot zi\right) \]
      10. Applied rewrites11.8%

        \[\leadsto maxCos \cdot \left(ux \cdot \color{blue}{zi}\right) \]
      11. Add Preprocessing

      Reproduce

      ?
      herbie shell --seed 2025149 
      (FPCore (xi yi zi ux uy maxCos)
        :name "UniformSampleCone 2"
        :precision binary32
        :pre (and (and (and (and (and (and (<= -10000.0 xi) (<= xi 10000.0)) (and (<= -10000.0 yi) (<= yi 10000.0))) (and (<= -10000.0 zi) (<= zi 10000.0))) (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) maxCos) ux) (* (* (- 1.0 ux) maxCos) ux))))) xi) (* (* (sin (* (* uy 2.0) PI)) (sqrt (- 1.0 (* (* (* (- 1.0 ux) maxCos) ux) (* (* (- 1.0 ux) maxCos) ux))))) yi)) (* (* (* (- 1.0 ux) maxCos) ux) zi)))